diff --git a/data/covid/preprints-summary.csv b/data/covid/preprints-summary.csv
index 2a6b455d..e2c80434 100644
--- a/data/covid/preprints-summary.csv
+++ b/data/covid/preprints-summary.csv
@@ -1,45 +1,45 @@
-emergency medicine,obstetrics and gynecology,radiology and imaging,allergy and immunology,pathology,biochemistry,ophthalmology,dentistry and oral medicine,Total,cardiovascular medicine,evolutionary biology,health systems and quality improvement,hiv aids,surgery,health economics,infectious diseases,public and global health,immunology,psychiatry and clinical psychology,intensive care and critical care medicine,pharmacology and therapeutics,neurology,oncology,microbiology,epidemiology,dermatology,primary care research,scientific communication and education,orthopedics,genetic and genomic medicine,health informatics,biophysics,month,bioinformatics,genomics,respiratory medicine,health policy,geriatric medicine,occupational and environmental health,pediatrics,systems biology,molecular biology
-,,,,,,,,1,,,,,,,1,,,,,,,,,,,,,,,,,Sep-23,,,,,,,,,
-,,,,,,,,6,,,,,,,,1,,,,,,,,3,,1,,,,,,Aug-23,,,,,,1,,,
-,,,,,,,,6,,,2,,,,,1,,,,,,,,2,,,,,1,,,Jul-23,,,,,,,,,
-,,,,,,,,7,,,,,,,2,,,,,,,,,1,,,1,1,,1,,Jun-23,,,,,,1,,,
-,,,,,,,,6,,,,,,,1,1,1,,,,,,,2,,,,,,,,May-23,,,1,,,,,,
-,,,,,,,,3,,,,,,,1,2,,,,,,,,,,,,,,,,Apr-23,,,,,,,,,
-,,,,,,,,8,,,,,,,3,2,,,,,,,,2,,,,,,,,Mar-23,,,,,,1,,,
-,,,,,,,,6,,,,,,,,2,,,,,1,,,2,,,,,,,,Feb-23,,,1,,,,,,
-,,,,,,,,6,,,,,,,1,,,,,,,,,5,,,,,,,,Jan-23,,,,,,,,,
-,,,,1,,,,12,,,,,,,4,1,,,,,,,,3,,,,,,,,Dec-22,,,2,1,,,,,
-,,,,,,,,4,,,,,,,4,,,,,,,,,,,,,,,,,Nov-22,,,,,,,,,
-,,,,,,,,6,1,,,,,,2,2,,,,,,,,1,,,,,,,,Oct-22,,,,,,,,,
-,,,,,,,,9,,,,,,,2,1,,,,,,,1,1,,,,,,,,Sep-22,,,1,,,2,1,,
-,,,,,,,,10,,,,,,,3,3,,,,,,,,4,,,,,,,,Aug-22,,,,,,,,,
-,,,,,,,,7,,,,,,,3,,1,,,,,,,1,,,,,,1,,Jul-22,,,,,,,1,,
-,,,,,,,,18,,,,,,,4,1,,5,,,,,,6,,,,,1,1,,Jun-22,,,,,,,,,
-,,,,,,,,12,,,1,,,1,5,1,,2,,,,,1,1,,,,,,,,May-22,,,,,,,,,
-,,,,,,,,16,1,,2,,,1,3,1,,,,,,,1,5,,,,,,,,Apr-22,,,1,,,1,,,
-,,,,,,,,17,,1,,,,,5,,,1,,,,,,8,,1,,,,,,Mar-22,,,1,,,,,,
-,,,,,,,,12,,,,,,,4,1,,,,,1,,,6,,,,,,,,Feb-22,,,,,,,,,
-,,,,,,,,13,1,,,,,,3,1,1,,,,,,,4,,,,,,2,,Jan-22,,,,,,1,,,
-,,,,,,,,24,1,,,,,,8,1,,,,,1,,1,10,,1,,,,,,Dec-21,,,,,,,1,,
-,,,,,,,,24,,,2,,,,5,2,,1,1,,1,,,9,,1,,,,,1,Nov-21,,1,,,,,,,
-,,,,,,,,11,,,,,,,3,,,2,,,,,,4,,,,,,,,Oct-21,,,,,1,,1,,
-,,,,,,,,17,1,,,,,,5,2,,,1,1,,,,6,,,,,,1,,Sep-21,,,,,,,,,
-,,,,,,,,13,1,,,,,,3,3,,,1,,,,,2,,,,,,1,,Aug-21,,,1,,,1,,,
-1,,,,,,,,25,,,,,,,11,4,,,1,,,1,,3,,,,,1,,,Jul-21,,,2,,,,1,,
-,,,1,,,,,28,,,1,,,,7,4,1,1,1,,1,,,7,,1,,,,1,,Jun-21,,,,,,1,1,,
-,,,,,,,,22,,,,,,,8,1,,1,,,,,,9,1,,,,1,1,,May-21,,,,,,,,,
-,,,1,,,,,20,,,1,,,,7,1,,1,,,,,1,4,,1,,,,1,,Apr-21,,,,,,2,,,
-,,1,,,1,,,36,,,,,1,,14,5,,1,,,1,,,6,,,,,1,2,,Mar-21,,,,,2,,1,,
-,,,,,,,,24,1,,1,,1,1,9,1,,,,,,,,9,,,,,,1,,Feb-21,,,,,,,,,
-,,,,,,,1,23,,,1,,,,8,3,1,1,1,,,,,4,,1,,,,,,Jan-21,,,,1,1,,,,
-,,,,,,,,21,1,,1,,,,3,3,,2,,,,,1,4,,1,,,,3,,Dec-20,,2,,,,,,,
-,,,,,,,,28,,,,,,,13,5,1,,,,,,,6,,,,,,1,,Nov-20,1,,,1,,,,,
-,,,,,1,,,31,,,,,,,12,,1,3,1,,,1,,6,,1,,,,1,,Oct-20,1,,,1,1,,,1,
-3,,,,,,,,26,,,,1,,,7,3,,2,1,,,,1,6,,1,,,,1,,Sep-20,,,,,,,,,
-2,1,,,,,,,26,,,1,,,,12,1,,,,,,,,6,,,,,1,,,Aug-20,,,,,,1,,,1
-,,,,,,,,27,1,,,,,,7,4,1,1,1,,,,,10,,,,,,,,Jul-20,,1,1,,,,,,
-,,,,,,1,,37,1,,1,,,,10,3,1,4,3,,,1,,7,,,,,,1,,Jun-20,1,,1,1,1,,,,
-,,,,,,,,37,2,,,,,1,10,9,,,1,,,1,,8,,,,,,1,,May-20,1,,1,,1,1,,,
-,,,,,,,,18,,,1,,,,7,1,,,,,,,,7,,,,,2,,,Apr-20,,,,,,,,,
-,,,,,,,,8,,,,,,,1,3,,,,,,,,4,,,,,,,,Mar-20,,,,,,,,,
-,,,,,,,,7,,,,,,,1,2,,,,,,,,4,,,,,,,,Feb-20,,,,,,,,,
+cardiovascular medicine,scientific communication and education,month,ophthalmology,emergency medicine,respiratory medicine,surgery,epidemiology,health economics,orthopedics,oncology,public and global health,occupational and environmental health,primary care research,immunology,health informatics,obstetrics and gynecology,hiv aids,pathology,intensive care and critical care medicine,dermatology,radiology and imaging,microbiology,geriatric medicine,allergy and immunology,dentistry and oral medicine,health systems and quality improvement,molecular biology,pediatrics,genomics,systems biology,pharmacology and therapeutics,bioinformatics,biochemistry,evolutionary biology,genetic and genomic medicine,infectious diseases,psychiatry and clinical psychology,biophysics,Total,health policy,neurology
+,,Sep-23,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,1,,
+,,Aug-23,,,,,4,,,,1,1,1,,,,,,,,,,,,,,,,,,,,,,,,,,7,,
+,,Jul-23,,,,,3,,,,1,,,,,,,,,,,,,,,2,,,,,,,,,1,,,,7,,
+,1,Jun-23,,,,,1,,1,,,1,,,1,,,,,,,,,,,,,,,,,,,,,2,,,7,,
+,,May-23,,,1,,2,,,,1,,,1,,,,,,,,,,,,,,,,,,,,,,1,,,6,,
+,,Apr-23,,,,,,,,,2,,,,,,,,,,,,,,,,,,,,,,,,,1,,,3,,
+,,Mar-23,,,,,2,,,,2,1,,,,,,,,,,,,,,,,,,,,,,,,3,1,,9,,
+,,Feb-23,,,1,,4,,,,2,,,,,,,,,,,,,,,,,,,,,,,,,,,,8,,1
+,,Jan-23,,,,,5,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,,,6,,
+,,Dec-22,,,2,,3,,,,1,,,,,,,1,,,,,,,,,,,,,,,,,,4,,,12,1,
+,,Nov-22,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,4,,,4,,
+1,,Oct-22,,,,,1,,,,2,,,,,,,,,,,,,,,,,,,,,,,,,2,,,6,,
+,,Sep-22,,,1,,1,,,,1,2,,,,,,,,,,1,,,,,,1,,,,,,,,2,,,9,,
+,,Aug-22,,,,,4,,,,3,,,,,,,,,,,,,,,,,,,,,,,,,3,,,10,,
+,,Jul-22,,,,,2,,,,,,,1,1,,,,,,,,,,,,,1,,,,,,,,3,,,8,,
+,,Jun-22,,,,,6,,,,1,,,,1,,,,,,,,,,,,,,,,,,,,1,4,5,,18,,
+,,May-22,,,,,2,1,,,1,,1,,,,,,,,,1,,,,1,,,,,,,,,,5,2,,14,,
+1,,Apr-22,,,1,,5,1,,,1,1,,,,,,,,,,1,,,,2,,,,,,,,,,3,,,16,,
+,,Mar-22,,,1,,9,,,,,,1,,,,,,,,,,,,,,,,,,,,,1,,4,1,,17,,
+,,Feb-22,,,,,6,,,,1,,,,,,,,,,,,,,,,,,,,,,,,,4,,,12,,1
+1,,Jan-22,,,,,5,,,,1,1,,1,2,,,,,,,,,,,,,,,,,,,,,3,,,14,,
+1,,Dec-21,,,,,10,,,,,,1,,,,,,,,,,,,,,,1,,,,,,,,8,,,22,,1
+,,Nov-21,,,,,9,,,,3,,1,,,,,,1,,,,,,,2,,,1,,,,,,,4,1,1,24,,1
+,,Oct-21,,,,,4,,,,,,,,,,,,,,,,1,,,,,1,,,,,,,,3,2,,11,,
+1,,Sep-21,,,,,6,,,,2,,,,1,,,,1,,,,,,,,,,,,1,,,,,4,,,16,,
+1,,Aug-21,,,1,,2,,,,3,1,,,1,,,,1,,,,,,,,,,,,,,,,,3,,,13,,
+,,Jul-21,,1,2,,3,,,,4,,,,,,,,1,,,,,,,,,1,,,,,,,1,12,,,25,,
+,,Jun-21,,,,,6,,,,4,1,1,1,1,,,,1,,,,,1,,1,,1,,,,,,,,7,1,,27,,1
+,,May-21,,,,,11,,,,1,,,,,,,,,1,,,,,,,,,,,,,,,1,7,1,,22,,
+,,Apr-21,,,,,3,,,,1,2,1,,1,,,,,,,1,,1,,1,,,,,,,,,,7,1,,19,,
+,,Mar-21,,,,1,5,,,,5,,,,2,,,,,,1,,2,,,,,1,,,,,1,,1,17,1,,38,,1
+,,Feb-21,,,,1,9,1,,,1,,,,1,,,,,,,,,,,1,,,,,,,,,,9,,,23,,
+,,Jan-21,,,,,4,,,,3,,1,,,,,,1,,,,1,,1,1,,,,,,,,,,8,1,,22,1,
+2,,Dec-20,,,,,4,,,,3,,1,,3,,,,,,,1,,,,1,,,2,,,,,,,4,2,,23,,
+,,Nov-20,,,,,5,,,,5,,,1,1,,,,,,,,,,,,,,,,,1,,,,12,,,26,1,
+,,Oct-20,,,,,6,,,1,,,1,1,1,,,,1,,,,1,,,,,,,1,,1,,,,12,3,,30,1,
+,,Sep-20,,2,,,6,,,,3,,1,,1,,1,,1,,,1,,,,,,,,,,,,,,8,2,,26,,
+,,Aug-20,,2,,,6,,,,2,1,,,,1,,,,,,,,,,1,1,,,,,,,,1,12,,,27,,
+1,,Jul-20,,,1,,10,,,,4,,,1,,,,,1,,,,,,,,,,1,,,,,,,8,1,,28,,
+,,Jun-20,1,,1,,7,,,1,3,,,1,1,,,,3,,,,1,,,1,,,,,,1,,,,10,4,,36,1,
+2,,May-20,,,1,,8,1,,1,8,1,,,1,,,,1,,,,1,,,,,,,,,1,,,,10,,,36,,
+,,Apr-20,,,,,7,,,,1,,,,,,,,,,,,,,,1,,,1,,,,,,2,7,,,19,,
+,,Mar-20,,,,,4,,,,3,,,,,,,,,,,,,,,,,,,,,,,,,1,,,8,,
+,,Feb-20,,,,,4,,,,2,,,,,,,,,,,,,,,,,,,,,,,,,,,,6,,
diff --git a/data/covid/preprints.csv b/data/covid/preprints.csv
index 8d7e115d..86e2524a 100644
--- a/data/covid/preprints.csv
+++ b/data/covid/preprints.csv
@@ -1,5 +1,11 @@
 site,doi,date,link,title,authors,affiliations,abstract,category,match_type,author_similarity,affiliation_similarity
-medRxiv,10.1101/2023.08.30.23294821,2023-09-01,https://medrxiv.org/cgi/content/short/2023.08.30.23294821,Symptom experience before vs. after confirmed SARS-CoV-2 infection: a population and case control study using prospectively recorded symptom data.,Carole Helene Sudre; Michela Antonelli; Nathan J Cheetham; Erika Molteni; Liane S Canas; Vicky Bowyer; Benjamin Murray; Khaled Rjoob; Marc Modat; Joan Capdevia Pujol; Christina Hu; Jonathan Wolf; Timothy D Spector; Alexander Hammers; Claire J Steves; Sebastien Ourselin; Emma L Duncan,University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; King's College London; Zoe Ltd; Zoe Ltd; Zoe Ltd; King's College London; King's College London; King's College London; King's College London; King's College London,"Background: Some individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration. Methods Survival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([&ge;]8 weeks, 906 [67.1%] with illness [&ge;]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms. Findings: Individuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly. Interpretation: Individuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.",infectious diseases,fuzzy,94,100
+medRxiv,10.1101/2023.08.30.23294821,2023-09-01,https://medrxiv.org/cgi/content/short/2023.08.30.23294821,Symptom experience before vs. after confirmed SARS-CoV-2 infection: a population and case control study using prospectively recorded symptom data.,Carole Helene Sudre; Michela Antonelli; Nathan J Cheetham; Erika Molteni; Liane S Canas; Vicky Bowyer; Benjamin Murray; Khaled Rjoob; Marc Modat; Joan Capdevia Pujol; Christina Hu; Jonathan Wolf; Timothy D Spector; Alexander Hammers; Claire J Steves; Sebastien Ourselin; Emma L Duncan,University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; King's College London; Zoe Ltd; Zoe Ltd; Zoe Ltd; King's College London; King's College London; King's College London; King's College London; King's College London,"BackgroundSome individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration.
+
+MethodsSurvival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([&ge;]8 weeks, 906 [67.1%] with illness [&ge;]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms.
+
+FindingsIndividuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly.
+
+InterpretationIndividuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.",infectious diseases,fuzzy,94,100
 medRxiv,10.1101/2023.08.25.23294609,2023-08-25,https://medrxiv.org/cgi/content/short/2023.08.25.23294609,Risk factors for SARS-Cov-2 infection at a United Kingdom electricity-generating company: a test-negative design case-control study,Charlotte E Rutter; Martie J Van Tongeren; Tony Fletcher; Sarah E Rhodes; Yiqun Chen; Ian Hall; Nicholas Warren; Neil Pearce,London School of Hygiene and Tropical Medicine; University of Manchester; London School of Hygiene and Tropical Medicine; University of Manchester; Health and Safety Executive; University of Manchester; Health and Safety Executive; London School of Hygiene and Tropical Medicine,"ObjectivesIdentify workplace risk factors for SARS-Cov-2 infection, using data collected by a United Kingdom electricity-generating company.
 
 MethodsUsing a test-negative design case-control study we estimated the odds ratios (OR) of infection by job category, site, test reason, sex, vaccination status, vulnerability, site outage, and site COVID-19 weekly risk rating, adjusting for age, test date and test type.
@@ -61,6 +67,27 @@ Added value of this studyThis study is the first to quantify changes in fit note
 
 Implications of all the available evidenceWhile we have likely underestimated the fit note rate due to overcounting of people in the workforce and misclassification of COVID-19 status, we still identified a substantial increased risk of receiving a fit note in people with COVID-19 compared with the general population over all years, even after adjusting for demographics and a wide range of clinical characteristics. The increased risk persisted into 2022, in an era where most people are vaccinated and the severity of COVID-19 illness is lessened. Given the high infection rates still occurring, these findings provide evidence for a substantial impact of COVID-19 on productivity and further evidence of the long-term impacts of COVID-19.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2023.08.02.23293519,2023-08-04,https://medrxiv.org/cgi/content/short/2023.08.02.23293519,Real-time epidemiological modelling during the COVID-19 emergency in Wales,Michael Gravenor; Mark Dawson; Ed Bennett; Ben Thorpe; Carla White; Alma Rahat; Daniel Archambault; Noemi Picco; Gibin Powathil; Biagio Lucini,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"The sudden outbreak of the COVID-19 pandemic presented governments, policy makers and health services with an unprecedented challenge of taking real-time decisions that could keep the disease under control with non-pharmaceutical interventions, while at the same time limit as much as possible severe consequences of a very strict lockdown. Mathematical modelling has proved to be a crucial element for informing those decisions. Here we report on the rapid development and application of the Swansea Model, a mathematical model of disease spread in real time, to inform policy decisions during the COVID-19 pandemic in Wales.",epidemiology,fuzzy,100,100
+medRxiv,10.1101/2023.08.01.23293491,2023-08-02,https://medrxiv.org/cgi/content/short/2023.08.01.23293491,Health inequalities in SARS-CoV-2 infection during the second wave in England: REACT-1 study,Haowei Wang; Kylie E. C. Ainslie; Oliver Eales; Caroline E. Walters; David Haw; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Christl A Donnelly; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","ObjectivesThe rapid spread of SARS-CoV-2 infection caused high levels of hospitalisation and deaths in late 2020 and early 2021 during the second wave in England. Severe disease during this period was associated with marked health inequalities across ethnic and sociodemographic subgroups. In this paper, we aimed to investigate how inequalities influence the risk of getting infected across ethnic and sociodemographic subgroups during a key period before widespread vaccination.
+
+DesignRepeated cross-sectional community-based study.
+
+MethodsWe analysed risk factors for test-positivity for SARS-CoV-2, based on self-administered throat and nose swabs in the community during rounds 5 to 10 of the REal-time Assessment of Community Transmission-1 (REACT-1) study between 18 September 2020 and 30 March 2021.
+
+ResultsCompared to white ethnicity, people of Asian and black ethnicity had a higher risk of infection during rounds 5 to 10, with odds of 1.46 (1.27, 1.69) and 1.35 (1.11, 1.64) respectively. Among ethnic subgroups, the highest and the second-highest odds were found in Bangladeshi and Pakistan participants at 3.29 (2.23, 4.86) and 2.15 (1.73, 2.68) respectively when compared to British whites. People in larger (compared to smaller) households had higher odds of infection. Health care workers with direct patient contact and care home workers showed higher odds of infection compared to other essential/key workers. Additionally, the odds of infection among participants in public-facing activities or settings were greater than among those not working in those activities or settings.
+
+ConclusionOur findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future severe waves of respiratory pathogens should include policies to reduce inequality in the risk of infection by ethnicity, household size, and occupational activity in order to reduce inequality in disease.
+
+Summary boxWhat is already known on this topic
+
+Extensive studies have described the relationship between socio-demographic factors and SARS-CoV-2 outcomes such as hospitalisations and deaths, rather than SARS-CoV-2 infection. Limited community-based studies investigated risk factors associated with SARS-CoV-2 infection, with the time frame of these studies has mainly focused on the period of the first wave of infection, or the beginning of the second wave, or the rollout of the first dose of the vaccine after the second wave period. We did not find studies that covered the critical period of the second wave in England when levels of social mixing were high, but no vaccine was available.
+
+What this study adds
+
+We show health inequalities across ethnic and sociodemographic subgroups during a key period: before widespread vaccination, but, largely, not during the period of stringent social distancing. We observed substantial ethnic and occupational differences in the risk of SARS-CoV-2 infection. Minority ethnic groups, including those of Bangladeshi and Pakistani ethnicity, had an excess risk of infection compared with the British white population. Healthcare workers, care home workers and people who work in public-facing activities or settings were associated with higher odds of infection. The risk of SARS-CoV-2 infection increased monotonically as household size increased, and more deprived neighbourhood areas were associated with a higher risk of infection.
+
+How this study might affect research, practice or policy
+
+Our findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future waves of severe respiratory infection should explicitly aim to reduce inequalities in infection in order to reduce inequality in disease.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2023.07.31.23293422,2023-07-31,https://medrxiv.org/cgi/content/short/2023.07.31.23293422,Associations between SARS-CoV-2 infection and subsequent economic inactivity and employment status: pooled analyses of five linked longitudinal surveys,Richard John Shaw; Rebecca Rhead; Richard J Silverwood; Jacques Wels; Jingmin Zhu; Olivia KL Hamilton; Giorgio Di Gessa; Ruth CE Bowyer; Bettina Moltrecht; Michael J Green; Evangelia Demou; Serena Pattaro; Paola Zaninotto; Andy W Boyd; Felix Greaves; Nish Chaturvedi; George B Ploubidis; Srinivasa Vittal Katikireddi,"University of Glasgow; King's College London; University College London; Centre Metices, Universite libre de Bruxelles, Brussels, BE.; University College London; University of Glasgow; University College London; King's College London; University College London; Duke University School of Medicine, Durham, NC, USA.; University of Glasgow; University of Glasgow; University College London, UK; University of Bristol; Imperial College London; University College London; University College London; University of Glasgow","IntroductionFollowing the acute phase of the COVID-19 pandemic, record numbers of people became economically inactive (i.e., neither working nor looking for work), or non-employed (including unemployed job seekers and economically inactive people). A possible explanation is people leaving the workforce after contracting COVID-19. We investigated whether testing positive for SARS-CoV-2 is related to subsequent economic inactivity and non-employment, among people employed pre-pandemic.
 
 MethodsThe data came from five UK longitudinal population studies held by both the UK Longitudinal Linkage Collaboration (UK LLC; primary analyses) and the UK Data Service (UKDS; secondary analyses). We pooled data from five long established studies (1970 British Cohort Study, English Longitudinal Study of Ageing, 1958 National Child Development Study, Next Steps, and Understanding Society). The study population were aged 25-65 years between March 2020 to March 2021 and employed pre-pandemic. Outcomes were economic inactivity and non-employment measured at the time of the last follow-up survey (November 2020 to March 2021, depending on study). For the UK LLC sample (n=8,174), COVID-19 infection was indicated by a positive SARS-CoV-2 test in NHS England records. For the UKDS sample we used self-reported measures of COVID-19 infection (n=13,881). Logistic regression models estimated odds ratios (ORs) with 95% confidence intervals (95%CIs) adjusting for potential confounders including sociodemographic variables, pre-pandemic health and occupational class.
@@ -99,6 +126,11 @@ MethodsWe implemented a computer simulation model of patient flow through an int
 ResultsThe results from the simulation model suggest that, without mitigation, the impact of COVID-19 will be an increase in pressure on GP and specialist community based services by 50% and 50-100% respectively. Simulating the impact of possible mitigation strategies, results show that increasing capacity in lower-acuity services, such as GP, results in demand being shifted to other parts of the mental health system while decreasing length of stay in higher acuity services is insufficient to mitigate the impact of increased demand.
 
 ConclusionIn capturing the interrelation of patient flow related dynamics between various mental health care settings, we demonstrate the value of computer simulation for assessing the impact of interventions on system flow.",health systems and quality improvement,fuzzy,100,100
+medRxiv,10.1101/2023.07.16.23292705,2023-07-18,https://medrxiv.org/cgi/content/short/2023.07.16.23292705,"Community-onset urinary tract infection in females in the context of COVID-19: a longitudinal population cohort study exploring case presentation, management, and outcomes",Nina J Zhu; Benedict Hayhoe; Raheelah Ahmad; James R Price; Donna Lecky; Monsey McLeod; Elena Ferran; Timothy M Rawson; Emma Carter; Alison H Holmes; Paul Aylin,"National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom; Division of Health Services Research and Management, School of Health Sciences, City, University of London, London, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; Primary Care and Interventions Unit, United Kingdom Health Security Agency (UKHSA), Gloucestershire, United Kingdom; NHS England and NHS Improvement, London, United Kingdom; Barts Health NHS Trust, London, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; Primary Care and Interventions Unit, United Kingdom Health Security Agency (UKHSA), Gloucestershire, United Kingdom","BackgroundCOVID-19 affected the epidemiology of other infectious diseases and how they were managed. Urinary tract infection (UTI) is one of the most common infections treated in the community in England. We investigated the impact of the COVID-19 pandemic on UTI primary care consultations and outcomes in female patients.
+
+Methods and findingsWe analysed General Practice (GP) consultation and hospital admission records using the Whole Systems Integrated Care (WSIC) data in North West London between 2016 and 2021. We quantified the changes in UTI GP consultation rates using time series analysis before and during the pandemic. We assessed the outcomes of UTI, measured by subsequent bacteraemia and sepsis within 60 days, for consultations delivered face-to-face or remotely, with or without diagnostic tests recommended by the national guidelines, and with or without antibiotic treatment. Between January 2016 and December 2021, we identified 375,859 UTI episodes in 233,450 female patients. Before the COVID-19 pandemic (January 2016 - February 2020), the UTI GP consultation rate stayed level at 522.8 cases per 100,000 population per month, with a seasonal pattern of peaking in October. Since COVID-19, (March 2020 - December 2021), monthly UTI GP consultations declined when COVID-19 cases surged and rose when COVID-19 case fell. During the pandemic, the UTI consultations delivered face-to-face reduced from 72.0% to 29.4%, the UTI consultations with appropriate diagnostic tests, including urine culture and urinalysis, reduced from 17.3% to 10.4%, and the UTI cases treated with antibiotics reduced from 52.0% to 47.8%. The likelihood of antibiotics being prescribed was not affected by whether the consultation was delivered face-to-face or remotely but associated with whether there was a diagnostic test. Regardless of whether the UTI consultation occurred before or during the pandemic, the absence of antibiotic treatment for UTI is associated with a 10-fold increase in the risk of having bacteraemia or sepsis within 60 days, though the patients who consulted GPs for UTI during the pandemic were older and more co-morbid. Across the study period (January 2016 - December 2021), nitrofurantoin remained the first-line antibiotic option for UTI. The percentage of non-prophylactic acute UTI antibiotic prescriptions with durations that exceeded the guideline recommendations was 58.7% before the pandemic, and 49.4% since. This led to 830,522 total excess days of treatment, account for 63.3% of all non-prophylactic acute antibiotics prescribed for UTI. Before the pandemic, excess antibiotic days of UTI drugs had been reducing consistently. However, this decline slowed down during the pandemic. Having a diagnostic test was associated with 0.6 less excess days of antibiotic treatment.
+
+ConclusionsThis analysis provides a comprehensive examination of management and outcomes of community-onset UTI in female patients, considering the changes in GP consultations during the COVID-19 pandemic. Our findings highlighted the importance of appropriate urine testing to support UTI diagnosis in symptomatic patients and initiation of antibiotic treatment with appropriate course duration. Continued monitoring is required to assess the overall impact on patients and health systems from the changed landscape of primary care delivery.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2023.07.06.23292295,2023-07-07,https://medrxiv.org/cgi/content/short/2023.07.06.23292295,Spatio-temporal surveillance and early detection of SARS-CoV-2 variants of concern,Massimo Cavallaro; Louise Dyson; Michael J Tildesley; Daniel Todkill; Matt J Keeling,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"The SARS-CoV-2 pandemic has been characterized by the repeated emergence of genetically distinct virus variants of increased transmissibility and immune evasion compared to pre-existing lineages. In many countries, their containment required the intervention of public health authorities and the imposition of control measures. While the primary role of testing is to identify infection, target treatment, and limit spread (through isolation and contact tracing), a secondary benefit is in terms of surveillance and the early detection of new variants. Here we study the spatial invasion and early spread of the Alpha, Delta, and Omicron (BA.1 and BA.2) variants in England from September 2020 to February 2022 using the random neighbourhood covering (RaNCover) method, a statistical technique for the detection of aberrations in spatial point processes, applied to community PCR (polymerase-chain-reaction) test data where the TaqPath kit provides a proxy measure of the switch between variants. The application of RaNCover method could rapidly detect outbreaks of future SARS-CoV-2 variants of concern and hence inform optimal spatial interventions.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2023.07.03.23291596,2023-07-05,https://medrxiv.org/cgi/content/short/2023.07.03.23291596,Risk of COVID-19 death in adults who received booster COVID-19 vaccinations: national retrospective cohort study on 14.6 million people in England,Isobel L Ward; Chris Robertson; Utkarsh Agrawal; Lynsey Patterson; Declan T Bradley; Ting Shi; Simon de Lusignan; Richard Hobbs; Aziz Sheikh; Vahe Nafilyan,"Office for National Statistics, Newport, UK; Department of Mathematics and Statistics, Strathclyde University, Glasgow, Scotland and Public Health Scotland, Glasgow, Scotland; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Centre for Public Health, Queen's University Belfast, Belfast, UK and Public Health Agency, Belfast, UK; Centre for Public Health, Queen's University Belfast, Belfast, UK and Public Health Agency, Belfast, UK; Usher Institute, University of Edinburgh, Edinburgh, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Usher Institute, University of Edinburgh, Edinburgh, UK; Office for National Statistics, Newport, UK","ImportanceThe emergence of the COVID-19 vaccination has been critical in changing the course of the COVID-19 pandemic, with estimates suggesting vaccinations have prevented millions of deaths worldwide. To ensure protection remains high in vulnerable groups booster vaccinations in the UK have been targeted based on age and clinical vulnerabilities.
 
@@ -262,6 +294,27 @@ C_LIO_LIThe use of an additional control group from the general public for compa
 C_LIO_LIIn the subgroup analyses, PCR+ cases and PCR- controls were compared with the population controls to assess the risk factors for those aged 18-55 years. Hence, the results may not be generalisable to patients older than 55 years.
 C_LIO_LIPCR test results, rather than symptoms, were used to categorise the participants into cases or controls, and therefore risk factors for SARS-CoV-2 infection and not COVID-19 disease were assessed.
 C_LI",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2023.03.15.23287292,2023-03-15,https://medrxiv.org/cgi/content/short/2023.03.15.23287292,Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic,Eoin McElroy; Emily Herrett; Kishan Patel; Dominik M Piehlmaier; Giorgio Di Gessa; Charlotte Huggins; Michael J Green; Alex SF Kwong; Ellen J Thompson; Jingmin Zhu; Kathryn E Mansfield; Richard J Silverwood; Rosie Mansfield; Jane Maddock; Rohini Mathur; Ruth E Costello; Anthony A Matthews; John Tazare; Alasdair Henderson; Kevin Wing; Lucy Bridges; Sebastian Bacon; Amir Mehrkar; - OpenSafely Collaborative; Richard John Shaw; Jacques Wels; Srinivasa Vittal Katikireddi; Nishi Chaturvedi; Laurie Tomlinson; Praveetha Patalay,"School of Psychology, Ulster University, Coleraine, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; University of Sussex Business Sch; Department of Epidemiology & Public Health, University College London, London, UK; Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Division of Psychiatry, University of Edinburgh, Edinburgh, UK; Department of Twin Research and Genetic Epidemiology, Kings College London; Department of Epidemiology & Public Health, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Centre for Longitudinal Studies, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Primary Care, Wolfson Insitute of Population Health, Queen Mary, University of London, London; London School of Hygiene and Tropical Medicine, London, UK; Karolinska Institutet, Stockholm, Sweden; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; ; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK","ObjectivesTo describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap.
+
+DesignTen population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs).
+
+SettingUK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database.
+
+ParticipantsParticipants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people.
+
+Main outcome measuresIn the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses.
+
+ResultsThe LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed.
+
+ConclusionsMultiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.
+
+Summary BoxO_ST_ABSWhat is already known on the topic?C_ST_ABSHouseholds with one individual are an increasing demographic, comprising over a quarter of all households in the UK in 2021. However, the mental health gap between those who live alone compared to those who live with others is not well described and even less is known about the relative gaps in need and healthcare-seeking and access. The pandemic and associated restrictive measures further increased the likelihood of isolation for this group, which may have impacted mental health.
+
+What this study adds?We present comprehensive evidence from both population-based surveys and electronic health records regarding the greater levels of mental health symptoms and in recorded diagnoses for common (anxiety, depression) and less common (OCD, eating disorders, SMIs) mental health conditions for people living alone compared to those living with others.
+
+Our analyses indicate that mental health conditions are more common among those who live alone compared to those who live with others. Although levels of reported distress increased for both groups during the pandemic, healthcare-seeking dropped in both groups, and the rates of healthcare-seeking among those who live alone converged with those who live with others for common mental health conditions. This suggests greater barriers for treatment access among those that live alone.
+
+The findings have implications for mental health service planning and efforts to reduce barriers to treatment access, especially for individuals who live on their own.",psychiatry and clinical psychology,fuzzy,100,100
 medRxiv,10.1101/2023.02.26.23286474,2023-03-06,https://medrxiv.org/cgi/content/short/2023.02.26.23286474,Improving the representativeness of UKs national COVID-19 Infection Survey through spatio-temporal regression and post-stratification,Koen B Pouwels; David W Eyre; Thomas House; Ben Aspey; Philippa C Matthews; Nicole Stoesser; John Newton; Ian Diamond; Ruth Studley; Nick Taylor; John Bell; Jeremy Farrar; Jaison Kolenchery; Brian Marsden; Sarah Hoosdally; Yvonne Jones; David Stuart; Derrick Crook; tim E peto; Ann Sarah Walker; - COVID-19 Infection Survey Team,University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; The Francis Crick Institute; University of Oxford; University of Exeter; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; oxford university; University of Oxford; -,"Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we use spatio-temporal regression and post-stratification models to UKs national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21%), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2023.03.01.23286627,2023-03-03,https://medrxiv.org/cgi/content/short/2023.03.01.23286627,Effectiveness of successive booster vaccine doses against SARS-CoV-2 related mortality in residents of Long-Term Care Facilities in the VIVALDI study,Oliver Stirrup; Madhumita Shrotri; Natalie L. Adams; Maria Krutikov; Borscha Azmi; Igor Monakhov; Gokhan Tut; Paul Moss; Andrew Hayward; Andrew Copas; Laura Shallcross,University College London; University College London; University College London; University College London; University College London; UK Health Security Agency; University of Birmingham; University of Birmingham; University College London; University College London; University College London,"We evaluated the effectiveness of 1-3 booster vaccinations against SARS-CoV-2 related mortality among a cohort of 13407 older residents of long-term care facilities (LTCFs) participating in the VIVALDI study in England in 2022. Cox regression was used to estimate relative hazards of SARS-CoV-2 related death following booster vaccination relative to 2 doses (after 84+ days), stratified by previous SARS-CoV-2 infection and adjusting for age, sex and LTCF capacity. Each booster provided additional short-term protection relative to primary vaccination, with consistent pattern of waning to 45-75% reduction in risk beyond 112 days.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2023.03.01.23286624,2023-03-03,https://medrxiv.org/cgi/content/short/2023.03.01.23286624,Risk of cardiovascular events following COVID-19 in people with and without pre-existing chronic respiratory disease,Hannah Whittaker; Costantinos Kallis; Angela Wood; Thomas Bolton; Samantha Walker; Aziz Sheikh; Alex Brownrigg; Ashley Akbari; Kamil Sterniczuk; Jennifer K Quint,"Imperial College London; Imperial College London; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom; Health Data Research UK; Asthm + Lung; The University of Edinburgh College of Medicine and Veterinary Medicine; Health Data Research UK BREATHE; Swansea University; Health Data Research UK BREATHE; Imperial College London","BackgroundCOVID-19 is associated with a higher risk of cardiovascular outcomes in the general population, but it is unknown whether people with pre-existing chronic respiratory disease (CRD) have a higher risk of cardiovascular events post-COVID-19 compared with the general population and, if so, what respiratory-related risk factors may modify this risk in these people.
@@ -331,6 +384,13 @@ ResultsIgG spike-protein antibodies were undetectable in 23.3%, 14.1% and 20.7%
 ConclusionsApproximately one in five individuals with SOT, RAIRD and LM have no detectable IgG spike-protein antibodies despite three or more vaccines, but this proportion reduces with sequential booster doses. Choice of immunosuppressant and disease-type is strongly associated with serological response. Antibody testing could enable rapid identification of individuals who are most likely to benefit from additional COVID-19 interventions.
 
 Trial registrationClinicaltrials.gov, NCT05148806",public and global health,fuzzy,100,100
+medRxiv,10.1101/2023.02.06.23285513,2023-02-06,https://medrxiv.org/cgi/content/short/2023.02.06.23285513,A Rapid review on the COVID-19 Pandemic's Global Impact on Breast Cancer Screening Participation Rates and Volumes from January-December 2020,"Reagan Lee; - UNCOVER; Wei Xu; - International Partnership for Resilience in Cancer Systems (I-PaRCS), Breast Cancer Working Group 2; Marshall Dozier; Ruth McQuillan; Evropi Theodoratou; Jonine Figueroa",University of Edinburgh; -; University of Edinburgh; -; University of Edinburgh; University of Edinburgh; The University of Edinburgh; University of Edinburgh,"BackgroundCOVID-19 has strained population breast mammography screening programs that aim to diagnose and treat breast cancers earlier. As the pandemic has affected countries differently, we aimed to quantify changes in breast screening volume and uptake during the first year of the COVID-19 pandemic.
+
+MethodsWe systematically searched Medline, the WHO (World Health Organization) COVID-19 database, and governmental databases. Studies covering January 2020 to March 2022 were included. We extracted and analyzed data regarding study methodology, screening volume and uptake. To assess for risk-of-bias, we used the Joanna Briggs Institute Critical Appraisal tool.
+
+ResultsTwenty-six cross-sectional descriptive studies were included out of 935 independent records. Reductions in screening volume and uptake rates were observed among eight countries. Changes in screening participation volume in five countries with national population-based screening ranged from -13% to -31%. Among two countries with limited population-based programs the decline ranged from -61% to -41%. Within the USA, population participation volumes varied ranging from +18% to -39% with suggestion of differences by insurance status (HMO, Medicare, and low-income programs). Almost all studies had high risk-of-bias due to insufficient statistical analysis and confounding factors.
+
+Discussion and ConclusionExtent of COVID-19-induced reduction in breast screening participation volume differed by region and data suggested potential differences by healthcare setting (e.g., national health insurance vs private health care). Recovery efforts should monitor access to screening and early diagnosis to determine if prevention services need strengthening to increase coverage of marginalized groups and reduce disparities.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2023.02.01.23285333,2023-02-02,https://medrxiv.org/cgi/content/short/2023.02.01.23285333,Associations between reported healthcare disruption due to COVID-19 and avoidable hospitalisation: Evidence from seven linked longitudinal studies for England,Mark A Green; Martin McKee; Olivia Hamilton; Richard Shaw; John MacLeod; Andrew Boyd; - The LH&W NCS Collaborative; Srinivasa Vittal Katikireddi,University of Liverpool; London School of Hygiene and Tropical Medicine; University of Glasgow; University of Glasgow; University of Bristol; University of Bristol; ; University of Glasgow,"BackgroundHealth services across the UK struggled to cope during the COVID-19 pandemic. Many treatments were postponed or cancelled, although the impact was mitigated by new models of delivery. While the scale of disruption has been studied, much less is known about if this disruption impacted health outcomes. The aim of our paper is to examine whether there is an association between individuals experiencing disrupted access to healthcare during the pandemic and risk of an avoidable hospitalisation.
 
 MethodsWe used individual-level data for England from seven longitudinal cohort studies linked to electronic health records from NHS Digital (n = 29 276) within the UK Longitudinal Linkage Collaboration trusted research environment. Avoidable hospitalisations were defined as emergency hospital admissions for ambulatory care sensitive and emergency urgent care sensitive conditions (1st March 2020 to 25th August 2022). Self-reported measures of whether people had experienced disruption during the pandemic to appointments (e.g., visiting their GP or an outpatient department), procedures (e.g., surgery, cancer treatment) or medications were used as our exposures. Logistic regression models examined associations.
@@ -338,6 +398,12 @@ MethodsWe used individual-level data for England from seven longitudinal cohort
 Results35% of people experienced some form of disrupted access to healthcare. Those whose access was disrupted were at increased risk of any (Odds Ratio (OR) = 1.80, 95% Confidence Intervals (CIs) = 1.34-2.41), acute (OR = 1.68, CIs = 1.13-2.53) and chronic (OR = 1.93, CIs = 1.40-2.64) ambulatory care sensitive hospital admissions. There were positive associations between disrupted access to appointments and procedures to measures of avoidable hospitalisations as well.
 
 ConclusionsOur study presents novel evidence from linked individual-level data showing that people whose access to healthcare was disrupted were more likely to have an avoidable or potentially preventable hospitalisation. Our findings highlight the need to increase healthcare investment to tackle the short- and long-term implications of the pandemic beyond directly dealing with SARS-CoV-2 infections.",public and global health,fuzzy,100,100
+medRxiv,10.1101/2023.01.31.23285232,2023-02-01,https://medrxiv.org/cgi/content/short/2023.01.31.23285232,"Cohort profile: Virus Watch: Understanding community incidence, symptom profiles, and transmission of COVID-19 in relation to population movement and behaviour",Thomas Edward Byrne; Jana Kovar; Sarah Beale; Isobel Braithwaite; Ellen Fragaszy; Wing Lam Erica Fong; Cyril Geismar; Susan J Hoskins; Annalan Mathew Dwight Navaratnam; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Alexei Yavlinsky; Pia Hardelid; Linda Wijlaars; Eleni Nastouli; Moira Spyer; Anna Ayree; Ingemar Cox; Vasileios Lampos; Rachel A McKendry; Tao Cheng; Anne M Johnson; Susan Fiona Michie; Jo Gibbs; Richard Gilson; Alison Rodger; Ibrahim Abubakar; Andrew Hayward; Robert W Aldridge,University College London; University College London; University College London; University College London; UCL; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCLH; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCL,"Key FeaturesO_LIVirus Watch is a national community cohort study of COVID-19 in households in England and Wales, established in June 2020. The study aims to provide evidence on which public health approaches are most effective in reducing transmission, and investigate community incidence, symptoms, and transmission of COVID-19 in relation to population movement and behaviours.
+C_LIO_LI28,527 households and 58,628 participants of age (0-98 years, mean age 48), were recruited between June 2020 - July 2022
+C_LIO_LIData collected include demographics, details on occupation, co-morbidities, medications, and infection-prevention behaviours. Households are followed up weekly with illness surveys capturing symptoms and their severity, activities in the week prior to symptom onset and any COVID-19 test results. Monthly surveys capture household finance, employment, mental health, access to healthcare, vaccination uptake, activities and contacts. Data have been linked to Hospital Episode Statistics (HES), inpatient and critical care episodes, outpatient visits, emergency care contacts, mortality, virology testing and vaccination data held by NHS Digital.
+C_LIO_LINested within Virus Watch are a serology & PCR cohort study (n=12,877) and a vaccine evaluation study (n=19,555).
+C_LIO_LIStudy data are deposited in the Office of National Statistics (ONS) Secure Research Service (SRS). Survey data are available under restricted access upon request to ONS SRS.
+C_LI",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2023.01.29.23285160,2023-01-30,https://medrxiv.org/cgi/content/short/2023.01.29.23285160,High number of SARS-CoV-2 persistent infections uncovered through genetic analysis of samples from a large community-based surveillance study,Mahan Ghafari; Matthew Hall; Tanya Golubchik; Daniel Ayoubkhani; Thomas House; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; Roberto Cahuantzi; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Jeff Barrett; Christophe Fraser; David Bonsall; Sarah Walker; Katrina A Lythgoe,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Office for National Statistics; -; -; -; Wellcome Sanger Institute; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections may act as viral reservoirs that could seed future outbreaks 1-5, give rise to highly divergent lineages 6-8, and contribute to cases with post-acute Coronavirus disease 2019 (COVID-19) sequelae (Long Covid) 9,10. However, the population prevalence of persistent infections, their viral load kinetics, and evolutionary dynamics over the course of infections remain largely unknown. We identified 381 infections lasting at least 30 days, of which 54 lasted at least 60 days. These persistently infected individuals had more than 50% higher odds of self-reporting Long Covid compared to the infected controls, and we estimate that 0.09-0.5% of SARS-CoV-2 infections can become persistent and last for at least 60 days. In nearly 70% of the persistent infections we identified, there were long periods during which there were no consensus changes in virus sequences, consistent with prolonged presence of non-replicating virus. Our findings also suggest reinfections with the same major lineage are rare and that many persistent infections are characterised by relapsing viral load dynamics. Furthermore, we found a strong signal for positive selection during persistent infections, with multiple amino acid substitutions in the Spike and ORF1ab genes emerging independently in different individuals, including mutations that are lineage-defining for SARS-CoV-2 variants, at target sites for several monoclonal antibodies, and commonly found in immunocompromised patients 11-14. This work has significant implications for understanding and characterising SARS-CoV-2 infection, epidemiology, and evolution.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2023.01.24.23284906,2023-01-25,https://medrxiv.org/cgi/content/short/2023.01.24.23284906,The impact of COVID-19 lockdown on a cohort of adults with recurrent major depressive disorder from Catalonia: a decentralized longitudinal study using remote measurement technology,Raffaele Lavalle Sr.; Elena Condominas; Josep Maria Haro; Iago Gine-Vazquez; Raquel Bailon; Estela Laporta; Ester Garcia; Spyridon Kontaxis; Gemma Riquelme; Federica Lombardini; Antonio Preti; Maria Teresa Penarrubia Maria; Marta Coromina; Belen Arranz; Elisabet Vilella; Elena Rubio Abadal; Faith Matcham; Femke Lamers; Matthew Hotopf; Brenda W.J.H Penninx; Peter Annas; Vaibhav Narayan; Sara Katherine Simblett; Sara Siddi,"Dipartimento di neuroscienze, Universita degli studi di Torino, Italia; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain; Aragon Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, Spain; Centros de investigacion biomedica en red en el area de bioingenieria, biomateriales y nanomedicina (CIBER BBN), Madrid, Spain; Microelectronica y Sistemas Electronicos, Universidad Autonoma de Barcelona, Spain; Centros de Investigacion Biomedica en Red en el Area de Bioingenieria, Biomateriales y Nanomedicina (CIBER BBN), 28029 Madrid, Spain; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain; Dipartimento di neuroscienze, Universita degli studi di Torino, Italia; Health Technology Assessment in Primary Care and Mental Health (PRISMA) Research Group, Parc Sanitari Sant Joan de Deu, Institut de Recerca Sant Joan de Deu, St; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain; Hospital Universitari Institut Pere Mata, Reus, Spain Institut d'Investigacio Sanitaria Pere Virgili CERCA, Reus, Spain; Universitat Rovira i Virgili, Reus, Spa; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain; King's College London: London, GB; VU medisch centrum: Amsterdam, Noord-Holland, NL; Kings College London, Institute of Psychiatry, Psychology and Neuroscience, UK; Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Boelelaan 1117, Amsterdam, The Netherlands; H. Lundbeck A/S, Valby, Denmark; Research and Development Information Technology, Janssen Research & Development, LLC, Titusville, NJ, USA; Kings College London, Institute of Psychiatry, Psychology and Neuroscience, UK; Parc Sanitari Sant Joan de Deu, Fundacio Sant Joan de Deu, CIBERSAM,Universitat de Barcelona, Barcelona, Spain","BackgroundThe present study analyzes the effects of each containment phase of the first COVID-19 wave on depression levels in a cohort of adults with a history of major depressive disorder (MDD).
 
@@ -822,6 +888,13 @@ To our knowledge, there are no studies examining the symptom profile of post-COV
 Added-value of this studyOur study aimed to identify symptom profiles for post-COVID syndrome across the dominant variants in 2020 and 2021, and across vaccination status at the time of infection, using a large sample with prospectively collected longitudinal self-reports of symptoms. For individuals developing 12 weeks or more of symptoms, we identified three main symptom profiles which were consistent across variants and by vaccination status, differing only in the ratio of individuals affected by each profile and symptom duration overall.
 
 Implications of all the available evidenceWe demonstrate the existence of different post-COVID syndromes, which share commonalities across SARS-CoV-2 variant types in both symptoms themselves and how they evolved through the illness. We describe subgroups of patients with specific post-COVID presentations which might reflect different underlying pathophysiological mechanisms. Given the time-series component, our study is relevant for post-COVID prognostication, indicating how long certain symptoms last. These insights could aid in the development of personalised diagnosis and treatment, as well as helping policymakers plan for the delivery of care for people living with post-COVID syndrome.",health informatics,fuzzy,100,100
+medRxiv,10.1101/2022.07.29.22278186,2022-07-30,https://medrxiv.org/cgi/content/short/2022.07.29.22278186,Comparative effectiveness of BNT162b2 versus mRNA-1273 boosting in England: a cohort study in OpenSAFELY-TPP,WIlliam J Hulme; Elsie M F Horne; Edward P K Parker; Ruth H Keogh; Elizabeth J Williamson; Venexia Walker; Tom Palmer; Helen J Curtis; Alex Walker; Amir Mehrkar; Jessica Morley; Brian MacKenna; Sebastian C J Bacon; Ben Goldacre; Miguel A Hernan; Jonathan A C Sterne,"The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit, Bristol Medical Scho; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit, Bristol Medical Scho; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA 02115; Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health,; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; H","IntroductionThe COVID-19 booster vaccination programme in England used both BNT162b2 and mRNA-1273 vaccines. Direct comparisons of the effectiveness against severe COVID-19 of these two vaccines for boosting have not been made in trials or observational data.
+
+MethodsOn behalf of NHS England, we used the OpenSAFELY-TPP database to match adult recipients of each vaccine type on date of vaccination, primary vaccine course, age, and other characteristics. Recipients were eligible if boosted between 29 October 2021 and 31 January 2022, and followed up for 12 weeks. Outcomes were positive SARS-CoV-2 test, COVID-19 hospitalisation, and COVID-19 death. We estimated the cumulative incidence of each outcome, and quantified comparative effectiveness using risk differences (RD) and hazard ratios (HRs).
+
+Results1,528,431 people were matched in each group, contributing a total 23,150,504 person-weeks of follow-up. The 12-week risks per 1,000 people of positive SARS-CoV-2 test were 103.2 (95%CI 102.4 to 104.0) for BNT162b2 and 96.0 (95.2 to 96.8) for mRNA-1273: the HR comparing mRNA-1273 with BNT162b2 was 0.92 (95%CI 0.91 to 0.92). For COVID-19 hospitalisations the 12-week risks per 1,000 were 0.65 (95%CI 0.56 to 0.75) and 0.44 (0.36 to 0.54): HR 0.67 (95%CI 0.58 to 0.78). COVID-19 deaths were rare: the 12-week risks per 1,000 were 0.03 (95%CI 0.02 to 0.06) and 0.01 (0.01 to 0.02): HR 1.23 (95%CI 0.59 to 2.56). Comparative effectiveness was generally similar within subgroups defined by the primary course vaccine brand, age, prior SARS-CoV-2 infection and clinical vulnerability.
+
+ConclusionBooster vaccination with mRNA-1273 COVID-19 vaccine was more effective than BNT162b2 in preventing SARS-CoV-2 infection and COVID-19 hospitalisation during the first 12 weeks after vaccination, during a period of Delta followed by Omicron variant dominance.",epidemiology,fuzzy,100,100
 bioRxiv,10.1101/2022.07.26.501570,2022-07-26,https://biorxiv.org/cgi/content/short/2022.07.26.501570,Primary Omicron infection elicits weak antibody response but robust cellularimmunity in children,Alexander C Dowell; Tara Lancaster; Rachel Bruton; Georgina Ireland; Christopher Bentley; Panagiota Sylla; Jianmin Zuo; Sam Scott; Azar Jardin; Jusnara Begum; Thomas Roberts; Christine Stephens; Shabana Ditta; Rebecca Shepherdson; Annable Powell; Andrew Brent; Bernadette Brent; Frances Baawuah; Ifeanyichukwu Okike; Joanna Beckmann; Shazaad Ahmad; Felicity Aiano; Joanna Garstang; Mary Ramsay; Rafaq Azad; Dagmar Waiblinger; Brian Willet; John Wright; Shamez Ladhani; Paul Moss,"Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; East London NHS Foundation Trust, 9 Allie Street, London E1 8DE, UK; Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Birmingham Community Healthcare NHS Trust, Holt Street, Aston B7 4BN, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK","Omicron variants of SARS-CoV-2 are globally dominant and infection rates are very high in children. We determined immune responses following Omicron BA.1/2 infection in children aged 6-14 years and related this to prior and subsequent SARS-CoV-2 infection or vaccination. Primary Omicron infection elicited a weak antibody response with poor functional neutralizing antibodies. Subsequent Omicron reinfection or COVID-19 vaccination elicited increased antibody titres with broad neutralisation of Omicron subvariants. Prior pre-Omicron SARS-CoV-2 virus infection or vaccination primed for robust antibody responses following Omicron infection but these remained primarily focussed against ancestral variants. Primary Omicron infection thus elicits a weak antibody response in children which is boosted after reinfection or vaccination. Cellular responses were robust and broadly equivalent in all groups, providing protection against severe disease irrespective of SARS-CoV-2 variant. Immunological imprinting is likely to act as an important determinant of long-term humoral immunity, the future clinical importance of which is unknown.",immunology,fuzzy,100,100
 medRxiv,10.1101/2022.07.20.22277838,2022-07-21,https://medrxiv.org/cgi/content/short/2022.07.20.22277838,"National and regional prevalence of SARS-CoV-2 antibodies in primary and secondary school children in England: the School Infection Survey, a national open cohort study, November 2021",Annabel A Powell; Georgina Ireland; Rebecca Leeson; Andrea Lacey; Ben Ford; John Poh; Samreen Ijaz; Justin Shute; Peter Cherepanov; Richard Tedder; Christian Bottomley; Fiona Dawe; Punam Mangtani; Peter Jones; Patrick Nguipdop-Djomo; Shamez Ladhani,UK Health Security Agency; UK Health Security Agency; Office for National Statistics; Office for National Statistics; Office for National Statistics; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; Imperial College London; Francis Crick Institute; London School of Hygiene & Tropical Medicine; Office for National Statistics; London School of Hygiene & Tropical Medicine; Office for National Statistics; London School of Hygiene & Tropical Medicine; UK Health Security Agency,"BackgroundRisk factors for infection and, therefore, antibody positivity rates will be different in children compared to adults. We aim to estimate national and regional prevalence of SARS-CoV-2 antibodies in primary (4-11-year-olds) and secondary (11-15-year-olds) school children between 10 November and 10 December 2021.
 
@@ -975,6 +1048,21 @@ ResultsFollowing an initial plateau of 1.54% until mid-January, infection preval
 
 ConclusionHigh-resolution prevalence data fitted to P-splines allowed us to show that the lockdown was highly effective at reducing risk of infection with school holidays/closures playing a significant part.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2022.05.23.22275458,2022-05-25,https://medrxiv.org/cgi/content/short/2022.05.23.22275458,Covid-19 is a leading cause of death in children and young people ages 0-19 years in the United States,Seth Flaxman; Charles Whittaker; Elizaveta Semenova; Theo Rashid; Robbie Parks; Alexandra Blenkinsop; H Juliette T Unwin; Swapnil Mishra; Samir Bhatt; Deepti Gurdasani; Oliver Ratmann,"Oxford; Imperial College London; AstraZeneca; Imperial College London; Columbia University; Imperial College London; Imperial College London; University of Copenhagen; University of Copenhagen, Imperial College London; Queen Mary University of London; Imperial College London","Covid-19 has caused more than 1 million deaths in the US, including at least 1,204 deaths among children and young people (CYP) aged 0-19 years, with 796 occurring in the one year period April 1, 2021 - March 31, 2022. Deaths among US CYP are rare in general, and so we argue here that the mortality burden of Covid-19 in CYP is best understood in the context of all other causes of CYP death. Using publicly available data from CDC WONDER on NCHSs 113 Selected Causes of Death, and comparing to mortality in 2019, the immediate pre-pandemic period, we find that Covid-19 mortality is among the 10 leading causes of death in CYP aged 0-19 years in the US, ranking 8th among all causes of deaths, 5th in disease-related causes of deaths (excluding accidents, assault and suicide), and 1st in deaths caused by infectious or respiratory diseases. Covid-19 deaths constitute 2.3% of the 10 leading causes of death in this age group. Covid-19 caused substantially more deaths in CYP than major vaccine-preventable diseases did historically in the period before vaccines became available. Various factors including underreporting and Covid-19s role as a contributing cause of death from other diseases mean that our estimates may understate the true mortality burden of Covid-19. Our findings underscore the public health relevance of Covid-19 to CYP. In the likely future context of sustained SARS-CoV-2 circulation, pharmaceutical and non-pharmaceutical interventions will continue to play an important role in limiting transmission of the virus in CYP and mitigating severe disease.",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2022.05.22.22275417,2022-05-23,https://medrxiv.org/cgi/content/short/2022.05.22.22275417,Comparative effectiveness of sotrovimab and molnupiravir for prevention of severe COVID-19 outcomes in non-hospitalised patients: an observational cohort study using the OpenSAFELY platform,Bang Zheng; Amelia CA Green; John Tazare; Helen J Curtis; Louis Fisher; Linda Nab; Anna Schultze; Viyaasan Mahalingasivam; Edward Parker; William J Hulme; Sebastian CJ Bacon; Nicholas J DeVito; Christopher Bates; David Evans; Peter Inglesby; Henry Drysdale; Simon Davy; Jonathan Cockburn; Caroline E Morton; George Hickman; Tom Ward; Rebecca M Smith; John Parry; Frank Hester; Sam Harper; Amir Mehrkar; Rosalind M Eggo; Alex J Walker; Stephen JW Evans; Ian J Douglas; Brian MacKenna; Ben Goldacre; Laurie A Tomlinson,London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Trop. Med.; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; TPP; TPP; University of Oxford; London School of Hygiene & Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine,"ObjectiveTo compare the effectiveness of sotrovimab (a neutralising monoclonal antibody) vs. molnupiravir (an antiviral) in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients.
+
+DesignWith the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform.
+
+SettingPatient-level electronic health record data were obtained from 24 million people registered with a general practice in England that uses TPP software. The primary care data were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death within the OpenSAFELY-TPP platform, covering a period where both medications were frequently prescribed in community settings.
+
+ParticipantsNon-hospitalised adult COVID-19 patients at high risk of severe outcomes treated with sotrovimab or molnupiravir since December 16, 2021.
+
+InterventionsSotrovimab or molnupiravir administered in the community by COVID-19 Medicine Delivery Units.
+
+Main outcome measureCOVID-19 related hospitalisation or COVID-19 related death within 28 days after treatment initiation.
+
+ResultsBetween December 16, 2021 and February 10, 2022, 3331 and 2689 patients were treated with sotrovimab and molnupiravir, with no substantial differences in their baseline characteristics. The mean age of all 6020 patients was 52 (SD=16) years; 59% were female, 89% White and 88% had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 87 (1.4%) COVID-19 related hospitalisations/deaths were observed (32 treated with sotrovimab and 55 with molnupiravir). Cox proportional hazards models stratified by area showed that after adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, treatment with sotrovimab was associated with a substantially lower risk than treatment with molnupiravir (hazard ratio, HR=0.54, 95% CI: 0.33 to 0.88; P=0.014). Consistent results were obtained from propensity score weighted Cox models (HR=0.50, 95% CI: 0.31 to 0.81; P=0.005) and when restricted to fully vaccinated people (HR=0.53, 95% CI: 0.31 to 0.90; P=0.019). No substantial effect modifications by other characteristics were detected (all P values for interaction>0.10). Findings were similar in an exploratory analysis of patients treated between February 16 and May 1, 2022 when the Omicron BA.2 variant was dominant in England.
+
+ConclusionIn routine care of non-hospitalised high-risk adult patients with COVID-19 in England, those who received sotrovimab were at lower risk of severe COVID-19 outcomes than those receiving molnupiravir.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2022.05.21.22275368,2022-05-23,https://medrxiv.org/cgi/content/short/2022.05.21.22275368,"Variant-specific symptoms of COVID-19 among 1,542,510 people in England",Matthew Whitaker; Joshua Elliott; Barbara Bodinier; Wendy S Barclay; Helen Ward; Graham Cooke; Christl A Donnelly; Marc Chadeau-Hyam; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health,"Infection with SARS-CoV-2 virus is associated with a wide range of symptoms. The REal-time Assessment of Community Transmission -1 (REACT-1) study has been monitoring the spread and clinical manifestation of SARS-CoV-2 among random samples of the population in England from 1 May 2020 to 31 March 2022. We show changing symptom profiles associated with the different variants over that period, with lower reporting of loss of sense of smell and taste for Omicron compared to previous variants, and higher reporting of cold-like and influenza-like symptoms, controlling for vaccination status. Contrary to the perception that recent variants have become successively milder, Omicron BA.2 was associated with reporting more symptoms, with greater disruption to daily activities, than BA.1. With restrictions lifted and routine testing limited in many countries, monitoring the changing symptom profiles associated with SARS-CoV-2 infection and induced changes in daily activities will become increasingly important.",infectious diseases,fuzzy,96,100
 medRxiv,10.1101/2022.05.19.22275214,2022-05-22,https://medrxiv.org/cgi/content/short/2022.05.19.22275214,Antibody levels following vaccination against SARS-CoV-2: associations with post-vaccination infection and risk factors,Nathan J Cheetham; Milla Kibble; Andrew Wong; Richard J Silverwood; Anika Knuppel; Dylan M Williams; Olivia K L Hamilton; Paul H Lee; Charis Bridger Staatz; Giorgio Di Gessa; Jingmin Zhu; Srinivasa Vittal Katikireddi; George B Ploubidis; Ellen J Thompson; Ruth C E Bowyer; Xinyuan Zhang; Golboo Abbasian; Maria Paz Garcia; Deborah Hart; Jeffrew Seow; Carl Graham; Neophytos Kouphou; Sam Acors; Michael H Malim; Ruth E Mitchell; Kate Northstone; Daniel Major-Smith; Sarah Matthews; Thomas Breeze; Michael Crawford; Lynn Molloy; Alex Siu Fung Kwong; Katie J Doores; Nishi Chaturvedi; Emma L Duncan; Nicholas J Timpson; Claire J Steves,King's College London; University of Cambridge; University College London; University College London; University College London; University College London; University of Glasgow; University of Leicester; University College London; University College London; University College London; University of Glasgow; University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; King's College London; University College London; King's College London; University of Bristol; King's College London,"SARS-CoV-2 antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. From cross-sectional antibody testing of 9,361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies (jointly in April-May 2021, and TwinsUK only in November 2021-January 2022), we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection and SARS-CoV-2 vaccination variables.
 
@@ -1033,6 +1121,32 @@ In a mixed methods study, we therefore aim to: (1) describe the usual healthcare
 Methods and analysisA mixed methods study will address our aims. Qualitative data collection from patients and health professionals will be achieved through surveys, interviews and focus group discussions, to understand their experience and document the function of clinics. A patient cohort study will provide an understanding of outcomes and costs of care. Accessible data will be further analysed to understand the nature of Long Covid, and the care received.
 
 Ethics and disseminationEthical approval was obtained from South Central - Berkshire Research Ethics Committee (reference 303958). The dissemination plan will be decided by the patient and public involvement and engagement (PPIE) group members and study Co-Is, but will target 1) policy makers, and those responsible for commissioning and delivering Long Covid services, 2) patients and the public, and 3) academics.",health systems and quality improvement,fuzzy,100,100
+medRxiv,10.1101/2022.05.05.22273234,2022-05-07,https://medrxiv.org/cgi/content/short/2022.05.05.22273234,Changes in English medication safety indicators throughout the COVID-19 pandemic: a federated analysis of 57 million patients' primary care records in situ using OpenSAFELY,Louis Fisher; Lisa E M Hopcroft; Sarah Rodgers; James Barrett; Kerry Oliver; Anthony J Avery; Dai Evans; Helen Curtis; Richard Croker; Orla Macdonald; Jessica Morley; Amir Mehrkar; Seb Bacon; Simon Davy; Iain Dillingham; David Evans; George Hickman; Peter Inglesby; Caroline E Morton; Becky Smith; Tom Ward; William Hulme; Amelia Green; Jon Massey; Alex J Walker; Chris Bates; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Shaun O'Hanlon; Alex Eavis; Richard Jarvis; Dima Avramov; Paul Griffiths; Aaron Fowles; Nasreen Parkes; Ben Goldacre; Brian MacKenna,"Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; Centre for Academic Primary Care, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG","ObjectiveTo describe the impact of the COVID-19 pandemic on safe prescribing, using the PINCER prescribing indicators; to implement complex prescribing indicators at national scale using GP data.
+
+DesignPopulation based cohort study, with the approval of NHS England using the OpenSAFELY platform.
+
+SettingElectronic health record data from 56.8 million NHS patients general practice records.
+
+ParticipantsAll NHS patients registered at a GP practice using TPP or EMIS computer systems and recorded as at risk of at least one potentially hazardous PINCER indicator between September 2019 and September 2021.
+
+Main outcome measureMonthly trends and between-practice variation for compliance with 13 PINCER measures between September 2019 and September 2021.
+
+ResultsThe indicators were successfully implemented across GP data in OpenSAFELY. Hazardous prescribing remained largely unchanged during the COVID-19 pandemic, with only small reductions in achievement of the PINCER indicators. There were transient delays in blood test monitoring for some medications, particularly ACE inhibitors. All indicators exhibited substantial recovery by September 2021. We identified 1,813,058 patients at risk of at least one hazardous prescribing event.
+
+ConclusionGood performance was maintained during the COVID-19 pandemic across a diverse range of widely evaluated measures of safe prescribing.
+
+Summary box O_TEXTBOXWHAT IS ALREADY KNOWN ON THIS TOPICO_LIPrimary care services were substantially disrupted by the COVID-19 pandemic.
+C_LIO_LIDisruption to safe prescribing during the pandemic has not previously been evaluated.
+C_LIO_LIPINCER is a nationally adopted programme of activities that aims to identify and correct hazardous prescribing in GP practices, by conducting manual audit on subgroups of practices.
+C_LI
+
+WHAT THIS STUDY ADDSO_LIFor the first time, we were able to successfully generate data on PINCER indicators for almost the whole population of England, in a single analysis.
+C_LIO_LIOur study is the most comprehensive assessment of medication safety during the COVID-19 pandemic in England, covering 95% of the population using well-validated measures.
+C_LIO_LIGood performance was maintained across many PINCER indicators throughout the pandemic.
+C_LIO_LIDelays in delivering some medication-related blood test monitoring were evident though considerable recovery was made by the end of the study period.
+C_LI
+
+C_TEXTBOX",primary care research,fuzzy,100,100
 medRxiv,10.1101/2022.05.03.22274395,2022-05-05,https://medrxiv.org/cgi/content/short/2022.05.03.22274395,Development and evaluation of low-volume tests to detect and characterise antibodies to SARS-CoV-2,Alice Halliday; Anna E Long; Holly E Baum; Amy C Thomas; Kathryn L Shelley; Elizabeth Oliver; Kapil Gupta; Ore Francis; Maia Kavanagh Williamson; Natalie Di Bartolo; Matthew J Randell; Yassin Ben Khoud; Ilana Kelland; Georgina Mortimer; Olivia Ball; Charlie Plumptre; Kyla Chandler; Ulrike Obst; Massimiliano Secchi; Lorenzo Piemonti; Vito Lampasona; Joyce Smith; Michaela Gregorova; Lea Knezevic; Jane Metz; Rachael Barr; Begonia Morales-Aza; Jennifer Oliver; Lucy Collingwood; Benjamin Hitchings; Susan Ring; Linda Wooldridge; Laura Rivino; Nicholas J Timpson; Jorgen McKernon; Peter Muir; Fergus W Hamilton; David Arnold; Derek N Woolfson; Anu Goenka; Andrew D Davidson; Ashley Mark Toye; Imre Berger; Mick Bailey; Kathleen M Gillespie; Alistair JK Williams; Adam Finn,"University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; IRCCS Ospedale San Raffaele; IRCCS Ospedale San Raffaele; IRCCS Ospedale San Raffaele; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; National Infection Service, UK Health Security Agency, Southmead Hospital, Bristol, UK; National Infection Service, UK Health Security Agency, Southmead Hospital, Bristol, UK; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol","Low-volume antibody assays can be used to track SARS-CoV-2 infection rates in settings where active testing for virus is limited and remote sampling is optimal. We developed 12 ELISAs detecting total or antibody isotypes to SARS-CoV-2 nucleocapsid, spike protein or its receptor binding domain (RBD), 3 anti-RBD isotype specific luciferase immunoprecipitation system (LIPS) assays and a novel Spike-RBD bridging LIPS total-antibody assay. We utilised pre-pandemic (n=984) and confirmed/suspected recent COVID-19 sera taken pre-vaccination rollout in 2020 (n=269). Assays measuring total antibody discriminated best between pre-pandemic and COVID-19 sera and were selected for diagnostic evaluation. In the blind evaluation, two of these assays (Spike Pan ELISA and Spike-RBD Bridging LIPS assay) demonstrated >97% specificity and >92% sensitivity for samples from COVID- 19 patients taken >21 days post symptom onset or PCR test. These assays offered better sensitivity for the detection of COVID-19 cases than a commercial assay which requires 100-fold larger serum volumes. This study demonstrates that low-volume in- house antibody assays can provide good diagnostic performance, and highlights the importance of using well-characterised samples and controls for all stages of assay development and evaluation. These cost-effective assays may be particularly useful for seroprevalence studies in low and middle-income countries.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2022.05.03.22274602,2022-05-03,https://medrxiv.org/cgi/content/short/2022.05.03.22274602,Accident and emergency (AE) attendance in England following infection with SARS-CoV-2 Omicron or Delta,Daniel J Grint; Kevin Wing; Hamish P Gibbs; Stephen JW Evans; Elizabeth J Williamson; Krishnan Bhaskaran; Helen I McDonald; Alex J Walker; David Evans; George Hickman; Rohini Mathur; Anna Schultze; Christopher T Rentsch; John Tazare; Ian J Douglas; Helen J Curtis; Caroline E Morton; Sebastian CJ Bacon; Simon Davy; Brian MacKenna; Peter Inglesby; Richard Croker; John Parry; Frank Hester; Sam Harper; Nicholas J DeVito; William J Hulme; Christopher Bates; Jonathan Cockburn; Amir Mehrkar; Ben Goldacre; Rosalind M Eggo; Laurie Tomlinson,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; TPP; TPP; University of Oxford; University of Oxford; TPP; TPP; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"The SARS-CoV-2 Omicron variant is increasing in prevalence around the world. Accurate estimation of disease severity associated with Omicron is critical for pandemic planning. We found lower risk of accident and emergency (AE) attendance following SARS-CoV-2 infection with Omicron compared to Delta (HR: 0.39 (95% CI: 0.30 - 0.51; P<.0001). For AE attendances that lead to hospital admission, Omicron was associated with an 85% lower hazard compared with Delta (HR: 0.14 (95% CI: 0.09 - 0.24; P<.0001)).
 
@@ -1206,13 +1320,6 @@ ConclusionThere is no evidence of an association between COVID-19 vaccination an
 What is already known on this topicSeveral studies have highlighted the association between COVID-19 vaccination and the risk of myocarditis, myopericarditis, and other cardiac problems, especially in young people, but associated risk of mortality is unclear. Since younger people have lower risk of COVID-19 hospitalisation and mortality, the mortality risk associated with vaccination is potentially more important to them in balancing the risk and benefit of vaccination.
 
 What this study addsAlthough there is a risk of myocarditis or myopericarditis with COVID-19, there is no evidence of increased risk of cardiac or all-cause mortality following COVID-19 vaccination in young people aged 12 to 29. Given the increased risk of mortality following SARS-CoV-2 infection in this group, the risk-benefit analysis favours COVID-19 vaccination for this age group.",epidemiology,fuzzy,100,100
-medRxiv,10.1101/2022.03.23.22272804,2022-03-23,https://medrxiv.org/cgi/content/short/2022.03.23.22272804,Waning effectiveness of BNT162b2 and ChAdOx1 COVID-19 vaccines over six months since second dose: a cohort study using linked electronic health records,Elsie MF Horne; William J Hulme; Ruth H Keogh; Tom M Palmer; Elizabeth J Williamson; Edward PK Parker; Amelia Green; Venexia Walker; Alex J Walker; Helen Curtis; Louis Fisher; Brian MacKenna; Richard Croker; Lisa Hopcroft; Robin Y Park; Jon Massey; Jessica Morely; Amir Mehrkar; Sebastian Bacon; David Evans; Peter Inglesby; Caroline E Morton; George Hickman; Simon Davy; Tom Ward; Iain Dillingham; Ben Goldacre; Miguel A Hernan; Jonathan AC Sterne,University of Bristol; Univeristy of Oxford; London School of Hygiene and Tropical Medicine; University of Bristol; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Univeristy of Oxford; University of Bristol; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Harvard University; University of Bristol,"BackgroundThe rate at which COVID-19 vaccine effectiveness wanes over time is crucial for vaccination policies, but is incompletely understood with conflicting results from different studies.
-
-MethodsThis cohort study, using the OpenSAFELY-TPP database and approved by NHS England, included individuals without prior SARS-CoV-2 infection assigned to vaccines priority groups 2-12 defined by the UK Joint Committee on Vaccination and Immunisation. We compared individuals who had received two doses of BNT162b2 or ChAdOx1 with unvaccinated individuals during six 4-week comparison periods, separately for subgroups aged 65+ years; 16-64 years and clinically vulnerable; 40-64 years and 18-39 years. We used Cox regression, stratified by first dose eligibility and geographical region and controlled for calendar time, to estimate adjusted hazard ratios (aHRs) comparing vaccinated with unvaccinated individuals, and quantified waning vaccine effectiveness as ratios of aHRs per-4-week period. The outcomes were COVID-19 hospitalisation, COVID-19 death, positive SARS-CoV-2 test, and non-COVID-19 death.
-
-FindingsThe BNT162b2, ChAdOx1 and unvaccinated groups comprised 1,773,970, 2,961,011 and 2,433,988 individuals, respectively. Waning of vaccine effectiveness was similar across outcomes and vaccine brands: e.g. in the 65+ years subgroup ratios of aHRs versus unvaccinated for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test ranged from 1.23 (95% CI 1.15-1.32) to 1.27 (1.20-1.34) for BNT162b2 and 1.16 (0.98-1.37) to 1.20 (1.14-1.27) for ChAdOx1. Despite waning, rates of COVID-19 hospitalisation and COVID-19 death were substantially lower among vaccinated individuals compared to unvaccinated individuals up to 26 weeks after second dose, with estimated aHRs <0.20 (>80% vaccine effectiveness) for BNT162b2, and <0.26 (>74%) for ChAdOx1. By weeks 23-26, rates of SARS-CoV-2 infection in fully vaccinated individuals were similar to or higher than those in unvaccinated individuals: aHRs ranged from 0.85 (0.78-0.92) to 1.53 (1.07-2.18) for BNT162b2, and 1.21 (1.13-1.30) to 1.99 (1.94-2.05) for ChAdOx1.
-
-InterpretationThe rate at which estimated vaccine effectiveness waned was strikingly consistent for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test, and similar across subgroups defined by age and clinical vulnerability. If sustained to outcomes of infection with the Omicron variant and to booster vaccination, these findings will facilitate scheduling of booster vaccination doses.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2022.03.18.22272607,2022-03-21,https://medrxiv.org/cgi/content/short/2022.03.18.22272607,"Multi-organ impairment and Long COVID: a 1-year prospective, longitudinal cohort study",Andrea Dennis; Daniel J Cuthbertson; Dan Wootton; Michael Crooks; Mark Gabbay; Nicole Eichert; Sofia Mouchti; Michele Pansini; Adriana Roca-Fernandez; Helena Thomaides-Brears; Matt Kelly; Matthew Robson; Lyth Hishmeh; Emily Attree; Melissa J Heightman; Rajarshi Banerjee; Amitava Banerjee,Perspectum Ltd; University of Liverpool; University of Liverpool; University of Hull; University of Liverpool; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Diagnostics; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Long COVID SoS; UKDoctors#Longcovid; UCLH; Perspectum Ltd; University College London,"ImportanceMulti-organ impairment associated with Long COVID is a significant burden to individuals, populations and health systems, presenting challenges for diagnosis and care provision. Standardised assessment across multiple organs over time is lacking, particularly in non-hospitalised individuals.
 
 ObjectiveTo determine the prevalence of organ impairment in Long COVID patients at 6 and at 12 months after initial symptoms and to explore links to clinical presentation.
@@ -1246,6 +1353,7 @@ ResultsThe baseline model (without any interventions) showed different workplace
 ConclusionThis work suggests that, without interventions, significant transmission could have occured in these workplaces, but that these posed minimal risk to customers. We found that identifying and isolating regular close-contacts of infectious individuals (i.e. house-share, carpools, or delivery pairs) is an efficient measure for stopping workplace outbreaks. Regular testing can make these isolation measures even more effective but also increases the number of staff isolating at one time. It is therefore more efficient to use these isolation measures in addition to social distancing and contact reduction interventions, rather than instead of, as these reduce both transmission and the number of people needing to isolate at one time.
 
 Author summaryDuring the COVID-19 pandemic the home-delivery sector was vital to maintaining peoples access to certain goods, and sustaining levels of economic activity for a variety of businesses. However, this important work necessarily involved contact with a large number of customers as well as colleagues. This means that questions have often been raised about whether enough was being done to keep customers and staff safe. Estimating the potential risk to customers and staff is complex, but here we tackle this problem by building a model of workplace and customer contacts, from which we simulate SARS-CoV-2 transmission. By involving industry representatives in the development of this model, we have simulated interventions that have either been applied or considered, and so the findings of this study are relevant to decisions made in that sector. Furthermore, we can learn generic lessons from this specific case study which apply to many types of shared workplace as well as highlighting implications of the highly stochastic nature of disease transmission in small populations.",epidemiology,fuzzy,100,100
+medRxiv,10.1101/2022.03.17.22272535,2022-03-18,https://medrxiv.org/cgi/content/short/2022.03.17.22272535,Comparison of the 2021 COVID-19 'Roadmap' Projections against Public Health Data,Matt J Keeling; Louise J Dyson; Michael Tildesley; Edward M Hill; Sam M Moore,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Control and mitigation of the COVID-19 pandemic in England has relied on a combination of vaccination and non-pharmaceutical interventions (NPIs). Some of these NPIs are extremely costly (economically and socially), so it was important to relax these promptly without overwhelming already burdened health services. The eventual policy was a Roadmap of four relaxation steps throughout 2021, taking England from lock-down to the cessation of all restrictions on social interaction. In a series of six Roadmap documents generated throughout 2021, models assessed the potential risk of each relaxation step. Here we show that the model projections generated a reliable estimation of medium-term hospital admission trends, with the data points up to September 2021 generally lying within our 95% prediction intervals. The greatest uncertainties in the modelled scenarios came from vaccine efficacy estimates against novel variants, and from assumptions about human behaviour in the face of changing restrictions and risk.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2022.03.15.22272362,2022-03-16,https://medrxiv.org/cgi/content/short/2022.03.15.22272362,Community-level characteristics of COVID-19 vaccine hesitancy in England: A nationwide cross-sectional study,Georges Bucyibaruta; Marta Blangialdo; Garyfallos Konstantinoudis,Imperial College London; Imperial College London; Imperial College London,"One year after the start of the COVID-19 vaccination programme in England, more than 43 million people older than 12 years old had received at least a first dose. Nevertheless, geographical differences persist, and vaccine hesitancy is still a major public health concern; understanding its determinants is crucial to managing the COVID-19 pandemic and preparing for future ones. In this cross-sectional population-based study we used cumulative data on the first dose of vaccine received by 01-01-2022 at Middle Super Output Area level in England. We used Bayesian hierarchical spatial models and investigated if the geographical differences in vaccination uptake can be explained by a range of community-level characteristics covering socio-demographics, political view, COVID-19 health risk awareness and targeting of high risk groups and accessibility. Deprivation is the covariate most strongly associated with vaccine uptake (Odds Ratio 0.55, 95%CI 0.54-0.57; most versus least deprived areas). The most ethnically diverse areas have a 38% (95%CI 36-40%) lower odds of vaccine uptake compared with those least diverse. Areas with the highest proportion of population between 12 and 24 years old had lower odds of vaccination (0.87, 95%CI 0.85-0.89). Finally increase in vaccine accessibility is associated with higher COVID-19 uptake (OR 1.07, 95%CI 1.03-1.12). Our results suggest that one year after the start of the vaccination programme, there is still evidence of inequalities in uptake, affecting particularly minorities and marginalised groups. Strategies including prioritising active outreach across communities and removing practical barriers and factors that make vaccines less accessible are needed to level up the differences.",epidemiology,fuzzy,94,100
 medRxiv,10.1101/2022.03.14.22272283,2022-03-14,https://medrxiv.org/cgi/content/short/2022.03.14.22272283,Migrants' primary care utilisation before and during the COVID-19 pandemic in England: An interrupted time series,Claire X Zhang; Yamina Boukari; Neha Pathak; Rohini Mathur; Srinivasa Vittal Katikireddi; Parth Patel; Inês Campos-Matos; Dan Lewer; Vincent Nguyen; Greg Hugenholtz; Rachel Burns; Amy R Mulick; Alasdair Henderson; Robert W Aldridge,UCL; University College London; University College London; London School of Hygiene and Tropical Medicine; University of Glasgow; University College London; Department of Health and Social Care; University College London; University College London; University College London; University College London; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; UCL,"BackgroundHow international migrants access and use primary care in England is poorly understood. We aimed to compare primary care consultation rates between international migrants and non-migrants in England before and during the COVID-19 pandemic (2015- 2020).
 
@@ -1557,6 +1665,7 @@ Method and FindingsThis multi-phase, prospective mixed-methods study took place
 
 ConclusionsThe SBQ-LC is a comprehensive patient-reported assessment of Long COVID symptom burden developed using modern psychometric methods. It measures symptoms of Long COVID important to individuals with lived experience and may be used to evaluate the impact of interventions and inform best practice in clinical management.",health informatics,fuzzy,100,100
 medRxiv,10.1101/2022.01.13.22268948,2022-01-14,https://medrxiv.org/cgi/content/short/2022.01.13.22268948,Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: Insights from Rapid COVID-19 Diagnosis by Adversarial Learning,Jenny Yang; Andrew AS Soltan; Yang Yang; David A Clifton,The University of Oxford; University of Oxford; The University of Oxford; The University of Oxford,"Machine learning is becoming increasingly prominent in healthcare. Although its benefits are clear, growing attention is being given to how machine learning may exacerbate existing biases and disparities. In this study, we introduce an adversarial training framework that is capable of mitigating biases that may have been acquired through data collection or magnified during model development. For example, if one class is over-presented or errors/inconsistencies in practice are reflected in the training data, then a model can be biased by these. To evaluate our adversarial training framework, we used the statistical definition of equalized odds. We evaluated our model for the task of rapidly predicting COVID-19 for patients presenting to hospital emergency departments, and aimed to mitigate regional (hospital) and ethnic biases present. We trained our framework on a large, real-world COVID-19 dataset and demonstrated that adversarial training demonstrably improves outcome fairness (with respect to equalized odds), while still achieving clinically-effective screening performances (NPV>0.98). We compared our method to the benchmark set by related previous work, and performed prospective and external validation on four independent hospital cohorts. Our method can be generalized to any outcomes, models, and definitions of fairness.",health informatics,fuzzy,100,100
+medRxiv,10.1101/2022.01.05.21268323,2022-01-06,https://medrxiv.org/cgi/content/short/2022.01.05.21268323,Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey,Katrina A Lythgoe; Tanya Golubchik; Matthew Hall; Thomas House; Roberto Cahuantzi; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; Mahan Ghafari; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Christophe Fraser; Ian Diamond; Jeff Barrett; Ann Sarah Walker; David Bonsall,University of Oxford; University of Oxford; University of Oxford; University of Manchester; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Wellcome Sanger Institute; Office for National Statistics; ; University of Oxford; Office for National Statistics; Wellcome Sanger Institute; University of Oxford; University of Oxford,"The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non- SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly in the current phase of the pandemic with routine RT-PCR testing now ended in the community.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2022.01.01.21268131,2022-01-05,https://medrxiv.org/cgi/content/short/2022.01.01.21268131,Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England,Laura Marcela Guzman Rincon; Edward M Hill; Louise Dyson; Michael J Tildesley; Matt J Keeling,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Quantitative assessments of the recent state of an epidemic and short-term projections into the near future are key public health tools that have substantial policy impacts, helping to determine if existing control measures are sufficient or need to be strengthened. Key to these quantitative assessments is the ability to rapidly and robustly measure the speed with which the epidemic is growing or decaying. Frequently, epidemiological trends are addressed in terms of the (time-varying) reproductive number R. Here, we take a more parsimonious approach and calculate the exponential growth rate, r, using a Bayesian hierarchical model to fit a Gaussian process to the epidemiological data. We show how the method can be employed when only case data from positive tests are available, and the improvement gained by including the total number of tests as a measure of heterogeneous testing effort. Although the methods are generic, we apply them to SARS-CoV-2 cases and testing in England, making use of the available high-resolution spatio-temporal data to determine long-term patterns of national growth, highlight regional growth and spatial heterogeneity.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2021.12.31.21268587,2022-01-02,https://medrxiv.org/cgi/content/short/2021.12.31.21268587,"The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data",Caroline E Dale; Rohan Takhar; Ray Carragher; Fatemeh Torabi; Michalis Katsoulis; Stephen Duffield; Seamus Kent; Tanja Mueller; Amanj Kurdi; Stuart McTaggart; Hoda Abbasizanjani; Sam Hollings; Andrew Scourfield; Ronan Lyons; Rowena Griffiths; Jane Lyons; Gareth Davies; Dan Harris; Alex Handy; Mehrdad Alizadeh Mizani; Chris Tomlinson; Mark Ashworth; Spiros Denaxas; Amitava Banerjee; Jonathan Sterne; Kate Lovibond; Paul Brown; Ian Bullard; Rouven Priedon; Mamas A Mamas; Ann Slee; Paula Lorgelly; Munir Pirmohamed; Kamlesh Khunti; Naveed Sattar; Andrew Morris; Cathie Sudlow; Ashley Akbari; Marion Bennie; Reecha Sofat; - CVD-COVID-UK Consortium,"Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Swansea University; Institute of Health Informatics Research, University College London; NICE; NICE; University of Strathclyde; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Public Health Scotland; Swansea University; NHS Digital, Leeds; UCLH NHS Foundation Trust; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; King's College London; Institute of Health Informatics Research, University College London; University College London; University of Bristol; Royal College of Physicians; NHS Digital, Leeds; NHS Digital; British Heart Foundation Data Science Centre, Health Data Research UK, London; Keele University; NHSX; Department of Applied Health Research, University College London; University of Liverpool; University of Leicester; University of Glasgow; Health Data Research UK; British Heart Foundation Data Science Centre, Health Data Research UK, London; Swansea University; University of Strathclyde; Institute of Health Informatics Research, University College London; ","ObjectivesTo estimate the impact of the COVID-19 pandemic on cardiovascular disease (CVD) and CVD management using routinely collected medication data as a proxy.
 
@@ -1619,7 +1728,6 @@ MethodTrial emulation was conducted by pooling results from six cohorts whose re
 ResultsAcross six cohorts, there were a total of 21,283 participants who were eligible and vaccinated with either ChAdOx1 (n = 13,813) or BNT162b2 (n = 7,470) with a median follow-up time of 266 days (IQR: 235 - 282). By November 12th 2021, 750 (5.4%) adults who had ChAdOx1 as their vaccine experienced a SARS-CoV-2 infection, compared to 296 (4.0%) who had BNT162b2. We found that people who received ChAdOx1 vaccinations had 10.54 per 1000 people higher cumulative incidence for SARS-CoV-2 infection compared to BNT162b2 for infections during a maximum of 315 days of follow-up. When adjusted for age at vaccination, sex, minority ethnic status, index of multiple deprivation, and clinical vulnerability status, we found a pooled adjusted hazard ratio of 1.35 [HR: 1.35, 95%CI: 1.15 - 1.58], demonstrating a 35% increase in SARS-CoV-2 infections in people who received ChAdOx1 compared to BNT162b2.
 
 DiscussionWe found evidence of greater effectiveness of receiving BNT162b2 compared to ChAdOx1 vaccines against SARS-CoV-2 infection in England and Wales during a time period when Delta became the most prevalent variant of concern. Our findings demonstrate the importance of booster (third) doses to maintain protection and suggest that these should be prioritised to those who received ChAdOx1 as their primary course.",epidemiology,fuzzy,100,100
-bioRxiv,10.1101/2021.12.17.473248,2021-12-21,https://biorxiv.org/cgi/content/short/2021.12.17.473248,"SARS-CoV-2 Omicron spike mediated immune escape, infectivity and cell-cell fusion",Bo Meng; Isabella Ferreira; Adam Abdullahi; Niluka Goonawardane; Akatsuki Saito; Izumi Kimura; Daichi Yamasoba; Steven A Kemp; Guido Papa; Saman Fatihi; Surabhi Rathore; Pehuen Perera Gerba; Terumasa Ikeda; Mako Toyoda; Toong Seng Tan; Jin Kuramochi; Shigeki Mitsunaga; Takamasa Ueno; Oscar Charles; Dami Collier; - CITIID-NIHR BioResource COVID-19 Collaboration; - The Genotype to Phenotype Japan (G2P-Japan) Consortium; - Ecuador-COVID19 Consortium; John Bradley; Jinwook Choi; Kenneth Smith; Elo Madissoon; Kerstin Meyer; Petra Mlcochova; Rainer Doffinger; Sarah A Teichmann; Leo James; Joo Hyeon Lee; Teresa Brevini; Matteo Pizzuto; Myra Hosmillo; Donna Mallery; Samantha Zepeda; Alexandra Walls; Anshu Joshi; John Bowen; John Briggs; Alex Sigal; Laurelle Jackson; Sandile Cele; Anna De Marco; Fotios Sampaziotis; Davide Corti; David Veesler; Nicholas Matheson; Ian Goodfellow; Lipi Thukral; Kei Sato; Ravindra K Gupta,"University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Miyazaki; The University of Tokyo; Kumamoto University; University of Cambridge; LMB Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; CSIR Institute of Genomics and Integrative Biology, Delhi, India; University of Cambridge; Kumamoto Univ; Kumamoto University, Kumamoto; Kuramochi Clinic Interpark; Kuramochi Clinic Interpark; National Institute of Genetics, Mishima, Shizuoka; Kumamoto University, Kumamoto; University College London; University of Cambridge; -; -; -; University of Cambridge; University of Cambridge; University of Cambridge; Wellcome Sanger Institute; Wellcome Sanger Institute; University of Cambridge; Cambridge University Hospitals NHS Trust; Cambridge University; MRC LMB; University of Cambridge; University of Cambridge; Humabs Biomed SA; University of Cambridge; MRC LMB Cambridge; University of Washington; University of Washington; University of Washington; University of Washington; University of Heidelberg; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Humabs Biomed SA; University of Cambridge; Humabs Biomed SA; University of Washington; University of Cambridge; University of Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; The University of Tokyo; University of Cambridge","The SARS-CoV-2 Omicron BA.1 variant emerged in late 2021 and is characterised by multiple spike mutations across all spike domains. Here we show that Omicron BA.1 has higher affinity for ACE2 compared to Delta, and confers very significant evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralising antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralisation. Importantly, antiviral drugs remdesevir and molnupiravir retain efficacy against Omicron BA.1. We found that in human nasal epithelial 3D cultures replication was similar for both Omicron and Delta. However, in lower airway organoids, Calu-3 lung cells and gut adenocarcinoma cell lines live Omicron virus demonstrated significantly lower replication in comparison to Delta. We noted that despite presence of mutations predicted to favour spike S1/S2 cleavage, the spike protein is less efficiently cleaved in live Omicron virions compared to Delta virions. We mapped the replication differences between the variants to entry efficiency using spike pseudotyped virus (PV) entry assays. The defect for Omicron PV in specific cell types correlated with higher cellular RNA expression of TMPRSS2, and accordingly knock down of TMPRSS2 impacted Delta entry to a greater extent as compared to Omicron. Furthermore, drug inhibitors targeting specific entry pathways demonstrated that the Omicron spike inefficiently utilises the cellular protease TMPRSS2 that mediates cell entry via plasma membrane fusion. Instead, we demonstrate that Omicron spike has greater dependency on cell entry via the endocytic pathway requiring the activity of endosomal cathepsins to cleave spike. Consistent with suboptimal S1/S2 cleavage and inability to utilise TMPRSS2, syncytium formation by the Omicron spike was dramatically impaired compared to the Delta spike. Overall, Omicron appears to have gained significant evasion from neutralising antibodies whilst maintaining sensitivity to antiviral drugs targeting the polymerase. Omicron has shifted cellular tropism away from TMPRSS2 expressing cells that are enriched in cells found in the lower respiratory and GI tracts, with implications for altered pathogenesis.",microbiology,fuzzy,100,100
 medRxiv,10.1101/2021.12.20.21268098,2021-12-21,https://medrxiv.org/cgi/content/short/2021.12.20.21268098,"Therapies for Long COVID in non-hospitalised individuals - from symptoms, patient-reported outcomes, and immunology to targeted therapies (The TLC Study): Study protocol",Shamil Haroon; Krishnarajah Nirantharakumar; Sarah Hughes; Anuradhaa Subramanian; Olalekan Lee Aiyegbusi; Elin Haf Davies; Puja Myles; Tim Williams; Grace Turner; Joht Singh Chandan; Christel McMullan; Janet Lord; David Wraith; Kirsty McGee; Alastair Denniston; Tom Taverner; Louise Jackson; Elizabeth Sapey; Georgios Gkoutos; Krishna Gokhale; Edward Leggett; Clare Iles; Christopher Frost; Gary McNamara; Amy Bamford; Tom Marshall; Dawit Zemedikun; Gary Price; Steven Marwaha; Nikita Simms-Williams; Kirsty Brown; Anita Walker; Karen Jones; Karen Matthews; Jennifer Camaradou; Michael Saint-Cricq; Sumita Kumar; Yvonne Alder; David Stanton; Lisa Agyen; Megan Baber; Hannah Blaize; Melanie Calvert,University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; Aparito; Medicines and Healthcare Products Regulatory Agency; Medicines and Healthcare Products Regulatory Agency; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University Hospitals Birmingham NHS Foundation Trust; University of Birmingham; University of Birmingham; University of Birmingham; University ofBirmingham; University of Birmingham; Medicines and Healthcare Products Regulatory Agency; Medicines and Healthcare Products Regulatory Agency; Aparito; Aparito; University Hospitals Birmingham NHS Foundation Trust; University of Birmingham; University of Birmingham; N/A; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; University ofBirmingham,"IntroductionIndividuals with COVID-19 frequently experience symptoms and impaired quality of life beyond 4-12 weeks, commonly referred to as Long COVID. Whether Long COVID is one or several distinct syndromes is unknown. Establishing the evidence base for appropriate therapies is needed. We aim to evaluate the symptom burden and underlying pathophysiology of Long COVID syndromes in non-hospitalised individuals and evaluate potential therapies.
 
 Methods and analysisA cohort of 4000 non-hospitalised individuals with a past COVID-19 diagnosis and 1000 matched controls will be selected from anonymised primary care records from the Clinical Practice Research Datalink (CPRD) and invited by their general practitioners to participate on a digital platform (Atom5). Individuals will report symptoms, quality of life, work capability, and patient reported outcome measures. Data will be collected monthly for one year.
@@ -1704,13 +1812,6 @@ Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe systematically s
 Added value of this studyIn a diverse population of adults post-hospital admission with COVID-19, our large UK prospective multi-centre study reports several novel findings: the minority felt fully recovered at one year with minimal recovery from five months across any health domain; female sex and obesity are associated with being less likely to feel fully recovered at one year; several inflammatory mediators were increased in individuals with the most severe physical, mental health, and cognitive impairments compared to individuals with milder ongoing impairments.
 
 Implications of all the available evidenceBoth pharmacological and non-pharmacological interventions are urgently needed to improve the ongoing burden following hospitalisation for COVID-19 both for individuals and healthcare systems; our findings support the use of a precision medicine approach with potential treatable traits of systemic inflammation and obesity.",infectious diseases,fuzzy,100,100
-medRxiv,10.1101/2021.12.13.21267368,2021-12-15,https://medrxiv.org/cgi/content/short/2021.12.13.21267368,Acute COVID-19 severity and 16-month mental morbidity trajectories in patient populations of six nations,Ingibjorg Magnusdottir; Aniko Lovik; Anna Bara Unnarsdottir; Daniel L. McCartney; Helga Ask; Kadri Koiv; Lea Arregui Nordahl Christoffersen; Sverre Urnes Johnson; Andrew M McIntosh; Anna K. Kahler; Archie Campbell; Arna Hauksdottir; Chloe Fawns-Ritchie; Christian Erikstrup; Dorte Helenius; Drew Altschul; Edda Bjork Thordardottir; Elias Eythorsson; Emma M. Frans; Gunnar Tomasson; Harpa Lind Jonsdottir; Harpa Runarsdottir; Henrik Hjalgrim; Hronn Hardardottir; Juan Gonzalez-Hijon; Karina Banasik; Khoa Manh Dinh; Li Lu; Lili Milani; Lill Trogstad; Maria Didriksen; Omid V. Ebrahimi; Patrick F. Sullivan; Per Minor Magnus; Qing Shen; Ragnar Nesvag; Reedik Magi; Runolfur Palsson; Sisse Rye Ostrowski; Thomas Werge; Asle Hoffart; David J. Porteous; Fang Fang; Johanna Jakobsdottir; Kelli Lehto; Ole A. Andreassen; Ole B.V. Pedersen; Thor Aspelund; Unnur Anna Valdimarsdottir,"Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Oslo, Oslo, Norway; Division of Psychiatry, University of Edinburgh, Edinburgh, UK; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark; Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Edinburgh, Edinburgh, UK; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Faculty of Psychology, University of Iceland School of Health Sciences, Reykjavik, Iceland; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Danish Cancer Society Research Center, Copenhagen, Denmark; Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Translational Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Oslo, Oslo, Norway; Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA; Centre of Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway.; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Oslo, Oslo, Norway; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Immunology, Zealand University Hospital, Denmark; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland","BACKGROUNDThe aim of this multinational study was to assess the development of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis.
-
-METHODSParticipants consisted of 247 249 individuals from seven cohorts across six countries (Denmark, Estonia, Iceland, Norway, Scotland, and Sweden) recruited from April 2020 through August 2021. We used multivariable Poisson regression to contrast symptom-prevalence of depression, anxiety, COVID-19 related distress, and poor sleep quality among individuals with and without a diagnosis of COVID-19 at entry to respective cohorts by time (0-16 months) from diagnosis. We also applied generalised estimating equations (GEE) analysis to test differences in repeated measures of mental health symptoms before and after COVID-19 diagnosis among individuals ever diagnosed with COVID-19 over time.
-
-FINDINGSA total of 9979 individuals (4%) were diagnosed with COVID-19 during the study period and presented overall with a higher symptom burden of depression (prevalence ratio [PR] 1{middle dot}18, 95% confidence interval [95% CI] 1{middle dot}03-1{middle dot}36) and poorer sleep quality (1{middle dot}13, 1{middle dot}03-1{middle dot}24) but not with higher levels of symptoms of anxiety or COVID-19 related distress compared with individuals without a COVID-19 diagnosis. While the prevalence of depression and COVID-19 related distress attenuated with time, the trajectories varied significantly by COVID-19 acute infection severity. Individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risks of depression and anxiety (PR 0{middle dot}83, 95% CI 0{middle dot}75-0{middle dot}91 and 0{middle dot}77, 0{middle dot}63-0{middle dot}94, respectively), while patients bedridden for more than 7 days were persistently at higher risks of symptoms of depression and anxiety (PR 1{middle dot}61, 95% CI 1{middle dot}27-2{middle dot}05 and 1{middle dot}43, 1{middle dot}26-1{middle dot}63, respectively) throughout the 16-month study period.
-
-CONCLUSIONAcute infection severity is a key determinant of long-term mental morbidity among COVID-19 patients.",public and global health,fuzzy,100,92
 medRxiv,10.1101/2021.12.14.21267460,2021-12-15,https://medrxiv.org/cgi/content/short/2021.12.14.21267460,Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales,Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne Johnson; Martie Van Tongeren; Robert W Aldridge; Andrew Hayward,University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Manchester; University College London; University College London,"BackgroundWorkers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase.
 
 MethodsData from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR).
@@ -1820,13 +1921,6 @@ Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existin
 Added value of this studyUsing data from one of the largest UK citizen science epidemiological initiatives, we describe and compare illness (symptom duration, burden, profile, risk of long illness, and hospital attendance) in symptomatic community-based adults presenting when either the Alpha or Delta variant was the predominant circulating strain of SARS-CoV-2 in the UK. We assess evidence of transmission, reinfection, and vaccine effectiveness. Our data show that the seven most common symptoms with Delta infection were the same as with Alpha infection. Risks of illness duration [&ge;]7 days and [&ge;]28 days, and of requiring hospital care, were not increased. In line with previous research, we found increased transmissibility of Delta vs. previous variants; and no evidence of increased re-infection rates. Our data support high vaccine efficacy of BNT162b2 and ChAdOx1 nCoV-19 formulations against Delta variant infection. Overall, our study adds quantitative information regarding meaningful clinical differences in COVID-19 due to Delta vs. other variants.
 
 Implications of all the available evidenceOur observational data confirm that COVID-19 disease in UK in adults is generally comparable to infection with the Alpha variant, including in elderly individuals. Our data contribute to epidemiological surveillance from the wider UK population and may capture information from COVID-19 presentation within the community that might be missed in healthcare-based surveillance. Our data may be useful in informing healthcare service planning, vaccination policies, and measures for social protection.",epidemiology,fuzzy,94,100
-medRxiv,10.1101/2021.11.22.21266692,2021-11-24,https://medrxiv.org/cgi/content/short/2021.11.22.21266692,Serological responses to COVID-19 booster vaccine in England,Georgina Ireland; Heather Whitaker; Shamez N Ladhani; Frances Baawuah; Vani Subbarao; Ezra Linley; Lenesha Warrener; Michelle O'Brien; Corrine Whillock; Paul Moss; Mary E Ramsay; Gayatri Amirthalingam; Kevin E Brown,"UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; Brondesbury Medical Centre, Kilburn, London, United Kingdom; UK Health Security Agency; University of Birmingham; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency","IntroductionThere are limited data on immune responses after COVID-19 vaccine boosters in individuals receiving primary immunisation with BNT162b2 (Pfizer-BioNTech) or AZD1222 (AstraZeneca).
-
-MethodsA prospective, cohort study to assess SARS-CoV-2 antibody responses before and after booster vaccination with BNT162b2 in adults receiving either (i) two BNT162b2 doses <30 days apart (BNT162b2-control), (ii) two BNT162b2 doses [&ge;]30 days apart (BNT162b2-extended) or (iii) two AZD1222 doses [&ge;]30 days apart (AZD1222-extended) in London, England. SARS-CoV-2 spike protein antibody geometric mean titres (GMTs) before and 2-4 weeks after booster were compared.
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-ResultsOf 750 participants, 626 provided serum samples for up to 38 weeks after their second vaccine dose. Antibody GMTs peaked at 2-4 weeks after the second dose, before declining by 68% at 36-38 weeks after dose 2 for BNT162b2-control participants, 85% at 24-29 weeks for BNT162b2-extended participants and 78% at 24-29 weeks for AZD1222-extended participants. Antibody GMTs was highest in BNT162b2-extended participants (942 [95%CI, 797-1113]) than AZD1222-extended (183 [124-268]) participants at 24-29 weeks or BNT162b2-control participants at 36-38 weeks (208; 95%CI, 150-289). At 2-4 weeks after booster, GMTs were significantly higher than after primary vaccination in all three groups: 18,104 (95%CI, 13,911-23,560; n=47) in BNT162b2-control (76.3-fold), 13,980 (11,902-16,421; n=118) in BNT162b2-extended (15.9-fold) and 10,799 (8,510-13,704; n=43) in AZD1222-extended (57.2-fold) participants. BNT162b2-control participants (median:262 days) had a longer interval between primary and booster doses than BNT162b2-extended or AZD1222-extended (both median:186 days) participants.
-
-ConclusionsWe observed rapid serological responses to boosting with BNT162b2, irrespective of vaccine type or schedule used for primary immunisation, with higher post-booster responses with longer interval between primary immunisation and boosting. Boosters will not only provide additional protection for those at highest risk of severe COVID-19 but also prevent infection and, therefore, interrupt transmission, thereby reducing infections rates in the population. Ongoing surveillance will be important for monitoring the duration of protection after the booster.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.11.22.21266512,2021-11-24,https://medrxiv.org/cgi/content/short/2021.11.22.21266512,Association of COVID-19 with arterial and venous vascular diseases: a population-wide cohort study of 48 million adults in England and Wales,Rochelle Knight; Venexia Walker; Samantha Ip; Jennifer A Cooper; Thomas Bolton; Spencer Keene; Rachel Denholm; Ashley Akbari; Hoda Abbasizanjani; Fatemeh Torabi; Efosa Omigie; Sam Hollings; Teri-Louise North; Renin Toms; Emanuele Di Angelantonio; Spiros Denaxas; Johan H Thygesen; Christopher Tomlinson; Ben Bray; Craig J Smith; Mark Barber; George Davey Smith; Nishi Chaturvedi; Cathie Sudlow; William N Whiteley; Angela Wood; Jonathan A C Sterne; - CVD-COVID-UK/COVID-IMPACT consortium; - Longitudinal Health and Wellbeing COVID-19 National Core Study,University of Bristol; University of Bristol; University of Cambridge; University of Bristol; University of Cambridge; University of Cambridge; University of Bristol; Swansea University; Swansea University; Swansea University; NHS Digital; NHS Digital; University of Bristol; University of Bristol; University of Cambridge; University College London; University College London; University College London; Kings College London; University of Manchester; Glasgow Caledonian University; University of Bristol; University College London; Health Data Research UK; University of Edinburgh; University of Cambridge; University of Bristol; ; ,"ImportanceThe long-term effects of COVID-19 on the incidence of vascular diseases are unclear.
 
 ObjectiveTo quantify the association between time since diagnosis of COVID-19 and vascular disease, overall and by age, sex, ethnicity, and pre-existing disease.
@@ -1872,6 +1966,17 @@ ResultsCompared to those who remained working, furloughed workers were at greate
 
 ConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.",psychiatry and clinical psychology,fuzzy,100,100
 medRxiv,10.1101/2021.11.15.21266255,2021-11-16,https://medrxiv.org/cgi/content/short/2021.11.15.21266255,"COVID-19 vaccination, risk-compensatory behaviours, and social contacts in four countries in the UK",John Buckell; Joel Jones; Philippa C Matthews; Ian Diamond; Emma Rourke; Ruth Studley; Duncan Cook; Ann Sarah Walker; Koen B Pouwels; - The COVID-19 Infection Survey Team,University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; ,"The physiological effects of vaccination against SARS-CoV-2 (COVID-19) are well documented, yet the behavioural effects are largely unknown. Risk compensation suggests that gains in personal safety, as a result of vaccination, are offset by increases in risky behaviour, such as socialising, commuting and working outside the home. This is potentially problematic because transmission of SARS-CoV-2 is driven by contacts, which could be amplified by vaccine-related risk compensation behaviours. Here, we show that behaviours were overall unrelated to personal vaccination, but - adjusting for variation in mitigation policies - were responsive to the level of vaccination in the wider population: individuals in the UK were risk compensating when rates of vaccination were rising. This effect was observed across four nations of the UK, each of which varied policies autonomously.",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2021.11.10.21266124,2021-11-11,https://medrxiv.org/cgi/content/short/2021.11.10.21266124,Differences in COVID-19 vaccination coverage by occupation in England: a national linked data study,Vahe Nafilyan; Ted Dolby; Katie Finning; Jasper Morgan; Rhiannon Edge; Myer Glickman; Neil Pearce; Martie Van Tongeren,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Lancaster University; Office for National Statistics; London School of Hygiene and Tropical Medicine; University of Manchester,"BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation.
+
+MethodsUsing nationwide population-level data, we calculated the proportion of people who had received two doses of a COVID-19 vaccine (assessed on 31 August 2021) by detailed occupational categories in adults aged 40-64 and estimated adjusted odds ratios to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.
+
+ResultsOur study population included 14,298,147 adults 40-64. Vaccination rates differed markedly by occupation, being higher in administrative and secretarial occupations (90.8%); professional occupations (90.7%); and managers, directors and senior officials (90.6%); and lowest (83.1%) in people working in elementary occupations. We found substantial differences in vaccination rates looking at finer occupational groups even after adjusting for confounding factors, such as education. Vaccination rates were higher in occupations which can be done from home and lower in those which cannot. Many occupations with low vaccination rates also involved contact with the public or with vulnerable people
+
+ConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection, especially in occupations that cannot be done from home and involve contacts with the public. Policies such as  work from home if you can may only have limited future impact on hospitalisations and deaths
+
+What is already known on this subject?Whilst several studies highlight differences in vaccination coverage by ethnicity, religion, socio-demographic factors and certain underlying health conditions, there is very little evidence on how vaccination coverage varies by occupation, in the UK and elsewhere. The few study looking at occupational differences in vaccine hesitancy focus on healthcare workers or only examined broad occupational groups. There is currently no large-scale study on occupational differences in COVID-19 vaccination coverage in the UK.
+
+What this study adds?Using population-level linked data combining the 2011 Census, primary care records, mortality and vaccination data, we found that the vaccination rates of adults aged 40 to 64 years in England differed markedly by occupation. Vaccination rates were high in administrative and secretarial occupations, professional occupations and managers, directors and senior officials and low in people working in elementary occupations. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were also associated with the ability to work from home, with the vaccination rate being higher in occupations which can be done performed from home. Policies aiming to increase vaccination rates in occupations that cannot be done from home and involve contacts with the public should be priorities",public and global health,fuzzy,100,100
 medRxiv,10.1101/2021.11.05.21265968,2021-11-09,https://medrxiv.org/cgi/content/short/2021.11.05.21265968,Waning of SARS-CoV-2 antibodies targeting the Spike protein in individuals post second dose of ChAdOx1 and BNT162b2 COVID-19 vaccines and risk of breakthrough infections: analysis of the Virus Watch community cohort.,Robert William Aldridge; Alexei Yavlinsky; Vincent Grigori Nguyen; Max T Eyre; Madhumita Shrotri; Annalan Mathew Dwight Navaratnam; Sarah Beale; Isobel Braithwaite; Thomas Edward Byrne; Jana Kovar; Ellen Fragaszy; Erica Wing Lam Fong; Cyril Roman Geismar; Parth Patel; Alison Rodger; Anne M Johnson; Andrew C Hayward,"University College London; University College London; University College London; Lancaster University, Liverpool School of Tropical Medicine; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London","BackgroundSARS-CoV-2 vaccines stimulate production of antibodies targeting the spike protein (anti-S). The level of antibodies following vaccination and trajectories of waning may differ between vaccines influencing the level of protection, how soon protection is reduced and, consequently the optimum timing of booster doses.
 
 MethodsWe measured SARS-CoV-2 anti-S titre in the context of seronegativity for SARS-CoV-2 anti-Nucleocapsid (anti-N), in samples collected between 1st July and 24th October 2021 in a subset of adults in the Virus Watch community cohort. We compared anti-S levels after BNT162b2 (BioNTech/Pfizer) or ChAdOx1 (AstraZeneca/Oxford) vaccination using time since second dose of vaccination, age, sex and clinical vulnerability to investigate antibody waning. To investigate the use of anti-S levels as a correlate of protection against SARS-CoV-2 infection, we undertook a survival analysis (Kaplan-Meier and Cox) with individuals entering 21 days after their second dose of vaccine, or first antibody test after 1st July (whichever was latest) and exiting with the outcome of SARS-Cov-2 infection or at the end of follow up 24th October 2021. We also undertook a negative test design case-control analysis of infections occurring after the second vaccine dose (breakthrough infections) to determine whether the type of vaccine affected the risk of becoming infected.
@@ -2138,7 +2243,6 @@ Methods and findingsWe performed a rapid systematic review, searching Medline, E
 49 observational studies (15 peer-reviewed papers and 34 preprints) reported primary outcomes for eight drug groups hypothesised to be deleterious. Meta-analysis showed that acute inpatient corticosteroid use was associated with increased mortality (OR 2.22, 95% CI 1.26-3.90), however this result appeared to have been biased by confounding via indication. One subgroup analysis indicated an association between immunosuppressant use and susceptibility to COVID-19 among case control and cross-sectional studies (OR 1.29, 95% CI 1.19-1.40) but this was not found with cohort studies (OR 1.11, 95% CI 0.86-1.43). Studies which adjusted for multiple confounders showed that people taking angiotensin-converting-enzyme inhibitors (ACEIs) or angiotensin-II-receptor blockers (ARBs) required a lower level of care (OR 0.85, 95% CI 0.74-0.98). Furthermore, studies which combined these two drug groups in their analysis demonstrated an association with a lower mortality (OR 0.68, 95% CI 0.55-0.85).
 
 ConclusionsWe found minimal high quality or consistent evidence that any drug groups increase susceptibility, severity or mortality in COVID-19. Converse to initial hypotheses, we found some evidence that regular use of ACEIs and ARBs prior to infection may be effective in reducing the level of care required, such as requiring intensive care, in patients with COVID-19.",pharmacology and therapeutics,fuzzy,100,100
-medRxiv,10.1101/2021.09.13.21263487,2021-09-16,https://medrxiv.org/cgi/content/short/2021.09.13.21263487,SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population,Jia Wei; Koen B. Pouwels; Nicole Stoesser; Philippa C. Matthews; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John I Bell; John N Newton; Jeremy Farrar; Alison Howarth; Brian D. Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W. Crook; Tim E.A. Peto; A.Sarah Walker; David W. Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.09.13.21262360,2021-09-16,https://medrxiv.org/cgi/content/short/2021.09.13.21262360,Efficacy of two doses of COVID-19 vaccine against severe COVID-19 in those with risk conditions and residual risk to the clinically extremely vulnerable: the REACT-SCOT case-control study,Paul M McKeigue; David McAllister; Chris Robertson; Sharon J Hutchinson; Stuart McGurnaghan; Diane Stockton; Helen M Colhoun,University of Edinburgh; University of Glasgow; University of Strathclyde; Glasgow Caledonian University; University of Edinburgh; Public Health Scotland; University of Edinburgh,"ObjectivesTo determine whether COVID-19 efficacy varies with clinical risk category and to investigate risk factors for severe COVID-19 in those who have received two doses of vaccine.
 
 DesignMatched case-control study (REACT-SCOT).
@@ -2390,13 +2494,6 @@ QuestionDoes the association between BMI and COVID-19 mortality vary by ethnicit
 FindingsIn this study of 12.6 million adults, BMI was associated with COVID-19 in all ethnicities, but with stronger associations in ethnic minority populations such that the risk of COVID-19 mortality for a BMI of 40 kg/m2 in white ethnicities was observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in black, South Asian and other ethnicities, respectively.
 
 MeaningBMI is a stronger risk factor for COVID-19 mortality in ethnic minorities. Obesity management is therefore a priority in these populations.",epidemiology,fuzzy,100,100
-medRxiv,10.1101/2021.07.20.21260558,2021-07-22,https://medrxiv.org/cgi/content/short/2021.07.20.21260558,Intentions to participate in cervical and colorectal cancer screening during the COVID-19 pandemic: a mixed-methods study,Rebecca Wilson; Harriet Quinn-Scoggins; Yvonne Moriarty; Jacqueline Hughes; Mark Goddard; Rebecca Cannings-John; Victoria Whitelock; Katriina L Whitaker; Detelina Grozeva; Julia Townson; Kirstie Osborne; Stephanie Smits; Michael Robling; Julie Hepburn; Graham Moore; Ardiana Gjini; Kate Brain; Jo Waller,"Cardiff University; Cardiff University; Cardiff University; Cardiff University; Cardiff University; Cardiff University; Cancer Research UK; University of Surrey; Cardiff University; Cardiff University; Cancer Research UK; Cardiff University; Cardiff University; Public Involvement Community, Health and Care Research Wales; Cardiff University; Public Health Wales; Cardiff University; Kings College London","Worldwide, cancer screening faced significant disruption in 2020 due to the COVID-19 pandemic. If this has led to changes in public attitudes towards screening and reduced intention to participate, there is a risk of long-term adverse impact on cancer outcomes. In this study, we examined previous participation and future intentions to take part in cervical and colorectal cancer (CRC) screening following the first national lockdown in the UK.
-
-Overall, 7543 adults were recruited to a cross-sectional online survey in August-September 2020. Logistic regression analyses were used to identify correlates of strong screening intentions among 2,319 participants eligible for cervical screening and 2,502 eligible for home-based CRC screening. Qualitative interviews were conducted with a sub-sample of 30 participants. Verbatim transcripts were analysed thematically.
-
-Of those eligible, 74% of survey participants intended to attend cervical screening and 84% intended to complete home-based CRC screening when next invited. Thirty percent and 19% of the cervical and CRC samples respectively said they were less likely to attend a cancer screening appointment now than before the pandemic. Previous non-participation was the strongest predictor of low intentions for cervical (aOR 26.31, 95% CI: 17.61-39.30) and CRC (aOR 67.68, 95% CI: 33.91-135.06) screening. Interview participants expressed concerns about visiting healthcare settings but were keen to participate when screening programmes resumed.
-
-Intentions to participate in future screening were high and strongly associated with previous engagement in both programmes. As screening services recover, it will be important to monitor participation and to ensure people feel safe to attend.",oncology,fuzzy,100,98
 medRxiv,10.1101/2021.07.19.21260782,2021-07-22,https://medrxiv.org/cgi/content/short/2021.07.19.21260782,Does COVID-19 vaccination improve mental health? A difference-in-difference analysis of the UnderstandingCoronavirus in America study,Jonathan Koltai; Julia Raifman; Jacob Bor; Martin McKee; David Stuckler,University of New Hampshire; Boston University; Boston University; London School of Hygiene and Tropical Medicine; Bocconi University,"BackgroundMental health problems increased during the COVID-19 pandemic. Knowledge that one is less at risk after being vaccinated may alleviate distress, but this hypothesis remains unexplored. Here we test whether psychological distress declined in those vaccinated against COVID-19 in the US and whether changes in perceived risk mediated any association.
 
 MethodsA nationally-representative cohort of U.S. adults (N=5,792) in the Understanding America Study were interviewed every two weeks from March 2020 to June 2021 (28 waves). Difference-in-difference regression tested whether getting vaccinated reduced distress (PHQ-4 scores), with mediation analysis used to identify potential mechanisms, including perceived risks of infection, hospitalization, and death.
@@ -2556,6 +2653,25 @@ ResultsIn round 13 interim, we found 237 positives from 47,729 swabs giving a we
 
 DiscussionWe are entering a critical period with a number of important competing processes: continued vaccination rollout to the whole adult population in England, increased natural immunity through infection, reduced social mixing of children during school holidays, increased proportion of mixing occurring outdoors during summer, the intended full opening of hospitality and entertainment and cessation of mandated social distancing and mask wearing. Surveillance programmes are essential during this next phase of the epidemic to provide clear evidence to the government and the public on the levels and trends in prevalence of infections and their relationship to vaccine coverage, hospitalisations, deaths and Long COVID.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.07.02.21259897,2021-07-05,https://medrxiv.org/cgi/content/short/2021.07.02.21259897,Anti-spike antibody response to natural SARS-CoV-2 infection in the general population,Jia Wei; Philippa C Matthews; Nicole Stoesser; Thomas Maddox; Luke Lorenzi; Ruth Studley; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Emma Rourke; Alison Howarth; Brian D Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W Crook; Tim E.A. Peto; Koen B. Pouwels; A. Sarah Walker; David W Eyre,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as  non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2021.06.28.21259452,2021-07-03,https://medrxiv.org/cgi/content/short/2021.06.28.21259452,"Persistent symptoms following SARS-CoV-2 infection in a random community sample of 508,707 people",Matthew Whitaker; Joshua Elliott; Marc Chadeau-Hyam; Steven Riley; Ara Darzi; Graham Cooke; Helen Ward; Paul Elliott,"Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health","BackgroundLong COVID, describing the long-term sequelae after SARS-CoV-2 infection, remains a poorly defined syndrome. There is uncertainty about its predisposing factors and the extent of the resultant public health burden, with estimates of prevalence and duration varying widely.
+
+MethodsWithin rounds 3-5 of the REACT-2 study, 508,707 people in the community in England were asked about a prior history of COVID-19 and the presence and duration of 29 different symptoms. We used uni-and multivariable models to identify predictors of persistence of symptoms (12 weeks or more). We estimated the prevalence of symptom persistence at 12 weeks, and used unsupervised learning to cluster individuals by symptoms experienced.
+
+FindingsAmong the 508,707 participants, the weighted prevalence of self-reported COVID-19 was 19.2% (95% CI: 19.1,19.3). 37.7% of 76,155 symptomatic people post COVID-19 experienced at least one symptom, while 14.8% experienced three or more symptoms, lasting 12 weeks or more. This gives a weighted population prevalence of persistent symptoms of 5.75% (5.68, 5.81) for one and 2.22% (2.1, 2.26) for three or more symptoms. Almost a third of people (8,771/28,713 [30.5%]) with at least one symptom lasting 12 weeks or more reported having had severe COVID-19 symptoms (""significant effect on my daily life"") at the time of their illness, giving a weighted prevalence overall for this group of 1.72% (1.69,1.76). The prevalence of persistent symptoms was higher in women than men (OR: 1.51 [1.46,1.55]) and, conditional on reporting symptoms, risk of persistent symptoms increased linearly with age by 3.5 percentage points per decade of life. Obesity, smoking or vaping, hospitalisation, and deprivation were also associated with a higher probability of persistent symptoms, while Asian ethnicity was associated with a lower probability. Two stable clusters were identified based on symptoms that persisted for 12 weeks or more: in the largest cluster, tiredness predominated, while in the second there was a high prevalence of respiratory and related symptoms.
+
+InterpretationA substantial proportion of people with symptomatic COVID-19 go on to have persistent symptoms for 12 weeks or more, which is age-dependent. Clinicians need to be aware of the differing manifestations of Long COVID which may require tailored therapeutic approaches. Managing the long-term sequelae of SARS-CoV-2 infection in the population will remain a major challenge for health services in the next stage of the pandemic.
+
+FundingThe study was funded by the Department of Health and Social Care in England.
+
+Research in contextO_ST_ABSEvidence before this studyC_ST_ABSRecent systematic reviews have documented the wide range of symptoms and reported prevalence of persistent symptoms following COVID-19. A dynamic review of Long COVID studies (NIHR Evidence) in March 2021 summarised the literature on the prevalence of persistent symptoms after acute COVID19, and reported that most studies (14) were of hospitalised patients, with higher prevalence of persistent symptoms compared with two community-based studies. There was limited evidence from community studies beyond 12 weeks. Another systematic review reported a median of over 70% of people with symptoms lasting at least 60 days. A review of risk factors for Long COVID found consistent evidence for an increased risk amongst women and those with high body mass index (BMI) but inconsistent findings on the role of age and little evidence concerning risks among different socioeconomic or ethnic groups which are often not well captured in routine healthcare records. Long COVID is increasingly recognised as heterogenous, likely underpinned by differing biological mechanisms, but there is not yet consensus on defining subtypes of the condition.
+
+Added value of this studyThis community-based study of over half a million people was designed to be representative of the adult population of England. A random sample of adults ages 18 years and above registered with a GP were invited irrespective of previous access to services for COVID-19, providing an estimate of population prevalence that was representative of the whole population. The findings show substantial declines in symptom prevalence over the first 12 weeks following Covid-19, reported by nearly one fifth of respondents, of whom over a third remained symptomatic at 12 weeks and beyond, with little evidence for decline thereafter.
+
+Risk factors identified for persistent symptoms (12 weeks or more) suggestive of Long COVID confirm some previous findings - an increased risk in women, obese and overweight individuals and those hospitalised for COVID-19, with strong evidence for an increasing risk with age. Additional evidence was found for an increased risk in those with lower income, smoking or vaping and healthcare or care home workers. A lower risk was found in those of Asian ethnicity.
+
+Clustering identified two distinct groups of individuals with different symptom profiles at 12 weeks, highlighting the heterogeneity of clinical presentation. The smaller cluster had higher prevalence of respiratory and related symptoms, while for those in the larger cluster tiredness was the dominant symptom, with lower prevalence of organ-specific symptoms.
+
+Implications of available evidenceThere is a high prevalence of persistent symptoms beyond 12 weeks after acute COVID-19, with little evidence of decline thereafter. This highlights the needs for greater support for patients, both through specialised services and, for those from low-income settings, financial support. The understanding that there are distinct clusters of persistent symptoms, the most common of which is dominated by fatigue, is important for the recognition and clinical management of the condition outside of specialised services.",infectious diseases,fuzzy,96,100
 medRxiv,10.1101/2021.06.28.21259529,2021-07-01,https://medrxiv.org/cgi/content/short/2021.06.28.21259529,Global patterns of genetic variation and association with clinical phenotypes at genes involved in SARS-CoV-2 infection,Chao Zhang; Anurag Verma; Yuanqing Feng; Marcelo C. R. Melo; Michael McQuillan; Matthew Hansen; Anastasia Lucas; Joseph Park; Alessia Ranciaro; Simon Thompson; Meghan A. Rubel; Michael C. Campbell; William Beggs; JIBRIL HIRBO; Sununguko Wata Mpoloka; Gaonyadiwe George Mokone; - Regeneron Genetic Center; Thomas Nyambo; Dawit Wolde Meskel; Gurja Belay; Charles Fokunang; Alfred K. Njamnshi; Sabah A. Omar; Scott Williams; Daniel Rader; Marylyn D Ritchie; Cesar de la Fuente Nunez; Giorgio Sirugo; Sarah Tishkoff,"University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; Perelman School of Medicine at the University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Howard; University of Pennsylvania; Vanderbilt University Medical Center; University of Botswana, Biological Sciences, Gaborone, Botswana; University of Botswana, Faculty of Medicine, Gaborone, Botswana; ; Department of Biochemistry, Kampala International University in Tanzania, Dar es Salaam, Tanzania; Addis Ababa University Department of Microbial Cellular and Molecular Biology, Addis Ababa, Ethiopia; Addis Ababa University Department of Microbial Cellular and Molecular Biology, Addis Ababa, Ethiopia; Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, The University of Yaounde I, Yaounde, Cameroon; Department of Neurology, Central Hospital Yaounde; Brain Research Africa Initiative (BRAIN), Neuroscience Lab, Faculty of Medicine and Biomedical Sciences, The ; Center for Biotechnology Research and Development, Kenya Medical Research Institute, Nairobi, Kenya; Case Western Reserve University; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania; University of Pennsylvania","We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (ACE2, TMPRSS2, DPP4, and LY6E). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2, we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.",genetic and genomic medicine,fuzzy,100,100
 medRxiv,10.1101/2021.06.23.21259400,2021-06-30,https://medrxiv.org/cgi/content/short/2021.06.23.21259400,Temporal trends in primary care-recorded self-harm during and beyond the first year of the COVID-19 pandemic: time series analysis of electronic healthcare records for 2.8 million patients in the Greater Manchester Care Record,Sarah Steeg; Lana Bojanić; George Tilston; Richard Williams; David A Jenkins; Matthew J Carr; Niels Peek; Darren M Ashcroft; Nav Kapur; Jennifer Voorhees; Roger T Webb,University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester; University of Manchester,"BackgroundSurveillance of clinically treated self-harm episode frequency is an important component of suicide prevention in the dynamic context of COVID-19. Studies published to date have investigated the initial months following the onset of the pandemic, despite national and regional restrictions persisting to Summer 2021.
 
@@ -2679,15 +2795,6 @@ Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed
 Added value of this studyImmune interference and safety are always a concern when two vaccines are administered at the same time. This is the first study to demonstrate the safety and immunogenicity profile and clinical vaccine efficacy of a COVID-19 vaccine when co-administered with a seasonal influenza vaccine.
 
 Implications of all the available evidenceThis study provides much needed information to help guide national immunisation policy decision making on the critical issue of concomitant use of COVID-19 vaccines with influenza vaccines.",allergy and immunology,fuzzy,95,100
-medRxiv,10.1101/2021.06.08.21258533,2021-06-12,https://medrxiv.org/cgi/content/short/2021.06.08.21258533,The impact of co-circulating pathogens on SARS-CoV-2/COVID-19 surveillance. How concurrent epidemics may decrease true SARS-CoV-2 percent positivity.,Aleksandra Kovacevic; Rosalind M Eggo; Marc Baguelin; Matthieu Domenech de Cellès; Lulla Opatowski,Institut Pasteur; London School of Hygiene & Tropical Medicine; Imperial College London; Max Planck Institute for Infection Biology; Univ Versailles Saint Quentin / Institut Pasteur / Inserm,"BackgroundCirculation of non-SARS-CoV-2 respiratory viruses during the COVID-19 pandemic may alter quality of COVID-19 surveillance, with possible consequences for real-time analysis and delay in implementation of control measures. Here, we assess the impact of an increased circulation of other respiratory viruses on the monitoring of positivity rates of SARS-CoV-2 and interpretation of surveillance data.
-
-MethodsUsing a multi-pathogen Susceptible-Exposed-Infectious-Recovered (SEIR) transmission model formalizing co-circulation of SARS-CoV-2 and another respiratory we assess how an outbreak of secondary virus may inflate the number of SARS-CoV-2 tests and affect the interpretation of COVID-19 surveillance data. Using simulation, we assess to what extent the use of multiplex PCR tests on a subsample of symptomatic individuals can support correction of the observed SARS-CoV-2 percent positive during other virus outbreaks and improve surveillance quality.
-
-ResultsModel simulations demonstrated that a non-SARS-CoV-2 epidemic creates an artificial decrease in the observed percent positivity of SARS-CoV-2, with stronger effect during the growth phase, until the peak is reached. We estimate that performing one multiplex test for every 1,000 COVID-19 tests on symptomatic individuals could be sufficient to maintain surveillance of other respiratory viruses in the population and correct the observed SARS-CoV-2 percent positive.
-
-ConclusionsThis study highlights that co-circulating respiratory viruses can disrupt SARS-CoV-2 surveillance. Correction of the positivity rate can be achieved by using multiplex PCR, and a low number of samples is sufficient to avoid bias in SARS-CoV-2 surveillance.
-
-SummaryCOVID-19 surveillance indicators may be impacted by increased co-circulation of other respiratory viruses delaying control measure implementation. Continued surveillance through multiplex PCR testing in a subsample of the symptomatic population may play a role in fixing this problem.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2021.06.08.21258546,2021-06-12,https://medrxiv.org/cgi/content/short/2021.06.08.21258546,Inequalities in healthcare disruptions during the Covid-19 pandemic: Evidence from 12 UK population-based longitudinal studies,Jane Maddock; Sam Parsons; Giorgio Di Gessa; Michael J Green; Ellen J Thompson; Anna J Stevenson; Alex S.F. Kwong; Eoin McElroy; Gillian Santorelli; Richard J Silverwood; Gabriella Captur; Nish Chaturvedi; Claire J Steves; Andrew Steptoe; Praveetha Patalay; George B Ploubidis; Srinivasa Vittal Katikireddi,University College London; University College London; University College London; University of Glasgow; King's College London; University of Edinburgh; University of Bristol; University of Leicester; Bradford Institute for Health Research; University College London; University College London; University College London; King's College London; University College London; University College London; University College London; University of Glasgow,"BackgroundHealth systems worldwide have faced major disruptions due to COVID-19 which could exacerbate health inequalities. The UK National Health Service (NHS) provides free healthcare and prioritises equity of delivery, but the pandemic may be hindering the achievement of these goals. We investigated associations between multiple social characteristics (sex, age, occupational social class, education and ethnicity) and self-reported healthcare disruptions in over 65,000 participants across twelve UK longitudinal studies.
 
 MethodsParticipants reported disruptions from March 2020 up to late January 2021. Associations between social characteristics and three types of self-reported healthcare disruption (medication access, procedures, appointments) and a composite of any of these were assessed in logistic regression models, adjusting for age, sex and ethnicity where relevant. Random-effects meta-analysis was conducted to obtain pooled estimates.
@@ -2794,15 +2901,6 @@ MethodsVirus Watch is a large community cohort with prospective daily recording
 FindingsWe included results from 8213 swabbed illnesses, 944 of which tested positive for SARS-CoV-2. All symptoms were more common in test positive than test negative illnesses and symptoms were also more severe and of longer duration. Common symptoms such as cough, headache, fatigue, muscle aches, and loss of appetite occurred early in the course of illness but were also very common in test-negative illnesses. In contrast, high temperature and loss of or altered sense of smell or taste were less frequently identified in swab positive illnesses but were markedly more common than in swab negative illnesses. The current UK definition had a sensitivity and specificity of 81% and 47% respectively for symptomatic COVID-19 compared to 93% and 26% for the broader definition. On average, cases met the broader case definition 0.3 days earlier than the current definition. 1.7-fold more illnesses met the broader definition than the current case definition.
 
 InterpretationCOVID-19 is difficult to distinguish from other respiratory infections and common ailments on the basis of symptoms. Broadening the list of symptoms used to encourage engagement with TTI could moderately increase the number of infections identified and shorten delays to isolation, but with a large increase in the number of tests needed and the number of unwell individuals and contacts who are advised to self-isolate whilst awaiting results, and subsequently test negative for SARS-CoV-2.",epidemiology,fuzzy,100,100
-medRxiv,10.1101/2021.05.18.21257267,2021-05-18,https://medrxiv.org/cgi/content/short/2021.05.18.21257267,"Colchicine in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial",Peter W Horby; Mark Campbell; Enti Spata; Jonathan R Emberson; Natalie Staplin; Guilherme Pessoa-Amorim; Leon Peto; Martin Wiselka; Laura Wiffen; Simon Tiberi; Ben Caplin; Caroline Wroe; Christopher Green; Paul Hine; Benjamin Prudon; Tina George; Andrew Wight; J Kenneth Baillie; Buddha Basnyat; Maya H Buch; Lucy C Chappell; Jeremy N Day; Saul N Faust; Raph L Hamers; Thomas Jaki; Edmund Juszczak; Katie Jeffery; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; Marion Mafham; Richard Haynes; Martin J Landray,"Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom and International Severe Acute Res; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and Oxford University Hospitals NHS Foundation Trust, Oxford, United King; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom and Nuffield Department of Populat; Department of Infectious Diseases, University Hospital Leicester, Leicester, United Kingdom; Portsmouth Hospitals University NHS Foundation Trust, Portsmouth, United Kingdom; Department of Infection, Barts Health NHS Trust, London, United Kingdom; Department of Renal Medicine, University College London, London, United Kingdom and Royal Free London NHS Trust, London, United Kingdom; James Cook University Hospital, Middlesbrough, United Kingdom; University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom; Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom; North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom; Basildon and Thurrock Hospitals NHS Foundation Trust, Basildon, United Kingdom; Wirral University Teaching Hospital NHS Foundation Trust, Birkenhead, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Oxford University Clinical Research Unit -Nepal, Patan Academy of Health Sciences, Kathmandu, Nepal; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; School of Life Course Sciences, King?s College London, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam and Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Univer; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia and Faculty of Medicine, University of Indonesia, Jakarta, Indonesia and Centre for Tropical Medicine ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom and MRC Biostatistics Unit, University of Cambridge, Cambridge, United; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom and Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Notting; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom; Intensive Care National Audit & Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam and Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Univer; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and Oxford University Hospitals NHS Foundation Trust, Oxford, United King; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un","BackgroundColchicine has been proposed as a treatment for COVID-19 on the basis of its anti-inflammatory actions.
-
-MethodsIn this randomised, controlled, open-label trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19. Eligible and consenting adults were randomly allocated in a 1:1 ratio to either usual standard of care alone or usual standard of care plus colchicine twice daily for 10 days or until discharge (or one of the other treatment arms) using web-based simple (unstratified) randomisation with allocation concealment. The primary outcome was 28-day mortality. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).
-
-FindingsBetween 27 November 2020 and 4 March 2021, 5610 patients were randomly allocated to receive colchicine and 5730 patients to receive usual care alone. Overall, 1173 (21%) patients allocated to colchicine and 1190 (21%) patients allocated to usual care died within 28 days (rate ratio 1.01; 95% confidence interval [CI] 0.93-1.10; p=0.77). Consistent results were seen in all pre-specified subgroups of patients. There was no significant difference in duration of hospitalisation (median 10 days vs. 10 days) or the proportion of patients discharged from hospital alive within 28 days (70% vs. 70%; rate ratio 0.98; 95% CI 0.94-1.03; p=0.44). Among those not on invasive mechanical ventilation at baseline, there was no significant difference in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (25% vs. 25%; risk ratio 1.02; 95% CI 0.96-1.09; p=0.47).
-
-InterpretationIn adults hospitalised with COVID-19, colchicine was not associated with reductions in 28-day mortality, duration of hospital stay, or risk of progressing to invasive mechanical ventilation or death.
-
-FundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056). Wellcome Trust (Grant Ref: 222406/Z/20/Z) through the COVID-19 Therapeutics Accelerator.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.05.17.21256818,2021-05-18,https://medrxiv.org/cgi/content/short/2021.05.17.21256818,Local prevalence of transmissible SARS-CoV-2 infection : an integrative causal model for debiasing fine-scale targeted testing data,George Nicholson; Brieuc CL Lehmann; Tullia Padellini; Koen B Pouwels; Radka Jersakova; James Lomax; Ruairidh E King; Ann-Marie Mallon; Peter J Diggle; Sylvia Richardson; Marta Blangiardo; Chris Holmes,University of Oxford; University of Oxford; Imperial College London; University of Oxford; The Alan Turing Institute; The Alan Turing Institute; MRC Harwell Institute; MRC Harwell Institute; Lancaster University; MRC Biostatistics Unit; Imperial College London; University of Oxford,"Targeted surveillance testing schemes for SARS-CoV-2 focus on certain subsets of the population, such as individuals experiencing one or more of a prescribed list of symptoms. These schemes have routinely been used to monitor the spread of SARS-CoV-2 in countries across the world. The number of positive tests in a given region can provide local insights into important epidemiological parameters, such as prevalence and effective reproduction number. Moreover, targeted testing data has been used inform the deployment of localised non-pharmaceutical interventions. However, surveillance schemes typically suffer from ascertainment bias; the individuals who are tested are not necessarily representative of the wider population of interest. Here, we show that data from randomised testing schemes, such as the REACT study in the UK, can be used to debias fine-scale targeted testing data in order to provide accurate localised estimates of the number of infectious individuals. We develop a novel, integrative causal framework that explicitly models the process underlying the selection of individuals for targeted testing. The output from our model can readily be incorporated into longitudinal analyses to provide local estimates of the reproduction number. We apply our model to characterise the size of the infectious population in England between June 2020 and January 2021. Our local estimates of the effective reproduction number are predictive of future changes in positive case numbers. We also capture local increases in both prevalence and effective reproductive number in the South East from November 2020 to December 2020, reflecting the spread of the Kent variant. Our results illustrate the complementary roles of randomised and targeted testing schemes. Preparations for future epidemics should ensure the rapid deployment of both types of schemes to accurately monitor the spread of emerging and ongoing infectious diseases.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.05.15.21257017,2021-05-17,https://medrxiv.org/cgi/content/short/2021.05.15.21257017,Extended interval BNT162b2 vaccination enhances peak antibody generation in older people,Helen M Parry; Rachel Bruton; Christine Stephens; Kevin Brown; Gayatri Amirthalingam; Bassam Hallis; Ashley Otter; Jianmin Zuo; Paul Moss,"University of Birmingham, Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham. B15 2TT, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham. B15 2TT, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham. B15 2TT, UK; National infection Service, Public Health England, Colindale, London NW9 5EQ, UK; National infection Service, Public Health England, Colindale, London NW9 5EQ, UK; National infection Service, Public Health England,  Porton Down, Salisbury, SP4 OJG, UK; National infection Service, Public Health England,  Porton Down, Salisbury, SP4 OJG, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham. B15 2TT, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham. B15 2TT, UK","ObjectivesTo assess the relative immunogenicity of standard or extended interval BNT162b2 vaccination.
 
@@ -2821,6 +2919,19 @@ ConclusionPeak antibody responses after the second BNT162b2 vaccine are markedly
 What is already known on this topicThe BNT162b2 vaccine is highly effective against Covid-19 infection and was delivered with a 3-week time interval in registration studies. However, this interval has been extended in many countries in order to extend population coverage with a single vaccine. It is not known how immune responses after the second dose are influenced by delaying the second vaccine.
 
 What this study addsWe provide the first assessment of immune responses in the first 14 weeks after standard or extended interval BNT162b2 vaccination and show that delaying the second dose acts to strongly boost the peak antibody response in older people. The extended interval vaccination may offer a longer period of clinical protection. This information will be of value in optimizing vaccine regimens and help guide guide vaccination policies.",infectious diseases,fuzzy,100,92
+medRxiv,10.1101/2021.05.12.21257123,2021-05-17,https://medrxiv.org/cgi/content/short/2021.05.12.21257123,Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults,Vahe Nafilyan; Piotr Pawelek; Daniel Ayoubkhani; Sarah Rhodes; Lucy Pembrey; Melissa Matz; Michel P Coleman; Claudia Allemani; Ben Windsor-Shellard; Martie van Tongeren; Neil Pearce,"Office for National Statistics; Office for National Statistics; Office for National Statistics; School of Health Sciences, University of Manchester; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Office for National Statistics; School of Health Sciences, University of Manchester; London School of Hygiene and Tropical Medicine","ObjectiveTo estimate occupational differences in COVID-19 mortality, and test whether these are confounded by factors, such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation or pre-pandemic health.
+
+DesignRetrospective cohort study
+
+SettingPeople living in private households England
+
+Participants14,295,900 people aged 40-64 years (mean age 52 years, 51% female) who were alive on 24 January 2020, living in private households in England in 2019, were employed in 2011, and completed the 2011 census.
+
+Main outcome measuresCOVID-19 related death, assessed between 24 January 2020 and 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk (ASMR) stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding (region, ethnicity, education), as well as non-workplace factors that are related to occupation.
+
+ResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three-fold or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating non-workplace factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62-5.84] to 1.47 [1.14-1.89] after adjustment. More generally, the overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.
+
+ConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2021.05.13.21257144,2021-05-17,https://medrxiv.org/cgi/content/short/2021.05.13.21257144,REACT-1 round 11 report: low prevalence of SARS-CoV-2 infection in the community prior to the third step of the English roadmap out of lockdown,Steven Riley; David J Haw; Caroline E Walters; Howei Wang; Oliver Eales; Kylie E C Ainslie; Christina Atchison; Claudio Fronterre; Peter J Diggle; Andrew J Page; Alexander J Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Justin O'Grady; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; Imperial College London; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; ; Imperial College London; University of Oxford; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London","BackgroundNational epidemic dynamics of SARS-CoV-2 infections are being driven by: the degree of recent indoor mixing (both social and workplace), vaccine coverage, intrinsic properties of the circulating lineages, and prior history of infection (via natural immunity). In England, infections, hospitalisations and deaths fell during the first two steps of the ""roadmap"" for exiting the third national lockdown. The third step of the roadmap in England takes place on 17 May 2021.
 
 MethodsWe report the most recent findings on community infections from the REal-time Assessment of Community Transmission-1 (REACT-1) study in which a swab is obtained from a representative cross-sectional sample of the population in England and tested using PCR. Round 11 of REACT-1 commenced self-administered swab-collection on 15 April 2021 and completed collections on 3 May 2021. We compare the results of REACT-1 round 11 to round 10, in which swabs were collected from 11 to 30 March 2021.
@@ -2864,6 +2975,17 @@ MethodsAdults aged [&ge;]18 years from households enrolled in Virus Watch, a pro
 Results8,517 vaccinated participants (median age 65 years [IQR: 58, 71]), contributed 13,232 samples (8,115 following ChAdOx1, 5,008 following BNT162b2). Seropositivity to Spike was 96.42% (95%CI 96, 96.79) at 28-34 days following a single dose, reaching 99.08% (97.8, 99.62) at 7-14 days after a second dose. Seropositivity rates, and Spike-antibody levels rose more quickly following the first dose of BNT162b2, however, were equivalent for both vaccines by 4 and 8 weeks, respectively. There was evidence of lower S-antibody levels with increasing age (p=0.0001). In partially vaccinated 65-79 year-olds, lower S-antibody levels were observed in men (25.9 vs 42.3 U/ml, p<0.0001), those with a chronic condition (33.0 vs 41.2 U/ml, p<0.0001), diabetes (22.32 vs 36.01 U/ml, p<0.0001), cardiovascular disease (32.1 vs 36.7 U/ml, p=0.0002), or history of cancer (30.1 vs 35.7 U/ml, p=0.0001), particularly those with haematological rather than solid organ cancer (7.48 vs 31.68 U/ml, p<0.0001), and those currently on immunosuppressive therapy (21.7 vs 35.6 U/ml, p<0.0001). Following a second dose, high S-antibody titres ([&ge;]250U/ml) were observed for nearly all individuals.
 
 InterpretationA single dose of either BNT162b2 or ChAdOx1 leads to high Spike seropositivity rates in SARS-CoV-2-naive individuals. However, observed disparities in antibody levels after the first dose by vaccine type, age, and comorbidities highlight the importance of ongoing non-pharmaceutical preventative measures such as social distancing, for partially vaccinated adults, particularly those who are older and more clinically vulnerable.",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2021.05.06.21256757,2021-05-14,https://medrxiv.org/cgi/content/short/2021.05.06.21256757,COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study,Yiqun Chen; Timothy Aldridge; - UK COVID-19 National Core Studies Consortium; Claire F Ferraro; Fu-Meng Khaw,"Health and Safety Executive, UK; Health and Safety Executive, UK; ; National Infection Service, Public Health England, UK; Public Health England, UK","BackgroundA large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic. However, information on the rate of outbreak occurrences which helps to identify the type of workplaces that are more likely to experience an outbreak, or infection attack rates which estimates the potential extent of the virus transmission in an outbreak, has not yet been available to inform intervention strategies to limit transmission.
+
+ObjectivesTo link datasets on workplace settings and COVID-19 workplace outbreaks in England in order to: identify the geographical areas and workplace sectors with a high rate of outbreaks; and compare infection attack rates by workplace size and sector.
+
+MethodsWe analysed Public Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, covering the time period of 18 May - 12 October 2020. The workplaces analysed excluded care homes, hospitals and educational settings. We calculated the workplace outbreak rates by nine English regions, 151 Upper Tier Local Authorities (UTLAs) and twelve industrial sectors, using National Population Database (NPD) data extracted in May 2019 on the total number of the relevant workplaces as the denominator. We also calculated the infection attack rates by enterprise size (small, medium, large) and industrial sector, using PHE Situations of Interest (SOI) data on the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator, and using NPD data on the number employed in that workplace as the denominator.
+
+ResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone data, of which 1,305 were available for estimation of outbreak rates. The average outbreak rate was 66 per 100,000 workplaces. Of the nine geographical regions in England, the North West had the highest workplace outbreak rate (155/100,000 workplaces), based on 351 outbreaks. Of the UTLAs, the highest workplace outbreak rate was Blackburn with Darwen (387/100,000 workplaces). The industrial sector with the highest workplace outbreak rate was manufacturers and packers of food (1,672/100,000), based on 117 outbreaks: this was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.
+
+In total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%).
+
+ConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2021.05.08.21256867,2021-05-14,https://medrxiv.org/cgi/content/short/2021.05.08.21256867,SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples,Oliver Eales; Andrew Page; Sonja N. Tang; Caroline E. Walters; Haowei Wang; David Haw; Alexander J. Trotter; Thanh Le Viet; Ebenezer Foster-Nyarko; Sophie Prosolek; Christina Atchinson; Deborah Ashby; Graham Cooke; Wendy Barclay; Christl A Donnelly; Justin O'Grady; Erik Volz; - The COVID-19 Genomics UK (COG-UK) Consortium; Ara Darzi; Helen Ward; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; ; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.05.11.21257040,2021-05-13,https://medrxiv.org/cgi/content/short/2021.05.11.21257040,Trajectories of child emotional and behavioural difficulties before and during the COVID-19 pandemic in a longitudinal UK cohort,Elise Paul; Daphne Kounali; Alex Siu Fung Kwong; Daniel Smith; Ilaria Costantini; Deborah A Lawlor; Kapil Sayal; Helen Bould; Nicholas J Timpson; Kate Northstone; Melanie Lewcock; Kate J Tilling; Rebecca Pearson,University College London; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Nottingham; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol,"ImportanceCOVID-19 public health mitigation measures are likely to have detrimental effects on emotional and behavioural problems in children. However, longitudinal studies with pre-pandemic data are scarce.
 
@@ -2900,9 +3022,6 @@ MethodsThe Virus Watch study is a household community cohort of acute respirator
 ResultsThe proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (6.6%; 73/1,102) and lowest in the under-occupied group (2.9%; 682/23,219). In a mixed effects logistic regression model that included age, sex, ethnicity, household income and geographical region, we found strong evidence of an increased odds of having a positive PCR SARS-CoV-2 antigen result (Odds Ratio 3.72; 95% CI: 1.92, 7.13; p-value < 0.001) and increased odds of having a positive SARS-CoV-2 antibody result in individuals living in overcrowded houses (2.96; 95% CI: 1.13, 7.74; p-value =0.027) compared to people living in under-occupied houses. The proportion of variation at the household level was 9.91% and 9.97% in the PCR and antibody models respectively.
 
 DiscussionPublic health interventions to prevent and stop the spread of SARS-CoV-2 should consider the much greater risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission. There is an urgent need to better recognise housing as a leading determinant of health in the context of a pandemic and beyond.",infectious diseases,fuzzy,100,100
-medRxiv,10.1101/2021.05.05.21256668,2021-05-09,https://medrxiv.org/cgi/content/short/2021.05.05.21256668,COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland,Sofia de la Fuente Garcia; Fasih Haider; Saturnino Luz,The University of Edinburgh; The University of Edinburgh; The University of Edinburgh,"The COVID-19 pandemic has led to unprecedented restrictions in peoples lifestyle which have affected their psychological wellbeing. In this context, this paper investigates the use of social signal processing techniques for remote assessment of emotions. It presents a machine learning method for affect recognition applied to recordings taken during the COVID-19 winter lockdown in Scotland (UK). This method is exclusively based on acoustic features extracted from voice recordings collected through home and mobile devices (i.e. phones, tablets), thus providing insight into the feasibility of monitoring peoples psychological wellbeing remotely, automatically and at scale. The proposed model is able to predict affect with a concordance correlation coefficient of 0.4230 (using Random Forest) and 0.3354 (using Decision Trees) for arousal and valence respectively.
-
-Clinical relevanceIn 2018/2019, 12% and 14% of Scottish adults reported depression and anxiety symptoms. Remote emotion recognition through home devices would support the detection of these difficulties, which are often underdiagnosed and, if untreated, may lead to temporal or chronic disability.",health informatics,fuzzy,100,100
 medRxiv,10.1101/2021.05.05.21256649,2021-05-08,https://medrxiv.org/cgi/content/short/2021.05.05.21256649,Illness duration and symptom profile in a large cohort of symptomatic UK school-aged children tested for SARS-CoV-2,Erika Molteni; Carole Helene Sudre; Liane Santos Canas; Sunil S Bhopal; Robert C Hughes; Michela S Antonelli; Benjamin Murray; Kerstin Klaser; Eric Kerfoot; Liyuan Chen; Jie Deng; Christina Hu; Somesh Selvachandran; Kenneth Read; Joan Capdevila Pujol; Alexander Hammers; Timothy Spector; Sebastien Ourselin; Claire J Steves; Marc Modat; Michael Absoud; Emma L Duncan,King's College London; University College London; King's College London; King's College London; Newcastle University; London School of Hygiene & Tropical Medicine; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; ZOE Global Ltd; Zoe Global Ltd; ZOE Global Ltd; Zoe Global Ltd; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; Evelina Hospital London; King's College London,"BackgroundIn children, SARS-CoV-2 is usually asymptomatic or causes a mild illness of short duration. Persistent illness has been reported; however, its prevalence and characteristics are unclear. We aimed to determine illness duration and characteristics in symptomatic UK school-aged children tested for SARS-CoV-2 using data from the COVID Symptom Study, the largest UK citizen participatory epidemiological study to date.
 
 MethodsData from 258,790 children aged 5-17 years were reported by an adult proxy between 24 March 2020 and 22 February 2021. Illness duration and symptom profiles were analysed for all children testing positive for SARS-CoV-2 for whom illness duration could be determined, considered overall and within younger (5-11 years) and older (12-17 years) groups. Data from symptomatic children testing negative for SARS-CoV-2, matched 1:1 for age, gender, and week of testing, were also assessed.
@@ -2952,13 +3071,6 @@ What this study addsO_LIIn 70,464 people with atrial fibrillation, at the thresh
 C_LIO_LIThis might be explained by OACs preventing severe COVID-19 outcomes, or more cautious behaviours and environmental factors reducing the risk of SARS-CoV-2 infection in those taking OACs.
 C_LIO_LIIn 372,746 people with non-valvular atrial fibrillation, there was no evidence of a higher risk of severe COVID-19 outcomes associated with warfarin compared with DOACs.
 C_LI",epidemiology,fuzzy,100,100
-medRxiv,10.1101/2021.04.26.21255732,2021-04-28,https://medrxiv.org/cgi/content/short/2021.04.26.21255732,Deprivation and Exposure to Public Activities during the COVID-19 Pandemic in England and Wales,Sarah Beale; Isobel Braithwaite; Annalan MD Navaratnam; Pia Hardelid; Alison Rodger; Anna Aryee; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Robert W Aldridge; Andrew C Hayward; - Virus Watch Collaborative,"University College London; University College London; University College London; University College London; University College London; Royal Free London NHS Foundation Trust,; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; ","BackgroundDifferential exposure to public activities and non-household contacts may contribute to stark deprivation-related inequalities in SARS-CoV-2 infection and outcomes, but has not been directly investigated. We set out to investigate whether participants in Virus Watch - a large community cohort study based in England and Wales - reported different levels of exposure to public activities and non-household contacts during the Autumn-Winter phase of the COVID-19 pandemic according to postcode-level socioeconomic deprivation.
-
-MethodsParticipants (n=20120-25228 across surveys) reported their daily activities during three weekly periods in late November 2020, late December 2020, and mid-February 2021. Deprivation was quantified based on participants postcode of residence using English or Welsh Indices of Multiple Deprivation quintiles. We used Poisson mixed effect models with robust standard errors to estimate the relationship between deprivation and risk of exposure to public activities during each survey period.
-
-ResultsRelative to participants in the least deprived areas, participants in the most deprived areas persistently exhibited elevated risk of exposure to vehicle sharing (aRR range across time points 1.73-8.52), public transport (aRR 3.13-5.73), work or education outside of the household (aRR 1.09-1.21), essential shops (aRR 1.09-1.13) and non-household contacts (aRR 1.15-1.19) across multiple survey periods.
-
-ConclusionDifferential exposure to essential public activities in deprived communities is likely to contribute to inequalities in infection risk and outcomes during the COVID-19 pandemic. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2021.04.24.21255968,2021-04-27,https://medrxiv.org/cgi/content/short/2021.04.24.21255968,MORTALITY OF CARE HOME RESIDENTS AND COMMUNITY-DWELLING CONTROLS DURING THE COVID-19 PANDEMIC IN 2020: MATCHED COHORT STUDY,Martin C Gulliford; A Toby Prevost; Andrew Clegg; Emma C Rezel-Potts,King's College London; King's College London; University of Leeds; King's College London,"ObjectiveTo estimate mortality of care home (CH) residents, and matched community-dwelling controls, during the Covid-19 pandemic from primary care electronic health records.
 
 DesignMatched cohort study
@@ -3128,6 +3240,13 @@ FindingsWe recorded 446 incident cases of COVID-19 in 15,227 participants (2.9%)
 InterpretationAfter rigorous adjustment for factors influencing exposure to SARS-CoV-2, Asian/Asian British ethnicity and raised BMI were associated with increased risk of developing COVID-19, while atopic disease was associated with decreased risk.
 
 FundingBarts Charity, Health Data Research UK",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2021.03.21.21254061,2021-03-26,https://medrxiv.org/cgi/content/short/2021.03.21.21254061,Quantitative SARS-CoV-2 anti-spike responses to Pfizer-BioNTech and Oxford-AstraZeneca vaccines by previous infection status,David W Eyre; Sheila F Lumley; Jia Wei; Stuart Cox; Tim James; Anita Justice; Gerald Jesuthasan; Alison Howarth; Stephanie B Hatch; Brian D Marsden; E Yvonne Jones; David I Stuart; Daniel Ebner; Sarah Hoosdally; Derrick Crook; Tim EA Peto; Timothy M Walker; Nicole EA Stoesser; Philippa C Matthews; Koen B Pouwels; A Sarah Walker; Katie Jeffery,University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals,"ObjectivesWe investigate determinants of SARS-CoV-2 anti-spike IgG responses in healthcare workers (HCWs) following one or two doses of Pfizer-BioNTech or Oxford-AstraZeneca vaccines.
+
+MethodsHCWs participating in regular SARS-CoV-2 PCR and antibody testing were invited for serological testing prior to first and second vaccination, and 4 weeks post-vaccination if receiving a 12-week dosing interval. Quantitative post-vaccination anti-spike antibody responses were measured using the Abbott SARS-CoV-2 IgG II Quant assay (detection threshold: [&ge;]50 AU/ml). We used multivariable logistic regression to identify predictors of seropositivity and generalised additive models to track antibody responses over time.
+
+ResultsVaccine uptake was 80%, but less in lower-paid roles and Black, south Asian and minority ethnic groups. 3570/3610(98.9%) HCWs were seropositive >14 days post-first vaccination and prior to second vaccination, 2706/2720(99.5%) after Pfizer-BioNTech and 864/890(97.1%) following Oxford-AstraZeneca vaccines. Previously infected and younger HCWs were more likely to test seropositive post-first vaccination, with no evidence of differences by sex or ethnicity. All 470 HCWs tested >14 days after second vaccine were seropositive. Quantitative antibody responses were higher after previous infection: median(IQR) >21 days post-first Pfizer-BioNTech 14,604(7644-22,291) AU/ml vs. 1028(564-1985) AU/ml without prior infection (p<0.001). Oxford-AstraZeneca vaccine recipients had lower readings post-first dose compared to Pfizer-BioNTech, with and without previous infection, 10,095(5354-17,096) and 435(203-962) AU/ml respectively (both p<0.001 vs. Pfizer-BioNTech). Antibody responses post-second vaccination were similar to those after prior infection and one vaccine dose.
+
+ConclusionsVaccination leads to detectable anti-spike antibodies in nearly all adult HCWs. Whether differences in response impact vaccine efficacy needs further study.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.03.21.21253968,2021-03-26,https://medrxiv.org/cgi/content/short/2021.03.21.21253968,Characteristics of Long Covid: findings from a social media surve,Nida Ziauddeen; Deepti Gurdasani; Margaret E O'Hara; Claire Hastie; Paul Roderick; Guiqing Yao; Nisreen A Alwan,"University of Southampton; Queen Mary University of London; Patient contributor, Long Covid Support: www.longcovid.org; Patient contributor, Long Covid Support: www.longcovid.org; University of Southampton; University of Leicester; University of Southampton","Many people are not recovering for months after being infected with SARS-CoV-2. Long Covid has emerged as a major public health concern that needs defining, quantifying, and describing. We aimed to explore the initial and ongoing symptoms of Long Covid following SARS-CoV-2 infection and describe its impact on daily life in people who were not admitted to hospital during the first two weeks of the illness. We co-produced a survey with people living with Long Covid. We collected the data through an online survey using convenience non-probability sampling, with the survey posted both specifically on Long Covid support groups and generally on social media. The criteria for inclusion were adults with lab-confirmed (PCR or antibody) or suspected COVID-19 managed in the community (non-hospitalised) in the first two weeks of illness. We used agglomerative hierarchical clustering to identify specific symptom clusters, and their demographic and functional correlates.
 
 We analysed data from 2550 participants with a median duration of illness of 7.7 months (interquartile range (IQR) 7.4-8.0). The mean age was 46.5 years (standard deviation 11 years) with 82.8% females and 79.9% of participants based in the UK. 89.5% described their health as good, very good or excellent before COVID-19. The most common initial symptoms that persisted were exhaustion, chest pressure/tightness, shortness of breath and headache. Cough, fever, and chills were common initial symptoms that became less prevalent later in the illness, whereas cognitive dysfunction and palpitations became more prevalent later in the illness. 26.5% reported lab-confirmation of infection. The biggest difference in ongoing symptoms between those who reported testing positive and those who did not was loss of smell/taste. Ongoing symptoms affected at least 3 organ systems in 83.5% of participants.
@@ -3285,7 +3404,6 @@ Added value of this studyThrough prospective collection of symptom and test repo
 Implications of all the available evidenceDespite the UK having a simple set of symptom-based testing criteria, with tests made freely available through nationalised healthcare, a quarter of individuals with qualifying symptoms do not get tested. Our findings suggest testing uptake may be limited by individuals not acting on mild or transient symptoms, not recognising the testing criteria, and not knowing where to get tested. Improved messaging may help address this testing gap, with opportunities to target individuals of older age or fewer years of education. Messaging may prove even more valuable in countries with more fragmented testing infrastructure or more nuanced testing criteria, where knowledge barriers are likely to be greater.",public and global health,fuzzy,94,100
 bioRxiv,10.1101/2021.03.14.435295,2021-03-16,https://biorxiv.org/cgi/content/short/2021.03.14.435295,3D genomic capture of regulatory immuno-genetic profiles in COVID-19 patients for prognosis of severe COVID disease outcome,Ewan Hunter; Christina Koutsothanasi; Adam Wilson; Francisco Coroado Santos; Matthew Salter; Ryan Powell; Ann Dring; Paulina Brajer; Benedict Egan; Jurjen Westra; Aroul Ramadass; William Messner; Amanda Brunton; Zoe Lyski; Rama Vancheeswaran; Andrew Barlow; Dmitri Pchejetski; Alexandre Akoulitchev,"Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oxford BioDynamics Plc, Oxford UK; Oregon Health & Science University, Portland, OR; Oregon Health & Science University, Portland, OR; Oregon Health & Science University, Portland, OR; West Hertfordshire NHS Trust, Watford, UK; West Hertfordshire NHS Trust, Watford, UK; Norwich Medical School, University of East Anglia; Oxford BioDynamics Plc, Oxford UK","Human infection with the SARS-CoV-2 virus leads to coronavirus disease (COVID-19). A striking characteristic of COVID-19 infection in humans is the highly variable host response and the diverse clinical outcomes, ranging from clinically asymptomatic to severe immune reactions leading to hospitalization and death. Here we used a 3D genomic approach to analyse blood samples at the time of COVID diagnosis, from a global cohort of 80 COVID-19 patients, with different degrees of clinical disease outcomes. Using 3D whole genome EpiSwitch(R) arrays to generate over 1 million data points per patient, we identified a distinct and measurable set of differences in genomic organization at immune-related loci that demonstrated prognostic power at baseline to stratify patients with mild forms of illness and those with severe forms that required hospitalization and intensive care unit (ICU) support. Further analysis revealed both well established and new COVID-related dysregulated pathways and loci, including innate and adaptive immunity; ACE2; olfactory, G{beta}{psi}, Ca2+ and nitric oxide (NO) signalling; prostaglandin E2 (PGE2), the acute inflammatory cytokine CCL3, and the T-cell derived chemotactic cytokine CCL5. We identified potential therapeutic agents for mitigation of severe disease outcome, with several already being tested independently, including mTOR inhibitors (rapamycin and tacrolimus) and general immunosuppressants (dexamethasone and hydrocortisone). Machine learning algorithms based on established EpiSwitch(R) methodology further identified a subset of 3D genomic changes that could be used as prognostic molecular biomarker leads for the development of a COVID-19 disease severity test.",biochemistry,fuzzy,92,100
 medRxiv,10.1101/2021.03.09.21253012,2021-03-15,https://medrxiv.org/cgi/content/short/2021.03.09.21253012,The local and systemic response to SARS-CoV-2 infection in children and adults,Masahiro Yoshida; Kaylee B Worlock; Ni Huang; Rik GH Lindeboom; Colin R Butler; Natsuhiko Kumasaka; Cecilia Dominguez Conde; Lira Mamanova; Liam Bolt; Laura Richardson; Krzysztof Polanski; Elo Madissoon; Josephine L Barnes; Jessica Allen-Hyttinen; Eliz Kilich; Brendan C Jones; Angus de Wilton; Anna Wilbrey-Clark; Waradon Sungnak; Jan Patrick Prett; Elena Prigmore; Henry Yung; Puja Mehta; Aarash Saleh; Anita Saigal; Vivian Chu; Jonathan M Cohen; Clare Cane; Aikaterini Iordanidou; Soichi Shibuya; Ann-Kathrin Reuschl; A. Christine Argento; Richard G Wunderink; Sean B Smith; Taylor A Poor; Catherine A Gao; Jane E Dematte; - NU SCRIPT Study Investigators; Gary Reynolds; Muzlifah Haniffa; Georgina S Bowyer; Matthew Coates; Menna R Clatworthy; Fernando J Calero-Nieto; Berthold Gottgens; Neil J Sebire; Clare Jolly; Paolo de Coppi; Claire M Smith; Alexander V Misharin; Sam M Janes; Sarah A Teichmann; Marko Z Nikolic; Kerstin B Meyer,"UCL Respiratory, Division of Medicine, University College London, London, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Great Ormond Street Institute of Child Health, London, UK; Wellcome Trust Sanger Institute; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; University College London Hospitals NHS Foundation Trust, London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; University College London Hospital Trust; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute; Wellcome Sanger Institute, Cambridge, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; Royal Free Hospital, London, UK; Royal Free Hospital, London, UK; Royal Free Hospital, London, UK; University College London Hospitals NHS Foundation Trust, London, UK; Royal Free Hospital, London, UK; Royal Free Hospital, London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; Division of Infection and Immunity, University College London, London, UK; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Northwestern University Feinberg School of Medicine; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; Division of Pulmonary and Critical Care Medicine, Northwestern University, Feinberg School of Medicine, Chicago, USA; ; Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK; Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK; Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK; University of Cambridge, Department of Medicine; University of Cambride, Department of Medicine; Wellcome Trust & MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Cambridge UK; Wellcome Trust & MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Cambridge UK; NIHR Great Ormond Street BRC and Institute of Child Health, London, UK; Division of Infection and Immunity, University College London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; UCL Great Ormond Street Institute of Child Health, London, UK; Northwestern University; UCL Respiratory, Division of Medicine, University College London, London, UK; Wellcome Sanger Institute, Cambridge, UK; UCL Respiratory, Division of Medicine, University College London, London, UK; Wellcome Sanger Institute, Cambridge, UK","While a substantial proportion of adults infected with SARS-CoV-2 progress to develop severe disease, children rarely manifest respiratory complications. Therefore, understanding differences in the local and systemic response to SARS-CoV-2 infection between children and adults may provide important clues about the pathogenesis of SARS-CoV-2 infection. To address this, we first generated a healthy reference multi-omics single cell data set from children (n=30) in whom we have profiled triple matched samples: nasal and tracheal brushings and PBMCs, where we track the developmental changes for 42 airway and 31 blood cell populations from infancy, through childhood to adolescence. This has revealed the presence of naive B and T lymphocytes in neonates and infants with a unique gene expression signature bearing hallmarks of innate immunity. We then contrast the healthy reference with equivalent data from severe paediatric and adult COVID-19 patients (total n=27), from the same three types of samples: upper and lower airways and blood. We found striking differences: children with COVID-19 as opposed to adults had a higher proportion of innate lymphoid and non-clonally expanded naive T cells in peripheral blood, and a limited interferon-response signature. In the airway epithelium, we found the highest viral load in goblet and ciliated cells and describe a novel inflammatory epithelial cell population. These cells represent a transitional regenerative state between secretory and ciliated cells; they were found in healthy children and were enriched in paediatric and adult COVID-19 patients. Epithelial cells display an antiviral and neutrophil-recruiting gene signature that is weaker in severe paediatric versus adult COVID-19. Our matched blood and airway samples allowed us to study the spatial dynamics of infection. Lastly, we provide a user-friendly interface for this data1 as a highly granular reference for the study of immune responses in airways and blood in children.",pediatrics,fuzzy,100,100
-medRxiv,10.1101/2021.03.12.21253484,2021-03-13,https://medrxiv.org/cgi/content/short/2021.03.12.21253484,Limits of lockdown: characterising essential contacts during strict physical distancing,Amy C Thomas; Leon Danon; Hannah Christensen; Kate Northstone; Daniel Smith; Emily J Nixon; Adam Trickey; Gibran Hemani; Sarah Sauchelli; Adam Finn; Nicholas J Timpson; Ellen Brooks-Pollock,"University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; NIHR Bristol Biomedical Research Centre, University of Bristol; University of Bristol; University of Bristol; University of Bristol","COVID-19 has exposed health inequalities within countries and globally. The fundamental determining factor behind an individuals risk of infection is the number of social contacts they make. In many countries, physical distancing measures have been implemented to control transmission of SARS-CoV-2, reducing social contacts to a minimum. Characterising unavoidable social contacts is key for understanding the inequalities behind differential risks and planning vaccination programmes. We utilised an existing English longitudinal birth cohort, which is broadly representative of the wider population (n=6807), to explore social contact patterns and behaviours when strict physical distancing measures were in place during the UKs first lockdown in March-May 2020. Essential workers, specifically those in healthcare, had 4.5 times as many contacts as non-essential workers [incident rate ratio = 4.42 (CI95%: 3.88-5.04)], whilst essential workers in other sectors, mainly teaching and the police force had three times as many contacts [IRR = 2.84 (2.58-3.13)]. The number of individuals in a household, which is conflated by number of children, increases essential social contacts by 40%. Self-isolation effectively reduces numbers of contacts outside of the home, but not entirely. Together, these findings will aid the interpretation of epidemiological data and impact the design of effective SARS-CoV-2 control strategies, such as vaccination, testing and contact tracing.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2021.03.10.21253173,2021-03-12,https://medrxiv.org/cgi/content/short/2021.03.10.21253173,"High household transmission of SARS-CoV-2 in the United States: living density, viral load, and disproportionate impact on communities of color",Carla Cerami; Tyler Rapp; Feng-Chang Lin; Kathleen Tompkins; Christopher Basham; Meredith Smith Muller; Maureen Whittelsey; Haoming Zhang; Srijana Bhattarai Chhetri; Judy Smith; Christy Litel; Kelly Lin; Mehal Churiwal; Salman Khan; Faith Claman; Rebecca Rubinstein; Katie Mollan; David Wohl; Lakshmanane Premkumar; Jonathan J. Juliano; Jessica T Lin,"MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; University of North Carolina School of Medicine; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA; Institute of Global Health and Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, NC USA","BackgroundFew prospective studies of SARS-CoV-2 transmission within households have been reported from the United States, where COVID-19 cases are the highest in the world and the pandemic has had disproportionate impact on communities of color.
 
 Methods and FindingsThis is a prospective observational study. Between April-October 2020, the UNC CO-HOST study enrolled 102 COVID-positive persons and 213 of their household members across the Piedmont region of North Carolina, including 45% who identified as Hispanic/Latinx or non-white. Households were enrolled a median of 6 days from onset of symptoms in the index case. Secondary cases within the household were detected either by PCR of a nasopharyngeal (NP) swab on study day 1 and weekly nasal swabs (days 7, 14, 21) thereafter, or based on seroconversion by day 28. After excluding household contacts exposed at the same time as the index case, the secondary attack rate (SAR) among susceptible household contacts was 60% (106/176, 95% CI 53%-67%). The majority of secondary cases were already infected at study enrollment (73/106), while 33 were observed during study follow-up. Despite the potential for continuous exposure and sequential transmission over time, 93% (84/90, 95% CI 86%-97%) of PCR-positive secondary cases were detected within 14 days of symptom onset in the index case, while 83% were detected within 10 days. Index cases with high NP viral load (>10^6 viral copies/ul) at enrollment were more likely to transmit virus to household contacts during the study (OR 4.9, 95% CI 1.3-18 p=0.02). Furthermore, NP viral load was correlated within families (ICC=0.44, 95% CI 0.26-0.60), meaning persons in the same household were more likely to have similar viral loads, suggesting an inoculum effect. High household living density was associated with a higher risk of secondary household transmission (OR 5.8, 95% CI 1.3-55) for households with >3 persons occupying <6 rooms (SAR=91%, 95% CI 71-98%). Index cases who self-identified as Hispanic/Latinx or non-white were more likely to experience a high living density and transmit virus to a household member, translating into an SAR in minority households of 70%, versus 52% in white households (p=0.05).
@@ -3325,6 +3443,15 @@ medRxiv,10.1101/2021.03.11.21253106,2021-03-12,https://medrxiv.org/cgi/content/s
 Method and resultsWe used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existent heart disease and in-hospital mortality. 16,511 patients with COVID-19 were included (21.1% aged 66 - 75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male and often had other comorbid conditions when compared to those without. Mortality was higher in patients with cardiac disease (29.7%; n=1545 versus 15.9%; n=1797). However, following multivariable adjustment this difference was not significant (adjusted risk ratio (aRR) 1.08 [95% CI 1.02 - 1.15; p-value 0.12 (corrected for multiple testing)]). Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure aRR (1.19 [1.10 - 1.30]; p-value <0.018) particularly for severe NYHA III/IV) heart failure (aRR 1.41 [95% CI 1.20 - 1.64; p-value <0.018]. None of the other heart disease subtypes, including ischemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients.
 
 ConclusionConsiderable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare.",epidemiology,fuzzy,100,100
+medRxiv,10.1101/2021.03.09.21253218,2021-03-12,https://medrxiv.org/cgi/content/short/2021.03.09.21253218,An observational cohort study on the incidence of SARS-CoV-2 infection and B.1.1.7 variant infection in healthcare workers by antibody and vaccination status,Sheila F Lumley; Gillian Rodger; Bede Constantinides; Nicholas Sanderson; Kevin K Chau; Teresa L Street; Alison Howarth; Stephanie B Hatch; Brian D Marsden; Stuart Cox; Tim James; Fiona Warren; Liam J Peck; Thomas G Ritter; Zoe de Toledo; Laura Warren; David Axten; Richard J Cornall; E Yvonne Jones; David I Stuart; Gavin Screaton; Daniel Ebner; Sarah Hoosdally; Meera Chand; - Oxford University Hospitals Staff Testing Group; Derrick Crook; Christopher P Conlon; Koen B Pouwels; A Sarah Walker; Tim EA Peto; Susan Hopkins; Timothy M Walker; Nicole EA Stoesser; Philippa C Matthews; Katie Jeffery; David W Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Public Health England; ; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Public Health England; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; University of Oxford,"BackgroundNatural and vaccine-induced immunity will play a key role in controlling the SARS-CoV-2 pandemic. SARS-CoV-2 variants have the potential to evade natural and vaccine-induced immunity.
+
+MethodsIn a longitudinal cohort study of healthcare workers (HCWs) in Oxfordshire, UK, we investigated the protection from symptomatic and asymptomatic PCR-confirmed SARS-CoV-2 infection conferred by vaccination (Pfizer-BioNTech BNT162b2, Oxford-AstraZeneca ChAdOx1 nCOV-19) and prior infection (determined using anti-spike antibody status), using Poisson regression adjusted for age, sex, temporal changes in incidence and role. We estimated protection conferred after one versus two vaccinations and from infections with the B.1.1.7 variant identified using whole genome sequencing.
+
+Results13,109 HCWs participated; 8285 received the Pfizer-BioNTech vaccine (1407 two doses) and 2738 the Oxford-AstraZeneca vaccine (49 two doses). Compared to unvaccinated seronegative HCWs, natural immunity and two vaccination doses provided similar protection against symptomatic infection: no HCW vaccinated twice had symptomatic infection, and incidence was 98% lower in seropositive HCWs (adjusted incidence rate ratio 0.02 [95%CI <0.01-0.18]). Two vaccine doses or seropositivity reduced the incidence of any PCR-positive result with or without symptoms by 90% (0.10 [0.02-0.38]) and 85% (0.15 [0.08-0.26]) respectively. Single-dose vaccination reduced the incidence of symptomatic infection by 67% (0.33 [0.21-0.52]) and any PCR-positive result by 64% (0.36 [0.26-0.50]). There was no evidence of differences in immunity induced by natural infection and vaccination for infections with S-gene target failure and B.1.1.7.
+
+ConclusionNatural infection resulting in detectable anti-spike antibodies and two vaccine doses both provide robust protection against SARS-CoV-2 infection, including against the B.1.1.7 variant.
+
+SummaryNatural infection resulting in detectable anti-spike antibodies and two vaccine doses both provided [&ge;] 85% protection against symptomatic and asymptomatic SARS-CoV-2 infection in healthcare workers, including against the B.1.1.7 variant. Single dose vaccination reduced symptomatic infection by 67%.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.03.08.21253110,2021-03-10,https://medrxiv.org/cgi/content/short/2021.03.08.21253110,Incidence of SARS-CoV-2 infection according to baseline antibody status in staff and residents of 100 Long Term Care Facilities (VIVALDI study),Maria Krutikov; Tom Palmer; Gokhan Tut; Chris Fuller; Madhumita Shrotri; Haydn Williams; Daniel Davies; Aidan Irwin-Singer; James Robson; Andrew Hayward; Paul Moss; Andrew Copas; Laura J Shallcross,UCL; UCL; University of Birmingham; UCL; UCL; Four Seasons Healthcare Group; Palantir Ltd; UK Department of Health and Social Care; Four Seasons Healthcare Group; UCL; University of Birmingham; UCL; UCL,"BackgroundSARS-CoV-2 infection represents a major challenge for Long Term Care Facilities (LTCFs) and many residents and staff are now sero-positive following persistent outbreaks. We investigated the relationship between the presence of SARS-CoV-2 specific antibodies and subsequent infection in this population.
 
 MethodsProspective cohort study of infection in staff and residents in 100 LTCFs in England between October 2020 and February 2021. Blood samples were collected at baseline (June 2020), 2 and 4 months and tested for IgG antibodies to nucleocapsid and spike protein. PCR testing for SARS-CoV-2 was undertaken weekly in staff and monthly in residents. The primary analysis estimated the relative hazard of a PCR-positive test by baseline antibody status, from Cox regression adjusted for age and gender, and stratified by LTCF.
@@ -3380,6 +3507,7 @@ Funding statementN/A",public and global health,fuzzy,100,100
 medRxiv,10.1101/2021.03.04.21252931,2021-03-08,https://medrxiv.org/cgi/content/short/2021.03.04.21252931,A common TMPRSS2 variant protects against severe COVID-19,"Alessia David; Nicholas Parkinson; Thomas P Peacock; Erola Pairo-Castineira; Tarun Khanna; Aurelie Cobat; Albert Tenesa; Vanessa Sancho-Shimizu; - GenOMICC Investigators, ISARIC4C Investigators; Jean-Laurent Casanova; Laurent Abel; Wendy S Barclay; J Kenneth Baillie; Michael J.E. Sternberg","Centre for Integrative System Biology and Bioinformatics, Imperial College London, London; Roslin Institute, University of Edinburgh; Department of Infectious Diseases, Imperial College London; Roslin Institute, University of Edinburgh; Centre for Integrative System Biology and Bioinformatics, Imperial College London; Laboratory of Human Genetics of Infectious Diseases, INSERM; Roslin Institute, University of Edinburgh; Department of Paediatric Infectious Diseases & Virology, Imperial College London; ; St. Giles Laboratory of Human Genetics of Infectious Diseases, The Rockefeller University; Laboratory of Human Genetics of Infectious Diseases, INSERM; Department of Infectious Diseases, Imperial College London; Roslin Institute, University of Edinburgh; Centre for Integrative System Biology and Bioinformatics, Imperial College London","Infection with SARS-CoV-2 has a wide range of clinical presentations, from asymptomatic to life-threatening. Old age is the strongest factor associated with increased COVID19-related mortality, followed by sex and pre-existing conditions. The importance of genetic and immunological factors on COVID19 outcome is also starting to emerge, as demonstrated by population studies and the discovery of damaging variants in genes controlling type I IFN immunity and of autoantibodies that neutralize type I IFNs. The human protein transmembrane protease serine type 2 (TMPRSS2) plays a key role in SARS-CoV-2 infection, as it is required to activate the virus spike protein, facilitating entry into target cells. We focused on the only common TMPRSS2 non-synonymous variant predicted to be damaging (rs12329760), which has a minor allele frequency of [~]25% in the population. In a large population of SARS-CoV-2 positive patients, we show that this variant is associated with a reduced likelihood of developing severe COVID19 (OR 0.87, 95%CI:0.79-0.97, p=0.01). This association was stronger in homozygous individuals when compared to the general population (OR 0.65, 95%CI:0.50-0.84, p=1.3x10-3). We demonstrate in vitro that this variant, which causes the amino acid substitution valine to methionine, impacts the catalytic activity of TMPRSS2 and is less able to support SARS-CoV-2 spike-mediated entry into cells.
 
 TMPRSS2 rs12329760 is a common variant associated with a significantly decreased risk of severe COVID19. Further studies are needed to assess the expression of the TMPRSS2 across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID19. Clinical trials are needed to confirm this.",genetic and genomic medicine,fuzzy,100,100
+medRxiv,10.1101/2021.03.04.21252528,2021-03-08,https://medrxiv.org/cgi/content/short/2021.03.04.21252528,Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England,Daniel J Grint; Kevin Wing; Elizabeth Williamson; Helen I McDonald; Krishnan Bhaskaran; David Evans; Stephen JW Evans; Alex J Walker; George Hickman; Emily Nightingale; Anna Schultze; Christopher T Rentsch; Chris Bates; Jonathan Cockburn; Helen J Curtis; Caroline E Morton; Sebastian Bacon; Simon Davy; Angel YS Wong; Amir Mehrkar; Laurie Tomlinson; Ian J Douglas; Rohini Mathur; Paula Blomquist; Brian MacKenna; Peter Ingelsby; Richard Croker; John Parry; Frank Hester; Sam Harper; Nicolas J DeVito; Will Hulme; John Tazare; Ben Goldacre; Liam Smeeth; Rosalind M Eggo,"Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; COVID-19 Outbreak Surveillance Team, Public Health England, London, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK",The B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (HR: 1.67 (95% CI: 1.34 - 2.09; P<.0001). Absolute risk of death by 28-days increased with age and comorbidities. VOC has potential to spread faster with higher mortality than the pandemic to date.,infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.03.08.21253112,2021-03-08,https://medrxiv.org/cgi/content/short/2021.03.08.21253112,OpenSAFELY: Risks of COVID-19 hospital admission and death for people with learning disabilities - a cohort study.,Elizabeth Williamson; Helen I McDonald; Krishnan Bhaskaran; Alex J Walker; Sebastian Bacon; Simon Davy; Anna Schultze; Laurie Tomlinson; Chris Bates; Mary Ramsay; Helen J Curtis; Harriet Forbes; Kevin Wing; Caroline Minassian; John Tazare; Caroline E Morton; Emily Nightingale; Amir Mehrkar; Dave Evans; Peter Inglesby; Brian MacKenna; Jonathan Cockburn; Christopher T Rentsch; Rohini Mathur; Angel Wong; Rosalind M Eggo; William J Hulme; Richard Croker; John Parry; Frank Hester; Sam Harper; Ian Douglas; Stephen JW Evans; Liam Smeeth; Ben Goldacre; Hannah Kuper,"London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; NIHR Health Protection Research Unit (HPRU) in Immunisation; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; Public Health England, London; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine, Keppel Street, WC1E 7HT","ObjectivesTo assess the association between learning disability and risk of hospitalisation and mortality from COVID-19 in England among adults and children.
 
 DesignWorking on behalf of NHS England, two cohort studies using patient-level data for >17 million people from primary care electronic health records were linked with death data from the Office for National Statistics and hospitalization data from NHS Secondary Uses Service using the OpenSAFELY platform.
@@ -3634,13 +3762,6 @@ ResultsWave 2 patients were younger, more ethnically diverse, had less co-morbid
 
 ConclusionPrior to new SARS-CoV-2 variants, outcomes for hospitalised patients with COVID-19 were improving but with similar intensive care needs.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2021.02.03.21251054,2021-02-05,https://medrxiv.org/cgi/content/short/2021.02.03.21251054,Age-related heterogeneity in Neutralising antibody responses to SARS-CoV-2 following BNT162b2 vaccination,Dami Collier; Isabella Ferreira; Rawlings Datir; Prasanti Kotagiri; Eleanor Lim; Bo Meng; - The CITIID-NIHR Bioresource COVID-19 Collaboration; Anne Elmer; Nathalie Kingston; Barbara Graves; Barbara Graves; Kenneth GC Smith; John Bradley; Paul Lyons; Lourdes Ceron-Gutierrez; Gabriela Barcenas-Morales; Michelle Linterman; Laura McCoy; Rainer Doffinger; Mark Wills; Ravindra K Gupta,UCL; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; -; Cambridge; NIHR; NIHR; Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Babraham Institute; UCL; University of Cambridge; University of Cambridge; University of Cambridge,"Two dose mRNA vaccination provides excellent protection against SARS-CoV-2. However, there are few data on vaccine efficacy in elderly individuals above the age of 801. Additionally, new variants of concern (VOC) with reduced sensitivity to neutralising antibodies have raised fears for vulnerable groups. Here we assessed humoral and cellular immune responses following vaccination with mRNA vaccine BNT162b22 in elderly participants prospectively recruited from the community and younger health care workers. Median age was 72 years and 51% were females amongst 140 participants. Neutralising antibody responses after the first vaccine dose diminished with increasing age, with a marked drop in participants over 80 years old. Sera from participants below and above 80 showed significantly lower neutralisation potency against B.1.1.7, B.1.351 and P.1. variants of concern as compared to wild type. Those over 80 were more likely to lack any neutralisation against VOC compared to younger participants following first dose. The adjusted odds ratio for inadequate neutralisation activity against the B.1.1.7, P.1 and B.1.351 variant in the older versus younger age group was 4.3 (95% CI 2.0-9.3, p<0.001), 6.7 (95% CI 1.7-26.3, p=0.008) and 1.7 (95% CI 0.5-5.7, p=0.41). Binding IgG and IgA antibodies were lower in the elderly, as was the frequency of SARS-CoV-2 Spike specific B-memory cells. We observed a trend towards lower somatic hypermutation in participants with suboptimal neutralisation, and elderly participants demonstrated clear reduction in class switched somatic hypermutation, driven by the IgA1/2 isotype. SARS-CoV-2 Spike specific T-cell IFN{gamma} and IL-2 responses fell with increasing age, and both cytokines were secreted primarily by CD4 T cells. We conclude that the elderly are a high risk population that warrant specific measures in order to mitigate against vaccine failure, particularly where variants of concern are circulating.",infectious diseases,fuzzy,100,100
-medRxiv,10.1101/2021.02.02.21251043,2021-02-05,https://medrxiv.org/cgi/content/short/2021.02.02.21251043,COVID-19 infection and subsequent thromboembolism: A self-controlled case series analysis of a population cohort,Frederick Ho; Kenneth Man; Mark Toshner; Colin Church; Carlos Celis-Morales; Ian Wong; Colin Berry; Naveed Sattar; Jill Pell,University of Glasgow; UCL; University of Cambridge; NHS Greater Glasgow and Clyde; University of Glasgow; UCL; University of Glasgow; University of Glasgow; University of Glasgow,"ObjectiveAn unexpectedly large number of people infected with Covid-19 had experienced a thrombotic event. This study aims to assess the associations between Covid-19 infection and thromboembolism including myocardial infarction (MI), ischaemic stroke, deep-vein thrombosis (DVT), and pulmonary embolism (PE).
-
-Patients and MethodsA self-controlled case-series study was conducted covering the whole of Scotlands general population. The study population comprised individuals with confirmed (positive test) Covid-19 and at least one thromboembolic event between March 2018 and October 2020. Their incidence rates during the risk interval (5 days before to 56 days after the positive test) and the control interval (the remaining periods) were compared intra-personally.
-
-ResultsAcross Scotland, 1,449 individuals tested positive for Covid-19 and experienced a thromboembolic event. The risk of thromboembolism was significantly elevated over the whole risk period but highest in the 7 days following the positive test (IRR 12.01, 95% CI 9.91-14.56) in all included individuals. The association was also present in individuals not originally hospitalised for Covid-19 (IRR 4.07, 95% CI 2.83-5.85). Risk of MI, stroke, PE and DVT were all significantly higher in the week following a positive test. The risk of PE and DVT was particularly high and remained significantly elevated even 56 days following the test.
-
-ConclusionConfirmed Covid-19 infection was associated with early elevations in risk with MI, ischaemic stroke, and substantially stronger and prolonged elevations with DVT and PE both in hospital and community settings. Clinicians should consider thromboembolism, especially PE, among people with Covid-19 in the community.",cardiovascular medicine,fuzzy,100,100
 medRxiv,10.1101/2021.02.03.21251004,2021-02-05,https://medrxiv.org/cgi/content/short/2021.02.03.21251004,Ethnic differences in COVID-19 mortality during the first two waves of the Coronavirus Pandemic: a nationwide cohort study of 29 million adults in England,Vahe Nafilyan; Nazrul Islam; Rohini Mathur; Daniel Ayoubkhani; Amitava Banerjee; Myer Glickman; Ben Humberstone; Ian DIamond; Kamlesh Khunti,"Office for National Statistics; Nuffield Department of Population Health, Big Data Institute, University of Oxford; London School of Hygiene and Tropical Medicine; Office for National Statistics; University College London; Office for National Statistics; Office for National Statistics; Office for National Statistics; Diabetes Research Centre, University of Leicester","BackgroundEthnic minorities have experienced disproportionate COVID-19 mortality rates in the UK and many other countries. We compared the differences in the risk of COVID-19 related death between ethnic groups in the first and second waves the of COVID-19 pandemic in England. We also investigated whether the factors explaining differences in COVID-19 death between ethnic groups changed between the two waves.
 
 MethodsUsing data from the Office for National Statistics Public Health Data Asset on individuals aged 30-100 years living in private households, we conducted an observational cohort study to examine differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24th January 2020 until 31st August 2020) and second wave (from 1st September to 28th December 2020). We estimated age-standardised mortality rates (ASMR) in the two waves stratified by ethnic groups and sex. We also estimated hazard ratios (HRs) for ethnic-minority groups compared with the White British population, adjusted for geographical factors, socio-demographic characteristics, and pre-pandemic health conditions.
@@ -3812,7 +3933,6 @@ RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSPublic policy measu
 Added value of this studyCommissioned by the Chief Medical Officer for England, we validated the novel clinical risk prediction model (QCovid) to identify risks of short-term severe outcomes due to COVID-19. We used national linked datasets from general practice, death registry and hospital episode data for a population-representative sample of over 34 million adults. The risk models have excellent discrimination in men and women (Harrells C statistic>0.9) and are well calibrated. QCovid represents a new, evidence-based opportunity for population risk-stratification.
 
 Implications of all the available evidenceQCovid has the potential to support public health policy, from enabling shared decision making between clinicians and patients in relation to health and work risks, to targeted recruitment for clinical trials, and prioritisation of vaccination, for example.",public and global health,fuzzy,100,100
-bioRxiv,10.1101/2021.01.25.428136,2021-01-25,https://biorxiv.org/cgi/content/short/2021.01.25.428136,mRNA-1273 efficacy in a severe COVID-19 model: attenuated activation of pulmonary immune cells after challenge,Michelle Meyer; Yuan Wang; Darin Edwards; Gregory R Smith; Aliza B Rubenstein; Palaniappan Ramanathan; Chad E Mire; Colette Pietzsch; Xi Chen; Yongchao Ge; Wan Sze Cheng; Carole Henry; Angela Woods; LingZhi Ma; Guillaume B. E. Stewart-Jones; Kevin W Bock; Minai Mahnaz; Bianca M Nagata; Sivakumar Periasamy; Pei-Yong Shi; Barney S Graham; Ian N Moore; Irene Ramos; Olga G. Troyanskaya; Elena Zaslavsky; Andrea Carfi; Stuart C Sealfon; Alexander Bukreyev,"University of Texas Medical Branch; Princeton University; Moderna Inc; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; University of Texas Medical Branch; University of Texas Medical Branch; University of Texas Medical Branch; Flatiron Institute, Simons Foundation; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Moderna Inc; Moderna Inc; Moderna Inc; Moderna Inc; National Institute of Health; National Institutes of Health; National Institutes of Health; University of Texas Medical Branch; University of Texas Medical Branch; National Institutes of Health; National Institutes of Health; Icahn School of Medicine at Mount Sinai; Princeton University; Icahn School of Medicine at Mount Sinai; Moderna Inc; Icahn School of Medicine at Mount Sinai; University of Texas Medical Branch at Galveston","The mRNA-1273 vaccine was recently determined to be effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from interim Phase 3 results. Human studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Hamsters are the only model that reliably exhibit more severe SARS-CoV-2 disease similar to hospitalized patients, making them pertinent for vaccine evaluation. We demonstrate that prime or prime-boost administration of mRNA-1273 in hamsters elicited robust neutralizing antibodies, ameliorated weight loss, suppressed SARS-CoV-2 replication in the airways, and better protected against disease at the highest prime-boost dose. Unlike in mice and non-human primates, mRNA-1273- mediated immunity was non-sterilizing and coincided with an anamnestic response. Single-cell RNA sequencing of lung tissue permitted high resolution analysis which is not possible in vaccinated humans. mRNA-1273 prevented inflammatory cell infiltration and the reduction of lymphocyte proportions, but enabled antiviral responses conducive to lung homeostasis. Surprisingly, infection triggered transcriptome programs in some types of immune cells from vaccinated hamsters that were shared, albeit attenuated, with mock-vaccinated hamsters. Our results support the use of mRNA-1273 in a two-dose schedule and provides insight into the potential responses within the lungs of vaccinated humans who are exposed to SARS-CoV-2.",immunology,fuzzy,96,94
 medRxiv,10.1101/2021.01.21.20240887,2021-01-22,https://medrxiv.org/cgi/content/short/2021.01.21.20240887,"The psychosocial impact of the COVID-19 pandemic on 4,378 UK healthcare workers and ancillary staff: initial baseline data from a cohort study collected during the first wave of the pandemic.",Danielle Lamb; Sam Gnanapragasam; Neil Greenberg; Rupa Bhundia; Ewan Carr; Matthew Hotopf; Reza Razavi; Rosalind Raine; Sean Cross; Amy Dewar; Mary Docherty; Sarah Dorrington; Stephani Hatch; Charlotte Wilson-Jones; Daniel Leightley; Ira Madan; Sally Marlow; Isabel McMullen; Anne Marie Rafferty; Martin Parsons; Catherine Polling; Danai Serfioti; Helen Gaunt; Peter Aitken; Joanna Morris-Bone; Chloe Simela; Veronica French; Rachel Harris; Sharon A.M. Stevelink; Simon Wessely,"Department of Applied Health Research, UCL, 1-19 Torrington Place, London, WC1E 7HB; South London and Maudsley NHS Foundation Trust, London, UK; Health Protection Research Unit, King's College London, Weston Education Centre, 10 Cutcombe Road, London, SE5 9RJ; Department of Psychological Medicine, King's College London, London, UK.; Department of Biostatistics and Health Informatics, King's College London, London, UK; National Institute of Health Research Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust.; 1 Lambeth Palace Rd, South Bank, London, SE1 7EU; Dept of Applied Health Research, UCL; Department of Psychological Medicine, King's College Hospital. Denmark Hill. SE5 9RS; Guy's and St Thomas' NHS Foundation Trust; Department of Psychological Medicine, King's College Hospital. Denmark Hill. SE5 9RS; Institute of Psychiatry, Psychology and Neuroscience, King's College London; Institute of Psychiatry, Psychology and Neuroscience, King's College London; Institute of Psychiatry, Psychology and Neuroscience, King's College London; King's Centre for Military Health Research, Department of Psychological Medicine, King's College London, London, UK. AND Department of Psychological Medicine, K; Guy's and St Thomas' NHS Foundation Trust, London; Institute of Psychiatry, Psychology and Neuroscience, King's College London; Department of Psychological Medicine, King's College Hospital, South London and Maudsley NHS Foundation Trust; Adult Nursing, King's College London; Mental Health Liaison Team, King's College Hospital; Institute of Psychiatry, Psychology and Neuroscience, King's College London; King's Centre for Military Health Research, King's College London, Room 307, Weston Education Centre, 10 Cutcombe Road, London SE5 9RJ; University Hospital of Leciester NHS Trust. Groby Road Leciester LE4 9QP; Devon Partnership NHS Trust, Trust HQ, R&D, Dryden Road, Exeter, Devon, EX2 5AF; Avon & Wiltshire Mental Health Partnership NHS Trust, R&D, Fromeside, Blackberry Hill Hospital, Bristol, BS16 1EG; Guy's and St Thomas' NHS Foundation Trust, London; Nottinghamshire Healthcare NHS Foundation Trust; Cornwall Partnership Foundation NHS Trust/ Research and Innovation Team; King's Centre for Military Health Research, Department of Psychological Medicine, King's College London, London, UK. AND Department of Psychological Medicine, K; Department of Psychological Medicine, King's College London, Weston Education, Denmark Hill, London, SE5 9JR","ObjectivesThis study reports preliminary findings on the prevalence of, and factors associated with, mental health and wellbeing outcomes of healthcare workers during the early months (April-June) of the COVID-19 pandemic in the UK.
 
 MethodsPreliminary cross-sectional data were analysed from a cohort study (n=4,378). Clinical and non-clinical staff of three London-based NHS Trusts (UK), including acute and mental health Trusts, took part in an online baseline survey. The primary outcome measure used is the presence of probable common mental disorders (CMDs), measured by the General Health Questionnaire (GHQ-12). Secondary outcomes are probable anxiety (GAD-7), depression (PHQ-9), Post-Traumatic Stress Disorder (PTSD) (PCL-6), suicidal ideation (CIS-R), and alcohol use (AUDIT). Moral injury is measured using the Moray Injury Event Scale (MIES).
@@ -4034,6 +4154,15 @@ MethodsREACT-1 is a series of community surveys of SARS-CoV-2 RT-PCR swab-positi
 ResultsBetween 13th November and 3rd December (round 7) there were 1,299 positive swabs out of 168,181 giving a weighted prevalence of 0.94% (95% CI 0.87%, 1.01%) or 94 per 10,000 people infected in the community in England. This compares with a prevalence of 1.30% (1.21%, 1.39%) from 16th October to 2nd November 2020 (round 6), a decline of 28%. Prevalence during the latter half of round 7 was 0.91% (95% CI, 0.81%, 1.03%) compared with 0.96% (0.87%, 1.05%) in the first half. The national R number in round 7 was estimated at 0.96 (0.88, 1.03) with a decline in prevalence observed during the first half of this period no longer apparent during the second half at the end of lockdown. During round 7 there was a marked fall in prevalence in West Midlands, a levelling off in some regions and a rise in London. R numbers at regional level ranged from 0.60 (0.41, 0.80) in West Midlands up to 1.27 (1.04, 1.54) in London, where prevalence was highest in the east and south-east of the city. Nationally, between 13th November and 3rd December, the highest prevalence was in school-aged children especially at ages 13-17 years at 2.04% (1.69%, 2.46%), or approximately 1 in 50.
 
 ConclusionBetween the previous round and round 7 (during lockdown), there was a fall in prevalence of SARS-CoV-2 swab-positivity nationally, but it did not fall uniformly over time or by geography. Continued vigilance is required to reduce rates of infection until effective immunity at the population level can be achieved through the vaccination programme.",epidemiology,fuzzy,100,100
+medRxiv,10.1101/2020.12.10.20245944,2020-12-14,https://medrxiv.org/cgi/content/short/2020.12.10.20245944,"Azithromycin in Hospitalised Patients with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial",Peter W Horby; Alistair Roddick; Enti Spata; Natalie Staplin; Jonathan R Emberson; Guilherme Pessoa-Amorim; Leon Peto; Mark Campbell; Christopher Brightling; Ben Prudon; David Chadwick; Andrew Ustianowski; Abdul Ashish; Stacy Todd; Bryan Yates; Robert Buttery; Stephen Scott; Diego Maseda; J Kenneth Baillie; Maya H Buch; Lucy C Chappell; Jeremy N Day; Saul N Faust; Thomas Jaki; Katie Jeffery; Edmund Juszczak; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; Marion Mafham; Richard Haynes; Martin J Landray,"Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom; Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom; North Manchester General Hospital & University of Manchester, Manchester, United Kingdom; Wrightington Wigan and Leigh NHS Foundation Trust, Wigan, United Kingdom; Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom; Northumbria Healthcare NHS Foundation Trust, North Tyneside, United Kingdom; North West Anglia NHS Foundation Trust, Peterborough, United Kingdom; The Countess of Chester Hospital NHS Foundation Trust, Chester, United Kingdom; Mid Cheshire Hospitals NHS Foundation Trust, Crewe, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; School of Life Sciences, King's College London, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; MRC Biostatistics Unit, University of Cambridge, Cambridge, United Ki; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United kingdom; Intensive Care National Audit & Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom","BackgroundAzithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatory actions. We evaluated the efficacy and safety of azithromycin in hospitalised patients with COVID-19.
+
+MethodsIn this randomised, controlled, open-label, adaptive platform trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19 in the UK. Eligible and consenting patients were randomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once daily by mouth or intravenously for 10 days or until discharge (or one of the other treatment arms). Patients were twice as likely to be randomised to usual care as to any of the active treatment groups. The primary outcome was 28-day mortality. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).
+
+FindingsBetween 7 April and 27 November 2020, 2582 patients were randomly allocated to receive azithromycin and 5182 patients to receive usual care alone. Overall, 496 (19%) patients allocated to azithromycin and 997 (19%) patients allocated to usual care died within 28 days (rate ratio 1{middle dot}00; 95% confidence interval [CI] 0{middle dot}90-1{middle dot}12; p=0{middle dot}99). Consistent results were seen in all pre-specified subgroups of patients. There was no difference in duration of hospitalisation (median 12 days vs. 13 days) or the proportion of patients discharged from hospital alive within 28 days (60% vs. 59%; rate ratio 1{middle dot}03; 95% CI 0{middle dot}97-1{middle dot}10; p=0{middle dot}29). Among those not on invasive mechanical ventilation at baseline, there was no difference in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (21% vs. 22%; risk ratio 0{middle dot}97; 95% CI 0{middle dot}89-1{middle dot}07; p=0{middle dot}54).
+
+InterpretationIn patients hospitalised with COVID-19, azithromycin did not provide any clinical benefit. Azithromycin use in patients hospitalised with COVID-19 should be restricted to patients where there is a clear antimicrobial indication.
+
+FundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2020.12.11.20247742,2020-12-14,https://medrxiv.org/cgi/content/short/2020.12.11.20247742,Changes in cardiovascular disease monitoring in English primary care during the COVID-19 pandemic: an observational cohort study,Clare R Bankhead; Sarah Lay-Flurrie; Brian D Nicholson; James P Sheppard; Chris P Gale; Harshana Liyanage; Dylan McGagh; Mark Minchin; Rafael Perera; Julian Sherlock; Margaret Smith; Nicholas PB Thomas; Cynthia Wright Drakesmith; Simon D de Lusignan; Richard Hobbs,University of Oxford; University of Oxford; Nuffield Department of Primary Care Health Sciences; University of Oxford; University of Leeds; University of Oxford; University of Oxford; National Institute for Health and Care Excellence; University of Oxford; University of Oxford; University of Oxford; Royal College of General Practitioners; University of Oxford; University of Oxford; University of Oxford,"ObjectiveTo quantify the impact and recovery in cardiovascular disease monitoring in primary care associated with the first COVID-19 lockdown.
 
 DesignRetrospective nationwide primary care cohort study, utilising data from 1st January 2018 to 27th September 2020.
@@ -4077,6 +4206,15 @@ MethodsWe conducted a cohort study of consecutive adults hospitalised for severe
 FindingsAmong 1,721 patients (median age 71 years, 57% male), 349 (20.3%) had pre-existing CVD (CVD), 888 (51.6%) had CV risk factors without CVD (RF-CVD), 484 (28.1%) had neither. Patients with CVD were older with a higher burden of non-CV comorbidities. During follow-up, 438 (25.5%) patients died: 37% with CVD, 25.7% with RF-CVD and 16.5% with neither. CVD was independently associated with in-hospital mortality among patients <70 years of age (adjusted HR 2.43 [95%CI 1.16-5.07]), but not in those [&ge;]70 years (aHR 1.14 [95%CI 0.77-1.69]). RF-CVD were not independently associated with mortality in either age group (<70y aHR 1.21 [95%CI 0.72-2.01], [&ge;]70y aHR 1.07 [95%CI 0.76-1.52]). Most CV complications occurred in patients with CVD (66%) versus RF-CVD (17%) or neither (11%; p<0.001). 213 [12.4%] patients developed venous thromboembolism (VTE). CVD was not an independent predictor of VTE.
 
 InterpretationIn patients hospitalised with COVID-19, pre-existing established CVD appears to be a more important contributor to mortality than CV risk factors in the absence of CVD. CVD-related hazard may be mediated, in part, by new CV complications. Optimal care and vigilance for destabilised CVD are essential in this patient group.",cardiovascular medicine,fuzzy,100,100
+medRxiv,10.1101/2020.12.03.20243535,2020-12-04,https://medrxiv.org/cgi/content/short/2020.12.03.20243535,OpenSAFELY: impact of national guidance on switching from warfarin to direct oral anticoagulants (DOACs) in early phase of COVID-19 pandemic in England,Helen J Curtis; Brian MacKenna; Alex J Walker; Richard Croker; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Peter Inglesby; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan Bhaskaran; Anna Schultze; Christopher T Rentsch; Elizabeth Williamson; William Hulme; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Henry Drysdale; Rosalind M Eggo; Kevin Wing; Angel Wong; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Ian J Douglas; Liam Smeeth; Ben Goldacre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundEarly in the COVID-19 pandemic the NHS recommended that appropriate patients anticoagulated with warfarin should be switched to direct acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately co-prescribed two anticoagulants following a medication change, and associated monitoring.
+
+ObjectiveTo describe which people were switched from warfarin to DOACs; identify potentially unsafe co-prescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic.
+
+MethodsWorking on behalf of NHS England we conducted a population cohort based study using routine clinical data from >17 million adults in England.
+
+Results20,000 of 164,000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in co-prescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. INR testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420).
+
+ConclusionsIncreased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people co-prescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.",cardiovascular medicine,fuzzy,100,100
 medRxiv,10.1101/2020.11.30.20240010,2020-12-03,https://medrxiv.org/cgi/content/short/2020.11.30.20240010,Is Point-of-Care testing feasible and safe in care homes in England? An exploratory usability and accuracy evaluation of Point-of-Care Polymerase Chain Reaction test for SARS-COV-2,Massimo Micocci; Adam Gordon; Mikyung Kelly Seo; Joy A Allen; Kerrie Davies; Dan Lasserson; Carl Thompson; Karen Spilsbury; Cyd Akrill; Ros Heath; Anita Astle; Claire Sharpe; Rafael Perera; Gail Hayward; Peter Buckle,"NIHR London In Vitro Diagnostics Co-operative, Dept of Surgery and Cancer, Faculty of Medicine, Imperial College London St. Mary's Hospital London; Division of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Nottingham, UK;NIHR Applied Research Collaboration-East Midlands (ARC-EM), N; NIHR London In Vitro Diagnostics Co-operative, Dept of Surgery and Cancer, Faculty of Medicine, Imperial College London St. Mary's Hospital London; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK; Healthcare Associated Infections Research Group, University of Leeds and Leeds Teaching Hospitals NHS Trust, Leeds, UK; Warwick Medical School, University of Warwick, UK; School of Healthcare, University of Leeds, Leeds, UK; School of Healthcare, University of Leeds, Leeds, UK; NIHR Applied Research Collaboration Yorkshire and Humber, UK; Springfield Healthcare, Leeds, UK; Landermeads Nursing Home, Nottingham, UK; Wren Hall Nursing Home, Selston, UK; Ashmere Nottinghamshire Ltd, Notts, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; NIHR Community Healthcare MedTech and IVD Co-operative,Oxford,UK; NIHR London In Vitro Diagnostics Co-operative, Dept of Surgery and Cancer, Faculty of Medicine, Imperial College London St. Mary's Hospital London","IntroductionReliable rapid testing on COVID-19 is needed in care homes to reduce the risk of outbreaks and enable timely care. Point-of-care testing (POCT) in care homes could provide rapid actionable results. This study aimed to examine the usability and test performance of point of care polymerase chain reaction (PCR) for COVID-19 in care homes.
 
 MethodsPoint-of-care PCR for detection of SARS-COV2 was evaluated in a purposeful sample of four UK care homes. Test agreement with laboratory real-time PCR and usability and use errors were assessed.
@@ -4144,7 +4282,6 @@ C_LIO_LIOptimal symptom combinations maximise case capture considering available
 C_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health
 C_LI",health informatics,fuzzy,100,100
 medRxiv,10.1101/2020.11.19.20234120,2020-11-23,https://medrxiv.org/cgi/content/short/2020.11.19.20234120,Actionable druggable genome-wide Mendelian randomization identifies repurposingopportunities for COVID-19,Liam Gaziano; Claudia Giambartolomei; Alexandre C Pereira; Anna Gaulton; Daniel C Posner; Sonja A Swanson; Yuk Lam Ho; Sudha K Iyengar; Nicole M Kosik; Marijana Vujkovic; David R Gagnon; A Patricia Bento; Pedro Beltrao; Inigo Barrio Hernandez; Lars Ronnblom; Niklas Hagberg; Christian Lundtoft; Claudia Langenberg; Maik Pietzner; Dennis Valentine; Elias Allara; Praveen Surendran; Stephen Burgess; Jing Hua Zhao; James E Peters; Bram P Prins; John Danesh; Poornima Devineni; Yunling Shi; Kristine E Lynch; Scott L DuVall; Helene Garcon; Lauren Thomann; Jin J Zhou; Bryan R Gorman; Jennifer E Huffman; Christopher J O'Donnell; Philip S Tsao; Jean C Beckham; Saiju Pyarajan; Sumitra Muralidhar; Grant D Huang; Rachel Ramoni; Adriana M Hung; Kyong-Mi Chang; Yan V Sun; Jacob Joseph; Andrew R Leach; Todd L Edwards; Kelly Cho; J Michael Gaziano; Adam S Butterworth; Juan P Casas,"VA Boston Healthcare System, University of Cambridge; Instituto Italiano di Tecnologia, University of California Los Angeles; University of Sao Paulo, Harvard University; European Molecular Biology Laboratory, European Bioinformatics Institute; VA Boston Healthcare System; Erasmus Medical Center; VA Boston Healthcare System; Case Western Reserve University and Louis Stoke Cleveland VAMC; VA Boston Healthcare System; The Corporal Michael J. Crescenz VA Medical Center, the University of Pennsylvania Perelman School of Medicine; Boston University, VA Boston Healthcare System; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; Uppsala University; Uppsala University; Uppsala University; Charite University Medicine Berlin,  Universityof Cambridge; Universityof Cambridge; University College London; University of Cambridge; Wellcome Genome Campus and University of Cambridge; University of Cambridge; University of Cambridge; Imperial College London; Wellcome Genome Campus and University of Cambridge; University of Cambridge; VA Boston Healthcare System; VA Boston Healthcare System; VA Salt Lake City Health Care System, University of Utah; VA Salt Lake City Health Care System, University of Utah; VA Boston Healthcare System; VA Boston Healthcare System; University of Arizona, Phoenix VA Health Care System; VA Boston Healthcare System; VA Boston Healthcare System; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Palo Alto Health Care System, Stanford University School of Medicine; Durham VA Medical Center, Duke University School of Medicine; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs, Vanderbilt University; The Corporal Michael J. Crescenz VA Medical Center, University of Pennsylvania; Atlanta VA Health Care System, Emory University Rollins School of Public Health; VA Boston Healthcare System and Brigham & Women's Hospital; European Molecular Biology Laboratory, European Bioinformatics Institute; Department of Veterans Affairs Tennessee Valley Healthcare System, Vanderbilt Genetics Institute Vanderbilt University Medical Center; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; University of Cambridge, Wellcome Genome Campus and University of Cambridge; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School","Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization (MR) analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2: P=1.6x10-6, IFNAR2: P=9.8x10-11, and IL-10RB: P=1.9x10-14) using cis-eQTL genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared eQTL signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.",epidemiology,fuzzy,100,100
-medRxiv,10.1101/2020.11.19.20234849,2020-11-22,https://medrxiv.org/cgi/content/short/2020.11.19.20234849,Community factors and excess mortality in first wave of the COVID-19 pandemic.,Bethan Davies; Brandon L Parkes; James Bennett; Daniela Fecht; Marta Blangiardo; Majid Ezzati; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2020.11.18.20233932,2020-11-20,https://medrxiv.org/cgi/content/short/2020.11.18.20233932,REACT-1 round 6 updated report: high prevalence of SARS-CoV-2 swab positivity with reduced rate of growth in England at the start of November 2020,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E. Walters; Haowei Wang; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Christl A Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear","BackgroundEngland is now in the midst of its second wave of the COVID-19 pandemic. Multiple regions of the country are at high infection prevalence and all areas experienced rapid recent growth of the epidemic during October 2020.
 
 MethodsREACT-1 is a series of community surveys of SARS-CoV-2 RT-PCR swab-positivity in England designed to monitor the spread of the epidemic and thus increase situational awareness. Round 6 of REACT-1 commenced swab-collection on 16th October. A prior interim report included data from 16th to 25th October for 85,971 participants. Here, we report data for the entire round on 160,175 participants with swab results obtained up to 2nd November 2020.
@@ -4159,13 +4296,6 @@ MethodsWe use a data-driven approach to parameterise an individual-based network
 ResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.
 
 ConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread.",infectious diseases,fuzzy,100,100
-medRxiv,10.1101/2020.11.18.20225029,2020-11-20,https://medrxiv.org/cgi/content/short/2020.11.18.20225029,The Invasive Respiratory Infection Surveillance (IRIS) Initiative reveals significant reductions in invasive bacterial infections during the COVID-19 pandemic,Angela B Brueggemann; Melissa J Jansen van Rensburg; David Shaw; Noel D McCarthy; Keith A Jolley; Martin CJ Maiden; Mark PG van der Linden,University of Oxford; University of Oxford; University of Oxford; University of Warwick; University of Oxford; University of Oxford; University Hospital RWTH Aachen,"BackgroundStreptococcus pneumoniae, Haemophilus influenzae and Neisseria meningitidis are leading causes of invasive diseases including bacteraemic pneumonia and meningitis, and of secondary infections post-viral respiratory disease. They are typically transmitted via respiratory droplets. We investigated rates of invasive disease due to these pathogens during the early phase of the COVID-19 pandemic.
-
-MethodsLaboratories in 26 countries across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae and N meningitidis from 1 January 2018 to 31 May 2020. Weekly cases in 2020 vs 2018-2019 were compared. Streptococcus agalactiae data were collected from nine laboratories for comparison to a non-respiratory pathogen. The stringency of COVID-19 containment measures was quantified by the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed by Google COVID-19 Community Mobility Reports. Interrupted time series modelling quantified changes in rates of invasive disease in 2020 relative to when containment measures were imposed.
-
-FindingsAll countries experienced a significant, sustained reduction in invasive diseases due to S pneumoniae, H influenzae and N meningitidis, but not S agalactiae, in early 2020, which coincided with the introduction of COVID-19 containment measures in each country. Similar impacts were observed across most countries despite differing stringency in COVID-19 control policies. There was no evidence of a specific effect due to enforced school closures.
-
-InterpretationThe introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of these bacterial respiratory pathogens, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2020.11.18.20234369,2020-11-19,https://medrxiv.org/cgi/content/short/2020.11.18.20234369,Antibodies to SARS-CoV-2 are associated with protection against reinfection,Sheila F Lumley; Nicole E Stoesser; Philippa C Matthews; Alison Howarth; Stephanie B Hatch; Brian D Marsden; Stuart Cox; Tim James; Fiona Warren; Liam J Peck; Thomas G Ritter; Zoe de Toledo; Laura Warren; David Axten; Richard J Cornall; E Yvonne Jones; David I Stuart; Gavin Screaton; Daniel Ebner; Sarah Hoosdally; Meera Chand; - Oxford University Hospitals Staff Testing Group; Derrick W Crook; Christopher P Conlon; Koen B Pouwels; A Sarah Walker; Tim EA Peto; Susan Hopkins; Tim M Walker; Katie Jeffery; David W Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Public Health England; ; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Public Health England; University of Oxford; University of Oxford; University of Oxford,"BackgroundIt is critical to understand whether infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) protects from subsequent reinfection.
 
 MethodsWe investigated the incidence of SARS-CoV-2 PCR-positive results in seropositive and seronegative healthcare workers (HCWs) attending asymptomatic and symptomatic staff testing at Oxford University Hospitals, UK. Baseline antibody status was determined using anti-spike and/or anti-nucleocapsid IgG assays and staff followed for up to 30 weeks. We used Poisson regression to estimate the relative incidence of PCR-positive results and new symptomatic infection by antibody status, accounting for age, gender and changes in incidence over time.
@@ -4315,7 +4445,6 @@ RESULTS IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSA small study in 47
 Added value of this studyTo our knowledge this is the first study to explore changes in healthcare contacts for acute physical and mental health conditions in a large population representative of the UK. We used electronic primary care health records of nearly 10 million individuals across the UK to investigate the indirect impact of COVID-19 on primary care contacts for mental health, acute alcohol-related events, asthma/chronic obstructive pulmonary disease (COPD) exacerbations, and cardiovascular and diabetic emergencies up to July 2020. For all conditions studied, we found primary care contacts dropped dramatically following the introduction of population-wide restriction measures in March 2020. By July 2020, with the exception of unstable angina and acute alcohol-related events, primary care contacts for all conditions studied had not recovered to pre-lockdown levels. In the general population, estimates of the absolute reduction in the number of primary care contacts up to July 2020, compared to what we would expect from previous years varied from fewer than 10 contacts per million for some cardiovascular outcomes, to 12,800 per million for depression and 6,600 for anxiety. In people with COPD, we estimated there were 43,900 per million fewer contacts for COPD exacerbations up to July 2020 than what we would expect from previous years.
 
 Implicatins of all the available evidenceWhile our results may represent some genuine reduction in disease frequency (e.g. the restriction measures may have improved diabetic glycaemic control due to more regular daily routines at home), it is more likely the reduced primary care conatcts we saw represent a substantial burden of unmet need (particularly for mental health conditions) that may be reflected in subsequent increased mortality and morbidity. Health service providers should take steps to prepare for increased demand in the coming months and years due to the short and longterm ramifications of reduced access to care for severe acute physical and mental health conditions. Maintaining access to primary care is key to future public health planning in relation to the pandemic.",primary care research,fuzzy,100,100
-bioRxiv,10.1101/2020.10.29.339317,2020-10-30,https://biorxiv.org/cgi/content/short/2020.10.29.339317,"COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning",- The COVID Moonshot Consortium; Hagit Achdout; Anthony Aimon; Dominic S Alonzi; Robert Arbon; Elad Bar-David; Haim Barr; Amir Ben-Shmuel; James Bennett; Vitaliy A. Bilenko; Vitaliy A. Bilenko; Melissa L. Boby; Bruce Borden; Pascale Boulet; Gregory R. Bowman; Juliane Brun; Lennart Brwewitz; Sarma BVNBS; Mark Calmiano; Anna Carbery; Daniel Carney; Emma Cattermole; Edcon Chang; Eugene Chernyshenko; John D. Chodera; Austin Clyde; Joseph E. Coffland; Galit Cohen; Jason Cole; Alessandro Contini; Lisa Cox; Tristan Ian Croll; Milan Cvitkovic; Alex Dias; Kim Donckers; David L. Dotson; Alice Douangamath; Shirly Duberstein; Tim Dudgeon; Louise Dunnett; Peter K. Eastman; Noam Erez; Charles J. Eyermann; Mike Fairhead; Gwen Fate; Daren Fearon; Oleg Fedorov; Matteo Ferla; Rafaela S. Fernandes; Lori Ferrins; Mihajlo Filep; Richard Foster; Holly Foster; Laurent Fraisse; Ronen Gabizon; Adolfo Garcia-Sastre; Victor O. Gawriljuk; Paul Gehrtz; Carina Gileadi; Charline Giroud; William G. Glass; Robert Glen; Itai Glinert; Andre S. Godoy; Marian Gorichko; Tyler Gorrie-Stone; Ed J. Griffen; Sophie Hahn; Amna Haneef; Storm Hassell Hart; Jag Heer; Michael Henry; Michelle Hill; Sam Horrell; Qiu Yu Huang; Victor D. Huliak; Victor D. Huliak; Matthew F.D. Hurley; Tomer Israely; Andrew Jajack; Jitske Jansen; Eric Jnoff; Dirk Jochmans; Tobias John; Steven De Jonghe; Benjamin Kaminow; Lulu Kang; Anastassia L. Kantsadi; Peter W. Kenny; J. L. Kiappes; Serhii O. Kinakh; Serhii O. Kinakh; Lizbe Koekemoer; Boris Kovar; Tobias Krojer; Van La; Alpha A. Lee; Bruce A. Lefker; Haim Levy; Ivan G. Logvinenko; Ivan G. Logvinenko; Nir London; Petra Lukacik; Hannah Bruce Macdonald; Elizabeth M. MacLean; Laetitia L Makower; Tika R. Malla; Tatiana Matviiuk; Willam McCorkindale; Briana L. McGovern; Sharon Melamed; Kostiantyn P. Melnykov; Kostiantyn P. Melnykov; Oleg Michurin; Pascal Miesen; Halina Mikolajek; Bruce F. Milne; David Minh; Aaron Morris; Garrett M. Morris; Melody Jane Morwitzer; Demetri Moustakas; Charles Mowbray; Aline M. Nakamura; Jose Brandao Neto; Johan Neyts; Luong Nguyen; Gabriela D. Noske; Vladas Oleinikovas; Glaucius Oliva; Gijs J. Overheul; David Owen; Ruby Pai; Jin Pan; Nir Paran; Alexander Payne; Benjamin Perry; Maneesh Pingle; Jakir Pinjari; Boaz Politi; Ailsa Powell; Vladimir Psenak; Ivan Pulido; Reut Puni; Victor L. Rangel; Rambabu N. Reddi; Paul Rees; St Patrick Reid; Lauren Reid; Efrat Resnick; Emily Grace Ripka; Matthew C. Robinson; Ralph P. Robinson; Jaime Rodriguez-Guerra; Romel Rosales; Dominic A. Rufa; Kadi Saar; Kumar Singh Saikatendu; Eidarus Salah; David Schaller; Jenke Scheen; Celia A. Schiffer; Chris Schofield; Mikhail Shafeev; Aarif Shaikh; Ala M. Shaqra; Jiye Shi; Khriesto Shurrush; Sukrit Singh; Assa Sittner; Peter Sjo; Rachael Skyner; Adam Smalley; Bart Smeets; Mihaela D. Smilova; Leonardo J. Solmesky; John Spencer; Claire Strain-Damerell; Vishwanath Swamy; Hadas Tamir; Jenny C. Taylor; Rachael E. Tennant; Warren Thompson; Andrew Thompson; Susana Tomasio; Charlie Tomlinson; Igor S. Tsurupa; Igor S. Tsurupa; Anthony Tumber; Ioannis Vakonakis; Ronald P. van Rij; Laura Vangeel; Finny S. Varghese; Mariana Vaschetto; Einat B. Vitner; Vincent Voelz; Andrea Volkamer; Frank von Delft; Annette von Delft; Martin Walsh; Walter Ward; Charlie Weatherall; Shay Weiss; Kris M. White; Conor Francis Wild; Karolina D Witt; Matthew Wittmann; Nathan Wright; Yfat Yahalom-Ronen; Nese Kurt Yilmaz; Daniel Zaidmann; Ivy Zhang; Hadeer Zidane; Nicole Zitzmann; Sarah N Zvornicanin,"; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; The Weizmann Institute of Science; Israel Institution of Biological Research; University of Oxford; Enamine Ltd; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Folding@home Consortium; DNDi; Washington University School of Medicine; University of Oxford; University of Oxford; Sai Life Sciences; UCB; University of Oxford;Diamond Light Source; Takeda Development Center Americas, Inc.; University of Oxford; Takeda Development Center Americas, Inc.; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Argonne National Laboratory; N/A; The Weizmann Institute of Science; Cambridge Crystallographic Datacentre; University of Milan; Life Compass Consulting Ltd; Cambridge Institute for Medical Research, The University of Cambridge; PostEra Inc.; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; N/A; Diamond Light Source Ltd; Research Complex at Harwell; The Weizmann Institute of Science; Informatics Matters; Diamond Light Source Ltd; Research Complex at Harwell; Department of Bioengineering until Sept. 1, then Department of Chemistry; Israel Institution of Biological Research; Northeastern University; University of Oxford; Thames Pharma Partners; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; University of Oxford; University of Sao Paulo; Northeastern University; Weizmann Institute of Science; University of Leeds; University of Leeds; DNDi; The Weizmann Institute of Science; Icahn School of Medicine at Mount Sinai; University of Sao Paulo; The Weizmann Institute of Science; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Cambridge; Israel Institution of Biological Research; University of Sao Paulo; Taras Shevchenko National University of Kyiv; Diamond Light Source Ltd; Research Complex at Harwell; MedChemica Ltd; DNDi; Illinois Institute of Technology; University of Sussex; UCB; Memorial Sloan Kettering Cancer Center; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; University of Massachusetts Chan Medical School; Enamine Ltd; Enamine Ltd; Temple University; Israel Institution of Biological Research; PostEra Inc.; Radboud University Medical Center; UCB; Katholieke Universiteit Leuven; University of Oxford; Katholieke Universiteit Leuven; Memorial Sloan Kettering Cancer Center; Illinois Institute of Technology; University of Oxford; Independent Scientist; University of Oxford; Enamine Ltd; Enamine Ltd; University of Oxford; M2M solutions, s.r.o; University of Oxford; Illinois Institute of Technology; PostEra Inc.; University of Cambridge; Thames Pharma Partners LLC; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; The Weizmann Institute of Science; Diamond Light Source Ltd; Research Complex at Harwell; Memorial Sloan Kettering Cancer Center; University of Oxford; University of Oxford; University of Oxford; Enamine Ltd; University of Cambridge; Icahn School of Medicine at Mount Sinai; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; Enamine Ltd; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; University of Coimbra and University of Aberdeen; Illinois Institute of Technology; PostEra Inc; University of Oxford; Department of Pathology and Microbiology; Relay Therapeutics; DNDi; University of Sao Paulo; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; PostEra Inc.; University of Sao Paulo; UCB; University of Sao Paulo; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; PostEra Inc.; PostEra Inc.; Israel Institution of Biological Research; Memorial Sloan Kettering Cancer Center; DNDi; Sai Life Sciences; Sai Life Sciences; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; M2M solutions, s.r.o; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; School of Pharmaceutical Sciences of Ribeirao Preto; The Weizmann Institute of Science; Compass Bussiness Partners Ltd; Department of Pathology and Microbiology; MedChemica Ltd; The Weizmann Institute of Science; PostEra Inc.; PostEra Inc.; Thames Pharma Partners LLC; Charite Universitatsmedizin Berlin; Icahn School of Medicine at Mount Sinai; Memorial Sloan Kettering Cancer Center; University of Cambridge; Takeda Development Center Americas, Inc.; University of Oxford; Charite Universitatsmedizin Berlin; Memorial Sloan Kettering Cancer Center; University of Massachusetts Chan Medical School; University of Oxford; Enamine Ltd; Sai Life Sciences; University of Massachusetts Chan Medical School; UCB; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; DNDi; Diamond Light Source Ltd; Research Complex at Harwell; UCB; Radboud University Medical Center; University of Oxford; The Weizmann Institute of Science; University of Sussex; Diamond Light Source Ltd; Research Complex at Harwell; Sai Life Sciences; Israel Institution of Biological Research; University of Oxford; Lhasa Limited; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Collaborative Drug Discovery; Diamond Light Source Ltd; Research Complex at Harwell; Enamine Ltd; Enamine Ltd; University of Oxford; University of Oxford; Radboud University Medical Center; Katholieke Universiteit Leuven; Radboud University Medical Center; Collaborative Drug Discovery; Israel Institution of Biological Research; Temple University; Charite Universitatsmedizin Berlin; Diamond Light Source Ltd; University of Oxford; Research Complex at Harwell; University of Johannesburg; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; Walter Ward Consultancy & Training; Collaborative Drug Discovery; Israel Institution of Biological Research; Icahn School of Medicine at Mount Sinai; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Oxford; Israel Institution of Biological Research; University of Massachusetts Chan Medical School; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; The Weizmann Institute of Science; University of Oxford; University of Massachusetts Chan Medical School","The COVID-19 pandemic was a stark reminder that a barren global antiviral pipeline has grave humanitarian consequences. Pandemics could be prevented in principle by accessible, easily deployable broad-spectrum oral antivirals. Here we report the results of the COVID Moonshot, a fully open-science, crowd sourced, structure-enabled drug discovery campaign targeting the SARS-CoV-2 main protease. We discovered a novel chemical series that is differentiated from current Mpro inhibitors in that it maintains a new non-covalent, non-peptidic scaffold with nanomolar potency. Our approach leveraged crowdsourcing, high-throughput structural biology, machine learning, and exascale molecular simulations and high-throughput chemistry. In the process, we generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. In a first for a structure-based drug discovery campaign, all compound designs (>18,000 designs), crystallographic data (>840 ligand-bound X-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2,400 compounds) for this campaign were shared rapidly and openly, creating a rich open and IP-free knowledgebase for future anti-coronavirus drug discovery.",biochemistry,fuzzy,100,100
 bioRxiv,10.1101/2020.10.26.356014,2020-10-28,https://biorxiv.org/cgi/content/short/2020.10.26.356014,"COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms",Marek Ostaszewski; Anna Niarakis; Alexander Mazein; Inna Kuperstein; Robert Phair; Aurelio Orta-Resendiz; Vidisha Singh; Sara Sadat Aghamiri; Marcio Luis Acencio; Enrico Glaab; Andreas Ruepp; Gisela Fobo; Corinna Montrone; Barbara Brauner; Goar Frishman; Julia Somers; Matti Hoch; Shailendra Kumar Gupta; Julia Scheel; Hanna Borlinghaus; Tobias Czauderna; Falk Schreiber; Arnau Montagud; Miguel Ponce de Leon; Akira Funahashi; Yusuke Hiki; Noriko Hiroi; Takahiro G Yamada; Andreas Drager; Alina Renz; Muhammad Naveez; Zsolt Bocskei; Daniela Bornigen; Liam Fergusson; Marta Conti; Marius Rameil; Vanessa Nakonecnij; Jakob Vanhoefer; Leonard Schmiester; Muying Wang; Emily E Ackerman; Jason E Shoemaker; Jeremy Zucker; Kristie L Oxford; Jeremy Teuton; Ebru Kocakaya; Gokce Yagmur Summak; Kristina Hanspers; Martina Kutmon; Susan Coort; Lars Eijssen; Friederike Ehrhart; Rex D. A. B.; Denise Slenter; Marvin Martens; Nhung Pham; Robin Haw; Bijay Jassal; Lisa Matthews; Marija Orlic-Milacic; Andrea Senff-Ribeiro; Karen Rothfels; Veronica Shamovsky; Ralf Stephan; Cristoffer Sevilla; Thawfeek Mohamed Varusai; Jean-Marie Ravel; Vera Ortseifen; Silvia Marchesi; Piotr Gawron; Ewa Smula; Laurent Heirendt; Venkata Satagopam; Guanming Wu; Anders Riutta; Martin Golebiewski; Stuart Owen; Carole Goble; Xiaoming Hu; Rupert Overall; Dieter Maier; Angela Bauch; Benjamin M Gyori; John A Bachman; Carlos Vega; Valentin Groues; Miguel Vazquez; Pablo Porras; Luana Licata; Marta Iannuccelli; Francesca Sacco; Denes Turei; Augustin Luna; Ozgun Babur; Sylvain Soliman; Alberto Valdeolivas; Marina Esteban-Medina; Maria Pena-Chilet; Kinza Rian; Tomas Helikar; Bhanwar Lal Puniya; Anastasia Nesterova; Anton Yuryev; Anita de Waard; Dezso Modos; Agatha Treveil; Marton Laszlo Olbei; Bertrand De Meulder; Aurelien Naldi; Aurelien Dugourd; Laurence Calzone; Chris Sander; Emek Demir; Tamas Korcsmaros; Tom C Freeman; Franck Auge; Jacques S Beckmann; Jan Hasenauer; Olaf Wolkenhauer; Egon Willighagen; Alexander R Pico; Chris Evelo; Lincoln D Stein; Henning Hermjakob; Julio Saez-Rodriguez; Joaquin Dopazo; Alfonso Valencia; Hiroaki Kitano; Emmanuel Barillot; Charles Auffray; Rudi Balling; Reinhard Schneider; - the COVID-19 Disease Map Community,"Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Department of Biology, Univ. Evry, University of Paris-Saclay, GenHotel, Genopole, 91025, Evry, France; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Institut Curie, PSL Research University, Paris, France.; Integrative Bioinformatics, Inc., 346 Paul Ave, Mountain View, CA, USA; Institut Pasteur, HIV, Inflammation and Persistence Unit, Paris, France; Laboratoire Europeen de Recherche pour la Polyarthrite Rhumatoide - Genhotel, Univ Evry, Universite Paris-Saclay, 2, rue Gaston Cremieux, 91057 EVRY-GENOPOLE ce; Inserm- Institut national de la sante et de la recherche medicale. Saint-Louis Hospital 1 avenue Claude Vellefaux Pavillon Bazin 75475 Paris; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Institute of Experimental Genetics (IEG), Helmholtz Zentrum Munchen-German Research Center for Environmental Health (GmbH), Ingolstadter Landstrasse 1, D-85764 ; Oregong Health & Sciences Univerity; Department of Molecular and Medical Genetics; 3222 SW Research Drive, Portland, Oregon, U.S.A 97239; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany; Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Monash University, Faculty of Information Technology, Department of Human-Centred Computing, Wellington Rd, Clayton VIC 3800, Australia; Department of Computer and Information Science, University of Konstanz, Konstanz, Germany; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Sanyo-Onoda City University, Faculty of Pharmaceutical Sciences, University St.1-1-1, Yamaguchi, Japan 756-0884; Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi Kouhoku-ku Yokohama Japan 223-8522; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu; Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tu; Riga Technical University, Institute of Applied Computer Systems,1 Kalku Street, LV-1658 Riga, Latvia; Sanofi R&D Translational Sciences; Bioinformatics Core Facility, Universitaetsklinikum Hamburg-Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany; The University of Edinburgh, Royal (Dick) School of Veterinary Medicine, Easter Bush Campus, Midlothian, EH25 9RG; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; University of Bonn, Germany; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Faculty of Mathematics and Natural Sciences, University of Bonn, Bonn, Germany; Helmholtz Zentrum Munchen - German Research Center for Environmental Health, Institute of Computational Biology, 85764 Neuherberg, Germany; Department of Chemical Engineering, University of Pittsburgh; University of Pittsburgh, Department of Chemical and Petroleum Engineering; Dept. of Chemical & Petroleum Engineering, University of Pittsburgh; Pacific Northwest National Laboratory; Pacific Northwest National Laboratory; Pacific Northwest National Laboratory; Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY; Ankara University, Stem Cell Institute, Ceyhun Atif Kansu St. No: 169 06520 Cevizlidere/ANKARA/TURKEY; Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158; Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands; Department of Bioninformatics-BiGCaT, NUTRIM, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, The Netherlands; Maastricht University, Department of Bioinformatics, NUTRIM, Universiteitssingel 60; 6229 ER Maastricht; The Netherlands; Center for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Mangalore 575018, India; Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, 6229 ER Maastricht, The Netherlands; Maastricht University, NUTRIM, Bioinformatics-BiGCaT, PO Box 616, 6200 MD, Maastricht, the Netherlands; Adaptive Oncology, Ontario Institute for Cancer Research, MaRS Centre, 661 University Avenue, Suite 510, Toronto, Ontario, Canada M5G 0A3; Ontario Institute for Cancer Research (OICR), 661 University Ave Suite 510, Toronto, ON M5G 0A3, Canada; NYU Grossman School of Medicine, New York NY 10016 USA; Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada; Ontario Institute for Cancer Research (OICR) (Canada); Ontario Institute for Cancer Research, Department of Computational Biology, MaRS Centre, South Tower, 661 University Avenue, Suite 500, Toronto, Ontario, Canada; NYU Langone Medical Center, New York, USA; Ontario Institute for Cancer Research, MaRS Centre, 661 University Ave, Suite 510, Toronto, Ontario, Canada; EMBL-EBI, Molecular Systems, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD; Reactome, EMBL-EBI, Cambridge, UK; University of Lorraine, INSERM UMR_S 1256, Nutrition, Genetics, and Environmental Risk Exposure (NGERE), Faculty of Medicine of Nancy, F-54000 Nancy, France.; Senior Research Group in Genome Research of Industrial Microorganisms, Center for Biotechnology, Bielefeld University, Universitaetsstrasse 27, 33615 Bielefeld,; Uppsala University - Sweden; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 S.W. Sam Jackson Park Road, Portland, OR 97239-3098, USA; Gladstone Institutes, Institute for Data Science and Biotechnology, 1650 Owens St., San Francisco, CA 94131, USA; Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany); The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK; The University of Manchester, Department of Computer Science, Oxford Road, Manchester, M13 9PL, UK; Heidelberg Institute for Theoretical Studies (HITS), Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany); German Center for Neurodegenerative Diseases (DZNE) Dresden, Tatzberg 41, 01307 Dresden, Germany.; Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany; Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany; Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA; Harvard Medical School, Laboratory of Systems Pharmacology, 200 Longwood Avenue, Boston, MA; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Barcelona Supercomputing Center (BSC), Barcelona, Spain; EMBL-EBI, Molecular Systems, Wellcome Genome Campus, CB10 1SD, Hinxton, UK; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; University of Rome Tor Vergata, Department of Biology, Via della Ricerca Scientifica 1, 00133 Rome, Italy; Heidelberg Univarsity, Institute for Computational Biomedicine, BQ 0053, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany; cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.; University of Massachusetts Boston, Computer Science Department, 100 William T, Morrissey Blvd, Boston, MA 02125; Inria Saclay Ile-de-France; Heidelberg University, Faculty of Medicine and Heidelberg University Hospital, Institute of Computational Biomedicine, Bioquant, 69120 Heidelberg, Germany; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013, Sevilla, Spain.; University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA; University of Nebraska-Lincoln, Department of Biochemistry, 1901 Vine St., Lincoln, NE, 68588, USA; Elsevier, Life Science Department; Elsevier, Professional Services, 1600 John F Kennedy Blvd #1800, Philadelphia, PA 19103; Elsevier, Research Collaborations Unit, 71 Hanley Lane, Jericho, VT 05465; Quadram Institute Bioscience, Rosalind Franklin Road, Norwich Research Park, Norwich, NR4 7UQ, United Kingdom; Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom; Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom; Association EISBM; Inria Saclay - Ile de France, Lifeware group, 91120 Palaiseau, France; Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany; Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France.; cBio Center, Divisions of Biostatistics and Computational Biology, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA.; Oregon Health and Science University, Department of Molecular and Medical Genetics, 3222 SW Research Drive, Mail Code: L103, Portland, Oregon, U.S.A. 97239; Earlham Institute, Norwich Research Park, NR4 7UZ, Norwich, UK; The Roslin Institute, University of Edinburgh EH25 9RG; Sanofi R&D, Translational Sciences, 1 av Pierre Brossolette 91395 Chilly-Mazarin France; University of Lausanne, Lausanne, Switzerland; Interdisciplinary Research Unit Mathematics and Life Sciences, University of Bonn, Germany; University of Rostock, Dept of Systems Biology & Bioinformatics; Department of Bioinformatics-BiGCaT, NUTRIM, Maastricht University, Maastricht, The Netherlands; Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA; Dept. Bioinformatics - BiGCaT, Maastricht University, The Netherlands; Ontario Institute for Cancer Research, Adaptive Oncology Theme, 661 University Ave, Toronto, ON M5G 1M1 Canada; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, UK; Institute for Computational Biomedicine Heidelberg University, Faculty of Medicine, Im Neuenheimer Feld 267, 69120 Heidelberg; Clinical Bioinformatics Area. Fundacion Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio. 41013. Sevilla. Spain.; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Systems Biology Institute, Tokyo Japan; Institut Curie, PSL Research University, Paris, France.; European Institute for Systems Biology and Medicine (EISBM), Vourles, France; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg; -","We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.",systems biology,fuzzy,100,100
 medRxiv,10.1101/2020.10.25.20219048,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.25.20219048,Viral load in community SARS-CoV-2 cases varies widely and temporally,Ann Sarah Walker; Emma Pritchard; Thomas House; Julie V Robotham; Paul J Birrell; Iain Bell; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Ruth Studley; Jodie Hay; Karina-Doris Vihta; Timothy EA Peto; Nicole Stoesser; Philippa C Matthews; David W Eyre; Koen Pouwels; - the COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Manchester; Public Health England; Public Health England; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Glasgow; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load). Of 3,312,159 nose and throat swabs taken 26-April-2020 to 13-March-2021 in the UKs national COVID-19 Infection Survey, 27,902(0.83%) were RT-PCR-positive, 10,317(37%), 11,012(40%) and 6,550(23%) for 3, 2 or 1 of the N, S and ORF1ab genes respectively, with median Ct=29.2 ([~]215 copies/ml; IQR Ct=21.9-32.8, 14-56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity and age. Single-gene positives almost invariably had Ct>30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6,189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4,808(78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody-negative. Community SARS-CoV-2 Ct values could be a useful epidemiological early-warning indicator.
 
@@ -4611,6 +4740,27 @@ Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPublished trials an
 Added value of this studyIn this cohort study representing 40% of the population of England, we investigated whether routine use of hydroxychloroquine prior to the COVID-19 outbreak prevented COVID-19 mortality. Using robust pharmacoepidemiological methods, we found no evidence to support a substantial benefit of hydroxychloroquine in preventing COVID-19 mortality. At the same time, we have shown no significant harm, and this generates the equipoise to justify continuing randomised trials. We have demonstrated in this study that it is feasible to address specific hypotheses about medicines in a rapid and transparent manner to inform interim clinical decision making and support the need for large-scale, randomised trial data.
 
 Implications of all the available evidenceThis is the first study to investigate the ongoing routine use of hydroxychloroquine and risk of COVID-19 mortality in a general population. While we found no evidence of any protective benefit, due to the observational nature of the study, residual confounding remains a possibility. Completion of trials for prevention of severe outcomes is warranted, but prior to the completion of these, we found no evidence to support the use of hydroxychloroquine for prevention of COVID-19 mortality.",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2020.09.05.20188821,2020-09-08,https://medrxiv.org/cgi/content/short/2020.09.05.20188821,Ethnicity and clinical outcomes in COVID-19A Systematic Review and Meta-analysis,Shirley Sze; Daniel Pan; Laura J Gray; Clareece R Nevill; Christopher A Martin; Joshua Nazareth; Jatinder S Minhas; Pip Divall; Kamlesh Khunti; Keith Abrams; Laura B Nellums; Manish Pareek,University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University Hospitals of Leicester NHS Trust; University of Leicester; University of Leicester; University of Nottingham; University of Leicester,"ImportanceThe association of ethnicity with outcomes in patients with COVID-19 is unclear.
+
+ObjectiveTo determine whether the risk of SARS-CoV-2 infection, COVID-19 intensive care unit (ICU) admission and mortality are associated with ethnicity.
+
+Data SourcesWe searched all English language articles published 1st December 2019 - 30th June 2020 within MEDLINE, EMBASE, PROSPERO and the Cochrane library using indexing terms for COVID-19 and ethnicity, as well as manuscripts awaiting peer review on MedRxiv during the same period.
+
+Study SelectionIncluded studies reported original clinical data, disaggregated by ethnicity, on patients with confirmed or suspected COVID-19. We excluded correspondence, area level, modelling and basic science articles. Two independent reviewers screened articles for inclusion. Of 926 identified articles, 35 were included in the meta-analyses.
+
+Data Extraction and SynthesisThe review was conducted according to PRISMA guidelines. Reviewers independently extracted data using a piloted form on: (1) rates of infection, ICU admission and mortality by ethnicity; and (2) unadjusted and adjusted data comparing ethnic minority and White groups. Data were pooled using random effects models.
+
+Main Outcomes and MeasuresOutcomes were: (1) infection with SARS-CoV-2 confirmed on molecular testing; (2) ICU admission; and (3) mortality in COVID-19 confirmed and suspected cases.
+
+Results13,535,562 patients from 35 studies were included in the meta-analyses. Black, Asian and Hispanic individuals had a greater risk of infection compared to White individuals (Black: pooled adjusted RR: 2.06, 95% CI: 1.59-2.67; Asian: 1.35, 95%CI: 1.15-1.59; Hispanic: 1.77, 95% CI: 1.39-2.25). Black individuals were significantly more likely to be admitted to ICU than White individuals (pooled adjusted RR: 1.61, 95% CI: 1.02-2.55). Risk of mortality was similar across ethnicities among hospitalised patients, but increased among Asian and Mixed ethnic groups in the general population.
+
+ConclusionsBlack, Asian and Hispanic ethnic groups are at increased risk of SARS-CoV-2 infection. Black individuals may be more likely to require ICU admission for COVID-19. There may also be disparities in risk of death from COVID-19 at a population level. Our findings are of critical public health importance and should inform policy on minimising SARS-CoV-2 exposure in ethnic minority groups.
+
+KEY POINTSO_ST_ABSQuestionC_ST_ABSIs ethnicity associated with vulnerability to, and outcomes from, coronavirus disease 2019 (COVID-19)?
+
+FindingsIn this systematic review and meta-analysis, rates of infection and outcomes from COVID-19 were compared between ethnic groups. Individuals from Black, Asian and Hispanic ethnicity were significantly more vulnerable to SARS-CoV-2 infection than those of White ethnicity. Black individuals were more likely to need intensive care unit (ICU) admission for COVID-19 than White individuals. Risk of mortality was similar across ethnicities among hospitalised patients, but increased among Asian and Mixed ethnic groups in the general population.
+
+MeaningThere is strong evidence for an increased risk of SARS-CoV-2 infection amongst ethnic minorities, and targeted public health policies are required to reduce this risk.",infectious diseases,fuzzy,100,100
 medRxiv,10.1101/2020.09.02.20185892,2020-09-07,https://medrxiv.org/cgi/content/short/2020.09.02.20185892,Prognostic accuracy of emergency department triage tools for adults with suspected COVID-19: The PRIEST observational cohort study,Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Amanda Loban; Simon Waterhouse; Richard Simmonds; Katie Biggs; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust,"ObjectivesThe World Health Organisation (WHO) and National Institute for Health and Care Excellence (NICE) recommend various triage tools to assist decision-making for patients with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in adults presenting to the emergency department (ED) with suspected COVID-19 infection.
 
 MethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 EDs across the United Kingdom (UK). We collected data from people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment with the following triage tools: the WHO algorithm, NEWS2, CURB-65, CRB-65, PMEWS and the swine flu adult hospital pathway (SFAHP). We used 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.
@@ -4629,15 +4779,6 @@ MethodsIn this analysis of the Bug Watch prospective community cohort study, we
 ResultsThe baseline incidence of cough or fever in the UK is expected to rise rapidly from 154,554 (95%CI 103,083 - 231,725) cases per day in August 2020 to 250,708 (95%CI 181,095 - 347,080) in September, peaking at 444,660 (95%CI 353,084 - 559,988) in December. If 80% of baseline cough or fever cases request tests, average daily UK testing demand would exceed current capacity for five consecutive months (October 2020 to February 2021), with a peak demand of 147,240 (95%CI 73,978 - 239,502) tests per day above capacity in December 2020.
 
 ConclusionsOur results show that current national COVID-19 testing capacity is likely to be exceeded by demand due to baseline cough and fever alone. This study highlights that the UKs response to the COVID-19 pandemic must ensure that a high proportion of people with symptoms request tests, and that testing capacity is immediately scaled up to meet this high predicted demand.",epidemiology,fuzzy,100,100
-medRxiv,10.1101/2020.09.01.20185793,2020-09-03,https://medrxiv.org/cgi/content/short/2020.09.01.20185793,Prognostic accuracy of emergency department triage tools for children with suspected COVID-19: The PRIEST observational cohort study,Katie Biggs; Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Matthew Bursnall; Amanda Loban; Simon Waterhouse; Richard Simmonds; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust,"ObjectivesEmergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection.
-
-MethodsWe undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Childrens Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.
-
-ResultsWe collected data from 1530 children, including 26 (1.7%) with an adverse outcome. C-statistics were 0.80 (95% confidence interval 0.73-0.87) for the WHO algorithm, 0.80 (0.71-0.90) for POPS, 0.76 (0.67-0.85) for COAST, and 0.71 (0.59-0.82) for SFHPC. Using pre-specified thresholds, the WHO algorithm had the highest sensitivity (0.85) and lowest specificity (0.75), but POPS and COAST could optimise sensitivity (0.96 and 0.92 respectively) at the expense of specificity (0.25 and 0.38 respectively) by using a threshold of any score above zero instead of the pre-specified threshold.
-
-ConclusionExisting triage tools have good but not excellent prediction for adverse outcome in children with suspected COVID-19. POPS and COAST could achieve an appropriate balance of sensitivity and specificity for supporting decisions to discharge home by considering any score above zero to be positive.
-
-RegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",emergency medicine,fuzzy,100,100
 medRxiv,10.1101/2020.09.02.20186502,2020-09-03,https://medrxiv.org/cgi/content/short/2020.09.02.20186502,Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection,Thibaut Jombart; Stephane Ghozzi; Dirk Schumacher; Quentin Leclerc; Mark Jit; Stefan Flasche; Felix Greaves; Tom Ward; Rosalind M Eggo; Emily Nightingale; Sophie Meakin; Oliver J Brady; - Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group; Graham Medley; Michael Hohle; John Edmunds,"London School of Hygiene and Tropical Medicine (LSHTM); Department of Epidemiology, Helmholtz Centre for Infection Research, Brunswick, Lower Saxony, Germany; R Epidemics Consortium; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; LSHTM; Joint Biosecurity Centre; Joint Biosecurity Centre; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; LSHTM; London School of Hygiene and Tropical Medicine; ; LSHTM; Department of Mathematics, Stockholm University, Sweden; LSHTM","As several countries gradually release social distancing measures, rapid detection of new localised COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (Automatic Selection of Models and Outlier Detection for Epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterise the main trend in an incidence. We then derive prediction intervals and classify data points outside this interval as outliers, which provides an objective criterion for identifying departures from previous trends. We also provide a method for selecting the optimal breakpoints, used to define how many recent data points are to be excluded from the trend fitting procedure. The analysis of simulated COVID-19 outbreaks suggest ASMODEE compares favourably with a state-of-art outbreak-detection algorithm while being simpler and more flexible. We illustrate our method using publicly available data of NHS Pathways reporting potential COVID-19 cases in England at a fine spatial scale, for which we provide a template automated analysis pipeline. ASMODEE is implemented in the free R package trendbreaker.",health informatics,fuzzy,100,100
 medRxiv,10.1101/2020.09.02.20186817,2020-09-03,https://medrxiv.org/cgi/content/short/2020.09.02.20186817,Revealing the extent of the COVID-19 pandemic in Kenya based on serological and PCR-test data,John Ojal; Samuel PC Brand; Vincent Were; Emelda A Okiro; Ivy Kadzo Kombe; Caroline Mburu; Rabia Aziza; Morris Ogero; Ambrose Agweyu; George M Warimwe; Sophie Uyoga; Ifedayo M. O Adetifa; John Anthony Scott; Edward Otieno; Lynette I Ochola-Oyier; Charles Nyaigoti Agoti; Kadondi Kasera; Patrick Amoth; Mercy Mwangangi; Rashid Aman; Wangari Ng'ang'a; Benjamin Tsofa; Philip Bejon; Edwine Barasa; Matt J Keeling; D James Nokes,"Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya and London School of Hygiene and Tropical Medicine; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, UK.; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; KEMRI-Wellcome Trust Research Programme; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, UK.; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; KEMRI-Wellcome Trust Research Programme; KEMRI Wellcome Trust Research Programme; KEMRI-Wellcome Trust Research Programme; London School of Hygiene & Tropical Medicine; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; Ministry of Health, Government of Kenya, Kenya; Ministry of Health, Government of Kenya, Kenya; Ministry of Health, Government of Kenya, Kenya; Ministry of Health, Government of Kenya, Kenya; Presidential Policy & Strategy Unit, The Presidency, Government of Kenya; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; Kenya Medical Research Institute -Wellcome Trust Research Programme, Kenya; KEMRI-Wellcome Trust Research Programme; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, UK; KEMRI-Wellcome Trust Research Programme, Kenya and School of Life Sciences, University of Warwick, UK","Policy makers in Africa need robust estimates of the current and future spread of SARS-CoV-2. Data suitable for this purpose are scant. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya. We estimate that the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 34 - 41% of residents infected, and will peak elsewhere in the country within 2-3 months. Despite this penetration, reported severe cases and deaths are low. Our analysis suggests the COVID-19 disease burden in Kenya may be far less than initially feared. A similar scenario across sub-Saharan Africa would have implications for balancing the consequences of restrictions with those of COVID-19.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2020.09.01.20183822,2020-09-02,https://medrxiv.org/cgi/content/short/2020.09.01.20183822,Trust and Transparency in times of Crisis: Results from an Online Survey During the First Wave (April 2020) of the COVID-19 Epidemic in the UK,Luisa Enria; Naomi Waterlow; Nina Trivedy Rogers; Hannah Brindle; Sham Lal; Rosalind M Eggo; Shelley Lees; Chrissy h Roberts,London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; UCL; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine (LSHTM),"BackgroundThe success of a governments COVID-19 control strategy relies on public trust and broad acceptance of response measures. We investigated public perceptions of the UK governments COVID-19 response, focusing on the relationship between trust and transparency, during the first wave (April 2020) of the COVID-19 pandemic in the United Kingdom.
@@ -4716,6 +4857,7 @@ MethodsWe developed a simple, interactive tool to assess the impact of different
 ResultsWith sensitivity of 80%, infection prevalence of 1 in 2,000, and specificity 99.9% on all tests, PPV in the tested population of 100,000 will be only 29% with one test, increasing to > 99.5% (100% when rounded to the nearest %) with repeat testing in strategies 2 or 3. More realistically, if specificity is 95% for the first and 99.9% for subsequent tests, single test PPV will be only 1%, increasing to 86% with repeat testing in strategy 2, or 79% with strategy 3 (albeit with 6 fewer false negatives than strategy 2). In the whole population, or in particular individuals, PPV increases as infection becomes more common in the population but falls to unacceptably low levels with lower test specificity.
 
 ConclusionTo avoid multiple unnecessary restrictions on whole populations, and in particular individuals, from widespread population testing for SARS-CoV-2, the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions.",epidemiology,fuzzy,100,100
+medRxiv,10.1101/2020.08.17.20175117,2020-08-21,https://medrxiv.org/cgi/content/short/2020.08.17.20175117,Real-time spatial health surveillance: mapping the UK COVID-19 epidemic,Richard Fry; Joe Hollinghurst; Helen R Stagg; Daniel A Thompson; Claudio Fronterre; Chris Orton; Ronan A Lyons; David V Ford; Aziz Sheikh; Peter J Diggle,Swansea University; Swansea University; Edinburgh University; Swansea University; Lancaster University; Swansea University; Swansea University; Swansea University; Edinburgh University; Lancaster University,"The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. A pre-requisite to an effective control strategy is that predictions need to be accompanied by estimates of their precision, to guard against over-reaction to potentially spurious features of  best guess predictions. In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.",public and global health,fuzzy,100,100
 medRxiv,10.1101/2020.08.17.20161760,2020-08-19,https://medrxiv.org/cgi/content/short/2020.08.17.20161760,"SARS-CoV-2 (COVID-19) infection in pregnant women: characterization of symptoms and syndromes predictive of disease and severity through real-time, remote participatory epidemiology.",Erika Molteni; Christina M Astley; Wenjie Ma; Carole Helene Sudre; Laura A Magee; Benjamin Murray; Tove Fall; Maria F Gomez; Neli Tsereteli; Paul W Franks; John S Brownstein; Richard Davies; Jonathan Wolf; Timothy Spector; Sebastien Ourselin; Claire Steves; Andrew T Chan; Marc Modat,"King's College London; Boston Children's Hospital and Harvard Medical School; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA; King's College London; Department of Women and Childrens Health, School of Life Course Sciences and the Institute of Women and Childrens Health, Kings College London, London, United K; School of Biomedical Engineering & Imaging Sciences, Kings College London, London, United Kingdom; Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Sweden; Department of Clinical Sciences, Lund University Diabetes Centre, Jan Waldenstroems gata 35, SE-21428, Malmo, Sweden; Department of Clinical Sciences, Lund University Diabetes Centre, Jan Waldenstroems gata 35, SE-21428, Malmo, Sweden; Department of Clinical Sciences, Lund University Diabetes Centre, Jan Waldenstroems gata 35, SE-21428, Malmo, Sweden.; Boston Childrens Hospital and Harvard Medical School, Boston, MA, USA; Zoe Global Limited, London, United Kingdom; Zoe Global Limited, London, United Kingdom; King's College London; School of Biomedical Engineering & Imaging Sciences, Kings College London, London, United Kingdom; King's College London; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA; School of Biomedical Engineering & Imaging Sciences, Kings College London, London, United Kingdom","BackgroundFrom the beginning of COVID-19 pandemic, pregnant women have been considered at greater risk of severe morbidity and mortality. However, data on hospitalized pregnant women show that the symptom profile and risk factors for severe disease are similar to those among women who are not pregnant, although preterm birth, Cesarean delivery, and stillbirth may be more frequent and vertical transmission is possible. Limited data are available for the cohort of pregnant women that gave rise to these hospitalized cases, hindering our ability to quantify risk of COVID-19 sequelae for pregnant women in the community.
 
 ObjectiveTo test the hypothesis that pregnant women in community differ in their COVID-19 symptoms profile and disease severity compared to non-pregnant women. This was assessed in two community-based cohorts of women aged 18-44 years in the United Kingdom, Sweden and the United States of America.
@@ -5010,6 +5152,21 @@ ConclusionsIn patients hospitalized with COVID-19, hydroxychloroquine was not as
 FundingMedical Research Council and NIHR (Grant ref: MC_PC_19056).
 
 Trial registrationsThe trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).",infectious diseases,fuzzy,100,100
+medRxiv,10.1101/2020.07.13.20152793,2020-07-14,https://medrxiv.org/cgi/content/short/2020.07.13.20152793,At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR based tests?: A systematic review of individual participant data,Sue Mallett; Joy Allen; Sara Graziadio; Stuart A Taylor; Naomi S Sakai; Kile Green; Jana Suklan; Chris Hyde; Bethany Shinkins; Zhivko Zhelev; Jaime Peters; Philip Turner; Nia W Roberts; Lavinia Ferrante di Ruffano; Robert Wolff; Penny Whiting; Amanda Winter; Gauraang Bhatnagar; Brian D Nicholson; Steve Halligan,"University College London, UK; Newcastle University, UK; Newcastle upon Tyne Hospitals NHS Foundation Trust, UK; University College London, UK; University College London, UK; Newcastle University, UK; Newcastle University, UK; University of Exeter, UK; University of Leeds, UK; University of Exeter, UK; University of Exeter, UK; University of Oxford, UK; University of Oxford, UK; University of Birmingham, UK; Kleijnen Systematic Reviews Ltd, UK; University of Bristol, UK; Newcastle University, UK; Frimley Health NHS Foundation Trust, UK; University of Oxford, UK; University College London, UK","STRUCTURED SUMMARYO_ST_ABSBackgroundC_ST_ABSTests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA), using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity.
+
+MethodsWe conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS- 2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites.
+
+FindingsOf 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from -6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 to 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post- symptom onset.
+
+InterpretationRT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond ten days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias so the positivity rates are probably overestimated.
+
+PANEL: RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThere are numerous reports of negative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcription polymerase chain reaction (RT-PCR) test results in participants with known SARS-CoV-2 infection, and increasing awareness that the ability of RT-PCR tests to detect virus depends on the timing of sample retrieval and anatomical sampling site.
+
+Individual studies suggest that positive test results from RT-PCR with nasopharyngeal sampling declines within a week of symptoms and that a positive test later in the disease course is more likely from sputum, bronchoalveolar lavage (BAL) or stool, but data are inconsistent.
+
+Added value of this studyWe searched 5078 titles and abstracts for longitudinal studies reporting individual participant data (IPD) for RT-PCR for participants with COVID-19 linked to either time since symptom onset or time since hospitalisation. Search included SARS-CoV-2 and RT-PCR keywords and MeSH terms. Each included study was subject to careful assessment of risk of bias. This IPD systematic review (SR) addresses RT-PCR test detection rates at different times since symptom onset and hospitalisation for different sampling sites, and summarises the duration of detectable virus. To our knowledge, this is the first rapid SR addressing this topic. We identified 32 studies available as published articles or pre-prints between January 1st and April 24th 2020, including participants sampled at 11 different sampling sites and some participants sampled at more than one site. At earlier time points, nasopharyngeal sampling had the highest virus detection, but the duration of shedding was shorter compared to lower respiratory tract sampling. At 10 to 14 days post-symptom onset, the percentage of positive nasopharyngeal test results was 54% compared to 89% at day 0 to 4. Presence and duration of faecal detection varied by participant, and in nearly half duration was shorter than respiratory sample detection. Virus detection varies for participants and can continue to be detected up to 46 days post-symptom onset or hospitalisation. The included studies were open to substantial risk of bias, so the detection rates are probably overestimates. There was also poor reporting of sampling methods and sparse data on sampling methods that are becoming more widely implemented, such as self-sampling and short nasal swab sampling (anterior nares/mid turbinate).
+
+Implications of all the available evidenceResults from this IPD SR of SARS-CoV-2 testing at different time points and using different anatomical sample sites are important to inform strategies of testing. For prevention of ongoing transmission of SARS-CoV-2, samples for RT-PCR testing need to be taken as soon as possible post-symptom onset, as we confirm that RT-PCR misses more people with infection if sampling is delayed. The percentage of positive RT-PCR tests is also highly dependent on the anatomical site sampled in infected people. Sampling at more than one anatomical site may be advisable as there is variation between individuals in the sites that are infected, as well as the timing of SARS-CoV-2 virus detection at an anatomical site. Testing ten days after symptom onset will lead to a higher frequency of negative tests, particularly if using only upper respiratory tract sampling. However, our estimates may considerably understate the frequency of negative RT-PCR results in people with SARS-CoV- 2 infection. Further investment in this IPD approach is recommended as the amount data available was small given the scale of the pandemic and the importance of the question. More studies, learning from our observations about risk of bias and strengths of example studies (Box 1, Box 2) are urgently needed to inform the optimal sampling strategy by including self-collected samples such as saliva and short nasal swabs. Better reporting of anatomical sampling sites with a detailed methodology on sample collection is also urgently needed.",infectious diseases,fuzzy,92,100
 medRxiv,10.1101/2020.07.13.20152710,2020-07-14,https://medrxiv.org/cgi/content/short/2020.07.13.20152710,Excess mortality in mental health service users during the COVID-19 pandemic described by ethnic group: South London and Maudsley data,Robert Stewart; Matthew Broadbent; Jayati Das-Munshi,King's College London; South London and Maudsley NHS Foundation Trust; King's College London,"The COVID-19 pandemic in the UK was accompanied by excess all-cause mortality at a national level, only part of which was accounted for by known infections. Excess mortality has previously been described in people who had received care from the South London and Maudsley NHS Foundation Trust (SLaM), a large mental health service provider for 1.2m residents in south London. SLaMs Clinical Record Interactive Search (CRIS) data resource receives 24-hourly updates from its full electronic health record, including regularly sourced national mortality on all past and present SLaM service users. SLaMs urban catchment has high levels of deprivation and is ethnically diverse, so the objective of the descriptive analyses reported in this manuscript was to compare mortality in SLaM service users from 16th March to 15th May 2020 to that for the same period in 2019 within specific ethnic groups: i) White British, ii) Other White, iii) Black African/Caribbean, iv) South Asian, v) Other, and vi) missing/not stated. For Black African/Caribbean patients (the largest minority ethnic group) this ratio was 3.33, compared to 2.47 for White British patients. Considering premature mortality (restricting to deaths below age 70), these ratios were 2.74 and 1.96 respectively. Ratios were also high for those from Other ethnic groups (2.63 for all mortality, 3.07 for premature mortality).",psychiatry and clinical psychology,fuzzy,100,100
 medRxiv,10.1101/2020.07.11.20147157,2020-07-14,https://medrxiv.org/cgi/content/short/2020.07.11.20147157,Effects of environmental factors on severity and mortality of COVID-19,Domagoj Kifer; Dario Bugada; Judit Villar-Garcia; Ivan Gudelj; Cristina Menni; Carole Helene Sudre; Frano Vuckovic; Ivo Ugrina; Luca F Lorini; Silvia Bettinelli; Nicola Ughi; Alessandro Maloberti; Oscar Epis; Cristina Giannattasio; Claudio Rossetti; Livije Kalogjera; Jasminka Persec; Luke Ollivere; Benjamin Ollivere; Huadong Yan; Ting Cai; Guruprasad Aithal; Claire Steves; Anu Kantele; Mikael Kajova; Olli Vapalahti; Antti Sajantila; Rafal Wojtowicz; Waldemar Wierzba; Zbigniew Krol; Artur Zaczynski; Katarzyna Zycinska; Marek Postula; Ivica Luksic; Rok Civljak; Alemka Markotic; Christian Mahnkopf; Andreas Markl; Johannes Brachmann; Benjamin Murray; Sebastien Ourselin; Julio Pascual; Ana M Valdes; Margarita Posso; Juan Horcajada; Xavier Castells; Massimo Allegri; Dragan Primorac; Timothy Spector; Clara Barrios; Gordan Lauc,"University of Zagreb; Emergency and Intensive Care Department - ASST Papa Giovanni XXII Hospital - Bergamo - Italy; Hospital del Mar-IMIM, Barcelona, Spain; Genos; King's College London; KCL; Genos; Genos; Emergency and Intensive Care Department - ASST Papa Giovanni XXII Hospital - Bergamo - Italy; Emergency and Intensive Care Department - ASST Papa Giovanni XXII Hospital - Bergamo - Italy; ASST GOM Niguarda; ASST GOM Niguarda; ASST GOM Niguarda; ASST GOM Niguarda; ASST GOM Niguarda; School of Medicine, University Hospital ""Sestre milosrdnice"" Zagreb, Croatia; University Hospital Dubrava Zagreb, Croatia, University of Zagreb School of Dental Medicine; Nottingham University Trust; University of Nottingham, School of Medicine; Department of Infectious Diseases, Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, Hwamei Hospital, University of Chi; Hwa Mei Hospital, University of Chinese Academy of Sciences; School of Medicine, University of Nottingham; King's College London; Inflammation Centre, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Inflammation Centre, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; University of Helsinki; Department of Forensic Medicine, University of Helsinki, Finland; Central Clinical Hospital of the Ministry of the Interior and Administration in Warsaw, Poland; Central Clinical Hospital of the Ministry of the Interior and Administration in Warsaw, Poland; Central Clinical Hospital of the Ministry of the Interior and Administration in Warsaw, Poland; Central Clinical Hospital of the Ministry of the Interior and Administration in Warsaw, Poland; Medical University of Warsaw, Warsaw, Poland; Medical University of Warsaw, Warsaw, Poland; Clinical Hospital Dubrava, Zagreb; Hospital for Infectious Diseases, Zagreb, Croatia; Hospital for Infectious Diseases; REGIOMED-KLINIKEN GmbH, Gustav-Hirschfeld-Ring 3, 96450 Coburg, Germany; REGIOMED-KLINIKEN GmbH, Gustav-Hirschfeld-Ring 3, 96450 Coburg, Germany; REGIOMED Kliniken; School of Biomedical Engineering & Imaging Sciences, King's College London; School of Biomedical Engineering & Imaging Sciences, King's College London; Department of Nephrology, Hospital del Mar, Barcelona, Spain; University of Nottingham, School of Medicine, Nottingham NIHR BRC; Department of Epidemiology and Evaluation, Hospital del Mar-IMIM, Barcelona, Spain; Department of Infectious Diseases, Hospital del Mar. Barcelona, Spain; Department of Epidemiology and Evaluation, Hospital del Mar-IMIM, Barcelona, Spain; Pain Therapy Service Policlinico of Monza Hospital - Monza Italy & Italian Pain Group - Milan - Italy; St. Catherine Hospital; King's College London; Hospital del Mar. Barcelona, Spain; University of Zagreb","BackgroundMost respiratory viruses show pronounced seasonality, but for SARS-CoV-2 this still needs to be documented.
 
@@ -5266,15 +5423,6 @@ C_LI
 What do these findings mean?O_LIIndividuals with [&ge;]2 LTCs, especially if these are cardiometabolic in nature, should be particularly stringent in adhering to preventive measures, such as physical distancing and hand hygiene.
 C_LIO_LIOur findings have implications for clinicians, occupational health and employers when considering work-place environments, appropriate advice for patients, and adaptations that might be required to protect such staff, identified here, as higher risk.
 C_LI",epidemiology,fuzzy,100,91
-medRxiv,10.1101/2020.06.10.20127175,2020-06-11,https://medrxiv.org/cgi/content/short/2020.06.10.20127175,Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic.,Amitava Banerjee; Suliang Chen; Laura Pasea; Alvina Lai; Michail Katsoulis; Spiros Denaxas; Vahe Nafilyan; Bryan Williams; Wai Keong Wong; Ameet Bakhai; Kamlesh Khunti; Deenan Pillay; Mahdad Noursadeghi; Honghan Wu; Nilesh Pareek; Daniel Bromage; Theresa Mcdonagh; Jonathan Byrne; James T Teo; Ajay Shah; Ben Humberstone; Liang V Tang; Anoop SV Shah; Andrea Rubboli; Yutao Guo; Yu Hu; Cathie LM Sudlow; Gregory YH Lip; Harry Hemingway,"University College London; University College London; University College London; University College London; UCL; University College London; Office for National Statistics; UCL; University College London Hospitals NHS Trust; Royal Free Hospitals NHS Trust; University of Leicester; UCL; UCL; UCL; King's College Hospital; Kings College London; Kings College London; Kings London NHS Trust; Kings College Hospital NHS Foundation Trust; King's College London; Office for National Statistics; Huazhong University of Science and Technology, Wuhan, China; University of Edinburgh; Ospedale S. Maria delle Croci, Ravenna, Italy; PLA General Hospital, Beijing, China.; Huazhong University of Science and Technology, Wuhan, China.; University of Edinburgh; University of Liverpool; UCL","BackgroundCardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both ""direct"", through infection, and ""indirect"", through changes in healthcare.
-
-MethodsWe used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(""direct"" effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For ""indirect"" effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020.
-
-FindingsCVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths.
-
-InterpretationSupply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic.
-
-FundingNIHR, HDR UK, Astra Zeneca",cardiovascular medicine,fuzzy,100,100
 bioRxiv,10.1101/2020.06.11.145920,2020-06-11,https://biorxiv.org/cgi/content/short/2020.06.11.145920,SARS-CoV-2 mRNA Vaccine Development Enabled by Prototype Pathogen Preparedness,Kizzmekia S. Corbett; Darin Edwards; Sarah R. Leist; Olubukola M. Abiona; Seyhan Boyoglu-Barnum; Rebecca A. Gillespie; Sunny Himansu; Alexandra Schafer; Cynthia T. Ziwawo; Anthony T. DiPiazza; Kenneth H. Dinnon; Sayda M. Elbashir; Christine A. Shaw; Angela Woods; Ethan J. Fritch; David R. Martinez; Kevin W. Bock; Mahnaz Minai; Bianca M. Nagata; Geoffrey B. Hutchinson; Kapil Bahl; Dario Garcia-Dominguez; LingZhi Ma; Isabella Renzi; Wing-Pui Kong; Stephen D. Schmidt; Lingshu Wang; Yi Zhang; Laura J. Stevens; Emily Phung; Lauren A. Chang; Rebecca J. Loomis; Nedim Emil Altaras; Elisabeth Narayanan; Mihir Metkar; Vlad Presnyak; Catherine Liu; Mark K. Louder; Wei Shi; Kwanyee Leung; Eun Sung Yang; Ande West; Kendra L. Gully; Nianshuang Wang; Daniel Wrapp; Nicole A. Doria-Rose; Guillaume Stewart-Jones; Hamilton Bennett; Martha C. Nason; Tracy J. Ruckwardt; Jason S. McLellan; Mark R. Denison; James D. Chappell; Ian N. Moore; Kaitlyn M. Morabito; John R. Mascola; Ralph S. Baric; Andrea Carfi; Barney S Graham,"Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Moderna, Inc.; Department of Epidemiology; University of North Carolina at Chapel Hill; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Moderna, Inc.; Department of Epidemiology; University of North Carolina at Chapel Hill; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Department of Epidemiology; University of North Carolina at Chapel Hill; Moderna, Inc.; Moderna, Inc.; Moderna, Inc.; Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill; Department of Epidemiology; University of North Carolina at Chapel Hill; National Institute of Allergy and Infectious Diseases; National Institutes of Health; National Institute of Allergy and Infectious Diseases; National Institutes of Health; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Moderna, Inc.; Moderna, Inc.; Moderna, Inc.; Moderna, Inc.; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Department of Pediatrics, Vanderbilt University Medical Center; Institute for Biomedical Sciences, George Washington University; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Moderna, Inc.; Moderna, Inc.; Moderna, Inc.; Moderna, Inc.; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Department of Epidemiology; University of North Carolina at Chapel Hill; Department of Epidemiology; University of North Carolina at Chapel Hill; Department of Molecular Biosciences; University of Texas at Austin; Department of Molecular Biosciences; University of Texas at Austin; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Moderna, Inc.; Moderna, Inc.; Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Department of Molecular Biosciences; University of Texas at Austin; Department of Pediatrics, Vanderbilt University Medical Center; Department of Pediatrics, Vanderbilt University Medical Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Vaccine Research Center; National Institute of Allergy and Infectious Diseases; National Institutes of Health; Department of Epidemiology; University of North Carolina at Chapel Hill; Department of Microbiology and Immunology, School of Medicine, University of North Caro; Moderna, Inc.; Vaccine Research Center, NIAID, NIH","A SARS-CoV-2 vaccine is needed to control the global COVID-19 public health crisis. Atomic-level structures directed the application of prefusion-stabilizing mutations that improved expression and immunogenicity of betacoronavirus spike proteins. Using this established immunogen design, the release of SARS-CoV-2 sequences triggered immediate rapid manufacturing of an mRNA vaccine expressing the prefusion-stabilized SARS-CoV-2 spike trimer (mRNA-1273). Here, we show that mRNA-1273 induces both potent neutralizing antibody and CD8 T cell responses and protects against SARS-CoV-2 infection in lungs and noses of mice without evidence of immunopathology. mRNA-1273 is currently in a Phase 2 clinical trial with a trajectory towards Phase 3 efficacy evaluation.",immunology,fuzzy,96,94
 medRxiv,10.1101/2020.06.08.20120584,2020-06-09,https://medrxiv.org/cgi/content/short/2020.06.08.20120584,SARS-CoV-2 virus and antibodies in front-line Health Care Workers in an acute hospital in London: preliminary results from a longitudinal study,Catherine Houlihan; Nina Vora; Thomas Byrne; Dan Lewer; Judith Heaney; David A Moore; Rebecca Matthews; Sajida Adam; Louise Enfield; Abigail Severn; Angela McBride; Moira Jane Spyer; Rupert Beale; Peter Cherepanov; Kathleen Gaertner; Maryam Shahmanesh; - The SAFER Field Study Team; Kevin Ng; Georgina Cornish; Naomi Walker; Susan Michie; Ed Manley; Fabiana Lorencatto; - The Crick-COVID-Consortium; Richard Gilson; Sonia Gandhi; Steve Gamblin; George Kassiotis; Laura McCoy; Charles Swanton; Andrew Hayward; Eleni Nastouli,University College London Hospital; UCL; UCL; University College London; UCL; Francis Crick Institute; UCL; UCL; UCL; UCL; UCL; UCL; Francis Crick Institute; Francis Crick Institute; UCL; UCL; ; Francis Crick Institute; Francis Crick Institute; UCL; UCL; Leeds University; UCL; ; UCL; Francis Crick Institute; Francis Crick Institute; Francis Crick Institute; UCL; Francis Crick Institute; UCL; University College London,"BackgroundAlthough SARS-CoV-2 infection in Healthcare Workers (HCWs) is a public health concern, there is little description of their longitudinal antibody response in the presence or absence of SARS-CoV-2 and symptoms. We followed HCWs in an acute London hospital to measure seroconversion and RNA detection at the peak of the pandemic.
 
@@ -5509,9 +5657,6 @@ RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe interaction bet
 Added value of this studyData from a large UK population who are users of a symptom reporting app during the pandemic supports the hypothesis that smokers are more likely to develop symptoms consistent with COVID-19 and that they have an increased symptom burden.
 
 Implications of all the available evidenceThese population data, combined with evidence of a worse outcome in smokers hospitalised with the condition, support the contention that smoking increases individual risk from COVID-19. Support to help people to quit smoking should therefore form part of efforts to deal with the pandemic.",respiratory medicine,fuzzy,94,100
-medRxiv,10.1101/2020.05.14.20101824,2020-05-19,https://medrxiv.org/cgi/content/short/2020.05.14.20101824,Changing travel patterns in China during the early stages of the COVID-19 pandemic,Hamish Gibbs; Yang Liu; Carl AB Pearson; Christopher I Jarvis; Chris Grundy; Billy J Quilty; Charlie Diamond; Rosalind M Eggo,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigated the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020 and discussed their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower access to care. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and have not yet led to structural reorganisation of the transportation network at the time of this study.
-
-One sentence summaryUnderstanding travel before, during, and after the introduction of travel restrictions in China in response to the COVID-19 Pandemic.",public and global health,fuzzy,100,100
 medRxiv,10.1101/2020.05.11.20098269,2020-05-18,https://medrxiv.org/cgi/content/short/2020.05.11.20098269,Accessibility and allocation of public parks and gardens during COVID-19 social distancing in England and Wales,Niloofar Shoari; Majid Ezzati; Jill Baumgartner; Diego Malacarne; Daniela Fecht,Imperial College London; Imperial College London; McGill University; Imperial College London; Imperial College London,"Visiting parks and gardens may attenuate the adverse physical and mental health impacts of social distancing implemented to reduce the spread of COVID-19. We quantified access to public parks and gardens in urban areas of England and Wales, and the potential for park crowdedness during periods of high use. We combined data from the Office for National Statistics and Ordnance Survey to quantify (i) the number of parks within 500 and 1,000 metres of urban postcodes (i.e., availability), (ii) the distance of postcodes to the nearest park (i.e., accessibility), and (iii) per-capita space in each park for people living within 1,000m. We examined how these measures vary by city and share of homes that are flats. Around 25.4 million people can access public parks or gardens within a ten-minute walk, while 3.8 million residents live farther away; of these 21% are children and 13% are elderly. Areas with a higher share of flats on average are closer to a park but people living in these areas are potentially less able to meet social distancing requirements while in parks during periods of high use. Cities in England and Wales can provide residents with access to green space that enables outdoor exercise and play during social distancing. Cities aiming to facilitate social distancing while keeping public green spaces open might require implementing measures such as dedicated park times for different age groups or entry allocation systems that, combined with smartphone apps or drones, can monitor and manage the total number of people using the park.",public and global health,fuzzy,100,100
 medRxiv,10.1101/2020.05.12.20098921,2020-05-18,https://medrxiv.org/cgi/content/short/2020.05.12.20098921,Behavioural change towards reduced intensity physical activity is disproportionately prevalent among adults with serious health issues or self-perception of high risk during the UK COVID-19 lockdown.,Nina Trivedy Rogers; Naomi Waterlow; Hannah E Brindle; Luisa Enria; Rosalind M Eggo; Shelley Lees; Chrissy h Roberts,University College London (UCL); London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Bath; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine,"ImportanceThere are growing concerns that the UK COVID-19 lockdown has reduced opportunities to maintain health through physical activity, placing individuals at higher risk of chronic disease and leaving them more vulnerable to severe sequelae of COVID-19.
 
@@ -5784,6 +5929,13 @@ C_LIO_LIRisk stratification was improved by the addition of routinely-measured b
 C_LIO_LIThis improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites.
 C_LIO_LIWe benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches.
 C_LI",infectious diseases,fuzzy,100,100
+bioRxiv,10.1101/2020.04.28.066977,2020-04-29,https://biorxiv.org/cgi/content/short/2020.04.28.066977,"Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world",Jody Phelan; Wouter Deelder; Daniel Ward; Susana Campino; Martin L Hibberd; Taane G Clark,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines.
+
+MethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure.
+
+ResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades.
+
+ConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.",genomics,fuzzy,100,100
 medRxiv,10.1101/2020.04.23.20076521,2020-04-27,https://medrxiv.org/cgi/content/short/2020.04.23.20076521,"Geo-social gradients in predicted COVID-19 prevalence and severity in Great Britain: results from 2,266,235 users of the COVID-19 Symptoms Tracker app",Ruth Bowyer; Thomas Varsavsky; Carole H Sudre; Benjamin Murray; Maxim Freidin; Darioush Yarand; Sajaysurya Ganesh; Joan Capdevila; Ellen J Thompson; Elco Bakker; M Jorge Cardoso; Richard Davies; Jonathan Wolf; Tim D Spector; Sebastien Ourselin; Claire J Steves; Cristina Menni,King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; Zoe Global Limited; Zoe Global Limited; King's College London; Zoe Global Limited; King's College London; King's College London; Zoe Global Limited; King's College London; King's College London; King's College London; King's College London,"Understanding the geographical distribution of COVID-19 through the general population is key to the provision of adequate healthcare services. Using self-reported data from 2,266,235 unique GB users of the COVID Symptom Tracker app, we find that COVID-19 prevalence and severity became rapidly distributed across the UK within a month of the WHO declaration of the pandemic, with significant evidence of ""urban hot-spots"". We found a geo-social gradient associated with disease severity and prevalence suggesting resources should focus on urban areas and areas of higher deprivation. Our results demonstrate use of self-reported data to inform public health policy and resource allocation.",epidemiology,fuzzy,100,100
 medRxiv,10.1101/2020.04.22.20075663,2020-04-27,https://medrxiv.org/cgi/content/short/2020.04.22.20075663,Ethnic and socioeconomic differences in SARS-CoV2 infection in the UK Biobank cohort study,Claire L Niedzwiedz; Bhautesh D Jani; Evangelia Demou; Frederick K Ho; Carlos Celis-Morales; Barbara I Nicholl; Frances Mair; Paul Welsh; Naveed Sattar; Jill Pell; Srinivasa Vittal Katikireddi,University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University Of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow,"BackgroundUnderstanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study.
 
@@ -6007,12 +6159,3 @@ Added value of this studyThis study uses a mathematical model to assess the feas
 
 Implications of all the available evidenceContact tracing and isolation may not contain outbreaks of 2019-nCoV unless very high levels of contact tracing are achieved. Even in this case, if there is asymptomatic transmission, or a high fraction of transmission before onset of symptoms, this strategy may not achieve control within three months.",public and global health,fuzzy,100,100
 medRxiv,10.1101/2020.01.31.20019265,2020-02-02,https://medrxiv.org/cgi/content/short/2020.01.31.20019265,Effectiveness of airport screening at detecting travellers infected with 2019-nCoV,Billy Quilty; Sam Clifford; Stefan Flasche; Rosalind M Eggo,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"As the number of novel coronavirus cases grows both inside and outside of China, public health authorities require evidence on the effectiveness of control measures such as thermal screening of arrivals at airports. We evaluated the effectiveness of exit and entry screening for 2019-nCoV infection. In our baseline scenario, we estimated that 46.5% (95%CI: 35.9 to 57.7) of infected travellers would not be detected, depending on the incubation period, sensitivity of exit and entry screening, and the proportion of cases which are asymptomatic. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers. We developed an online tool so that results can be updated as new information becomes available.",epidemiology,fuzzy,100,100
-medRxiv,10.1101/2020.01.31.20019901,2020-02-02,https://medrxiv.org/cgi/content/short/2020.01.31.20019901,Early dynamics of transmission and control of 2019-nCoV: a mathematical modelling study,Adam J Kucharski; Timothy W Russell; Charlie Diamond; Yang Liu; CMMID nCoV working group; John Edmunds; Sebastian Funk; Rosalind M Eggo,London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine,"BackgroundAn outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.
-
-MethodsWe combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas.
-
-FindingsWe estimated that the median daily reproduction number, Rt, declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.
-
-InterpretationOur results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually.
-
-FundingWellcome Trust (206250/Z/17/Z, 210758/Z/18/Z), HDR UK (MR/S003975/1), Gates Foundation (INV-003174), NIHR (16/137/109)",infectious diseases,fuzzy,100,100
diff --git a/data/covid/preprints.exact.csv b/data/covid/preprints.exact.csv
index 93502485..0ee2cf63 100644
--- a/data/covid/preprints.exact.csv
+++ b/data/covid/preprints.exact.csv
@@ -141,6 +141,27 @@ C_LIO_LIThe use of an additional control group from the general public for compa
 C_LIO_LIIn the subgroup analyses, PCR+ cases and PCR- controls were compared with the population controls to assess the risk factors for those aged 18-55 years. Hence, the results may not be generalisable to patients older than 55 years.
 C_LIO_LIPCR test results, rather than symptoms, were used to categorise the participants into cases or controls, and therefore risk factors for SARS-CoV-2 infection and not COVID-19 disease were assessed.
 C_LI",infectious diseases,exact,100,100
+medRxiv,10.1101/2023.03.15.23287292,2023-03-15,https://medrxiv.org/cgi/content/short/2023.03.15.23287292,Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic,Eoin McElroy; Emily Herrett; Kishan Patel; Dominik M Piehlmaier; Giorgio Di Gessa; Charlotte Huggins; Michael J Green; Alex SF Kwong; Ellen J Thompson; Jingmin Zhu; Kathryn E Mansfield; Richard J Silverwood; Rosie Mansfield; Jane Maddock; Rohini Mathur; Ruth E Costello; Anthony A Matthews; John Tazare; Alasdair Henderson; Kevin Wing; Lucy Bridges; Sebastian Bacon; Amir Mehrkar; - OpenSafely Collaborative; Richard John Shaw; Jacques Wels; Srinivasa Vittal Katikireddi; Nishi Chaturvedi; Laurie Tomlinson; Praveetha Patalay,"School of Psychology, Ulster University, Coleraine, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; University of Sussex Business Sch; Department of Epidemiology & Public Health, University College London, London, UK; Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Division of Psychiatry, University of Edinburgh, Edinburgh, UK; Department of Twin Research and Genetic Epidemiology, Kings College London; Department of Epidemiology & Public Health, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Centre for Longitudinal Studies, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Primary Care, Wolfson Insitute of Population Health, Queen Mary, University of London, London; London School of Hygiene and Tropical Medicine, London, UK; Karolinska Institutet, Stockholm, Sweden; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; ; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK","ObjectivesTo describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap.
+
+DesignTen population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs).
+
+SettingUK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database.
+
+ParticipantsParticipants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people.
+
+Main outcome measuresIn the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses.
+
+ResultsThe LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed.
+
+ConclusionsMultiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.
+
+Summary BoxO_ST_ABSWhat is already known on the topic?C_ST_ABSHouseholds with one individual are an increasing demographic, comprising over a quarter of all households in the UK in 2021. However, the mental health gap between those who live alone compared to those who live with others is not well described and even less is known about the relative gaps in need and healthcare-seeking and access. The pandemic and associated restrictive measures further increased the likelihood of isolation for this group, which may have impacted mental health.
+
+What this study adds?We present comprehensive evidence from both population-based surveys and electronic health records regarding the greater levels of mental health symptoms and in recorded diagnoses for common (anxiety, depression) and less common (OCD, eating disorders, SMIs) mental health conditions for people living alone compared to those living with others.
+
+Our analyses indicate that mental health conditions are more common among those who live alone compared to those who live with others. Although levels of reported distress increased for both groups during the pandemic, healthcare-seeking dropped in both groups, and the rates of healthcare-seeking among those who live alone converged with those who live with others for common mental health conditions. This suggests greater barriers for treatment access among those that live alone.
+
+The findings have implications for mental health service planning and efforts to reduce barriers to treatment access, especially for individuals who live on their own.",psychiatry and clinical psychology,exact,100,100
 medRxiv,10.1101/2023.02.26.23286474,2023-03-06,https://medrxiv.org/cgi/content/short/2023.02.26.23286474,Improving the representativeness of UKs national COVID-19 Infection Survey through spatio-temporal regression and post-stratification,Koen B Pouwels; David W Eyre; Thomas House; Ben Aspey; Philippa C Matthews; Nicole Stoesser; John Newton; Ian Diamond; Ruth Studley; Nick Taylor; John Bell; Jeremy Farrar; Jaison Kolenchery; Brian Marsden; Sarah Hoosdally; Yvonne Jones; David Stuart; Derrick Crook; tim E peto; Ann Sarah Walker; - COVID-19 Infection Survey Team,University of Oxford; University of Oxford; University of Manchester; Office for National Statistics; The Francis Crick Institute; University of Oxford; University of Exeter; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; oxford university; University of Oxford; -,"Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we use spatio-temporal regression and post-stratification models to UKs national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21%), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.",infectious diseases,exact,100,100
 medRxiv,10.1101/2023.03.01.23286627,2023-03-03,https://medrxiv.org/cgi/content/short/2023.03.01.23286627,Effectiveness of successive booster vaccine doses against SARS-CoV-2 related mortality in residents of Long-Term Care Facilities in the VIVALDI study,Oliver Stirrup; Madhumita Shrotri; Natalie L. Adams; Maria Krutikov; Borscha Azmi; Igor Monakhov; Gokhan Tut; Paul Moss; Andrew Hayward; Andrew Copas; Laura Shallcross,University College London; University College London; University College London; University College London; University College London; UK Health Security Agency; University of Birmingham; University of Birmingham; University College London; University College London; University College London,"We evaluated the effectiveness of 1-3 booster vaccinations against SARS-CoV-2 related mortality among a cohort of 13407 older residents of long-term care facilities (LTCFs) participating in the VIVALDI study in England in 2022. Cox regression was used to estimate relative hazards of SARS-CoV-2 related death following booster vaccination relative to 2 doses (after 84+ days), stratified by previous SARS-CoV-2 infection and adjusting for age, sex and LTCF capacity. Each booster provided additional short-term protection relative to primary vaccination, with consistent pattern of waning to 45-75% reduction in risk beyond 112 days.",infectious diseases,exact,100,100
 medRxiv,10.1101/2023.03.01.23286624,2023-03-03,https://medrxiv.org/cgi/content/short/2023.03.01.23286624,Risk of cardiovascular events following COVID-19 in people with and without pre-existing chronic respiratory disease,Hannah Whittaker; Costantinos Kallis; Angela Wood; Thomas Bolton; Samantha Walker; Aziz Sheikh; Alex Brownrigg; Ashley Akbari; Kamil Sterniczuk; Jennifer K Quint,"Imperial College London; Imperial College London; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom; Health Data Research UK; Asthm + Lung; The University of Edinburgh College of Medicine and Veterinary Medicine; Health Data Research UK BREATHE; Swansea University; Health Data Research UK BREATHE; Imperial College London","BackgroundCOVID-19 is associated with a higher risk of cardiovascular outcomes in the general population, but it is unknown whether people with pre-existing chronic respiratory disease (CRD) have a higher risk of cardiovascular events post-COVID-19 compared with the general population and, if so, what respiratory-related risk factors may modify this risk in these people.
@@ -202,6 +223,13 @@ ResultsIgG spike-protein antibodies were undetectable in 23.3%, 14.1% and 20.7%
 ConclusionsApproximately one in five individuals with SOT, RAIRD and LM have no detectable IgG spike-protein antibodies despite three or more vaccines, but this proportion reduces with sequential booster doses. Choice of immunosuppressant and disease-type is strongly associated with serological response. Antibody testing could enable rapid identification of individuals who are most likely to benefit from additional COVID-19 interventions.
 
 Trial registrationClinicaltrials.gov, NCT05148806",public and global health,exact,100,100
+medRxiv,10.1101/2023.02.06.23285513,2023-02-06,https://medrxiv.org/cgi/content/short/2023.02.06.23285513,A Rapid review on the COVID-19 Pandemic's Global Impact on Breast Cancer Screening Participation Rates and Volumes from January-December 2020,"Reagan Lee; - UNCOVER; Wei Xu; - International Partnership for Resilience in Cancer Systems (I-PaRCS), Breast Cancer Working Group 2; Marshall Dozier; Ruth McQuillan; Evropi Theodoratou; Jonine Figueroa",University of Edinburgh; -; University of Edinburgh; -; University of Edinburgh; University of Edinburgh; The University of Edinburgh; University of Edinburgh,"BackgroundCOVID-19 has strained population breast mammography screening programs that aim to diagnose and treat breast cancers earlier. As the pandemic has affected countries differently, we aimed to quantify changes in breast screening volume and uptake during the first year of the COVID-19 pandemic.
+
+MethodsWe systematically searched Medline, the WHO (World Health Organization) COVID-19 database, and governmental databases. Studies covering January 2020 to March 2022 were included. We extracted and analyzed data regarding study methodology, screening volume and uptake. To assess for risk-of-bias, we used the Joanna Briggs Institute Critical Appraisal tool.
+
+ResultsTwenty-six cross-sectional descriptive studies were included out of 935 independent records. Reductions in screening volume and uptake rates were observed among eight countries. Changes in screening participation volume in five countries with national population-based screening ranged from -13% to -31%. Among two countries with limited population-based programs the decline ranged from -61% to -41%. Within the USA, population participation volumes varied ranging from +18% to -39% with suggestion of differences by insurance status (HMO, Medicare, and low-income programs). Almost all studies had high risk-of-bias due to insufficient statistical analysis and confounding factors.
+
+Discussion and ConclusionExtent of COVID-19-induced reduction in breast screening participation volume differed by region and data suggested potential differences by healthcare setting (e.g., national health insurance vs private health care). Recovery efforts should monitor access to screening and early diagnosis to determine if prevention services need strengthening to increase coverage of marginalized groups and reduce disparities.",epidemiology,exact,100,100
 medRxiv,10.1101/2023.02.01.23285333,2023-02-02,https://medrxiv.org/cgi/content/short/2023.02.01.23285333,Associations between reported healthcare disruption due to COVID-19 and avoidable hospitalisation: Evidence from seven linked longitudinal studies for England,Mark A Green; Martin McKee; Olivia Hamilton; Richard Shaw; John MacLeod; Andrew Boyd; - The LH&W NCS Collaborative; Srinivasa Vittal Katikireddi,University of Liverpool; London School of Hygiene and Tropical Medicine; University of Glasgow; University of Glasgow; University of Bristol; University of Bristol; ; University of Glasgow,"BackgroundHealth services across the UK struggled to cope during the COVID-19 pandemic. Many treatments were postponed or cancelled, although the impact was mitigated by new models of delivery. While the scale of disruption has been studied, much less is known about if this disruption impacted health outcomes. The aim of our paper is to examine whether there is an association between individuals experiencing disrupted access to healthcare during the pandemic and risk of an avoidable hospitalisation.
 
 MethodsWe used individual-level data for England from seven longitudinal cohort studies linked to electronic health records from NHS Digital (n = 29 276) within the UK Longitudinal Linkage Collaboration trusted research environment. Avoidable hospitalisations were defined as emergency hospital admissions for ambulatory care sensitive and emergency urgent care sensitive conditions (1st March 2020 to 25th August 2022). Self-reported measures of whether people had experienced disruption during the pandemic to appointments (e.g., visiting their GP or an outpatient department), procedures (e.g., surgery, cancer treatment) or medications were used as our exposures. Logistic regression models examined associations.
@@ -209,6 +237,12 @@ MethodsWe used individual-level data for England from seven longitudinal cohort
 Results35% of people experienced some form of disrupted access to healthcare. Those whose access was disrupted were at increased risk of any (Odds Ratio (OR) = 1.80, 95% Confidence Intervals (CIs) = 1.34-2.41), acute (OR = 1.68, CIs = 1.13-2.53) and chronic (OR = 1.93, CIs = 1.40-2.64) ambulatory care sensitive hospital admissions. There were positive associations between disrupted access to appointments and procedures to measures of avoidable hospitalisations as well.
 
 ConclusionsOur study presents novel evidence from linked individual-level data showing that people whose access to healthcare was disrupted were more likely to have an avoidable or potentially preventable hospitalisation. Our findings highlight the need to increase healthcare investment to tackle the short- and long-term implications of the pandemic beyond directly dealing with SARS-CoV-2 infections.",public and global health,exact,100,100
+medRxiv,10.1101/2023.01.31.23285232,2023-02-01,https://medrxiv.org/cgi/content/short/2023.01.31.23285232,"Cohort profile: Virus Watch: Understanding community incidence, symptom profiles, and transmission of COVID-19 in relation to population movement and behaviour",Thomas Edward Byrne; Jana Kovar; Sarah Beale; Isobel Braithwaite; Ellen Fragaszy; Wing Lam Erica Fong; Cyril Geismar; Susan J Hoskins; Annalan Mathew Dwight Navaratnam; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Alexei Yavlinsky; Pia Hardelid; Linda Wijlaars; Eleni Nastouli; Moira Spyer; Anna Ayree; Ingemar Cox; Vasileios Lampos; Rachel A McKendry; Tao Cheng; Anne M Johnson; Susan Fiona Michie; Jo Gibbs; Richard Gilson; Alison Rodger; Ibrahim Abubakar; Andrew Hayward; Robert W Aldridge,University College London; University College London; University College London; University College London; UCL; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCLH; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCL,"Key FeaturesO_LIVirus Watch is a national community cohort study of COVID-19 in households in England and Wales, established in June 2020. The study aims to provide evidence on which public health approaches are most effective in reducing transmission, and investigate community incidence, symptoms, and transmission of COVID-19 in relation to population movement and behaviours.
+C_LIO_LI28,527 households and 58,628 participants of age (0-98 years, mean age 48), were recruited between June 2020 - July 2022
+C_LIO_LIData collected include demographics, details on occupation, co-morbidities, medications, and infection-prevention behaviours. Households are followed up weekly with illness surveys capturing symptoms and their severity, activities in the week prior to symptom onset and any COVID-19 test results. Monthly surveys capture household finance, employment, mental health, access to healthcare, vaccination uptake, activities and contacts. Data have been linked to Hospital Episode Statistics (HES), inpatient and critical care episodes, outpatient visits, emergency care contacts, mortality, virology testing and vaccination data held by NHS Digital.
+C_LIO_LINested within Virus Watch are a serology & PCR cohort study (n=12,877) and a vaccine evaluation study (n=19,555).
+C_LIO_LIStudy data are deposited in the Office of National Statistics (ONS) Secure Research Service (SRS). Survey data are available under restricted access upon request to ONS SRS.
+C_LI",epidemiology,exact,100,100
 medRxiv,10.1101/2023.01.29.23285160,2023-01-30,https://medrxiv.org/cgi/content/short/2023.01.29.23285160,High number of SARS-CoV-2 persistent infections uncovered through genetic analysis of samples from a large community-based surveillance study,Mahan Ghafari; Matthew Hall; Tanya Golubchik; Daniel Ayoubkhani; Thomas House; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; Roberto Cahuantzi; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Jeff Barrett; Christophe Fraser; David Bonsall; Sarah Walker; Katrina A Lythgoe,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Office for National Statistics; -; -; -; Wellcome Sanger Institute; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections may act as viral reservoirs that could seed future outbreaks 1-5, give rise to highly divergent lineages 6-8, and contribute to cases with post-acute Coronavirus disease 2019 (COVID-19) sequelae (Long Covid) 9,10. However, the population prevalence of persistent infections, their viral load kinetics, and evolutionary dynamics over the course of infections remain largely unknown. We identified 381 infections lasting at least 30 days, of which 54 lasted at least 60 days. These persistently infected individuals had more than 50% higher odds of self-reporting Long Covid compared to the infected controls, and we estimate that 0.09-0.5% of SARS-CoV-2 infections can become persistent and last for at least 60 days. In nearly 70% of the persistent infections we identified, there were long periods during which there were no consensus changes in virus sequences, consistent with prolonged presence of non-replicating virus. Our findings also suggest reinfections with the same major lineage are rare and that many persistent infections are characterised by relapsing viral load dynamics. Furthermore, we found a strong signal for positive selection during persistent infections, with multiple amino acid substitutions in the Spike and ORF1ab genes emerging independently in different individuals, including mutations that are lineage-defining for SARS-CoV-2 variants, at target sites for several monoclonal antibodies, and commonly found in immunocompromised patients 11-14. This work has significant implications for understanding and characterising SARS-CoV-2 infection, epidemiology, and evolution.",epidemiology,exact,100,100
 medRxiv,10.1101/2023.01.24.23284916,2023-01-25,https://medrxiv.org/cgi/content/short/2023.01.24.23284916,"Real-world effectiveness of molnupiravir, nirmatrelvir-ritonavir, and sotrovimab on preventing hospital admission among higher-risk patients with COVID-19 in Wales: a retrospective cohort study",Andrew Evans; Cathy Qi; Lolu Adebayo; Jonathan Underwood; James Coulson; Rowena Bailey; Gareth John; Alison Cooper; Ashley Akbari; Ronan Lyons; Adrian Edwards,"Welsh Government; Swansea University Medical School; Swansea University Medical School; School of Medicine, Cardiff University; School of Medicine, Cardiff University,; Swansea University Medical School; Digital Health and Care Wales; Wales COVID-19 Evidence Centre; Swansea University; Swansea University; Wales COVID-19 Evidence Centre","ObjectiveTo compare the effectiveness of molnupiravir, nirmatrelvir-ritonavir, and sotrovimab with no treatment in preventing hospital admission or death in higher-risk patients infected with SARS-CoV-2 in the community.
 
@@ -877,6 +911,7 @@ ResultsBetween October-2020 and April-2022, 120,995 SARS-CoV-2 PCR-positive epis
 ConclusionsIncreases in sore throat (also common in the general community), and a marked reduction in loss of taste/smell, make Omicron harder to detect with symptom-based testing algorithms, with implications for institutional and national testing policies.
 
 SummaryIn a UK community study, loss of taste/smell was markedly less commonly reported with Omicron BA.1/BA.2 than Delta SARS-CoV-2 infections, with smaller declines in reported shortness of breath, myalgia and fatigue/weakness, but increases in sore throat, challenging symptom-based testing algorithms.",epidemiology,exact,100,100
+medRxiv,10.1101/2022.01.05.21268323,2022-01-06,https://medrxiv.org/cgi/content/short/2022.01.05.21268323,Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey,Katrina A Lythgoe; Tanya Golubchik; Matthew Hall; Thomas House; Roberto Cahuantzi; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; Mahan Ghafari; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Christophe Fraser; Ian Diamond; Jeff Barrett; Ann Sarah Walker; David Bonsall,University of Oxford; University of Oxford; University of Oxford; University of Manchester; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Wellcome Sanger Institute; Office for National Statistics; ; University of Oxford; Office for National Statistics; Wellcome Sanger Institute; University of Oxford; University of Oxford,"The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non- SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly in the current phase of the pandemic with routine RT-PCR testing now ended in the community.",epidemiology,exact,100,100
 medRxiv,10.1101/2021.12.31.21268587,2022-01-02,https://medrxiv.org/cgi/content/short/2021.12.31.21268587,"The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data",Caroline E Dale; Rohan Takhar; Ray Carragher; Fatemeh Torabi; Michalis Katsoulis; Stephen Duffield; Seamus Kent; Tanja Mueller; Amanj Kurdi; Stuart McTaggart; Hoda Abbasizanjani; Sam Hollings; Andrew Scourfield; Ronan Lyons; Rowena Griffiths; Jane Lyons; Gareth Davies; Dan Harris; Alex Handy; Mehrdad Alizadeh Mizani; Chris Tomlinson; Mark Ashworth; Spiros Denaxas; Amitava Banerjee; Jonathan Sterne; Kate Lovibond; Paul Brown; Ian Bullard; Rouven Priedon; Mamas A Mamas; Ann Slee; Paula Lorgelly; Munir Pirmohamed; Kamlesh Khunti; Naveed Sattar; Andrew Morris; Cathie Sudlow; Ashley Akbari; Marion Bennie; Reecha Sofat; - CVD-COVID-UK Consortium,"Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Swansea University; Institute of Health Informatics Research, University College London; NICE; NICE; University of Strathclyde; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Public Health Scotland; Swansea University; NHS Digital, Leeds; UCLH NHS Foundation Trust; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; King's College London; Institute of Health Informatics Research, University College London; University College London; University of Bristol; Royal College of Physicians; NHS Digital, Leeds; NHS Digital; British Heart Foundation Data Science Centre, Health Data Research UK, London; Keele University; NHSX; Department of Applied Health Research, University College London; University of Liverpool; University of Leicester; University of Glasgow; Health Data Research UK; British Heart Foundation Data Science Centre, Health Data Research UK, London; Swansea University; University of Strathclyde; Institute of Health Informatics Research, University College London; ","ObjectivesTo estimate the impact of the COVID-19 pandemic on cardiovascular disease (CVD) and CVD management using routinely collected medication data as a proxy.
 
 DesignDescriptive and interrupted time series analysis using anonymised individual-level population-scale data for 1.32 billion records of dispensed CVD medications across 15.8 million individuals in England, Scotland and Wales.
@@ -924,7 +959,6 @@ MethodTrial emulation was conducted by pooling results from six cohorts whose re
 ResultsAcross six cohorts, there were a total of 21,283 participants who were eligible and vaccinated with either ChAdOx1 (n = 13,813) or BNT162b2 (n = 7,470) with a median follow-up time of 266 days (IQR: 235 - 282). By November 12th 2021, 750 (5.4%) adults who had ChAdOx1 as their vaccine experienced a SARS-CoV-2 infection, compared to 296 (4.0%) who had BNT162b2. We found that people who received ChAdOx1 vaccinations had 10.54 per 1000 people higher cumulative incidence for SARS-CoV-2 infection compared to BNT162b2 for infections during a maximum of 315 days of follow-up. When adjusted for age at vaccination, sex, minority ethnic status, index of multiple deprivation, and clinical vulnerability status, we found a pooled adjusted hazard ratio of 1.35 [HR: 1.35, 95%CI: 1.15 - 1.58], demonstrating a 35% increase in SARS-CoV-2 infections in people who received ChAdOx1 compared to BNT162b2.
 
 DiscussionWe found evidence of greater effectiveness of receiving BNT162b2 compared to ChAdOx1 vaccines against SARS-CoV-2 infection in England and Wales during a time period when Delta became the most prevalent variant of concern. Our findings demonstrate the importance of booster (third) doses to maintain protection and suggest that these should be prioritised to those who received ChAdOx1 as their primary course.",epidemiology,exact,100,100
-bioRxiv,10.1101/2021.12.17.473248,2021-12-21,https://biorxiv.org/cgi/content/short/2021.12.17.473248,"SARS-CoV-2 Omicron spike mediated immune escape, infectivity and cell-cell fusion",Bo Meng; Isabella Ferreira; Adam Abdullahi; Niluka Goonawardane; Akatsuki Saito; Izumi Kimura; Daichi Yamasoba; Steven A Kemp; Guido Papa; Saman Fatihi; Surabhi Rathore; Pehuen Perera Gerba; Terumasa Ikeda; Mako Toyoda; Toong Seng Tan; Jin Kuramochi; Shigeki Mitsunaga; Takamasa Ueno; Oscar Charles; Dami Collier; - CITIID-NIHR BioResource COVID-19 Collaboration; - The Genotype to Phenotype Japan (G2P-Japan) Consortium; - Ecuador-COVID19 Consortium; John Bradley; Jinwook Choi; Kenneth Smith; Elo Madissoon; Kerstin Meyer; Petra Mlcochova; Rainer Doffinger; Sarah A Teichmann; Leo James; Joo Hyeon Lee; Teresa Brevini; Matteo Pizzuto; Myra Hosmillo; Donna Mallery; Samantha Zepeda; Alexandra Walls; Anshu Joshi; John Bowen; John Briggs; Alex Sigal; Laurelle Jackson; Sandile Cele; Anna De Marco; Fotios Sampaziotis; Davide Corti; David Veesler; Nicholas Matheson; Ian Goodfellow; Lipi Thukral; Kei Sato; Ravindra K Gupta,"University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Miyazaki; The University of Tokyo; Kumamoto University; University of Cambridge; LMB Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; CSIR Institute of Genomics and Integrative Biology, Delhi, India; University of Cambridge; Kumamoto Univ; Kumamoto University, Kumamoto; Kuramochi Clinic Interpark; Kuramochi Clinic Interpark; National Institute of Genetics, Mishima, Shizuoka; Kumamoto University, Kumamoto; University College London; University of Cambridge; -; -; -; University of Cambridge; University of Cambridge; University of Cambridge; Wellcome Sanger Institute; Wellcome Sanger Institute; University of Cambridge; Cambridge University Hospitals NHS Trust; Cambridge University; MRC LMB; University of Cambridge; University of Cambridge; Humabs Biomed SA; University of Cambridge; MRC LMB Cambridge; University of Washington; University of Washington; University of Washington; University of Washington; University of Heidelberg; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Humabs Biomed SA; University of Cambridge; Humabs Biomed SA; University of Washington; University of Cambridge; University of Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; The University of Tokyo; University of Cambridge","The SARS-CoV-2 Omicron BA.1 variant emerged in late 2021 and is characterised by multiple spike mutations across all spike domains. Here we show that Omicron BA.1 has higher affinity for ACE2 compared to Delta, and confers very significant evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralising antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralisation. Importantly, antiviral drugs remdesevir and molnupiravir retain efficacy against Omicron BA.1. We found that in human nasal epithelial 3D cultures replication was similar for both Omicron and Delta. However, in lower airway organoids, Calu-3 lung cells and gut adenocarcinoma cell lines live Omicron virus demonstrated significantly lower replication in comparison to Delta. We noted that despite presence of mutations predicted to favour spike S1/S2 cleavage, the spike protein is less efficiently cleaved in live Omicron virions compared to Delta virions. We mapped the replication differences between the variants to entry efficiency using spike pseudotyped virus (PV) entry assays. The defect for Omicron PV in specific cell types correlated with higher cellular RNA expression of TMPRSS2, and accordingly knock down of TMPRSS2 impacted Delta entry to a greater extent as compared to Omicron. Furthermore, drug inhibitors targeting specific entry pathways demonstrated that the Omicron spike inefficiently utilises the cellular protease TMPRSS2 that mediates cell entry via plasma membrane fusion. Instead, we demonstrate that Omicron spike has greater dependency on cell entry via the endocytic pathway requiring the activity of endosomal cathepsins to cleave spike. Consistent with suboptimal S1/S2 cleavage and inability to utilise TMPRSS2, syncytium formation by the Omicron spike was dramatically impaired compared to the Delta spike. Overall, Omicron appears to have gained significant evasion from neutralising antibodies whilst maintaining sensitivity to antiviral drugs targeting the polymerase. Omicron has shifted cellular tropism away from TMPRSS2 expressing cells that are enriched in cells found in the lower respiratory and GI tracts, with implications for altered pathogenesis.",microbiology,exact,100,100
 medRxiv,10.1101/2021.12.20.21268098,2021-12-21,https://medrxiv.org/cgi/content/short/2021.12.20.21268098,"Therapies for Long COVID in non-hospitalised individuals - from symptoms, patient-reported outcomes, and immunology to targeted therapies (The TLC Study): Study protocol",Shamil Haroon; Krishnarajah Nirantharakumar; Sarah Hughes; Anuradhaa Subramanian; Olalekan Lee Aiyegbusi; Elin Haf Davies; Puja Myles; Tim Williams; Grace Turner; Joht Singh Chandan; Christel McMullan; Janet Lord; David Wraith; Kirsty McGee; Alastair Denniston; Tom Taverner; Louise Jackson; Elizabeth Sapey; Georgios Gkoutos; Krishna Gokhale; Edward Leggett; Clare Iles; Christopher Frost; Gary McNamara; Amy Bamford; Tom Marshall; Dawit Zemedikun; Gary Price; Steven Marwaha; Nikita Simms-Williams; Kirsty Brown; Anita Walker; Karen Jones; Karen Matthews; Jennifer Camaradou; Michael Saint-Cricq; Sumita Kumar; Yvonne Alder; David Stanton; Lisa Agyen; Megan Baber; Hannah Blaize; Melanie Calvert,University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; Aparito; Medicines and Healthcare Products Regulatory Agency; Medicines and Healthcare Products Regulatory Agency; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University Hospitals Birmingham NHS Foundation Trust; University of Birmingham; University of Birmingham; University of Birmingham; University ofBirmingham; University of Birmingham; Medicines and Healthcare Products Regulatory Agency; Medicines and Healthcare Products Regulatory Agency; Aparito; Aparito; University Hospitals Birmingham NHS Foundation Trust; University of Birmingham; University of Birmingham; N/A; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; Not applicable; University ofBirmingham,"IntroductionIndividuals with COVID-19 frequently experience symptoms and impaired quality of life beyond 4-12 weeks, commonly referred to as Long COVID. Whether Long COVID is one or several distinct syndromes is unknown. Establishing the evidence base for appropriate therapies is needed. We aim to evaluate the symptom burden and underlying pathophysiology of Long COVID syndromes in non-hospitalised individuals and evaluate potential therapies.
 
 Methods and analysisA cohort of 4000 non-hospitalised individuals with a past COVID-19 diagnosis and 1000 matched controls will be selected from anonymised primary care records from the Clinical Practice Research Datalink (CPRD) and invited by their general practitioners to participate on a digital platform (Atom5). Individuals will report symptoms, quality of life, work capability, and patient reported outcome measures. Data will be collected monthly for one year.
@@ -1068,6 +1102,17 @@ ResultsCompared to those who remained working, furloughed workers were at greate
 
 ConclusionsDuring the early stages of the pandemic, those furloughed had increased risk for poor mental and social wellbeing. However, their excess risk was lower in magnitude than that of those who became or remained unemployed, suggesting that furlough may have partly mitigated poorer outcomes.",psychiatry and clinical psychology,exact,100,100
 medRxiv,10.1101/2021.11.15.21266255,2021-11-16,https://medrxiv.org/cgi/content/short/2021.11.15.21266255,"COVID-19 vaccination, risk-compensatory behaviours, and social contacts in four countries in the UK",John Buckell; Joel Jones; Philippa C Matthews; Ian Diamond; Emma Rourke; Ruth Studley; Duncan Cook; Ann Sarah Walker; Koen B Pouwels; - The COVID-19 Infection Survey Team,University of Oxford; Office for National Statistics; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; University of Oxford; ,"The physiological effects of vaccination against SARS-CoV-2 (COVID-19) are well documented, yet the behavioural effects are largely unknown. Risk compensation suggests that gains in personal safety, as a result of vaccination, are offset by increases in risky behaviour, such as socialising, commuting and working outside the home. This is potentially problematic because transmission of SARS-CoV-2 is driven by contacts, which could be amplified by vaccine-related risk compensation behaviours. Here, we show that behaviours were overall unrelated to personal vaccination, but - adjusting for variation in mitigation policies - were responsive to the level of vaccination in the wider population: individuals in the UK were risk compensating when rates of vaccination were rising. This effect was observed across four nations of the UK, each of which varied policies autonomously.",infectious diseases,exact,100,100
+medRxiv,10.1101/2021.11.10.21266124,2021-11-11,https://medrxiv.org/cgi/content/short/2021.11.10.21266124,Differences in COVID-19 vaccination coverage by occupation in England: a national linked data study,Vahe Nafilyan; Ted Dolby; Katie Finning; Jasper Morgan; Rhiannon Edge; Myer Glickman; Neil Pearce; Martie Van Tongeren,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Lancaster University; Office for National Statistics; London School of Hygiene and Tropical Medicine; University of Manchester,"BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation.
+
+MethodsUsing nationwide population-level data, we calculated the proportion of people who had received two doses of a COVID-19 vaccine (assessed on 31 August 2021) by detailed occupational categories in adults aged 40-64 and estimated adjusted odds ratios to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.
+
+ResultsOur study population included 14,298,147 adults 40-64. Vaccination rates differed markedly by occupation, being higher in administrative and secretarial occupations (90.8%); professional occupations (90.7%); and managers, directors and senior officials (90.6%); and lowest (83.1%) in people working in elementary occupations. We found substantial differences in vaccination rates looking at finer occupational groups even after adjusting for confounding factors, such as education. Vaccination rates were higher in occupations which can be done from home and lower in those which cannot. Many occupations with low vaccination rates also involved contact with the public or with vulnerable people
+
+ConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection, especially in occupations that cannot be done from home and involve contacts with the public. Policies such as  work from home if you can may only have limited future impact on hospitalisations and deaths
+
+What is already known on this subject?Whilst several studies highlight differences in vaccination coverage by ethnicity, religion, socio-demographic factors and certain underlying health conditions, there is very little evidence on how vaccination coverage varies by occupation, in the UK and elsewhere. The few study looking at occupational differences in vaccine hesitancy focus on healthcare workers or only examined broad occupational groups. There is currently no large-scale study on occupational differences in COVID-19 vaccination coverage in the UK.
+
+What this study adds?Using population-level linked data combining the 2011 Census, primary care records, mortality and vaccination data, we found that the vaccination rates of adults aged 40 to 64 years in England differed markedly by occupation. Vaccination rates were high in administrative and secretarial occupations, professional occupations and managers, directors and senior officials and low in people working in elementary occupations. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were also associated with the ability to work from home, with the vaccination rate being higher in occupations which can be done performed from home. Policies aiming to increase vaccination rates in occupations that cannot be done from home and involve contacts with the public should be priorities",public and global health,exact,100,100
 medRxiv,10.1101/2021.11.09.21266054,2021-11-09,https://medrxiv.org/cgi/content/short/2021.11.09.21266054,"Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England: a space-time study",Tullia Padellini; Radka Jersakova; Peter J Diggle; Chris Holmes; Ruairidh King; Brieuc Lehmann; Ann-Marie Mallon; George Nicholson; Sylvia Richardson; Marta Blangiardo,Imperial College London; The Alan Turing Institute; Lancaster University; The Alan Turing Institute; MRC Harwell; University of Oxford; MRC Harwell; University of Oxford; University of Cambridge; Imperial College London,"BackgroundEthnically diverse and socio-economically deprived communities have been differentially affected by the COVID-19 pandemic in the UK.
 
 MethodUsing a multilevel regression model we assess the time-varying association between SARS-CoV-2 infections and areal level deprivation and ethnicity. We separately consider weekly test positivity rate (number of positive tests over the total number of tests) and estimated unbiased prevalence (proportion of individuals in the population who would test positive) at the Lower Tier Local Authority (LTLA) level. The model also adjusts for age, urbanicity, vaccine uptake and spatio-temporal correlation structure.
@@ -1195,7 +1240,6 @@ ResultsThe trial opened on April 2, 2020, with randomisation to colchicine start
 ConclusionsColchicine did not improve time to recovery in people at higher risk of complications with COVID-19 in the community.
 
 Trial registrationISRCTN86534580.",infectious diseases,exact,100,100
-medRxiv,10.1101/2021.09.13.21263487,2021-09-16,https://medrxiv.org/cgi/content/short/2021.09.13.21263487,SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population,Jia Wei; Koen B. Pouwels; Nicole Stoesser; Philippa C. Matthews; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John I Bell; John N Newton; Jeremy Farrar; Alison Howarth; Brian D. Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W. Crook; Tim E.A. Peto; A.Sarah Walker; David W. Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.",infectious diseases,exact,100,100
 medRxiv,10.1101/2021.09.09.21263026,2021-09-13,https://medrxiv.org/cgi/content/short/2021.09.09.21263026,The clinically extremely vulnerable to COVID: Identification and changes in health care while self-isolating (shielding) during the coronavirus pandemic,Jessica Erin Butler; Mintu Nath; Dimitra Blana; William P Ball; Nicola Beech; Corri Black; Graham Osler; Sebastien Peytrignet; Katie Wilde; Artur Wozniak; Simon Sawhney,University of Aberdeen; University of Aberdeen; University of Aberdeen; University of Aberdeen; NHS Grampian; NHS Grampian and University of Aberdeen; NHS Grampian; Health Foundation; University of Aberdeen; University of Aberdeen; NHS Grampian and University of Aberdeen,"BackgroundIn March 2020, the government of Scotland identified people deemed clinically extremely vulnerable to COVID due to their pre-existing health conditions. These people were advised to strictly self-isolate (shield) at the start of the pandemic, except for necessary healthcare. We examined who was identified as clinically extremely vulnerable, how their healthcare changed during isolation, and whether this process exacerbated healthcare inequalities.
 
 MethodsWe linked those on the shielding register in NHS Grampian, a health authority in Scotland, to healthcare records from 2015-2020. We described the source of identification, demographics, and clinical history of the cohort. We measured changes in out-patient, in-patient, and emergency healthcare during isolation in the shielding population and compared to the general non-shielding population.
@@ -1459,6 +1503,19 @@ FindingsWe included results from 8213 swabbed illnesses, 944 of which tested pos
 
 InterpretationCOVID-19 is difficult to distinguish from other respiratory infections and common ailments on the basis of symptoms. Broadening the list of symptoms used to encourage engagement with TTI could moderately increase the number of infections identified and shorten delays to isolation, but with a large increase in the number of tests needed and the number of unwell individuals and contacts who are advised to self-isolate whilst awaiting results, and subsequently test negative for SARS-CoV-2.",epidemiology,exact,100,100
 medRxiv,10.1101/2021.05.17.21256818,2021-05-18,https://medrxiv.org/cgi/content/short/2021.05.17.21256818,Local prevalence of transmissible SARS-CoV-2 infection : an integrative causal model for debiasing fine-scale targeted testing data,George Nicholson; Brieuc CL Lehmann; Tullia Padellini; Koen B Pouwels; Radka Jersakova; James Lomax; Ruairidh E King; Ann-Marie Mallon; Peter J Diggle; Sylvia Richardson; Marta Blangiardo; Chris Holmes,University of Oxford; University of Oxford; Imperial College London; University of Oxford; The Alan Turing Institute; The Alan Turing Institute; MRC Harwell Institute; MRC Harwell Institute; Lancaster University; MRC Biostatistics Unit; Imperial College London; University of Oxford,"Targeted surveillance testing schemes for SARS-CoV-2 focus on certain subsets of the population, such as individuals experiencing one or more of a prescribed list of symptoms. These schemes have routinely been used to monitor the spread of SARS-CoV-2 in countries across the world. The number of positive tests in a given region can provide local insights into important epidemiological parameters, such as prevalence and effective reproduction number. Moreover, targeted testing data has been used inform the deployment of localised non-pharmaceutical interventions. However, surveillance schemes typically suffer from ascertainment bias; the individuals who are tested are not necessarily representative of the wider population of interest. Here, we show that data from randomised testing schemes, such as the REACT study in the UK, can be used to debias fine-scale targeted testing data in order to provide accurate localised estimates of the number of infectious individuals. We develop a novel, integrative causal framework that explicitly models the process underlying the selection of individuals for targeted testing. The output from our model can readily be incorporated into longitudinal analyses to provide local estimates of the reproduction number. We apply our model to characterise the size of the infectious population in England between June 2020 and January 2021. Our local estimates of the effective reproduction number are predictive of future changes in positive case numbers. We also capture local increases in both prevalence and effective reproductive number in the South East from November 2020 to December 2020, reflecting the spread of the Kent variant. Our results illustrate the complementary roles of randomised and targeted testing schemes. Preparations for future epidemics should ensure the rapid deployment of both types of schemes to accurately monitor the spread of emerging and ongoing infectious diseases.",infectious diseases,exact,100,100
+medRxiv,10.1101/2021.05.12.21257123,2021-05-17,https://medrxiv.org/cgi/content/short/2021.05.12.21257123,Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults,Vahe Nafilyan; Piotr Pawelek; Daniel Ayoubkhani; Sarah Rhodes; Lucy Pembrey; Melissa Matz; Michel P Coleman; Claudia Allemani; Ben Windsor-Shellard; Martie van Tongeren; Neil Pearce,"Office for National Statistics; Office for National Statistics; Office for National Statistics; School of Health Sciences, University of Manchester; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Office for National Statistics; School of Health Sciences, University of Manchester; London School of Hygiene and Tropical Medicine","ObjectiveTo estimate occupational differences in COVID-19 mortality, and test whether these are confounded by factors, such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation or pre-pandemic health.
+
+DesignRetrospective cohort study
+
+SettingPeople living in private households England
+
+Participants14,295,900 people aged 40-64 years (mean age 52 years, 51% female) who were alive on 24 January 2020, living in private households in England in 2019, were employed in 2011, and completed the 2011 census.
+
+Main outcome measuresCOVID-19 related death, assessed between 24 January 2020 and 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk (ASMR) stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding (region, ethnicity, education), as well as non-workplace factors that are related to occupation.
+
+ResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three-fold or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating non-workplace factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62-5.84] to 1.47 [1.14-1.89] after adjustment. More generally, the overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.
+
+ConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.",epidemiology,exact,100,100
 medRxiv,10.1101/2021.05.13.21257144,2021-05-17,https://medrxiv.org/cgi/content/short/2021.05.13.21257144,REACT-1 round 11 report: low prevalence of SARS-CoV-2 infection in the community prior to the third step of the English roadmap out of lockdown,Steven Riley; David J Haw; Caroline E Walters; Howei Wang; Oliver Eales; Kylie E C Ainslie; Christina Atchison; Claudio Fronterre; Peter J Diggle; Andrew J Page; Alexander J Trotter; Thanh Le Viet; Nabil-Fareed Alikhan; Justin O'Grady; - The COVID-19 Genomics UK (COG-UK) Consortium; Deborah Ashby; Christl Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; Imperial College London; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; ; Imperial College London; University of Oxford; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London","BackgroundNational epidemic dynamics of SARS-CoV-2 infections are being driven by: the degree of recent indoor mixing (both social and workplace), vaccine coverage, intrinsic properties of the circulating lineages, and prior history of infection (via natural immunity). In England, infections, hospitalisations and deaths fell during the first two steps of the ""roadmap"" for exiting the third national lockdown. The third step of the roadmap in England takes place on 17 May 2021.
 
 MethodsWe report the most recent findings on community infections from the REal-time Assessment of Community Transmission-1 (REACT-1) study in which a swab is obtained from a representative cross-sectional sample of the population in England and tested using PCR. Round 11 of REACT-1 commenced self-administered swab-collection on 15 April 2021 and completed collections on 3 May 2021. We compare the results of REACT-1 round 11 to round 10, in which swabs were collected from 11 to 30 March 2021.
@@ -1473,6 +1530,17 @@ MethodsThe Virus Watch study is an online, prospective, community cohort study f
 ResultsOut of 24,887 illnesses reported, 915 tested positive for SARS-CoV-2 and 186 likely infector-infectee pairs in 186 households amongst 372 individuals were identified. The mean COVID-19 serial interval was 3.18 (95%CI: 2.55 - 3.81) days. There was no significant difference (p=0.267) between the mean serial interval for Variants of Concern (VOC) hotspots (mean = 3.64 days, (95%CI: 2.55 - 4.73)) days and non-VOC hotspots, (mean = 2.72 days, (95%CI: 1.48 - 3.96)).
 
 ConclusionsOur estimates of the average serial interval of COVID-19 are broadly similar to estimates from previous studies and we find no evidence that B.1.1.7 is associated with a change in serial intervals. Alternative explanations such as increased viral load, longer period of viral shedding or improved receptor binding may instead explain the increased transmissibility and rapid spread and should undergo further investigation.",epidemiology,exact,100,100
+medRxiv,10.1101/2021.05.06.21256757,2021-05-14,https://medrxiv.org/cgi/content/short/2021.05.06.21256757,COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study,Yiqun Chen; Timothy Aldridge; - UK COVID-19 National Core Studies Consortium; Claire F Ferraro; Fu-Meng Khaw,"Health and Safety Executive, UK; Health and Safety Executive, UK; ; National Infection Service, Public Health England, UK; Public Health England, UK","BackgroundA large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic. However, information on the rate of outbreak occurrences which helps to identify the type of workplaces that are more likely to experience an outbreak, or infection attack rates which estimates the potential extent of the virus transmission in an outbreak, has not yet been available to inform intervention strategies to limit transmission.
+
+ObjectivesTo link datasets on workplace settings and COVID-19 workplace outbreaks in England in order to: identify the geographical areas and workplace sectors with a high rate of outbreaks; and compare infection attack rates by workplace size and sector.
+
+MethodsWe analysed Public Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, covering the time period of 18 May - 12 October 2020. The workplaces analysed excluded care homes, hospitals and educational settings. We calculated the workplace outbreak rates by nine English regions, 151 Upper Tier Local Authorities (UTLAs) and twelve industrial sectors, using National Population Database (NPD) data extracted in May 2019 on the total number of the relevant workplaces as the denominator. We also calculated the infection attack rates by enterprise size (small, medium, large) and industrial sector, using PHE Situations of Interest (SOI) data on the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator, and using NPD data on the number employed in that workplace as the denominator.
+
+ResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone data, of which 1,305 were available for estimation of outbreak rates. The average outbreak rate was 66 per 100,000 workplaces. Of the nine geographical regions in England, the North West had the highest workplace outbreak rate (155/100,000 workplaces), based on 351 outbreaks. Of the UTLAs, the highest workplace outbreak rate was Blackburn with Darwen (387/100,000 workplaces). The industrial sector with the highest workplace outbreak rate was manufacturers and packers of food (1,672/100,000), based on 117 outbreaks: this was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.
+
+In total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%).
+
+ConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.",epidemiology,exact,100,100
 medRxiv,10.1101/2021.05.08.21256867,2021-05-14,https://medrxiv.org/cgi/content/short/2021.05.08.21256867,SARS-CoV-2 lineage dynamics in England from January to March 2021 inferred from representative community samples,Oliver Eales; Andrew Page; Sonja N. Tang; Caroline E. Walters; Haowei Wang; David Haw; Alexander J. Trotter; Thanh Le Viet; Ebenezer Foster-Nyarko; Sophie Prosolek; Christina Atchinson; Deborah Ashby; Graham Cooke; Wendy Barclay; Christl A Donnelly; Justin O'Grady; Erik Volz; - The COVID-19 Genomics UK (COG-UK) Consortium; Ara Darzi; Helen Ward; Paul Elliott; Steven Riley,"School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; ; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc","Genomic surveillance for SARS-CoV-2 lineages informs our understanding of possible future changes in transmissibility and vaccine efficacy. However, small changes in the frequency of one lineage over another are often difficult to interpret because surveillance samples are obtained from a variety of sources. Here, we describe lineage dynamics and phylogenetic relationships using sequences obtained from a random community sample who provided a throat and nose swab for rt-PCR during the first three months of 2021 as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Overall, diversity decreased during the first quarter of 2021, with the B.1.1.7 lineage (first identified in Kent) predominant, driven by a 0.3 unit higher reproduction number over the prior wild type. During January, positive samples were more likely B.1.1.7 in younger and middle-aged adults (aged 18 to 54) than in other age groups. Although individuals infected with the B.1.1.7 lineage were no more likely to report one or more classic COVID-19 symptoms compared to those infected with wild type, they were more likely to be antibody positive 6 weeks after infection. Viral load was higher in B.1.1.7 infection as measured by cycle threshold (Ct) values, but did not account for the increased rate of testing positive for antibodies. The presence of infections with non-imported B.1.351 lineage (first identified in South Africa) during January, but not during February or March, suggests initial establishment in the community followed by fade-out. However, this occurred during a period of stringent social distancing and targeted public health interventions and does not immediately imply similar lineages could not become established in the future. Sequence data from representative community surveys such as REACT-1 can augment routine genomic surveillance.",infectious diseases,exact,100,100
 medRxiv,10.1101/2021.05.06.21256755,2021-05-13,https://medrxiv.org/cgi/content/short/2021.05.06.21256755,Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY,- The OpenSAFELY Collaborative; Alex J Walker; Brian MacKenna; Peter Inglesby; Christopher T Rentsch; Helen J Curtis; Caroline E Morton; Jessica Morley; Amir Mehrkar; Sebastian CJ Bacon; George Hickman; Christopher Bates; Richard Croker; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan Bhaskaran; Anna Schultze; Elizabeth J Williamson; William J Hulme; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Rosalind M Eggo; Kevin Wing; Angel YS Wong; Harriet Forbes; John Tazare; John Parry; Frank Hester; Sam Harper; Shaun O'Hanlon; Alex Eavis; Richard Jarvis; Dima Avramov; Paul Griffiths; Aaron Fowles; Nasreen Parkes; Ian J Douglas; Stephen JW Evans; Liam Smeeth; Ben Goldacre,; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; EMIS; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundLong COVID is a term to describe new or persistent symptoms at least four weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were released in November 2020 in the UK, but it is not known how these codes have been used in practice.
 
@@ -1481,9 +1549,6 @@ MethodsWorking on behalf of NHS England, we used OpenSAFELY data encompassing 96
 ResultsLong COVID was recorded for 23,273 people. Coding was unevenly distributed amongst practices, with 26.7% of practices having not used the codes at all. Regional variation was high, ranging between 20.3 per 100,000 people for East of England (95% confidence interval 19.3-21.4) and 55.6 in London (95% CI 54.1-57.1). The rate was higher amongst women (52.1, 95% CI 51.3-52.9) compared to men (28.1, 95% CI 27.5-28.7), and higher amongst practices using EMIS software (53.7, 95% CI 52.9-54.4) compared to TPP software (20.9, 95% CI 20.3-21.4).
 
 ConclusionsLong COVID coding in primary care is low compared with early reports of long COVID prevalence. This may reflect under-coding, sub-optimal communication of clinical terms, under-diagnosis, a true low prevalence of long COVID diagnosed by clinicians, or a combination of factors. We recommend increased awareness of diagnostic codes, to facilitate research and planning of services; and surveys of clinicians experiences, to complement ongoing patient surveys.",epidemiology,exact,100,100
-medRxiv,10.1101/2021.05.05.21256668,2021-05-09,https://medrxiv.org/cgi/content/short/2021.05.05.21256668,COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland,Sofia de la Fuente Garcia; Fasih Haider; Saturnino Luz,The University of Edinburgh; The University of Edinburgh; The University of Edinburgh,"The COVID-19 pandemic has led to unprecedented restrictions in peoples lifestyle which have affected their psychological wellbeing. In this context, this paper investigates the use of social signal processing techniques for remote assessment of emotions. It presents a machine learning method for affect recognition applied to recordings taken during the COVID-19 winter lockdown in Scotland (UK). This method is exclusively based on acoustic features extracted from voice recordings collected through home and mobile devices (i.e. phones, tablets), thus providing insight into the feasibility of monitoring peoples psychological wellbeing remotely, automatically and at scale. The proposed model is able to predict affect with a concordance correlation coefficient of 0.4230 (using Random Forest) and 0.3354 (using Decision Trees) for arousal and valence respectively.
-
-Clinical relevanceIn 2018/2019, 12% and 14% of Scottish adults reported depression and anxiety symptoms. Remote emotion recognition through home devices would support the detection of these difficulties, which are often underdiagnosed and, if untreated, may lead to temporal or chronic disability.",health informatics,exact,100,100
 medRxiv,10.1101/2021.05.04.21256507,2021-05-06,https://medrxiv.org/cgi/content/short/2021.05.04.21256507,Describing the burden of the COVID-19 pandemic in people with psoriasis: findings from a global cross-sectional study,Satveer K Mahil; Mark Yates; Zenas Z Yiu; Sinead M Langan; Teresa Tsakok; Nick Dand; Kayleigh J Mason; Helen McAteer; Freya Meynall; Bolaji Coker; Alexandra Vincent; Dominic Urmston; Amber Vesty; Jade Kelly; Camille Lancelot; Lucy Moorhead; Herve Bachelez; Francesca Capon; Claudia R Contreras; Claudia De La Cruz; Paola Di Meglio; Paolo Gisondi; Denis Jullien; Jo Lambert; Luigi Naldi; Sam Norton; Luis Puig; Phyllis Spuls; Tiago Torres; Richard B Warren; Hoseah Waweru; John Weinman; Matt A Brown; James B Galloway; Christopher M Griffiths; Jonathan N Barker; Catherine H Smith,"St Johns Institute of Dermatology, Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; Centre for Rheumatic Diseases, King's College London; Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Rese; Faculty of Epidemiology, and Population Health, London School of Hygiene and Tropical Medicine, London, UK; St Johns Institute of Dermatology, Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; Department of Medical and Molecular Genetics, School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London, UK; Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Rese; The Psoriasis Association, Northampton, UK; St Johns Institute of Dermatology, Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; NIHR Biomedical Research Centre at Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; NIHR Biomedical Research Centre at Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; The Psoriasis Association, Northampton, UK; The Psoriasis Association, Northampton, UK; Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Rese; International Federation of Psoriasis Associations; St Johns Institute of Dermatology, Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; Department of Dermatology, AP-HP Hopital Saint-Louis, Paris, France; King's College London; Catedra de Dermatologia, Hospital de Clinicas, Facultad de Ciencias Medicas, Universidad Nacional de Asuncion, Paraguay; Clinica Dermacross, Santiago, Chile; King's College London; Section of Dermatology and Venereology, University of Verona, Verona, Italy; Department of Dermatology, Edouard Herriot Hospital, Hospices Civils de Lyon, University of Lyon, Lyon, France; Department of Dermatology, Ghent University, Ghent, Belgium; Centro Studi GISED, Bergamo, Italy; Psychology Department, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, UK; Department of Dermatology, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain; Department of Dermatology, Amsterdam Public Health/Infection and Immunology, Amsterdam University Medical Centers, Location AMC, Amsterdam, The Netherlands; Department of Dermatology, Centro Hospitalar do Porto, Portugal; Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Rese; International Federation of Psoriasis Associations; School of Cancer and Pharmaceutical Sciences, Kings College London, London, UK; Centre for Rheumatic Diseases, King's College London, London, UK; Centre for Rheumatic Diseases, King's College London, London, UK; 3Dermatology Centre, Salford Royal NHS Foundation Trust, The University of Manchester, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Res; NIHR Biomedical Research Centre at Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK; St Johns Institute of Dermatology, Guys and St Thomas NHS Foundation Trust and Kings College London, London, UK","BackgroundIndirect excess morbidity has emerged as a major concern in the COVID-19 pandemic. People with psoriasis may be particularly vulnerable to this because of prevalent anxiety and depression, multimorbidity and therapeutic use of immunosuppression.
 
 ObjectiveCharacterise the factors associated with worsening psoriasis in the COVID-19 pandemic, using mental health status (anxiety and depression) as the main exposure of interest.
@@ -1515,13 +1580,6 @@ What this study addsO_LIIn 70,464 people with atrial fibrillation, at the thresh
 C_LIO_LIThis might be explained by OACs preventing severe COVID-19 outcomes, or more cautious behaviours and environmental factors reducing the risk of SARS-CoV-2 infection in those taking OACs.
 C_LIO_LIIn 372,746 people with non-valvular atrial fibrillation, there was no evidence of a higher risk of severe COVID-19 outcomes associated with warfarin compared with DOACs.
 C_LI",epidemiology,exact,100,100
-medRxiv,10.1101/2021.04.26.21255732,2021-04-28,https://medrxiv.org/cgi/content/short/2021.04.26.21255732,Deprivation and Exposure to Public Activities during the COVID-19 Pandemic in England and Wales,Sarah Beale; Isobel Braithwaite; Annalan MD Navaratnam; Pia Hardelid; Alison Rodger; Anna Aryee; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Robert W Aldridge; Andrew C Hayward; - Virus Watch Collaborative,"University College London; University College London; University College London; University College London; University College London; Royal Free London NHS Foundation Trust,; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; ","BackgroundDifferential exposure to public activities and non-household contacts may contribute to stark deprivation-related inequalities in SARS-CoV-2 infection and outcomes, but has not been directly investigated. We set out to investigate whether participants in Virus Watch - a large community cohort study based in England and Wales - reported different levels of exposure to public activities and non-household contacts during the Autumn-Winter phase of the COVID-19 pandemic according to postcode-level socioeconomic deprivation.
-
-MethodsParticipants (n=20120-25228 across surveys) reported their daily activities during three weekly periods in late November 2020, late December 2020, and mid-February 2021. Deprivation was quantified based on participants postcode of residence using English or Welsh Indices of Multiple Deprivation quintiles. We used Poisson mixed effect models with robust standard errors to estimate the relationship between deprivation and risk of exposure to public activities during each survey period.
-
-ResultsRelative to participants in the least deprived areas, participants in the most deprived areas persistently exhibited elevated risk of exposure to vehicle sharing (aRR range across time points 1.73-8.52), public transport (aRR 3.13-5.73), work or education outside of the household (aRR 1.09-1.21), essential shops (aRR 1.09-1.13) and non-household contacts (aRR 1.15-1.19) across multiple survey periods.
-
-ConclusionDifferential exposure to essential public activities in deprived communities is likely to contribute to inequalities in infection risk and outcomes during the COVID-19 pandemic. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities.",epidemiology,exact,100,100
 medRxiv,10.1101/2021.04.21.21255807,2021-04-27,https://medrxiv.org/cgi/content/short/2021.04.21.21255807,A randomised clinical trial of azithromycin versus standard care in ambulatory COVID-19 - the ATOMIC2 trial,Timothy SC Hinks; Lucy Cureton; Ruth Knight; Ariel Wang; Jennifer L Cane; Vicki S Barber; Joanna Black; Susan J Dutton; James Melhorn; Maisha Jabeen; Phil Moss; Rajendar Garlapati; Tanya Baron; Graham Johnson; Fleur Cantle; David Clarke; Samer Elkhodair; Jonathan Underwood; Daniel Lasserson; Ian D Pavord; Sophie B Morgan; Duncan Richards,"University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; St George's Hospital, London; East Lancashire NHS Hospitals; Oxford University Hospitals NHS Trust; Royal Derby Hospital; Kings College Hospital, London; Royal Berkshire Hospital; University College London Hospital; Cardiff University; Oxford University Hospitals NHS Trust; University of Oxford; University of Oxford; University of Oxford","BackgroundThe antibacterial, anti-inflammatory and antiviral properties of azithromycin suggest therapeutic potential against COVID-19. Randomised data in mild-moderate disease are lacking. We assessed whether azithromycin is effective in reducing hospitalisation in patients with mild-moderate COVID-19.
 
 MethodsThis open-label, randomised superiority clinical trial at 19 centres in the United Kingdom enrolled adults, [&ge;]18 years, presenting to hospitals with clinically-diagnosed highly-probable or confirmed COVID-19 infection, with <14 days symptoms, considered suitable for initial ambulatory management. Patients were randomised (1:1) to azithromycin (500 mg daily orally for 14 days) or to standard care without macrolides. The primary outcome was the difference in proportion of participants with death or hospital admission from any cause over the 28 days from randomisation, assessed according to intention-to-treat (ITT). Trial registration: ClinicalTrials.gov, NCT04381962, Study closed.
@@ -1965,6 +2023,15 @@ bioRxiv,10.1101/2020.12.23.424229,2020-12-25,https://biorxiv.org/cgi/content/sho
 medRxiv,10.1101/2020.12.18.20248477,2020-12-20,https://medrxiv.org/cgi/content/short/2020.12.18.20248477,Face covering adherence is positively associated with better mental health and wellbeing: a longitudinal analysis of the CovidLife surveys,Drew M Altschul; Chloe Fawns-Ritchie; Alex Kwong; Louise Hartley; Clifford Nangle; Rachel Edwards; Rebecca Dawson; Christie Levein; Archie Campbell; Robin Flaig; Andrew McIntosh; Ian Deary; Riccardo Marioni; Caroline Hayward; Cathie Sudlow; Elaine Douglas; David Bell; David Porteous,The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; University of Stirling; University of Stirling; The University of Edinburgh,"Face masks or coverings are effective at reducing airborne infection rates, yet pandemic mitigation measures, including wearing face coverings, have been suggested to contribute to reductions in quality of life and poorer mental health. Longitudinal analyses of more than 11,000 participants across the UK found no association between lower adherence to face covering guidelines and poorer mental health. The opposite appears to be true. Even after controlling for behavioral, social, and psychological confounds, including measures of pre-pandemic mental health, individuals who wore face coverings ""most of the time"" or ""always"" had better mental health and wellbeing than those who did not. These results suggest that wearing face coverings more often will not negatively impact mental health.",psychiatry and clinical psychology,exact,100,100
 medRxiv,10.1101/2020.12.10.20247155,2020-12-14,https://medrxiv.org/cgi/content/short/2020.12.10.20247155,Self-harm presentations to Emergency Departments and Place of Safety during the first wave of the UK COVID-19 pandemic: South London and Maudsley data on service use from February to June 2020.,Eleanor Nuzum; Evangelia Martin; Gemma Morgan; Rina Dutta; Christoph Mueller; Catherine Polling; Megan Pritchard; Sumithra Velupillai; Robert Stewart,South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"The lockdown and social distancing policy imposed due to the COVID-19 pandemic has had a substantial impact on both mental health service delivery, and the ways in which people are accessing these services. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for around 1.2m residents in South London) have highlighted increased use of virtual contacts by mental health teams, with dropping numbers of face-to-face contacts over the first wave of the pandemic. There has been concern that the impact of the COVID-19 pandemic would lead to higher mental health emergencies, particularly instances of self-harm. However, with people advised to stay at home during the  first wave lockdown, it is as yet unclear whether this impacted mental health service presentations. Taking advantage of SLaMs Clinical Records Interactive Search (CRIS) data resource with daily updates of information from its electronic mental health records, this paper describes overall presentations to Emergency Department (ED) mental health liaison teams, and those with self-harm. The paper focussed on three periods: i) a pre-lockdown period 1st February to 15th March, ii) a lockdown period 16th March to 10th May and iii) a post-lockdown period 11th May to 28th June. In summary, all attendances to EDs for mental health support decreased during the lockdown period, including those with self-harm. All types of self-harm decreased during lockdown, with self-poisoning remaining the most common. Attendances to EDs for mental health support increased post-lockdown, although were only just approaching pre-lockdown levels by the end of June 2020.",psychiatry and clinical psychology,exact,100,100
 medRxiv,10.1101/2020.12.07.20245183,2020-12-07,https://medrxiv.org/cgi/content/short/2020.12.07.20245183,"Indicators of COVID-19 status in a cohort study of university staff and post-graduate research students, including results from home antibody testing",Katrina A S Davis; Ewan Carr; Daniel Leightley; Valentina Vitiello; Gabriella Bergin Cartwright; Grace Lavelle; Alice Wickersham; Michael H Malim; Carolin Oetzmann; Catherine Polling; Sharon A.M. Stevelink; Reza Razavi; Matthew Hotopf; - KCL-CHECK research team,"KCL Institute of Psychiatry, Psychology and Neuroscience; KCL Institute of Psychiatry Psychology and Neuroscience; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; ","Background Definitive diagnosis of COVID-19 requires resources frequently restricted to the severely ill. Cohort studies must rely on surrogate indicators to define cases of COVID-19 in the community. We describe the prevalence and overlap of potential indicators including self-reported symptoms, suspicion, and routine test results, plus home antibody testing. Methods An occupational cohort of 2807 staff and postgraduate students at a large London university. Repeated surveys covering March to June 2020. Antibody test results from 'lateral flow' IgG/IgM cassettes in June 2020. Results 1882 participants had valid antibody test results, and 124 (7%) were positive. Core symptoms of COVID-19 were common (770 participants positive, 41%), although fewer met criteria on a symptom algorithm (n=297, 16%). Suspicion of COVID-19 (n=509, 27%) was much higher than positive external tests (n=39, 2%). Positive antibody tests were rare in people who had no suspicion (n=4, 1%) or no core symptoms (n=10, 2%). In those who reported external antibody tests, 15% were positive on the study antibody test, compared with 24% on earlier external antibody tests. Discussion Our results demonstrate the agreement between different COVID indicators. Antibody testing using lateral flow devices at home can detect asymptomatic cases and provide greater certainty to self-report; but due to weak and waning antibody responses to mild infection, may under-ascertain. Multiple indicators used in combination can provide a more complete story than one used alone. Cohort studies need to consider how they deal with different, sometimes conflicting, indicators of COVID-19 illness to understand its long-term outcomes.",epidemiology,exact,100,100
+medRxiv,10.1101/2020.12.03.20243535,2020-12-04,https://medrxiv.org/cgi/content/short/2020.12.03.20243535,OpenSAFELY: impact of national guidance on switching from warfarin to direct oral anticoagulants (DOACs) in early phase of COVID-19 pandemic in England,Helen J Curtis; Brian MacKenna; Alex J Walker; Richard Croker; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Peter Inglesby; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan Bhaskaran; Anna Schultze; Christopher T Rentsch; Elizabeth Williamson; William Hulme; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Henry Drysdale; Rosalind M Eggo; Kevin Wing; Angel Wong; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Ian J Douglas; Liam Smeeth; Ben Goldacre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundEarly in the COVID-19 pandemic the NHS recommended that appropriate patients anticoagulated with warfarin should be switched to direct acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately co-prescribed two anticoagulants following a medication change, and associated monitoring.
+
+ObjectiveTo describe which people were switched from warfarin to DOACs; identify potentially unsafe co-prescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic.
+
+MethodsWorking on behalf of NHS England we conducted a population cohort based study using routine clinical data from >17 million adults in England.
+
+Results20,000 of 164,000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in co-prescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. INR testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420).
+
+ConclusionsIncreased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people co-prescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.",cardiovascular medicine,exact,100,100
 medRxiv,10.1101/2020.11.27.20238147,2020-12-02,https://medrxiv.org/cgi/content/short/2020.11.27.20238147,"Ethnicity, Household Composition and COVID-19 Mortality: A National Linked Data Study",Vahe Nafilyan; Nazrul Islam; Daniel Ayoubkhani; Clare Gilles; Srinivasa Vittal Katikireddi; Rohini Mathur; Annabel Summerfield; Karen Tingay; Miqdad Asaria; Ann John; Peter Goldblatt; Amitava Banerjee; Myer Glickman; Kamlesh Khunti,"Office for National Statistics; Nuffield Department of Population Health, Big Data Institute, University of Oxford; Office for National Statistics; Diabetes Research Centre, University of Leicester; University of Glasgow; London School of Hygiene and Tropical Medicine; Office for National Statistics; Office for National Statistics; London School of Economics and Political Sciences; Swansea University; UCL Institute of Health Equity, University College London; University College London; Office for National Statistics; Diabetes Research Centre, University of Leicester","BackgroundEthnic minorities have experienced disproportionate COVID-19 mortality rates. We estimated associations between household composition and COVID-19 mortality in older adults ([&ge;] 65 years) using a newly linked census-based dataset, and investigated whether living in a multi-generational household explained some of the elevated COVID-19 mortality amongst ethnic minority groups.
 
 MethodsUsing retrospective data from the 2011 Census linked to Hospital Episode Statistics (2017-2019) and death registration data (up to 27th July 2020), we followed adults aged 65 years or over living in private households in England from 2 March 2020 until 27 July 2020 (n=10,078,568). We estimated hazard ratios (HRs) for COVID-19 death for people living in a multi-generational household compared with people living with another older adult, adjusting for geographical factors, socio-economic characteristics and pre-pandemic health. We conducted a causal mediation analysis to estimate the proportion of ethnic inequalities explained by living in a multi-generational household.
@@ -1988,7 +2055,6 @@ C_LIO_LIOptimal symptom combinations maximise case capture considering available
 C_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health
 C_LI",health informatics,exact,100,100
 medRxiv,10.1101/2020.11.19.20234120,2020-11-23,https://medrxiv.org/cgi/content/short/2020.11.19.20234120,Actionable druggable genome-wide Mendelian randomization identifies repurposingopportunities for COVID-19,Liam Gaziano; Claudia Giambartolomei; Alexandre C Pereira; Anna Gaulton; Daniel C Posner; Sonja A Swanson; Yuk Lam Ho; Sudha K Iyengar; Nicole M Kosik; Marijana Vujkovic; David R Gagnon; A Patricia Bento; Pedro Beltrao; Inigo Barrio Hernandez; Lars Ronnblom; Niklas Hagberg; Christian Lundtoft; Claudia Langenberg; Maik Pietzner; Dennis Valentine; Elias Allara; Praveen Surendran; Stephen Burgess; Jing Hua Zhao; James E Peters; Bram P Prins; John Danesh; Poornima Devineni; Yunling Shi; Kristine E Lynch; Scott L DuVall; Helene Garcon; Lauren Thomann; Jin J Zhou; Bryan R Gorman; Jennifer E Huffman; Christopher J O'Donnell; Philip S Tsao; Jean C Beckham; Saiju Pyarajan; Sumitra Muralidhar; Grant D Huang; Rachel Ramoni; Adriana M Hung; Kyong-Mi Chang; Yan V Sun; Jacob Joseph; Andrew R Leach; Todd L Edwards; Kelly Cho; J Michael Gaziano; Adam S Butterworth; Juan P Casas,"VA Boston Healthcare System, University of Cambridge; Instituto Italiano di Tecnologia, University of California Los Angeles; University of Sao Paulo, Harvard University; European Molecular Biology Laboratory, European Bioinformatics Institute; VA Boston Healthcare System; Erasmus Medical Center; VA Boston Healthcare System; Case Western Reserve University and Louis Stoke Cleveland VAMC; VA Boston Healthcare System; The Corporal Michael J. Crescenz VA Medical Center, the University of Pennsylvania Perelman School of Medicine; Boston University, VA Boston Healthcare System; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; European Molecular Biology Laboratory, European Bioinformatics Institute; Uppsala University; Uppsala University; Uppsala University; Charite University Medicine Berlin,  Universityof Cambridge; Universityof Cambridge; University College London; University of Cambridge; Wellcome Genome Campus and University of Cambridge; University of Cambridge; University of Cambridge; Imperial College London; Wellcome Genome Campus and University of Cambridge; University of Cambridge; VA Boston Healthcare System; VA Boston Healthcare System; VA Salt Lake City Health Care System, University of Utah; VA Salt Lake City Health Care System, University of Utah; VA Boston Healthcare System; VA Boston Healthcare System; University of Arizona, Phoenix VA Health Care System; VA Boston Healthcare System; VA Boston Healthcare System; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Palo Alto Health Care System, Stanford University School of Medicine; Durham VA Medical Center, Duke University School of Medicine; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs; Department of Veterans Affairs, Vanderbilt University; The Corporal Michael J. Crescenz VA Medical Center, University of Pennsylvania; Atlanta VA Health Care System, Emory University Rollins School of Public Health; VA Boston Healthcare System and Brigham & Women's Hospital; European Molecular Biology Laboratory, European Bioinformatics Institute; Department of Veterans Affairs Tennessee Valley Healthcare System, Vanderbilt Genetics Institute Vanderbilt University Medical Center; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School; University of Cambridge, Wellcome Genome Campus and University of Cambridge; VA Boston Healthcare System, Brigham and Women's Hospital, Harvard Medical School","Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization (MR) analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2: P=1.6x10-6, IFNAR2: P=9.8x10-11, and IL-10RB: P=1.9x10-14) using cis-eQTL genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared eQTL signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.",epidemiology,exact,100,100
-medRxiv,10.1101/2020.11.19.20234849,2020-11-22,https://medrxiv.org/cgi/content/short/2020.11.19.20234849,Community factors and excess mortality in first wave of the COVID-19 pandemic.,Bethan Davies; Brandon L Parkes; James Bennett; Daniela Fecht; Marta Blangiardo; Majid Ezzati; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.",epidemiology,exact,100,100
 medRxiv,10.1101/2020.11.06.20227108,2020-11-07,https://medrxiv.org/cgi/content/short/2020.11.06.20227108,Primary school staff reflections on school closures due to COVID-19 and recommendations for the future: a national qualitative survey,Emily Marchant; Charlotte Todd; Michaela James; Tom Crick; Russell Dwyer; Sinead Brophy,Swansea University; Swansea University; Swansea University; Swansea University; St Thomas Community Primary School; Swansea University,"School closures due to the COVID-19 global pandemic are likely to have a range of negative consequences spanning the domains of child development, education and health, in addition to the widening of inequalities and inequities. Research is required to improve understanding of the impact of school closures on the education, health and wellbeing of pupils and school staff, the challenges posed during reopening and importantly to identify how countries can return to in-school education and to inform policy. This qualitative study aimed to reflect on the perspectives and experiences of primary school staff (pupils aged 3-11) in Wales regarding school closures and the initial reopening of schools and to identify recommendations for the future. A total of 208 school staff completed a national online survey through the HAPPEN primary school network, consisting of questions about school closures (March to June 2020), the phased reopening of schools (June to July 2020) and a return to full-time education. Thematic analysis of survey responses highlighted that primary school staff perceive that gaps in learning, health and wellbeing have increased and inequalities have widened during school closures. Findings from this study identified five recommendations; (i) prioritise the health and wellbeing of pupils and staff; (ii) focus on enabling parental engagement and support; (iii) improve digital competence amongst pupils, teachers and parents; (iv) consider opportunities for smaller class sizes and additional staffing; and (v) improve the mechanism of communication between schools and families, and between government and schools.",public and global health,exact,100,100
 medRxiv,10.1101/2020.11.03.20220699,2020-11-04,https://medrxiv.org/cgi/content/short/2020.11.03.20220699,A prospective study of risk factors associated with seroprevalence of SARS-CoV-2 antibodies in healthcare workers at a large UK teaching hospital,Daniel J Cooper; Sara Lear; Laura Watson; Ashley Shaw; Mark Ferris; Rainer Doffinger; Rachel Bousfield; Katherine Sharrocks; Michael Weekes; Ben Warne; Dominic Sparkes; Nick K Jones; Lucy Rivett; Matthew Routledge; Afzal Chaudhry; Katherine Dempsey; Montgomery Matson; Adil Lakha; George Gathercole; Olivia O'Connor; Emily Wilson; Orthi Shahzad; Kieran Toms; Rachel Thompson; Ian Halsall; David Halsall; Sally Houghton; Sofia Papadia; Nathalie Kingston; Kathleen Stirrups; Barbara Graves; Neil Walker; Hannah Stark; - The CITIID-NIHR BioResource COVID-19 Collaboration; Daniela De Angelis; Shaun Seaman; John Bradley; M Estée Török; Ian G. Goodfellow; Stephen Baker,"Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; NIHR Cambridge Clinical Research Facility; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; NIHR Cambridge Clinical Research Facility.; University of Cambridge School of Clinical Medicine; University of Cambridge School of Clinical Medicine; University of Cambridge School of Clinical Medicine; University of Cambridge School of Clinical Medicine; University of Cambridge School of Clinical Medicine; University of Cambridge School of Clinical Medicine; University of Cambridge School of Clinical Medicine; University of Cambridge School of Clinical Medicine; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; NIHR BioResource, NIHR Cambridge Biomedical Research Centre; NIHR BioResource, NIHR Cambridge Biomedical Research Centre; NIHR BioResource, NIHR Cambridge Biomedical Research Centre; NIHR BioResource, NIHR Cambridge Biomedical Research Centre; NIHR BioResource, NIHR Cambridge Biomedical Research Centre; NIHR BioResource, Cambridge University Hospitals NHS Foundation Trust; ; MRC Biostatistics Unit, University of Cambridge; MRC Biostatistics Unit, University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Department of pathology, Division of virology, University of Cambridge; Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK","BackgroundThe COVID-19 pandemic continues to grow at an unprecedented rate. Healthcare workers (HCWs) are at higher risk of SARS-CoV-2 infection than the general population but risk factors for HCW infection are not well described.
 
@@ -2070,7 +2136,6 @@ RESULTS IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSA small study in 47
 Added value of this studyTo our knowledge this is the first study to explore changes in healthcare contacts for acute physical and mental health conditions in a large population representative of the UK. We used electronic primary care health records of nearly 10 million individuals across the UK to investigate the indirect impact of COVID-19 on primary care contacts for mental health, acute alcohol-related events, asthma/chronic obstructive pulmonary disease (COPD) exacerbations, and cardiovascular and diabetic emergencies up to July 2020. For all conditions studied, we found primary care contacts dropped dramatically following the introduction of population-wide restriction measures in March 2020. By July 2020, with the exception of unstable angina and acute alcohol-related events, primary care contacts for all conditions studied had not recovered to pre-lockdown levels. In the general population, estimates of the absolute reduction in the number of primary care contacts up to July 2020, compared to what we would expect from previous years varied from fewer than 10 contacts per million for some cardiovascular outcomes, to 12,800 per million for depression and 6,600 for anxiety. In people with COPD, we estimated there were 43,900 per million fewer contacts for COPD exacerbations up to July 2020 than what we would expect from previous years.
 
 Implicatins of all the available evidenceWhile our results may represent some genuine reduction in disease frequency (e.g. the restriction measures may have improved diabetic glycaemic control due to more regular daily routines at home), it is more likely the reduced primary care conatcts we saw represent a substantial burden of unmet need (particularly for mental health conditions) that may be reflected in subsequent increased mortality and morbidity. Health service providers should take steps to prepare for increased demand in the coming months and years due to the short and longterm ramifications of reduced access to care for severe acute physical and mental health conditions. Maintaining access to primary care is key to future public health planning in relation to the pandemic.",primary care research,exact,100,100
-bioRxiv,10.1101/2020.10.29.339317,2020-10-30,https://biorxiv.org/cgi/content/short/2020.10.29.339317,"COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning",- The COVID Moonshot Consortium; Hagit Achdout; Anthony Aimon; Dominic S Alonzi; Robert Arbon; Elad Bar-David; Haim Barr; Amir Ben-Shmuel; James Bennett; Vitaliy A. Bilenko; Vitaliy A. Bilenko; Melissa L. Boby; Bruce Borden; Pascale Boulet; Gregory R. Bowman; Juliane Brun; Lennart Brwewitz; Sarma BVNBS; Mark Calmiano; Anna Carbery; Daniel Carney; Emma Cattermole; Edcon Chang; Eugene Chernyshenko; John D. Chodera; Austin Clyde; Joseph E. Coffland; Galit Cohen; Jason Cole; Alessandro Contini; Lisa Cox; Tristan Ian Croll; Milan Cvitkovic; Alex Dias; Kim Donckers; David L. Dotson; Alice Douangamath; Shirly Duberstein; Tim Dudgeon; Louise Dunnett; Peter K. Eastman; Noam Erez; Charles J. Eyermann; Mike Fairhead; Gwen Fate; Daren Fearon; Oleg Fedorov; Matteo Ferla; Rafaela S. Fernandes; Lori Ferrins; Mihajlo Filep; Richard Foster; Holly Foster; Laurent Fraisse; Ronen Gabizon; Adolfo Garcia-Sastre; Victor O. Gawriljuk; Paul Gehrtz; Carina Gileadi; Charline Giroud; William G. Glass; Robert Glen; Itai Glinert; Andre S. Godoy; Marian Gorichko; Tyler Gorrie-Stone; Ed J. Griffen; Sophie Hahn; Amna Haneef; Storm Hassell Hart; Jag Heer; Michael Henry; Michelle Hill; Sam Horrell; Qiu Yu Huang; Victor D. Huliak; Victor D. Huliak; Matthew F.D. Hurley; Tomer Israely; Andrew Jajack; Jitske Jansen; Eric Jnoff; Dirk Jochmans; Tobias John; Steven De Jonghe; Benjamin Kaminow; Lulu Kang; Anastassia L. Kantsadi; Peter W. Kenny; J. L. Kiappes; Serhii O. Kinakh; Serhii O. Kinakh; Lizbe Koekemoer; Boris Kovar; Tobias Krojer; Van La; Alpha A. Lee; Bruce A. Lefker; Haim Levy; Ivan G. Logvinenko; Ivan G. Logvinenko; Nir London; Petra Lukacik; Hannah Bruce Macdonald; Elizabeth M. MacLean; Laetitia L Makower; Tika R. Malla; Tatiana Matviiuk; Willam McCorkindale; Briana L. McGovern; Sharon Melamed; Kostiantyn P. Melnykov; Kostiantyn P. Melnykov; Oleg Michurin; Pascal Miesen; Halina Mikolajek; Bruce F. Milne; David Minh; Aaron Morris; Garrett M. Morris; Melody Jane Morwitzer; Demetri Moustakas; Charles Mowbray; Aline M. Nakamura; Jose Brandao Neto; Johan Neyts; Luong Nguyen; Gabriela D. Noske; Vladas Oleinikovas; Glaucius Oliva; Gijs J. Overheul; David Owen; Ruby Pai; Jin Pan; Nir Paran; Alexander Payne; Benjamin Perry; Maneesh Pingle; Jakir Pinjari; Boaz Politi; Ailsa Powell; Vladimir Psenak; Ivan Pulido; Reut Puni; Victor L. Rangel; Rambabu N. Reddi; Paul Rees; St Patrick Reid; Lauren Reid; Efrat Resnick; Emily Grace Ripka; Matthew C. Robinson; Ralph P. Robinson; Jaime Rodriguez-Guerra; Romel Rosales; Dominic A. Rufa; Kadi Saar; Kumar Singh Saikatendu; Eidarus Salah; David Schaller; Jenke Scheen; Celia A. Schiffer; Chris Schofield; Mikhail Shafeev; Aarif Shaikh; Ala M. Shaqra; Jiye Shi; Khriesto Shurrush; Sukrit Singh; Assa Sittner; Peter Sjo; Rachael Skyner; Adam Smalley; Bart Smeets; Mihaela D. Smilova; Leonardo J. Solmesky; John Spencer; Claire Strain-Damerell; Vishwanath Swamy; Hadas Tamir; Jenny C. Taylor; Rachael E. Tennant; Warren Thompson; Andrew Thompson; Susana Tomasio; Charlie Tomlinson; Igor S. Tsurupa; Igor S. Tsurupa; Anthony Tumber; Ioannis Vakonakis; Ronald P. van Rij; Laura Vangeel; Finny S. Varghese; Mariana Vaschetto; Einat B. Vitner; Vincent Voelz; Andrea Volkamer; Frank von Delft; Annette von Delft; Martin Walsh; Walter Ward; Charlie Weatherall; Shay Weiss; Kris M. White; Conor Francis Wild; Karolina D Witt; Matthew Wittmann; Nathan Wright; Yfat Yahalom-Ronen; Nese Kurt Yilmaz; Daniel Zaidmann; Ivy Zhang; Hadeer Zidane; Nicole Zitzmann; Sarah N Zvornicanin,"; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; The Weizmann Institute of Science; Israel Institution of Biological Research; University of Oxford; Enamine Ltd; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Folding@home Consortium; DNDi; Washington University School of Medicine; University of Oxford; University of Oxford; Sai Life Sciences; UCB; University of Oxford;Diamond Light Source; Takeda Development Center Americas, Inc.; University of Oxford; Takeda Development Center Americas, Inc.; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Argonne National Laboratory; N/A; The Weizmann Institute of Science; Cambridge Crystallographic Datacentre; University of Milan; Life Compass Consulting Ltd; Cambridge Institute for Medical Research, The University of Cambridge; PostEra Inc.; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; N/A; Diamond Light Source Ltd; Research Complex at Harwell; The Weizmann Institute of Science; Informatics Matters; Diamond Light Source Ltd; Research Complex at Harwell; Department of Bioengineering until Sept. 1, then Department of Chemistry; Israel Institution of Biological Research; Northeastern University; University of Oxford; Thames Pharma Partners; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; University of Oxford; University of Sao Paulo; Northeastern University; Weizmann Institute of Science; University of Leeds; University of Leeds; DNDi; The Weizmann Institute of Science; Icahn School of Medicine at Mount Sinai; University of Sao Paulo; The Weizmann Institute of Science; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Cambridge; Israel Institution of Biological Research; University of Sao Paulo; Taras Shevchenko National University of Kyiv; Diamond Light Source Ltd; Research Complex at Harwell; MedChemica Ltd; DNDi; Illinois Institute of Technology; University of Sussex; UCB; Memorial Sloan Kettering Cancer Center; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; University of Massachusetts Chan Medical School; Enamine Ltd; Enamine Ltd; Temple University; Israel Institution of Biological Research; PostEra Inc.; Radboud University Medical Center; UCB; Katholieke Universiteit Leuven; University of Oxford; Katholieke Universiteit Leuven; Memorial Sloan Kettering Cancer Center; Illinois Institute of Technology; University of Oxford; Independent Scientist; University of Oxford; Enamine Ltd; Enamine Ltd; University of Oxford; M2M solutions, s.r.o; University of Oxford; Illinois Institute of Technology; PostEra Inc.; University of Cambridge; Thames Pharma Partners LLC; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; The Weizmann Institute of Science; Diamond Light Source Ltd; Research Complex at Harwell; Memorial Sloan Kettering Cancer Center; University of Oxford; University of Oxford; University of Oxford; Enamine Ltd; University of Cambridge; Icahn School of Medicine at Mount Sinai; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; Enamine Ltd; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; University of Coimbra and University of Aberdeen; Illinois Institute of Technology; PostEra Inc; University of Oxford; Department of Pathology and Microbiology; Relay Therapeutics; DNDi; University of Sao Paulo; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; PostEra Inc.; University of Sao Paulo; UCB; University of Sao Paulo; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; PostEra Inc.; PostEra Inc.; Israel Institution of Biological Research; Memorial Sloan Kettering Cancer Center; DNDi; Sai Life Sciences; Sai Life Sciences; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; M2M solutions, s.r.o; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; School of Pharmaceutical Sciences of Ribeirao Preto; The Weizmann Institute of Science; Compass Bussiness Partners Ltd; Department of Pathology and Microbiology; MedChemica Ltd; The Weizmann Institute of Science; PostEra Inc.; PostEra Inc.; Thames Pharma Partners LLC; Charite Universitatsmedizin Berlin; Icahn School of Medicine at Mount Sinai; Memorial Sloan Kettering Cancer Center; University of Cambridge; Takeda Development Center Americas, Inc.; University of Oxford; Charite Universitatsmedizin Berlin; Memorial Sloan Kettering Cancer Center; University of Massachusetts Chan Medical School; University of Oxford; Enamine Ltd; Sai Life Sciences; University of Massachusetts Chan Medical School; UCB; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; DNDi; Diamond Light Source Ltd; Research Complex at Harwell; UCB; Radboud University Medical Center; University of Oxford; The Weizmann Institute of Science; University of Sussex; Diamond Light Source Ltd; Research Complex at Harwell; Sai Life Sciences; Israel Institution of Biological Research; University of Oxford; Lhasa Limited; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Collaborative Drug Discovery; Diamond Light Source Ltd; Research Complex at Harwell; Enamine Ltd; Enamine Ltd; University of Oxford; University of Oxford; Radboud University Medical Center; Katholieke Universiteit Leuven; Radboud University Medical Center; Collaborative Drug Discovery; Israel Institution of Biological Research; Temple University; Charite Universitatsmedizin Berlin; Diamond Light Source Ltd; University of Oxford; Research Complex at Harwell; University of Johannesburg; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; Walter Ward Consultancy & Training; Collaborative Drug Discovery; Israel Institution of Biological Research; Icahn School of Medicine at Mount Sinai; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Oxford; Israel Institution of Biological Research; University of Massachusetts Chan Medical School; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; The Weizmann Institute of Science; University of Oxford; University of Massachusetts Chan Medical School","The COVID-19 pandemic was a stark reminder that a barren global antiviral pipeline has grave humanitarian consequences. Pandemics could be prevented in principle by accessible, easily deployable broad-spectrum oral antivirals. Here we report the results of the COVID Moonshot, a fully open-science, crowd sourced, structure-enabled drug discovery campaign targeting the SARS-CoV-2 main protease. We discovered a novel chemical series that is differentiated from current Mpro inhibitors in that it maintains a new non-covalent, non-peptidic scaffold with nanomolar potency. Our approach leveraged crowdsourcing, high-throughput structural biology, machine learning, and exascale molecular simulations and high-throughput chemistry. In the process, we generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. In a first for a structure-based drug discovery campaign, all compound designs (>18,000 designs), crystallographic data (>840 ligand-bound X-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2,400 compounds) for this campaign were shared rapidly and openly, creating a rich open and IP-free knowledgebase for future anti-coronavirus drug discovery.",biochemistry,exact,100,100
 medRxiv,10.1101/2020.10.25.20219048,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.25.20219048,Viral load in community SARS-CoV-2 cases varies widely and temporally,Ann Sarah Walker; Emma Pritchard; Thomas House; Julie V Robotham; Paul J Birrell; Iain Bell; John I Bell; John N Newton; Jeremy Farrar; Ian Diamond; Ruth Studley; Jodie Hay; Karina-Doris Vihta; Timothy EA Peto; Nicole Stoesser; Philippa C Matthews; David W Eyre; Koen Pouwels; - the COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Manchester; Public Health England; Public Health England; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; Office for National Statistics; Office for National Statistics; University of Glasgow; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; ,"Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load). Of 3,312,159 nose and throat swabs taken 26-April-2020 to 13-March-2021 in the UKs national COVID-19 Infection Survey, 27,902(0.83%) were RT-PCR-positive, 10,317(37%), 11,012(40%) and 6,550(23%) for 3, 2 or 1 of the N, S and ORF1ab genes respectively, with median Ct=29.2 ([~]215 copies/ml; IQR Ct=21.9-32.8, 14-56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity and age. Single-gene positives almost invariably had Ct>30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6,189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4,808(78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody-negative. Community SARS-CoV-2 Ct values could be a useful epidemiological early-warning indicator.
 
 IMPACT STATEMENTCt values from SARS-CoV-2 RT-PCR tests vary widely and over calendar time. They have the potential to be used more broadly in public testing programmes as an ""early-warning"" system for shifts in infectious load and hence transmission.",infectious diseases,exact,100,100
@@ -2242,15 +2307,6 @@ At the recommended threshold, PMEWS and the WHO criteria showed good sensitivity
 
 ConclusionCURB-65, PMEWS and NEWS2 provide good but not excellent prediction for adverse outcome in suspected COVID-19, and predicted death without organ support better than receipt of organ support. PMEWS, the WHO criteria and NEWS2 (using a lower threshold than usually recommended) provide good sensitivity at the expense of specificity.
 
-RegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",emergency medicine,exact,100,100
-medRxiv,10.1101/2020.09.01.20185793,2020-09-03,https://medrxiv.org/cgi/content/short/2020.09.01.20185793,Prognostic accuracy of emergency department triage tools for children with suspected COVID-19: The PRIEST observational cohort study,Katie Biggs; Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Matthew Bursnall; Amanda Loban; Simon Waterhouse; Richard Simmonds; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust,"ObjectivesEmergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection.
-
-MethodsWe undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Childrens Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.
-
-ResultsWe collected data from 1530 children, including 26 (1.7%) with an adverse outcome. C-statistics were 0.80 (95% confidence interval 0.73-0.87) for the WHO algorithm, 0.80 (0.71-0.90) for POPS, 0.76 (0.67-0.85) for COAST, and 0.71 (0.59-0.82) for SFHPC. Using pre-specified thresholds, the WHO algorithm had the highest sensitivity (0.85) and lowest specificity (0.75), but POPS and COAST could optimise sensitivity (0.96 and 0.92 respectively) at the expense of specificity (0.25 and 0.38 respectively) by using a threshold of any score above zero instead of the pre-specified threshold.
-
-ConclusionExisting triage tools have good but not excellent prediction for adverse outcome in children with suspected COVID-19. POPS and COAST could achieve an appropriate balance of sensitivity and specificity for supporting decisions to discharge home by considering any score above zero to be positive.
-
 RegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",emergency medicine,exact,100,100
 medRxiv,10.1101/2020.08.26.20182279,2020-09-01,https://medrxiv.org/cgi/content/short/2020.08.26.20182279,COVID-19 infection dynamics in care homes in the East of England: a retrospective genomic epidemiology study,William L Hamilton; Gerry Tonkin-Hill; Emily Smith; Dinesh Aggarwal; Charlotte Houldcroft; Ben Warne; Colin Brown; Luke Meredith; Myra Hosmillo; Aminu Jahun; Martin Curran; Surendra Parmar; Laura Caller; Sarah Caddy; Fahad Khokhar; Anna Yakovleva; Grant Hall; Theresa Feltwell; Malte Pinckert; Iliana Georgana; Yasmin Chaudhry; Nicholas Brown; Sonia Goncalves; Roberto Amato; Ewan Harrison; Mathew Beale; Michael Spencer Chapman; David Jackson; Ian Johnston; Alex Alderton; John Sillitoe; Cordelia Langford; Gordon Dougan; Sharon Peacock; Dominic Kwiatowski; Ian Goodfellow; M. Estee Torok; - COVID-19 Genomics Consortium UK,"University of Cambridge; Wellcome Sanger Institute; Cambridgeshire County Council, UK; Public Health England; University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; Public Health England; University of Cambridge; University of Cambridge; University of Cambridge; Public Health England; Public Health England; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Public Health England; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; University of Cambridge; University of Cambridge; Wellcome Sanger Institute; University of Cambridge; University of Cambridge; ","COVID-19 poses a major challenge to care homes, as SARS-CoV-2 is readily transmitted and causes disproportionately severe disease in older people. Here, 1,167 residents from 337 care homes were identified from a dataset of 6,600 COVID-19 cases from the East of England. Older age and being a care home resident were associated with increased mortality. SARS-CoV-2 genomes were available for 700 residents from 292 care homes. By integrating genomic and temporal data, 409 viral clusters within the 292 homes were identified, indicating two different patterns - outbreaks among care home residents and independent introductions with limited onward transmission. Approximately 70% of residents in the genomic analysis were admitted to hospital during the study, providing extensive opportunities for transmission between care homes and hospitals. Limiting viral transmission within care homes should be a key target for infection control to reduce COVID-19 mortality in this population.
 
@@ -2296,6 +2352,7 @@ MethodsWe developed a simple, interactive tool to assess the impact of different
 ResultsWith sensitivity of 80%, infection prevalence of 1 in 2,000, and specificity 99.9% on all tests, PPV in the tested population of 100,000 will be only 29% with one test, increasing to > 99.5% (100% when rounded to the nearest %) with repeat testing in strategies 2 or 3. More realistically, if specificity is 95% for the first and 99.9% for subsequent tests, single test PPV will be only 1%, increasing to 86% with repeat testing in strategy 2, or 79% with strategy 3 (albeit with 6 fewer false negatives than strategy 2). In the whole population, or in particular individuals, PPV increases as infection becomes more common in the population but falls to unacceptably low levels with lower test specificity.
 
 ConclusionTo avoid multiple unnecessary restrictions on whole populations, and in particular individuals, from widespread population testing for SARS-CoV-2, the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions.",epidemiology,exact,100,100
+medRxiv,10.1101/2020.08.17.20175117,2020-08-21,https://medrxiv.org/cgi/content/short/2020.08.17.20175117,Real-time spatial health surveillance: mapping the UK COVID-19 epidemic,Richard Fry; Joe Hollinghurst; Helen R Stagg; Daniel A Thompson; Claudio Fronterre; Chris Orton; Ronan A Lyons; David V Ford; Aziz Sheikh; Peter J Diggle,Swansea University; Swansea University; Edinburgh University; Swansea University; Lancaster University; Swansea University; Swansea University; Swansea University; Edinburgh University; Lancaster University,"The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. A pre-requisite to an effective control strategy is that predictions need to be accompanied by estimates of their precision, to guard against over-reaction to potentially spurious features of  best guess predictions. In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.",public and global health,exact,100,100
 medRxiv,10.1101/2020.08.12.20173690,2020-08-14,https://medrxiv.org/cgi/content/short/2020.08.12.20173690,"Antibody prevalence for SARS-CoV-2 in England following first peak of the pandemic: REACT2 study in 100,000 adults",Helen Ward; Christina J Atchison; Matthew Whitaker; Kylie E. C. Ainslie; Joshua Elliott; Lucy C Okell; Rozlyn Redd; Deborah Ashby; Christl A. Donnelly; Wendy Barclay; Ara Darzi; Graham Cooke; Steven Riley; Paul Elliott,"Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London","BackgroundEngland, UK has experienced a large outbreak of SARS-CoV-2 infection. As in USA and elsewhere, disadvantaged communities have been disproportionately affected.
 
 MethodsNational REal-time Assessment of Community Transmission-2 (REACT-2) prevalence study using a self-administered lateral flow immunoassay (LFIA) test for IgG among a random population sample of 100,000 adults over 18 years in England, 20 June to 13 July 2020.
@@ -2600,15 +2657,6 @@ MethodsWe investigated staff reports regarding the impact of the COVID-19 pandem
 Results2,180 staff from a range of sectors, professions and specialties participated. Immediate infection control concerns were highly salient for inpatient staff, new ways of working for community staff. Multiple rapid adaptations and innovations in response to the crisis were described, especially remote working. This was cautiously welcomed but found successful in only some clinical situations. Staff had specific concerns about many groups of service users, including people whose conditions are exacerbated by pandemic anxieties and social disruptions; people experiencing loneliness, domestic abuse and family conflict; those unable to understand and follow social distancing requirements; and those who cannot engage with remote care.
 
 ConclusionThis overview of staff concerns and experiences in the early COVID-19 pandemic suggests directions for further research and service development: we suggest that how to combine infection control and a therapeutic environment in hospital, and how to achieve effective and targeted tele-health implementation in the community, should be priorities. The limitations of our convenience sample must be noted.",psychiatry and clinical psychology,exact,100,100
-medRxiv,10.1101/2020.06.10.20127175,2020-06-11,https://medrxiv.org/cgi/content/short/2020.06.10.20127175,Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic.,Amitava Banerjee; Suliang Chen; Laura Pasea; Alvina Lai; Michail Katsoulis; Spiros Denaxas; Vahe Nafilyan; Bryan Williams; Wai Keong Wong; Ameet Bakhai; Kamlesh Khunti; Deenan Pillay; Mahdad Noursadeghi; Honghan Wu; Nilesh Pareek; Daniel Bromage; Theresa Mcdonagh; Jonathan Byrne; James T Teo; Ajay Shah; Ben Humberstone; Liang V Tang; Anoop SV Shah; Andrea Rubboli; Yutao Guo; Yu Hu; Cathie LM Sudlow; Gregory YH Lip; Harry Hemingway,"University College London; University College London; University College London; University College London; UCL; University College London; Office for National Statistics; UCL; University College London Hospitals NHS Trust; Royal Free Hospitals NHS Trust; University of Leicester; UCL; UCL; UCL; King's College Hospital; Kings College London; Kings College London; Kings London NHS Trust; Kings College Hospital NHS Foundation Trust; King's College London; Office for National Statistics; Huazhong University of Science and Technology, Wuhan, China; University of Edinburgh; Ospedale S. Maria delle Croci, Ravenna, Italy; PLA General Hospital, Beijing, China.; Huazhong University of Science and Technology, Wuhan, China.; University of Edinburgh; University of Liverpool; UCL","BackgroundCardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both ""direct"", through infection, and ""indirect"", through changes in healthcare.
-
-MethodsWe used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(""direct"" effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For ""indirect"" effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020.
-
-FindingsCVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths.
-
-InterpretationSupply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic.
-
-FundingNIHR, HDR UK, Astra Zeneca",cardiovascular medicine,exact,100,100
 medRxiv,10.1101/2020.06.08.20120584,2020-06-09,https://medrxiv.org/cgi/content/short/2020.06.08.20120584,SARS-CoV-2 virus and antibodies in front-line Health Care Workers in an acute hospital in London: preliminary results from a longitudinal study,Catherine Houlihan; Nina Vora; Thomas Byrne; Dan Lewer; Judith Heaney; David A Moore; Rebecca Matthews; Sajida Adam; Louise Enfield; Abigail Severn; Angela McBride; Moira Jane Spyer; Rupert Beale; Peter Cherepanov; Kathleen Gaertner; Maryam Shahmanesh; - The SAFER Field Study Team; Kevin Ng; Georgina Cornish; Naomi Walker; Susan Michie; Ed Manley; Fabiana Lorencatto; - The Crick-COVID-Consortium; Richard Gilson; Sonia Gandhi; Steve Gamblin; George Kassiotis; Laura McCoy; Charles Swanton; Andrew Hayward; Eleni Nastouli,University College London Hospital; UCL; UCL; University College London; UCL; Francis Crick Institute; UCL; UCL; UCL; UCL; UCL; UCL; Francis Crick Institute; Francis Crick Institute; UCL; UCL; ; Francis Crick Institute; Francis Crick Institute; UCL; UCL; Leeds University; UCL; ; UCL; Francis Crick Institute; Francis Crick Institute; Francis Crick Institute; UCL; Francis Crick Institute; UCL; University College London,"BackgroundAlthough SARS-CoV-2 infection in Healthcare Workers (HCWs) is a public health concern, there is little description of their longitudinal antibody response in the presence or absence of SARS-CoV-2 and symptoms. We followed HCWs in an acute London hospital to measure seroconversion and RNA detection at the peak of the pandemic.
 
 MethodsWe enrolled 200 patient-facing HCWs between 26 March and 8 April 2020 and collected twice-weekly self-administered nose and throat swabs, symptom data and monthly blood samples. Swabs were tested for SARS-CoV-2 by PCR, and serum for antibodies to spike protein by ELISA and flow cytometry.
@@ -2783,6 +2831,13 @@ C_LIO_LIRisk stratification was improved by the addition of routinely-measured b
 C_LIO_LIThis improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites.
 C_LIO_LIWe benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches.
 C_LI",infectious diseases,exact,100,100
+bioRxiv,10.1101/2020.04.28.066977,2020-04-29,https://biorxiv.org/cgi/content/short/2020.04.28.066977,"Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world",Jody Phelan; Wouter Deelder; Daniel Ward; Susana Campino; Martin L Hibberd; Taane G Clark,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines.
+
+MethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure.
+
+ResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades.
+
+ConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.",genomics,exact,100,100
 medRxiv,10.1101/2020.04.22.20072124,2020-04-24,https://medrxiv.org/cgi/content/short/2020.04.22.20072124,"Self-reported symptoms of covid-19 including symptoms most predictive of SARS-CoV-2 infection, are heritable",Frances MK Williams; Maxim Freydin; Massimo Mangino; Simon Couvreur; Alessia Visconti; Ruth CE Bowyer; Caroline I Le Roy; Mario Falchi; Carole Sudre; Richard Davies; Christopher Hammond; Cristina Menni; Claire Steves; Tim Spector,King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; Zoe Global Ltd; King's College London; King's College London; King's College London; King's College London,"Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n=2633) completing the C-19 Covid symptom tracker app allowed classical twin studies of covid-19 symptoms including predicted covid-19, a symptom-based algorithm predicting true infection derived in app users tested for SARS-CoV-2. We found heritability for fever = 41 (95% confidence intervals 12-70)%; anosmia 47 (27-67)%; delirium 49 (24-75)%; and predicted covid-19 gave heritability = 50 (29-70)%.",genetic and genomic medicine,exact,100,100
 medRxiv,10.1101/2020.04.21.20073049,2020-04-24,https://medrxiv.org/cgi/content/short/2020.04.21.20073049,What can trends in hospital deaths from COVID-19 tell us about the progress and peak of the pandemic? An analysis of death counts from England announced up to 20 April 2020,David A Leon; Christopher I Jarvis; Anne M Johnson; Liam Smeeth; Vladimir M Shkolnikov,London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; University College London; London School of Hygiene & Tropical Medicine; Max Planck Institute for Demographic Research,"BackgroundReporting of daily hospital COVID-19 deaths in the UK are promoted by the government and scientific advisers alike as a key metric for assessing the progress in the control of the epidemic. These data, however, have certain limitations, among which one of the most significant concerns the fact that the daily totals span deaths that have occurred between 1 and 10 days or more in the past.
 
diff --git a/data/covid/preprints.exact.json b/data/covid/preprints.exact.json
index fc828636..47e080d3 100644
--- a/data/covid/preprints.exact.json
+++ b/data/covid/preprints.exact.json
@@ -251,6 +251,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.03.15.23287292",
+    "date": "2023-03-15",
+    "link": "https://medrxiv.org/cgi/content/short/2023.03.15.23287292",
+    "title": "Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic",
+    "authors": "Eoin McElroy; Emily Herrett; Kishan Patel; Dominik M Piehlmaier; Giorgio Di Gessa; Charlotte Huggins; Michael J Green; Alex SF Kwong; Ellen J Thompson; Jingmin Zhu; Kathryn E Mansfield; Richard J Silverwood; Rosie Mansfield; Jane Maddock; Rohini Mathur; Ruth E Costello; Anthony A Matthews; John Tazare; Alasdair Henderson; Kevin Wing; Lucy Bridges; Sebastian Bacon; Amir Mehrkar; - OpenSafely Collaborative; Richard John Shaw; Jacques Wels; Srinivasa Vittal Katikireddi; Nishi Chaturvedi; Laurie Tomlinson; Praveetha Patalay",
+    "affiliations": "School of Psychology, Ulster University, Coleraine, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; University of Sussex Business Sch; Department of Epidemiology & Public Health, University College London, London, UK; Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Division of Psychiatry, University of Edinburgh, Edinburgh, UK; Department of Twin Research and Genetic Epidemiology, Kings College London; Department of Epidemiology & Public Health, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Centre for Longitudinal Studies, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Primary Care, Wolfson Insitute of Population Health, Queen Mary, University of London, London; London School of Hygiene and Tropical Medicine, London, UK; Karolinska Institutet, Stockholm, Sweden; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; ; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK",
+    "abstract": "ObjectivesTo describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap.\n\nDesignTen population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs).\n\nSettingUK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database.\n\nParticipantsParticipants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people.\n\nMain outcome measuresIn the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses.\n\nResultsThe LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed.\n\nConclusionsMultiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.\n\nSummary BoxO_ST_ABSWhat is already known on the topic?C_ST_ABSHouseholds with one individual are an increasing demographic, comprising over a quarter of all households in the UK in 2021. However, the mental health gap between those who live alone compared to those who live with others is not well described and even less is known about the relative gaps in need and healthcare-seeking and access. The pandemic and associated restrictive measures further increased the likelihood of isolation for this group, which may have impacted mental health.\n\nWhat this study adds?We present comprehensive evidence from both population-based surveys and electronic health records regarding the greater levels of mental health symptoms and in recorded diagnoses for common (anxiety, depression) and less common (OCD, eating disorders, SMIs) mental health conditions for people living alone compared to those living with others.\n\nOur analyses indicate that mental health conditions are more common among those who live alone compared to those who live with others. Although levels of reported distress increased for both groups during the pandemic, healthcare-seeking dropped in both groups, and the rates of healthcare-seeking among those who live alone converged with those who live with others for common mental health conditions. This suggests greater barriers for treatment access among those that live alone.\n\nThe findings have implications for mental health service planning and efforts to reduce barriers to treatment access, especially for individuals who live on their own.",
+    "category": "psychiatry and clinical psychology",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.02.26.23286474",
@@ -349,6 +363,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.02.06.23285513",
+    "date": "2023-02-06",
+    "link": "https://medrxiv.org/cgi/content/short/2023.02.06.23285513",
+    "title": "A Rapid review on the COVID-19 Pandemic's Global Impact on Breast Cancer Screening Participation Rates and Volumes from January-December 2020",
+    "authors": "Reagan Lee; - UNCOVER; Wei Xu; - International Partnership for Resilience in Cancer Systems (I-PaRCS), Breast Cancer Working Group 2; Marshall Dozier; Ruth McQuillan; Evropi Theodoratou; Jonine Figueroa",
+    "affiliations": "University of Edinburgh; -; University of Edinburgh; -; University of Edinburgh; University of Edinburgh; The University of Edinburgh; University of Edinburgh",
+    "abstract": "BackgroundCOVID-19 has strained population breast mammography screening programs that aim to diagnose and treat breast cancers earlier. As the pandemic has affected countries differently, we aimed to quantify changes in breast screening volume and uptake during the first year of the COVID-19 pandemic.\n\nMethodsWe systematically searched Medline, the WHO (World Health Organization) COVID-19 database, and governmental databases. Studies covering January 2020 to March 2022 were included. We extracted and analyzed data regarding study methodology, screening volume and uptake. To assess for risk-of-bias, we used the Joanna Briggs Institute Critical Appraisal tool.\n\nResultsTwenty-six cross-sectional descriptive studies were included out of 935 independent records. Reductions in screening volume and uptake rates were observed among eight countries. Changes in screening participation volume in five countries with national population-based screening ranged from -13% to -31%. Among two countries with limited population-based programs the decline ranged from -61% to -41%. Within the USA, population participation volumes varied ranging from +18% to -39% with suggestion of differences by insurance status (HMO, Medicare, and low-income programs). Almost all studies had high risk-of-bias due to insufficient statistical analysis and confounding factors.\n\nDiscussion and ConclusionExtent of COVID-19-induced reduction in breast screening participation volume differed by region and data suggested potential differences by healthcare setting (e.g., national health insurance vs private health care). Recovery efforts should monitor access to screening and early diagnosis to determine if prevention services need strengthening to increase coverage of marginalized groups and reduce disparities.",
+    "category": "epidemiology",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.02.01.23285333",
@@ -363,6 +391,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.01.31.23285232",
+    "date": "2023-02-01",
+    "link": "https://medrxiv.org/cgi/content/short/2023.01.31.23285232",
+    "title": "Cohort profile: Virus Watch: Understanding community incidence, symptom profiles, and transmission of COVID-19 in relation to population movement and behaviour",
+    "authors": "Thomas Edward Byrne; Jana Kovar; Sarah Beale; Isobel Braithwaite; Ellen Fragaszy; Wing Lam Erica Fong; Cyril Geismar; Susan J Hoskins; Annalan Mathew Dwight Navaratnam; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Alexei Yavlinsky; Pia Hardelid; Linda Wijlaars; Eleni Nastouli; Moira Spyer; Anna Ayree; Ingemar Cox; Vasileios Lampos; Rachel A McKendry; Tao Cheng; Anne M Johnson; Susan Fiona Michie; Jo Gibbs; Richard Gilson; Alison Rodger; Ibrahim Abubakar; Andrew Hayward; Robert W Aldridge",
+    "affiliations": "University College London; University College London; University College London; University College London; UCL; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCLH; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCL",
+    "abstract": "Key FeaturesO_LIVirus Watch is a national community cohort study of COVID-19 in households in England and Wales, established in June 2020. The study aims to provide evidence on which public health approaches are most effective in reducing transmission, and investigate community incidence, symptoms, and transmission of COVID-19 in relation to population movement and behaviours.\nC_LIO_LI28,527 households and 58,628 participants of age (0-98 years, mean age 48), were recruited between June 2020 - July 2022\nC_LIO_LIData collected include demographics, details on occupation, co-morbidities, medications, and infection-prevention behaviours. Households are followed up weekly with illness surveys capturing symptoms and their severity, activities in the week prior to symptom onset and any COVID-19 test results. Monthly surveys capture household finance, employment, mental health, access to healthcare, vaccination uptake, activities and contacts. Data have been linked to Hospital Episode Statistics (HES), inpatient and critical care episodes, outpatient visits, emergency care contacts, mortality, virology testing and vaccination data held by NHS Digital.\nC_LIO_LINested within Virus Watch are a serology & PCR cohort study (n=12,877) and a vaccine evaluation study (n=19,555).\nC_LIO_LIStudy data are deposited in the Office of National Statistics (ONS) Secure Research Service (SRS). Survey data are available under restricted access upon request to ONS SRS.\nC_LI",
+    "category": "epidemiology",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.01.29.23285160",
@@ -1287,6 +1329,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2022.01.05.21268323",
+    "date": "2022-01-06",
+    "link": "https://medrxiv.org/cgi/content/short/2022.01.05.21268323",
+    "title": "Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey",
+    "authors": "Katrina A Lythgoe; Tanya Golubchik; Matthew Hall; Thomas House; Roberto Cahuantzi; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; Mahan Ghafari; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Christophe Fraser; Ian Diamond; Jeff Barrett; Ann Sarah Walker; David Bonsall",
+    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Manchester; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Wellcome Sanger Institute; Office for National Statistics; ; University of Oxford; Office for National Statistics; Wellcome Sanger Institute; University of Oxford; University of Oxford",
+    "abstract": "The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non- SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly in the current phase of the pandemic with routine RT-PCR testing now ended in the community.",
+    "category": "epidemiology",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.12.31.21268587",
@@ -1357,20 +1413,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "bioRxiv",
-    "doi": "10.1101/2021.12.17.473248",
-    "date": "2021-12-21",
-    "link": "https://biorxiv.org/cgi/content/short/2021.12.17.473248",
-    "title": "SARS-CoV-2 Omicron spike mediated immune escape, infectivity and cell-cell fusion",
-    "authors": "Bo Meng; Isabella Ferreira; Adam Abdullahi; Niluka Goonawardane; Akatsuki Saito; Izumi Kimura; Daichi Yamasoba; Steven A Kemp; Guido Papa; Saman Fatihi; Surabhi Rathore; Pehuen Perera Gerba; Terumasa Ikeda; Mako Toyoda; Toong Seng Tan; Jin Kuramochi; Shigeki Mitsunaga; Takamasa Ueno; Oscar Charles; Dami Collier; - CITIID-NIHR BioResource COVID-19 Collaboration; - The Genotype to Phenotype Japan (G2P-Japan) Consortium; - Ecuador-COVID19 Consortium; John Bradley; Jinwook Choi; Kenneth Smith; Elo Madissoon; Kerstin Meyer; Petra Mlcochova; Rainer Doffinger; Sarah A Teichmann; Leo James; Joo Hyeon Lee; Teresa Brevini; Matteo Pizzuto; Myra Hosmillo; Donna Mallery; Samantha Zepeda; Alexandra Walls; Anshu Joshi; John Bowen; John Briggs; Alex Sigal; Laurelle Jackson; Sandile Cele; Anna De Marco; Fotios Sampaziotis; Davide Corti; David Veesler; Nicholas Matheson; Ian Goodfellow; Lipi Thukral; Kei Sato; Ravindra K Gupta",
-    "affiliations": "University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Miyazaki; The University of Tokyo; Kumamoto University; University of Cambridge; LMB Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; CSIR Institute of Genomics and Integrative Biology, Delhi, India; University of Cambridge; Kumamoto Univ; Kumamoto University, Kumamoto; Kuramochi Clinic Interpark; Kuramochi Clinic Interpark; National Institute of Genetics, Mishima, Shizuoka; Kumamoto University, Kumamoto; University College London; University of Cambridge; -; -; -; University of Cambridge; University of Cambridge; University of Cambridge; Wellcome Sanger Institute; Wellcome Sanger Institute; University of Cambridge; Cambridge University Hospitals NHS Trust; Cambridge University; MRC LMB; University of Cambridge; University of Cambridge; Humabs Biomed SA; University of Cambridge; MRC LMB Cambridge; University of Washington; University of Washington; University of Washington; University of Washington; University of Heidelberg; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Humabs Biomed SA; University of Cambridge; Humabs Biomed SA; University of Washington; University of Cambridge; University of Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; The University of Tokyo; University of Cambridge",
-    "abstract": "The SARS-CoV-2 Omicron BA.1 variant emerged in late 2021 and is characterised by multiple spike mutations across all spike domains. Here we show that Omicron BA.1 has higher affinity for ACE2 compared to Delta, and confers very significant evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralising antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralisation. Importantly, antiviral drugs remdesevir and molnupiravir retain efficacy against Omicron BA.1. We found that in human nasal epithelial 3D cultures replication was similar for both Omicron and Delta. However, in lower airway organoids, Calu-3 lung cells and gut adenocarcinoma cell lines live Omicron virus demonstrated significantly lower replication in comparison to Delta. We noted that despite presence of mutations predicted to favour spike S1/S2 cleavage, the spike protein is less efficiently cleaved in live Omicron virions compared to Delta virions. We mapped the replication differences between the variants to entry efficiency using spike pseudotyped virus (PV) entry assays. The defect for Omicron PV in specific cell types correlated with higher cellular RNA expression of TMPRSS2, and accordingly knock down of TMPRSS2 impacted Delta entry to a greater extent as compared to Omicron. Furthermore, drug inhibitors targeting specific entry pathways demonstrated that the Omicron spike inefficiently utilises the cellular protease TMPRSS2 that mediates cell entry via plasma membrane fusion. Instead, we demonstrate that Omicron spike has greater dependency on cell entry via the endocytic pathway requiring the activity of endosomal cathepsins to cleave spike. Consistent with suboptimal S1/S2 cleavage and inability to utilise TMPRSS2, syncytium formation by the Omicron spike was dramatically impaired compared to the Delta spike. Overall, Omicron appears to have gained significant evasion from neutralising antibodies whilst maintaining sensitivity to antiviral drugs targeting the polymerase. Omicron has shifted cellular tropism away from TMPRSS2 expressing cells that are enriched in cells found in the lower respiratory and GI tracts, with implications for altered pathogenesis.",
-    "category": "microbiology",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.12.20.21268098",
@@ -1595,6 +1637,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.11.10.21266124",
+    "date": "2021-11-11",
+    "link": "https://medrxiv.org/cgi/content/short/2021.11.10.21266124",
+    "title": "Differences in COVID-19 vaccination coverage by occupation in England: a national linked data study",
+    "authors": "Vahe Nafilyan; Ted Dolby; Katie Finning; Jasper Morgan; Rhiannon Edge; Myer Glickman; Neil Pearce; Martie Van Tongeren",
+    "affiliations": "Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Lancaster University; Office for National Statistics; London School of Hygiene and Tropical Medicine; University of Manchester",
+    "abstract": "BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation.\n\nMethodsUsing nationwide population-level data, we calculated the proportion of people who had received two doses of a COVID-19 vaccine (assessed on 31 August 2021) by detailed occupational categories in adults aged 40-64 and estimated adjusted odds ratios to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.\n\nResultsOur study population included 14,298,147 adults 40-64. Vaccination rates differed markedly by occupation, being higher in administrative and secretarial occupations (90.8%); professional occupations (90.7%); and managers, directors and senior officials (90.6%); and lowest (83.1%) in people working in elementary occupations. We found substantial differences in vaccination rates looking at finer occupational groups even after adjusting for confounding factors, such as education. Vaccination rates were higher in occupations which can be done from home and lower in those which cannot. Many occupations with low vaccination rates also involved contact with the public or with vulnerable people\n\nConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection, especially in occupations that cannot be done from home and involve contacts with the public. Policies such as  work from home if you can may only have limited future impact on hospitalisations and deaths\n\nWhat is already known on this subject?Whilst several studies highlight differences in vaccination coverage by ethnicity, religion, socio-demographic factors and certain underlying health conditions, there is very little evidence on how vaccination coverage varies by occupation, in the UK and elsewhere. The few study looking at occupational differences in vaccine hesitancy focus on healthcare workers or only examined broad occupational groups. There is currently no large-scale study on occupational differences in COVID-19 vaccination coverage in the UK.\n\nWhat this study adds?Using population-level linked data combining the 2011 Census, primary care records, mortality and vaccination data, we found that the vaccination rates of adults aged 40 to 64 years in England differed markedly by occupation. Vaccination rates were high in administrative and secretarial occupations, professional occupations and managers, directors and senior officials and low in people working in elementary occupations. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were also associated with the ability to work from home, with the vaccination rate being higher in occupations which can be done performed from home. Policies aiming to increase vaccination rates in occupations that cannot be done from home and involve contacts with the public should be priorities",
+    "category": "public and global health",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.11.09.21266054",
@@ -1777,20 +1833,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.09.13.21263487",
-    "date": "2021-09-16",
-    "link": "https://medrxiv.org/cgi/content/short/2021.09.13.21263487",
-    "title": "SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population",
-    "authors": "Jia Wei; Koen B. Pouwels; Nicole Stoesser; Philippa C. Matthews; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John I Bell; John N Newton; Jeremy Farrar; Alison Howarth; Brian D. Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W. Crook; Tim E.A. Peto; A.Sarah Walker; David W. Eyre",
-    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford",
-    "abstract": "We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.",
-    "category": "infectious diseases",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.09.09.21263026",
@@ -2281,6 +2323,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.05.12.21257123",
+    "date": "2021-05-17",
+    "link": "https://medrxiv.org/cgi/content/short/2021.05.12.21257123",
+    "title": "Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults",
+    "authors": "Vahe Nafilyan; Piotr Pawelek; Daniel Ayoubkhani; Sarah Rhodes; Lucy Pembrey; Melissa Matz; Michel P Coleman; Claudia Allemani; Ben Windsor-Shellard; Martie van Tongeren; Neil Pearce",
+    "affiliations": "Office for National Statistics; Office for National Statistics; Office for National Statistics; School of Health Sciences, University of Manchester; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Office for National Statistics; School of Health Sciences, University of Manchester; London School of Hygiene and Tropical Medicine",
+    "abstract": "ObjectiveTo estimate occupational differences in COVID-19 mortality, and test whether these are confounded by factors, such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation or pre-pandemic health.\n\nDesignRetrospective cohort study\n\nSettingPeople living in private households England\n\nParticipants14,295,900 people aged 40-64 years (mean age 52 years, 51% female) who were alive on 24 January 2020, living in private households in England in 2019, were employed in 2011, and completed the 2011 census.\n\nMain outcome measuresCOVID-19 related death, assessed between 24 January 2020 and 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk (ASMR) stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding (region, ethnicity, education), as well as non-workplace factors that are related to occupation.\n\nResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three-fold or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating non-workplace factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62-5.84] to 1.47 [1.14-1.89] after adjustment. More generally, the overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.\n\nConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.",
+    "category": "epidemiology",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.05.13.21257144",
@@ -2309,6 +2365,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.05.06.21256757",
+    "date": "2021-05-14",
+    "link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256757",
+    "title": "COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study",
+    "authors": "Yiqun Chen; Timothy Aldridge; - UK COVID-19 National Core Studies Consortium; Claire F Ferraro; Fu-Meng Khaw",
+    "affiliations": "Health and Safety Executive, UK; Health and Safety Executive, UK; ; National Infection Service, Public Health England, UK; Public Health England, UK",
+    "abstract": "BackgroundA large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic. However, information on the rate of outbreak occurrences which helps to identify the type of workplaces that are more likely to experience an outbreak, or infection attack rates which estimates the potential extent of the virus transmission in an outbreak, has not yet been available to inform intervention strategies to limit transmission.\n\nObjectivesTo link datasets on workplace settings and COVID-19 workplace outbreaks in England in order to: identify the geographical areas and workplace sectors with a high rate of outbreaks; and compare infection attack rates by workplace size and sector.\n\nMethodsWe analysed Public Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, covering the time period of 18 May - 12 October 2020. The workplaces analysed excluded care homes, hospitals and educational settings. We calculated the workplace outbreak rates by nine English regions, 151 Upper Tier Local Authorities (UTLAs) and twelve industrial sectors, using National Population Database (NPD) data extracted in May 2019 on the total number of the relevant workplaces as the denominator. We also calculated the infection attack rates by enterprise size (small, medium, large) and industrial sector, using PHE Situations of Interest (SOI) data on the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator, and using NPD data on the number employed in that workplace as the denominator.\n\nResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone data, of which 1,305 were available for estimation of outbreak rates. The average outbreak rate was 66 per 100,000 workplaces. Of the nine geographical regions in England, the North West had the highest workplace outbreak rate (155/100,000 workplaces), based on 351 outbreaks. Of the UTLAs, the highest workplace outbreak rate was Blackburn with Darwen (387/100,000 workplaces). The industrial sector with the highest workplace outbreak rate was manufacturers and packers of food (1,672/100,000), based on 117 outbreaks: this was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.\n\nIn total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%).\n\nConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.",
+    "category": "epidemiology",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.05.08.21256867",
@@ -2337,20 +2407,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.05.05.21256668",
-    "date": "2021-05-09",
-    "link": "https://medrxiv.org/cgi/content/short/2021.05.05.21256668",
-    "title": "COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland",
-    "authors": "Sofia de la Fuente Garcia; Fasih Haider; Saturnino Luz",
-    "affiliations": "The University of Edinburgh; The University of Edinburgh; The University of Edinburgh",
-    "abstract": "The COVID-19 pandemic has led to unprecedented restrictions in peoples lifestyle which have affected their psychological wellbeing. In this context, this paper investigates the use of social signal processing techniques for remote assessment of emotions. It presents a machine learning method for affect recognition applied to recordings taken during the COVID-19 winter lockdown in Scotland (UK). This method is exclusively based on acoustic features extracted from voice recordings collected through home and mobile devices (i.e. phones, tablets), thus providing insight into the feasibility of monitoring peoples psychological wellbeing remotely, automatically and at scale. The proposed model is able to predict affect with a concordance correlation coefficient of 0.4230 (using Random Forest) and 0.3354 (using Decision Trees) for arousal and valence respectively.\n\nClinical relevanceIn 2018/2019, 12% and 14% of Scottish adults reported depression and anxiety symptoms. Remote emotion recognition through home devices would support the detection of these difficulties, which are often underdiagnosed and, if untreated, may lead to temporal or chronic disability.",
-    "category": "health informatics",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.05.04.21256507",
@@ -2379,20 +2435,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.04.26.21255732",
-    "date": "2021-04-28",
-    "link": "https://medrxiv.org/cgi/content/short/2021.04.26.21255732",
-    "title": "Deprivation and Exposure to Public Activities during the COVID-19 Pandemic in England and Wales",
-    "authors": "Sarah Beale; Isobel Braithwaite; Annalan MD Navaratnam; Pia Hardelid; Alison Rodger; Anna Aryee; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Robert W Aldridge; Andrew C Hayward; - Virus Watch Collaborative",
-    "affiliations": "University College London; University College London; University College London; University College London; University College London; Royal Free London NHS Foundation Trust,; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; ",
-    "abstract": "BackgroundDifferential exposure to public activities and non-household contacts may contribute to stark deprivation-related inequalities in SARS-CoV-2 infection and outcomes, but has not been directly investigated. We set out to investigate whether participants in Virus Watch - a large community cohort study based in England and Wales - reported different levels of exposure to public activities and non-household contacts during the Autumn-Winter phase of the COVID-19 pandemic according to postcode-level socioeconomic deprivation.\n\nMethodsParticipants (n=20120-25228 across surveys) reported their daily activities during three weekly periods in late November 2020, late December 2020, and mid-February 2021. Deprivation was quantified based on participants postcode of residence using English or Welsh Indices of Multiple Deprivation quintiles. We used Poisson mixed effect models with robust standard errors to estimate the relationship between deprivation and risk of exposure to public activities during each survey period.\n\nResultsRelative to participants in the least deprived areas, participants in the most deprived areas persistently exhibited elevated risk of exposure to vehicle sharing (aRR range across time points 1.73-8.52), public transport (aRR 3.13-5.73), work or education outside of the household (aRR 1.09-1.21), essential shops (aRR 1.09-1.13) and non-household contacts (aRR 1.15-1.19) across multiple survey periods.\n\nConclusionDifferential exposure to essential public activities in deprived communities is likely to contribute to inequalities in infection risk and outcomes during the COVID-19 pandemic. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities.",
-    "category": "epidemiology",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.04.21.21255807",
@@ -3051,6 +3093,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2020.12.03.20243535",
+    "date": "2020-12-04",
+    "link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243535",
+    "title": "OpenSAFELY: impact of national guidance on switching from warfarin to direct oral anticoagulants (DOACs) in early phase of COVID-19 pandemic in England",
+    "authors": "Helen J Curtis; Brian MacKenna; Alex J Walker; Richard Croker; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Peter Inglesby; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan Bhaskaran; Anna Schultze; Christopher T Rentsch; Elizabeth Williamson; William Hulme; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Henry Drysdale; Rosalind M Eggo; Kevin Wing; Angel Wong; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Ian J Douglas; Liam Smeeth; Ben Goldacre",
+    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford",
+    "abstract": "BackgroundEarly in the COVID-19 pandemic the NHS recommended that appropriate patients anticoagulated with warfarin should be switched to direct acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately co-prescribed two anticoagulants following a medication change, and associated monitoring.\n\nObjectiveTo describe which people were switched from warfarin to DOACs; identify potentially unsafe co-prescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic.\n\nMethodsWorking on behalf of NHS England we conducted a population cohort based study using routine clinical data from >17 million adults in England.\n\nResults20,000 of 164,000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in co-prescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. INR testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420).\n\nConclusionsIncreased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people co-prescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.",
+    "category": "cardiovascular medicine",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.11.27.20238147",
@@ -3093,20 +3149,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.11.19.20234849",
-    "date": "2020-11-22",
-    "link": "https://medrxiv.org/cgi/content/short/2020.11.19.20234849",
-    "title": "Community factors and excess mortality in first wave of the COVID-19 pandemic.",
-    "authors": "Bethan Davies; Brandon L Parkes; James Bennett; Daniela Fecht; Marta Blangiardo; Majid Ezzati; Paul Elliott",
-    "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London",
-    "abstract": "Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.",
-    "category": "epidemiology",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.11.06.20227108",
@@ -3205,20 +3247,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "bioRxiv",
-    "doi": "10.1101/2020.10.29.339317",
-    "date": "2020-10-30",
-    "link": "https://biorxiv.org/cgi/content/short/2020.10.29.339317",
-    "title": "COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning",
-    "authors": "- The COVID Moonshot Consortium; Hagit Achdout; Anthony Aimon; Dominic S Alonzi; Robert Arbon; Elad Bar-David; Haim Barr; Amir Ben-Shmuel; James Bennett; Vitaliy A. Bilenko; Vitaliy A. Bilenko; Melissa L. Boby; Bruce Borden; Pascale Boulet; Gregory R. Bowman; Juliane Brun; Lennart Brwewitz; Sarma BVNBS; Mark Calmiano; Anna Carbery; Daniel Carney; Emma Cattermole; Edcon Chang; Eugene Chernyshenko; John D. Chodera; Austin Clyde; Joseph E. Coffland; Galit Cohen; Jason Cole; Alessandro Contini; Lisa Cox; Tristan Ian Croll; Milan Cvitkovic; Alex Dias; Kim Donckers; David L. Dotson; Alice Douangamath; Shirly Duberstein; Tim Dudgeon; Louise Dunnett; Peter K. Eastman; Noam Erez; Charles J. Eyermann; Mike Fairhead; Gwen Fate; Daren Fearon; Oleg Fedorov; Matteo Ferla; Rafaela S. Fernandes; Lori Ferrins; Mihajlo Filep; Richard Foster; Holly Foster; Laurent Fraisse; Ronen Gabizon; Adolfo Garcia-Sastre; Victor O. Gawriljuk; Paul Gehrtz; Carina Gileadi; Charline Giroud; William G. Glass; Robert Glen; Itai Glinert; Andre S. Godoy; Marian Gorichko; Tyler Gorrie-Stone; Ed J. Griffen; Sophie Hahn; Amna Haneef; Storm Hassell Hart; Jag Heer; Michael Henry; Michelle Hill; Sam Horrell; Qiu Yu Huang; Victor D. Huliak; Victor D. Huliak; Matthew F.D. Hurley; Tomer Israely; Andrew Jajack; Jitske Jansen; Eric Jnoff; Dirk Jochmans; Tobias John; Steven De Jonghe; Benjamin Kaminow; Lulu Kang; Anastassia L. Kantsadi; Peter W. Kenny; J. L. Kiappes; Serhii O. Kinakh; Serhii O. Kinakh; Lizbe Koekemoer; Boris Kovar; Tobias Krojer; Van La; Alpha A. Lee; Bruce A. Lefker; Haim Levy; Ivan G. Logvinenko; Ivan G. Logvinenko; Nir London; Petra Lukacik; Hannah Bruce Macdonald; Elizabeth M. MacLean; Laetitia L Makower; Tika R. Malla; Tatiana Matviiuk; Willam McCorkindale; Briana L. McGovern; Sharon Melamed; Kostiantyn P. Melnykov; Kostiantyn P. Melnykov; Oleg Michurin; Pascal Miesen; Halina Mikolajek; Bruce F. Milne; David Minh; Aaron Morris; Garrett M. Morris; Melody Jane Morwitzer; Demetri Moustakas; Charles Mowbray; Aline M. Nakamura; Jose Brandao Neto; Johan Neyts; Luong Nguyen; Gabriela D. Noske; Vladas Oleinikovas; Glaucius Oliva; Gijs J. Overheul; David Owen; Ruby Pai; Jin Pan; Nir Paran; Alexander Payne; Benjamin Perry; Maneesh Pingle; Jakir Pinjari; Boaz Politi; Ailsa Powell; Vladimir Psenak; Ivan Pulido; Reut Puni; Victor L. Rangel; Rambabu N. Reddi; Paul Rees; St Patrick Reid; Lauren Reid; Efrat Resnick; Emily Grace Ripka; Matthew C. Robinson; Ralph P. Robinson; Jaime Rodriguez-Guerra; Romel Rosales; Dominic A. Rufa; Kadi Saar; Kumar Singh Saikatendu; Eidarus Salah; David Schaller; Jenke Scheen; Celia A. Schiffer; Chris Schofield; Mikhail Shafeev; Aarif Shaikh; Ala M. Shaqra; Jiye Shi; Khriesto Shurrush; Sukrit Singh; Assa Sittner; Peter Sjo; Rachael Skyner; Adam Smalley; Bart Smeets; Mihaela D. Smilova; Leonardo J. Solmesky; John Spencer; Claire Strain-Damerell; Vishwanath Swamy; Hadas Tamir; Jenny C. Taylor; Rachael E. Tennant; Warren Thompson; Andrew Thompson; Susana Tomasio; Charlie Tomlinson; Igor S. Tsurupa; Igor S. Tsurupa; Anthony Tumber; Ioannis Vakonakis; Ronald P. van Rij; Laura Vangeel; Finny S. Varghese; Mariana Vaschetto; Einat B. Vitner; Vincent Voelz; Andrea Volkamer; Frank von Delft; Annette von Delft; Martin Walsh; Walter Ward; Charlie Weatherall; Shay Weiss; Kris M. White; Conor Francis Wild; Karolina D Witt; Matthew Wittmann; Nathan Wright; Yfat Yahalom-Ronen; Nese Kurt Yilmaz; Daniel Zaidmann; Ivy Zhang; Hadeer Zidane; Nicole Zitzmann; Sarah N Zvornicanin",
-    "affiliations": "; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; The Weizmann Institute of Science; Israel Institution of Biological Research; University of Oxford; Enamine Ltd; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Folding@home Consortium; DNDi; Washington University School of Medicine; University of Oxford; University of Oxford; Sai Life Sciences; UCB; University of Oxford;Diamond Light Source; Takeda Development Center Americas, Inc.; University of Oxford; Takeda Development Center Americas, Inc.; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Argonne National Laboratory; N/A; The Weizmann Institute of Science; Cambridge Crystallographic Datacentre; University of Milan; Life Compass Consulting Ltd; Cambridge Institute for Medical Research, The University of Cambridge; PostEra Inc.; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; N/A; Diamond Light Source Ltd; Research Complex at Harwell; The Weizmann Institute of Science; Informatics Matters; Diamond Light Source Ltd; Research Complex at Harwell; Department of Bioengineering until Sept. 1, then Department of Chemistry; Israel Institution of Biological Research; Northeastern University; University of Oxford; Thames Pharma Partners; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; University of Oxford; University of Sao Paulo; Northeastern University; Weizmann Institute of Science; University of Leeds; University of Leeds; DNDi; The Weizmann Institute of Science; Icahn School of Medicine at Mount Sinai; University of Sao Paulo; The Weizmann Institute of Science; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Cambridge; Israel Institution of Biological Research; University of Sao Paulo; Taras Shevchenko National University of Kyiv; Diamond Light Source Ltd; Research Complex at Harwell; MedChemica Ltd; DNDi; Illinois Institute of Technology; University of Sussex; UCB; Memorial Sloan Kettering Cancer Center; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; University of Massachusetts Chan Medical School; Enamine Ltd; Enamine Ltd; Temple University; Israel Institution of Biological Research; PostEra Inc.; Radboud University Medical Center; UCB; Katholieke Universiteit Leuven; University of Oxford; Katholieke Universiteit Leuven; Memorial Sloan Kettering Cancer Center; Illinois Institute of Technology; University of Oxford; Independent Scientist; University of Oxford; Enamine Ltd; Enamine Ltd; University of Oxford; M2M solutions, s.r.o; University of Oxford; Illinois Institute of Technology; PostEra Inc.; University of Cambridge; Thames Pharma Partners LLC; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; The Weizmann Institute of Science; Diamond Light Source Ltd; Research Complex at Harwell; Memorial Sloan Kettering Cancer Center; University of Oxford; University of Oxford; University of Oxford; Enamine Ltd; University of Cambridge; Icahn School of Medicine at Mount Sinai; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; Enamine Ltd; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; University of Coimbra and University of Aberdeen; Illinois Institute of Technology; PostEra Inc; University of Oxford; Department of Pathology and Microbiology; Relay Therapeutics; DNDi; University of Sao Paulo; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; PostEra Inc.; University of Sao Paulo; UCB; University of Sao Paulo; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; PostEra Inc.; PostEra Inc.; Israel Institution of Biological Research; Memorial Sloan Kettering Cancer Center; DNDi; Sai Life Sciences; Sai Life Sciences; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; M2M solutions, s.r.o; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; School of Pharmaceutical Sciences of Ribeirao Preto; The Weizmann Institute of Science; Compass Bussiness Partners Ltd; Department of Pathology and Microbiology; MedChemica Ltd; The Weizmann Institute of Science; PostEra Inc.; PostEra Inc.; Thames Pharma Partners LLC; Charite Universitatsmedizin Berlin; Icahn School of Medicine at Mount Sinai; Memorial Sloan Kettering Cancer Center; University of Cambridge; Takeda Development Center Americas, Inc.; University of Oxford; Charite Universitatsmedizin Berlin; Memorial Sloan Kettering Cancer Center; University of Massachusetts Chan Medical School; University of Oxford; Enamine Ltd; Sai Life Sciences; University of Massachusetts Chan Medical School; UCB; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; DNDi; Diamond Light Source Ltd; Research Complex at Harwell; UCB; Radboud University Medical Center; University of Oxford; The Weizmann Institute of Science; University of Sussex; Diamond Light Source Ltd; Research Complex at Harwell; Sai Life Sciences; Israel Institution of Biological Research; University of Oxford; Lhasa Limited; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Collaborative Drug Discovery; Diamond Light Source Ltd; Research Complex at Harwell; Enamine Ltd; Enamine Ltd; University of Oxford; University of Oxford; Radboud University Medical Center; Katholieke Universiteit Leuven; Radboud University Medical Center; Collaborative Drug Discovery; Israel Institution of Biological Research; Temple University; Charite Universitatsmedizin Berlin; Diamond Light Source Ltd; University of Oxford; Research Complex at Harwell; University of Johannesburg; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; Walter Ward Consultancy & Training; Collaborative Drug Discovery; Israel Institution of Biological Research; Icahn School of Medicine at Mount Sinai; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Oxford; Israel Institution of Biological Research; University of Massachusetts Chan Medical School; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; The Weizmann Institute of Science; University of Oxford; University of Massachusetts Chan Medical School",
-    "abstract": "The COVID-19 pandemic was a stark reminder that a barren global antiviral pipeline has grave humanitarian consequences. Pandemics could be prevented in principle by accessible, easily deployable broad-spectrum oral antivirals. Here we report the results of the COVID Moonshot, a fully open-science, crowd sourced, structure-enabled drug discovery campaign targeting the SARS-CoV-2 main protease. We discovered a novel chemical series that is differentiated from current Mpro inhibitors in that it maintains a new non-covalent, non-peptidic scaffold with nanomolar potency. Our approach leveraged crowdsourcing, high-throughput structural biology, machine learning, and exascale molecular simulations and high-throughput chemistry. In the process, we generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. In a first for a structure-based drug discovery campaign, all compound designs (>18,000 designs), crystallographic data (>840 ligand-bound X-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2,400 compounds) for this campaign were shared rapidly and openly, creating a rich open and IP-free knowledgebase for future anti-coronavirus drug discovery.",
-    "category": "biochemistry",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.10.25.20219048",
@@ -3583,20 +3611,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.09.01.20185793",
-    "date": "2020-09-03",
-    "link": "https://medrxiv.org/cgi/content/short/2020.09.01.20185793",
-    "title": "Prognostic accuracy of emergency department triage tools for children with suspected COVID-19: The PRIEST observational cohort study",
-    "authors": "Katie Biggs; Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Matthew Bursnall; Amanda Loban; Simon Waterhouse; Richard Simmonds; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter",
-    "affiliations": "University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust",
-    "abstract": "ObjectivesEmergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection.\n\nMethodsWe undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Childrens Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.\n\nResultsWe collected data from 1530 children, including 26 (1.7%) with an adverse outcome. C-statistics were 0.80 (95% confidence interval 0.73-0.87) for the WHO algorithm, 0.80 (0.71-0.90) for POPS, 0.76 (0.67-0.85) for COAST, and 0.71 (0.59-0.82) for SFHPC. Using pre-specified thresholds, the WHO algorithm had the highest sensitivity (0.85) and lowest specificity (0.75), but POPS and COAST could optimise sensitivity (0.96 and 0.92 respectively) at the expense of specificity (0.25 and 0.38 respectively) by using a threshold of any score above zero instead of the pre-specified threshold.\n\nConclusionExisting triage tools have good but not excellent prediction for adverse outcome in children with suspected COVID-19. POPS and COAST could achieve an appropriate balance of sensitivity and specificity for supporting decisions to discharge home by considering any score above zero to be positive.\n\nRegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",
-    "category": "emergency medicine",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.08.26.20182279",
@@ -3667,6 +3681,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2020.08.17.20175117",
+    "date": "2020-08-21",
+    "link": "https://medrxiv.org/cgi/content/short/2020.08.17.20175117",
+    "title": "Real-time spatial health surveillance: mapping the UK COVID-19 epidemic",
+    "authors": "Richard Fry; Joe Hollinghurst; Helen R Stagg; Daniel A Thompson; Claudio Fronterre; Chris Orton; Ronan A Lyons; David V Ford; Aziz Sheikh; Peter J Diggle",
+    "affiliations": "Swansea University; Swansea University; Edinburgh University; Swansea University; Lancaster University; Swansea University; Swansea University; Swansea University; Edinburgh University; Lancaster University",
+    "abstract": "The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. A pre-requisite to an effective control strategy is that predictions need to be accompanied by estimates of their precision, to guard against over-reaction to potentially spurious features of  best guess predictions. In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.",
+    "category": "public and global health",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.08.12.20173690",
@@ -4157,20 +4185,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.06.10.20127175",
-    "date": "2020-06-11",
-    "link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127175",
-    "title": "Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic.",
-    "authors": "Amitava Banerjee; Suliang Chen; Laura Pasea; Alvina Lai; Michail Katsoulis; Spiros Denaxas; Vahe Nafilyan; Bryan Williams; Wai Keong Wong; Ameet Bakhai; Kamlesh Khunti; Deenan Pillay; Mahdad Noursadeghi; Honghan Wu; Nilesh Pareek; Daniel Bromage; Theresa Mcdonagh; Jonathan Byrne; James T Teo; Ajay Shah; Ben Humberstone; Liang V Tang; Anoop SV Shah; Andrea Rubboli; Yutao Guo; Yu Hu; Cathie LM Sudlow; Gregory YH Lip; Harry Hemingway",
-    "affiliations": "University College London; University College London; University College London; University College London; UCL; University College London; Office for National Statistics; UCL; University College London Hospitals NHS Trust; Royal Free Hospitals NHS Trust; University of Leicester; UCL; UCL; UCL; King's College Hospital; Kings College London; Kings College London; Kings London NHS Trust; Kings College Hospital NHS Foundation Trust; King's College London; Office for National Statistics; Huazhong University of Science and Technology, Wuhan, China; University of Edinburgh; Ospedale S. Maria delle Croci, Ravenna, Italy; PLA General Hospital, Beijing, China.; Huazhong University of Science and Technology, Wuhan, China.; University of Edinburgh; University of Liverpool; UCL",
-    "abstract": "BackgroundCardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both \"direct\", through infection, and \"indirect\", through changes in healthcare.\n\nMethodsWe used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(\"direct\" effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For \"indirect\" effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020.\n\nFindingsCVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths.\n\nInterpretationSupply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic.\n\nFundingNIHR, HDR UK, Astra Zeneca",
-    "category": "cardiovascular medicine",
-    "match_type": "exact",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.06.08.20120584",
@@ -4423,6 +4437,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "bioRxiv",
+    "doi": "10.1101/2020.04.28.066977",
+    "date": "2020-04-29",
+    "link": "https://biorxiv.org/cgi/content/short/2020.04.28.066977",
+    "title": "Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world",
+    "authors": "Jody Phelan; Wouter Deelder; Daniel Ward; Susana Campino; Martin L Hibberd; Taane G Clark",
+    "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine",
+    "abstract": "BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines.\n\nMethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure.\n\nResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades.\n\nConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.",
+    "category": "genomics",
+    "match_type": "exact",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.04.22.20072124",
diff --git a/data/covid/preprints.json b/data/covid/preprints.json
index 1cd681ca..294a19d9 100644
--- a/data/covid/preprints.json
+++ b/data/covid/preprints.json
@@ -7,7 +7,7 @@
     "title": "Symptom experience before vs. after confirmed SARS-CoV-2 infection: a population and case control study using prospectively recorded symptom data.",
     "authors": "Carole Helene Sudre; Michela Antonelli; Nathan J Cheetham; Erika Molteni; Liane S Canas; Vicky Bowyer; Benjamin Murray; Khaled Rjoob; Marc Modat; Joan Capdevia Pujol; Christina Hu; Jonathan Wolf; Timothy D Spector; Alexander Hammers; Claire J Steves; Sebastien Ourselin; Emma L Duncan",
     "affiliations": "University College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; University College London; King's College London; Zoe Ltd; Zoe Ltd; Zoe Ltd; King's College London; King's College London; King's College London; King's College London; King's College London",
-    "abstract": "Background: Some individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration. Methods Survival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([&ge;]8 weeks, 906 [67.1%] with illness [&ge;]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms. Findings: Individuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly. Interpretation: Individuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.",
+    "abstract": "BackgroundSome individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration.\n\nMethodsSurvival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([&ge;]8 weeks, 906 [67.1%] with illness [&ge;]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms.\n\nFindingsIndividuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly.\n\nInterpretationIndividuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.",
     "category": "infectious diseases",
     "match_type": "fuzzy",
     "author_similarity": 94,
@@ -97,6 +97,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.08.01.23293491",
+    "date": "2023-08-02",
+    "link": "https://medrxiv.org/cgi/content/short/2023.08.01.23293491",
+    "title": "Health inequalities in SARS-CoV-2 infection during the second wave in England: REACT-1 study",
+    "authors": "Haowei Wang; Kylie E. C. Ainslie; Oliver Eales; Caroline E. Walters; David Haw; Christina Atchinson; Claudio Fronterre; Peter J. Diggle; Deborah Ashby; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Christl A Donnelly; Paul Elliott; Steven Riley",
+    "affiliations": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc",
+    "abstract": "ObjectivesThe rapid spread of SARS-CoV-2 infection caused high levels of hospitalisation and deaths in late 2020 and early 2021 during the second wave in England. Severe disease during this period was associated with marked health inequalities across ethnic and sociodemographic subgroups. In this paper, we aimed to investigate how inequalities influence the risk of getting infected across ethnic and sociodemographic subgroups during a key period before widespread vaccination.\n\nDesignRepeated cross-sectional community-based study.\n\nMethodsWe analysed risk factors for test-positivity for SARS-CoV-2, based on self-administered throat and nose swabs in the community during rounds 5 to 10 of the REal-time Assessment of Community Transmission-1 (REACT-1) study between 18 September 2020 and 30 March 2021.\n\nResultsCompared to white ethnicity, people of Asian and black ethnicity had a higher risk of infection during rounds 5 to 10, with odds of 1.46 (1.27, 1.69) and 1.35 (1.11, 1.64) respectively. Among ethnic subgroups, the highest and the second-highest odds were found in Bangladeshi and Pakistan participants at 3.29 (2.23, 4.86) and 2.15 (1.73, 2.68) respectively when compared to British whites. People in larger (compared to smaller) households had higher odds of infection. Health care workers with direct patient contact and care home workers showed higher odds of infection compared to other essential/key workers. Additionally, the odds of infection among participants in public-facing activities or settings were greater than among those not working in those activities or settings.\n\nConclusionOur findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future severe waves of respiratory pathogens should include policies to reduce inequality in the risk of infection by ethnicity, household size, and occupational activity in order to reduce inequality in disease.\n\nSummary boxWhat is already known on this topic\n\nExtensive studies have described the relationship between socio-demographic factors and SARS-CoV-2 outcomes such as hospitalisations and deaths, rather than SARS-CoV-2 infection. Limited community-based studies investigated risk factors associated with SARS-CoV-2 infection, with the time frame of these studies has mainly focused on the period of the first wave of infection, or the beginning of the second wave, or the rollout of the first dose of the vaccine after the second wave period. We did not find studies that covered the critical period of the second wave in England when levels of social mixing were high, but no vaccine was available.\n\nWhat this study adds\n\nWe show health inequalities across ethnic and sociodemographic subgroups during a key period: before widespread vaccination, but, largely, not during the period of stringent social distancing. We observed substantial ethnic and occupational differences in the risk of SARS-CoV-2 infection. Minority ethnic groups, including those of Bangladeshi and Pakistani ethnicity, had an excess risk of infection compared with the British white population. Healthcare workers, care home workers and people who work in public-facing activities or settings were associated with higher odds of infection. The risk of SARS-CoV-2 infection increased monotonically as household size increased, and more deprived neighbourhood areas were associated with a higher risk of infection.\n\nHow this study might affect research, practice or policy\n\nOur findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future waves of severe respiratory infection should explicitly aim to reduce inequalities in infection in order to reduce inequality in disease.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.07.31.23293422",
@@ -139,6 +153,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.07.16.23292705",
+    "date": "2023-07-18",
+    "link": "https://medrxiv.org/cgi/content/short/2023.07.16.23292705",
+    "title": "Community-onset urinary tract infection in females in the context of COVID-19: a longitudinal population cohort study exploring case presentation, management, and outcomes",
+    "authors": "Nina J Zhu; Benedict Hayhoe; Raheelah Ahmad; James R Price; Donna Lecky; Monsey McLeod; Elena Ferran; Timothy M Rawson; Emma Carter; Alison H Holmes; Paul Aylin",
+    "affiliations": "National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom; Division of Health Services Research and Management, School of Health Sciences, City, University of London, London, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; Primary Care and Interventions Unit, United Kingdom Health Security Agency (UKHSA), Gloucestershire, United Kingdom; NHS England and NHS Improvement, London, United Kingdom; Barts Health NHS Trust, London, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial ; Primary Care and Interventions Unit, United Kingdom Health Security Agency (UKHSA), Gloucestershire, United Kingdom",
+    "abstract": "BackgroundCOVID-19 affected the epidemiology of other infectious diseases and how they were managed. Urinary tract infection (UTI) is one of the most common infections treated in the community in England. We investigated the impact of the COVID-19 pandemic on UTI primary care consultations and outcomes in female patients.\n\nMethods and findingsWe analysed General Practice (GP) consultation and hospital admission records using the Whole Systems Integrated Care (WSIC) data in North West London between 2016 and 2021. We quantified the changes in UTI GP consultation rates using time series analysis before and during the pandemic. We assessed the outcomes of UTI, measured by subsequent bacteraemia and sepsis within 60 days, for consultations delivered face-to-face or remotely, with or without diagnostic tests recommended by the national guidelines, and with or without antibiotic treatment. Between January 2016 and December 2021, we identified 375,859 UTI episodes in 233,450 female patients. Before the COVID-19 pandemic (January 2016 - February 2020), the UTI GP consultation rate stayed level at 522.8 cases per 100,000 population per month, with a seasonal pattern of peaking in October. Since COVID-19, (March 2020 - December 2021), monthly UTI GP consultations declined when COVID-19 cases surged and rose when COVID-19 case fell. During the pandemic, the UTI consultations delivered face-to-face reduced from 72.0% to 29.4%, the UTI consultations with appropriate diagnostic tests, including urine culture and urinalysis, reduced from 17.3% to 10.4%, and the UTI cases treated with antibiotics reduced from 52.0% to 47.8%. The likelihood of antibiotics being prescribed was not affected by whether the consultation was delivered face-to-face or remotely but associated with whether there was a diagnostic test. Regardless of whether the UTI consultation occurred before or during the pandemic, the absence of antibiotic treatment for UTI is associated with a 10-fold increase in the risk of having bacteraemia or sepsis within 60 days, though the patients who consulted GPs for UTI during the pandemic were older and more co-morbid. Across the study period (January 2016 - December 2021), nitrofurantoin remained the first-line antibiotic option for UTI. The percentage of non-prophylactic acute UTI antibiotic prescriptions with durations that exceeded the guideline recommendations was 58.7% before the pandemic, and 49.4% since. This led to 830,522 total excess days of treatment, account for 63.3% of all non-prophylactic acute antibiotics prescribed for UTI. Before the pandemic, excess antibiotic days of UTI drugs had been reducing consistently. However, this decline slowed down during the pandemic. Having a diagnostic test was associated with 0.6 less excess days of antibiotic treatment.\n\nConclusionsThis analysis provides a comprehensive examination of management and outcomes of community-onset UTI in female patients, considering the changes in GP consultations during the COVID-19 pandemic. Our findings highlighted the importance of appropriate urine testing to support UTI diagnosis in symptomatic patients and initiation of antibiotic treatment with appropriate course duration. Continued monitoring is required to assess the overall impact on patients and health systems from the changed landscape of primary care delivery.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.07.06.23292295",
@@ -461,6 +489,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.03.15.23287292",
+    "date": "2023-03-15",
+    "link": "https://medrxiv.org/cgi/content/short/2023.03.15.23287292",
+    "title": "Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic",
+    "authors": "Eoin McElroy; Emily Herrett; Kishan Patel; Dominik M Piehlmaier; Giorgio Di Gessa; Charlotte Huggins; Michael J Green; Alex SF Kwong; Ellen J Thompson; Jingmin Zhu; Kathryn E Mansfield; Richard J Silverwood; Rosie Mansfield; Jane Maddock; Rohini Mathur; Ruth E Costello; Anthony A Matthews; John Tazare; Alasdair Henderson; Kevin Wing; Lucy Bridges; Sebastian Bacon; Amir Mehrkar; - OpenSafely Collaborative; Richard John Shaw; Jacques Wels; Srinivasa Vittal Katikireddi; Nishi Chaturvedi; Laurie Tomlinson; Praveetha Patalay",
+    "affiliations": "School of Psychology, Ulster University, Coleraine, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; University of Sussex Business Sch; Department of Epidemiology & Public Health, University College London, London, UK; Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Division of Psychiatry, University of Edinburgh, Edinburgh, UK; Department of Twin Research and Genetic Epidemiology, Kings College London; Department of Epidemiology & Public Health, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Centre for Longitudinal Studies, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Primary Care, Wolfson Insitute of Population Health, Queen Mary, University of London, London; London School of Hygiene and Tropical Medicine, London, UK; Karolinska Institutet, Stockholm, Sweden; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; London School of Hygiene and Tropical Medicine, London, UK; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; ; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; London School of Hygiene and Tropical Medicine, London, UK; MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK",
+    "abstract": "ObjectivesTo describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap.\n\nDesignTen population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs).\n\nSettingUK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database.\n\nParticipantsParticipants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people.\n\nMain outcome measuresIn the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses.\n\nResultsThe LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed.\n\nConclusionsMultiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.\n\nSummary BoxO_ST_ABSWhat is already known on the topic?C_ST_ABSHouseholds with one individual are an increasing demographic, comprising over a quarter of all households in the UK in 2021. However, the mental health gap between those who live alone compared to those who live with others is not well described and even less is known about the relative gaps in need and healthcare-seeking and access. The pandemic and associated restrictive measures further increased the likelihood of isolation for this group, which may have impacted mental health.\n\nWhat this study adds?We present comprehensive evidence from both population-based surveys and electronic health records regarding the greater levels of mental health symptoms and in recorded diagnoses for common (anxiety, depression) and less common (OCD, eating disorders, SMIs) mental health conditions for people living alone compared to those living with others.\n\nOur analyses indicate that mental health conditions are more common among those who live alone compared to those who live with others. Although levels of reported distress increased for both groups during the pandemic, healthcare-seeking dropped in both groups, and the rates of healthcare-seeking among those who live alone converged with those who live with others for common mental health conditions. This suggests greater barriers for treatment access among those that live alone.\n\nThe findings have implications for mental health service planning and efforts to reduce barriers to treatment access, especially for individuals who live on their own.",
+    "category": "psychiatry and clinical psychology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.02.26.23286474",
@@ -587,6 +629,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.02.06.23285513",
+    "date": "2023-02-06",
+    "link": "https://medrxiv.org/cgi/content/short/2023.02.06.23285513",
+    "title": "A Rapid review on the COVID-19 Pandemic's Global Impact on Breast Cancer Screening Participation Rates and Volumes from January-December 2020",
+    "authors": "Reagan Lee; - UNCOVER; Wei Xu; - International Partnership for Resilience in Cancer Systems (I-PaRCS), Breast Cancer Working Group 2; Marshall Dozier; Ruth McQuillan; Evropi Theodoratou; Jonine Figueroa",
+    "affiliations": "University of Edinburgh; -; University of Edinburgh; -; University of Edinburgh; University of Edinburgh; The University of Edinburgh; University of Edinburgh",
+    "abstract": "BackgroundCOVID-19 has strained population breast mammography screening programs that aim to diagnose and treat breast cancers earlier. As the pandemic has affected countries differently, we aimed to quantify changes in breast screening volume and uptake during the first year of the COVID-19 pandemic.\n\nMethodsWe systematically searched Medline, the WHO (World Health Organization) COVID-19 database, and governmental databases. Studies covering January 2020 to March 2022 were included. We extracted and analyzed data regarding study methodology, screening volume and uptake. To assess for risk-of-bias, we used the Joanna Briggs Institute Critical Appraisal tool.\n\nResultsTwenty-six cross-sectional descriptive studies were included out of 935 independent records. Reductions in screening volume and uptake rates were observed among eight countries. Changes in screening participation volume in five countries with national population-based screening ranged from -13% to -31%. Among two countries with limited population-based programs the decline ranged from -61% to -41%. Within the USA, population participation volumes varied ranging from +18% to -39% with suggestion of differences by insurance status (HMO, Medicare, and low-income programs). Almost all studies had high risk-of-bias due to insufficient statistical analysis and confounding factors.\n\nDiscussion and ConclusionExtent of COVID-19-induced reduction in breast screening participation volume differed by region and data suggested potential differences by healthcare setting (e.g., national health insurance vs private health care). Recovery efforts should monitor access to screening and early diagnosis to determine if prevention services need strengthening to increase coverage of marginalized groups and reduce disparities.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.02.01.23285333",
@@ -601,6 +657,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2023.01.31.23285232",
+    "date": "2023-02-01",
+    "link": "https://medrxiv.org/cgi/content/short/2023.01.31.23285232",
+    "title": "Cohort profile: Virus Watch: Understanding community incidence, symptom profiles, and transmission of COVID-19 in relation to population movement and behaviour",
+    "authors": "Thomas Edward Byrne; Jana Kovar; Sarah Beale; Isobel Braithwaite; Ellen Fragaszy; Wing Lam Erica Fong; Cyril Geismar; Susan J Hoskins; Annalan Mathew Dwight Navaratnam; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Alexei Yavlinsky; Pia Hardelid; Linda Wijlaars; Eleni Nastouli; Moira Spyer; Anna Ayree; Ingemar Cox; Vasileios Lampos; Rachel A McKendry; Tao Cheng; Anne M Johnson; Susan Fiona Michie; Jo Gibbs; Richard Gilson; Alison Rodger; Ibrahim Abubakar; Andrew Hayward; Robert W Aldridge",
+    "affiliations": "University College London; University College London; University College London; University College London; UCL; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCLH; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCL",
+    "abstract": "Key FeaturesO_LIVirus Watch is a national community cohort study of COVID-19 in households in England and Wales, established in June 2020. The study aims to provide evidence on which public health approaches are most effective in reducing transmission, and investigate community incidence, symptoms, and transmission of COVID-19 in relation to population movement and behaviours.\nC_LIO_LI28,527 households and 58,628 participants of age (0-98 years, mean age 48), were recruited between June 2020 - July 2022\nC_LIO_LIData collected include demographics, details on occupation, co-morbidities, medications, and infection-prevention behaviours. Households are followed up weekly with illness surveys capturing symptoms and their severity, activities in the week prior to symptom onset and any COVID-19 test results. Monthly surveys capture household finance, employment, mental health, access to healthcare, vaccination uptake, activities and contacts. Data have been linked to Hospital Episode Statistics (HES), inpatient and critical care episodes, outpatient visits, emergency care contacts, mortality, virology testing and vaccination data held by NHS Digital.\nC_LIO_LINested within Virus Watch are a serology & PCR cohort study (n=12,877) and a vaccine evaluation study (n=19,555).\nC_LIO_LIStudy data are deposited in the Office of National Statistics (ONS) Secure Research Service (SRS). Survey data are available under restricted access upon request to ONS SRS.\nC_LI",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2023.01.29.23285160",
@@ -1287,6 +1357,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2022.07.29.22278186",
+    "date": "2022-07-30",
+    "link": "https://medrxiv.org/cgi/content/short/2022.07.29.22278186",
+    "title": "Comparative effectiveness of BNT162b2 versus mRNA-1273 boosting in England: a cohort study in OpenSAFELY-TPP",
+    "authors": "WIlliam J Hulme; Elsie M F Horne; Edward P K Parker; Ruth H Keogh; Elizabeth J Williamson; Venexia Walker; Tom Palmer; Helen J Curtis; Alex Walker; Amir Mehrkar; Jessica Morley; Brian MacKenna; Sebastian C J Bacon; Ben Goldacre; Miguel A Hernan; Jonathan A C Sterne",
+    "affiliations": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit, Bristol Medical Scho; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit, Bristol Medical Scho; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK; CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA 02115; Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health,; Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; H",
+    "abstract": "IntroductionThe COVID-19 booster vaccination programme in England used both BNT162b2 and mRNA-1273 vaccines. Direct comparisons of the effectiveness against severe COVID-19 of these two vaccines for boosting have not been made in trials or observational data.\n\nMethodsOn behalf of NHS England, we used the OpenSAFELY-TPP database to match adult recipients of each vaccine type on date of vaccination, primary vaccine course, age, and other characteristics. Recipients were eligible if boosted between 29 October 2021 and 31 January 2022, and followed up for 12 weeks. Outcomes were positive SARS-CoV-2 test, COVID-19 hospitalisation, and COVID-19 death. We estimated the cumulative incidence of each outcome, and quantified comparative effectiveness using risk differences (RD) and hazard ratios (HRs).\n\nResults1,528,431 people were matched in each group, contributing a total 23,150,504 person-weeks of follow-up. The 12-week risks per 1,000 people of positive SARS-CoV-2 test were 103.2 (95%CI 102.4 to 104.0) for BNT162b2 and 96.0 (95.2 to 96.8) for mRNA-1273: the HR comparing mRNA-1273 with BNT162b2 was 0.92 (95%CI 0.91 to 0.92). For COVID-19 hospitalisations the 12-week risks per 1,000 were 0.65 (95%CI 0.56 to 0.75) and 0.44 (0.36 to 0.54): HR 0.67 (95%CI 0.58 to 0.78). COVID-19 deaths were rare: the 12-week risks per 1,000 were 0.03 (95%CI 0.02 to 0.06) and 0.01 (0.01 to 0.02): HR 1.23 (95%CI 0.59 to 2.56). Comparative effectiveness was generally similar within subgroups defined by the primary course vaccine brand, age, prior SARS-CoV-2 infection and clinical vulnerability.\n\nConclusionBooster vaccination with mRNA-1273 COVID-19 vaccine was more effective than BNT162b2 in preventing SARS-CoV-2 infection and COVID-19 hospitalisation during the first 12 weeks after vaccination, during a period of Delta followed by Omicron variant dominance.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "bioRxiv",
     "doi": "10.1101/2022.07.26.501570",
@@ -1623,6 +1707,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2022.05.22.22275417",
+    "date": "2022-05-23",
+    "link": "https://medrxiv.org/cgi/content/short/2022.05.22.22275417",
+    "title": "Comparative effectiveness of sotrovimab and molnupiravir for prevention of severe COVID-19 outcomes in non-hospitalised patients: an observational cohort study using the OpenSAFELY platform",
+    "authors": "Bang Zheng; Amelia CA Green; John Tazare; Helen J Curtis; Louis Fisher; Linda Nab; Anna Schultze; Viyaasan Mahalingasivam; Edward Parker; William J Hulme; Sebastian CJ Bacon; Nicholas J DeVito; Christopher Bates; David Evans; Peter Inglesby; Henry Drysdale; Simon Davy; Jonathan Cockburn; Caroline E Morton; George Hickman; Tom Ward; Rebecca M Smith; John Parry; Frank Hester; Sam Harper; Amir Mehrkar; Rosalind M Eggo; Alex J Walker; Stephen JW Evans; Ian J Douglas; Brian MacKenna; Ben Goldacre; Laurie A Tomlinson",
+    "affiliations": "London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Trop. Med.; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; TPP; TPP; University of Oxford; London School of Hygiene & Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine",
+    "abstract": "ObjectiveTo compare the effectiveness of sotrovimab (a neutralising monoclonal antibody) vs. molnupiravir (an antiviral) in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients.\n\nDesignWith the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform.\n\nSettingPatient-level electronic health record data were obtained from 24 million people registered with a general practice in England that uses TPP software. The primary care data were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death within the OpenSAFELY-TPP platform, covering a period where both medications were frequently prescribed in community settings.\n\nParticipantsNon-hospitalised adult COVID-19 patients at high risk of severe outcomes treated with sotrovimab or molnupiravir since December 16, 2021.\n\nInterventionsSotrovimab or molnupiravir administered in the community by COVID-19 Medicine Delivery Units.\n\nMain outcome measureCOVID-19 related hospitalisation or COVID-19 related death within 28 days after treatment initiation.\n\nResultsBetween December 16, 2021 and February 10, 2022, 3331 and 2689 patients were treated with sotrovimab and molnupiravir, with no substantial differences in their baseline characteristics. The mean age of all 6020 patients was 52 (SD=16) years; 59% were female, 89% White and 88% had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 87 (1.4%) COVID-19 related hospitalisations/deaths were observed (32 treated with sotrovimab and 55 with molnupiravir). Cox proportional hazards models stratified by area showed that after adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, treatment with sotrovimab was associated with a substantially lower risk than treatment with molnupiravir (hazard ratio, HR=0.54, 95% CI: 0.33 to 0.88; P=0.014). Consistent results were obtained from propensity score weighted Cox models (HR=0.50, 95% CI: 0.31 to 0.81; P=0.005) and when restricted to fully vaccinated people (HR=0.53, 95% CI: 0.31 to 0.90; P=0.019). No substantial effect modifications by other characteristics were detected (all P values for interaction>0.10). Findings were similar in an exploratory analysis of patients treated between February 16 and May 1, 2022 when the Omicron BA.2 variant was dominant in England.\n\nConclusionIn routine care of non-hospitalised high-risk adult patients with COVID-19 in England, those who received sotrovimab were at lower risk of severe COVID-19 outcomes than those receiving molnupiravir.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2022.05.21.22275368",
@@ -1735,6 +1833,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2022.05.05.22273234",
+    "date": "2022-05-07",
+    "link": "https://medrxiv.org/cgi/content/short/2022.05.05.22273234",
+    "title": "Changes in English medication safety indicators throughout the COVID-19 pandemic: a federated analysis of 57 million patients' primary care records in situ using OpenSAFELY",
+    "authors": "Louis Fisher; Lisa E M Hopcroft; Sarah Rodgers; James Barrett; Kerry Oliver; Anthony J Avery; Dai Evans; Helen Curtis; Richard Croker; Orla Macdonald; Jessica Morley; Amir Mehrkar; Seb Bacon; Simon Davy; Iain Dillingham; David Evans; George Hickman; Peter Inglesby; Caroline E Morton; Becky Smith; Tom Ward; William Hulme; Amelia Green; Jon Massey; Alex J Walker; Chris Bates; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Shaun O'Hanlon; Alex Eavis; Richard Jarvis; Dima Avramov; Paul Griffiths; Aaron Fowles; Nasreen Parkes; Ben Goldacre; Brian MacKenna",
+    "affiliations": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; Centre for Academic Primary Care, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG",
+    "abstract": "ObjectiveTo describe the impact of the COVID-19 pandemic on safe prescribing, using the PINCER prescribing indicators; to implement complex prescribing indicators at national scale using GP data.\n\nDesignPopulation based cohort study, with the approval of NHS England using the OpenSAFELY platform.\n\nSettingElectronic health record data from 56.8 million NHS patients general practice records.\n\nParticipantsAll NHS patients registered at a GP practice using TPP or EMIS computer systems and recorded as at risk of at least one potentially hazardous PINCER indicator between September 2019 and September 2021.\n\nMain outcome measureMonthly trends and between-practice variation for compliance with 13 PINCER measures between September 2019 and September 2021.\n\nResultsThe indicators were successfully implemented across GP data in OpenSAFELY. Hazardous prescribing remained largely unchanged during the COVID-19 pandemic, with only small reductions in achievement of the PINCER indicators. There were transient delays in blood test monitoring for some medications, particularly ACE inhibitors. All indicators exhibited substantial recovery by September 2021. We identified 1,813,058 patients at risk of at least one hazardous prescribing event.\n\nConclusionGood performance was maintained during the COVID-19 pandemic across a diverse range of widely evaluated measures of safe prescribing.\n\nSummary box O_TEXTBOXWHAT IS ALREADY KNOWN ON THIS TOPICO_LIPrimary care services were substantially disrupted by the COVID-19 pandemic.\nC_LIO_LIDisruption to safe prescribing during the pandemic has not previously been evaluated.\nC_LIO_LIPINCER is a nationally adopted programme of activities that aims to identify and correct hazardous prescribing in GP practices, by conducting manual audit on subgroups of practices.\nC_LI\n\nWHAT THIS STUDY ADDSO_LIFor the first time, we were able to successfully generate data on PINCER indicators for almost the whole population of England, in a single analysis.\nC_LIO_LIOur study is the most comprehensive assessment of medication safety during the COVID-19 pandemic in England, covering 95% of the population using well-validated measures.\nC_LIO_LIGood performance was maintained across many PINCER indicators throughout the pandemic.\nC_LIO_LIDelays in delivering some medication-related blood test monitoring were evident though considerable recovery was made by the end of the study period.\nC_LI\n\nC_TEXTBOX",
+    "category": "primary care research",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2022.05.03.22274395",
@@ -2043,20 +2155,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2022.03.23.22272804",
-    "date": "2022-03-23",
-    "link": "https://medrxiv.org/cgi/content/short/2022.03.23.22272804",
-    "title": "Waning effectiveness of BNT162b2 and ChAdOx1 COVID-19 vaccines over six months since second dose: a cohort study using linked electronic health records",
-    "authors": "Elsie MF Horne; William J Hulme; Ruth H Keogh; Tom M Palmer; Elizabeth J Williamson; Edward PK Parker; Amelia Green; Venexia Walker; Alex J Walker; Helen Curtis; Louis Fisher; Brian MacKenna; Richard Croker; Lisa Hopcroft; Robin Y Park; Jon Massey; Jessica Morely; Amir Mehrkar; Sebastian Bacon; David Evans; Peter Inglesby; Caroline E Morton; George Hickman; Simon Davy; Tom Ward; Iain Dillingham; Ben Goldacre; Miguel A Hernan; Jonathan AC Sterne",
-    "affiliations": "University of Bristol; Univeristy of Oxford; London School of Hygiene and Tropical Medicine; University of Bristol; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Univeristy of Oxford; University of Bristol; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Univeristy of Oxford; Harvard University; University of Bristol",
-    "abstract": "BackgroundThe rate at which COVID-19 vaccine effectiveness wanes over time is crucial for vaccination policies, but is incompletely understood with conflicting results from different studies.\n\nMethodsThis cohort study, using the OpenSAFELY-TPP database and approved by NHS England, included individuals without prior SARS-CoV-2 infection assigned to vaccines priority groups 2-12 defined by the UK Joint Committee on Vaccination and Immunisation. We compared individuals who had received two doses of BNT162b2 or ChAdOx1 with unvaccinated individuals during six 4-week comparison periods, separately for subgroups aged 65+ years; 16-64 years and clinically vulnerable; 40-64 years and 18-39 years. We used Cox regression, stratified by first dose eligibility and geographical region and controlled for calendar time, to estimate adjusted hazard ratios (aHRs) comparing vaccinated with unvaccinated individuals, and quantified waning vaccine effectiveness as ratios of aHRs per-4-week period. The outcomes were COVID-19 hospitalisation, COVID-19 death, positive SARS-CoV-2 test, and non-COVID-19 death.\n\nFindingsThe BNT162b2, ChAdOx1 and unvaccinated groups comprised 1,773,970, 2,961,011 and 2,433,988 individuals, respectively. Waning of vaccine effectiveness was similar across outcomes and vaccine brands: e.g. in the 65+ years subgroup ratios of aHRs versus unvaccinated for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test ranged from 1.23 (95% CI 1.15-1.32) to 1.27 (1.20-1.34) for BNT162b2 and 1.16 (0.98-1.37) to 1.20 (1.14-1.27) for ChAdOx1. Despite waning, rates of COVID-19 hospitalisation and COVID-19 death were substantially lower among vaccinated individuals compared to unvaccinated individuals up to 26 weeks after second dose, with estimated aHRs <0.20 (>80% vaccine effectiveness) for BNT162b2, and <0.26 (>74%) for ChAdOx1. By weeks 23-26, rates of SARS-CoV-2 infection in fully vaccinated individuals were similar to or higher than those in unvaccinated individuals: aHRs ranged from 0.85 (0.78-0.92) to 1.53 (1.07-2.18) for BNT162b2, and 1.21 (1.13-1.30) to 1.99 (1.94-2.05) for ChAdOx1.\n\nInterpretationThe rate at which estimated vaccine effectiveness waned was strikingly consistent for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test, and similar across subgroups defined by age and clinical vulnerability. If sustained to outcomes of infection with the Omicron variant and to booster vaccination, these findings will facilitate scheduling of booster vaccination doses.",
-    "category": "infectious diseases",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2022.03.18.22272607",
@@ -2085,6 +2183,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2022.03.17.22272535",
+    "date": "2022-03-18",
+    "link": "https://medrxiv.org/cgi/content/short/2022.03.17.22272535",
+    "title": "Comparison of the 2021 COVID-19 'Roadmap' Projections against Public Health Data",
+    "authors": "Matt J Keeling; Louise J Dyson; Michael Tildesley; Edward M Hill; Sam M Moore",
+    "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick",
+    "abstract": "Control and mitigation of the COVID-19 pandemic in England has relied on a combination of vaccination and non-pharmaceutical interventions (NPIs). Some of these NPIs are extremely costly (economically and socially), so it was important to relax these promptly without overwhelming already burdened health services. The eventual policy was a Roadmap of four relaxation steps throughout 2021, taking England from lock-down to the cessation of all restrictions on social interaction. In a series of six Roadmap documents generated throughout 2021, models assessed the potential risk of each relaxation step. Here we show that the model projections generated a reliable estimation of medium-term hospital admission trends, with the data points up to September 2021 generally lying within our 95% prediction intervals. The greatest uncertainties in the modelled scenarios came from vaccine efficacy estimates against novel variants, and from assumptions about human behaviour in the face of changing restrictions and risk.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2022.03.15.22272362",
@@ -2561,6 +2673,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2022.01.05.21268323",
+    "date": "2022-01-06",
+    "link": "https://medrxiv.org/cgi/content/short/2022.01.05.21268323",
+    "title": "Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey",
+    "authors": "Katrina A Lythgoe; Tanya Golubchik; Matthew Hall; Thomas House; Roberto Cahuantzi; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; Mahan Ghafari; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Christophe Fraser; Ian Diamond; Jeff Barrett; Ann Sarah Walker; David Bonsall",
+    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Manchester; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Wellcome Sanger Institute; Office for National Statistics; ; University of Oxford; Office for National Statistics; Wellcome Sanger Institute; University of Oxford; University of Oxford",
+    "abstract": "The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non- SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly in the current phase of the pandemic with routine RT-PCR testing now ended in the community.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2022.01.01.21268131",
@@ -2673,20 +2799,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "bioRxiv",
-    "doi": "10.1101/2021.12.17.473248",
-    "date": "2021-12-21",
-    "link": "https://biorxiv.org/cgi/content/short/2021.12.17.473248",
-    "title": "SARS-CoV-2 Omicron spike mediated immune escape, infectivity and cell-cell fusion",
-    "authors": "Bo Meng; Isabella Ferreira; Adam Abdullahi; Niluka Goonawardane; Akatsuki Saito; Izumi Kimura; Daichi Yamasoba; Steven A Kemp; Guido Papa; Saman Fatihi; Surabhi Rathore; Pehuen Perera Gerba; Terumasa Ikeda; Mako Toyoda; Toong Seng Tan; Jin Kuramochi; Shigeki Mitsunaga; Takamasa Ueno; Oscar Charles; Dami Collier; - CITIID-NIHR BioResource COVID-19 Collaboration; - The Genotype to Phenotype Japan (G2P-Japan) Consortium; - Ecuador-COVID19 Consortium; John Bradley; Jinwook Choi; Kenneth Smith; Elo Madissoon; Kerstin Meyer; Petra Mlcochova; Rainer Doffinger; Sarah A Teichmann; Leo James; Joo Hyeon Lee; Teresa Brevini; Matteo Pizzuto; Myra Hosmillo; Donna Mallery; Samantha Zepeda; Alexandra Walls; Anshu Joshi; John Bowen; John Briggs; Alex Sigal; Laurelle Jackson; Sandile Cele; Anna De Marco; Fotios Sampaziotis; Davide Corti; David Veesler; Nicholas Matheson; Ian Goodfellow; Lipi Thukral; Kei Sato; Ravindra K Gupta",
-    "affiliations": "University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Miyazaki; The University of Tokyo; Kumamoto University; University of Cambridge; LMB Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; CSIR Institute of Genomics and Integrative Biology, Delhi, India; University of Cambridge; Kumamoto Univ; Kumamoto University, Kumamoto; Kuramochi Clinic Interpark; Kuramochi Clinic Interpark; National Institute of Genetics, Mishima, Shizuoka; Kumamoto University, Kumamoto; University College London; University of Cambridge; -; -; -; University of Cambridge; University of Cambridge; University of Cambridge; Wellcome Sanger Institute; Wellcome Sanger Institute; University of Cambridge; Cambridge University Hospitals NHS Trust; Cambridge University; MRC LMB; University of Cambridge; University of Cambridge; Humabs Biomed SA; University of Cambridge; MRC LMB Cambridge; University of Washington; University of Washington; University of Washington; University of Washington; University of Heidelberg; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Africa Health Research Institute, Durban, South Africa; Humabs Biomed SA; University of Cambridge; Humabs Biomed SA; University of Washington; University of Cambridge; University of Cambridge; CSIR Institute of Genomics and Integrative Biology, Delhi, India; The University of Tokyo; University of Cambridge",
-    "abstract": "The SARS-CoV-2 Omicron BA.1 variant emerged in late 2021 and is characterised by multiple spike mutations across all spike domains. Here we show that Omicron BA.1 has higher affinity for ACE2 compared to Delta, and confers very significant evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralising antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralisation. Importantly, antiviral drugs remdesevir and molnupiravir retain efficacy against Omicron BA.1. We found that in human nasal epithelial 3D cultures replication was similar for both Omicron and Delta. However, in lower airway organoids, Calu-3 lung cells and gut adenocarcinoma cell lines live Omicron virus demonstrated significantly lower replication in comparison to Delta. We noted that despite presence of mutations predicted to favour spike S1/S2 cleavage, the spike protein is less efficiently cleaved in live Omicron virions compared to Delta virions. We mapped the replication differences between the variants to entry efficiency using spike pseudotyped virus (PV) entry assays. The defect for Omicron PV in specific cell types correlated with higher cellular RNA expression of TMPRSS2, and accordingly knock down of TMPRSS2 impacted Delta entry to a greater extent as compared to Omicron. Furthermore, drug inhibitors targeting specific entry pathways demonstrated that the Omicron spike inefficiently utilises the cellular protease TMPRSS2 that mediates cell entry via plasma membrane fusion. Instead, we demonstrate that Omicron spike has greater dependency on cell entry via the endocytic pathway requiring the activity of endosomal cathepsins to cleave spike. Consistent with suboptimal S1/S2 cleavage and inability to utilise TMPRSS2, syncytium formation by the Omicron spike was dramatically impaired compared to the Delta spike. Overall, Omicron appears to have gained significant evasion from neutralising antibodies whilst maintaining sensitivity to antiviral drugs targeting the polymerase. Omicron has shifted cellular tropism away from TMPRSS2 expressing cells that are enriched in cells found in the lower respiratory and GI tracts, with implications for altered pathogenesis.",
-    "category": "microbiology",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.12.20.21268098",
@@ -2813,20 +2925,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.12.13.21267368",
-    "date": "2021-12-15",
-    "link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267368",
-    "title": "Acute COVID-19 severity and 16-month mental morbidity trajectories in patient populations of six nations",
-    "authors": "Ingibjorg Magnusdottir; Aniko Lovik; Anna Bara Unnarsdottir; Daniel L. McCartney; Helga Ask; Kadri Koiv; Lea Arregui Nordahl Christoffersen; Sverre Urnes Johnson; Andrew M McIntosh; Anna K. Kahler; Archie Campbell; Arna Hauksdottir; Chloe Fawns-Ritchie; Christian Erikstrup; Dorte Helenius; Drew Altschul; Edda Bjork Thordardottir; Elias Eythorsson; Emma M. Frans; Gunnar Tomasson; Harpa Lind Jonsdottir; Harpa Runarsdottir; Henrik Hjalgrim; Hronn Hardardottir; Juan Gonzalez-Hijon; Karina Banasik; Khoa Manh Dinh; Li Lu; Lili Milani; Lill Trogstad; Maria Didriksen; Omid V. Ebrahimi; Patrick F. Sullivan; Per Minor Magnus; Qing Shen; Ragnar Nesvag; Reedik Magi; Runolfur Palsson; Sisse Rye Ostrowski; Thomas Werge; Asle Hoffart; David J. Porteous; Fang Fang; Johanna Jakobsdottir; Kelli Lehto; Ole A. Andreassen; Ole B.V. Pedersen; Thor Aspelund; Unnur Anna Valdimarsdottir",
-    "affiliations": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Oslo, Oslo, Norway; Division of Psychiatry, University of Edinburgh, Edinburgh, UK; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark; Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Edinburgh, Edinburgh, UK; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Faculty of Psychology, University of Iceland School of Health Sciences, Reykjavik, Iceland; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Danish Cancer Society Research Center, Copenhagen, Denmark; Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Translational Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Oslo, Oslo, Norway; Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA; Centre of Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway.; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland; Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; Department of Psychology, University of Oslo, Oslo, Norway; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia; NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Immunology, Zealand University Hospital, Denmark; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland; Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland",
-    "abstract": "BACKGROUNDThe aim of this multinational study was to assess the development of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis.\n\nMETHODSParticipants consisted of 247 249 individuals from seven cohorts across six countries (Denmark, Estonia, Iceland, Norway, Scotland, and Sweden) recruited from April 2020 through August 2021. We used multivariable Poisson regression to contrast symptom-prevalence of depression, anxiety, COVID-19 related distress, and poor sleep quality among individuals with and without a diagnosis of COVID-19 at entry to respective cohorts by time (0-16 months) from diagnosis. We also applied generalised estimating equations (GEE) analysis to test differences in repeated measures of mental health symptoms before and after COVID-19 diagnosis among individuals ever diagnosed with COVID-19 over time.\n\nFINDINGSA total of 9979 individuals (4%) were diagnosed with COVID-19 during the study period and presented overall with a higher symptom burden of depression (prevalence ratio [PR] 1{middle dot}18, 95% confidence interval [95% CI] 1{middle dot}03-1{middle dot}36) and poorer sleep quality (1{middle dot}13, 1{middle dot}03-1{middle dot}24) but not with higher levels of symptoms of anxiety or COVID-19 related distress compared with individuals without a COVID-19 diagnosis. While the prevalence of depression and COVID-19 related distress attenuated with time, the trajectories varied significantly by COVID-19 acute infection severity. Individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risks of depression and anxiety (PR 0{middle dot}83, 95% CI 0{middle dot}75-0{middle dot}91 and 0{middle dot}77, 0{middle dot}63-0{middle dot}94, respectively), while patients bedridden for more than 7 days were persistently at higher risks of symptoms of depression and anxiety (PR 1{middle dot}61, 95% CI 1{middle dot}27-2{middle dot}05 and 1{middle dot}43, 1{middle dot}26-1{middle dot}63, respectively) throughout the 16-month study period.\n\nCONCLUSIONAcute infection severity is a key determinant of long-term mental morbidity among COVID-19 patients.",
-    "category": "public and global health",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 92
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.12.14.21267460",
@@ -2995,20 +3093,6 @@
     "author_similarity": 94,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.11.22.21266692",
-    "date": "2021-11-24",
-    "link": "https://medrxiv.org/cgi/content/short/2021.11.22.21266692",
-    "title": "Serological responses to COVID-19 booster vaccine in England",
-    "authors": "Georgina Ireland; Heather Whitaker; Shamez N Ladhani; Frances Baawuah; Vani Subbarao; Ezra Linley; Lenesha Warrener; Michelle O'Brien; Corrine Whillock; Paul Moss; Mary E Ramsay; Gayatri Amirthalingam; Kevin E Brown",
-    "affiliations": "UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; Brondesbury Medical Centre, Kilburn, London, United Kingdom; UK Health Security Agency; University of Birmingham; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency",
-    "abstract": "IntroductionThere are limited data on immune responses after COVID-19 vaccine boosters in individuals receiving primary immunisation with BNT162b2 (Pfizer-BioNTech) or AZD1222 (AstraZeneca).\n\nMethodsA prospective, cohort study to assess SARS-CoV-2 antibody responses before and after booster vaccination with BNT162b2 in adults receiving either (i) two BNT162b2 doses <30 days apart (BNT162b2-control), (ii) two BNT162b2 doses [&ge;]30 days apart (BNT162b2-extended) or (iii) two AZD1222 doses [&ge;]30 days apart (AZD1222-extended) in London, England. SARS-CoV-2 spike protein antibody geometric mean titres (GMTs) before and 2-4 weeks after booster were compared.\n\nResultsOf 750 participants, 626 provided serum samples for up to 38 weeks after their second vaccine dose. Antibody GMTs peaked at 2-4 weeks after the second dose, before declining by 68% at 36-38 weeks after dose 2 for BNT162b2-control participants, 85% at 24-29 weeks for BNT162b2-extended participants and 78% at 24-29 weeks for AZD1222-extended participants. Antibody GMTs was highest in BNT162b2-extended participants (942 [95%CI, 797-1113]) than AZD1222-extended (183 [124-268]) participants at 24-29 weeks or BNT162b2-control participants at 36-38 weeks (208; 95%CI, 150-289). At 2-4 weeks after booster, GMTs were significantly higher than after primary vaccination in all three groups: 18,104 (95%CI, 13,911-23,560; n=47) in BNT162b2-control (76.3-fold), 13,980 (11,902-16,421; n=118) in BNT162b2-extended (15.9-fold) and 10,799 (8,510-13,704; n=43) in AZD1222-extended (57.2-fold) participants. BNT162b2-control participants (median:262 days) had a longer interval between primary and booster doses than BNT162b2-extended or AZD1222-extended (both median:186 days) participants.\n\nConclusionsWe observed rapid serological responses to boosting with BNT162b2, irrespective of vaccine type or schedule used for primary immunisation, with higher post-booster responses with longer interval between primary immunisation and boosting. Boosters will not only provide additional protection for those at highest risk of severe COVID-19 but also prevent infection and, therefore, interrupt transmission, thereby reducing infections rates in the population. Ongoing surveillance will be important for monitoring the duration of protection after the booster.",
-    "category": "infectious diseases",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.11.22.21266512",
@@ -3079,6 +3163,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.11.10.21266124",
+    "date": "2021-11-11",
+    "link": "https://medrxiv.org/cgi/content/short/2021.11.10.21266124",
+    "title": "Differences in COVID-19 vaccination coverage by occupation in England: a national linked data study",
+    "authors": "Vahe Nafilyan; Ted Dolby; Katie Finning; Jasper Morgan; Rhiannon Edge; Myer Glickman; Neil Pearce; Martie Van Tongeren",
+    "affiliations": "Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Lancaster University; Office for National Statistics; London School of Hygiene and Tropical Medicine; University of Manchester",
+    "abstract": "BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation.\n\nMethodsUsing nationwide population-level data, we calculated the proportion of people who had received two doses of a COVID-19 vaccine (assessed on 31 August 2021) by detailed occupational categories in adults aged 40-64 and estimated adjusted odds ratios to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.\n\nResultsOur study population included 14,298,147 adults 40-64. Vaccination rates differed markedly by occupation, being higher in administrative and secretarial occupations (90.8%); professional occupations (90.7%); and managers, directors and senior officials (90.6%); and lowest (83.1%) in people working in elementary occupations. We found substantial differences in vaccination rates looking at finer occupational groups even after adjusting for confounding factors, such as education. Vaccination rates were higher in occupations which can be done from home and lower in those which cannot. Many occupations with low vaccination rates also involved contact with the public or with vulnerable people\n\nConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection, especially in occupations that cannot be done from home and involve contacts with the public. Policies such as  work from home if you can may only have limited future impact on hospitalisations and deaths\n\nWhat is already known on this subject?Whilst several studies highlight differences in vaccination coverage by ethnicity, religion, socio-demographic factors and certain underlying health conditions, there is very little evidence on how vaccination coverage varies by occupation, in the UK and elsewhere. The few study looking at occupational differences in vaccine hesitancy focus on healthcare workers or only examined broad occupational groups. There is currently no large-scale study on occupational differences in COVID-19 vaccination coverage in the UK.\n\nWhat this study adds?Using population-level linked data combining the 2011 Census, primary care records, mortality and vaccination data, we found that the vaccination rates of adults aged 40 to 64 years in England differed markedly by occupation. Vaccination rates were high in administrative and secretarial occupations, professional occupations and managers, directors and senior officials and low in people working in elementary occupations. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were also associated with the ability to work from home, with the vaccination rate being higher in occupations which can be done performed from home. Policies aiming to increase vaccination rates in occupations that cannot be done from home and involve contacts with the public should be priorities",
+    "category": "public and global health",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.11.05.21265968",
@@ -3499,20 +3597,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.09.13.21263487",
-    "date": "2021-09-16",
-    "link": "https://medrxiv.org/cgi/content/short/2021.09.13.21263487",
-    "title": "SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population",
-    "authors": "Jia Wei; Koen B. Pouwels; Nicole Stoesser; Philippa C. Matthews; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John I Bell; John N Newton; Jeremy Farrar; Alison Howarth; Brian D. Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W. Crook; Tim E.A. Peto; A.Sarah Walker; David W. Eyre",
-    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford",
-    "abstract": "We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.",
-    "category": "infectious diseases",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.09.13.21262360",
@@ -3905,20 +3989,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.07.20.21260558",
-    "date": "2021-07-22",
-    "link": "https://medrxiv.org/cgi/content/short/2021.07.20.21260558",
-    "title": "Intentions to participate in cervical and colorectal cancer screening during the COVID-19 pandemic: a mixed-methods study",
-    "authors": "Rebecca Wilson; Harriet Quinn-Scoggins; Yvonne Moriarty; Jacqueline Hughes; Mark Goddard; Rebecca Cannings-John; Victoria Whitelock; Katriina L Whitaker; Detelina Grozeva; Julia Townson; Kirstie Osborne; Stephanie Smits; Michael Robling; Julie Hepburn; Graham Moore; Ardiana Gjini; Kate Brain; Jo Waller",
-    "affiliations": "Cardiff University; Cardiff University; Cardiff University; Cardiff University; Cardiff University; Cardiff University; Cancer Research UK; University of Surrey; Cardiff University; Cardiff University; Cancer Research UK; Cardiff University; Cardiff University; Public Involvement Community, Health and Care Research Wales; Cardiff University; Public Health Wales; Cardiff University; Kings College London",
-    "abstract": "Worldwide, cancer screening faced significant disruption in 2020 due to the COVID-19 pandemic. If this has led to changes in public attitudes towards screening and reduced intention to participate, there is a risk of long-term adverse impact on cancer outcomes. In this study, we examined previous participation and future intentions to take part in cervical and colorectal cancer (CRC) screening following the first national lockdown in the UK.\n\nOverall, 7543 adults were recruited to a cross-sectional online survey in August-September 2020. Logistic regression analyses were used to identify correlates of strong screening intentions among 2,319 participants eligible for cervical screening and 2,502 eligible for home-based CRC screening. Qualitative interviews were conducted with a sub-sample of 30 participants. Verbatim transcripts were analysed thematically.\n\nOf those eligible, 74% of survey participants intended to attend cervical screening and 84% intended to complete home-based CRC screening when next invited. Thirty percent and 19% of the cervical and CRC samples respectively said they were less likely to attend a cancer screening appointment now than before the pandemic. Previous non-participation was the strongest predictor of low intentions for cervical (aOR 26.31, 95% CI: 17.61-39.30) and CRC (aOR 67.68, 95% CI: 33.91-135.06) screening. Interview participants expressed concerns about visiting healthcare settings but were keen to participate when screening programmes resumed.\n\nIntentions to participate in future screening were high and strongly associated with previous engagement in both programmes. As screening services recover, it will be important to monitor participation and to ensure people feel safe to attend.",
-    "category": "oncology",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 98
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.07.19.21260782",
@@ -4171,6 +4241,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.06.28.21259452",
+    "date": "2021-07-03",
+    "link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259452",
+    "title": "Persistent symptoms following SARS-CoV-2 infection in a random community sample of 508,707 people",
+    "authors": "Matthew Whitaker; Joshua Elliott; Marc Chadeau-Hyam; Steven Riley; Ara Darzi; Graham Cooke; Helen Ward; Paul Elliott",
+    "affiliations": "Imperial College London; Imperial College London; Imperial College London; Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health",
+    "abstract": "BackgroundLong COVID, describing the long-term sequelae after SARS-CoV-2 infection, remains a poorly defined syndrome. There is uncertainty about its predisposing factors and the extent of the resultant public health burden, with estimates of prevalence and duration varying widely.\n\nMethodsWithin rounds 3-5 of the REACT-2 study, 508,707 people in the community in England were asked about a prior history of COVID-19 and the presence and duration of 29 different symptoms. We used uni-and multivariable models to identify predictors of persistence of symptoms (12 weeks or more). We estimated the prevalence of symptom persistence at 12 weeks, and used unsupervised learning to cluster individuals by symptoms experienced.\n\nFindingsAmong the 508,707 participants, the weighted prevalence of self-reported COVID-19 was 19.2% (95% CI: 19.1,19.3). 37.7% of 76,155 symptomatic people post COVID-19 experienced at least one symptom, while 14.8% experienced three or more symptoms, lasting 12 weeks or more. This gives a weighted population prevalence of persistent symptoms of 5.75% (5.68, 5.81) for one and 2.22% (2.1, 2.26) for three or more symptoms. Almost a third of people (8,771/28,713 [30.5%]) with at least one symptom lasting 12 weeks or more reported having had severe COVID-19 symptoms (\"significant effect on my daily life\") at the time of their illness, giving a weighted prevalence overall for this group of 1.72% (1.69,1.76). The prevalence of persistent symptoms was higher in women than men (OR: 1.51 [1.46,1.55]) and, conditional on reporting symptoms, risk of persistent symptoms increased linearly with age by 3.5 percentage points per decade of life. Obesity, smoking or vaping, hospitalisation, and deprivation were also associated with a higher probability of persistent symptoms, while Asian ethnicity was associated with a lower probability. Two stable clusters were identified based on symptoms that persisted for 12 weeks or more: in the largest cluster, tiredness predominated, while in the second there was a high prevalence of respiratory and related symptoms.\n\nInterpretationA substantial proportion of people with symptomatic COVID-19 go on to have persistent symptoms for 12 weeks or more, which is age-dependent. Clinicians need to be aware of the differing manifestations of Long COVID which may require tailored therapeutic approaches. Managing the long-term sequelae of SARS-CoV-2 infection in the population will remain a major challenge for health services in the next stage of the pandemic.\n\nFundingThe study was funded by the Department of Health and Social Care in England.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSRecent systematic reviews have documented the wide range of symptoms and reported prevalence of persistent symptoms following COVID-19. A dynamic review of Long COVID studies (NIHR Evidence) in March 2021 summarised the literature on the prevalence of persistent symptoms after acute COVID19, and reported that most studies (14) were of hospitalised patients, with higher prevalence of persistent symptoms compared with two community-based studies. There was limited evidence from community studies beyond 12 weeks. Another systematic review reported a median of over 70% of people with symptoms lasting at least 60 days. A review of risk factors for Long COVID found consistent evidence for an increased risk amongst women and those with high body mass index (BMI) but inconsistent findings on the role of age and little evidence concerning risks among different socioeconomic or ethnic groups which are often not well captured in routine healthcare records. Long COVID is increasingly recognised as heterogenous, likely underpinned by differing biological mechanisms, but there is not yet consensus on defining subtypes of the condition.\n\nAdded value of this studyThis community-based study of over half a million people was designed to be representative of the adult population of England. A random sample of adults ages 18 years and above registered with a GP were invited irrespective of previous access to services for COVID-19, providing an estimate of population prevalence that was representative of the whole population. The findings show substantial declines in symptom prevalence over the first 12 weeks following Covid-19, reported by nearly one fifth of respondents, of whom over a third remained symptomatic at 12 weeks and beyond, with little evidence for decline thereafter.\n\nRisk factors identified for persistent symptoms (12 weeks or more) suggestive of Long COVID confirm some previous findings - an increased risk in women, obese and overweight individuals and those hospitalised for COVID-19, with strong evidence for an increasing risk with age. Additional evidence was found for an increased risk in those with lower income, smoking or vaping and healthcare or care home workers. A lower risk was found in those of Asian ethnicity.\n\nClustering identified two distinct groups of individuals with different symptom profiles at 12 weeks, highlighting the heterogeneity of clinical presentation. The smaller cluster had higher prevalence of respiratory and related symptoms, while for those in the larger cluster tiredness was the dominant symptom, with lower prevalence of organ-specific symptoms.\n\nImplications of available evidenceThere is a high prevalence of persistent symptoms beyond 12 weeks after acute COVID-19, with little evidence of decline thereafter. This highlights the needs for greater support for patients, both through specialised services and, for those from low-income settings, financial support. The understanding that there are distinct clusters of persistent symptoms, the most common of which is dominated by fatigue, is important for the recognition and clinical management of the condition outside of specialised services.",
+    "category": "infectious diseases",
+    "match_type": "fuzzy",
+    "author_similarity": 96,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.06.28.21259529",
@@ -4451,20 +4535,6 @@
     "author_similarity": 95,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.06.08.21258533",
-    "date": "2021-06-12",
-    "link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258533",
-    "title": "The impact of co-circulating pathogens on SARS-CoV-2/COVID-19 surveillance. How concurrent epidemics may decrease true SARS-CoV-2 percent positivity.",
-    "authors": "Aleksandra Kovacevic; Rosalind M Eggo; Marc Baguelin; Matthieu Domenech de Cell\u00e8s; Lulla Opatowski",
-    "affiliations": "Institut Pasteur; London School of Hygiene & Tropical Medicine; Imperial College London; Max Planck Institute for Infection Biology; Univ Versailles Saint Quentin / Institut Pasteur / Inserm",
-    "abstract": "BackgroundCirculation of non-SARS-CoV-2 respiratory viruses during the COVID-19 pandemic may alter quality of COVID-19 surveillance, with possible consequences for real-time analysis and delay in implementation of control measures. Here, we assess the impact of an increased circulation of other respiratory viruses on the monitoring of positivity rates of SARS-CoV-2 and interpretation of surveillance data.\n\nMethodsUsing a multi-pathogen Susceptible-Exposed-Infectious-Recovered (SEIR) transmission model formalizing co-circulation of SARS-CoV-2 and another respiratory we assess how an outbreak of secondary virus may inflate the number of SARS-CoV-2 tests and affect the interpretation of COVID-19 surveillance data. Using simulation, we assess to what extent the use of multiplex PCR tests on a subsample of symptomatic individuals can support correction of the observed SARS-CoV-2 percent positive during other virus outbreaks and improve surveillance quality.\n\nResultsModel simulations demonstrated that a non-SARS-CoV-2 epidemic creates an artificial decrease in the observed percent positivity of SARS-CoV-2, with stronger effect during the growth phase, until the peak is reached. We estimate that performing one multiplex test for every 1,000 COVID-19 tests on symptomatic individuals could be sufficient to maintain surveillance of other respiratory viruses in the population and correct the observed SARS-CoV-2 percent positive.\n\nConclusionsThis study highlights that co-circulating respiratory viruses can disrupt SARS-CoV-2 surveillance. Correction of the positivity rate can be achieved by using multiplex PCR, and a low number of samples is sufficient to avoid bias in SARS-CoV-2 surveillance.\n\nSummaryCOVID-19 surveillance indicators may be impacted by increased co-circulation of other respiratory viruses delaying control measure implementation. Continued surveillance through multiplex PCR testing in a subsample of the symptomatic population may play a role in fixing this problem.",
-    "category": "epidemiology",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.06.08.21258546",
@@ -4675,20 +4745,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.05.18.21257267",
-    "date": "2021-05-18",
-    "link": "https://medrxiv.org/cgi/content/short/2021.05.18.21257267",
-    "title": "Colchicine in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial",
-    "authors": "Peter W Horby; Mark Campbell; Enti Spata; Jonathan R Emberson; Natalie Staplin; Guilherme Pessoa-Amorim; Leon Peto; Martin Wiselka; Laura Wiffen; Simon Tiberi; Ben Caplin; Caroline Wroe; Christopher Green; Paul Hine; Benjamin Prudon; Tina George; Andrew Wight; J Kenneth Baillie; Buddha Basnyat; Maya H Buch; Lucy C Chappell; Jeremy N Day; Saul N Faust; Raph L Hamers; Thomas Jaki; Edmund Juszczak; Katie Jeffery; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; Marion Mafham; Richard Haynes; Martin J Landray",
-    "affiliations": "Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom and International Severe Acute Res; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and Oxford University Hospitals NHS Foundation Trust, Oxford, United King; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom and Nuffield Department of Populat; Department of Infectious Diseases, University Hospital Leicester, Leicester, United Kingdom; Portsmouth Hospitals University NHS Foundation Trust, Portsmouth, United Kingdom; Department of Infection, Barts Health NHS Trust, London, United Kingdom; Department of Renal Medicine, University College London, London, United Kingdom and Royal Free London NHS Trust, London, United Kingdom; James Cook University Hospital, Middlesbrough, United Kingdom; University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom; Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom; North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom; Basildon and Thurrock Hospitals NHS Foundation Trust, Basildon, United Kingdom; Wirral University Teaching Hospital NHS Foundation Trust, Birkenhead, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Oxford University Clinical Research Unit -Nepal, Patan Academy of Health Sciences, Kathmandu, Nepal; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; School of Life Course Sciences, King?s College London, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam and Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Univer; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia and Faculty of Medicine, University of Indonesia, Jakarta, Indonesia and Centre for Tropical Medicine ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom and MRC Biostatistics Unit, University of Cambridge, Cambridge, United; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom and Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Notting; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom; Intensive Care National Audit & Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam and Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Univer; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and Oxford University Hospitals NHS Foundation Trust, Oxford, United King; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un",
-    "abstract": "BackgroundColchicine has been proposed as a treatment for COVID-19 on the basis of its anti-inflammatory actions.\n\nMethodsIn this randomised, controlled, open-label trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19. Eligible and consenting adults were randomly allocated in a 1:1 ratio to either usual standard of care alone or usual standard of care plus colchicine twice daily for 10 days or until discharge (or one of the other treatment arms) using web-based simple (unstratified) randomisation with allocation concealment. The primary outcome was 28-day mortality. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 27 November 2020 and 4 March 2021, 5610 patients were randomly allocated to receive colchicine and 5730 patients to receive usual care alone. Overall, 1173 (21%) patients allocated to colchicine and 1190 (21%) patients allocated to usual care died within 28 days (rate ratio 1.01; 95% confidence interval [CI] 0.93-1.10; p=0.77). Consistent results were seen in all pre-specified subgroups of patients. There was no significant difference in duration of hospitalisation (median 10 days vs. 10 days) or the proportion of patients discharged from hospital alive within 28 days (70% vs. 70%; rate ratio 0.98; 95% CI 0.94-1.03; p=0.44). Among those not on invasive mechanical ventilation at baseline, there was no significant difference in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (25% vs. 25%; risk ratio 1.02; 95% CI 0.96-1.09; p=0.47).\n\nInterpretationIn adults hospitalised with COVID-19, colchicine was not associated with reductions in 28-day mortality, duration of hospital stay, or risk of progressing to invasive mechanical ventilation or death.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056). Wellcome Trust (Grant Ref: 222406/Z/20/Z) through the COVID-19 Therapeutics Accelerator.",
-    "category": "infectious diseases",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.05.17.21256818",
@@ -4717,6 +4773,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 92
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.05.12.21257123",
+    "date": "2021-05-17",
+    "link": "https://medrxiv.org/cgi/content/short/2021.05.12.21257123",
+    "title": "Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults",
+    "authors": "Vahe Nafilyan; Piotr Pawelek; Daniel Ayoubkhani; Sarah Rhodes; Lucy Pembrey; Melissa Matz; Michel P Coleman; Claudia Allemani; Ben Windsor-Shellard; Martie van Tongeren; Neil Pearce",
+    "affiliations": "Office for National Statistics; Office for National Statistics; Office for National Statistics; School of Health Sciences, University of Manchester; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Office for National Statistics; School of Health Sciences, University of Manchester; London School of Hygiene and Tropical Medicine",
+    "abstract": "ObjectiveTo estimate occupational differences in COVID-19 mortality, and test whether these are confounded by factors, such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation or pre-pandemic health.\n\nDesignRetrospective cohort study\n\nSettingPeople living in private households England\n\nParticipants14,295,900 people aged 40-64 years (mean age 52 years, 51% female) who were alive on 24 January 2020, living in private households in England in 2019, were employed in 2011, and completed the 2011 census.\n\nMain outcome measuresCOVID-19 related death, assessed between 24 January 2020 and 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk (ASMR) stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding (region, ethnicity, education), as well as non-workplace factors that are related to occupation.\n\nResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three-fold or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating non-workplace factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62-5.84] to 1.47 [1.14-1.89] after adjustment. More generally, the overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.\n\nConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.05.13.21257144",
@@ -4773,6 +4843,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.05.06.21256757",
+    "date": "2021-05-14",
+    "link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256757",
+    "title": "COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study",
+    "authors": "Yiqun Chen; Timothy Aldridge; - UK COVID-19 National Core Studies Consortium; Claire F Ferraro; Fu-Meng Khaw",
+    "affiliations": "Health and Safety Executive, UK; Health and Safety Executive, UK; ; National Infection Service, Public Health England, UK; Public Health England, UK",
+    "abstract": "BackgroundA large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic. However, information on the rate of outbreak occurrences which helps to identify the type of workplaces that are more likely to experience an outbreak, or infection attack rates which estimates the potential extent of the virus transmission in an outbreak, has not yet been available to inform intervention strategies to limit transmission.\n\nObjectivesTo link datasets on workplace settings and COVID-19 workplace outbreaks in England in order to: identify the geographical areas and workplace sectors with a high rate of outbreaks; and compare infection attack rates by workplace size and sector.\n\nMethodsWe analysed Public Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, covering the time period of 18 May - 12 October 2020. The workplaces analysed excluded care homes, hospitals and educational settings. We calculated the workplace outbreak rates by nine English regions, 151 Upper Tier Local Authorities (UTLAs) and twelve industrial sectors, using National Population Database (NPD) data extracted in May 2019 on the total number of the relevant workplaces as the denominator. We also calculated the infection attack rates by enterprise size (small, medium, large) and industrial sector, using PHE Situations of Interest (SOI) data on the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator, and using NPD data on the number employed in that workplace as the denominator.\n\nResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone data, of which 1,305 were available for estimation of outbreak rates. The average outbreak rate was 66 per 100,000 workplaces. Of the nine geographical regions in England, the North West had the highest workplace outbreak rate (155/100,000 workplaces), based on 351 outbreaks. Of the UTLAs, the highest workplace outbreak rate was Blackburn with Darwen (387/100,000 workplaces). The industrial sector with the highest workplace outbreak rate was manufacturers and packers of food (1,672/100,000), based on 117 outbreaks: this was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.\n\nIn total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%).\n\nConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.",
+    "category": "epidemiology",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.05.08.21256867",
@@ -4829,20 +4913,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.05.05.21256668",
-    "date": "2021-05-09",
-    "link": "https://medrxiv.org/cgi/content/short/2021.05.05.21256668",
-    "title": "COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland",
-    "authors": "Sofia de la Fuente Garcia; Fasih Haider; Saturnino Luz",
-    "affiliations": "The University of Edinburgh; The University of Edinburgh; The University of Edinburgh",
-    "abstract": "The COVID-19 pandemic has led to unprecedented restrictions in peoples lifestyle which have affected their psychological wellbeing. In this context, this paper investigates the use of social signal processing techniques for remote assessment of emotions. It presents a machine learning method for affect recognition applied to recordings taken during the COVID-19 winter lockdown in Scotland (UK). This method is exclusively based on acoustic features extracted from voice recordings collected through home and mobile devices (i.e. phones, tablets), thus providing insight into the feasibility of monitoring peoples psychological wellbeing remotely, automatically and at scale. The proposed model is able to predict affect with a concordance correlation coefficient of 0.4230 (using Random Forest) and 0.3354 (using Decision Trees) for arousal and valence respectively.\n\nClinical relevanceIn 2018/2019, 12% and 14% of Scottish adults reported depression and anxiety symptoms. Remote emotion recognition through home devices would support the detection of these difficulties, which are often underdiagnosed and, if untreated, may lead to temporal or chronic disability.",
-    "category": "health informatics",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.05.05.21256649",
@@ -4899,20 +4969,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.04.26.21255732",
-    "date": "2021-04-28",
-    "link": "https://medrxiv.org/cgi/content/short/2021.04.26.21255732",
-    "title": "Deprivation and Exposure to Public Activities during the COVID-19 Pandemic in England and Wales",
-    "authors": "Sarah Beale; Isobel Braithwaite; Annalan MD Navaratnam; Pia Hardelid; Alison Rodger; Anna Aryee; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Vincent Nguyen; Parth Patel; Madhumita Shrotri; Robert W Aldridge; Andrew C Hayward; - Virus Watch Collaborative",
-    "affiliations": "University College London; University College London; University College London; University College London; University College London; Royal Free London NHS Foundation Trust,; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; ",
-    "abstract": "BackgroundDifferential exposure to public activities and non-household contacts may contribute to stark deprivation-related inequalities in SARS-CoV-2 infection and outcomes, but has not been directly investigated. We set out to investigate whether participants in Virus Watch - a large community cohort study based in England and Wales - reported different levels of exposure to public activities and non-household contacts during the Autumn-Winter phase of the COVID-19 pandemic according to postcode-level socioeconomic deprivation.\n\nMethodsParticipants (n=20120-25228 across surveys) reported their daily activities during three weekly periods in late November 2020, late December 2020, and mid-February 2021. Deprivation was quantified based on participants postcode of residence using English or Welsh Indices of Multiple Deprivation quintiles. We used Poisson mixed effect models with robust standard errors to estimate the relationship between deprivation and risk of exposure to public activities during each survey period.\n\nResultsRelative to participants in the least deprived areas, participants in the most deprived areas persistently exhibited elevated risk of exposure to vehicle sharing (aRR range across time points 1.73-8.52), public transport (aRR 3.13-5.73), work or education outside of the household (aRR 1.09-1.21), essential shops (aRR 1.09-1.13) and non-household contacts (aRR 1.15-1.19) across multiple survey periods.\n\nConclusionDifferential exposure to essential public activities in deprived communities is likely to contribute to inequalities in infection risk and outcomes during the COVID-19 pandemic. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities.",
-    "category": "epidemiology",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.04.24.21255968",
@@ -5179,6 +5235,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.03.21.21254061",
+    "date": "2021-03-26",
+    "link": "https://medrxiv.org/cgi/content/short/2021.03.21.21254061",
+    "title": "Quantitative SARS-CoV-2 anti-spike responses to Pfizer-BioNTech and Oxford-AstraZeneca vaccines by previous infection status",
+    "authors": "David W Eyre; Sheila F Lumley; Jia Wei; Stuart Cox; Tim James; Anita Justice; Gerald Jesuthasan; Alison Howarth; Stephanie B Hatch; Brian D Marsden; E Yvonne Jones; David I Stuart; Daniel Ebner; Sarah Hoosdally; Derrick Crook; Tim EA Peto; Timothy M Walker; Nicole EA Stoesser; Philippa C Matthews; Koen B Pouwels; A Sarah Walker; Katie Jeffery",
+    "affiliations": "University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals",
+    "abstract": "ObjectivesWe investigate determinants of SARS-CoV-2 anti-spike IgG responses in healthcare workers (HCWs) following one or two doses of Pfizer-BioNTech or Oxford-AstraZeneca vaccines.\n\nMethodsHCWs participating in regular SARS-CoV-2 PCR and antibody testing were invited for serological testing prior to first and second vaccination, and 4 weeks post-vaccination if receiving a 12-week dosing interval. Quantitative post-vaccination anti-spike antibody responses were measured using the Abbott SARS-CoV-2 IgG II Quant assay (detection threshold: [&ge;]50 AU/ml). We used multivariable logistic regression to identify predictors of seropositivity and generalised additive models to track antibody responses over time.\n\nResultsVaccine uptake was 80%, but less in lower-paid roles and Black, south Asian and minority ethnic groups. 3570/3610(98.9%) HCWs were seropositive >14 days post-first vaccination and prior to second vaccination, 2706/2720(99.5%) after Pfizer-BioNTech and 864/890(97.1%) following Oxford-AstraZeneca vaccines. Previously infected and younger HCWs were more likely to test seropositive post-first vaccination, with no evidence of differences by sex or ethnicity. All 470 HCWs tested >14 days after second vaccine were seropositive. Quantitative antibody responses were higher after previous infection: median(IQR) >21 days post-first Pfizer-BioNTech 14,604(7644-22,291) AU/ml vs. 1028(564-1985) AU/ml without prior infection (p<0.001). Oxford-AstraZeneca vaccine recipients had lower readings post-first dose compared to Pfizer-BioNTech, with and without previous infection, 10,095(5354-17,096) and 435(203-962) AU/ml respectively (both p<0.001 vs. Pfizer-BioNTech). Antibody responses post-second vaccination were similar to those after prior infection and one vaccine dose.\n\nConclusionsVaccination leads to detectable anti-spike antibodies in nearly all adult HCWs. Whether differences in response impact vaccine efficacy needs further study.",
+    "category": "infectious diseases",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.03.21.21253968",
@@ -5445,20 +5515,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.03.12.21253484",
-    "date": "2021-03-13",
-    "link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253484",
-    "title": "Limits of lockdown: characterising essential contacts during strict physical distancing",
-    "authors": "Amy C Thomas; Leon Danon; Hannah Christensen; Kate Northstone; Daniel Smith; Emily J Nixon; Adam Trickey; Gibran Hemani; Sarah Sauchelli; Adam Finn; Nicholas J Timpson; Ellen Brooks-Pollock",
-    "affiliations": "University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Bristol; NIHR Bristol Biomedical Research Centre, University of Bristol; University of Bristol; University of Bristol; University of Bristol",
-    "abstract": "COVID-19 has exposed health inequalities within countries and globally. The fundamental determining factor behind an individuals risk of infection is the number of social contacts they make. In many countries, physical distancing measures have been implemented to control transmission of SARS-CoV-2, reducing social contacts to a minimum. Characterising unavoidable social contacts is key for understanding the inequalities behind differential risks and planning vaccination programmes. We utilised an existing English longitudinal birth cohort, which is broadly representative of the wider population (n=6807), to explore social contact patterns and behaviours when strict physical distancing measures were in place during the UKs first lockdown in March-May 2020. Essential workers, specifically those in healthcare, had 4.5 times as many contacts as non-essential workers [incident rate ratio = 4.42 (CI95%: 3.88-5.04)], whilst essential workers in other sectors, mainly teaching and the police force had three times as many contacts [IRR = 2.84 (2.58-3.13)]. The number of individuals in a household, which is conflated by number of children, increases essential social contacts by 40%. Self-isolation effectively reduces numbers of contacts outside of the home, but not entirely. Together, these findings will aid the interpretation of epidemiological data and impact the design of effective SARS-CoV-2 control strategies, such as vaccination, testing and contact tracing.",
-    "category": "epidemiology",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.03.10.21253173",
@@ -5501,6 +5557,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.03.09.21253218",
+    "date": "2021-03-12",
+    "link": "https://medrxiv.org/cgi/content/short/2021.03.09.21253218",
+    "title": "An observational cohort study on the incidence of SARS-CoV-2 infection and B.1.1.7 variant infection in healthcare workers by antibody and vaccination status",
+    "authors": "Sheila F Lumley; Gillian Rodger; Bede Constantinides; Nicholas Sanderson; Kevin K Chau; Teresa L Street; Alison Howarth; Stephanie B Hatch; Brian D Marsden; Stuart Cox; Tim James; Fiona Warren; Liam J Peck; Thomas G Ritter; Zoe de Toledo; Laura Warren; David Axten; Richard J Cornall; E Yvonne Jones; David I Stuart; Gavin Screaton; Daniel Ebner; Sarah Hoosdally; Meera Chand; - Oxford University Hospitals Staff Testing Group; Derrick Crook; Christopher P Conlon; Koen B Pouwels; A Sarah Walker; Tim EA Peto; Susan Hopkins; Timothy M Walker; Nicole EA Stoesser; Philippa C Matthews; Katie Jeffery; David W Eyre",
+    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; Oxford University Hospitals; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Public Health England; ; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Public Health England; University of Oxford; University of Oxford; University of Oxford; Oxford University Hospitals; University of Oxford",
+    "abstract": "BackgroundNatural and vaccine-induced immunity will play a key role in controlling the SARS-CoV-2 pandemic. SARS-CoV-2 variants have the potential to evade natural and vaccine-induced immunity.\n\nMethodsIn a longitudinal cohort study of healthcare workers (HCWs) in Oxfordshire, UK, we investigated the protection from symptomatic and asymptomatic PCR-confirmed SARS-CoV-2 infection conferred by vaccination (Pfizer-BioNTech BNT162b2, Oxford-AstraZeneca ChAdOx1 nCOV-19) and prior infection (determined using anti-spike antibody status), using Poisson regression adjusted for age, sex, temporal changes in incidence and role. We estimated protection conferred after one versus two vaccinations and from infections with the B.1.1.7 variant identified using whole genome sequencing.\n\nResults13,109 HCWs participated; 8285 received the Pfizer-BioNTech vaccine (1407 two doses) and 2738 the Oxford-AstraZeneca vaccine (49 two doses). Compared to unvaccinated seronegative HCWs, natural immunity and two vaccination doses provided similar protection against symptomatic infection: no HCW vaccinated twice had symptomatic infection, and incidence was 98% lower in seropositive HCWs (adjusted incidence rate ratio 0.02 [95%CI <0.01-0.18]). Two vaccine doses or seropositivity reduced the incidence of any PCR-positive result with or without symptoms by 90% (0.10 [0.02-0.38]) and 85% (0.15 [0.08-0.26]) respectively. Single-dose vaccination reduced the incidence of symptomatic infection by 67% (0.33 [0.21-0.52]) and any PCR-positive result by 64% (0.36 [0.26-0.50]). There was no evidence of differences in immunity induced by natural infection and vaccination for infections with S-gene target failure and B.1.1.7.\n\nConclusionNatural infection resulting in detectable anti-spike antibodies and two vaccine doses both provide robust protection against SARS-CoV-2 infection, including against the B.1.1.7 variant.\n\nSummaryNatural infection resulting in detectable anti-spike antibodies and two vaccine doses both provided [&ge;] 85% protection against symptomatic and asymptomatic SARS-CoV-2 infection in healthcare workers, including against the B.1.1.7 variant. Single dose vaccination reduced symptomatic infection by 67%.",
+    "category": "infectious diseases",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.03.08.21253110",
@@ -5571,6 +5641,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2021.03.04.21252528",
+    "date": "2021-03-08",
+    "link": "https://medrxiv.org/cgi/content/short/2021.03.04.21252528",
+    "title": "Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England",
+    "authors": "Daniel J Grint; Kevin Wing; Elizabeth Williamson; Helen I McDonald; Krishnan Bhaskaran; David Evans; Stephen JW Evans; Alex J Walker; George Hickman; Emily Nightingale; Anna Schultze; Christopher T Rentsch; Chris Bates; Jonathan Cockburn; Helen J Curtis; Caroline E Morton; Sebastian Bacon; Simon Davy; Angel YS Wong; Amir Mehrkar; Laurie Tomlinson; Ian J Douglas; Rohini Mathur; Paula Blomquist; Brian MacKenna; Peter Ingelsby; Richard Croker; John Parry; Frank Hester; Sam Harper; Nicolas J DeVito; Will Hulme; John Tazare; Ben Goldacre; Liam Smeeth; Rosalind M Eggo",
+    "affiliations": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; COVID-19 Outbreak Surveillance Team, Public Health England, London, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK",
+    "abstract": "The B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (HR: 1.67 (95% CI: 1.34 - 2.09; P<.0001). Absolute risk of death by 28-days increased with age and comorbidities. VOC has potential to spread faster with higher mortality than the pandemic to date.",
+    "category": "infectious diseases",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.03.08.21253112",
@@ -5921,20 +6005,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2021.02.02.21251043",
-    "date": "2021-02-05",
-    "link": "https://medrxiv.org/cgi/content/short/2021.02.02.21251043",
-    "title": "COVID-19 infection and subsequent thromboembolism: A self-controlled case series analysis of a population cohort",
-    "authors": "Frederick Ho; Kenneth Man; Mark Toshner; Colin Church; Carlos Celis-Morales; Ian Wong; Colin Berry; Naveed Sattar; Jill Pell",
-    "affiliations": "University of Glasgow; UCL; University of Cambridge; NHS Greater Glasgow and Clyde; University of Glasgow; UCL; University of Glasgow; University of Glasgow; University of Glasgow",
-    "abstract": "ObjectiveAn unexpectedly large number of people infected with Covid-19 had experienced a thrombotic event. This study aims to assess the associations between Covid-19 infection and thromboembolism including myocardial infarction (MI), ischaemic stroke, deep-vein thrombosis (DVT), and pulmonary embolism (PE).\n\nPatients and MethodsA self-controlled case-series study was conducted covering the whole of Scotlands general population. The study population comprised individuals with confirmed (positive test) Covid-19 and at least one thromboembolic event between March 2018 and October 2020. Their incidence rates during the risk interval (5 days before to 56 days after the positive test) and the control interval (the remaining periods) were compared intra-personally.\n\nResultsAcross Scotland, 1,449 individuals tested positive for Covid-19 and experienced a thromboembolic event. The risk of thromboembolism was significantly elevated over the whole risk period but highest in the 7 days following the positive test (IRR 12.01, 95% CI 9.91-14.56) in all included individuals. The association was also present in individuals not originally hospitalised for Covid-19 (IRR 4.07, 95% CI 2.83-5.85). Risk of MI, stroke, PE and DVT were all significantly higher in the week following a positive test. The risk of PE and DVT was particularly high and remained significantly elevated even 56 days following the test.\n\nConclusionConfirmed Covid-19 infection was associated with early elevations in risk with MI, ischaemic stroke, and substantially stronger and prolonged elevations with DVT and PE both in hospital and community settings. Clinicians should consider thromboembolism, especially PE, among people with Covid-19 in the community.",
-    "category": "cardiovascular medicine",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.02.03.21251004",
@@ -6117,20 +6187,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "bioRxiv",
-    "doi": "10.1101/2021.01.25.428136",
-    "date": "2021-01-25",
-    "link": "https://biorxiv.org/cgi/content/short/2021.01.25.428136",
-    "title": "mRNA-1273 efficacy in a severe COVID-19 model: attenuated activation of pulmonary immune cells after challenge",
-    "authors": "Michelle Meyer; Yuan Wang; Darin Edwards; Gregory R Smith; Aliza B Rubenstein; Palaniappan Ramanathan; Chad E Mire; Colette Pietzsch; Xi Chen; Yongchao Ge; Wan Sze Cheng; Carole Henry; Angela Woods; LingZhi Ma; Guillaume B. E. Stewart-Jones; Kevin W Bock; Minai Mahnaz; Bianca M Nagata; Sivakumar Periasamy; Pei-Yong Shi; Barney S Graham; Ian N Moore; Irene Ramos; Olga G. Troyanskaya; Elena Zaslavsky; Andrea Carfi; Stuart C Sealfon; Alexander Bukreyev",
-    "affiliations": "University of Texas Medical Branch; Princeton University; Moderna Inc; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; University of Texas Medical Branch; University of Texas Medical Branch; University of Texas Medical Branch; Flatiron Institute, Simons Foundation; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Moderna Inc; Moderna Inc; Moderna Inc; Moderna Inc; National Institute of Health; National Institutes of Health; National Institutes of Health; University of Texas Medical Branch; University of Texas Medical Branch; National Institutes of Health; National Institutes of Health; Icahn School of Medicine at Mount Sinai; Princeton University; Icahn School of Medicine at Mount Sinai; Moderna Inc; Icahn School of Medicine at Mount Sinai; University of Texas Medical Branch at Galveston",
-    "abstract": "The mRNA-1273 vaccine was recently determined to be effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from interim Phase 3 results. Human studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Hamsters are the only model that reliably exhibit more severe SARS-CoV-2 disease similar to hospitalized patients, making them pertinent for vaccine evaluation. We demonstrate that prime or prime-boost administration of mRNA-1273 in hamsters elicited robust neutralizing antibodies, ameliorated weight loss, suppressed SARS-CoV-2 replication in the airways, and better protected against disease at the highest prime-boost dose. Unlike in mice and non-human primates, mRNA-1273- mediated immunity was non-sterilizing and coincided with an anamnestic response. Single-cell RNA sequencing of lung tissue permitted high resolution analysis which is not possible in vaccinated humans. mRNA-1273 prevented inflammatory cell infiltration and the reduction of lymphocyte proportions, but enabled antiviral responses conducive to lung homeostasis. Surprisingly, infection triggered transcriptome programs in some types of immune cells from vaccinated hamsters that were shared, albeit attenuated, with mock-vaccinated hamsters. Our results support the use of mRNA-1273 in a two-dose schedule and provides insight into the potential responses within the lungs of vaccinated humans who are exposed to SARS-CoV-2.",
-    "category": "immunology",
-    "match_type": "fuzzy",
-    "author_similarity": 96,
-    "affiliation_similarity": 94
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2021.01.21.20240887",
@@ -6467,6 +6523,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2020.12.10.20245944",
+    "date": "2020-12-14",
+    "link": "https://medrxiv.org/cgi/content/short/2020.12.10.20245944",
+    "title": "Azithromycin in Hospitalised Patients with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial",
+    "authors": "Peter W Horby; Alistair Roddick; Enti Spata; Natalie Staplin; Jonathan R Emberson; Guilherme Pessoa-Amorim; Leon Peto; Mark Campbell; Christopher Brightling; Ben Prudon; David Chadwick; Andrew Ustianowski; Abdul Ashish; Stacy Todd; Bryan Yates; Robert Buttery; Stephen Scott; Diego Maseda; J Kenneth Baillie; Maya H Buch; Lucy C Chappell; Jeremy N Day; Saul N Faust; Thomas Jaki; Katie Jeffery; Edmund Juszczak; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; Marion Mafham; Richard Haynes; Martin J Landray",
+    "affiliations": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom; Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom; North Manchester General Hospital & University of Manchester, Manchester, United Kingdom; Wrightington Wigan and Leigh NHS Foundation Trust, Wigan, United Kingdom; Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom; Northumbria Healthcare NHS Foundation Trust, North Tyneside, United Kingdom; North West Anglia NHS Foundation Trust, Peterborough, United Kingdom; The Countess of Chester Hospital NHS Foundation Trust, Chester, United Kingdom; Mid Cheshire Hospitals NHS Foundation Trust, Crewe, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; School of Life Sciences, King's College London, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; MRC Biostatistics Unit, University of Cambridge, Cambridge, United Ki; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United kingdom; Intensive Care National Audit & Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom",
+    "abstract": "BackgroundAzithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatory actions. We evaluated the efficacy and safety of azithromycin in hospitalised patients with COVID-19.\n\nMethodsIn this randomised, controlled, open-label, adaptive platform trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19 in the UK. Eligible and consenting patients were randomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once daily by mouth or intravenously for 10 days or until discharge (or one of the other treatment arms). Patients were twice as likely to be randomised to usual care as to any of the active treatment groups. The primary outcome was 28-day mortality. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 7 April and 27 November 2020, 2582 patients were randomly allocated to receive azithromycin and 5182 patients to receive usual care alone. Overall, 496 (19%) patients allocated to azithromycin and 997 (19%) patients allocated to usual care died within 28 days (rate ratio 1{middle dot}00; 95% confidence interval [CI] 0{middle dot}90-1{middle dot}12; p=0{middle dot}99). Consistent results were seen in all pre-specified subgroups of patients. There was no difference in duration of hospitalisation (median 12 days vs. 13 days) or the proportion of patients discharged from hospital alive within 28 days (60% vs. 59%; rate ratio 1{middle dot}03; 95% CI 0{middle dot}97-1{middle dot}10; p=0{middle dot}29). Among those not on invasive mechanical ventilation at baseline, there was no difference in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (21% vs. 22%; risk ratio 0{middle dot}97; 95% CI 0{middle dot}89-1{middle dot}07; p=0{middle dot}54).\n\nInterpretationIn patients hospitalised with COVID-19, azithromycin did not provide any clinical benefit. Azithromycin use in patients hospitalised with COVID-19 should be restricted to patients where there is a clear antimicrobial indication.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).",
+    "category": "infectious diseases",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.12.11.20247742",
@@ -6565,6 +6635,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2020.12.03.20243535",
+    "date": "2020-12-04",
+    "link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243535",
+    "title": "OpenSAFELY: impact of national guidance on switching from warfarin to direct oral anticoagulants (DOACs) in early phase of COVID-19 pandemic in England",
+    "authors": "Helen J Curtis; Brian MacKenna; Alex J Walker; Richard Croker; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Peter Inglesby; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan Bhaskaran; Anna Schultze; Christopher T Rentsch; Elizabeth Williamson; William Hulme; Helen I McDonald; Laurie Tomlinson; Rohini Mathur; Henry Drysdale; Rosalind M Eggo; Kevin Wing; Angel Wong; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Ian J Douglas; Liam Smeeth; Ben Goldacre",
+    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford",
+    "abstract": "BackgroundEarly in the COVID-19 pandemic the NHS recommended that appropriate patients anticoagulated with warfarin should be switched to direct acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately co-prescribed two anticoagulants following a medication change, and associated monitoring.\n\nObjectiveTo describe which people were switched from warfarin to DOACs; identify potentially unsafe co-prescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic.\n\nMethodsWorking on behalf of NHS England we conducted a population cohort based study using routine clinical data from >17 million adults in England.\n\nResults20,000 of 164,000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in co-prescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. INR testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420).\n\nConclusionsIncreased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people co-prescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.",
+    "category": "cardiovascular medicine",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.11.30.20240010",
@@ -6677,20 +6761,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.11.19.20234849",
-    "date": "2020-11-22",
-    "link": "https://medrxiv.org/cgi/content/short/2020.11.19.20234849",
-    "title": "Community factors and excess mortality in first wave of the COVID-19 pandemic.",
-    "authors": "Bethan Davies; Brandon L Parkes; James Bennett; Daniela Fecht; Marta Blangiardo; Majid Ezzati; Paul Elliott",
-    "affiliations": "Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London",
-    "abstract": "Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.",
-    "category": "epidemiology",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.11.18.20233932",
@@ -6719,20 +6789,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.11.18.20225029",
-    "date": "2020-11-20",
-    "link": "https://medrxiv.org/cgi/content/short/2020.11.18.20225029",
-    "title": "The Invasive Respiratory Infection Surveillance (IRIS) Initiative reveals significant reductions in invasive bacterial infections during the COVID-19 pandemic",
-    "authors": "Angela B Brueggemann; Melissa J Jansen van Rensburg; David Shaw; Noel D McCarthy; Keith A Jolley; Martin CJ Maiden; Mark PG van der Linden",
-    "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Warwick; University of Oxford; University of Oxford; University Hospital RWTH Aachen",
-    "abstract": "BackgroundStreptococcus pneumoniae, Haemophilus influenzae and Neisseria meningitidis are leading causes of invasive diseases including bacteraemic pneumonia and meningitis, and of secondary infections post-viral respiratory disease. They are typically transmitted via respiratory droplets. We investigated rates of invasive disease due to these pathogens during the early phase of the COVID-19 pandemic.\n\nMethodsLaboratories in 26 countries across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae and N meningitidis from 1 January 2018 to 31 May 2020. Weekly cases in 2020 vs 2018-2019 were compared. Streptococcus agalactiae data were collected from nine laboratories for comparison to a non-respiratory pathogen. The stringency of COVID-19 containment measures was quantified by the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed by Google COVID-19 Community Mobility Reports. Interrupted time series modelling quantified changes in rates of invasive disease in 2020 relative to when containment measures were imposed.\n\nFindingsAll countries experienced a significant, sustained reduction in invasive diseases due to S pneumoniae, H influenzae and N meningitidis, but not S agalactiae, in early 2020, which coincided with the introduction of COVID-19 containment measures in each country. Similar impacts were observed across most countries despite differing stringency in COVID-19 control policies. There was no evidence of a specific effect due to enforced school closures.\n\nInterpretationThe introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of these bacterial respiratory pathogens, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide.",
-    "category": "infectious diseases",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.11.18.20234369",
@@ -7027,20 +7083,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "bioRxiv",
-    "doi": "10.1101/2020.10.29.339317",
-    "date": "2020-10-30",
-    "link": "https://biorxiv.org/cgi/content/short/2020.10.29.339317",
-    "title": "COVID Moonshot: Open Science Discovery of SARS-CoV-2 Main Protease Inhibitors by Combining Crowdsourcing, High-Throughput Experiments, Computational Simulations, and Machine Learning",
-    "authors": "- The COVID Moonshot Consortium; Hagit Achdout; Anthony Aimon; Dominic S Alonzi; Robert Arbon; Elad Bar-David; Haim Barr; Amir Ben-Shmuel; James Bennett; Vitaliy A. Bilenko; Vitaliy A. Bilenko; Melissa L. Boby; Bruce Borden; Pascale Boulet; Gregory R. Bowman; Juliane Brun; Lennart Brwewitz; Sarma BVNBS; Mark Calmiano; Anna Carbery; Daniel Carney; Emma Cattermole; Edcon Chang; Eugene Chernyshenko; John D. Chodera; Austin Clyde; Joseph E. Coffland; Galit Cohen; Jason Cole; Alessandro Contini; Lisa Cox; Tristan Ian Croll; Milan Cvitkovic; Alex Dias; Kim Donckers; David L. Dotson; Alice Douangamath; Shirly Duberstein; Tim Dudgeon; Louise Dunnett; Peter K. Eastman; Noam Erez; Charles J. Eyermann; Mike Fairhead; Gwen Fate; Daren Fearon; Oleg Fedorov; Matteo Ferla; Rafaela S. Fernandes; Lori Ferrins; Mihajlo Filep; Richard Foster; Holly Foster; Laurent Fraisse; Ronen Gabizon; Adolfo Garcia-Sastre; Victor O. Gawriljuk; Paul Gehrtz; Carina Gileadi; Charline Giroud; William G. Glass; Robert Glen; Itai Glinert; Andre S. Godoy; Marian Gorichko; Tyler Gorrie-Stone; Ed J. Griffen; Sophie Hahn; Amna Haneef; Storm Hassell Hart; Jag Heer; Michael Henry; Michelle Hill; Sam Horrell; Qiu Yu Huang; Victor D. Huliak; Victor D. Huliak; Matthew F.D. Hurley; Tomer Israely; Andrew Jajack; Jitske Jansen; Eric Jnoff; Dirk Jochmans; Tobias John; Steven De Jonghe; Benjamin Kaminow; Lulu Kang; Anastassia L. Kantsadi; Peter W. Kenny; J. L. Kiappes; Serhii O. Kinakh; Serhii O. Kinakh; Lizbe Koekemoer; Boris Kovar; Tobias Krojer; Van La; Alpha A. Lee; Bruce A. Lefker; Haim Levy; Ivan G. Logvinenko; Ivan G. Logvinenko; Nir London; Petra Lukacik; Hannah Bruce Macdonald; Elizabeth M. MacLean; Laetitia L Makower; Tika R. Malla; Tatiana Matviiuk; Willam McCorkindale; Briana L. McGovern; Sharon Melamed; Kostiantyn P. Melnykov; Kostiantyn P. Melnykov; Oleg Michurin; Pascal Miesen; Halina Mikolajek; Bruce F. Milne; David Minh; Aaron Morris; Garrett M. Morris; Melody Jane Morwitzer; Demetri Moustakas; Charles Mowbray; Aline M. Nakamura; Jose Brandao Neto; Johan Neyts; Luong Nguyen; Gabriela D. Noske; Vladas Oleinikovas; Glaucius Oliva; Gijs J. Overheul; David Owen; Ruby Pai; Jin Pan; Nir Paran; Alexander Payne; Benjamin Perry; Maneesh Pingle; Jakir Pinjari; Boaz Politi; Ailsa Powell; Vladimir Psenak; Ivan Pulido; Reut Puni; Victor L. Rangel; Rambabu N. Reddi; Paul Rees; St Patrick Reid; Lauren Reid; Efrat Resnick; Emily Grace Ripka; Matthew C. Robinson; Ralph P. Robinson; Jaime Rodriguez-Guerra; Romel Rosales; Dominic A. Rufa; Kadi Saar; Kumar Singh Saikatendu; Eidarus Salah; David Schaller; Jenke Scheen; Celia A. Schiffer; Chris Schofield; Mikhail Shafeev; Aarif Shaikh; Ala M. Shaqra; Jiye Shi; Khriesto Shurrush; Sukrit Singh; Assa Sittner; Peter Sjo; Rachael Skyner; Adam Smalley; Bart Smeets; Mihaela D. Smilova; Leonardo J. Solmesky; John Spencer; Claire Strain-Damerell; Vishwanath Swamy; Hadas Tamir; Jenny C. Taylor; Rachael E. Tennant; Warren Thompson; Andrew Thompson; Susana Tomasio; Charlie Tomlinson; Igor S. Tsurupa; Igor S. Tsurupa; Anthony Tumber; Ioannis Vakonakis; Ronald P. van Rij; Laura Vangeel; Finny S. Varghese; Mariana Vaschetto; Einat B. Vitner; Vincent Voelz; Andrea Volkamer; Frank von Delft; Annette von Delft; Martin Walsh; Walter Ward; Charlie Weatherall; Shay Weiss; Kris M. White; Conor Francis Wild; Karolina D Witt; Matthew Wittmann; Nathan Wright; Yfat Yahalom-Ronen; Nese Kurt Yilmaz; Daniel Zaidmann; Ivy Zhang; Hadeer Zidane; Nicole Zitzmann; Sarah N Zvornicanin",
-    "affiliations": "; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; The Weizmann Institute of Science; Israel Institution of Biological Research; University of Oxford; Enamine Ltd; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Folding@home Consortium; DNDi; Washington University School of Medicine; University of Oxford; University of Oxford; Sai Life Sciences; UCB; University of Oxford;Diamond Light Source; Takeda Development Center Americas, Inc.; University of Oxford; Takeda Development Center Americas, Inc.; Enamine Ltd; Memorial Sloan Kettering Cancer Center; Argonne National Laboratory; N/A; The Weizmann Institute of Science; Cambridge Crystallographic Datacentre; University of Milan; Life Compass Consulting Ltd; Cambridge Institute for Medical Research, The University of Cambridge; PostEra Inc.; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; N/A; Diamond Light Source Ltd; Research Complex at Harwell; The Weizmann Institute of Science; Informatics Matters; Diamond Light Source Ltd; Research Complex at Harwell; Department of Bioengineering until Sept. 1, then Department of Chemistry; Israel Institution of Biological Research; Northeastern University; University of Oxford; Thames Pharma Partners; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; University of Oxford; University of Sao Paulo; Northeastern University; Weizmann Institute of Science; University of Leeds; University of Leeds; DNDi; The Weizmann Institute of Science; Icahn School of Medicine at Mount Sinai; University of Sao Paulo; The Weizmann Institute of Science; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Cambridge; Israel Institution of Biological Research; University of Sao Paulo; Taras Shevchenko National University of Kyiv; Diamond Light Source Ltd; Research Complex at Harwell; MedChemica Ltd; DNDi; Illinois Institute of Technology; University of Sussex; UCB; Memorial Sloan Kettering Cancer Center; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; University of Massachusetts Chan Medical School; Enamine Ltd; Enamine Ltd; Temple University; Israel Institution of Biological Research; PostEra Inc.; Radboud University Medical Center; UCB; Katholieke Universiteit Leuven; University of Oxford; Katholieke Universiteit Leuven; Memorial Sloan Kettering Cancer Center; Illinois Institute of Technology; University of Oxford; Independent Scientist; University of Oxford; Enamine Ltd; Enamine Ltd; University of Oxford; M2M solutions, s.r.o; University of Oxford; Illinois Institute of Technology; PostEra Inc.; University of Cambridge; Thames Pharma Partners LLC; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; The Weizmann Institute of Science; Diamond Light Source Ltd; Research Complex at Harwell; Memorial Sloan Kettering Cancer Center; University of Oxford; University of Oxford; University of Oxford; Enamine Ltd; University of Cambridge; Icahn School of Medicine at Mount Sinai; Israel Institution of Biological Research; Enamine Ltd; Enamine Ltd; Enamine Ltd; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; University of Coimbra and University of Aberdeen; Illinois Institute of Technology; PostEra Inc; University of Oxford; Department of Pathology and Microbiology; Relay Therapeutics; DNDi; University of Sao Paulo; Diamond Light Source Ltd; Research Complex at Harwell; Katholieke Universiteit Leuven; PostEra Inc.; University of Sao Paulo; UCB; University of Sao Paulo; Radboud University Medical Center; Diamond Light Source Ltd; Research Complex at Harwell; PostEra Inc.; PostEra Inc.; Israel Institution of Biological Research; Memorial Sloan Kettering Cancer Center; DNDi; Sai Life Sciences; Sai Life Sciences; Israel Institution of Biological Research; Diamond Light Source Ltd; Research Complex at Harwell; M2M solutions, s.r.o; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; School of Pharmaceutical Sciences of Ribeirao Preto; The Weizmann Institute of Science; Compass Bussiness Partners Ltd; Department of Pathology and Microbiology; MedChemica Ltd; The Weizmann Institute of Science; PostEra Inc.; PostEra Inc.; Thames Pharma Partners LLC; Charite Universitatsmedizin Berlin; Icahn School of Medicine at Mount Sinai; Memorial Sloan Kettering Cancer Center; University of Cambridge; Takeda Development Center Americas, Inc.; University of Oxford; Charite Universitatsmedizin Berlin; Memorial Sloan Kettering Cancer Center; University of Massachusetts Chan Medical School; University of Oxford; Enamine Ltd; Sai Life Sciences; University of Massachusetts Chan Medical School; UCB; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; Israel Institution of Biological Research; DNDi; Diamond Light Source Ltd; Research Complex at Harwell; UCB; Radboud University Medical Center; University of Oxford; The Weizmann Institute of Science; University of Sussex; Diamond Light Source Ltd; Research Complex at Harwell; Sai Life Sciences; Israel Institution of Biological Research; University of Oxford; Lhasa Limited; Diamond Light Source Ltd; Research Complex at Harwell; University of Oxford; Collaborative Drug Discovery; Diamond Light Source Ltd; Research Complex at Harwell; Enamine Ltd; Enamine Ltd; University of Oxford; University of Oxford; Radboud University Medical Center; Katholieke Universiteit Leuven; Radboud University Medical Center; Collaborative Drug Discovery; Israel Institution of Biological Research; Temple University; Charite Universitatsmedizin Berlin; Diamond Light Source Ltd; University of Oxford; Research Complex at Harwell; University of Johannesburg; University of Oxford; Diamond Light Source Ltd; Research Complex at Harwell; Walter Ward Consultancy & Training; Collaborative Drug Discovery; Israel Institution of Biological Research; Icahn School of Medicine at Mount Sinai; University of Oxford; University of Oxford; Memorial Sloan Kettering Cancer Center; University of Oxford; Israel Institution of Biological Research; University of Massachusetts Chan Medical School; The Weizmann Institute of Science; Memorial Sloan Kettering Cancer Center; The Weizmann Institute of Science; University of Oxford; University of Massachusetts Chan Medical School",
-    "abstract": "The COVID-19 pandemic was a stark reminder that a barren global antiviral pipeline has grave humanitarian consequences. Pandemics could be prevented in principle by accessible, easily deployable broad-spectrum oral antivirals. Here we report the results of the COVID Moonshot, a fully open-science, crowd sourced, structure-enabled drug discovery campaign targeting the SARS-CoV-2 main protease. We discovered a novel chemical series that is differentiated from current Mpro inhibitors in that it maintains a new non-covalent, non-peptidic scaffold with nanomolar potency. Our approach leveraged crowdsourcing, high-throughput structural biology, machine learning, and exascale molecular simulations and high-throughput chemistry. In the process, we generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. In a first for a structure-based drug discovery campaign, all compound designs (>18,000 designs), crystallographic data (>840 ligand-bound X-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2,400 compounds) for this campaign were shared rapidly and openly, creating a rich open and IP-free knowledgebase for future anti-coronavirus drug discovery.",
-    "category": "biochemistry",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "bioRxiv",
     "doi": "10.1101/2020.10.26.356014",
@@ -7699,6 +7741,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2020.09.05.20188821",
+    "date": "2020-09-08",
+    "link": "https://medrxiv.org/cgi/content/short/2020.09.05.20188821",
+    "title": "Ethnicity and clinical outcomes in COVID-19A Systematic Review and Meta-analysis",
+    "authors": "Shirley Sze; Daniel Pan; Laura J Gray; Clareece R Nevill; Christopher A Martin; Joshua Nazareth; Jatinder S Minhas; Pip Divall; Kamlesh Khunti; Keith Abrams; Laura B Nellums; Manish Pareek",
+    "affiliations": "University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University Hospitals of Leicester NHS Trust; University of Leicester; University of Leicester; University of Nottingham; University of Leicester",
+    "abstract": "ImportanceThe association of ethnicity with outcomes in patients with COVID-19 is unclear.\n\nObjectiveTo determine whether the risk of SARS-CoV-2 infection, COVID-19 intensive care unit (ICU) admission and mortality are associated with ethnicity.\n\nData SourcesWe searched all English language articles published 1st December 2019 - 30th June 2020 within MEDLINE, EMBASE, PROSPERO and the Cochrane library using indexing terms for COVID-19 and ethnicity, as well as manuscripts awaiting peer review on MedRxiv during the same period.\n\nStudy SelectionIncluded studies reported original clinical data, disaggregated by ethnicity, on patients with confirmed or suspected COVID-19. We excluded correspondence, area level, modelling and basic science articles. Two independent reviewers screened articles for inclusion. Of 926 identified articles, 35 were included in the meta-analyses.\n\nData Extraction and SynthesisThe review was conducted according to PRISMA guidelines. Reviewers independently extracted data using a piloted form on: (1) rates of infection, ICU admission and mortality by ethnicity; and (2) unadjusted and adjusted data comparing ethnic minority and White groups. Data were pooled using random effects models.\n\nMain Outcomes and MeasuresOutcomes were: (1) infection with SARS-CoV-2 confirmed on molecular testing; (2) ICU admission; and (3) mortality in COVID-19 confirmed and suspected cases.\n\nResults13,535,562 patients from 35 studies were included in the meta-analyses. Black, Asian and Hispanic individuals had a greater risk of infection compared to White individuals (Black: pooled adjusted RR: 2.06, 95% CI: 1.59-2.67; Asian: 1.35, 95%CI: 1.15-1.59; Hispanic: 1.77, 95% CI: 1.39-2.25). Black individuals were significantly more likely to be admitted to ICU than White individuals (pooled adjusted RR: 1.61, 95% CI: 1.02-2.55). Risk of mortality was similar across ethnicities among hospitalised patients, but increased among Asian and Mixed ethnic groups in the general population.\n\nConclusionsBlack, Asian and Hispanic ethnic groups are at increased risk of SARS-CoV-2 infection. Black individuals may be more likely to require ICU admission for COVID-19. There may also be disparities in risk of death from COVID-19 at a population level. Our findings are of critical public health importance and should inform policy on minimising SARS-CoV-2 exposure in ethnic minority groups.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSIs ethnicity associated with vulnerability to, and outcomes from, coronavirus disease 2019 (COVID-19)?\n\nFindingsIn this systematic review and meta-analysis, rates of infection and outcomes from COVID-19 were compared between ethnic groups. Individuals from Black, Asian and Hispanic ethnicity were significantly more vulnerable to SARS-CoV-2 infection than those of White ethnicity. Black individuals were more likely to need intensive care unit (ICU) admission for COVID-19 than White individuals. Risk of mortality was similar across ethnicities among hospitalised patients, but increased among Asian and Mixed ethnic groups in the general population.\n\nMeaningThere is strong evidence for an increased risk of SARS-CoV-2 infection amongst ethnic minorities, and targeted public health policies are required to reduce this risk.",
+    "category": "infectious diseases",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.09.02.20185892",
@@ -7727,20 +7783,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.09.01.20185793",
-    "date": "2020-09-03",
-    "link": "https://medrxiv.org/cgi/content/short/2020.09.01.20185793",
-    "title": "Prognostic accuracy of emergency department triage tools for children with suspected COVID-19: The PRIEST observational cohort study",
-    "authors": "Katie Biggs; Ben Thomas; Steve Goodacre; Ellen Lee; Laura Sutton; Matthew Bursnall; Amanda Loban; Simon Waterhouse; Richard Simmonds; Carl Marincowitz; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter",
-    "affiliations": "University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust",
-    "abstract": "ObjectivesEmergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection.\n\nMethodsWe undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Childrens Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.\n\nResultsWe collected data from 1530 children, including 26 (1.7%) with an adverse outcome. C-statistics were 0.80 (95% confidence interval 0.73-0.87) for the WHO algorithm, 0.80 (0.71-0.90) for POPS, 0.76 (0.67-0.85) for COAST, and 0.71 (0.59-0.82) for SFHPC. Using pre-specified thresholds, the WHO algorithm had the highest sensitivity (0.85) and lowest specificity (0.75), but POPS and COAST could optimise sensitivity (0.96 and 0.92 respectively) at the expense of specificity (0.25 and 0.38 respectively) by using a threshold of any score above zero instead of the pre-specified threshold.\n\nConclusionExisting triage tools have good but not excellent prediction for adverse outcome in children with suspected COVID-19. POPS and COAST could achieve an appropriate balance of sensitivity and specificity for supporting decisions to discharge home by considering any score above zero to be positive.\n\nRegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",
-    "category": "emergency medicine",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.09.02.20186502",
@@ -7923,6 +7965,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2020.08.17.20175117",
+    "date": "2020-08-21",
+    "link": "https://medrxiv.org/cgi/content/short/2020.08.17.20175117",
+    "title": "Real-time spatial health surveillance: mapping the UK COVID-19 epidemic",
+    "authors": "Richard Fry; Joe Hollinghurst; Helen R Stagg; Daniel A Thompson; Claudio Fronterre; Chris Orton; Ronan A Lyons; David V Ford; Aziz Sheikh; Peter J Diggle",
+    "affiliations": "Swansea University; Swansea University; Edinburgh University; Swansea University; Lancaster University; Swansea University; Swansea University; Swansea University; Edinburgh University; Lancaster University",
+    "abstract": "The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. A pre-requisite to an effective control strategy is that predictions need to be accompanied by estimates of their precision, to guard against over-reaction to potentially spurious features of  best guess predictions. In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.",
+    "category": "public and global health",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.08.17.20161760",
@@ -8385,6 +8441,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "medRxiv",
+    "doi": "10.1101/2020.07.13.20152793",
+    "date": "2020-07-14",
+    "link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152793",
+    "title": "At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR based tests?: A systematic review of individual participant data",
+    "authors": "Sue Mallett; Joy Allen; Sara Graziadio; Stuart A Taylor; Naomi S Sakai; Kile Green; Jana Suklan; Chris Hyde; Bethany Shinkins; Zhivko Zhelev; Jaime Peters; Philip Turner; Nia W Roberts; Lavinia Ferrante di Ruffano; Robert Wolff; Penny Whiting; Amanda Winter; Gauraang Bhatnagar; Brian D Nicholson; Steve Halligan",
+    "affiliations": "University College London, UK; Newcastle University, UK; Newcastle upon Tyne Hospitals NHS Foundation Trust, UK; University College London, UK; University College London, UK; Newcastle University, UK; Newcastle University, UK; University of Exeter, UK; University of Leeds, UK; University of Exeter, UK; University of Exeter, UK; University of Oxford, UK; University of Oxford, UK; University of Birmingham, UK; Kleijnen Systematic Reviews Ltd, UK; University of Bristol, UK; Newcastle University, UK; Frimley Health NHS Foundation Trust, UK; University of Oxford, UK; University College London, UK",
+    "abstract": "STRUCTURED SUMMARYO_ST_ABSBackgroundC_ST_ABSTests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA), using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity.\n\nMethodsWe conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS- 2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites.\n\nFindingsOf 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from -6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 to 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post- symptom onset.\n\nInterpretationRT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond ten days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias so the positivity rates are probably overestimated.\n\nPANEL: RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThere are numerous reports of negative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcription polymerase chain reaction (RT-PCR) test results in participants with known SARS-CoV-2 infection, and increasing awareness that the ability of RT-PCR tests to detect virus depends on the timing of sample retrieval and anatomical sampling site.\n\nIndividual studies suggest that positive test results from RT-PCR with nasopharyngeal sampling declines within a week of symptoms and that a positive test later in the disease course is more likely from sputum, bronchoalveolar lavage (BAL) or stool, but data are inconsistent.\n\nAdded value of this studyWe searched 5078 titles and abstracts for longitudinal studies reporting individual participant data (IPD) for RT-PCR for participants with COVID-19 linked to either time since symptom onset or time since hospitalisation. Search included SARS-CoV-2 and RT-PCR keywords and MeSH terms. Each included study was subject to careful assessment of risk of bias. This IPD systematic review (SR) addresses RT-PCR test detection rates at different times since symptom onset and hospitalisation for different sampling sites, and summarises the duration of detectable virus. To our knowledge, this is the first rapid SR addressing this topic. We identified 32 studies available as published articles or pre-prints between January 1st and April 24th 2020, including participants sampled at 11 different sampling sites and some participants sampled at more than one site. At earlier time points, nasopharyngeal sampling had the highest virus detection, but the duration of shedding was shorter compared to lower respiratory tract sampling. At 10 to 14 days post-symptom onset, the percentage of positive nasopharyngeal test results was 54% compared to 89% at day 0 to 4. Presence and duration of faecal detection varied by participant, and in nearly half duration was shorter than respiratory sample detection. Virus detection varies for participants and can continue to be detected up to 46 days post-symptom onset or hospitalisation. The included studies were open to substantial risk of bias, so the detection rates are probably overestimates. There was also poor reporting of sampling methods and sparse data on sampling methods that are becoming more widely implemented, such as self-sampling and short nasal swab sampling (anterior nares/mid turbinate).\n\nImplications of all the available evidenceResults from this IPD SR of SARS-CoV-2 testing at different time points and using different anatomical sample sites are important to inform strategies of testing. For prevention of ongoing transmission of SARS-CoV-2, samples for RT-PCR testing need to be taken as soon as possible post-symptom onset, as we confirm that RT-PCR misses more people with infection if sampling is delayed. The percentage of positive RT-PCR tests is also highly dependent on the anatomical site sampled in infected people. Sampling at more than one anatomical site may be advisable as there is variation between individuals in the sites that are infected, as well as the timing of SARS-CoV-2 virus detection at an anatomical site. Testing ten days after symptom onset will lead to a higher frequency of negative tests, particularly if using only upper respiratory tract sampling. However, our estimates may considerably understate the frequency of negative RT-PCR results in people with SARS-CoV- 2 infection. Further investment in this IPD approach is recommended as the amount data available was small given the scale of the pandemic and the importance of the question. More studies, learning from our observations about risk of bias and strengths of example studies (Box 1, Box 2) are urgently needed to inform the optimal sampling strategy by including self-collected samples such as saliva and short nasal swabs. Better reporting of anatomical sampling sites with a detailed methodology on sample collection is also urgently needed.",
+    "category": "infectious diseases",
+    "match_type": "fuzzy",
+    "author_similarity": 92,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.07.13.20152710",
@@ -8847,20 +8917,6 @@
     "author_similarity": 100,
     "affiliation_similarity": 91
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.06.10.20127175",
-    "date": "2020-06-11",
-    "link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127175",
-    "title": "Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic.",
-    "authors": "Amitava Banerjee; Suliang Chen; Laura Pasea; Alvina Lai; Michail Katsoulis; Spiros Denaxas; Vahe Nafilyan; Bryan Williams; Wai Keong Wong; Ameet Bakhai; Kamlesh Khunti; Deenan Pillay; Mahdad Noursadeghi; Honghan Wu; Nilesh Pareek; Daniel Bromage; Theresa Mcdonagh; Jonathan Byrne; James T Teo; Ajay Shah; Ben Humberstone; Liang V Tang; Anoop SV Shah; Andrea Rubboli; Yutao Guo; Yu Hu; Cathie LM Sudlow; Gregory YH Lip; Harry Hemingway",
-    "affiliations": "University College London; University College London; University College London; University College London; UCL; University College London; Office for National Statistics; UCL; University College London Hospitals NHS Trust; Royal Free Hospitals NHS Trust; University of Leicester; UCL; UCL; UCL; King's College Hospital; Kings College London; Kings College London; Kings London NHS Trust; Kings College Hospital NHS Foundation Trust; King's College London; Office for National Statistics; Huazhong University of Science and Technology, Wuhan, China; University of Edinburgh; Ospedale S. Maria delle Croci, Ravenna, Italy; PLA General Hospital, Beijing, China.; Huazhong University of Science and Technology, Wuhan, China.; University of Edinburgh; University of Liverpool; UCL",
-    "abstract": "BackgroundCardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both \"direct\", through infection, and \"indirect\", through changes in healthcare.\n\nMethodsWe used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(\"direct\" effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For \"indirect\" effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020.\n\nFindingsCVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths.\n\nInterpretationSupply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic.\n\nFundingNIHR, HDR UK, Astra Zeneca",
-    "category": "cardiovascular medicine",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "bioRxiv",
     "doi": "10.1101/2020.06.11.145920",
@@ -9225,20 +9281,6 @@
     "author_similarity": 94,
     "affiliation_similarity": 100
   },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.05.14.20101824",
-    "date": "2020-05-19",
-    "link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101824",
-    "title": "Changing travel patterns in China during the early stages of the COVID-19 pandemic",
-    "authors": "Hamish Gibbs; Yang Liu; Carl AB Pearson; Christopher I Jarvis; Chris Grundy; Billy J Quilty; Charlie Diamond; Rosalind M Eggo",
-    "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine",
-    "abstract": "Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigated the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020 and discussed their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower access to care. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and have not yet led to structural reorganisation of the transportation network at the time of this study.\n\nOne sentence summaryUnderstanding travel before, during, and after the introduction of travel restrictions in China in response to the COVID-19 Pandemic.",
-    "category": "public and global health",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
-  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.05.11.20098269",
@@ -9603,6 +9645,20 @@
     "author_similarity": 100,
     "affiliation_similarity": 100
   },
+  {
+    "site": "bioRxiv",
+    "doi": "10.1101/2020.04.28.066977",
+    "date": "2020-04-29",
+    "link": "https://biorxiv.org/cgi/content/short/2020.04.28.066977",
+    "title": "Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world",
+    "authors": "Jody Phelan; Wouter Deelder; Daniel Ward; Susana Campino; Martin L Hibberd; Taane G Clark",
+    "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine",
+    "abstract": "BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines.\n\nMethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure.\n\nResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades.\n\nConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.",
+    "category": "genomics",
+    "match_type": "fuzzy",
+    "author_similarity": 100,
+    "affiliation_similarity": 100
+  },
   {
     "site": "medRxiv",
     "doi": "10.1101/2020.04.23.20076521",
@@ -10036,19 +10092,5 @@
     "match_type": "fuzzy",
     "author_similarity": 100,
     "affiliation_similarity": 100
-  },
-  {
-    "site": "medRxiv",
-    "doi": "10.1101/2020.01.31.20019901",
-    "date": "2020-02-02",
-    "link": "https://medrxiv.org/cgi/content/short/2020.01.31.20019901",
-    "title": "Early dynamics of transmission and control of 2019-nCoV: a mathematical modelling study",
-    "authors": "Adam J Kucharski; Timothy W Russell; Charlie Diamond; Yang Liu; CMMID nCoV working group; John Edmunds; Sebastian Funk; Rosalind M Eggo",
-    "affiliations": "London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine",
-    "abstract": "BackgroundAn outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.\n\nMethodsWe combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas.\n\nFindingsWe estimated that the median daily reproduction number, Rt, declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.\n\nInterpretationOur results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually.\n\nFundingWellcome Trust (206250/Z/17/Z, 210758/Z/18/Z), HDR UK (MR/S003975/1), Gates Foundation (INV-003174), NIHR (16/137/109)",
-    "category": "infectious diseases",
-    "match_type": "fuzzy",
-    "author_similarity": 100,
-    "affiliation_similarity": 100
   }
 ]
\ No newline at end of file
diff --git a/data/covid/raw-preprints.json b/data/covid/raw-preprints.json
index dcb855d1..7fbc37bd 100644
--- a/data/covid/raw-preprints.json
+++ b/data/covid/raw-preprints.json
@@ -101,6 +101,45 @@
     "type": "new results",
     "category": "microbiology"
   },
+  {
+    "rel_doi": "10.1101/2023.09.04.556192",
+    "rel_title": "Correlation of myeloid-derived suppressor cell expansion with upregulated transposable elements in severe COVID-19 unveiled in single-cell RNA sequencing reanalysis",
+    "rel_date": "2023-09-05",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.04.556192",
+    "rel_abs": "Some studies investigated the potential role of transposable elements (TEs) in COVID-19 pathogenesis and complications. However, to the best of our knowledge, there is no study to examine the possible association of TEs expression in cell functions and its potential role in COVID-19 immune response at the single-cell level. In this study, we reanalyzed single-cell RNA seq data of bronchoalveolar lavage (BAL) samples obtained from six severe COVID-19 patients and three healthy donors to assess the probable correlation of TE expression with the immune responses induced by the SARS-CoV-2 virus in COVID-19 patients. Our findings indicated that the expansion of myeloid-derived suppressor cells (MDSCs (may be a characteristic feature of COVID-19. Additionally, a significant increase in TEs expression in MDSCs was observed. This upregulation of TEs in COVID-19 may be linked to the adaptability of these cells in response to their microenvironments. Furthermore, it appears that the identification of overexpressed TEs by Pattern recognition receptors (PRRs) in MDSCs may enhance the suppressive capacity of these cells. Thus, this study emphasizes the crucial role of TEs in the functionality of MDSCs during COVID-19.",
+    "rel_num_authors": 6,
+    "rel_authors": [
+      {
+        "author_name": "Mitra Farahmandnejad",
+        "author_inst": "Shiraz University of Medical Sciences"
+      },
+      {
+        "author_name": "Pouria Mosadeghi",
+        "author_inst": "Shiraz University of Medical Sciences"
+      },
+      {
+        "author_name": "Mohammadreza Dorvash",
+        "author_inst": "Monash University"
+      },
+      {
+        "author_name": "Amirhossein Sakhteman",
+        "author_inst": "Shiraz University of Medical Sciences"
+      },
+      {
+        "author_name": "Pouya Faridi",
+        "author_inst": "Monash University"
+      },
+      {
+        "author_name": "Manica Negahdaripour",
+        "author_inst": "Shiraz University of Medical Sciences"
+      }
+    ],
+    "version": "1",
+    "license": "cc_no",
+    "type": "new results",
+    "category": "systems biology"
+  },
   {
     "rel_doi": "10.1101/2023.08.28.555008",
     "rel_title": "Reference materials for SARS-CoV-2 molecular diagnostic: validation of encapsulated synthetic RNAs for room temperature storage and shipping",
@@ -837,7 +876,7 @@
     "rel_date": "2023-09-01",
     "rel_site": "bioRxiv",
     "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.01.555834",
-    "rel_abs": "An increasing number of reports suggest an association between COVID-19 infection and initiation or acceleration of neurodegenerative diseases including Alzheimer's disease (AD) and Creutzfeldt-Jakob disease (CJD). Both these diseases and several other neurodegenerative diseases are caused by conversion of human proteins into a misfolded, aggregated amyloid fibril state. The fibril formation process is self-perpetuating by seeded conversion from preformed fibril seeds. We recently described a plausible mechanism for amyloid fibril formation of SARS-CoV-2 spike protein. Spike-protein formed amyloid fibrils upon cleavage by neutrophil elastase, abundant in the inflammatory response to COVID-19 infection. We here provide evidence of significant Spike-amyloid fibril seeded acceleration of amyloid formation of CJD associated human prion protein (HuPrP) using an in vitro conversion assay. By seeding the HuPrP conversion assay with other in vitro generated disease associated amyloid fibrils we demonstrate that this is not a general effect but a specific feature of spike-amyloid fibrils. We also showed that the amyloid fibril formation of AD associated A{beta}1-42 was accelerated by Spike-amyloid fibril seeds. Of seven different 20-amino acid long peptides, Spike532 (532NLVKNKCVNFNFNGLTGTGV551) was most efficient in seeding HuPrP and Spike601 (601GTNTSNQVAVLYQDVNCTEV620) was most effective in seeding A{beta}1-42, suggesting substrate dependent selectivity of the cross-seeding activity. Albeit purely in vitro, our data suggest that cross-seeding by Spike-amyloid fibrils can be implicated in the increasing number of reports of CJD, AD, and possibly other neurodegenerative diseases in the wake of COVID-19.",
+    "rel_abs": "An increasing number of reports suggest an association between COVID-19 infection and initiation or acceleration of neurodegenerative diseases (NDs) including Alzheimers disease (AD) and Creutzfeldt-Jakob disease (CJD). Both these diseases and several other NDs are caused by conversion of human proteins into a misfolded, aggregated amyloid fibril state. The fibril formation process is self-perpetuating by seeded conversion from preformed fibril seeds. We recently described a plausible mechanism for amyloid fibril formation of SARS-CoV-2 spike protein. Spike-protein formed amyloid fibrils upon cleavage by neutrophil elastase, abundant in the inflammatory response to COVID-19 infection.\n\nWe here provide evidence of significant Spike-amyloid fibril seeded acceleration of amyloid formation of CJD associated human prion protein (HuPrP) using an in vitro conversion assay. By seeding the HuPrP conversion assay with other in vitro generated disease associated amyloid fibrils we demonstrate that this is not a general effect but a specific feature of spike-amyloid fibrils. We also showed that the amyloid fibril formation of AD associated A{beta}1-42 was accelerated by Spike-amyloid fibril seeds. Of seven different 20-amino acid long peptides, Spike532 (532NLVKNKCVNFNFNGLTGTGV551) was most efficient in seeding HuPrP and Spike601 (601GTNTSNQVAVLYQDVNCTEV620) was most effective in seeding A{beta}1-42, suggesting substrate dependent selectivity of the cross-seeding activity.\n\nAlbeit purely in vitro, our data suggest that cross-seeding by Spike-amyloid fibrils can be implicated in the increasing number of reports of CJD, AD, and possibly other NDs in the wake of COVID-19.",
     "rel_num_authors": 4,
     "rel_authors": [
       {
@@ -868,7 +907,7 @@
     "rel_date": "2023-09-01",
     "rel_site": "bioRxiv",
     "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.31.555800",
-    "rel_abs": "Coronaviridae are significant human pathogens, as evidenced by several outbreaks of severe respiratory infections in the past 20 years and culminating with the COVID-19 pandemic. Mouse models of COVID-19 have included transgenic expression of the main SARS coronavirus entry receptor on human cells, human angiotensin-convertase 2 (hACE2). However, the original hACE2-Tg mouse strain overexpresses many copies of the transgene, leading to neuropathology not representative of human infection. Aiming to improve physiological relevance, we generated two new lines of hACE2-Tg mice using the original transgene construct expressing hACE2 under the control of the keratin 18 promoter (K18-hACE2). We show that relative to the original strain, which expressed 8 copies of the transgene (8-hACE2-Tg), lines 1 and 2 expressed 1 and 2 copies of the transgene (1-hACE-2-Tg and 2-hACE-2-Tg, respectively). Upon intranasal (i.n.) infection with 103 plaque-forming units (pfu) SARS-CoV-2 WA-1/US, 8-hACE2-Tg mice succumbed to infection by d. 7. 2-hACE2-Tg mice exhibited 31% survival, with less viral replication in the lung and brain when compared to 8-hACE2-Tg mice. Furthermore, SARS-CoV-2 infection in 1-hACE2-Tg mice exhibited no mortality and had no detectable virus in the brain, although they did show clear virus replication in the lung. All three mouse strains analyzed showed SARS-CoV-2-related weight loss that tracked with the mortality rates. 1-hACE2-Tg mice mounted detectable primary and memory T effector cell and antibody responses. We conclude that these strains, particularly 1-hACE2-Tg mice, provide improved models to study hACE2-mediated viral infections.",
+    "rel_abs": "Coronaviridae are significant human pathogens, as evidenced by several outbreaks of severe respiratory infections in the past 20 years and culminating with the COVID-19 pandemic. Mouse models of COVID-19 have included transgenic expression of the main SARS coronavirus entry receptor on human cells, human angiotensin-converting enzyme 2 (hACE2). However, the original hACE2-Tg mouse strain overexpresses many copies of the transgene, leading to neuropathology not representative of human infection. Aiming to improve physiological relevance, we generated two new lines of hACE2-Tg mice using the original transgene construct expressing hACE2 under the control of the keratin 18 promoter (K18-hACE2).\n\nWe show that relative to the original strain, which expressed 8 copies of the transgene (8-hACE2-Tg), lines 1 and 2 expressed 1 and 2 copies of the transgene (1-hACE-2-Tg and 2-hACE-2-Tg, respectively). Upon intranasal (i.n.) infection with 103 plaque-forming units (pfu) SARS-CoV-2 WA-1/US, 8-hACE2-Tg mice succumbed to infection by d. 7. 2-hACE2-Tg mice exhibited 31% survival, with less viral replication in the lung and brain when compared to 8-hACE2-Tg mice. Furthermore, SARS-CoV-2 infection in 1-hACE2-Tg mice exhibited no mortality and had no detectable virus in the brain, although they did show clear virus replication in the lung. All three mouse strains analyzed showed SARS-CoV-2-related weight loss that tracked with the mortality rates. 1-hACE2-Tg mice mounted detectable primary and memory T effector cell and antibody responses. We conclude that these strains, particularly 1-hACE2-Tg mice, provide improved models to study hACE2-mediated viral infections.",
     "rel_num_authors": 8,
     "rel_authors": [
       {
@@ -1160,7 +1199,7 @@
     "rel_date": "2023-09-01",
     "rel_site": "bioRxiv",
     "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.31.555819",
-    "rel_abs": "EG.5.1 is a subvariant of the SARS-CoV-2 Omicron XBB variant that is rapidly increasing in prevalence worldwide. EG.5.1 has additional substitutions in its spike protein (namely, Q52H and F456L) compared with XBB.1.5. However, the pathogenicity, transmissibility, and immune evasion properties of clinical isolates of EG.5.1 are largely unknown. In this study, we used wild-type Syrian hamsters to investigate the replicative ability, pathogenicity, and transmissibility of a clinical EG.5.1 isolate. Our data show that there are no obvious differences in growth ability and pathogenicity between EG.5.1 and XBB.1.5, and both EG.5.1 and XBB.1.5 are attenuated compared to a Delta variant isolate. We also found that EG.5.1 is transmitted more efficiently between hamsters compared with XBB.1.5. In addition, unlike XBB.1.5, we detected EG.5.1 virus in the lungs of four of six exposed hamsters, suggesting that the virus tropism of EG.5.1 is different from that of XBB.1.5 after airborne transmission. Finally, we assessed the neutralizing ability of plasma from convalescent individuals and found that the neutralizing activity against EG.5.1 was slightly, but significantly, lower than that against XBB.1.5 or XBB.1.9.2. This suggests that EG.5.1 effectively evades humoral immunity and that the amino acid differences in the S protein of EG.5.1 compared with that of XBB.1.5 or XBB.1.9.2 (i.e., Q52H, R158G, and F456L) alter the antigenicity of EG.5.1. Our data suggest that the increased transmissibility and altered antigenicity of EG.5.1 may be driving its increasing prevalence over XBB.1.5 in the human population.",
+    "rel_abs": "EG.5.1 is a subvariant of the SARS-CoV-2 Omicron XBB variant that is rapidly increasing in prevalence worldwide. EG.5.1 has additional substitutions in its spike protein (namely, Q52H and F456L) compared with XBB.1.5. However, the pathogenicity, transmissibility, and immune evasion properties of clinical isolates of EG.5.1 are largely unknown.\n\nIn this study, we used wild-type Syrian hamsters to investigate the replicative ability, pathogenicity, and transmissibility of a clinical EG.5.1 isolate. Our data show that there are no obvious differences in growth ability and pathogenicity between EG.5.1 and XBB.1.5, and both EG.5.1 and XBB.1.5 are attenuated compared to a Delta variant isolate.\n\nWe also found that EG.5.1 is transmitted more efficiently between hamsters compared with XBB.1.5. In addition, unlike XBB.1.5, we detected EG.5.1 virus in the lungs of four of six exposed hamsters, suggesting that the virus tropism of EG.5.1 is different from that of XBB.1.5 after airborne transmission.\n\nFinally, we assessed the neutralizing ability of plasma from convalescent individuals and found that the neutralizing activity against EG.5.1 was slightly, but significantly, lower than that against XBB.1.5 or XBB.1.9.2. This suggests that EG.5.1 effectively evades humoral immunity and that the amino acid differences in the S protein of EG.5.1 compared with that of XBB.1.5 or XBB.1.9.2 (i.e., Q52H, R158G, and F456L) alter the antigenicity of EG.5.1.\n\nOur data suggest that the increased transmissibility and altered antigenicity of EG.5.1 may be driving its increasing prevalence over XBB.1.5 in the human population.",
     "rel_num_authors": 20,
     "rel_authors": [
       {
@@ -1329,7 +1368,7 @@
     "rel_date": "2023-09-01",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.28.23294675",
-    "rel_abs": "Background: Burnout is a phenomenon characterized as a consistent state of being exhausted physically, mentally, and emotionally. Grit, tolerance for ambiguity, religiosity, and social support are protective factors that may mitigate burnout and improve life satisfaction. This study assessed the association between specific protective resources of students from a medical school in Visayas at all year levels with online-based education-related burnout during the COVID-19 pandemic. Methods: A total of 234 medical students from a medical school in Visayas during the academic year 2020-2021 were sampled using stratified random sampling technique. Demographics were obtained. Specific protective resources of grit, religiosity, social support and tolerance for ambiguity, and burnout symptoms were measured using validated online questionnaires. Protective associations of specific resources on burnout levels were assessed using multivariate logistic regression analysis. Predictive capabilities of resources with statistically significant protective effects were summarized using Receiving Operating Characteristic (ROC) curve. Results: All year levels experienced burnout based on Maslach Burnout Inventory-Student Survey (MBI-SS) subscales, with PBL 2 having the highest incidence comprising 33 respondents (49%). Majority of the students experienced moderate burnout on emotional exhaustion (44%) and low burnout on depersonalization (58%), while all of them had high burnout levels on the subscale of personal accomplishment (100%). Most students were moderately gritty (91%) and had high tolerance for ambiguity (98%), overall religiosity index (82%), and social support from significant others (68%); family (68%); and friends (76%). Grit, religiosity and social support had positive significant correlations and reductive effects to burnout. Tolerance for ambiguity did not show any significant relationship with burnout. Grit, religiosity and social support are good predictors of burnout. Grit had good diagnostic accuracy and discrimination. Religiosity and social support were moderately accurate predictors of burnout. Conclusions: Grit, religiosity and social support are significantly protective on burnout levels of medical students from online-based education during the COVID-19 pandemic. Keywords: Burnout, grit, religiosity, social support, tolerance for ambiguity",
+    "rel_abs": "BackgroundBurnout is a phenomenon characterized as a consistent state of being exhausted physically, mentally, and emotionally. Grit, tolerance for ambiguity, religiosity, and social support are protective factors that may mitigate burnout and improve life satisfaction. This study assessed the association between specific protective resources of students from a medical school in Visayas at all year levels with online-based education-related burnout during the COVID-19 pandemic.\n\nMethodsA total of 234 medical students from a medical school in Visayas during the academic year 2020-2021 were sampled using stratified random sampling technique. Demographics were obtained. Specific protective resources of grit, religiosity, social support and tolerance for ambiguity, and burnout symptoms were measured using validated online questionnaires. Protective associations of specific resources on burnout levels were assessed using multivariate logistic regression analysis. Predictive capabilities of resources with statistically significant protective effects were summarized using Receiving Operating Characteristic (ROC) curve.\n\nResultsAll year levels experienced burnout based on Maslach Burnout Inventory-Student Survey (MBI-SS) subscales, with PBL 2 having the highest incidence comprising 33 respondents (49%). Majority of the students experienced moderate burnout on emotional exhaustion (44%) and low burnout on depersonalization (58%), while all of them had high burnout levels on the subscale of personal accomplishment (100%). Most students were moderately gritty (91%) and had high tolerance for ambiguity (98%), overall religiosity index (82%), and social support from significant others (68%); family (68%); and friends (76%). Grit, religiosity and social support had positive significant correlations and reductive effects to burnout. Tolerance for ambiguity did not show any significant relationship with burnout. Grit, religiosity and social support are good predictors of burnout. Grit had good diagnostic accuracy and discrimination. Religiosity and social support were moderately accurate predictors of burnout.\n\nConclusionsGrit, religiosity and social support are significantly protective on burnout levels of medical students from online-based education during the COVID-19 pandemic.",
     "rel_num_authors": 9,
     "rel_authors": [
       {
@@ -1380,7 +1419,7 @@
     "rel_date": "2023-09-01",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.29.23294764",
-    "rel_abs": "Background The COVID-19 pandemic negatively affected child and adolescent mental health and at the end of the pandemic (April 2022) child mental health had not returned to pre-pandemic levels. We investigated whether this observed increase in mental health problems has continued, halted, or reversed after the end of the pandemic in children from the general population and in children in psychiatric care. Methods We collected parent-reported and child-reported data at two additional post-pandemic time points (November/December 2022 and March/April 2023) in children (8-18 years) from two general population samples (N=818-1056 per measurement) and one clinical sample receiving psychiatric care (N=320-370) and compared these with data from before the pandemic. We collected parent-reported data on internalizing and externalizing problems with the Brief Problem Monitor (BPM) and self-reported data on Anxiety, Depressive symptoms, Sleep-related impairments, Anger, Global health, and Peer relations with the Patient-Reported Outcomes Measurement Information System (PROMIS). Results In the general population, parents reported no changes in externalizing problems but did report higher internalizing problems post-pandemic than pre-pandemic. Children also reported increased mental health problems post-pandemic, especially in anxiety and depression, to a lesser extent in sleep-related impairment and global health, and least in anger. In the clinical sample, parents reported higher internalizing, but not externalizing problems post-pandemic compared to the start of the pandemic. Children reported greatest increases in problems in anxiety, depression, and global health, to a lesser extent on sleep-related impairment, and least on anger. Conclusions Child mental health problems in the general population are substantially higher post-pandemic compared to pre-pandemic measurements. In children in psychiatric care mental health problems have increased during the pandemic and are substantially higher post-pandemic than at the start of the pandemic. Longitudinal and comparative studies are needed to assess what the most important drivers of these changes are.",
+    "rel_abs": "BackgroundThe COVID-19 pandemic negatively affected child and adolescent mental health and at the end of the pandemic (April 2022) child mental health had not returned to pre-pandemic levels. We investigated whether this observed increase in mental health problems has continued, halted, or reversed after the end of the pandemic in children from the general population and in children in psychiatric care.\n\nMethodsWe collected parent-reported and child-reported data at two additional post-pandemic time points (November/December 2022 and March/April 2023) in children (8-18 years) from two general population samples (N=818-1056 per measurement) and one clinical sample receiving psychiatric care (N=320-370) and compared these with data from before the pandemic. We collected parent-reported data on internalizing and externalizing problems with the Brief Problem Monitor (BPM) and self-reported data on Anxiety, Depressive symptoms, Sleep-related impairments, Anger, Global health, and Peer relations with the Patient-Reported Outcomes Measurement Information System (PROMIS(R)).\n\nResultsIn the general population, parents reported no changes in externalizing problems but did report higher internalizing problems post-pandemic than pre-pandemic. Children also reported increased mental health problems post-pandemic, especially in anxiety and depression, to a lesser extent in sleep-related impairment and global health, and least in anger. In the clinical sample, parents reported higher internalizing, but not externalizing problems post-pandemic compared to the start of the pandemic. Children reported greatest increases in problems in anxiety, depression, and global health, to a lesser extent on sleep-related impairment, and least on anger.\n\nConclusionsChild mental health problems in the general population are substantially higher post-pandemic compared to pre-pandemic measurements. In children in psychiatric care mental health problems have increased during the pandemic and are substantially higher post-pandemic than at the start of the pandemic. Longitudinal and comparative studies are needed to assess what the most important drivers of these changes are.",
     "rel_num_authors": 27,
     "rel_authors": [
       {
@@ -1503,7 +1542,7 @@
     "rel_date": "2023-09-01",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.30.23294831",
-    "rel_abs": "The main objective of this study is to analyse the clinical efficacy of medium-term telerehabilitation in the recovery of patients with Long COVID using ReCOVery APP, administered in the Primary Health Care (PHC) setting. The second objective is to identify significant patterns associated with an improvement in their quality of life predicted by other study variables. To this end, a randomised clinical trial was conducted with two parallel groups of a total of 100 patients with Long COVID. The control group continued with their usual treatment (TAU), established by their primary care physician. The intervention group, in addition to continuing with their TAU, attended three sessions based on motivational methodology and used ReCOVery APP for six months. The main variable was quality of life. The results of this study concluded that ReCOVery APP was not significantly more effective in improving the quality of life of patients with Long COVID. There was low adherence of participants. However, linear regression analyses revealed significant patterns of improvement in overall quality of life and mental health predicted by time of use of the APP and the personal construct of self-efficacy. In addition, all participants significantly improved their physical and mental health over the duration of the intervention. In conclusion, meaningful use of the ReCOVery APP may contribute to improving the quality of life of patients with Long COVID, but strategies to improve adherence need to be encouraged.",
+    "rel_abs": "The main objective of this study is to analyse the clinical efficacy of medium-term telerehabilitation in the recovery of patients with Long COVID using ReCOVery APP, administered in the Primary Health Care (PHC) setting. The second objective is to identify significant patterns associated with an improvement in their quality of life predicted by other study variables. To this end, a randomised clinical trial was conducted with two parallel groups of a total of 100 patients with Long COVID. The control group continued with their usual treatment (TAU), established by their primary care physician. The intervention group, in addition to continuing with their TAU, attended three sessions based on motivational methodology and used ReCOVery APP for six months. The main variable was quality of life. The results of this study concluded that ReCOVery APP was not significantly more effective in improving the quality of life of patients with Long COVID. There was low adherence of participants. However, linear regression analyses revealed significant patterns of improvement in overall quality of life and mental health predicted by time of use of the APP and the personal construct of self-efficacy. In addition, all participants significantly improved their physical and mental health over the duration of the intervention. In conclusion, meaningful use of the ReCOVery APP may contribute to improving the quality of life of patients with Long COVID, but strategies to improve adherence need to be encouraged.\n\nTrial Registration NoISRCTN91104012.",
     "rel_num_authors": 6,
     "rel_authors": [
       {
@@ -1593,7 +1632,7 @@
     "rel_date": "2023-09-01",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.30.23294821",
-    "rel_abs": "Background: Some individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration. Methods Survival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([&ge;]8 weeks, 906 [67.1%] with illness [&ge;]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms. Findings: Individuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly. Interpretation: Individuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.",
+    "rel_abs": "BackgroundSome individuals experience prolonged illness after acute COVID-19. We assessed whether pre-infection symptoms affected post-COVID illness duration.\n\nMethodsSurvival analysis was performed in adults (n=23,452) with community-managed SARC-CoV-2 infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence vs. absence of baseline symptoms (4-8 weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness ([&ge;]8 weeks, 906 [67.1%] with illness [&ge;]12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups; and against post-COVID symptoms.\n\nFindingsIndividuals reporting baseline symptoms had longer post-COVID symptom duration (from 10 to 15 days) with baseline fatigue nearly doubling duration. Two-thirds (910 of 1350 [67.4%]) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, vs. 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms increased the odds ratio for long illness (2.14 [CI: 1.78; 2.57]). Prior comorbidities were more common in individuals with long vs. short illness. In individuals with long illness, baseline symptomatic (vs. asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms and symptom burden correlated strongly.\n\nInterpretationIndividuals experiencing symptoms before COVID-19 have longer illness duration and increased odds of long illness. However, many individuals with long illness are well before SARS-CoV-2 infection.",
     "rel_num_authors": 17,
     "rel_authors": [
       {
@@ -1671,69 +1710,21 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.08.29.23294793",
-    "rel_title": "Can long-term COVID-19 vaccination be improved by serological surveillance?: a modeling study for Mozambique",
+    "rel_doi": "10.1101/2023.08.29.23294791",
+    "rel_title": "How will COVID-19 persist in the future? Simulating future dynamics of COVID-19 using an agent-based network model",
     "rel_date": "2023-09-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.29.23294793",
-    "rel_abs": "Seroprevalence provides an estimate of the population-level susceptibility to infection. In this study, we used a transmission model to examine the potential of using serological surveillance to inform the timing of COVID-19 boosters in Mozambique. We simulated using population-level seroprevalence thresholds as an estimate of the risk of outbreaks to trigger the timing of re-vaccination campaigns among older adults. We compare this approach to a strategy of re-vaccination at fixed time intervals. Vaccinating older adults each time the seroprevalence among older adults falls below 50% and 80% resulted in medians of 20% and 71% reduction in deaths, respectively, and number-needed-to-vaccinate to avert one death (NNT) of 1,499 (2.5th-97.5th centile:1,252-1,905) and 3,151 (2,943-3,429), respectively. In comparison, biennial and annual re-vaccination of older adults resulted in medians of 35% and 52% deaths averted, respectively, and NNTs of 1,443 (1,223-1,733) and 1,941 (1,805-2,112), respectively. We conducted sensitivity analysis over a range of antibody waning rates and epidemic scenarios and found that re-vaccination trigger thresholds of 50-60% seroprevalence are most likely to be efficient compared to fixed-time strategies. However, given marginal gains in efficiency even in the best-case scenarios, our results favor the use of simpler fixed-time strategies for long-term control of SARS-CoV-2.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.29.23294791",
+    "rel_abs": "Despite the United States Center for Disease Control (CDC)s May 2023 expiration of the declared public health emergency pertaining to the COVID-19 pandemic (Silk 2023), approximately 3 years after the first cases of SARS-CoV-2 appeared in the United Sates, thousands of new cases persist daily. Many questions persist about the future dynamics of SARS-CoV-2s in the United States, including: will COVID continue to circulate as a seasonal disease like influenza, and will annual vaccinations be required to prevent outbreaks? In response, we present an Agent Based Networked Simulation of COVID-19 transmission to evaluate recurrent future outbreaks of the disease, accounting for contact heterogeneity and waning vaccine-derived and natural immunity. Our model is parameterized with data collected as part of the Berkeley Interpersonal Contact Survey (BICS; Feehan and Mahmud 2021) and is used to simulate time series of confirmed cases of and deaths due to SARS-CoV-2, paying special attention to seasonal forces and waning immunity (Kronfeld-Schor et al. 2021; X. Liu et al. 2021; Nichols et al. 2021). From the BICS ABM model we simulate SARS-CoV-2 dynamics over the 10-year period beginning in 2021 with waning immunity and inclusion of annual booster doses under a variety of transmission scenarios. We find that SARS-CoV-2 outbreaks are likely to occur frequently, and that distribution of booster doses during certain times of the year--notably in the late winter/early spring--may reduce the severity of a wintertime outbreak depending on the seasonal epidemiology of the pathogen.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Carol Y Liu",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Kayoko Shioda",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Alicia Kraay",
-        "author_inst": "University of Illinois Urbana-Champaign"
-      },
-      {
-        "author_name": "Sergio Massora",
-        "author_inst": "Centro de Investigacao em Saude de Manhica (CISM)"
-      },
-      {
-        "author_name": "Auria de Jesus",
-        "author_inst": "Centro de Investigacao em Saude de Manhica (CISM)"
-      },
-      {
-        "author_name": "Arsenia Massinga",
-        "author_inst": "Centro de Investigacao em Saude de Manhica (CISM)"
-      },
-      {
-        "author_name": "Celso Monjane",
-        "author_inst": "Mozambique Instituto Nacional de Saude"
-      },
-      {
-        "author_name": "Saad B Omer",
-        "author_inst": "Yale University School of Medicine"
-      },
-      {
-        "author_name": "Samuel M Jenness",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Kristin Nelson",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Stefan Y Flasche",
-        "author_inst": "LSHTM"
-      },
-      {
-        "author_name": "Inacio Mandomando",
-        "author_inst": "Centro de Investigacao em Saude de Manhica (CISM)"
-      },
-      {
-        "author_name": "Benjamin A Lopman",
-        "author_inst": "Emory University"
+        "author_name": "Ethan Roubenoff",
+        "author_inst": "University of California, Berkeley"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -3669,59 +3660,31 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2023.08.26.554935",
-    "rel_title": "Self-assembly vascularized human cardiac organoids model cardiac diseases in petri dishes and in mice",
+    "rel_doi": "10.1101/2023.08.26.23294658",
+    "rel_title": "Limited impact of lifting universal masks on SARS-COV-2 transmission in schools: The crucial role of outcome measurements",
     "rel_date": "2023-08-28",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.26.554935",
-    "rel_abs": "In this study, we generated self-assembly cardiac organoids (COs) from human pluripotent stem cells by dual-phase modulation of Wnt/{beta}-catenin pathway, utilizing CHIR99021 and IWR-1-endo. The resulting COs exhibited a diverse array of cardiac-specific cell lineages, cardiac cavity-like structures and demonstrated the capacity of spontaneous beating and vascularization in vitro. We further employed these complex and functional COs to replicate conditions akin to human myocardial infarction and SARS-CoV-2 induced fibrosis. These models accurately captured the pathological characteristics of these diseases, in both in vitro and in vivo settings. In addition, we transplanted the COs into NOD SCID mice and observed that they survived and exhibited ongoing expansion in vivo. Impressively, over a span of 75-day transplantation, these COs not only established blood vessel-like structures but also integrated with the host mices vascular system. It is noteworthy that these COs developed to a size of approximately 8 mm in diameter, slightly surpassing the dimensions of the mouse heart. This innovative research highlighted the potential of our COs as a promising avenue for cardiovascular research and therapeutic exploration.",
-    "rel_num_authors": 10,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.26.23294658",
+    "rel_abs": "As the pandemics dynamics changed, many municipalities lifted face wearing requirement in school which was initially implemented to mitigate the transmission of COVID-19. This study examines the effects of lifting mask mandates on COVID-19 transmission within Massachusetts school districts. We first replicated previous research by Cowger et al. (2022) utilizing a Difference-in-Difference (DID) model. Then, we back project the case infection and calculate the Rt value to redo the DID analysis. However, when shifting the outcome measurement to the reproductive number (Rt), our findings suggest that lifting mask mandates can only significantly influence the Rt first two weeks post-intervention. This implies that while mask mandate plays a role in mitigation, its lifting does not drastically influence COVID-19 transmissibility in the long term.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Qixing Zhong",
-        "author_inst": "West China Hospital, Sichuan University"
-      },
-      {
-        "author_name": "Yao He",
-        "author_inst": "Sichuan Junhui Biotechnology Co., Ltd."
-      },
-      {
-        "author_name": "Li Teng",
-        "author_inst": "Sichuan Junhui Biotechnology Co., Ltd."
-      },
-      {
-        "author_name": "Yinqian Zhang",
-        "author_inst": "West China Hospital, Sichuan University"
+        "author_name": "Mingwei Li",
+        "author_inst": "The University of Hong Kong; Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park"
       },
       {
-        "author_name": "Ting Zhang",
-        "author_inst": "West China Hospital, Sichuan University"
-      },
-      {
-        "author_name": "Yinbing Zhang",
-        "author_inst": "West China Hospital, Sichuan University"
-      },
-      {
-        "author_name": "Qinxi Li",
-        "author_inst": "Sichuan Junhui Biotechnology Co., Ltd."
-      },
-      {
-        "author_name": "Bangcheng Zhao",
-        "author_inst": "West China Hospital, Sichuan University"
-      },
-      {
-        "author_name": "Daojun Chen",
-        "author_inst": "Sichuan Junhui Biotechnology Co., Ltd."
+        "author_name": "Bingyi Yang",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Zhihui Zhong",
-        "author_inst": "West China Hospital, Sichuan University"
+        "author_name": "Benjamin J Cowling",
+        "author_inst": "The University of Hong Kong"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "cell biology"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.08.28.23294549",
@@ -5231,87 +5194,27 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2023.08.23.23293081",
-    "rel_title": "Pediatric and Adult Patients with ME/CFS following COVID-19: A Structured Approach to Diagnosis Using the Munich Berlin Symptom Questionnaire (MBSQ)",
+    "rel_doi": "10.1101/2023.08.23.23294470",
+    "rel_title": "Risk Factors for Post-Traumatic Stress Disorder (PTSD) in COVID Survivors A Cross-Sectional Study",
     "rel_date": "2023-08-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.23.23293081",
-    "rel_abs": "PurposeA subset of patients with post-COVID-19 condition (PCC) fulfill the clinical criteria of myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS). To establish the diagnosis of ME/CFS for clinical and research purposes, comprehensive scores have to be evaluated.\n\nMethodsWe developed the Munich Berlin Symptom Questionnaires (MBSQs) and supplementary scoring sheets (SSSs) to allow for a rapid evaluation of common ME/CFS case definitions. The MBSQs were applied to young patients with chronic fatigue and post-exertional malaise (PEM) who presented to the MRI Chronic Fatigue Center for Young People (MCFC). Trials were retrospectively registered (NCT05778006, NCT05638724).\n\nResultsUsing the MBSQs and SSSs, we report on ten patients aged 11 to 25 years diagnosed with ME/CFS after asymptomatic SARS-CoV-2 infection or mild to moderate COVID-19. Results from their MBSQs and from well-established patient-reported outcome measures indicated severe impairments of daily activities and health-related quality of life.\n\nConclusionsME/CFS can follow SARS-CoV-2 infection in patients younger than 18 years, rendering structured diagnostic approaches most relevant for pediatric PCC clinics. The MBSQs and SSSs represent novel diagnostic tools that can facilitate the diagnosis of ME/CFS in children, adolescents, and adults with PCC and other post-viral syndromes.\n\nWhat is knownME/CFS is a frequent debilitating illness. For diagnosis, an extensive differential diagnostic workup is required and the evaluation of clinical ME/CFS criteria. ME/CFS following COVID-19 has been reported in adults but not in pediatric patients younger than 19 years of age.\n\nWhat is newWe present novel questionnairs (MBSQs), as tools to assess common ME/CFS case definitions in pediatric and adult patients with post-COVID-19 condition and beyond. We report on ten patients aged 11 to 25 years diagnosed with ME/CFS following asymptomatic SARS-CoV-2 infection or mild to moderate COVID-19.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.23.23294470",
+    "rel_abs": "The study aimed to investigate the impact of demographic, socio-economic, health, and lifestyle variables on the development of PTSD symptoms in COVID survivors. The study used a cross-sectional design, and data were collected via a standard set of questionnaires from 228 COVID survivors, who required oxygen support and were admitted to Damak COVID hospital from April to October 2021.\n\nDescriptive statistics such as frequency and percentage were used to summarize the data and inferential statistics such as chi-square test, Fishers exact test, and Binary logistic regression were used to analyze the data and to infer the overall result from the taken sample. The study found that only three variables, i.e., gender, diabetes, and chronic obstructive pulmonary disorder (COPD), were significant factors that posed a higher threat of PTSD in COVID survivors. Additionally, the study uses model adequacy tests such as Pseudo R2 test, Reliability test and Hosmer and Lemeshow test to validate the model fitted.\n\nThe study found that only three variables had significant impact PTSD symptoms in COVID survivors. Male patients were more likely to have PTSD symptoms than female patients. The presence of diabetes before or after the infection increased the risk of PTSD. The patients with high blood pressure before COVID and those who developed chronic obstructive pulmonary disorder (COPD) after COVID were more likely to experience PTSD symptoms. The study provides valuable information on the risk factors for developing PTSD symptoms in COVID survivors. This study can contribute to the understanding and growing body of research on the psychological impact of COVID and help healthcare professionals identify patients who are at risk of developing PTSD and provide them with appropriate interventions to prevent or treat PTSD.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Laura C. Peo",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Katharina Wiehler",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Johannes Paulick",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Katrin Gerrer",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Ariane Leone",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Anja Viereck",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Matthias Haegele",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Silvia Stojanov",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Cordula Warlitz",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Silvia Augustin",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Martin Alberer",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Daniel R. B. Hattesohl",
-        "author_inst": "German Association for ME/CFS, Hamburg, Germany"
-      },
-      {
-        "author_name": "Laura Froehlich",
-        "author_inst": "Research Center CATALPA, FernUniversitaet in Hagen, Hagen, Germany"
-      },
-      {
-        "author_name": "Carmen Scheibenbogen",
-        "author_inst": "Charite Fatigue Center (CFC), Berlin, Germany"
-      },
-      {
-        "author_name": "Lorenz L Mihatsch",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Rafael Pricoco",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany"
+        "author_name": "Surakshaya Dhakal",
+        "author_inst": "Tribhuvan University"
       },
       {
-        "author_name": "Uta Behrends",
-        "author_inst": "MRI Chronic Fatigue Center for Young People (MCFC), Children's Hospital, TUM School of Medicine, Technical University of Munich, Munich, Germany; German Associa"
+        "author_name": "Ram  Prasad Khatiwada",
+        "author_inst": "Tribhuvan University Institute of Science and Technology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pediatrics"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2023.08.23.23294474",
@@ -7005,43 +6908,75 @@
     "category": "cell biology"
   },
   {
-    "rel_doi": "10.1101/2023.08.20.554012",
-    "rel_title": "Multi-cell type deconvolution using a probabilistic model for single-molecule DNA methylation haplotypes",
+    "rel_doi": "10.1101/2023.08.19.23294311",
+    "rel_title": "Seroepidemiology of COVID-19 in pregnant women and their infants in Uganda and Malawi across multiple waves 2020-2022",
     "rel_date": "2023-08-21",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.20.554012",
-    "rel_abs": "BackgroundDeconvolution is used to estimate the proportion of mixed cell types from tissue or blood samples based on genomic profiling. DNA methylation is commonly used because specific CpG positions reflect cell type identity and can be accurately measured at either the population or single-molecule level. Methylation sequencing techniques can profile multiple individual CpGs on a single DNA molecule, but few deconvolution models have been developed to exploit these single-molecule methylation haplotypes for cell type deconvolution.\n\nResults and ConclusionsWe used simulated whole-genome methylation data and in silico mixtures of real data to compare existing deconvolution tools with two new models developed here. We found that adapting an existing model CelFiE to incorporate methylation haplotype information improved deconvolution accuracy by [~]30% over other tools, including the original CelFiE. In addition to overall higher accuracy, our new tool CelFiE Integrated Single-molecule Haplotypes (or CelFiE-ISH) outperformed others in detecting rare cell types present at 0.1% and below. Detection of rare cell types is important for the analysis of circulating DNA, which we demonstrate using a patient-derived plasma sequencing dataset.Finally,we show that marker selection strategy has a strong effect on deconvolution accuracy, concluding that haplotype-aware deconvolution can take advantage of markers tailored for that purpose.",
-    "rel_num_authors": 6,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.19.23294311",
+    "rel_abs": "Data on SARS-CoV-2 infection in pregnancy and infancy has accumulated throughout the course of the pandemic. However, limited information is available from countries in sub-Saharan Africa (SSA). Evidence regarding asymptomatic SARS-CoV-2 infection and adverse birth outcomes are also scarce in these countries. The pregnant woman and infant COVID in Africa study (PeriCOVID Africa) is a South-South-North partnership involving hospitals and health centres in five countries: Malawi, Uganda, Mozambique, The Gambia, and Kenya. The study leveraged data from three ongoing prospective cohort studies: Preparing for Group B Streptococcal Vaccines (GBS PREPARE), SARS-CoV-2 infection and COVID-19 in women and their infants in Kampala and Mukono (COMAC) and Pregnancy Care Integrating Translational Science Everywhere (PRECISE). In this paper we describe the seroepidemiology of SARS-CoV-2 infection in pregnant women enrolled in sites in Uganda and Malawi, and the impact of SARS-CoV-2 infection on pregnancy and infant outcomes.\n\nThe PeriCOVID study is a prospective mother-infant cohort study that recruited pregnant women at any gestation antenatally or on the day of delivery. A nasopharyngeal swab was taken from mothers at enrolment for RT-PCR confirmation of SARS-CoV-2 infection, and maternal and cord blood samples were tested for SARS-CoV-2 antibodies using Wantai and Euroimmune ELISA. The primary outcome was seroprevalence of SARS-CoV-2 antibodies in maternal blood, reported as the proportion of seropositive women by study site and wave of COVID-19 within each country. Placental transfer of antibodies was described using the geometric mean ratio (GMR). We also estimated the proportion of asymptomatic or subclinical COVID-19 infections in pregnant women using serological testing and collected adverse pregnancy and infancy outcomes (e.g. still-birth, prematurity, maternal or infant death).\n\nIn total, 1379 women were enrolled, giving birth to 1387 infants. Overall, 63% of pregnant women had a SARS-CoV-2 positive serology. Over subsequent waves (delta and omicron), in the absence of vaccination, seropositivity rose from 20% to over 80%. The placental transfer GMR was 1.7, indicating active placental transfer of anti-spike IgG. There was no association between SARS-CoV-2 antibody positivity and adverse pregnancy or infancy outcomes. This study describes the increasing prevalence of SARS CoV-2 antibodies in pregnant woman in Uganda and Malawi across waves of SARS-CoV-2 infection. Our study adds to existing evidence that suggests under-reporting of infection if based solely on cases with clinical disease, or a positive RT-PCR for SARS-CoV-2, as most of the women in our study had asymptomatic infections and did not seek medical care. This has implications for screening in subsequent outbreaks and pandemics where protection of pregnant women and effect of infection in pregnancy on the infant are unknown.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Irene Unterman",
-        "author_inst": "Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, "
+        "author_name": "Lauren Hookham",
+        "author_inst": "St George's University of London"
       },
       {
-        "author_name": "Dana Avrahami",
-        "author_inst": "Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel"
+        "author_name": "Liberty Cantrell",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Efrat Katsman",
-        "author_inst": "Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, "
+        "author_name": "Stephen Cose",
+        "author_inst": "London School of Hygiene & Tropical Medicine Centre of Global Change and Health: London School of Hygiene & Tropical Medicine"
       },
       {
-        "author_name": "Timothy J Triche Jr.",
-        "author_inst": "Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI, USA"
+        "author_name": "Bridget Freyne",
+        "author_inst": "Malawi-Liverpool-Wellcome Trust Clinical Research Programme"
       },
       {
-        "author_name": "Benjamin Glaser",
-        "author_inst": "Department of Endocrinology and Metabolism, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel"
+        "author_name": "Luis Gadama",
+        "author_inst": "Kamuzu University of Health Sciences: University of Malawi College of Medicine"
+      },
+      {
+        "author_name": "Esther Imede",
+        "author_inst": "MRC/UVRI Uganda Research Unit On AIDS: MRC/UVRI and LSHTM Uganda Research Unit"
+      },
+      {
+        "author_name": "Kondwani Kawaza",
+        "author_inst": "Kamuzu University of Health Sciences: University of Malawi College of Medicine"
+      },
+      {
+        "author_name": "Sam Lissauer",
+        "author_inst": "Malawi-Liverpool-Wellcome Trust Clinical Research Programme"
+      },
+      {
+        "author_name": "Phillipa Musoke",
+        "author_inst": "Makerere University"
+      },
+      {
+        "author_name": "Victoria Nankabirwa",
+        "author_inst": "Makerere University"
+      },
+      {
+        "author_name": "Musa Sekikubo",
+        "author_inst": "Makerere University"
+      },
+      {
+        "author_name": "Halvor Sommerfelt",
+        "author_inst": "University of Bergen: Universitetet i Bergen"
+      },
+      {
+        "author_name": "Merryn Voysey",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Benjamin P Berman",
-        "author_inst": "Department of Developmental Biology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, "
+        "author_name": "Kirsty Le Doare",
+        "author_inst": "St George's University"
       }
     ],
     "version": "1",
     "license": "cc_by",
-    "type": "new results",
-    "category": "bioinformatics"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.08.18.23293746",
@@ -7953,7 +7888,7 @@
     "rel_date": "2023-08-16",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.14.23293945",
-    "rel_abs": "During the COVID-19 pandemic, many countries have investigated the potential usefulness of wastewater-based epidemiology as an early warning system. Initially, methods were created to detect the presence of SARS-CoV-2 RNA in wastewater. Researchers have since conducted extensive studies to examine the link between viral concentration in wastewater and COVID-19 cases in areas served by sewage treatment plants over time. However, only a few reports have attempted to create predictive models for hospitalizations based on SARS-CoV-2 RNA concentrations in wastewater. This study implemented a linear mixed-effects model that connects the levels of virus in wastewater (WW) to hospitalizations. The model was then utilized to predict short-term trends in 21 counties in California, based on data from March 14, 2022, to May 21, 2023. The modeling framework proposed here permits repeated measurements as well as fixed and random effects. The mathematical model that utilized wastewater data showed strong performance and successfully identified trends in hospitalizations. Additionally, the proposed model allows for predicting SARS-CoV-2 hospitalizations two weeks ahead, which is critical for optimizing hospital resource allocation.",
+    "rel_abs": "During the COVID-19 pandemic, many countries and regions investigated the potential use of wastewater-based disease surveillance as an early warning system. Initially, methods were created to detect the presence of SARS-CoV-2 RNA in wastewater. Investigators have since conducted extensive studies to examine the link between viral concentration in wastewater and COVID-19 cases in areas served by sewage treatment plants over time. However, only a few reports have attempted to create predictive models for hospitalizations at county-level based on SARS-CoV-2 RNA concentrations in wastewater. This study implemented a linear mixed-effects model that observes the association between levels of virus in wastewater and county-level hospitalizations. The model was then utilized to predict short-term county-level hospitalization trends in 21 counties in California based on data from March 21, 2022, to May 21, 2023. The modeling framework proposed here permits repeated measurements as well as fixed and random effects. The model that assumed wastewater data as an input variable, instead of cases or test positivity rate, showed strong performance and successfully captured trends in hospitalizations. Additionally, the model allows for the prediction of SARS-CoV-2 hospitalizations two weeks ahead. Forecasts of COVID-19 hospitalizations could provide crucial information for hospitals to better allocate resources and prepare for potential surges in patient numbers.",
     "rel_num_authors": 6,
     "rel_authors": [
       {
@@ -8659,25 +8594,25 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2023.08.10.23293925",
-    "rel_title": "Effect of vaccination certification with mass vaccination and non-pharmaceutical interventions on mitigating COVID-19",
+    "rel_doi": "10.1101/2023.08.10.23293942",
+    "rel_title": "A Susceptible Vaccinated Exposed Infected Hospitalised and Removed/Recovered (SVEIHR) Model Framework for COVID-19",
     "rel_date": "2023-08-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.10.23293925",
-    "rel_abs": "As COVID-19 vaccines became abundantly available around the world since the second half of 2021, many countries carried out a vaccination certificate (green pass) policy to encourage vaccination and help reopen their economies. This policy granted certified people more freedom of gathering and movement than unvaccinated individuals. Accordingly, pre-existing non-pharmaceutical interventions (NPIs) were adjusted under the vaccination certificate policy. The vaccination certificate also induced heterogeneous behaviors between unvaccinated and vaccinated groups, which complicates the modeling of COVID-19 transmission. Still, limited work is available in evaluating the impact of the green pass policy on COVID-19 transmission using quantitative methods. To characterize the major changes caused by the green pass policy, a modified susceptible-exposed-infected-removed (SEIR) epidemiological model SEIQRD2 is proposed in this paper. By integrating different behavior patterns of unvaccinated and vaccinated groups under the green pass policy, SEIQRD2 adopts the inherent variability and complexity of human behaviors in the context of vaccination and NPIs and their effect on COVID-19 transmissions. Three countries: Greece, Austria, and Israel are selected as case studies to demonstrate the validity of SEIQRD2. The simulation results illustrate that the combination of NPIs and vaccination still plays a pivotal role in containing the resurgence of COVID-19 by enforcing vaccination certification.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.10.23293942",
+    "rel_abs": "In reaction to the severe socio-economic effects and upheavals that the Covid-19 sickness had on the world within the first few weeks of its introduction, everyone involved had to act quickly to look for possible solutions for preventing the ensuing epidemics. A prompt response is more critical given Nigerias subpar social, economic, and healthcare infrastructure. Investigated was the efficacy of various pharmacological, non-pharmaceutical, or a combination of both therapies in flattening the Covid-19 incidence curve. In order to investigate the impact of these interventions, a deterministic SVEIHR model was created and applied. The Nigerian Center for Disease Control (NCDC) portals Covid-19 data were used to parametrize the model. For simulations using a system dynamic simulation, estimated parameters were employed. The fundamental reproduction number, R0, was used to evaluate the success of our suggested intervention in effectively managing COVID-19 transmission. The simulation results demonstrated that the use of only non-pharmaceutical interventions, such as the use of face masks, a light lockdown, and hand washing at baseline or high levels, is insufficient, with the R0 varying from vaccination at the vaccination rate of 0.5% with non-pharmaceutical interventions at any level of compliance, and a combination of vaccination at 0.05% and high hygiene level were effective in flattening the Covid-19 disease incidence curve in Nigeria, returning a R0 less than 0. Furthermore, maintaining a high level of cleanliness, which includes hand washing and the use of a face mask, would be sufficient to stop the spread of Covid-19 disease and eventually flatten Covid-19 disease incidence curve in Nigeria, given a low turnout of 0.05% for vaccination and the easing of lockdown.",
     "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Hu Cao",
-        "author_inst": "Macquarie University"
+        "author_name": "Oluwafemi S Oyamakin",
+        "author_inst": "University of Ibadan"
       },
       {
-        "author_name": "Longbing Cao",
-        "author_inst": "Macquarie University"
+        "author_name": "John I Popoola",
+        "author_inst": "University of Ibadan"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -9985,37 +9920,33 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.08.06.23293729",
-    "rel_title": "Why some countries but not others? Urbanisation, GDP and endemic disease predict global SARS-CoV-2 excess mortality patterns.",
+    "rel_doi": "10.1101/2023.08.07.23293747",
+    "rel_title": "Young Healthcare Workers' Employment Status and Mental Distress over SARS-CoV-2 in Bolivia",
     "rel_date": "2023-08-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.06.23293729",
-    "rel_abs": "The global impact of the SARS-CoV-2 pandemic has been uneven, with some regions experiencing significant excess mortality while others have been relatively unaffected. Yet factors which predict this variation remain enigmatic, particularly at large spatial scales. We used spatially explicit Bayesian models that integrate socio-demographic and endemic disease data at the country level to provide robust global estimates of excess SARS-CoV-2 mortality (P scores) for the years 2020 and 2021. We find that gross domestic product (GDP), spatial patterns and urbanization are strong predictors of excess mortality, with countries characterized by low GDP but high urbanization experiencing the highest levels of excess mortality. Intriguingly, we also observed that the prevalence of malaria and human immunodeficiency virus (HIV) are associated with country-level SARS-CoV-2 excess mortality in Africa and the Western Pacific, whereby countries with low HIV prevalence but high malaria prevalence tend to have lower levels of excess mortality. While these associations are correlative in nature at the macro-scale, they emphasize that patterns of endemic disease and socio-demographic factors are needed to understand the global dynamics of SARS-CoV-2.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.07.23293747",
+    "rel_abs": "BackgroundHealthcare workers (HCW) have been particularly affected by the SARS-CoV-2 pandemic as it influenced employment conditions and unemployment/insecure employment. Their deterioration is associated with mental distress.\n\nObjectiveThe aim of the study was to assess the trajectory of mental distress among HCW graduates during the COVID-19 pandemic in relation to their employment status.\n\nMethodsWe compared the change in mental distress over time among recent HCW graduates who were formally employed, to those who were unemployed/insecurely employed during the pandemic. In 2018 and 2022, we prospectively surveyed HCW who were in their final year of study in 2018 in Bolivia. Information was collected on socio-demographic characteristics, employment status, and mental distress. Mental distress was assessed using the 12-item General Health Questionnaire. Generalized Estimating Equations were implemented to examine changes in mental distress over time and the role of employment status in this development. Of the 663 HCW at baseline, 116 could be followed up.\n\nFindingsOver the course of the pandemic, formal employment after graduation did not change the odds of mental distress (odds ratio (OR)=0.93 [95% confidence interval (CI) 0.13-6.83]). In contrast, unemployment/insecure employment statistically significantly increased the odds of mental distress (OR=2.10 [CI 1.05-4.24]) over time.\n\nConclusionsEspecially in countries with limited social support for unemployed/insecurely employed citizens, interventions and policies to prevent mental distress among newly graduated HCW are important. This is particularly relevant in the face of crises such as the COVID-19 pandemic.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Nicholas M Fountain-Jones",
-        "author_inst": "University of Tasmania"
+        "author_name": "Lea John",
+        "author_inst": "Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital Munich"
       },
       {
-        "author_name": "Michael Charleston",
-        "author_inst": "University of Tasmania"
+        "author_name": "Katja Radon",
+        "author_inst": "Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital Munich"
       },
       {
-        "author_name": "Emily Flies",
-        "author_inst": "University of Tasmania"
+        "author_name": "Mira Muehlhaeusser",
+        "author_inst": "Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital Munich"
       },
       {
-        "author_name": "Scott Carver",
-        "author_inst": "University of Tasmania"
-      },
-      {
-        "author_name": "Luke Yates",
-        "author_inst": "University of Tasmania"
+        "author_name": "Maria Teresa Solis-Soto",
+        "author_inst": "OH TARGET Competence Center, Universidad San Francisco Xavier de Chuquisaca, Calle Junin esq. Estudiantes"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -10801,7 +10732,7 @@
     "rel_date": "2023-08-08",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.03.23293622",
-    "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) in solid organ transplant (SOT) patients is associated with more severe outcomes than non-immunosuppressed hosts. However, exactly which risk factors cause Long COVID in acute COVID cases remains unknown. More importantly, the impact of Long COVID on patient survival remains understudied, especially when examined alongside the effect of SOT.\n\nMethodsAll patients have been identified with acute COVID in the National COVID Collaborative Cohort registry from July 1, 2020, to June 30, 2022. We compared patient demographics in Long COVID vs. those without Long COVID based on descriptive statistics. Multivariable logistics regressions were used to determine the factors related to the likelihood of developing Long COVID from a case of acute COVID. Multi-variables Cox regression was used to determine the time-to-event outcome of patient survival with Long COVID.\n\nResultsThis study reviewed data from a cohort of 6,416,500 acute COVID patients. Of that group, 31,744 (0.5%) patients developed Long COVID from ICD diagnosis. The mean (q1, q3) age was 39 (22, 57) years old, and 55% of patients were female. From this cohort, a total of 31,744 (1%) developed Long COVID and 43,565 (1%) had SOT, with a total of 698 SOT patients identified with Long COVID. Mean age of those with Long COVID was 52 (39, 64) years old and 64% of patients were female. Most of the SOT patients were kidney transplant recipients. From the Cox regression analysis of patient survival, there were many significant factors related to patient survival (death), with elderly SOT patients having a much higher hazard ratio of 27.8 (26.3, 29.4).\n\nConclusionThis study has identified the important risk factors that are more likely to cause Long COVID in an acute COVID cohort. We investigated hazard ratios of patient survival based on multivariable Cox models, which found that Long COVID had a more direct impact on survival in elderly patients and those with SOT.",
+    "rel_abs": "medRxiv has withdrawn this preprint owing to lack of consent from all listed authors. Therefore, this work should not be cited as a reference for this project.",
     "rel_num_authors": 5,
     "rel_authors": [
       {
@@ -11491,93 +11422,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.08.03.23293611",
-    "rel_title": "Work Attendance during Acute Respiratory Illness Before and During the COVID-19 Pandemic, United States, 2018-2022",
+    "rel_doi": "10.1101/2023.08.03.23293586",
+    "rel_title": "COVID-19 among migrants, refugees, and internally displaced persons: systematic review, meta-analysis and qualitative synthesis of the global empirical literature",
     "rel_date": "2023-08-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.03.23293611",
-    "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and influenza viruses can be transmitted by infected persons who are pre-symptomatic or symptomatic. To assess impact of the COVID-19 pandemic on work attendance during illness, we analyzed prospectively collected data from persons with acute respiratory illness (ARI) enrolled in a multi-state study during 2018-2022. Persons with prior experience working from home were significantly less likely than those without this experience to work onsite on the day before illness and during the first 3 days of illness; the effect was more pronounced for the COVID-19 pandemic period than the pre-pandemic influenza seasons. Persons with influenza or COVID-19 were significantly less likely to work onsite than persons with other ARIs. Among persons for whom positive COVID-19 test results were available by the second or third day of illness, few worked onsite. Work-from-home policies may reduce the likelihood of workplace exposures to respiratory viruses.\n\nArticles summary lineWork-from-home policies may reduce the likelihood of workplace exposures to SARS-CoV-2 and influenza viruses.",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.03.23293586",
+    "rel_abs": "BackgroundPandemic response and preparedness plans aim at mitigating the spread of infectious diseases and protecting public health, but migrants are often side-lined. Evidence amounted early that migrants are disproportionately affected by the COVID-19 pandemic and its consequences. However, synthesised evidence is lacking that quantifies the inequalities in infection risk and disease outcomes, or contextualises the consequences of pandemic measures and their underlying mechanisms.\n\nMethodsSystematic review searching 25 databases and grey literature (12/2019 to 11/2021). We considered empirical articles covering migrants, refugees, asylum-seekers, and internally displaced persons reporting SARS-CoV-2 cases, hospitalisation, ICU admission, mortality, COVID-19 vaccination rates or health consequences of pandemic measures. Random-effects meta-analysis of observational studies and qualitative analysis were performed for evidence synthesis. A Protocol was registered with PROSPERO (CRD42021296952).\n\nFindingsOut of 6956 studies, we included 241 in the review. For the quantitative studies (n=46), meta-analysis with over 40 million study participants showed that compared to non-migrants, migrants have an elevated risk of infection (RR = 2{middle dot}33; 95%-CI: 1{middle dot}88-2{middle dot}89) but similar risk for hospitalisation (RR = 1{middle dot}05; 0{middle dot}80-1{middle dot}37), while the likelihood of ICU admission was higher (RR = 1{middle dot}36; 1{middle dot}04-1{middle dot}78). Among those hospitalised, migrants had a lower risk of mortality (RR = 0{middle dot}47; 0{middle dot}30-0{middle dot}73), while their population-based excess mortality tended to be higher (RR = 1{middle dot}31; 0{middle dot}95-1{middle dot}80). The qualitative synthesis (n=44) highlighted the complex interplay of social and COVID-19-related factors at different levels. This involved increased exposure, risk, and impact of pandemic measures that compromised the health of migrants.\n\nInterpretationEven in the advanced stages of the pandemic, migrants faced higher infection risks and disproportionately suffered from the consequences of COVID-19 disease, including deaths. Population-level interventions in future health emergencies must better consider socio-economic, structural and community-level exposures to mitigate risks among migrants and enhance health information systems, to close coverage gaps in migrant groups.\n\nFundingNone.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Faruque Ahmed",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Mary Patricia Nowalk",
-        "author_inst": "University of Pittsburgh"
-      },
-      {
-        "author_name": "Richard Zimmerman",
-        "author_inst": "University of Pittsburgh"
-      },
-      {
-        "author_name": "Todd Bear",
-        "author_inst": "University of Pittsburgh"
-      },
-      {
-        "author_name": "Carlos G Grijalva",
-        "author_inst": "Vanderbilt University Medical Center"
-      },
-      {
-        "author_name": "H. Keipp Talbot",
-        "author_inst": "Vanderbilt University Medical Center"
-      },
-      {
-        "author_name": "Ana Florea",
-        "author_inst": "Kaiser Permanente Southern California"
-      },
-      {
-        "author_name": "Sara Tartof",
-        "author_inst": "Kaiser Permanente Southern California"
-      },
-      {
-        "author_name": "Manjusha Gaglani",
-        "author_inst": "Baylor Scott and White Health"
+        "author_name": "Maren Hintermeier",
+        "author_inst": "University Hospital Heidelberg; Bielefeld School of Public Health, Germany"
       },
       {
-        "author_name": "Michael E Smith",
-        "author_inst": "Baylor Scott and White Health"
+        "author_name": "Nora Dalia Gottlieb",
+        "author_inst": "Bielefeld School of Public Health, Germany"
       },
       {
-        "author_name": "Huong Q McLean",
-        "author_inst": "Marshfield Clinic Research Institute"
+        "author_name": "Sven Rohleder",
+        "author_inst": "Bielefeld School of Public Health; University Hospital Heidelberg, Germany"
       },
       {
-        "author_name": "Jennifer King",
-        "author_inst": "Marshfield Clinic Research Institute"
+        "author_name": "Jan Oppenberg",
+        "author_inst": "Bielefeld School of Public Health, Germany"
       },
       {
-        "author_name": "Emily Toth Martin",
-        "author_inst": "University of Michigan-Ann Arbor"
+        "author_name": "Mazen Baroudi",
+        "author_inst": "Umea University, Sweden"
       },
       {
-        "author_name": "Arnold Monto",
-        "author_inst": "University of Michigan-Ann Arbor"
+        "author_name": "Sweetmavourneen Pernitez-Agan",
+        "author_inst": "International Organization for Migration, Manila, Philippines"
       },
       {
-        "author_name": "Hallie Phillips",
-        "author_inst": "Kaiser Permanente Washington Health Research Institute"
+        "author_name": "Janice Lopez",
+        "author_inst": "International Organisation for Migration, Manila, Philippines"
       },
       {
-        "author_name": "Karen J Wernli",
-        "author_inst": "Kaiser Permanente Washington Health Research Institute"
+        "author_name": "Sergio Flores",
+        "author_inst": "Uppsala University, Sweden"
       },
       {
-        "author_name": "Brendan Flannery",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Amir Mohsen Mohsenpour",
+        "author_inst": "Bielefeld School of Public Health, Germany"
       },
       {
-        "author_name": "Jessie Chung",
-        "author_inst": "US Centers for Disease Control and Prevention"
+        "author_name": "Kolitha Wickramage",
+        "author_inst": "UN Migration Agency Global Data Institute, Migration Health Division, International Organization for Migration, Berlin, Germany"
       },
       {
-        "author_name": "Amra Uzicanin",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Kayvan Bozorgmehr",
+        "author_inst": "Bielefeld School of Public Health; University Hospital Heidelberg, Germany"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -13141,35 +13040,83 @@
     "category": "neuroscience"
   },
   {
-    "rel_doi": "10.1101/2023.08.01.23293497",
-    "rel_title": "Recommended distances for physical distancing during COVID-19 pandemics reveal cultural connections between countries",
+    "rel_doi": "10.1101/2023.08.01.23293491",
+    "rel_title": "Health inequalities in SARS-CoV-2 infection during the second wave in England: REACT-1 study",
     "rel_date": "2023-08-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.01.23293497",
-    "rel_abs": "During COVID-19 pandemic several public health measures were implemented by diverse countries to reduce the risk of COVID-19, including social distancing. Here we collected the minimal distance recommended by each country for physical distancing at the onset of the pandemic and aimed to examine whether it had an impact on the outbreak dynamics and how this specific value was chosen. Despite an absence of data on SARS-CoV-2 viral transmission at the beginning of the pandemic, we found that most countries recommended physical distancing with a precise minimal distance, between one meter/three feet and two meters/six feet. 45% of the countries advised one meter/three feet and 49% advised a higher minimal distance. The recommended minimal distance did not show a clear correlation with reproduction rate nor with the number of new cases per million, suggesting that the overall COVID-19 dynamics in each country depended on multiple interacting factors. Interestingly, the recommended minimal distance correlated with several cultural parameters: it was higher in countries with larger interpersonal distance between two interacting individuals in non-epidemic conditions, and it correlated with civil law systems, and with currency. This suggests that countries which share common conceptions such as civil law systems and currency unions tend to adopt the same public health measures.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.01.23293491",
+    "rel_abs": "ObjectivesThe rapid spread of SARS-CoV-2 infection caused high levels of hospitalisation and deaths in late 2020 and early 2021 during the second wave in England. Severe disease during this period was associated with marked health inequalities across ethnic and sociodemographic subgroups. In this paper, we aimed to investigate how inequalities influence the risk of getting infected across ethnic and sociodemographic subgroups during a key period before widespread vaccination.\n\nDesignRepeated cross-sectional community-based study.\n\nMethodsWe analysed risk factors for test-positivity for SARS-CoV-2, based on self-administered throat and nose swabs in the community during rounds 5 to 10 of the REal-time Assessment of Community Transmission-1 (REACT-1) study between 18 September 2020 and 30 March 2021.\n\nResultsCompared to white ethnicity, people of Asian and black ethnicity had a higher risk of infection during rounds 5 to 10, with odds of 1.46 (1.27, 1.69) and 1.35 (1.11, 1.64) respectively. Among ethnic subgroups, the highest and the second-highest odds were found in Bangladeshi and Pakistan participants at 3.29 (2.23, 4.86) and 2.15 (1.73, 2.68) respectively when compared to British whites. People in larger (compared to smaller) households had higher odds of infection. Health care workers with direct patient contact and care home workers showed higher odds of infection compared to other essential/key workers. Additionally, the odds of infection among participants in public-facing activities or settings were greater than among those not working in those activities or settings.\n\nConclusionOur findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future severe waves of respiratory pathogens should include policies to reduce inequality in the risk of infection by ethnicity, household size, and occupational activity in order to reduce inequality in disease.\n\nSummary boxWhat is already known on this topic\n\nExtensive studies have described the relationship between socio-demographic factors and SARS-CoV-2 outcomes such as hospitalisations and deaths, rather than SARS-CoV-2 infection. Limited community-based studies investigated risk factors associated with SARS-CoV-2 infection, with the time frame of these studies has mainly focused on the period of the first wave of infection, or the beginning of the second wave, or the rollout of the first dose of the vaccine after the second wave period. We did not find studies that covered the critical period of the second wave in England when levels of social mixing were high, but no vaccine was available.\n\nWhat this study adds\n\nWe show health inequalities across ethnic and sociodemographic subgroups during a key period: before widespread vaccination, but, largely, not during the period of stringent social distancing. We observed substantial ethnic and occupational differences in the risk of SARS-CoV-2 infection. Minority ethnic groups, including those of Bangladeshi and Pakistani ethnicity, had an excess risk of infection compared with the British white population. Healthcare workers, care home workers and people who work in public-facing activities or settings were associated with higher odds of infection. The risk of SARS-CoV-2 infection increased monotonically as household size increased, and more deprived neighbourhood areas were associated with a higher risk of infection.\n\nHow this study might affect research, practice or policy\n\nOur findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future waves of severe respiratory infection should explicitly aim to reduce inequalities in infection in order to reduce inequality in disease.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Dongwoo Chai",
-        "author_inst": "Universite Paris Cite"
+        "author_name": "Haowei Wang",
+        "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc"
       },
       {
-        "author_name": "Layla El Mossadeq",
-        "author_inst": "Universite Paris Cite"
+        "author_name": "Kylie E. C. Ainslie",
+        "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc"
+      },
+      {
+        "author_name": "Oliver Eales",
+        "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc"
+      },
+      {
+        "author_name": "Caroline E. Walters",
+        "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc"
+      },
+      {
+        "author_name": "David Haw",
+        "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc"
       },
       {
-        "author_name": "Michel Raymond",
-        "author_inst": "ISEM: Institut des sciences de l'evolution de Montpellier"
+        "author_name": "Christina Atchinson",
+        "author_inst": "School of Public Health, Imperial College London, UK"
+      },
+      {
+        "author_name": "Claudio Fronterre",
+        "author_inst": "CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK"
+      },
+      {
+        "author_name": "Peter J. Diggle",
+        "author_inst": "CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK"
+      },
+      {
+        "author_name": "Deborah Ashby",
+        "author_inst": "School of Public Health, Imperial College London, UK"
       },
       {
-        "author_name": "Virginie Orgogozo",
-        "author_inst": "Universit\u00e9 Paris Cit\u00e9: Universite Paris Cite"
+        "author_name": "Graham Cooke",
+        "author_inst": "Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic"
+      },
+      {
+        "author_name": "Wendy Barclay",
+        "author_inst": "Department of Infectious Disease, Imperial College London, UK"
+      },
+      {
+        "author_name": "Helen Ward",
+        "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear"
+      },
+      {
+        "author_name": "Ara Darzi",
+        "author_inst": "Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a"
+      },
+      {
+        "author_name": "Christl A Donnelly",
+        "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc"
+      },
+      {
+        "author_name": "Paul Elliott",
+        "author_inst": "School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear"
+      },
+      {
+        "author_name": "Steven Riley",
+        "author_inst": "School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.07.27.23293244",
@@ -15099,87 +15046,87 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2023.07.26.550688",
-    "rel_title": "Competitive fitness and homologous recombination of SARS-CoV-2 variants of concern",
+    "rel_doi": "10.1101/2023.07.26.550660",
+    "rel_title": "Interaction of SCoV-2 NSP7 or NSP8 alone may cause constriction of the RNA entry channel in NSP12: Implications for novel RdRp inhibitor drug discovery",
     "rel_date": "2023-07-27",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.26.550688",
-    "rel_abs": "SARS-CoV-2 variants continue to emerge and cocirculate in humans and wild animals. The factors driving the emergence and replacement of novel variants and recombinants remain incompletely understood. Herein, we comprehensively characterized the competitive fitness of SARS-CoV-2 wild type (WT) and three variants of concern (VOCs), Alpha, Beta and Delta, by coinfection and serial passaging assays in different susceptible cells. Deep sequencing analyses revealed cell-specific competitive fitness: the Beta variant showed enhanced replication fitness during serial passage in Caco-2 cells, whereas the WT and Alpha variant showed elevated fitness in Vero E6 cells. Interestingly, a high level of neutralizing antibody sped up competition and completely reshaped the fitness advantages of different variants. More importantly, single clone purification identified a significant proportion of homologous recombinants that emerged during the passage history, and immune pressure reduced the frequency of recombination. Interestingly, a recombination hot region located between nucleotide sites 22995 and 28866 of the viral genomes could be identified in most of the detected recombinants. Our study not only profiled the variable competitive fitness of SARS-CoV-2 under different conditions, but also provided direct experimental evidence of homologous recombination between SARS-CoV-2 viruses, as well as a model for investigating SARS-CoV-2 recombination.\n\nImportanceSARS-CoV-2 variants or subvariants keep emerging and the epidemic strains keeps changing in humans and animals. The continued replacement of the epidemic strains was attributed to higher competitive fitness evolved by the newly appeared ones than the older ones, but which factors affect the final outcomes are still not entirely clear. In this study, we performed in vitro coinfection and serial passage with three VOCs and WT under different conditions. Our results showed that the competition outcomes of these viral strains varied in different cell lines or under different immune pressure, confirming the probable effects of these two factors for the competitive fitness of different SARS-CoV-2 viral strains. Meanwhile, strikingly, we found that coinfection and serial passage with different SARS-CoV-2 viral strains can mimic the recombination process of SARS-CoV-2 occurred in coinfection individual, indicating it is a novel model to investigate the SARS-CoV-2 recombination mechanism.",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.26.550660",
+    "rel_abs": "RNA-dependent RNA polymerase (RdRP) is a critical component of the RNA virus life cycle, including SCoV-2. Among the Coronavirus-encoded proteins, non-structural protein 12 (NSP12) exhibits polymerase activity in collaboration with one unit of NSP7 and two units of NSP8, constituting the RdRp holoenzyme. While there is abundant information on SCoV-2 RdRp-mediated RNA replication, the influence of interplay among NSP12, NSP7, and NSP8 on template RNA binding and primer extension activity remains relatively unexplored and poorly understood. Here, we recreated a functional RdRp holoenzyme in vitro using recombinant SCoV-2 NSP12, NSP7, and NSP8, and established its functional activity. Subsequently, molecular interactions among the NSPs in the presence of a variety of templates and their effects on polymerase activity were studied, wherein we found that NSP12 alone exhibited notable polymerase activity that increased significantly in the presence of NSP7 and NSP8. However, this activity was completely shut down, and the template RNA-primer complex was detached from NSP12 when one of the two cofactors was present. Through computational analysis, we found that the template RNA entry channel was more constricted in the presence of one of the two cofactors, which was relatively more constricted in the presence of NSP8 compared to that in the presence of NSP7. In conclusion, we report that NSP7 and NSP8 together synergise to enhance the activity of NSP12, but antagonise when present alone. Our findings have implications for novel drug development, and compounds that obstruct the binding of NSP7 or NSP8 to NSP12 can have lethal effects on viral RNA replication.",
     "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Cheng-Feng Qin",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Deepa Singh",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India"
       },
       {
-        "author_name": "Qi Chen",
-        "author_inst": "Institute of Microbiology and Epidemiology"
+        "author_name": "Tushar Kushwaha",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India."
       },
       {
-        "author_name": "Qin Si",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Rajkumar Kulandaisamy",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India"
       },
       {
-        "author_name": "Hangyu Zhou",
-        "author_inst": "Chinese Academy of Medical Sciences & Peking Union Medical College"
+        "author_name": "Vikas Kumar",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India"
       },
       {
-        "author_name": "Yong-Qiang Deng",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Kamal Baswal",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India."
       },
       {
-        "author_name": "Pan-Deng Shi",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Saras H Tiwari",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India."
       },
       {
-        "author_name": "Hui Zhao",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Arkadyuti Ghorai",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India."
       },
       {
-        "author_name": "Xiao-Feng Li",
-        "author_inst": "Academy of Military Medical Sciences Institute of Microbiology and Epidemiology"
+        "author_name": "Manoj Kumar",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India."
       },
       {
-        "author_name": "Xing-Yao Huang",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Saroj Kumar",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India"
       },
       {
-        "author_name": "Yarong Wu",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Aparoy Polamarasetty",
+        "author_inst": "Faculty of Biology, Indian Institute of Petroleum & Energy, Visakhapatnam, Andhra Pradesh, India."
       },
       {
-        "author_name": "Yan Guo",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Deepak Sehgal",
+        "author_inst": "Virology Lab, Department of Life Sciences, Shiv Nadar University, Greater Noida, Uttar Pradesh, India."
       },
       {
-        "author_name": "Guangqian Pei",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiolog"
+        "author_name": "Madhumohan R Katika",
+        "author_inst": "ESIC Medical College and Hospital, Sanath Nagar, Hyderabad, Telangana, India."
       },
       {
-        "author_name": "Yunfei Wang",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Suresh Gadde",
+        "author_inst": "Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada."
       },
       {
-        "author_name": "Si-Qi Sun",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Marceline C\u00f4t\u00e9",
+        "author_inst": "Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, Canada"
       },
       {
-        "author_name": "Zong-Min Du",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Sarala R Kayampeta",
+        "author_inst": "R & D Division, Srikara Biologicals Private Limited, Tirupati, Andhra Pradesh, India."
       },
       {
-        "author_name": "Yujun Cui",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Mohan B Appaiahgari",
+        "author_inst": "R & D Division, Srikara Biologicals Private Limited, Tirupati, Andhra Pradesh, India."
       },
       {
-        "author_name": "Hang Fan",
-        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Krishna K Inampudi",
+        "author_inst": "Department of Biophysics, All India Institute of Medical Sciences, New Delhi, Delhi, India."
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2023.07.24.23293101",
@@ -16745,83 +16692,47 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2023.07.24.550352",
-    "rel_title": "Endothelial SARS-CoV-2 infection is not the underlying cause of COVID19-associated vascular pathology in mice",
+    "rel_doi": "10.1101/2023.07.24.550324",
+    "rel_title": "Revealing and evaluation of antivirals targeting multiple druggable sites of RdRp complex in SARS-CoV-2",
     "rel_date": "2023-07-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.24.550352",
-    "rel_abs": "Endothelial damage and vascular pathology have been recognized as major features of COVID-19 since the beginning of the pandemic. Two main theories regarding how Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) damages endothelial cells and causes vascular pathology have been proposed: direct viral infection of endothelial cells or indirect damage mediated by circulating inflammatory molecules and immune mechanisms. However, these proposed mechanisms remain largely untested in vivo. Here, we utilized a set of new mouse genetic tools1 developed in our lab to test both the necessity and sufficiency of endothelial human angiotensin-converting enzyme 2 (hACE2) in COVID19 pathogenesis. Our results demonstrate that endothelial ACE2 and direct infection of vascular endothelial cells does not contribute significantly to the diverse vascular pathology associated with COVID-19.",
-    "rel_num_authors": 16,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.24.550324",
+    "rel_abs": "SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) complex consisting of nsp12, nsp7, and nsp8 as the key enzyme for viral genome replication and is a proven antiviral drug target. In this study, molecular interactions of nsp7 and nsp8 with nsp12 and the active site of nsp12 were coterminously targeted using in-silico screening of small molecule libraries to identify potential antivirals. Surface plasmon resonance (SPR) based assay using purified nsp7 and nsp8 proteins was developed, and the binding of identified molecules to targets was validated. The antiviral efficacy of identified small molecules was evaluated using cell-based assays, and potent antiviral effect with EC50 values of 0.56 M, 0.73 M, and 2.8 M was demonstrated by fangchinoline, cepharanthine, and sennoside B, respectively. Further in vivo, investigation using hACE2 mice is being conducted. This is the first study that targets multiple sites in the RdRp complex of SARS-CoV-2 using a structure-based molecular repurposing approach and suggests potential therapeutic options for emerging variants of SARS-CoV-2.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Siqi Gao",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Alan T Tang",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Min Wang",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "David W Buchholz",
-        "author_inst": "Cornell University"
-      },
-      {
-        "author_name": "Brian Imbiakha",
-        "author_inst": "Cornell University"
-      },
-      {
-        "author_name": "Jisheng Yang",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Xiaowen Chen",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Peter Hewins",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Patricia Mericko-Ishizuka",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "N. Adrian Leu",
-        "author_inst": "University of Pennsylvania School of Veterinary Medicine"
+        "author_name": "Ruchi Rani",
+        "author_inst": "Indian Institute of Technology, Roorkee, Uttarakhand, India"
       },
       {
-        "author_name": "Stephanie Sterling",
-        "author_inst": "University of Pennsylvania School of Veterinary Medicine"
+        "author_name": "Sanketkumar Nehul",
+        "author_inst": "Indian Institute of Technology, Roorkee, Uttarakhand, India"
       },
       {
-        "author_name": "Avery August",
-        "author_inst": "Cornell University"
+        "author_name": "Shweta Choudhary",
+        "author_inst": "Indian Institute of Technology, Roorkee, Uttarakhand, India"
       },
       {
-        "author_name": "Kellie Jurado",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Anushka Upadhyay",
+        "author_inst": "Indian Institute of Technology, Roorkee, Uttarakhand, India"
       },
       {
-        "author_name": "Edward Morrisey",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Gaurav Kumar Sharma",
+        "author_inst": "ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India"
       },
       {
-        "author_name": "Hector Aguilar-Carreno",
-        "author_inst": "Cornell University"
+        "author_name": "Pravindra Kumar",
+        "author_inst": "Indian Institute of Technology, Roorkee,  Uttarakhand, India"
       },
       {
-        "author_name": "Mark L Kahn",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Shailly Tomar",
+        "author_inst": "Indian Institute of Technology Roorkee, Uttarakhand, India"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "pathology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2023.07.24.550379",
@@ -18387,87 +18298,63 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2023.07.17.549425",
-    "rel_title": "A laboratory framework for ongoing optimisation of amplification based genomic surveillance programs",
+    "rel_doi": "10.1101/2023.07.16.23292705",
+    "rel_title": "Community-onset urinary tract infection in females in the context of COVID-19: a longitudinal population cohort study exploring case presentation, management, and outcomes",
     "rel_date": "2023-07-18",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.17.549425",
-    "rel_abs": "Constantly evolving viral populations affect the specificity of primers and quality of genomic surveillance. This study presents a framework for continuous optimisation of sequencing efficiency for public health surveillance based on the ongoing evolution of the COVID-19 pandemic. SARS-CoV-2 genomic clustering capacity based on three amplification based whole genome sequencing schemes was assessed using decreasing thresholds of genome coverage and measured against epidemiologically linked cases. Overall genome coverage depth and individual amplicon depth were used to calculate an amplification efficiency metric. Significant loss of genome coverage over time was documented which was recovered by optimisation of primer pooling or implementation of new primer sets. A minimum of 95% genome coverage was required to cluster 94% of epidemiologically defined SARS-CoV-2 transmission events. Clustering resolution fell to 70% when only 85% of genome coverage was achieved. The framework presented in this study can provide public health genomic surveillance programs a systematic process to ensure an agile and effective laboratory response during rapidly evolving viral outbreaks.",
-    "rel_num_authors": 17,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.16.23292705",
+    "rel_abs": "BackgroundCOVID-19 affected the epidemiology of other infectious diseases and how they were managed. Urinary tract infection (UTI) is one of the most common infections treated in the community in England. We investigated the impact of the COVID-19 pandemic on UTI primary care consultations and outcomes in female patients.\n\nMethods and findingsWe analysed General Practice (GP) consultation and hospital admission records using the Whole Systems Integrated Care (WSIC) data in North West London between 2016 and 2021. We quantified the changes in UTI GP consultation rates using time series analysis before and during the pandemic. We assessed the outcomes of UTI, measured by subsequent bacteraemia and sepsis within 60 days, for consultations delivered face-to-face or remotely, with or without diagnostic tests recommended by the national guidelines, and with or without antibiotic treatment. Between January 2016 and December 2021, we identified 375,859 UTI episodes in 233,450 female patients. Before the COVID-19 pandemic (January 2016 - February 2020), the UTI GP consultation rate stayed level at 522.8 cases per 100,000 population per month, with a seasonal pattern of peaking in October. Since COVID-19, (March 2020 - December 2021), monthly UTI GP consultations declined when COVID-19 cases surged and rose when COVID-19 case fell. During the pandemic, the UTI consultations delivered face-to-face reduced from 72.0% to 29.4%, the UTI consultations with appropriate diagnostic tests, including urine culture and urinalysis, reduced from 17.3% to 10.4%, and the UTI cases treated with antibiotics reduced from 52.0% to 47.8%. The likelihood of antibiotics being prescribed was not affected by whether the consultation was delivered face-to-face or remotely but associated with whether there was a diagnostic test. Regardless of whether the UTI consultation occurred before or during the pandemic, the absence of antibiotic treatment for UTI is associated with a 10-fold increase in the risk of having bacteraemia or sepsis within 60 days, though the patients who consulted GPs for UTI during the pandemic were older and more co-morbid. Across the study period (January 2016 - December 2021), nitrofurantoin remained the first-line antibiotic option for UTI. The percentage of non-prophylactic acute UTI antibiotic prescriptions with durations that exceeded the guideline recommendations was 58.7% before the pandemic, and 49.4% since. This led to 830,522 total excess days of treatment, account for 63.3% of all non-prophylactic acute antibiotics prescribed for UTI. Before the pandemic, excess antibiotic days of UTI drugs had been reducing consistently. However, this decline slowed down during the pandemic. Having a diagnostic test was associated with 0.6 less excess days of antibiotic treatment.\n\nConclusionsThis analysis provides a comprehensive examination of management and outcomes of community-onset UTI in female patients, considering the changes in GP consultations during the COVID-19 pandemic. Our findings highlighted the importance of appropriate urine testing to support UTI diagnosis in symptomatic patients and initiation of antibiotic treatment with appropriate course duration. Continued monitoring is required to assess the overall impact on patients and health systems from the changed landscape of primary care delivery.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Connie Lam",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, AUSTRALIA"
+        "author_name": "Nina J Zhu",
+        "author_inst": "National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial "
       },
       {
-        "author_name": "Jessica Johnson-Mackinnon",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, AUSTRALIA"
-      },
-      {
-        "author_name": "Kerri Basile",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
-      },
-      {
-        "author_name": "Winkie Fong",
-        "author_inst": "Centre for Infectious Diseases and Microbiology - Public Health, Institute for Clinical Pathology and Medical Research Westmead Hospital, Westmead, AUSTRALIA"
-      },
-      {
-        "author_name": "Carl J.E Suster",
-        "author_inst": "Centre for Infectious Diseases and Microbiology - Public Health, Institute for Clinical Pathology and Medical Research Westmead Hospital, Westmead, AUSTRALIA"
-      },
-      {
-        "author_name": "Mailie Gall",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
-      },
-      {
-        "author_name": "Jessica Aguis",
-        "author_inst": "Centre for Infectious Diseases and Microbiology - Public Health, Institute for Clinical Pathology and Medical Research Westmead Hospital, Westmead, AUSTRALIA"
-      },
-      {
-        "author_name": "Shona Chandra",
-        "author_inst": "Centre for Infectious Diseases and Microbiology - Public Health, Institute for Clinical Pathology and Medical Research Westmead Hospital, Westmead, AUSTRALIA"
+        "author_name": "Benedict Hayhoe",
+        "author_inst": "Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom"
       },
       {
-        "author_name": "Jenny Draper",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
+        "author_name": "Raheelah Ahmad",
+        "author_inst": "Division of Health Services Research and Management, School of Health Sciences, City, University of London, London, United Kingdom"
       },
       {
-        "author_name": "Elena Martinez",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
+        "author_name": "James R Price",
+        "author_inst": "National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial "
       },
       {
-        "author_name": "Alexander Drew",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
+        "author_name": "Donna Lecky",
+        "author_inst": "Primary Care and Interventions Unit, United Kingdom Health Security Agency (UKHSA), Gloucestershire, United Kingdom"
       },
       {
-        "author_name": "Qinning Wang",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
+        "author_name": "Monsey McLeod",
+        "author_inst": "NHS England and NHS Improvement, London, United Kingdom"
       },
       {
-        "author_name": "Sharon Chen",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
+        "author_name": "Elena Ferran",
+        "author_inst": "Barts Health NHS Trust, London, United Kingdom"
       },
       {
-        "author_name": "Jen Kok",
-        "author_inst": "Centre for Infectious Diseases and Microbiology-Laboratory Services, Institute for Clinical Pathology and Medical Research, NSW Health Pathology, Sydney, AUSTRA"
+        "author_name": "Timothy M Rawson",
+        "author_inst": "National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial "
       },
       {
-        "author_name": "Dominic L Dwyer",
-        "author_inst": "Westmead Hospital"
+        "author_name": "Emma Carter",
+        "author_inst": "National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial "
       },
       {
-        "author_name": "Vitali Sintchenko",
-        "author_inst": "Institute of Clinical Pathology and Medical Research"
+        "author_name": "Alison H Holmes",
+        "author_inst": "National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Healthcare Associated Infections and Antimicrobial Resistance, Imperial "
       },
       {
-        "author_name": "Rebecca J Rockett",
-        "author_inst": "University of Sydney"
+        "author_name": "Paul Aylin",
+        "author_inst": "Primary Care and Interventions Unit, United Kingdom Health Security Agency (UKHSA), Gloucestershire, United Kingdom"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "genomics"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.07.17.23292714",
@@ -19969,67 +19856,63 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.07.12.548630",
-    "rel_title": "Utility of nasal swabs for assessing mucosal immune responses towards SARS-CoV-2",
+    "rel_doi": "10.1101/2023.07.13.23292597",
+    "rel_title": "Booster dose of self-amplifying SARS-CoV-2 RNA vaccine vs. mRNA vaccine: a phase 3 comparison of ARCT-154 with Comirnaty",
     "rel_date": "2023-07-13",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.12.548630",
-    "rel_abs": "SARS-CoV-2 has caused millions of infections worldwide since its emergence in 2019. Understanding how infection and vaccination induce mucosal immune responses and how they fluctuate over time is important, especially since they are key in preventing infection and reducing disease severity. We established a novel methodology for assessing SARS-CoV-2 cytokine and antibody responses at the nasal epithelium by using nasopharyngeal swabs collected longitudinally before and after either SARS-CoV-2 infection or vaccination. We then compared responses between mucosal and systemic compartments. We demonstrate that cytokine and antibody profiles differ markedly between compartments. Nasal cytokines show a wound healing phenotype while plasma cytokines are consistent with pro-inflammatory pathways. We found that nasal IgA and IgG have different kinetics after infection, with IgA peaking first. Although vaccination results in low nasal IgA, IgG induction persists for up to 180 days post-vaccination. This research highlights the importance of studying mucosal responses in addition to systemic responses to respiratory infections to understand the correlates of disease severity and immune memory. The methods described herein can be used to further mucosal vaccine development by giving us a better understanding of immunity at the nasal epithelium providing a simpler, alternative clinical practice to studying mucosal responses to infection.\n\nTeaserA nasopharyngeal swab can be used to study the intranasal immune response and yields much more information than a simple viral diagnosis.",
-    "rel_num_authors": 12,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.13.23292597",
+    "rel_abs": "BackgroundLicensed mRNA vaccines demonstrated initial effectiveness against COVID-19 but require booster doses to broaden the anti-SARS-CoV-2 response. There is an unmet need for novel highly immunogenic and broadly protective vaccines. We compared immunogenicity and tolerability of ARCT-154, a novel self-amplifying mRNA vaccine with the mRNA vaccine, Comirnaty(R).\n\nMethodsWe compared immune responses to ARCT-154 and Comirnaty booster doses in healthy 18- 77-year-old Japanese adults initially immunised with two doses of mRNA COVID-19 vaccine (Comirnaty or Spikevax(R)) then a third dose of Comirnaty at least 3 months previously. Neutralising antibodies were measured before and 28 days after booster vaccination. The primary objective was to demonstrate non-inferiority of the immune response against Wuhan-Hu-1 SARS-CoV-2 virus as geometric mean titre (GMT) ratios and seroresponse rates (SRR) of neutralising antibodies; key secondary endpoints included the immune response against the Omicron BA.4/5 variant and vaccine tolerability assessed using participant-completed electronic diaries.\n\nFindingsBetween December 13, 2022 and February 25, 2023 we enrolled 828 participants randomised 1:1 to receive ARCT-154 (n = 420) or Comirnaty (n = 408) booster doses. Four weeks after boosting, ARCT-154 induced higher Wuhan-Hu-1 neutralising antibodies GMTs than Comirnaty (5641 [95% CI: 4321, 7363] and 3934 [2993, 5169], respectively), a GMT ratio of 1{middle dot}43 (95% CI: 1{middle dot}26-1{middle dot}63), with SRR of 65{middle dot}2% (60{middle dot}2-69{middle dot}9) and 51{middle dot}6% (46{middle dot}4-56{middle dot}8) meeting the non-inferiority criteria. Respective anti-Omicron BA.4/5 GMTs were 2551 (1687-3859) and 1958 (1281-2993), a GMT ratio of 1{middle dot}30 (95% CI: 1{middle dot}07-1{middle dot}58), with SRR of 69{middle dot}9% (65{middle dot}0-74{middle dot}4) and 58{middle dot}0% (52{middle dot}8-63{middle dot}1), meeting the superiority criteria for ARCT-154 over Comirnaty. Booster doses of either ARCT-154 or Comirnaty were equally well-tolerated with no causally-associated severe or serious adverse events; 94{middle dot}8% and 96{middle dot}8% of ARCT-154 and Comirnaty vaccinees reported local reactions and 65{middle dot}7% and 62{middle dot}5% had solicited systemic adverse events. Events were mainly mild in severity, occurring and resolving within 3-4 days of vaccination.\n\nInterpretationImmune responses four weeks after an ARCT-154 booster dose in mRNA-immunised adults were higher than after a Comirnaty booster, meeting non-inferiority criteria against the prototype Wuhan-Hu-1 virus, and superiority criteria against the Omicron BA.4/5 variant.\n\nFundingThe study was funded by the Japanese Ministry of Health, Labour, and Welfare following a public invitation to bid for an urgent improvement project for vaccine manufacturing systems, fourth invitation, Grant number: 1212-3.\n\nClinical Trials registration and identifierThe study was registered on the Japan Registry for Clinical Trials (jRCT 2071220080).",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Ericka Kirkpatrick Roubidoux",
-        "author_inst": "St. Jude Children's Research Hospital"
-      },
-      {
-        "author_name": "Pamela H Brigleb",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Yoshiaki Oda",
+        "author_inst": "Meiji Seika Pharma Co., Ltd."
       },
       {
-        "author_name": "Kasi Vegesana",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Yuji Kumagai",
+        "author_inst": "Kitasato University Kitasato Institute Hospital"
       },
       {
-        "author_name": "Aisha Souquette",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Manabu Kanai",
+        "author_inst": "Meiji Seika Pharma Co., Ltd."
       },
       {
-        "author_name": "Kendall Whitt",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Yasuhiro Iwama",
+        "author_inst": "Meiji Seika Pharma Co., Ltd."
       },
       {
-        "author_name": "Pamela Freiden",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Iori Okura",
+        "author_inst": "Meiji Seika Pharma Co., Ltd."
       },
       {
-        "author_name": "- St. Jude Investigative Team",
-        "author_inst": "-"
+        "author_name": "Takeshi Minamida",
+        "author_inst": "Meiji Seika Pharma Co., Ltd."
       },
       {
-        "author_name": "Amanda Green",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Yukihiro Yagi",
+        "author_inst": "Meiji Seika Pharma Co., Ltd."
       },
       {
-        "author_name": "Paul G Thomas",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Toru Kurosawa",
+        "author_inst": "Meiji Seika Pharma Co., Ltd."
       },
       {
-        "author_name": "Maureen A McGargill",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Benjamin Greener",
+        "author_inst": "Arcturus Therapeutics, Inc., San Diego, CA, USA"
       },
       {
-        "author_name": "Joshua Wolf",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Ye Zhang",
+        "author_inst": "Arcturus Therapeutics, Inc., San Diego, CA, USA"
       },
       {
-        "author_name": "Stacey Schultz-Cherry",
-        "author_inst": "St. Jude Children's Research Hospital"
+        "author_name": "Judd L. Walson",
+        "author_inst": "Arcturus Therapeutics, Inc., San Diego, CA, USA."
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "immunology"
+    "license": "cc_by_nc",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2023.07.12.23292576",
@@ -21396,7 +21279,7 @@
     "rel_date": "2023-07-09",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.08.23292389",
-    "rel_abs": "Antimicrobial peptides (AMPs) are a complex network of 10-100 amino acid sequence molecules, widely distributed in Nature. Even though more than 300 AMPs have been described in mammals, cathelicidins and defensins remain the most investigated to date.\n\nSome publications examined the role of AMPs in COVID-19, but the findings are preliminary and in vivo studies are still lacking. Here, we report the plasma levels of five AMPs (LL-37, -defensin 1, -defensin 3, {beta}-defensin 1 and {beta}-defensin 3) and five cytokines (tumor necrosis factor-, interleukin-1{beta}, interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1), in 15 healthy volunteers, 36 COVID-19 patients without Acute Kidney Injury (AKI) and 17 COVID-19 patients with AKI, since AKI is a well-known marker of worse prognosis in Sars-CoV-2 infections.\n\nWe found increased levels of -defensin 1, -defensin 3 and {beta}-defensin 3, but not LL-37 or {beta}-defensin 3, in our COVID-19 population, when compared with the healthy controls, in conjunction with higher levels of interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1, putting in evidence that these AMPs and cytokines may have an important role in the systemic inflammatory response and tissue damage that characterizes severe COVID-19.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC=\"FIGDIR/small/23292389v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@a6300org.highwire.dtl.DTLVardef@1e9c84forg.highwire.dtl.DTLVardef@15deeceorg.highwire.dtl.DTLVardef@1e94331_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
+    "rel_abs": "Antimicrobial peptides (AMPs) are a complex network of 10-100 amino acid sequence molecules, widely distributed in Nature. Even though more than 300 AMPs have been described in mammals, cathelicidins and defensins remain the most investigated to date.\n\nSome publications examined the role of AMPs in COVID-19, but the findings are preliminary and in vivo studies are still lacking. Here, we report the plasma levels of five AMPs (LL-37, -defensin 1, -defensin 3, {beta}-defensin 1 and {beta}-defensin 3) and five cytokines (tumor necrosis factor-, interleukin-1{beta}, interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1), in 15 healthy volunteers, 36 COVID-19 patients without Acute Kidney Injury (AKI) and 17 COVID-19 patients with AKI, since AKI is a well-known marker of worse prognosis in Sars-CoV-2 infections.\n\nWe found increased levels of -defensin 1, -defensin 3 and {beta}-defensin 3, but not LL-37 or {beta}-defensin 3, in our COVID-19 population, when compared with the healthy controls, in conjunction with higher levels of interleukin-6, interleukin-10, interferon-{gamma} and monocyte chemoattractant protein-1, putting in evidence that these AMPs and cytokines may have an important role in the systemic inflammatory response and tissue damage that characterizes severe COVID-19.\n\nGraphic Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC=\"FIGDIR/small/23292389v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@6a7377org.highwire.dtl.DTLVardef@c2a89dorg.highwire.dtl.DTLVardef@1cc1540org.highwire.dtl.DTLVardef@1875c3f_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
     "rel_num_authors": 5,
     "rel_authors": [
       {
@@ -21595,51 +21478,55 @@
     "category": "neurology"
   },
   {
-    "rel_doi": "10.1101/2023.07.07.23292215",
-    "rel_title": "Comparative Reconstruction of SARS-CoV-2 transmission in three African countries using a mathematical model integrating immunity data.",
-    "rel_date": "2023-07-08",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.07.23292215",
-    "rel_abs": "ObjectivesAfrica has experienced fewer coronavirus disease 2019 (COVID-19) cases and deaths than other regions, with a contrasting epidemiological situation between countries, raising questions regarding the determinants of disease spread in Africa.\n\nMethodWe built a susceptible-exposed-infected-recovered model including COVID-19 mortality data where recovery class is structured by specific immunization and modeled by a partial differential equation considering the opposed effects of immunity decline and immunization. This model was applied to Tunisia, Senegal, and Madagascar.\n\nFindingSenegal and Tunisia experienced two epidemic phases. Initially, infections emerged in naive individuals and were limited by social distancing. Variants of concern (VOCs) were also introduced. The second phase was characterized by successive epidemic waves driven by new VOCs that escaped host immunity. Meanwhile, Madagascar demonstrated a different profile, characterized by longer intervals between epidemic waves, increasing the pool of susceptible individuals who had lost their protective immunity. The impact of vaccination in Tunisia and Senegal on model parameters was evaluated.\n\nInterpretationLoss of immunity and vaccination-induced immunity have played crucial role in controlling the African pandemic. Severe acute respiratory syndrome coronavirus 2 has become endemic now and will continue to circulate in African populations. However, previous infections provide significant protection against severe diseases, thus providing a basis for future vaccination strategies.",
-    "rel_num_authors": 8,
+    "rel_doi": "10.1101/2023.07.05.547902",
+    "rel_title": "SARS-CoV-2 Nsp1 regulates translation start site fidelity to promote infection",
+    "rel_date": "2023-07-07",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.05.547902",
+    "rel_abs": "A better mechanistic understanding of virus-host interactions can help reveal vulnerabilities and identify opportunities for therapeutic interventions. Of particular interest are essential interactions that enable production of viral proteins, as those could target an early step in the virus lifecycle. Here, we use subcellular proteomics, ribosome profiling analyses and reporter assays to detect changes in polysome composition and protein synthesis during SARS-CoV-2 (CoV2) infection. We identify specific translation factors and molecular chaperones whose inhibition impairs infectious particle production without major toxicity to the host. We find that CoV2 non-structural protein Nsp1 selectively enhances virus translation through functional interactions with initiation factor EIF1A. When EIF1A is depleted, more ribosomes initiate translation from an upstream CUG start codon, inhibiting translation of non-structural genes and reducing viral titers. Together, our work describes multiple dependencies of CoV2 on host biosynthetic networks and identifies druggable targets for potential antiviral development.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "bechir neffeti",
-        "author_inst": "university of Tunis el Manar"
+        "author_name": "Ranen Aviner",
+        "author_inst": "CZ Biohub: Chan Zuckerberg Biohub"
       },
       {
-        "author_name": "amira kebir",
-        "author_inst": "University of Tunis el Manar"
+        "author_name": "Peter  V Lidsky",
+        "author_inst": "UCSF: University of California San Francisco"
       },
       {
-        "author_name": "walid ben aribi",
-        "author_inst": "university of Tunis el manar"
+        "author_name": "Yinghong Xiao",
+        "author_inst": "UCSF: University of California San Francisco"
       },
       {
-        "author_name": "Maryam Diarra",
-        "author_inst": "Instutit Pasteur de Dakar"
+        "author_name": "Michel Tasseto",
+        "author_inst": "UCSF: University of California San Francisco"
       },
       {
-        "author_name": "matthieu schoenhals",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Lichao Zhang",
+        "author_inst": "CZ Biohub: Chan Zuckerberg Biohub"
       },
       {
-        "author_name": "ines vigan-womas",
-        "author_inst": "institut pasteur de dakar"
+        "author_name": "Patrick  L McAlpine",
+        "author_inst": "Chan Zuckerberg Biohub"
       },
       {
-        "author_name": "koussay dellagi",
-        "author_inst": "Pasteur Network"
+        "author_name": "Joshua Elias",
+        "author_inst": "CZ Biohub: Chan Zuckerberg Biohub"
       },
       {
-        "author_name": "slimane ben miled",
-        "author_inst": "University of Tunis el manar"
+        "author_name": "Judith Frydman",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Raul Andino",
+        "author_inst": "University of California San Francisco"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2023.07.06.547945",
@@ -23677,21 +23564,29 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2023.06.30.23292087",
-    "rel_title": "Pre-pandemic activity on a myalgic encephalomyelitis/chronic fatigue syndrome support forum is highly associated with later activity on a long COVID support forum for a variety of reasons: a mixed methods study.",
+    "rel_doi": "10.1101/2023.06.29.23291797",
+    "rel_title": "Community Antibiotic Prescribing in Patients with COVID-19 Across Three Pandemic Waves: A Population-Based Cohort Study",
     "rel_date": "2023-07-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.30.23292087",
-    "rel_abs": "Encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID share some clinical and social characteristics. We predicted that this would lead to an increased interaction between pre-pandemic members of an ME/CFS online support community and a long COVID community. We performed a mixed-methods retrospective observational study of the Reddit activity of 7,544 users active on Reddits long COVID forum. From among 1600 forums, pre-pandemic activity specifically on a ME/CFS forum is the top predictor of later participation on the long COVID forum versus an acute COVID support forum. In the qualitative portion, motives for this co-participation included seeking mutual support and dual identification with both conditions. Some of this effect may be explained by pre-existing ME/CFS possibly being a risk factor for long COVID and/or SARS-CoV-2 infection being a cause of ME/CFS relapse. The high rate of ME/CFS patients seeking mutual support on a long COVID forum speaks to the longsuffering experience of these patients not feeling heard or respected, and the hope of some ME/CFS patients to gain legitimacy through the publics growing recognition of long COVID.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.29.23291797",
+    "rel_abs": "BackgroundReported changes in antibiotic prescribing during the COVID-19 pandemic have focused on hospital prescribing or community population trends. Community antibiotic prescribing for individuals with COVID-19 are less well described.\n\nMethodsData covering a complete geographic population ([~]800,000) were utilised. SARS-CoV-2 virus test results from February 1, 2020-March 31, 2022 were included. Anonymised data were linked to prescription data +/-28 days of the test, GP data for high-risk comorbidities, and demographic data. Multivariate binary logistic regression examined associations between patient factors and the odds of antibiotic prescription.\n\nResultsData included 768,206 tests for 184,954 individuals, identifying 16,240 COVID-19 episodes involving 16,025 individuals. There were 3,263 antibiotic prescriptions +/-28 days for 2,385 patients. 35.6% of patients had a prescription only before the test date, 52.5% of patients after, and 11.9% before and after. Antibiotic prescribing reduced over time: 20.4% of episodes in wave one, 17.7% in wave two, and 12.0% in wave three. In multivariate logistic regression, being female (OR 1.31, 95% CI 1.19,1.45), older (OR 3.02, 95% CI 2.50, 3.68 75+ vs <25 years), having a high-risk comorbidity (OR 1.45, 95% CI 1.31, 1.61), a hospital admission +/-28 days of an episode (OR 1.58, 95% CI 1.42, 1.77), and health board region (OR 1.14, 95% CI 1.03, 1.25, board B versus A) increased the odds of receiving an antibiotic.\n\nConclusionCommunity antibiotic prescriptions in COVID-19 episodes were uncommon in this population and likelihood was associated with patient factors. The reduction over pandemic waves may represent increased knowledge regarding COVID-19 treatment and/or evolving symptomatology.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "William U Meyerson",
-        "author_inst": "Duke University Health System"
+        "author_name": "Laura Ciaccio",
+        "author_inst": "Division of Population Health and Genomics, School of Medicine, University of Dundee"
       },
       {
-        "author_name": "Rick H Hoyle",
-        "author_inst": "Duke University"
+        "author_name": "Peter T Donnan",
+        "author_inst": "Division of Population Health and Genomics, School of Medicine, University of Dundee"
+      },
+      {
+        "author_name": "Benjamin J Parcell",
+        "author_inst": "Department of Medical Microbiology, Ninewells Hospital and School of Medicine"
+      },
+      {
+        "author_name": "Charis A Marwick",
+        "author_inst": "Division of Population Health and Genomics, School of Medicine, University of Dundee"
       }
     ],
     "version": "1",
@@ -26011,55 +25906,55 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2023.06.27.546790",
-    "rel_title": "A human primary airway microphysiological system infected with SARS-CoV-2 distinguishes the treatment efficacy between nirmatrelvir and repurposed compounds fluvoxamine and amodiaquine",
+    "rel_doi": "10.1101/2023.06.28.23291948",
+    "rel_title": "Targeting Multiple Conserved T-Cell Epitopes for Protection against COVID-19 Moderate-Severe Disease by a Pan-Sarbecovirus Vaccine",
     "rel_date": "2023-06-28",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.27.546790",
-    "rel_abs": "The COVID-19 pandemic necessitated a rapid mobilization of resources toward the development of safe and efficacious vaccines and therapeutics. Finding effective treatments to stem the wave of infected individuals needing hospitalization and reduce the risk of adverse events was paramount. For scientists and healthcare professionals addressing this challenge, the need to rapidly identify medical countermeasures became urgent, and many compounds in clinical use for other indications were repurposed for COVID-19 clinical trials after preliminary preclinical data demonstrated antiviral activity against SARS-CoV-2. Two repurposed compounds, fluvoxamine and amodiaquine, showed efficacy in reducing SARS-CoV-2 viral loads in preclinical experiments, but ultimately failed in clinical trials, highlighting the need for improved predictive preclinical tools that can be rapidly deployed for events such as pandemic emerging infectious diseases. The PREDICT96-ALI platform is a high-throughput, high-fidelity microphysiological system (MPS) that recapitulates primary human tracheobronchial tissue and supports highly robust and reproducible viral titers of SARS-CoV-2 variants Delta and Omicron. When amodiaquine and fluvoxamine were tested in PREDICT96-ALI, neither compound demonstrated an antiviral response, consistent with clinical outcomes and in contrast with prior reports assessing the efficacy of these compounds in other human cell-based in vitro platforms. These results highlight the unique prognostic capability of the PREDICT96-ALI proximal airway MPS to assess the potential antiviral response of lead compounds.",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.28.23291948",
+    "rel_abs": "BackgroundMost of current approved vaccines, based on a Spike-only as single immunogen, fall short of producing a full-blown T-cell immunity. SARS-CoV-2 continues to evolve with ever-emergent higher-contagious mutants that may take a turn going beyond Omicron to bring about a new pandemic outbreak. New recombinant SARS-CoV-2 species could be man-made through genetic manipulation to infect systemically. Development of composition-innovated, pan-variant COVID-19 vaccines to prevent from hospitalization and severe disease, and to forestall the next pandemic catastrophe, is an urgent global objective.\n\nMethods and findingsIn a retrospective, e-questionnaire Observational Study, extended from a clinical Phase-2 trial conducted in Taiwan, during the prime time of Omicron outbreak dominated by BA.2 and BA.5 variants, we investigated the preventive effects against COVID-19 moderate-severe disease (hospitalization and ICU admission) by a pan-Sarbecovirus vaccine UB-612 that targets monomeric S1-RBD-focused subunit protein and five designer peptides comprising sequence-conserved, non-mutable helper and cytotoxic T lymphocyte (Th/CTL) epitopes derived from Spike (S2), Membrane (M) and Nucleocapsid (N) proteins. Per UB-612 vaccination, there were no hospitalization and ICU admission cases (0% rate, 6 months after Omicron outbreak) reported [&ge;]14 months post-2nd dose of primary series, and [&ge;]10 months post-booster (3rd dose), to which the potent memory cytotoxic CD8 T cell immunity may be the pivotal in control of the infection disease severity. Six months post-booster, the infection rate (asymptomatic and symptomatic mild) was only 1.2%, which increased to 27.8% observed [&ge;]10 months post-booster. The notable protection effects are in good alignment with a preliminary Phase-3 heterologous booster trial report showing that UB-612 can serve as a competent booster substitute for other EUA-approved vaccine platforms to enhance their seroconversion rate and viral-neutralizing titer against Omicron BA.5.\n\nConclusionsUB-612, a universal multitope vaccine promoting full-blown T cell immunity, may work as a competent primer and booster for persons vulnerable to Sarbecovirus infection.\n\nTrial RegistrationClinicalTrials.gov ID: NCT04773067.\n\nAUTHOR SUMMARYA COVID-19 vaccine based on a Spike-only single immunogen would fall short of producing a full-blown, escape-proof T cell immunity. In Omicron era plagued with ever-evolving and higher-contagious SARS-CoV-2 mutants, immune antibodies against variants beyond BA.5 are seen on a cliff drop, rendering the viral-neutralizing titer strength an increasingly less relevant immunity parameter. The true, urgent issue at heart in vaccine development has not been updating variant component to increase antibody titer for prevention of infection, but to validate universal vaccines that would have a potential to head off hospitalization, severe disease and ultimately reinfection altogether, and so to forestall a new catastrophe of pandemic outbreak. To reach the ideal goals, a universal vaccine able to produce potent, broadly recognizing and durable memory T cell immunity would be essential. UB-612, a pan-Sarbecovirus T cell immunity-promoting mutitope vaccine, has been shown to provide strong and long-lasting [&ge;]10 month protective effect against COVID-19 moderate-severe disease (0% cases of hospitalization and ICU admission). UB-612 is a unique S1-RBD subunit protein vaccine armed with five designer peptides comprising sequence-conserved helper and cytotoxic T lymphocyte (Th/CTL) epitopes derived from Spike (S2x3), Membrane (M) and Nucleocapsid (N) proteins across Sarbecovirus species.",
     "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Landys Lopez Quezada",
-        "author_inst": "Draper"
+        "author_name": "Chang Yi Wang",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Felix Mba Medie",
-        "author_inst": "Draper"
+        "author_name": "Be-Sheng Kuo",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Elizabeth P. Gabriel",
-        "author_inst": "Draper"
+        "author_name": "Yu-Hsiang Lee",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Rebeccah J. Luu",
-        "author_inst": "Draper"
+        "author_name": "Yu-Hsin Ho",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Logan D. Rubio",
-        "author_inst": "Draper"
+        "author_name": "Yi-Hua Pan",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Thomas J. Mulhern",
-        "author_inst": "Draper"
+        "author_name": "Ya-Ting Yang",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Jeffrey T. Borenstein",
-        "author_inst": "Draper"
+        "author_name": "Hsi-Chi Chang",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Christine R. Fisher",
-        "author_inst": "Draper"
+        "author_name": "Lin-Fang Fu",
+        "author_inst": "UBI Asia"
       },
       {
-        "author_name": "Ashley L Gard",
-        "author_inst": "Draper"
+        "author_name": "Wen-Jiun Peng",
+        "author_inst": "UBI Asia"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "bioengineering"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2023.06.26.23291891",
@@ -27449,41 +27344,29 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2023.06.20.23291649",
-    "rel_title": "Association between post-infection COVID-19 vaccination and symptom severity of post COVID-19 condition among patients on Bonaire, Caribbean Netherlands: a retrospective cohort study",
+    "rel_doi": "10.1101/2023.06.20.23291688",
+    "rel_title": "Evaluating the buffering role of perceived social support and coping resources against the adult mental health impacts of COVID-19 psychosocial stress: a cross-sectional study in South Africa",
     "rel_date": "2023-06-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.20.23291649",
-    "rel_abs": "ObjectivesIn this retrospective cohort study, we aimed to investigate symptom severity change following COVID-19 vaccination among post COVID-19 condition (PCC) patients on Bonaire.\n\nMethodsSymptomatic cases who tested positive for SARS-CoV-2 between the start of the pandemic and 1 October 2021, were unrecovered on the interview day and unvaccinated prior to infection were identified from the national case registry. Patients were interviewed by telephone between 15 November and 4 December 2021 about sociodemographic factors, pre-pandemic health, COVID-19 symptoms and vaccination status. We compared symptom severity change between the acute and post-acute disease phase (>4 weeks after disease onset) of 14 symptoms on a five-point Likert scale for 36 PCC patients having received at least one dose of the BNT162 (BioNTech/Pfizer) vaccine and 11 patients who remained unvaccinated, using separate multiple linear regression models.\n\nResultsMost common post-acute symptoms included fatigue (81%), reduced physical endurance (79%), and reduced muscle strength (64%). Post-infection vaccination was significantly associated with reduced severity of heart palpitations, after adjusting for acute phase severity and duration of illness ({beta} 0.60, 95% CI 0.18-1.02). We did not find a statistically significant association with symptom severity change for other, more prevalent symptoms.\n\nConclusionsLarger prospective studies are needed to confirm our observation in a small study population that post-infection COVID-19 vaccination was associated with reduced severity of heart palpitations among those with this symptom self-attributed to SARS-CoV-2 infection.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.20.23291688",
+    "rel_abs": "ObjectiveswGrowing evidence has highlighted the global mental health impacts of the COVID- 19 pandemic and lockdown, particularly in societies with pre-existing socioeconomic adversities and public health concerns. Despite the sudden and prolonged nature of many psychosocial stressors during the pandemic, recent studies have shown that communities utilized several coping mechanisms to buffer the mental health consequences of COVID-related stress. This paper examines the extent to which coping resources and social support buffered against the mental health effects of COVID-19 psychosocial stress among adults in South Africa.\n\nMaterials & MethodsAdult participants (n=117) completed an online survey during the second and third waves of the COVID-19 pandemic in South Africa (January-July 2021), which assessed experiences of stress, coping resources, social support, and four mental health outcomes: depression, anxiety, post-traumatic stress disorder, and bipolar disorder. Moderation analyses examined the potential buffering role of coping resources and social support against the mental health effects of COVID-19 stress.\n\nResultsAdults reported elevated rates of psychiatric symptoms. Coping resources buffered against the poor mental health effects of COVID-19 psychosocial stress, whereas perceived social support did not significantly moderate the association between COVID-19 stress and adult mental health.\n\nDiscussionThese results suggest that adults in our sample utilized a variety of coping resources to protect their mental health against psychosocial stress experienced during the COVID-19 lockdown and pandemic in South Africa. Additionally, existing mental health conditions and strained social relationships may have attenuated the potential stress-buffering effect of perceived social support on adult mental health.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Danytza Berry",
-        "author_inst": "National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, The Netherlands"
-      },
-      {
-        "author_name": "Thomas Dalhuisen",
-        "author_inst": "National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, The Netherlands"
-      },
-      {
-        "author_name": "Giramin Marchena",
-        "author_inst": "Public Health Department Bonaire, Public Entity of Bonaire, Caribbean Netherlands"
-      },
-      {
-        "author_name": "Ivo Tiemessen",
-        "author_inst": "Mobilito, Bonaire, Caribbean Netherlands"
+        "author_name": "Andrew  Wooyoung Kim",
+        "author_inst": "University of California Berkeley"
       },
       {
-        "author_name": "Eveline Geubbels",
-        "author_inst": "National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, The Netherlands"
+        "author_name": "Someleze Swana",
+        "author_inst": "Witwatersrand Health Sciences: University of the Witwatersrand Johannesburg Faculty of Health Sciences"
       },
       {
-        "author_name": "Loes Jaspers",
-        "author_inst": "Public Health Department Bonaire, Public Entity of Bonaire, Caribbean Netherlands"
+        "author_name": "Mallika Sarma",
+        "author_inst": "Johns Hopkins Medical Institutions: Johns Hopkins Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -29379,75 +29262,35 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2023.06.16.23291449",
-    "rel_title": "Timing and Predictors of Loss of Infectivity among Healthcare Workers with Primary and Recurrent COVID-19: a Prospective Observational Cohort Study",
-    "rel_date": "2023-06-18",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.16.23291449",
-    "rel_abs": "BackgroundThere is a need to understand the duration of infectivity of primary and recurrent COVID-19 and identify predictors of loss of infectivity.\n\nMethodsProspective observational cohort study with serial viral culture, rapid antigen detection test (RADT) and RT-PCR on nasopharyngeal specimens of healthcare workers with COVID-19. The primary outcome was viral culture positivity as indicative of infectivity. Predictors of loss of infectivity were determined using multivariate regression model. The performance of the US CDC criteria (fever resolution, symptom improvement and negative RADT) to predict loss of infectivity was also investigated.\n\nResults121 participants (91 female [79.3%]; average age, 40 years) were enrolled. Most (n=107, 88.4%) had received [&ge;]3 SARS-CoV-2 vaccine doses, and 20 (16.5%) had COVID-19 previously. Viral culture positivity decreased from 71.9% (87/121) on day 5 of infection to 18.2% (22/121) on day 10. Participants with recurrent COVID-19 had a lower likelihood of infectivity than those with primary COVID-19 at each follow-up (day 5 OR, 0.14; p<0.001]; day 7 OR, 0.04; p=0.003]) and were all non-infective by day 10 (p=0.02). Independent predictors of infectivity included prior COVID-19 (adjusted OR [aOR] on day 5, 0.005; p=0.003), a RT-PCR Ct value <23 (aOR on day 5, 22.75; p<0.001), but not symptom improvement or RADT result.\n\nThe CDC criteria would identify 36% (24/67) of all non-infectious individuals on Day 7. However, 17% (5/29) of those meeting all the criteria had a positive viral culture.\n\nConclusionsInfectivity of recurrent COVID-19 is shorter than primary infections. Loss of infectivity algorithms could be optimized.",
-    "rel_num_authors": 14,
+    "rel_doi": "10.1101/2023.06.15.545172",
+    "rel_title": "SARS-CoV-2 Delta Variant Remains Viable in Environmental Biofilms found in Meat Packaging Plants",
+    "rel_date": "2023-06-16",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.15.545172",
+    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a coronavirus that directly infects human airway epithelial cells and caused the COVID-19 pandemic. At the start of the pandemic in 2020, meat-packaging plants saw a surge in SARS-CoV-2 cases, which forced many to temporarily close. To determine why SARS-CoV-2 appears to thrive specifically well in meat packaging plants, we used SARS-CoV-2 Delta variant and meat packaging plant drain samples to develop mixed-species biofilms on materials commonly found within meat packaging plants (stainless steel (SS), PVC, and ceramic tile). Our data provides evidence that SARS-CoV-2 Delta variant remained viable on all the surfaces tested with and without an environmental biofilm. We observed that SARS-CoV-2 Delta variant was able to remain infectious with each of the environmental biofilms, however, we detected a significant reduction in viability post-exposure to Plant B biofilm on SS, PVC, and on ceramic tile chips, and to Plant C biofilm on SS and PVC chips. The numbers of viable SARS-CoV-2 Delta viral particles was 1.81 - 4.57-fold high than the viral inoculum incubated with the Plant B and Plant C environmental biofilm on SS, and PVC chips. We did not detect a significant difference in viability when SARS-CoV-2 Delta variant was incubated with the biofilm obtained from Plant A on any of the materials tested and SARS-CoV-2 Delta variant had higher plaque numbers when inoculated with Plant C biofilm on tile chips, with a 2.75-fold difference compared to SARS-CoV-2 Delta variant on tile chips by itself. In addition, we detected an increase in the biofilm biovolume in response to SARS-CoV-2 Delta variant which is also a concern for food safety due to the potential for foodborne pathogens to respond likewise when they come into contact with the virus. These results indicate a complex virus-environmental biofilm interaction which correlates to the different bacteria found in each biofilm. Our results also indicate that there is the potential for biofilms to protect SARS-CoV-2 from disinfecting agents and remaining prevalent in meat packaging plants. With the highly infectious nature of some SARS-CoV-2 variants such as Delta, and more so with the Omicron variant, even a minimal amount of virus could have serious health implications for the spread and reoccurrence of SARS-CoV-2 outbreaks in meat packaging plants.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Stefka Dzieciolowska",
-        "author_inst": "McGill University Faculty of Medicine, Montreal, Canada"
-      },
-      {
-        "author_name": "Hugues Charest",
-        "author_inst": "Laboratoire de Sante Publique du Quebec, Sainte-Anne-de-Bellevue, Canada"
-      },
-      {
-        "author_name": "Tonya Roy",
-        "author_inst": "Laboratoire de Sante Publique du Quebec, Sainte-Anne-de-Bellevue, Canada"
-      },
-      {
-        "author_name": "Judith Fafard",
-        "author_inst": "Laboratoire de Sante Publique du Quebec, Institut national de sante publique du Quebec"
-      },
-      {
-        "author_name": "Sara Carazo",
-        "author_inst": "Institut national de sante publique du Quebec"
-      },
-      {
-        "author_name": "Ines Levade",
-        "author_inst": "Laboratoire de Sante Publique du Quebec, Sainte-Anne-de-Bellevue, Canada"
-      },
-      {
-        "author_name": "Jean Longtin",
-        "author_inst": "Centre hospitalier universitaire (CHU) de Quebec"
-      },
-      {
-        "author_name": "Leighanne Parkes",
-        "author_inst": "Jewish General Hospital Sir Mortimer B. Davis, Montreal, Canada"
-      },
-      {
-        "author_name": "Sylvie Nancy Beaulac",
-        "author_inst": "Laboratoire de Sante Publique du Quebec, Sainte-Anne-de-Bellevue, Canada"
-      },
-      {
-        "author_name": "Jasmin Villeneuve",
-        "author_inst": "Institut National de Sante Publique du Quebec, Quebec City, Canada"
-      },
-      {
-        "author_name": "Patrice Savard",
-        "author_inst": "Centre Hospitalier de Universite de Montreal (CHUM) and CHUM Research Center, Montreal, Canada"
+        "author_name": "Sapna Chitlapilly Dass",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "Jacques Corbeil",
-        "author_inst": "Universite Laval, Quebec City, Canada"
+        "author_name": "Austin B Featherstone",
+        "author_inst": "Texas A&M"
       },
       {
-        "author_name": "Gaston De Serres",
-        "author_inst": "Institut National de Sante Publique du Quebec, Quebec City, Canada"
+        "author_name": "Arnold JTM Mathijssen",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "Yves Longtin",
-        "author_inst": "Jewish General Hospital Sir Mortimer B. Davis, Montreal, Canada"
+        "author_name": "Amanda C Brown",
+        "author_inst": "Tarleton State University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "type": "new results",
+    "category": "ecology"
   },
   {
     "rel_doi": "10.1101/2023.06.16.545251",
@@ -31189,77 +31032,61 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.06.09.23291201",
-    "rel_title": "SARS-CoV-2 seroprevalence in pregnant women during the first three COVID-19 waves in The Gambia",
+    "rel_doi": "10.1101/2023.06.12.23291266",
+    "rel_title": "Global seasonal activities of respiratory syncytial virus before the COVID-19 pandemic: a systematic review",
     "rel_date": "2023-06-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.09.23291201",
-    "rel_abs": "ObjectivesSARS-CoV-2 transmission in Sub-Saharan Africa has probably been underestimated. Population-based seroprevalence studies are needed to determine the extent of transmission in the continent.\n\nMethodsBlood samples from a cohort of Gambian pregnant women were tested for SARS-CoV-2 total IgM/IgG before (Pre-pandemic1: October-December 2019 and Pre-pandemic2: February-June 2020) and during the pandemic (Post-wave1: October-December 2020, Post-wave2: May-June 2021; and Post-wave3: October-December 2021). Samples positive for total SARS-CoV-2 IgM/IgG were tested for protein-specific antibodies.\n\nResultsSARS-CoV-2 total IgM/IgG seroprevalence was 0.9% 95%CI (0.2, 4.9) in Pre-pandemic1; 4.1% (1.4, 11.4) in Pre-pandemic2; 31.1% (25.2, 37.7) in Post-wave1; 62.5% (55.8, 68.8) in Post-wave2 and 90.0% (85.1, 93.5) in Post-wave3. S-protein IgG and NCP-protein IgG seroprevalence also increased at each Post-wave period. Although S-protein IgG and NCP-protein IgG seroprevalence was similar at Post-wave1, S-protein IgG seroprevalence was higher at Post-wave2 and Post-wave3, [prevalence difference (PD) 13.5 (0.1, 26.8) and prevalence ratio (PR) 1.5 (1.0, 2.3) in Post-wave2; and 22.9 (9.2, 36.6) and 1.4 (1.1, 1.8) in Post-wave3 respectively, p<0.001].\n\nConclusionSARS-CoV-2 transmission in The Gambia during the first three COVID-19 waves was high, differing significantly from official numbers of COVID-19 cases reported. Our findings are important for policy makers in managing the near-endemic COVID-19.\n\nHighlightsO_LIHigh specificity of the IgM/IgG SARS-CoV-2 test using samples collected prepandemic\nC_LIO_LIVery high (>90%) SARS-CoV-2 seroprevalence after third COVID-19 wave in The Gambia\nC_LIO_LIHigh SARS-CoV-2 transmission contrasts with low number of COVID-19 reported cases\nC_LI",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.12.23291266",
+    "rel_abs": "BackgroundVaried seasonal patterns of respiratory syncytial virus (RSV) have been reported worldwide. We aimed to review the patterns of RSV activity globally before the COVID-19 pandemic and to explore factors potentially associated with RSV seasonality.\n\nMethodsWe conducted a systematic review on articles identified in PubMed reporting RSV seasonality based on data collected before 1 January 2020. Information on the timing of the start, peak, and end of an RSV season, study location, study period, and details in study methods were extracted. RSV seasonal patterns were examined by geographic location, calendar month, analytic method and meteorological factors including temperature and absolute humidity. Correlation and regression analyses were conducted to explore the relationship between RSV seasonality and study methods and characteristics of study locations.\n\nResultsRSV seasons were reported in 209 articles published in 1973-2023 for 317 locations in 77 countries. Variations were identified in types of data, data collection and analytical methods across the studies. Regular RSV seasons were similarly reported in countries in temperate regions, with highly variable seasons identified in subtropical and tropical countries. Durations of RSV seasons were relatively longer in subtropical and tropical regions than from temperate regions. Longer durations of RSV seasons were associated with a higher daily average mean temperature and daily average mean absolute humidity.\n\nConclusionsThe global seasonal patterns of RSV provided important information for optimizing interventions against RSV infection. Heterogeneity in study methods highlighted the importance of developing and applying standardized approaches in RSV surveillance and data reporting.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Ramatoulie E. Janha",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
-      },
-      {
-        "author_name": "Alasana Bah",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
-      },
-      {
-        "author_name": "Hawanatu Jah",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
-      },
-      {
-        "author_name": "Fatima Touray",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
-      },
-      {
-        "author_name": "Yahaya Idris",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Songwei Shan",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Saikou Keita",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Weixin Zhang",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Yassin Gaye",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical"
+        "author_name": "Huizhi Gao",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Samba Jallow",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Pei-Yu Huang",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Tisbeh Faye-Joof",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Zhanwei Du",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Baboucarr Njie",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Yuan Bai",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Rachel Craik",
-        "author_inst": "Department of Women and Childrens Health, School of Life Course Science, Faculty of Life Sciences and Medicine, Kings College London, 5th Floor, Becket House, 1"
+        "author_name": "Yiu-Chung Lau",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Nuredin I Mohammed",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Dongxuan Chen",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Peter von Dadelszen",
-        "author_inst": "Department of Women and Childrens Health, School of Life Course Science, Faculty of Life Sciences and Medicine, Kings College London, 5th Floor, Becket House, 1"
+        "author_name": "Eric HY Lau",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Umberto D'Alessandro",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Joshua Nealon",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Anna Roca",
-        "author_inst": "Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia"
+        "author_name": "Peng Wu",
+        "author_inst": "The University of Hong Kong"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -32783,131 +32610,35 @@
     "category": "rehabilitation medicine and physical therapy"
   },
   {
-    "rel_doi": "10.1101/2023.06.06.23290826",
-    "rel_title": "OpenSAFELY: The impact of COVID-19 on azathioprine, leflunomide, and methotrexate monitoring, and factors associated with change in monitoring rate.",
+    "rel_doi": "10.1101/2023.06.06.23290982",
+    "rel_title": "Estimating the effectiveness of COVID-19 vaccination against COVID-19 hospitalisation and death: a cohort study based on the 2021 Census, England.",
     "rel_date": "2023-06-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.06.23290826",
-    "rel_abs": "BackgroundThe COVID-19 pandemic created unprecedented pressure on healthcare services. This study aimed to investigate if disease-modifying anti-rheumatic drug (DMARD) safety monitoring was affected during the COVID-19 pandemic.\n\nMethodsA population-based cohort study was conducted with the approval of NHS England, using the OpenSAFELY platform to access electronic health record data from 24{middle dot}2 million patients registered at general practices using TPPs SystmOne software. Patients were included for further analysis if prescribed azathioprine, leflunomide, or methotrexate between November 2019 and July 2022. Outcomes were assessed as monthly trends and variation between various sociodemographic and clinical groups for adherence with standard safety monitoring recommendations.\n\nFindingsAn acute increase in the rate of missed monitoring occurred across the study population (+12{middle dot}4 percentage points) when lockdown measures were implemented in March 2020. This increase was more pronounced for some patient groups (70-79 year-olds: +13{middle dot}7 percentage points; females: +12{middle dot}8 percentage points), regions (North West: +17{middle dot}0 percentage points), medications (Leflunomide: +20{middle dot}7 percentage points), and monitoring tests (Blood Pressure: +24{middle dot}5 percentage points). Missed monitoring rates decreased substantially for all groups by July 2022. Substantial and consistent differences were observed in overall missed monitoring rates between several groups throughout the study.\n\nInterpretationDMARD monitoring rates temporarily deteriorated during the COVID-19 pandemic. Deterioration coincided with the onset of lockdown measures, with monitoring rates recovering rapidly as lockdown measures were eased. Differences observed in monitoring rates between medications, tests, regions, and patient groups, highlight opportunities to tackle potential inequalities in the provision or uptake of monitoring services. Further research should aim to evaluate the causes of the differences identified between groups.\n\nFundingNone.\n\nResearch in context Evidence before this studyDisease-modifying anti-rheumatic drugs (DMARDs) are immunosuppressive and/or immunomodulatory drugs, which carry risks of serious adverse effects such as; gastrointestinal, renal, hepatic, and pulmonary toxicity; myelosuppression; and increased susceptibility to infection. To mitigate these safety risks, national safety guidance recommends that patients taking these drugs receive regular monitoring. We searched PubMed, Web of Science and Scopus for studies published between database inception and July 28th, 2022, using the terms ([covid-19] AND [monitoring OR shared care OR dmard OR outcome factors] AND [primary care]), with no language restrictions. Studies that investigated the effect of the COVID-19 pandemic on healthcare services were identified. One key study in England showed disruption to various monitoring services in primary care had occurred during the pandemic. Another English study highlighted a disproportionate impact of the COVID-19 pandemic on health outcomes in certain groups.\n\nAdded value of this studyPrior to this study knowledge of how high-risk drugs, such as DMARDs, were affected by the COVID-19 pandemic was limited. This study reports the impact of COVID-19 on the safety monitoring of DMARDs. Moreover, it reports variation in DMARD monitoring rates between demographic, clinical and regional subgroups, which has not yet been described. This is enabled through use of the OpenSAFELY platform, which provides secure access to pseudonymised primary care patient records in England for the purposes of analysing the COVID-19 pandemic impact.\n\nImplications of all the available evidenceDMARD monitoring rates transiently deteriorated during the COVID-19 pandemic, consistent with previous research on other monitoring tests. Deterioration coincided with the onset of lockdown measures, with performance recovering rapidly as lockdown measures were eased. Differences observed in monitoring rates between demographic, clinical and regional subgroups highlight opportunities to identify and tackle potential inequalities in the provision or uptake of monitoring services. Further research should aim to evaluate the causes of the differences identified between groups, and establish the clinical relevance of missed monitoring. Several studies have demonstrated the capability of the OpenSAFELY platform as a secure and efficient approach for analysing NHS primary care data at scale, generating meaningful insights on service delivery.",
-    "rel_num_authors": 28,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.06.23290982",
+    "rel_abs": "ObjectiveTo estimate the effectiveness of COVID-19 vaccination against hospitalisation for COVID-19 and death involving COVID-19 in England using linked population level data sources including the 2021 Census.\n\nDesignRetrospective cohort study.\n\nSettingEngland, 21 March 2021 to 20 March 2022.\n\nParticipantsIndividuals alive and aged 16+ on 21 March 2021, resident in England, enumerated in the 2021 Census as a usual resident, and able to link to an NHS number. A sample of 583,840 individuals was used for the analysis.\n\nExposuresCOVID-19 vaccination: first dose, second dose and third dose/first booster dose, with categories for time since each dose.\n\nMain outcome measuresHospitalisation for COVID-19 or death involving COVID-19. An adjusted Cox proportional hazard model was used to estimate the hazard ratio for the outcomes for vaccinated participants for different doses and time since dose compared to unvaccinated individuals. Vaccine effectiveness was estimated as (1-hazard ratio)x100%. A control outcome of non-COVID-19 death was also assessed.\n\nResultsVaccine effectiveness against hospitalisation for COVID-19 was 52.1% (95% confidence interval 51.3% to 52.8%) for a first dose, 55.6% (55.2% to 56.1%) for a second dose and 77.6% (77.3% to 78.0%) for a third dose, with a decrease in vaccine effectiveness 3+ months after the third dose.\n\nVaccine effectiveness against COVID-19 mortality was 58.7% (52.7% to 63.9%) for a first dose, 88.5% (87.5% to 89.5%) for a second dose and 93.2% (92.9% to 93.5%) for a third dose, with evidence of waning 3+ months after the second and third doses.\n\nFor the second dose, which is the most comparable across the different time-periods, vaccine effectiveness was higher against COVID-19 hospitalisation but slightly lower against COVID-19 mortality in the Omicron dominant period than the period before the Omicron variant became dominant. Vaccine effectiveness against both COVID-19 hospitalisation and mortality was higher in general for mRNA vaccines than non mRNA vaccines, however this could be influenced by the different populations given each vaccine vector. Non-zero VE against non-COVID-19 mortality indicates that residual confounding may impact the results, despite the inclusion of up-to-date socio-demographic adjustments and various sources of health data, with possible frailty bias, confounding by indication and a healthy vaccinee effect observed.\n\nConclusionsThe vaccine effectiveness estimates show increased protection with number of doses and a high level of protection against both COVID-19 hospitalisation and mortality for the third/booster dose, as would be expected from previous research. However, despite the various sources of health data used to adjust the models, the estimates for different breakdowns and for non-COVID-19 mortality expose residual confounding by health status, which should be considered when interpreting estimates of vaccine effectiveness.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "- The OpenSAFELY Collaborative",
-        "author_inst": ""
-      },
-      {
-        "author_name": "Andrew D Brown",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Louis Fisher",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Helen J Curtis",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Milan Wiedemann",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "William J Hulme",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Lisa EM Hopcroft",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Christine Cunningham",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Victoria Speed",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Ruth E Costello",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "James B Galloway",
-        "author_inst": "King's College London"
-      },
-      {
-        "author_name": "Mark D Russell",
-        "author_inst": "King's College London"
-      },
-      {
-        "author_name": "Katie Bechman",
-        "author_inst": "King's College London"
-      },
-      {
-        "author_name": "Zeyneb Kurt",
-        "author_inst": "Northumbria University"
-      },
-      {
-        "author_name": "Richard Croker",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Christopher Wood",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Alex J Walker",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Andrea L Schaffer",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Seb CJ Bacon",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Amir Mehrkar",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "George Hickman",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Chris Bates",
-        "author_inst": "TPP"
-      },
-      {
-        "author_name": "Jonathan Cockburn",
-        "author_inst": "TPP"
-      },
-      {
-        "author_name": "John Parry",
-        "author_inst": "TPP"
-      },
-      {
-        "author_name": "Frank Hester",
-        "author_inst": "TPP"
+        "author_name": "Charlotte Bermingham",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Sam Harper",
-        "author_inst": "TPP"
+        "author_name": "Vahe Nafilyan",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Ben Goldacre",
-        "author_inst": "University of Oxford"
+        "author_name": "Nick Andrews",
+        "author_inst": "UK Health Security Agency"
       },
       {
-        "author_name": "Brian MacKenna",
-        "author_inst": "University of Oxford"
+        "author_name": "Owen Gethings",
+        "author_inst": "Office for National Statistics"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "primary care research"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.06.06.23291015",
@@ -34661,49 +34392,453 @@
     "category": "pain medicine"
   },
   {
-    "rel_doi": "10.1101/2023.05.31.23290799",
-    "rel_title": "A quantitative evaluation of the impact of vaccine roll-out rate and coverage on reducing deaths from COVID-19: a counterfactual study on the impact of the delayed vaccination programme in Iran",
+    "rel_doi": "10.1101/2023.05.30.23290732",
+    "rel_title": "Challenges of COVID-19 Case Forecasting in the US, 2020-2021",
     "rel_date": "2023-06-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.31.23290799",
-    "rel_abs": "Vaccination has been a crucial factor in the fight against COVID-19 because of its effectiveness in suppressing virus circulation, lowering the risk of severe disease, and ultimately saving lives. Many countries with an early and rapid distribution of COVID-19 vaccines performed much better in reducing their total number of deaths than those with lower coverage and slower roll-out pace. However, we still do not know how many more deaths could have been averted if countries with slower vaccine roll-outs followed the same rate as countries with earlier and faster distribution of vaccines. Here, we investigated counterfactual scenarios for the number of avertable COVID-19 deaths in a given country based on other countries vaccine roll-out rates. As a case study, we compared Iran to eight model countries with similar income brackets and dominant COVID-19 vaccine types. Our analysis revealed that faster roll-outs were associated with higher numbers of averted deaths. While Irans percentage of fully vaccinated individuals would have been similar to Bangladesh, Nepal, Sri Lanka, and Turkey under counterfactual roll-out rates, adopting Turkeys rates could have averted up to 50,000 more deaths, whereas following Bangladeshs rates could have led to up to 52,800 additional losses of lives in Iran. Notably, a counterfactual scenario based on Argentinas early but slow roll-out rate resulted in a smaller number of averted deaths in Iran, up to 12,600 more individuals. Following Montenegros or Bolivias model of faster per capita roll-out rates for Iran could have resulted in more averted deaths in older age groups, particularly during the Alpha and Delta waves, despite their lower overall coverage. Also, following Bahrains model as an upper bound benchmark, Iran could have averted 75,300 deaths throughout the pandemic, primarily in the >50 age groups. This study provides insights into future decisions on the management of infectious disease epidemics through vaccination strategies by comparing the relative performance of different countries in terms of their timing, pace, and coverage of vaccination in preventing COVID-19 deaths.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.30.23290732",
+    "rel_abs": "During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naive baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.\n\nAuthor SummaryAs SARS-CoV-2 began to spread throughout the world in early 2020, modelers played a critical role in predicting how the epidemic could take shape. Short-term forecasts of epidemic outcomes (for example, infections, cases, hospitalizations, or deaths) provided useful information to support pandemic planning, resource allocation, and intervention. Yet, infectious disease forecasting is still a nascent science, and the reliability of different types of forecasts is unclear. We retrospectively evaluated COVID-19 case forecasts, which were often unreliable. For example, forecasts did not anticipate the speed of increase in cases in early winter 2020. This analysis provides insights on specific problems that could be addressed in future research to improve forecasts and their use. Identifying the strengths and weaknesses of forecasts is critical to improving forecasting for current and future public health responses.",
+    "rel_num_authors": 109,
     "rel_authors": [
       {
-        "author_name": "Mahan Ghafari",
-        "author_inst": "University of Oxford"
+        "author_name": "Velma Lopez",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Sepanta Hosseinpour",
-        "author_inst": "University of Queensland"
+        "author_name": "Estee  Y Cramer",
+        "author_inst": "University of Massachusetts Amherst"
       },
       {
-        "author_name": "Mohammad Saeid Rezaee-Zavareh",
-        "author_inst": "Middle East Liver Diseases (MELD) Center"
+        "author_name": "Robert Pagano",
+        "author_inst": "Unafilliated"
       },
       {
-        "author_name": "Stefan Dascalu",
-        "author_inst": "University of Oxford"
+        "author_name": "John  M Drake",
+        "author_inst": "University of Georgia"
       },
       {
-        "author_name": "Somayeh Rostamian",
-        "author_inst": "Imperial College London"
+        "author_name": "Eamon  B O'Dea",
+        "author_inst": "University of Georgia"
       },
       {
-        "author_name": "Kiarash Aramesh",
-        "author_inst": "PennWest University"
+        "author_name": "Benjamin  P Linas",
+        "author_inst": "Boston University"
       },
       {
-        "author_name": "Kaveh Madani",
-        "author_inst": "United Nations University Institute for Water, Environment and Health"
+        "author_name": "Turgay Ayer",
+        "author_inst": "Georgia Institute of Technology"
       },
       {
-        "author_name": "Shahram Kordasti",
-        "author_inst": "King's College London"
+        "author_name": "Jade Xiao",
+        "author_inst": "Georgia Institute of Technology"
+      },
+      {
+        "author_name": "Madeline Adee",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Jagpreet Chhatwal",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Mary  A Ladd",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Peter  P Mueller",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Ozden  O Dalgic",
+        "author_inst": "Value Analytics Lab"
+      },
+      {
+        "author_name": "Johannes Bracher",
+        "author_inst": "Karlsruher Institut fur Technologie"
+      },
+      {
+        "author_name": "Tilmann Gneiting",
+        "author_inst": "Heidelberg Institute for Theoretical Studies"
+      },
+      {
+        "author_name": "Anja M\u00fchlemann",
+        "author_inst": "University of Bern: Universitat Bern"
+      },
+      {
+        "author_name": "Jarad Niemi",
+        "author_inst": "Iowa State University"
+      },
+      {
+        "author_name": "Ray  L Evan",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Martha Zorn",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Yuxin Huang",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Yijin Wang",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Aaron Gerding",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Ariane Stark",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Dasuni Jayawardena",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Khoa Le",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Nutcha Wattanachit",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Abdul  H Kanji",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Alvaro  J Castro Rivadeneira",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Sen Pei",
+        "author_inst": "Columbia University Mailman School of Public Health"
+      },
+      {
+        "author_name": "Jeffrey Shaman",
+        "author_inst": "Columbia University Mailman School of Public Health"
+      },
+      {
+        "author_name": "Teresa  K Yamana",
+        "author_inst": "Columbia University Mailman School of Public Health"
+      },
+      {
+        "author_name": "Xinyi Li",
+        "author_inst": "Clemson University"
+      },
+      {
+        "author_name": "Guannan Wang",
+        "author_inst": "William & Mary"
+      },
+      {
+        "author_name": "Lei Gao",
+        "author_inst": "George Mason University"
+      },
+      {
+        "author_name": "Zhiling Gu",
+        "author_inst": "Iowa State University"
+      },
+      {
+        "author_name": "Myungjin Kim",
+        "author_inst": "Kyungpook National University"
+      },
+      {
+        "author_name": "Lily Wang",
+        "author_inst": "George Mason University"
+      },
+      {
+        "author_name": "Yueying Wang",
+        "author_inst": "Amazon"
+      },
+      {
+        "author_name": "Shan Yu",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Daniel  J Wilson",
+        "author_inst": "Federal Reserve Bank San Francisco"
+      },
+      {
+        "author_name": "Samuel  R Tarasewicz",
+        "author_inst": "Federal Reserve Bank San Francisco"
+      },
+      {
+        "author_name": "Brad Suchoski",
+        "author_inst": "IEM"
+      },
+      {
+        "author_name": "Steve Stage",
+        "author_inst": "IEM"
+      },
+      {
+        "author_name": "Heidi Gurung",
+        "author_inst": "IEM"
+      },
+      {
+        "author_name": "Sid Baccam",
+        "author_inst": "IEM"
+      },
+      {
+        "author_name": "Maximilian Marshall",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Lauren Gardner",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Sonia Jindal",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Kristen Nixon",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Joseph  C Lemaitre",
+        "author_inst": "Ecole Polytechnique Federale de Lausanne"
+      },
+      {
+        "author_name": "Juan Dent",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Alison  L Hill",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Joshua Kaminsky",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Elizabeth  C Lee",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Justin Lessler",
+        "author_inst": "UNC-Chapel Hill: The University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Claire  P Smith",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Shaun Truelove",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Matt Kinsey",
+        "author_inst": "Johns Hopkins University Applied Physics Laboratory"
+      },
+      {
+        "author_name": "Katharine Tallaksen",
+        "author_inst": "Johns Hopkins University Applied Physics Laboratory"
+      },
+      {
+        "author_name": "Shelby Wilson",
+        "author_inst": "Johns Hopkins University Applied Physics Laboratory"
+      },
+      {
+        "author_name": "Luke  C Mullany",
+        "author_inst": "Johns Hopkins University Applied Physics Laboratory"
+      },
+      {
+        "author_name": "Lauren Shin",
+        "author_inst": "Johns Hopkins University Applied Physics Laboratory"
+      },
+      {
+        "author_name": "Kaitlin Rainwater-Lovett",
+        "author_inst": "Johns Hopkins University Applied Physics Laboratory"
+      },
+      {
+        "author_name": "Dean Karlen",
+        "author_inst": "University of Victoria"
+      },
+      {
+        "author_name": "Lauren Castro",
+        "author_inst": "Los Alamos National Laboratory"
+      },
+      {
+        "author_name": "Geoffrey Fairchild",
+        "author_inst": "Los Alamos National Laboratory"
+      },
+      {
+        "author_name": "Isaac Michaud",
+        "author_inst": "Los Alamos National Laboratory"
+      },
+      {
+        "author_name": "Dave Osthus",
+        "author_inst": "Los Alamos National Laboratory"
+      },
+      {
+        "author_name": "Alessandro Vespignani",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Matteo Chinazzi",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Jessica  T Davis",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Kunpeng Mu",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Xinyue Xiong",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Ana Pastore y Piontti",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Shun Zheng",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Zhifeng Gao",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Wei Cao",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Jiang Bian",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Chaozhuo Li",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Xing Xie",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Tie-Yan Liu",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Juan Lavista Ferres",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Shun Zhang",
+        "author_inst": "Microsoft Corp"
+      },
+      {
+        "author_name": "Robert Walraven",
+        "author_inst": "Unaffiliated"
+      },
+      {
+        "author_name": "Jinghui Chen",
+        "author_inst": "University of California Los Angeles"
+      },
+      {
+        "author_name": "Quanquan Gu",
+        "author_inst": "University of California Los Angeles"
+      },
+      {
+        "author_name": "Lingxiao Wang",
+        "author_inst": "University of California Los Angeles"
+      },
+      {
+        "author_name": "Pan Xu",
+        "author_inst": "University of California Los Angeles"
+      },
+      {
+        "author_name": "Weitong Zhang",
+        "author_inst": "University of California Los Angeles"
+      },
+      {
+        "author_name": "Difan Zou",
+        "author_inst": "University of California Los Angeles"
+      },
+      {
+        "author_name": "Graham Casey Gibson",
+        "author_inst": "Los Alamos National Laboratory"
+      },
+      {
+        "author_name": "Daniel Sheldon",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Ajitesh Srivastava",
+        "author_inst": "University of Southern California"
+      },
+      {
+        "author_name": "Aniruddha Adiga",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Benjamin Hurt",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Gursharn Kaur",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Bryan Lewis",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Madhav Marathe",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Akhil  S Peddireddy",
+        "author_inst": "Discreet Labs"
+      },
+      {
+        "author_name": "Przemyslaw Porebski",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Srinivasan Venkatramanan",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Lijing Wang",
+        "author_inst": "University of Virginia"
+      },
+      {
+        "author_name": "Pragati  V Prasad",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Alexander  E Webber",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Jo  W Walker",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Rachel  B Slayton",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Matthew Biggerstaff",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Nicholas  G Reich",
+        "author_inst": "University of Massachusetts Amherst"
+      },
+      {
+        "author_name": "Michael  A Johansson",
+        "author_inst": "Centers for Disease Control and Prevention"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -36443,33 +36578,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.05.27.23290638",
-    "rel_title": "A patient-centered view of symptoms, functional impact, and priorities in post-COVID-19 syndrome: Cross-sectional results from the Quebec Action Post-COVID cohort",
+    "rel_doi": "10.1101/2023.05.22.23290323",
+    "rel_title": "Analysing the psychosocial and health impacts of Long COVID in Pakistan: A cross sectional study",
     "rel_date": "2023-05-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.27.23290638",
-    "rel_abs": "BackgroundHealth services planning and mechanism-focused research would benefit from a clearer picture of symptoms, impact, and personal priorities in post-COVID-19 syndrome (PCS). This study aimed to provide estimates of the symptom, function, and quality of life (QOL) impact of PCS.\n\nMethodsPeople living in Quebec, aged [&ge;]18, were eligible for the Quebec Action for/pour le Post-COVID (QAPC) study if they had symptoms lasting more than 4 weeks post-acute SARS-CoV-2 infection, with or without a positive COVID-19 test. Recruitment was through conventional and social media between September 2022-January 2023. Standardized and individualized questionnaires, in French or English, were accessed through an online portal. We report cross-sectional results from the baseline visit of the first 414 participants in this ongoing longitudinal study.\n\nResultsIndividuals spontaneously reported symptoms attributable to an average of 4.5 organ systems. Fatigue was most frequent. Effects on function and quality of life were moderate to severe, and had already persisted for a year or more in the majority. Personal intervention priorities included fatigue and post-exercise malaise, cognitive symptoms, shortness of breath, and impaired taste and smell. Women and men were similar on PCS impact, while older age was associated with lower impact.\n\nInterpretationSymptom clusters defined a range of severity, with fatigue a pervasive symptom at all levels of severity. Participants in this study are likely to be representative of those seeking health care for post-COVID-19 symptoms in Canada and the results can inform next steps for clinical, research, and health services planning.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.22.23290323",
+    "rel_abs": "Long COVID corresponds to the occurrence of symptoms beyond twelve weeks after the onset of acute COVID-19 illness. The study aimed to analyze impacts of long COVID on the general health and psychosocial well-being of the Pakistani population. This cross-sectional study aimed to analyse the impacts of long COVID on general health and psychosocial well-being. For this study, the participants were interviewed, and their responses were recorded on a questionnaire capturing information on demographics, COVID-19 status, duration of symptoms and long COVID symptoms. The psychological impacts of the pandemic were assessed using scales like Short Mood and feeling questionnaire (sMFQ), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), Generalized Anxiety Disorder Assessment (GAD-7) and Perceived Stress Scale (PSS). Regression analysis was conducted to analyse the predictors of long COVID. A total of 300 participants were interviewed, of which 155 (52%) had COVID-19 illness. Of these 54 (35%) had persistent symptoms for a period of more than 12 weeks classified as long COVID. Muscle problems and fatigue were the most frequent (14.7%) symptoms encountered, followed by breathing problems (12.6%) and cognitive issues (12.6%). Symptoms such as decrease in appetite and confusion or disorientation during the initial phase of the infection were associated with long COVID. Majority of the participants (83.3%) had moderate level of perceived stress while moderate to severe levels of stress was observed in 17.3% of the individuals. Moreover, a high level positive mental wellbeing was also observed.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Nancy Elizabeth Mayo",
-        "author_inst": "McGill University"
+        "author_name": "Madeeha Khan",
+        "author_inst": "Directorate of Research, Shifa Tameer-e-Millat University, Islamabad, Pakistan"
       },
       {
-        "author_name": "Marie-Josee Brouillette",
-        "author_inst": "McGill University"
+        "author_name": "Sadaf Majeed",
+        "author_inst": "Department of Physiology, Shifa College of Medicine, Shifa Tameer e Millat University, Islamabad, Pakistan"
       },
       {
-        "author_name": "Emilia Liana Falcone",
-        "author_inst": "Montreal Clinical Research Institute"
+        "author_name": "Quratul Ain",
+        "author_inst": "Directorate of Research, Shifa Tameer-e-Millat University, Islamabad, Pakistan"
       },
       {
-        "author_name": "Lesley Fellows",
-        "author_inst": "McGill University"
+        "author_name": "Amjad Nawaz",
+        "author_inst": "Directorate of Research, Shifa Tameer-e-Millat University, Islamabad, Pakistan"
+      },
+      {
+        "author_name": "Khadija Awais Sumra",
+        "author_inst": "Agha Khan University, Karachi, Pakistan"
+      },
+      {
+        "author_name": "Vilma Lammi",
+        "author_inst": "Institute for Molecular Medicine, Helsinki Institute of Life Science, University of Helsinki, Finland"
+      },
+      {
+        "author_name": "Faizan Nihal",
+        "author_inst": "Department of Vascular Surgery, Shifa International Hospital, Islamabad, Pakistan"
+      },
+      {
+        "author_name": "Aleena Afrah",
+        "author_inst": "Department of Psychology, University of Wah, Wah Cantt, Pakistan"
+      },
+      {
+        "author_name": "Ejaz Ahmed Khan",
+        "author_inst": "Department of Infectious Diseases, Shifa International Hospital, Islamabad, Pakistan"
+      },
+      {
+        "author_name": "Mohammad Iqbal Khan",
+        "author_inst": "Shifa Tameer-e-Millat University, Islamabad, Pakistan"
+      },
+      {
+        "author_name": "Fouzia Sadiq",
+        "author_inst": "Shifa Tameer-e-Millat University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -39137,23 +39300,51 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2023.05.22.23290349",
-    "rel_title": "Pandemic Lessons of Sustainability: Higher Covid-19 Mortality in Less Sustainable US States",
+    "rel_doi": "10.1101/2023.05.22.23290332",
+    "rel_title": "Wastewater-based reproduction numbers and projections of COVID-19 cases in multiple cities in Japan, 2022",
     "rel_date": "2023-05-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.22.23290349",
-    "rel_abs": "This paper intends to contribute to the current debate over what lessons the United States should take away from the Covid-19 pandemic. It focuses on the role that sustainability played in shaping different pandemic outcomes among the 50 states. By the end of 2021, Mississippi reported the highest standardized death rate from Covid-19 in the country, more than five times higher than Vermont, which reported the lowest standardized death rate. If Mississippi had the same rate as Vermont, approximately 83% of the lives lost (7,958 individuals) could have been saved. If all 50 states had the same rate as Vermont, approximately 583,296 individuals (76% of the total deceased) would have survived. The inter-state difference in excess death rates was even larger. It was 18.19% in Arizona, 8.5 times as high as in Hawaii. Political ideology is currently a popular possible explanation for discrepancies among states in pandemic outcomes, given that Republican states tended to have higher death rates compared to Democratic ones. Additionally, partisan politics have been criticized for hindering the US pandemic response, especially in the early stages of the pandemic. However, the current debate lacks an attention to sustainability. This study demonstrates that indicators of sustainability may serve as more significant predictors of the death rates among the US states than political affiliation. Using the percentage of votes for Trump per state in 2020 as a proxy variable, this study found that the correlation between political affiliation and the death rates was significant only when it was the lone parameter. Its effects were overshadowed when vaccination rates and eco-friendliness were included in the equation. Above all, when the Sustainable Development Goal (SDG) index was added to the regression, it became the only significant predictor of the death rates. This suggests that it was not \"red\" or \"blue,\" but rather \"green\" that was the most important factor in determining Covid-19 mortality. Pandemic lessons are lessons of sustainability.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.22.23290332",
+    "rel_abs": "BackgroundWastewater surveillance has expanded globally to monitor the spread of infectious diseases. An inherent challenge is substantial noise and bias in wastewater data due to their sampling and quantification process, leading to the limited applicability of wastewater surveillance as a monitoring tool and the difficulty.\n\nAimIn this study, we present an analytical framework for capturing the growth trend of circulating infections from wastewater data and conducting scenario analyses to guide policy decisions.\n\nMethodsWe developed a mathematical model for translating the observed SARS-CoV-2 viral load in wastewater into effective reproduction numbers. We used an extended Kalman filter to infer underlying transmissions by smoothing out observational noise. We also illustrated the impact of different countermeasures such as expanded vaccinations and non-pharmaceutical interventions on the projected number of cases using three study areas in Japan as an example.\n\nResultsOur analyses showed an adequate fit to the data, regardless of study area and virus quantification method, and the estimated reproduction numbers derived from wastewater data were consistent with notification-based reproduction numbers. Our projections showed that a 10-20% increase in vaccination coverage or a 10% reduction in contact rate may suffice to initiate a declining trend in study areas.\n\nConclusionOur study demonstrates how wastewater data can be used to track reproduction numbers and perform scenario modelling to inform policy decisions. The proposed framework complements conventional clinical surveillance, especially when reliable and timely epidemiological data are not available.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "LEE na LIU",
-        "author_inst": "University of Central Missouri"
+        "author_name": "Shogo Miyazawa",
+        "author_inst": "Data Science Department, Shionogi & Co, Ltd, Osaka, Japan"
+      },
+      {
+        "author_name": "TingSam Wong",
+        "author_inst": "AdvanSentinel Inc., Osaka, Japan"
+      },
+      {
+        "author_name": "Genta Ito",
+        "author_inst": "Data Science Department, Shionogi & Co, Ltd, Osaka, Japan"
+      },
+      {
+        "author_name": "Ryo Iwamoto",
+        "author_inst": "AdvanSentinel Inc., Osaka, Japan"
+      },
+      {
+        "author_name": "Kozo Watanabe",
+        "author_inst": "Center for Marine Environmental Studies (CMES), Ehime University, Ehime, Japan"
+      },
+      {
+        "author_name": "Michiel van Boven",
+        "author_inst": "National Institute for Public Health and the Environment"
+      },
+      {
+        "author_name": "Jacco Wallinga",
+        "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands"
+      },
+      {
+        "author_name": "Fuminari Miura",
+        "author_inst": "Center for Marine Environmental Studies (CMES), Ehime University, Ehime, Japan"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2023.05.16.23290059",
@@ -40871,107 +41062,99 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2023.05.15.540756",
-    "rel_title": "A synthetic delivery vector for mucosal vaccination",
+    "rel_doi": "10.1101/2023.05.12.23289890",
+    "rel_title": "Heterogeneous changes in mobility in response to the SARS-CoV-2 Omicron BA.2 outbreak in Shanghai",
     "rel_date": "2023-05-16",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.15.540756",
-    "rel_abs": "The success of mRNA-based vaccines during the Covid-19 pandemic has highlighted the value of this new platform for vaccine development against infectious disease. However, the CD8+ T cell response remains modest with mRNA vaccines, and these do not induce mucosal immunity, which would be needed to prevent viral spread in the healthy population. To address this drawback, we developed a dendritic cell targeting mucosal vaccination vector, the homopentameric STxB. Here, we describe the highly efficient chemical synthesis of the protein, and its in vitro folding. This straightforward preparation led to a synthetic delivery tool whose biophysical and intracellular trafficking characteristics were largely indistinguishable from recombinant STxB. The chemical approach allowed for the generation of new variants with bioorthogonal handles. Selected variants were chemically coupled to several types of antigens derived from the mucosal viruses SARS-CoV-2 and type 16 human papillomavirus. Upon intranasal administration in mice, mucosal immunity, including resident memory CD8+ T cells and IgA antibodies was induced against these antigens. Our study thereby identifies a novel synthetic antigen delivery tool for mucosal vaccination with an unmatched potential to respond to an urgent medical need.",
-    "rel_num_authors": 22,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.12.23289890",
+    "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic and the measures taken by authorities to control its spread had altered human behavior and mobility patterns in an unprecedented way. However, it remains unclear whether the population response to a COVID-19 outbreak varies within a city or among demographic groups. Here we utilized passively recorded cellular signaling data at a spatial resolution of 1km x 1km for over 5 million users and epidemiological surveillance data collected during the SARS-CoV-2 Omicron BA.2 outbreak from February to June 2022 in Shanghai, China, to investigate the heterogeneous response of different segments of the population at the within-city level and examine its relationship with the actual risk of infection. Changes in behavior were spatially heterogenous within the city and population groups, and associated with both the infection incidence and adopted interventions. We also found that males and individuals aged 30-59 years old traveled more frequently, traveled longer distances, and their communities were more connected; the same groups were also associated with the highest SARS-CoV-2 incidence. Our results highlight the heterogeneous behavioral change of the Shanghai population to the SARS-CoV-2 Omicron BA.2 outbreak and the its effect on the heterogenous spread of COVID-19, both spatially and demographically. These findings could be instrumental for the design of targeted interventions for the control and mitigation of future outbreaks of COVID-19 and, more broadly, of respiratory pathogens.\n\nSignificance StatementOur study utilized passively recorded cellular signaling data and epidemiological surveillance data to investigate the changes human mobility to a COVID-19 outbreak at an unprecedented within-city level and examine its relationship with the actual risk of infection. Our findings highlight the heterogeneous behavioral change of the Shanghai population to the 2022 SARS-CoV-2 Omicron BA.2 outbreak and its heterogenous effect on the SARS-CoV-2 spread, both spatially and demographically. The implications of our findings could be instrumental to inform spatially targeted interventions at the within-city scale to mitigate possible new surges of COVID-19 cases as well as fostering preparedness for future respiratory infections disease outbreaks.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Anne Billet",
-        "author_inst": "Institut Curie"
-      },
-      {
-        "author_name": "Justine Hadjerci",
-        "author_inst": "Institut Curie"
-      },
-      {
-        "author_name": "Thi Tran",
-        "author_inst": "PARCC"
+        "author_name": "Juanjuan Zhang",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Pascal Kessler",
-        "author_inst": "CEA"
+        "author_name": "Suoyi Tan",
+        "author_inst": "College of Systems Engineering, National University of Defense Technology"
       },
       {
-        "author_name": "Jonathan Ulmer",
-        "author_inst": "Institut Curie"
+        "author_name": "Cheng Peng",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Gilles Mourier",
-        "author_inst": "CEA"
+        "author_name": "Xiangyanyu Xu",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Marine Ghazarian",
-        "author_inst": "CEA"
+        "author_name": "Mengning Wang",
+        "author_inst": "College of Systems Engineering, National University of Defense Technology"
       },
       {
-        "author_name": "Anthony Gonzalez",
-        "author_inst": "CEA"
+        "author_name": "Wanying Lu",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Robert Thai",
-        "author_inst": "CEA"
+        "author_name": "Yanpeng Wu",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Pauline Urquia",
-        "author_inst": "PARCC"
+        "author_name": "Bin Sai",
+        "author_inst": "College of Systems Engineering, National University of Defense Technology"
       },
       {
-        "author_name": "Anne-Cecile Vanbaelen",
-        "author_inst": "CEA"
+        "author_name": "Mengsi Cai",
+        "author_inst": "College of Systems Engineering, National University of Defense Technology"
       },
       {
-        "author_name": "Annalisa Meola",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Allisandra G. Kummer",
+        "author_inst": "Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health"
       },
       {
-        "author_name": "Ignacio Fernandez",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Zhiyuan Chen",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Stephanie Deville-Foillard",
-        "author_inst": "Institut de Chimie des Substances Naturelles"
+        "author_name": "Junyi Zou",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Ewan MacDonald",
-        "author_inst": "Institut Curie"
+        "author_name": "Wenxin Li",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Lea Paolini",
-        "author_inst": "PARCC"
+        "author_name": "Wen Zheng",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Frederic Schmidt",
-        "author_inst": "Institut Curie"
+        "author_name": "Yuxia Liang",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Felix A Rey",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Yuchen Zhao",
+        "author_inst": "School of Public Health, Fudan University"
       },
       {
-        "author_name": "Michael S Kay",
-        "author_inst": "University of Utah"
+        "author_name": "Alessandro Vespignani",
+        "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University"
       },
       {
-        "author_name": "Eric Tartour",
-        "author_inst": "PARCC"
+        "author_name": "Marco Ajelli",
+        "author_inst": "Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health"
       },
       {
-        "author_name": "Denis Servent",
-        "author_inst": "CEA"
+        "author_name": "Xin Lu",
+        "author_inst": "College of Systems Engineering, National University of Defense Technology; Department of Public Health Sciences, Karolinska Institutet"
       },
       {
-        "author_name": "Ludger Johannes",
-        "author_inst": "Institut Curie"
+        "author_name": "Hongjie Yu",
+        "author_inst": "School of Public Health, Fudan University"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "new results",
-    "category": "biochemistry"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2023.05.11.23289882",
@@ -42509,95 +42692,31 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2023.05.09.540089",
-    "rel_title": "Single-cell transcriptome landscape of circulating CD4+ T cell populations in human autoimmune diseases",
+    "rel_doi": "10.1101/2023.05.10.540124",
+    "rel_title": "PandoGen: Generating complete instances of future SARS-CoV2 sequences using Deep Learning",
     "rel_date": "2023-05-10",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.09.540089",
-    "rel_abs": "CD4+ T cells are a key mediator of various autoimmune diseases; however, how they contribute to disease development remains obscure primarily because of their cellular heterogeneity. Here, we evaluated CD4+ T cell subpopulations by decomposition-based transcriptome characterization together with canonical clustering strategies. This approach identified 12 independent transcriptional gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of canonical clustering. In addition, we performed a meta-analysis using public single-cell data sets of over 1.8M peripheral CD4+ T cells from 953 individuals by projecting cells onto the reference and cataloged cell frequency and qualitative alterations of the populations in 20 diseases. The analyses revealed that the 12 transcriptional programs were useful in characterizing each autoimmune disease and predicting its clinical status. Moreover, genetic variants associated with autoimmune diseases showed disease-specific enrichment within the 12 gene programs. The results collectively provide a landscape of single-cell transcriptomes of CD4+ T cell subpopulations involved in autoimmune disease.",
-    "rel_num_authors": 19,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.10.540124",
+    "rel_abs": "Deep generative models have achieved breakthrough performance in generating computer code, instances of human language and images. We explore the use of these models to create as yet undiscovered instances of viral sequences in a pandemic situation. Towards this goal, we formulate a novel framework for training models to align the sequence generation problem to the characteristics of a pandemic. We applied our method to modeling the SARS-CoV2 Spike protein, the primary driver of the COVID-19 pandemic, and compared our method to models trained via prevalent practices applied to biological sequence modeling. Our method substantially outperforms a state-of-the-art generative model finetuned on SARS-CoV2 data, producing samples containing sequences which are four times as likely to be real, undiscovered sequences, and ten times as infectious. Our method can forecast novel lineages of the virus up to approximately 3 months in advance. Given a limited sequence budget, our method generates sequences belonging to the Delta variant and multiple dominant Omicron subvariants up to a month in advance.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Yoshiaki Yasumizu",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Daiki Takeuchi",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Reo Morimoto",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Yusuke Takeshima",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Tatsusada Okuno",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Makoto Kinoshita",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Takayoshi Morita",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Yasuhiro Kato",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Min Wang",
-        "author_inst": "Chinese Academy of Medical Sciences and Peking Union Medical College"
-      },
-      {
-        "author_name": "Daisuke Motooka",
-        "author_inst": "Osaka University Research Institute for Microbial Diseases"
-      },
-      {
-        "author_name": "Daisuke Okuzaki",
-        "author_inst": "Osaka University Research Institute for Microbial Diseases"
-      },
-      {
-        "author_name": "Yamami Nakamura",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Norihisa Mikami",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Masaya Arai",
-        "author_inst": "Osaka university"
-      },
-      {
-        "author_name": "Xuan Zhang",
-        "author_inst": "PUMC HOSPITAL"
-      },
-      {
-        "author_name": "A. Kumanogoh",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Hideki Mochizuki",
-        "author_inst": "Osaka University Graduate School of Medicine"
+        "author_name": "Anand Ramachandran",
+        "author_inst": "University of Illinois at Urbana-Champaign"
       },
       {
-        "author_name": "Naganari Ohkura",
-        "author_inst": "Osaka university"
+        "author_name": "Steven S Lumetta",
+        "author_inst": "University of Illinois at Urbana-Champaign"
       },
       {
-        "author_name": "Shimon Sakaguchi",
-        "author_inst": "Osaka university"
+        "author_name": "Deming Chen",
+        "author_inst": "University of Illinois at Urbana-Champaign"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "immunology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2023.05.10.23289557",
@@ -44123,83 +44242,35 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2023.05.05.23289503",
-    "rel_title": "Primary series and booster COVID-19 vaccine effectiveness in a cohort of healthcare workers in Albania during a BA.1 and BA.2 variant period, January - May 2022",
+    "rel_doi": "10.1101/2023.05.05.23289561",
+    "rel_title": "COVID-19 vaccination at a hospital in Paris: spatial analyses and inverse equity hypothesis",
     "rel_date": "2023-05-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.05.23289503",
-    "rel_abs": "BackgroundHealthcare workers (HCWs) have experienced high rates of COVID-19 morbidity and mortality. We estimated COVID-19 two-dose primary series and monovalent booster vaccine effectiveness (VE) against symptomatic SARS-CoV-2 Omicron (BA.1 and BA.2) infection among HCWs in three Albanian hospitals during January-May 2022.\n\nMethodsStudy participants completed weekly symptom questionnaires, underwent PCR testing when symptomatic, and provided quarterly blood samples for serology. We estimated VE using Cox regression models (1-hazard ratio), with vaccination status as the time-varying exposure and unvaccinated HCWs as the reference group, adjusting for potential confounders: age, sex, prior SARS-CoV-2 infection (detected by PCR, rapid-antigen test or serology), and household size.\n\nResultsAt the start of the analysis period, 76% of 1,462 HCWs had received a primary series, 10% had received a booster dose, and 9% were unvaccinated; 1,307 (89%) HCWs had evidence of prior infection. Overall, 86% of primary series and 98% of booster doses received were BNT162b2. The median time interval from the second dose and the booster dose to the start of the analysis period was 289 days (IQR:210- 292) and 30 days (IQR:22-46), respectively. VE against symptomatic PCR-confirmed infection was 34% (95%CI: -36;68) for the primary series and 88% (95%CI: 38;98) for the booster.\n\nConclusionsAmong Albanian HCWs, most of whom had been previously infected, COVID-19 booster dose offered improved VE during a period of Omicron BA.1 and BA.2 circulation. Our findings support promoting booster dose uptake among Albanian HCWs, which, as of January 2023, was only 20%.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.05.23289561",
+    "rel_abs": "BackgroundVaccination against SARS-CoV-2 has been deployed in France since January 2021. Evidence was beginning to show that the most vulnerable populations were the most affected by COVID-19. Without specific action for different population subgroups, the inverse equity hypothesis postulates that people in the least deprived neighbourhoods will be the first to benefit.\n\nMethodsWe performed a spatial analysis using primary data from the vaccination centre of the Avicenne Hospital in Bobigny (Seine-Saint-Denis, France) from January 8th to September 30th, 2021. We used secondary data to calculate the social deprivation index. We performed flow analysis, k-means aggregation, and mapping.\n\nResultsDuring the period, 32,712 people were vaccinated at the study centre. Vaccination flow to the hospital shows that people living in the least disadvantaged areas were the first to be vaccinated. The number of people immunized according to the level of social deprivation then scales out with slightly more access to the vaccination centre for the most advantaged. The furthest have travelled more than 100 kilometres, and more than 1h45 of transport time to get to this vaccination centre. Access times are, on average, 50 minutes in February to 30 minutes in May 2021.\n\nConclusionThe study confirms the inverse equity hypothesis and shows that vaccination preparedness strategies must take equity issues into account. Public health interventions should be implemented according to proportionate universalism and use community health, health mediation, and outreach activities for more equity.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Iris Finci",
-        "author_inst": "World Health Organisation, Regional Office for Europe"
-      },
-      {
-        "author_name": "Madelyn Yiseth Rojas Castro",
-        "author_inst": "Epiconcept, Paris, France"
-      },
-      {
-        "author_name": "Iris Hasibra",
-        "author_inst": "Institute of Public Health, Tirana, Albania"
-      },
-      {
-        "author_name": "Jonilda Sulo",
-        "author_inst": "Southeast European Center for Surveillance and Control of Infectious Disease, Tirana, Albania"
-      },
-      {
-        "author_name": "Albana Fico",
-        "author_inst": "Institute of Public Health, Tirana, Albania"
-      },
-      {
-        "author_name": "Rovena Daja",
-        "author_inst": "Institute of Public Health, Tirana, Albania"
-      },
-      {
-        "author_name": "Adela Vasili",
-        "author_inst": "Institute of Public Health, Tirana, Albania"
-      },
-      {
-        "author_name": "Majlinda Kota",
-        "author_inst": "Institute of Public Health, Tirana, Albania"
-      },
-      {
-        "author_name": "Iria Preza",
-        "author_inst": "World Health Organization, Country Office Albania, Tirana, Albania"
-      },
-      {
-        "author_name": "Barbara Muehlemann",
-        "author_inst": "Institute of Virology, Charite-Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt- Universitaet zu Berlin, and Berlin Institut"
-      },
-      {
-        "author_name": "Christian Drosten",
-        "author_inst": "Institute of Virology, Charite-Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt- Universitaet zu Berlin, and Berlin Institut"
-      },
-      {
-        "author_name": "Richard Pebody",
-        "author_inst": "World Health Organization Regional Office for Europe, Copenhagen, Denmark"
+        "author_name": "Valery Ridde",
+        "author_inst": "University of Paris: Universite Paris Cite"
       },
       {
-        "author_name": "Kathryn E Lafond",
-        "author_inst": "Influenza Division, US Centers for Disease Control, Atlanta, Georgia"
+        "author_name": "Gaelle Andre",
+        "author_inst": "University Paris 1 Pantheon-Sorbonne"
       },
       {
-        "author_name": "Esther Kissling",
-        "author_inst": "Epiconcept, Paris, France"
+        "author_name": "Olivier Bouchaud",
+        "author_inst": "Universite Sorbonne Paris Nord"
       },
       {
-        "author_name": "Mark A Katz",
-        "author_inst": "World Health Organization Regional Office for Europe, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Silvia Bino",
-        "author_inst": "Institute of Public Health, Tirana, Albania"
+        "author_name": "Emmanuel Bonnet",
+        "author_inst": "Universite Paris 1 Pantheon-Sorbonne"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2023.05.03.23289488",
@@ -46161,47 +46232,39 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2023.05.01.23289307",
-    "rel_title": "Hear my Voice: Understanding how community health workers in the Peruvian Amazon expanded their roles to mitigate the impact of the COVID-19 pandemic through Community-Based Participatory Action Research",
+    "rel_doi": "10.1101/2023.05.02.23289404",
+    "rel_title": "Sex and age-dependent alterations of drug consumption during the COVID-19 lockdown in Spain: Lessons learned for the future",
     "rel_date": "2023-05-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.01.23289307",
-    "rel_abs": "IntroductionThe COVID-19 pandemic led to the collapse of the Peruvian health system, which disrupted healthcare access for indigenous communities in the Amazon. We aimed to understand how the COVID-19 pandemic transformed the responsibilities of community health workers (CHWs) from indigenous communities in the Peruvian Amazon so policymakers can support indigenous health efforts.\n\nMethodsFourteen CHWs from Loreto, Peru participated in a community-based Participatory Action Research (CBPR) project using Photovoice, a technique that encourages vulnerable groups to take photos and develop stories illustrating their lived experiences. Participants were recruited from Mamas del Rio, a local university-based program, through purposive sampling. CHWs were trained in Photovoice and asked to photograph how the pandemic affected their lives and work. Participants met four times over five months to share photos and develop action items. Data were organized into key themes using a general inductive method. Final photos and action items were shared with policymakers during galleries in Iquitos and Lima.\n\nResultsCHWs took a total of 36 photos with 33 accompanying texts highlighting their roles during the pandemic. Four core themes emerged: (1) the collapse of social infrastructure, (2) the use of medicinal plants versus pharmaceuticals, (3) the community adaptations and struggles, and (4) the importance of CHWs. CHWs expanded their responsibilities or leveraged their leadership across these themes to support COVID-19 patients, vaccination, and mandates without training or resources from the government. CHWs asked policymakers for formal integration into the health system, standardization of CHW training, and better management of community pharmacies.\n\nConclusionCHWs, who work on a voluntary basis, took on additional roles during the pandemic with little to no training from the government. CHWs demonstrated how their roles could be better supported by the government to ameliorate future health catastrophes in the Peruvian Amazon.\n\nShort SummaryHealth care delivery in the Peruvian Amazon collapsed during the COVID-19 pandemic. Community health workers provided frontline care, education, and logistical support without formal training, resources, or compensation from the Ministry of Health. The government can better leverage, supervise, recognize, and integrate the role of community health workers to strengthen the health system.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.02.23289404",
+    "rel_abs": "In order to reduce the spread of COVID-19, lockdown has been one of the most implemented measures worldwide. Spain had one of the harshest lockdowns in Europe, impacting the social and psychological health of the population. The aim of this paper is to study how the lockdown has affected drug consumption patterns and the extent to which age and sex are influential factors. We have developed an online survey in which people were asked about their consumption of alcohol, marihuana, cocaine, and sedative and tranquilizers before and during the COVID-19 lockdown. Data revealed a general reduction in the consumption of all the drugs surveyed. Interestingly, when data was analysed by sex or age, we detected alterations in the consumption patterns depending on these variables that were of special relevance in the case of alcohol, marihuana and non-prescription sedatives and tranquilizers. Our data revealed a general decrease in the use of these drugs in the case of young adults, revealing that their use is strongly linked to social life, whereas the middle-aged population has experienced alterations in their consumption patterns, whereby their use has increased to daily. In addition, the use of non-prescription sedatives and tranquilizers has increased in specific populations. In conclusion, our data reveals important alterations during the lockdown in the consumption pattern of both legal and illegal drugs (sex and age dependent) in the Spanish population, and these alterations might be considered for future national strategies of preventative actions.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Tina Samsamshariat",
-        "author_inst": "University of Arizona College of Medicine - Phoenix"
-      },
-      {
-        "author_name": "Purnima Madhivanan",
-        "author_inst": "The University of Arizona"
-      },
-      {
-        "author_name": "Alexandra Reyes",
-        "author_inst": "Pontificia Universidad Cat\u00f3lica de Per\u00fa"
+        "author_name": "Jesus David Lorente",
+        "author_inst": "Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain"
       },
       {
-        "author_name": "Eva Moya",
-        "author_inst": "The University of Texas at El Paso, Department of Social Work"
+        "author_name": "Anabel Forte",
+        "author_inst": "Department of Statistics and Operations Research. University of Valencia, Valencia, Spain"
       },
       {
-        "author_name": "Graciela Meza",
-        "author_inst": "Universidad Nacional de la Amazonia Peruana"
+        "author_name": "Javier Cuitavi",
+        "author_inst": "Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain"
       },
       {
-        "author_name": "Stefan Reinders",
-        "author_inst": "Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine;  Universidad Peruana Cayetano Heredia"
+        "author_name": "Francesc Verdu",
+        "author_inst": "Drug Dependence Section of the Department of Universal Health and Public Health, Generalitat Valenciana. Systems Information area of Government Delegation for t"
       },
       {
-        "author_name": "Magaly Blas",
-        "author_inst": "Universidad Peruana Cayetano Heredia"
+        "author_name": "Lucia Hipolito",
+        "author_inst": "Department of Pharmacy and Pharmaceutical Technology and Parasitology, University of Valencia, Valencia, Spain"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "addiction medicine"
   },
   {
     "rel_doi": "10.1101/2023.05.01.23289163",
@@ -48615,59 +48678,243 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.04.25.538294",
-    "rel_title": "Intranasal VLP-RBD vaccine adjuvanted with BECC470 confers immunity against Delta SARS-CoV-2 challenge in K18-hACE2-mice",
+    "rel_doi": "10.1101/2023.04.25.538264",
+    "rel_title": "Surveillance of Vermont wildlife in 2021-2022 reveals no detected SARS-CoV-2 viral RNA",
     "rel_date": "2023-04-26",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.25.538294",
-    "rel_abs": "As the COVID-19 pandemic transitions to endemic, seasonal boosters are a plausible reality across the globe. We hypothesize that intranasal vaccines can provide better protection against asymptomatic infections and more transmissible variants of SARS-CoV-2. To formulate a protective intranasal vaccine, we utilized a VLP-based platform. Hepatitis B surface antigen- based virus like particles (VLP) linked with receptor binding domain (RBD) antigen were paired with the TLR4-based agonist adjuvant, BECC 470. K18-hACE2 mice were primed and boosted at four-week intervals with either VLP-RBD-BECC or mRNA-1273. Both VLP-RBD-BECC and mRNA-1273 vaccination resulted in production of RBD-specific IgA antibodies in serum. RBD- specific IgA was also detected in the nasal wash and lung supernatants and were highest in VLP-RBD-BECC vaccinated mice. Interestingly, VLP-RBD-BECC vaccinated mice showed slightly lower levels of pre-challenge IgG responses, decreased RBD-ACE2 binding inhibition, and lower neutralizing activity in vitro than mRNA-1273 vaccinated mice. Both VLP-RBD-BECC and mRNA-1273 vaccinated mice were protected against challenge with a lethal dose of Delta variant SARS-CoV-2. Both vaccines limited viral replication and viral RNA burden in the lungs of mice. CXCL10 is a biomarker of severe SARS-CoV-2 infection and we observed both vaccines limited expression of serum and lung CXCL10. Strikingly, VLP-RBD-BECC when administered intranasally, limited lung inflammation at early timepoints that mRNA-1273 vaccination did not. VLP-RBD-BECC immunization elicited antibodies that do recognize SARS-CoV-2 Omicron variant. However, VLP-RBD-BECC immunized mice were protected from Omicron challenge with low viral burden. Conversely, mRNA-1273 immunized mice had low to no detectable virus in the lungs at day 2. Together, these data suggest that VLP-based vaccines paired with BECC adjuvant can be used to induce protective mucosal and systemic responses against SARS- CoV-2.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.25.538264",
+    "rel_abs": "Previous studies have documented natural infections of SARS-CoV-2 in various domestic and wild animals. More recently, studies have been published noting the susceptibility of members of the Cervidae family, and infections in both wild and captive cervid populations. In this study, we investigated the presence of SARS-CoV-2 in mammalian wildlife within the state of Vermont. 739 nasal or throat samples were collected from wildlife throughout the state during the 2021 and 2022 harvest season. Data was collected from red and gray foxes (Vulpes vulples and Urocyon cineroargentus, respectively), fishers (Martes pennati), river otters (Lutra canadensis), coyotes (Canis lantrans), bobcats (Lynx rufus rufus), black bears (Ursus americanus), and white-tailed deer (Odocoileus virginianus). Samples were tested for the presence of SARS-CoV-2 via quantitative RT-qPCR using the CDC N1/N2 primer set and/or the WHO-E gene primer set. Our results indicate that no sampled wildlife were positive for SARS-CoV-2. This finding is surprising, given that most published North America studies have found SARS-CoV-2 within their deer populations. The absence of SARS-CoV-2 RNA in populations sampled here may provide insights in to the various environmental and anthropogenic factors that reduce spillover and spread in North Americans wildlife populations.",
+    "rel_num_authors": 56,
     "rel_authors": [
       {
-        "author_name": "Fredrick Heath Damron",
-        "author_inst": "West Virginia University"
+        "author_name": "Hannah W. Despres",
+        "author_inst": "University of Vermont"
       },
       {
-        "author_name": "Katherine S Lee",
-        "author_inst": "West Virginia University"
+        "author_name": "Margaret G. Mills",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Nathaniel A Rader",
-        "author_inst": "West Virginia University"
+        "author_name": "Madaline M. Schmidt",
+        "author_inst": "University of Vermont"
       },
       {
-        "author_name": "Olivia A Miller-Stump",
-        "author_inst": "West Virginia University"
+        "author_name": "Jolene Gov",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Melissa Cooper",
-        "author_inst": "West Virginia University"
+        "author_name": "Yael Perez",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Ting Y Wong",
-        "author_inst": "West Virginia University"
+        "author_name": "Mars Jindrich",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Md Shahrier Amin",
-        "author_inst": "West Virginia University"
+        "author_name": "Allison M. L. Crawford",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Mariette Barbier",
-        "author_inst": "West Virginia University"
+        "author_name": "Warren T. Kohl",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Justin R. Bevere",
-        "author_inst": "West Virginia University"
+        "author_name": "Elias Rosenblatt",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Robert K Ernst",
-        "author_inst": "University of Maryland, College Park"
+        "author_name": "Hannah C. Kubinski",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Benjamin C. Simmons",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Miles C. Nippes",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Anne J. Goldenberg",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Kristina E. Murtha",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Samantha Nicoloro",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Mia J. Harris",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Avery C. Feeley",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Taylor K. Gelinas",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Maeve K. Cronin",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Robert S. Frederick",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Matthew Thomas",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Meaghan E. Johnson",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "James Murphy",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Elle B. Lenzini",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Peter A. Carr Jr.",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Danielle H. Berger",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Soham P. Mehta",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Christopher J. Floreani",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Amelia C. Koval",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Aleah L. Young",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Jess H. Fish",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Jack Wallace",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Ella Chaney",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Grace Ushay",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Madeline Waterman",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Rebecca S. Ross",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Erin M. Vostal",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Maya C. Thisner",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Kyliegh E. Gonet",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Owen C. Deane",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Pelletiere R. Kari",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Vegas C. Rockafeller",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Madeline Waterman",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Tyler W. Barry",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Catriona C. Goering",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Sarah D. Shipman",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Allie C. Shiers",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Claire E. Reilly",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Alanna M. Duff",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "David J. Shirley",
+        "author_inst": "Faraday Inc."
+      },
+      {
+        "author_name": "Keith R. Jerome",
+        "author_inst": "Univerity of Washington"
+      },
+      {
+        "author_name": "Ailyn C. P\u00e9rez-Osorio",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "Alexander L. Greninger",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "Nick Fortin",
+        "author_inst": "Vermont Agency of Natural Resources"
+      },
+      {
+        "author_name": "Brittany A. Mosher",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Emily A. Bruce",
+        "author_inst": "University of Vermont"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2023.04.25.538336",
@@ -50385,63 +50632,71 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.04.19.23288804",
-    "rel_title": "Assessing Willingness to receive COVID-19 Vaccines, associated factors and reasons for hesitancy among persons aged 13-80 years in Central Uganda. A population-based surveillance Cohort.",
-    "rel_date": "2023-04-23",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.19.23288804",
-    "rel_abs": "BackgroundVaccination is essential for controlling the COVID-19 pandemic. However adequate vaccine coverage is a critical to the effectiveness of the vaccine at a population level. Data on to acceptability of the vaccine in Urban areas are limited. This study examined the prevalence, factors associated with willingness to receive COVID-19 vaccine and reasons for hesitancy in the predominantly urban in central Uganda (Wakiso)\n\nMethodsData were obtained from a cross-sectional study conducted from March 1st, 2021, to September 30th, 2021 in the urban population-based cohort of the Africa Medical and behavioral Sciences Organization (AMBSO). Multivariable modified Poisson regression analysis was used to estimate adjusted prevalence ratios (aPR) and 95% confidence intervals of willingness to accept the COVID-19 vaccine.\n\nResultsA total of 1,903 participants were enrolled in the study; 61% of whom were females. About 63% of participants indicated willingness to accept the COVID-19 vaccine. Younger age groups (13-19 and 20-29) were less likely to accept the vaccine compared to the persons ages 40-49 years (aPR=0.79; 95% CI: 0.74, 0.84 for the 13-19 years and 0.93; 95% CI: 0.88, 0.98 for age group 20-29, compared to those ages 40-49 years. Post-primary education (aPR=1.05; 95% CI: 1.02, 1.09 compared to primary level), being a students and government staff (APR=1.13; 95% CI: 1.04, 1.23 compared to construction and Mechanic workers) were associated with willingness to receive COVID-19 vaccine. Some of the reported reasons for hesitancy included; concerns about side effects 154(57.0%), about 64(23.7%) did not think the vaccines were effective, and those who did not like the vaccines 32(11.9%).\n\nConclusionA substantial proportion of individuals were not willingness to receive the COVID-19 vaccine. More effort is needed to reduce vaccine hesitancy, especially among the young and people with lower formal education.",
-    "rel_num_authors": 11,
+    "rel_doi": "10.1101/2023.04.20.537680",
+    "rel_title": "Establishment of a screening platform based on human coronavirus OC43 for the identification of microbial natural products with antiviral activity",
+    "rel_date": "2023-04-21",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.20.537680",
+    "rel_abs": "Human coronaviruses (HCoVs) cause respiratory tract infections and are of great importance due to the recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Human betacoronavirus OC43 (HCoV-OC43) is an adequate surrogate for SARS-CoV-2 because it infects the human respiratory system, presents a comparable biology, and is transmitted in a similar way. Its use is advantageous since it only requires biosafety level (BSL)-2 infrastructure which minimizes costs and biosafety associated limitations. In this report, we describe a high-throughput screening (HTS) platform to identify compounds that inhibit the propagation of HCoV-OC43. Optimization of assays based on inhibition of the cytopathic effect and virus immunodetection with a specific antibody, has provided a robust methodology for the screening of a selection of microbial natural product extracts from the Fundacion MEDINA collection. Using this approach, a subset of 1280 extracts has been explored. Of these, upon hit confirmation and early LC-MS dereplication, 10 extracts were identified that contain potential new compounds. In addition, we report on the novel antiviral activity of some previously described natural products whose presence in bioactive extracts was confirmed by LC/MS analysis.\n\nIMPORTANCEThe COVID-19 pandemic has revealed the lack of effective treatments against betacoronaviruses and the urgent need for new broad-spectrum antivirals. Natural products are a valuable source of bioactive compounds with pharmaceutical potential that may lead to the discovery of new antiviral agents. Specifically, compared to conventional synthetic molecules, microbial natural extracts possess a unique and vast chemical diversity and are amenable to large-scale production. The implementation of a high-throughput screening platform using the betacoronavirus OC43 in a human cell line infection model has provided proof of concept of the approach and has allowed for the rapid and efficient evaluation of 1280 microbial extracts. The identification of several active compounds validates the potential of the platform for the search for new compounds with antiviral capacity.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "ALEX DAAMA",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Blanca Mart\u00ednez-Arribas",
+        "author_inst": "Consejo Superior de Investigaciones Cientificas"
       },
       {
-        "author_name": "Rashid Naziru",
-        "author_inst": "Makerere University CHS: Makerere University College of Health Sciences"
+        "author_name": "Frederick Boye Annang",
+        "author_inst": "Fundaci\u00f3n Centro De Excelencia en Investigaci\u00f3n de Medicamentos Innovadores en Andaluc\u00eda, Fundaci\u00f3n MEDINA, Granada"
       },
       {
-        "author_name": "Asani Kasango",
-        "author_inst": "Makerere University CHS: Makerere University College of Health Sciences"
+        "author_name": "Rosario D\u00edaz-Gonz\u00e1lez",
+        "author_inst": "Consejo Superior de Investigaciones Cientificas"
       },
       {
-        "author_name": "Grace Kigozi Nalwoga",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Guiomar P\u00e9rez-Moreno",
+        "author_inst": "Consejo Superior de Investigaciones Cient\u00edficas"
       },
       {
-        "author_name": "Fred Nalugoda",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Jes\u00fas Mart\u00edn",
+        "author_inst": "Fundaci\u00f3n MEDINA, Centro de Excelencia en Investigaci\u00f3n de Medicamentos Innovadores en Andaluc\u00eda"
       },
       {
-        "author_name": "Robert Bulamba",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Thomas A Mackenzie",
+        "author_inst": "Fundacion Centro de Excelencia en Investigacion de Medicamentos Innovadores en Andalucia"
       },
       {
-        "author_name": "Emmanuel Kyasanku",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Francisco Castillo",
+        "author_inst": "Fundacion Centro de Excelencia en Investigacion de Medicamentos Innovadores en Andalucia"
       },
       {
-        "author_name": "Gertrude Nakigozi",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Fernando Reyes",
+        "author_inst": "Fundaci\u00f3n MEDINA, Centro de Excelencia en Investigaci\u00f3n de Medicamentos Innovadores en Andaluc\u00eda"
       },
       {
-        "author_name": "Godfrey Kigozi",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Olga Genilloud",
+        "author_inst": "Fundaci\u00f3n MEDINA, Spain"
       },
       {
-        "author_name": "Joseph Kagaayi",
-        "author_inst": "Makerere University CHS: Makerere University College of Health Sciences"
+        "author_name": "Luis Miguel Ru\u00edz-P\u00e9rez",
+        "author_inst": "Consejo Superior de Investigaciones Cientificas"
+      },
+      {
+        "author_name": "Francisca Vicente",
+        "author_inst": "Fundaci\u00f3n MEDINA, Centro de Excelencia en Investigaci\u00f3n de Medicamentos Innovadores en Andaluc\u00eda"
+      },
+      {
+        "author_name": "Mar\u00eda C Ramos",
+        "author_inst": "Fundacion Centro de Excelencia en Investigacion de Medicamentos Innovadores en Andalucia"
       },
       {
-        "author_name": "Stephen Mugamba",
-        "author_inst": "Africa Medical and Behavioral Sciences Organization"
+        "author_name": "Dolores Gonzalez-Pacanowska",
+        "author_inst": "Consejo Superior de Investigaciones Cientificas"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2023.04.20.537738",
@@ -52691,47 +52946,59 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2023.04.14.23288559",
-    "rel_title": "Longitudinal sequencing and variant detection of SARS-CoV-2 across Southern California wastewater from April 2020 - August 2021",
-    "rel_date": "2023-04-18",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.14.23288559",
-    "rel_abs": "Wastewater based epidemiology (WBE) is a useful method to detect pathogen prevalence and may serve to effectively monitor diseases at a broad scale. WBE has been used throughout the COVID-19 pandemic to track localized and population-level disease burden through the quantification of SARS-CoV-2 RNA present in wastewater. Aside from case load estimation, WBE is being used to assay viral genomic diversity and the emergence of potential SARS-CoV-2 variants.\n\nHere, we present a study in which we sequenced RNA extracted from sewage influent samples obtained from eight wastewater treatment plants representing 16 million people in Southern California over April 2020 - August 2021. We sequenced SARS-CoV-2 with two methods: Illumina Respiratory Virus Enrichment and metatranscriptomic sequencing (N = 269), and QIAseq SARS-CoV-2 tiled amplicon sequencing (N = 95). We were able to classify SARS-CoV-2 reads into lineages and sublineages that approximated several named variants across a full year, and we identified a diversity of single nucleotide variants (SNVs) of which many are putatively novel SNVs, and SNVs of unknown potential function and prevalence. Through our retrospective study, we also show that several sublineages of SARS-CoV-2 were detected in wastewater up to several months before clinical detection, which may assist in the prediction of future Variants of Concern. Lastly, we show that sublineage diversity was similar between wastewater treatment plants across Southern California, and that diversity changed by sampling month indicating that WBE is effective across megaregions.\n\nAs the COVID-19 pandemic moves to new phases, and additional SARS-CoV-2 variants emerge, the ongoing monitoring of wastewater is important to understand local and population-level dynamics of the virus. Our study shows the potential of WBE to detect SARS-CoV-2 variants throughout Southern Californias wastewater and track the diversity of viral SNVs and strains in urban and suburban locations. These results will aid in our ability to monitor the evolutionary potential of SARS-CoV-2 and help understand circulating SNVs to further combat COVID-19.",
-    "rel_num_authors": 7,
+    "rel_doi": "10.1101/2023.04.15.537011",
+    "rel_title": "SARS-CoV-2 shifts transcription of host gene to increase Spike acylation and boost infectivity",
+    "rel_date": "2023-04-17",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.15.537011",
+    "rel_abs": "SARS-CoV-2 infection requires Spike protein mediating fusion between the viral and cellular membranes. The fusogenic activity of Spike requires its post-translational lipid modification by host S-acyltransferases, predominantly ZDHHC20. Previous observations indicate that SARS-CoV-2 infection augments the S-acylation of Spike when compared to transfection. Here, we find that SARS-CoV-2 infection triggers a change in the transcriptional start site of the zddhc20 gene, both in cells and in an in vivo infection model, resulting in a 67-amino-acid-long N-terminally extended protein with 37-times higher Spike acylating activity, leading to enhanced viral infectivity. Furthermore, we observed the same induced transcriptional change in response to other challenges, such as chemically induced colitis, indicating that SARS-CoV-2 hijacks an existing cell damage response pathway to generate more infectious viruses.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Jason A Rothman",
-        "author_inst": "University of California: Irvine"
+        "author_name": "Francisco Sarmento Mesquita",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
       },
       {
-        "author_name": "Andrew Saghir",
-        "author_inst": "University of California: Irvine"
+        "author_name": "Laurence Abrami",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
       },
       {
-        "author_name": "Amity G Zimmer-Faust",
-        "author_inst": "Southern California Coastal Water Research Project"
+        "author_name": "Lucie Bracq",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
       },
       {
-        "author_name": "Kylie Langlois",
-        "author_inst": "Southern California Coastal Water Research Project"
+        "author_name": "Nattawadee Panyain",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
       },
       {
-        "author_name": "Joshua A Steele",
-        "author_inst": "Southern California Coastal Water Research Project"
+        "author_name": "Vincent Mercier",
+        "author_inst": "ACCESS, Department of Biochemistry, University of Geneva, Switzerland"
       },
       {
-        "author_name": "John F Griffith",
-        "author_inst": "Southern California Coastal Water Research Project"
+        "author_name": "Beatrice Kunz",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
       },
       {
-        "author_name": "Katrine L Whiteson",
-        "author_inst": "University of California: Irvine"
+        "author_name": "Audrey Chuat",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
+      },
+      {
+        "author_name": "Joana Carlevaro-Fita",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
+      },
+      {
+        "author_name": "Didier Trono",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
+      },
+      {
+        "author_name": "F. Gisou van der Goot",
+        "author_inst": "Global Health Institute, School of Life Sciences, EPFL, Lausanne"
       }
     ],
     "version": "1",
     "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "type": "new results",
+    "category": "cell biology"
   },
   {
     "rel_doi": "10.1101/2023.04.15.536998",
@@ -54324,39 +54591,75 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.04.11.23288409",
-    "rel_title": "A methodological framework for assessing the benefit of SARS-CoV-2 vaccination following previous infection: case study of five to eleven year olds in the UK",
+    "rel_doi": "10.1101/2023.04.11.23288403",
+    "rel_title": "Effectiveness of mRNA COVID-19 monovalent and bivalent vaccine booster doses against Omicron severe outcomes among adults aged >=50 years in Ontario, Canada",
     "rel_date": "2023-04-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.11.23288409",
-    "rel_abs": "Vaccination rates against SARS-CoV-2 in children aged five to 11 years remain low in many countries. The current benefit of vaccination in this age group has been questioned given that the large majority of children have now experienced at least one SARS-CoV-2 infection. However, protection from infection, vaccination or both wanes over time. National decisions on offering vaccines to this age group have tended to be made without considering time since infection.\n\nThere is an urgent need to evaluate the additional benefits of vaccination in previously infected children and under what circumstances those benefits accrue. We present a novel methodological framework for estimating the potential benefits of COVID-19 vaccination in previously infected children aged five to 11, accounting for waning. We apply this framework to the UK context and for two adverse outcomes: hospitalisation related to SARS-CoV-2 infection and Long Covid.\n\nWe show that the most important drivers of benefit are: the degree of protection provided by previous infection; the protection provided by vaccination; the time since previous infection; and future attack rates. Vaccination can be very beneficial for previously infected children if future attack rates are high and several months have elapsed since the previous major wave in this group.\n\nBenefits are generally larger for Long Covid than hospitalisation, because Long Covid is both more common than hospitalisation and previous infection offers less protection against it.\n\nOur framework provides a structure for policy makers to explore the additional benefit of vaccination across a range of adverse outcomes and different parameter assumptions. It can be easily updated as new evidence emerges.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.11.23288403",
+    "rel_abs": "ObjectiveWe estimated the effectiveness of booster doses of monovalent and bivalent mRNA COVID-19 vaccines against Omicron-associated severe outcomes among adults aged [&ge;]50 years in Ontario, Canada.\n\nMethodsWe used a test-negative design to estimate vaccine effectiveness (VE), with unvaccinated adults as the comparator, against hospitalization or death among SARS-CoV-2-tested adults aged [&ge;]50 years between June 19, 2022 and January 28, 2023 stratified by time since vaccination. We explored VE by vaccine product (Moderna Spikevax(R) monovalent; Pfizer-BioNTech Comirnaty(R) monovalent; Moderna Spikevax(R) BA.1 bivalent; Pfizer-BioNTech Comirnaty(R) BA.4/BA.5 bivalent).\n\nResultsWe included 3,755 Omicron cases and 14,338 test-negative controls. For the Moderna and Pfizer-BioNTech monovalent vaccines, VE 7-29 days after vaccination was 85% (95% confidence interval [CI], 72-92%) and 88% (95%CI, 82-92%), respectively, and was 82% (95%CI, 76-87%) and 82% (95%CI, 77-86%) 90-119 days after vaccination. For the Moderna BA.1 bivalent vaccine, VE was 86% (95%CI, 82-90%) 7-29 days after vaccination and was 76% (95%CI, 66-83%) 90-119 days after vaccination. For the Pfizer-BioNTech BA.4/BA.5 bivalent vaccine, VE 7-29 days after vaccination was 83% (95%CI, 77-88%) and was 81% (95%CI 72-87%) 60-89 days after vaccination.\n\nConclusionsBooster doses of monovalent and bivalent mRNA COVID-19 vaccines provided similar, strong initial protection against severe outcomes in community-dwelling adults aged [&ge;]50 years in Ontario. Nonetheless, uncertainty remains around waning protection of these vaccines.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Christina Pagel",
-        "author_inst": "University College London"
+        "author_name": "Ramandip Grewal",
+        "author_inst": "Public Health Ontario"
       },
       {
-        "author_name": "Harrison Wilde",
-        "author_inst": "University College London"
+        "author_name": "Sarah A Buchan",
+        "author_inst": "Public Health Ontario"
       },
       {
-        "author_name": "Christopher Tomlinson",
-        "author_inst": "UCL"
+        "author_name": "Lena Nguyen",
+        "author_inst": "ICES"
       },
       {
-        "author_name": "Bilal A Mateen",
-        "author_inst": "University College London"
+        "author_name": "Sharifa Nasreen",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Katherine Brown",
-        "author_inst": "Great Ormond Street Hospital for Children"
+        "author_name": "Peter C Austin",
+        "author_inst": "ICES"
+      },
+      {
+        "author_name": "Kevin  A Brown",
+        "author_inst": "Public Health Ontario"
+      },
+      {
+        "author_name": "Jonathan Gubbay",
+        "author_inst": "BC Children's Hospital"
+      },
+      {
+        "author_name": "Nelson Lee",
+        "author_inst": "University of Toronto"
+      },
+      {
+        "author_name": "Kevin L Schwartz",
+        "author_inst": "Public Health Ontario"
+      },
+      {
+        "author_name": "Mina Tadrous",
+        "author_inst": "Women's College Hospital"
+      },
+      {
+        "author_name": "Kumanan Wilson",
+        "author_inst": "Ottawa Hospital Research Institute"
+      },
+      {
+        "author_name": "Sarah E Wilson",
+        "author_inst": "Public Health Ontario"
+      },
+      {
+        "author_name": "Jeffrey C Kwong",
+        "author_inst": "ICES"
+      },
+      {
+        "author_name": "- on behalf of the CIRN Provincial Collaborative Network investigators",
+        "author_inst": "-"
       }
     ],
     "version": "1",
-    "license": "",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2023.04.05.23288177",
@@ -56314,33 +56617,93 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2023.04.03.23288102",
-    "rel_title": "SARS-CoV-2 infection and post-acute risk of non-Covid-19 infectious disease hospitalizations: a nationwide cohort study of Danish adults aged >=50 years",
+    "rel_doi": "10.1101/2023.04.03.23287498",
+    "rel_title": "Longitudinal Analysis of Humoral and Cellular Immune Response Following SARS-CoV-2 Vaccination Supports Utilizing Point-Of-Care Tests to Enhance COVID-19 Booster Uptake.",
     "rel_date": "2023-04-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.03.23288102",
-    "rel_abs": "Reports suggest that the potential long-lasting health consequences of SARS-CoV-2 infection may involve persistent dysregulation of some immune populations, but the potential clinical implications are unknown. In a nationwide cohort of 2,430,694 50+-year-olds, we compared the rates of non-Covid-19 infectious disease inpatient hospitalizations (of [&ge;]5 hours) following the acute phase of SARS-CoV-2 infection in 930,071 individuals with rates among SARS-CoV-2 uninfected from 1 January 2021 to 10 December 2022. The post-acute phase of SARS-CoV-2 infection was associated with an incidence rate ratio of 0.90 (95% confidence interval 0.88-0.92) for any infectious disease hospitalization. Findings were similar for upper- (1.08, 0.97-1.20), lower respiratory tract (0.90, 0.87-0.93), influenza (1.04, 0.94-1.15), gastrointestinal (1.28, 0.78-2.09), skin (0.98, 0.93-1.03), urinary tract (1.01, 0.96-1.08), certain invasive bacterial (0.96, 0.91-0.1.01), and other (0.96, 0.92-1.00) infectious disease hospitalizations and in subgroups. Our study does not support an increased susceptibility to non-Covid-19 infectious disease hospitalization following SARS-CoV-2 infection.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.03.23287498",
+    "rel_abs": "Individuals with weaker neutralizing responses show reduced protection with SARS-CoV-2 variants. Booster vaccines are recommended for vaccinated individuals, but the uptake is low. We present the feasibility of utilizing point-of-care tests (POCT) to support evidence-based decision-making around COVID-19 booster vaccinations. Using infectious virus neutralization, ACE2 blocking, spike binding, and TCR sequencing assays, we investigated the dynamics of changes in the breadth and depth of blood and salivary antibodies as well as T-cell clonal response following mRNA vaccination in a cohort of healthcare providers. We evaluated the accuracy of two POCTs utilizing either blood or saliva to identify those in whom humoral immunity was inadequate. >4 months after two doses of mRNA vaccine, SARS-CoV-2 binding and neutralizing Abs (nAbs) and T-cell clones declined 40-80%, and 2/3rd lacked Omicron nAbs. After the third mRNA booster, binding and neutralizing Abs increased overall in the systemic compartment; notably, individuals with previously weak nAbs gained sharply. The third dose failed to stimulate secretory IgA, but salivary IgG closely tracked systemic IgG levels. Vaccine boosting increased Ab breadth against a divergent bat sarbecovirus, SHC014, although the TCR-beta sequence breadth was unchanged. Post 3rd booster dose, Ab avidity increased for the Wuhan and Delta strains, while avidity against Omicron and SHC014 increased to levels seen for Wuhan after the second dose. Negative results on POCTs strongly correlated with a lack of functional humoral immunity. The third booster dose helps vaccinees gain depth and breadth of systemic Abs against evolving SARS-CoV-2 and related viruses. Our findings show that POCTs are useful and easy-to-access tools to inform inadequate humoral immunity accurately. POCTs designed to match the circulating variants can help individuals with booster vaccine decisions and could serve as a population-level screening platform to preserve herd immunity.\n\nOne Sentence SummarySARS-CoV-2 point-of-care antibody tests are valuable and easy-to-access tools to inform inadequate humoral immunity and to support informed decision-making regarding the current and future booster vaccination.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Niklas Worm Andersson",
-        "author_inst": "Statens Serum Institut"
+        "author_name": "Michael Mallory",
+        "author_inst": "Department of Microbiology & Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA"
       },
       {
-        "author_name": "Emilia Myrup Thiesson",
-        "author_inst": "Statens Serum Institut"
+        "author_name": "Jennifer E. Munt",
+        "author_inst": "Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"
       },
       {
-        "author_name": "Ria Lassauniere",
-        "author_inst": "Statens Serum Institut"
+        "author_name": "Tara M. Narowski",
+        "author_inst": "Department of Microbiology & Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA"
       },
       {
-        "author_name": "Joergen Vinsloev Hansen",
-        "author_inst": "Statens Serum Institut"
+        "author_name": "Izabella Castillo",
+        "author_inst": "Department of Microbiology & Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA"
       },
       {
-        "author_name": "Anders Hviid",
-        "author_inst": "Statens Serum Institut"
+        "author_name": "Edwing Cuadra",
+        "author_inst": "Department of Microbiology & Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA"
+      },
+      {
+        "author_name": "Nora Pisanic",
+        "author_inst": "Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA"
+      },
+      {
+        "author_name": "Paul Fields",
+        "author_inst": "Adaptive Biotechnologies, Seattle, Washington, USA."
+      },
+      {
+        "author_name": "John M. Powers",
+        "author_inst": "Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"
+      },
+      {
+        "author_name": "Alexandria Dickson",
+        "author_inst": "Department of Molecular Microbiology & Immunology, Saint Louis University School of Medicine, Saint Louis, Missouri, USA."
+      },
+      {
+        "author_name": "Rohan Harris",
+        "author_inst": "Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA."
+      },
+      {
+        "author_name": "Richard Wargowsky",
+        "author_inst": "Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA."
+      },
+      {
+        "author_name": "Seamus Moran",
+        "author_inst": "Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA."
+      },
+      {
+        "author_name": "Ahmed Allabban",
+        "author_inst": "Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA."
+      },
+      {
+        "author_name": "Kristin Raphel",
+        "author_inst": "Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA."
+      },
+      {
+        "author_name": "Timothy A. McCaffrey",
+        "author_inst": "Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA."
+      },
+      {
+        "author_name": "James D. Brien",
+        "author_inst": "Department of Molecular Microbiology & Immunology, Saint Louis University School of Medicine, Saint Louis, Missouri, USA."
+      },
+      {
+        "author_name": "Christopher D. Heaney",
+        "author_inst": "Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA"
+      },
+      {
+        "author_name": "John E. Lafleur",
+        "author_inst": "Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA."
+      },
+      {
+        "author_name": "Ralph S. Baric",
+        "author_inst": "Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"
+      },
+      {
+        "author_name": "Lakshmanane Premkumar",
+        "author_inst": "Department of Microbiology & Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA"
       }
     ],
     "version": "1",
@@ -58140,91 +58503,63 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.03.28.23287848",
-    "rel_title": "Lasting first impression: Pre-existing immunity restricts mucosal antibody responses during Omicron breakthrough",
+    "rel_doi": "10.1101/2023.03.26.23287673",
+    "rel_title": "Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of COVID-19 Recovery",
     "rel_date": "2023-03-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.28.23287848",
-    "rel_abs": "Understanding mucosal antibody responses from SARS-CoV-2 infection and/or vaccination is crucial to develop strategies for longer term immunity, especially against emerging viral variants. We profiled serial paired mucosal and plasma antibodies from: COVID-19 vaccinated only vaccinees (vaccinated, uninfected), COVID-19 recovered vaccinees (convalescent, vaccinated) and individuals with breakthrough Delta or Omicron BA.2 infections (vaccinated, infected). Saliva from COVID-19 recovered vaccinees displayed improved antibody neutralizing activity, Fc{gamma}R engagement and IgA compared to COVID-19 uninfected vaccinees. Furthermore, repeated mRNA vaccination boosted SARS-CoV-2-specific IgG2 and IgG4 responses in both mucosa biofluids (saliva and tears) and plasma. IgG, but not IgA, responses to breakthrough COVID-19 variants were dampened and narrowed by increased pre-existing vaccine-induced immunity to the ancestral strain. Salivary antibodies delayed initiation of boosting following breakthrough COVID-19 infection, especially Omicron BA.2, however, rose rapidly thereafter. Our data highlight how pre-existing immunity shapes mucosal SARS-CoV-2-specific antibody responses and has implications for long-term protection from COVID-19.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.26.23287673",
+    "rel_abs": "Conventional whole-body 18F-FDG PET imaging provides a semi-quantitative evaluation of overall glucose metabolism without gaining insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19).\n\nMethodsThe study included thirteen healthy subjects and twelve recovering COVID-19 subjects within eight weeks of confirmed diagnosis. Each subject had a dynamic 18F-FDG scan on the uEXPLORER total-body PET/CT system for one hour. Semiquantitative standardized uptake value (SUV) and SUV ratio relative to blood (SUVR) were calculated for regions of interest (ROIs) in different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify microparametric rate constants K1 and k3 that characterize 18F-FDG blood-to-tissue delivery and intracellular phosphorylation, respectively, and a macroparameter Ki that represents 18F-FDG net influx rate. Statistical tests were performed to examine differences between the healthy controls and recovering COVID-19 subjects. Impact of COVID-19 vaccination was investigated. We further generated parametric images to confirm the ROI-based analysis.\n\nResultsWe detected no significant difference in lung SUV but significantly higher lung SUVR and Ki in the recovering COVID-19 subjects, indicating an improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k3, but not with the delivery rate K1, which suggests it is glucose phosphorylation, not glucose delivery, that drives the observed difference of glucose metabolism in the lungs. Meanwhile, there was no or little difference in bone marrow metabolism measured with SUV, SUVR and Ki, but a significant increase in bone-marrow 18F-FDG delivery rate K1 in the COVID-19 group (p < 0.05), revealing a difference of glucose delivery in this immune-related organ. The observed differences were lower or similar in vaccinated COVID-19 subjects as compared to unvaccinated ones. The organ ROI-based findings were further supported by parametric images.\n\nConclusionsHigher lung glucose metabolism and bone-marrow glucose delivery were observed with total-body multiparametric 18F-FDG PET in recovering COVID-19 subjects as compared to healthy subjects, which suggests continued inflammation due to COVID-19 during the early stages of recovery. Total-body multiparametric PET of 18F-FDG delivery and metabolism can provide a more sensitive tool and more insights than conventional static whole-body 18F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Kevin J Selva",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Pradhipa Ramanathan",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Ebene R Haycroft",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Arnold Reynaldi",
-        "author_inst": "Kirby Institute, University of NSW"
-      },
-      {
-        "author_name": "Deborah Cromer",
-        "author_inst": "Kirby Institute, University of NSW"
-      },
-      {
-        "author_name": "Chee Wah Tan",
-        "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School"
-      },
-      {
-        "author_name": "Lin-Fa Wang",
-        "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School"
-      },
-      {
-        "author_name": "Bruce D Wines",
-        "author_inst": "Immune Therapies Laboratory, Burnet Institute"
+        "author_name": "Yiran Wang",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "P. Mark Hogarth",
-        "author_inst": "Immune Therapies Laboratory, Burnet Institute"
+        "author_name": "Lorenzo Nardo",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Laura E Downie",
-        "author_inst": "Department of Optometry and Vision Sciences, University of Melbourne"
+        "author_name": "Benjamin A. Spencer",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Samantha K Davis",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Yasser G. Abdelhafez",
+        "author_inst": "University of California, Davis, and Assiut University"
       },
       {
-        "author_name": "Ruth A Purcell",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Elizabeth J. Li",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Helen E Kent",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Negar Omidvari",
+        "author_inst": "University of California Davis"
       },
       {
-        "author_name": "Jennifer A Juno",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Abhijit J. Chaudhari",
+        "author_inst": "University of California Davis"
       },
       {
-        "author_name": "Adam K Wheatley",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Ramsey D. Badawi",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Miles Philip Davenport",
-        "author_inst": "Kirby Institute, University of New South Wales"
+        "author_name": "Terry Jones",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Stephen J Kent",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Simon R. Cherry",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Amy W Chung",
-        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Guobao Wang",
+        "author_inst": "University of California - Davis"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2023.03.29.23287924",
@@ -59697,35 +60032,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.03.25.534209",
-    "rel_title": "AI-Designed, Mutation-Resistant Broad Neutralizing Antibodies Against Multiple SARS-CoV-2 Strains",
+    "rel_doi": "10.1101/2023.03.27.23287800",
+    "rel_title": "Lower vaccination coverage against COVID-19 in school-aged children is associated with low socioeconomic status in the Metropolitan Area of Santiago, Chile.",
     "rel_date": "2023-03-27",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.25.534209",
-    "rel_abs": "In this study, we generated a Digital Twin for SARS-CoV-2 by integrating data and meta-data with multiple data types and processing strategies, including machine learning, natural language processing, protein structural modeling, and protein sequence language modeling. This approach enabled the computational design of broadly neutralizing antibodies against over 1300 different historical strains of SARS-COV-2 containing 64 mutations in the receptor binding domain (RBD) region. The AI-designed antibodies were experimentally validated in real-virus neutralization assays against multiple strains including the newer Omicron strains that were not included in the initial design base. Many of these antibodies demonstrate strong binding capability in ELISA assays against the RBD of multiple strains. These results could help shape future therapeutic design for existing strains, as well as predicting hidden patterns in viral evolution that can be learned by AI for developing future antiviral treatments.",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.27.23287800",
+    "rel_abs": "BackgroundThe burden of COVID-19 has been heterogeneous, indicating that the effects of this disease are synergistic with both other non-communicable diseases and socioeconomic status (SES), high-lighting its syndemic character. While the appearance of vaccines has moderated the pandemic effects, their coverage has also been heterogeneous, both when comparing different countries, and when comparing different populations within countries. Of note, once again SES appears to be a correlated factor.\n\nMethodsTo examine the relationship between SES and vaccination coverage, we analyzed publicly available data detailing the percentage of school-aged vaccinated children in different municipalities belonging to the Metropolitan Area (MA) of Santiago, Chile, one of the most largely vaccinated countries in the world. Vaccination data was compiled per school type, either public, state-subsidized and private, at three different dates along the COVID-19 pandemic so to cover the dispersion of Delta, and Omicron, including Omicron subvariants BA.4 and BA.5. We computed the median vaccination ratio for each municipality and school type and calculated their Spearmans rank correlation coefficient with each one of nine SES indices.\n\nFindingsIn the MA of Santiago, Chile, the percentage of school-age children who have received vaccinations against COVID-19 correlates with SES. Vulnerable municipalities with low SES exhibit low levels of vaccination coverage. Of note, this strong correlation is observed in both public and state-subsidized schools, but to a meaningless extent in private schools. Although inequity in vaccination coverage decreases over time, it remains higher among students enrolled either in public and state-subsidized schools compared to those of private schools.\n\nInterpretationAvailable data is insufficient to explore plausible causes behind lower vaccination coverage in vulnerable municipalities in the MA of Santiago, Chile. However, considering the available literature, it is likely that a combination of factors including the lack of proper information about the importance of vaccination, the lack of incentives for childrens vaccination, low trust in the government, and/or limited access to vaccines for lower-income people, may all have contributed to this low vaccination coverage. Importantly, unless corrected, the inequity in vaccination coverage will exacerbate the syndemic nature of COVID-19.\n\nFundingThis material is based upon work supported by the U.S. Air Force Office of Scientific Research under award number FA9550-20-1-0196. Financial support is also acknowledged to Centro Ciencia & Vida, FB210008, Financiamiento Basal para Centros Cientificos y Tecnologicos de Excelencia de ANID.",
     "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Yue Kang",
-        "author_inst": "Ainnocence Inc."
+        "author_name": "Enzo Guerrero-Araya",
+        "author_inst": "Fundacion Ciencia & Vida"
       },
       {
-        "author_name": "Yang Jiao",
-        "author_inst": "Ainnocence Inc."
+        "author_name": "Cesar R Ravello",
+        "author_inst": "Universidad San Sebastian"
       },
       {
-        "author_name": "Kevin Jin",
-        "author_inst": "Ainnocence Inc."
+        "author_name": "Mario Rosemblatt",
+        "author_inst": "Fundacion Ciencia & Vida, Universidad San Sebastian"
       },
       {
-        "author_name": "Lurong Pan",
-        "author_inst": "Ainnocence Inc."
+        "author_name": "Tomas Perez-Acle",
+        "author_inst": "Fundacion Ciencia y Vida, Universidad San Sebastian"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc_by_nc",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2023.03.22.23287571",
@@ -61479,35 +61814,23 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.03.22.23287577",
-    "rel_title": "Coverage of state-initiated contact-tracing during COVID-19 and factors influencing it: evidence from real-world data",
+    "rel_doi": "10.1101/2023.03.21.23287546",
+    "rel_title": "How influenza vaccination changed over the COVID-19 pandemic?",
     "rel_date": "2023-03-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.22.23287577",
-    "rel_abs": "Contact tracing has been one of the central non-pharmaceutical interventions implemented worldwide to try to control the spread of Sars-CoV-2, but its effectiveness strongly depends on its ability to detect contacts. To investigate this issue, we analysed an extensive operational database of SARS-CoV-2 tests in Geneva and used permutations statistics to estimate the number of secondary infectious contacts occurring at the same address. Results show that manual contact tracing captured on average 41% of the secondary infections occurring at the address, with variation in time from 23% during epidemic peaks to 60% during low epidemic activity. The under-reporting of contacts is influenced by both socio-economic and structural factors. People living in wealthy neighbourhoods are less likely to report contacts (adjusted odds ratio (aOR): 1.6) People living in buildings are also less likely to report contacts, with an aOR of 1.08 to 3.14 depending on the variant of concern, the size of the building and if the building had shops. This under-reporting of contacts in buildings decreased during periods of mandatory mask wearing and restriction of private gathering, highlighting the importance of public measures in reducing unnoticed infections in shared spaces. More effective contact tracing strategy should be partly digitalized to avoid saturation of contact tracing capacity during high activity of the pandemics. Public message and outreach should communicate on avoiding unnoticed infectious contacts in large building and may benefit from targeting specific population, such as those in wealthy areas.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched MEDLINE via Pubmed and the WHO-COVID-19 research database from the database inception until February 27, 2023 for relevant studies on the effect of contact tracing to curb COVID-19 transmission or on contact tracing coverage, with no language restriction, using the following terms: (COVID-19) AND (Contact tracing) AND (Efficacy or effectiveness or digital or transmission or coverage).\n\nSimilarly to what has been reported by a recent systematic review evaluating the effect of contact tracing in controlling the spread of infectious disease, we mostly found mathematical modelling studies, and 13 observational studies. Observational studies have contrasted results about contact tracing effectiveness. Only 2 of them report global contact tracing coverage, estimated as the percentage of cases that were identified as contacts, which are below 11%. No study identify the factors affecting the contact tracing coverage. Modeling studies identified the adherence to quarantine, the notification delay and the contact tracing coverage (for manual contact tracing) or the app adherence (for mobile app based contact tracing) as the key factors for contact tracing efficiency.\n\nAdded value of this studyAn operational COVID-19 infections database register and the use of permutation tests allowed a precise quantification of the coverage of the manual contact tracing system of the state of Geneva, Switzerland, and the factor affecting it. On average, 41% of the infected persons residing at the same address were reported. The rich information available in the register was used to identify the factors associated with under-reporting, which were wealthy neighborhoods, large buildings, and non-vaccination of the index-contact pair.\n\nImplications of all the available evidenceImplementing more efficient contact tracing for future covid-19 resurgence or other pandemics is crucial. A multi-modal approach, consisting of manual and digital contact tracing and prevention of unnoticed infection, with a particular focus on populations with high contact under-reporting, could help reduce the transmission of infectious disease. However, at least for similar highly contagious aerosol-transmitted diseases, contact tracing will not be sufficient, and systemic policies such as masking, air filtration or gathering restrictions may be necessary.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.21.23287546",
+    "rel_abs": "BackgroundVaccination for seasonal influenzas is particularly important during the COVID-19 pandemic, but the influenza vaccination coverage in the U.S. was far lower than the targeted rate.\n\nObjectiveTo examine how peoples actual uptake of the influenza vaccine and the disparity of the vaccination changed during the pandemic.\n\nMethodsA survey was conducted online in November 2022. Respondents were asked for influenza vaccination during each of the three latest seasons, prior influenza vaccination history, and COVID-19 vaccination. A linear regression model was used to estimate how the respondents change in influenza vaccination was associated with their demographics, COVID-19 vaccination status, and other related variables.\n\nResultsNearly 70% of US adults had influenza vaccine each season during past the three seasons of the COVID-19 pandemic. The prevalence of influenza vaccination varied markedly across demographics. Non-Hispanic Black, Hispanic, and people with low educational attainment were more likely to see relatively negative changes in their level of influenza vaccination. Respondents who uptook their COVID-19 vaccine in 2022 increased their level of influenza vaccine more than those who uptook the vaccine in 2021.\n\nConclusionsOur study indicated that influenza vaccination increased during the pandemic compared with before the pandemic. The disparity of influenza vaccination by race/ethnicity and socioeconomic status may enlarge during the pandemic. Tailored interventions were needed to target some groups to promote their vaccination uptake.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Denis Mongin",
-        "author_inst": "University of Geneva"
-      },
-      {
-        "author_name": "Nils Burgisser",
-        "author_inst": "Geneva University Hospitals"
-      },
-      {
-        "author_name": "Delphine Sophie Courvoisier",
-        "author_inst": "University of Geneva"
-      },
-      {
-        "author_name": "- Covid-SMC Study Group",
-        "author_inst": "-"
+        "author_name": "Yong Yang",
+        "author_inst": "University of Memphis"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2023.03.22.23287566",
@@ -63436,93 +63759,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.03.17.23287396",
-    "rel_title": "Demographic and co-morbidity characteristics of patients tested for SARS-CoV-2 from March 2020 to January 2022 in a national clinical research network: results from PCORnet(R)",
+    "rel_doi": "10.1101/2023.03.17.23287411",
+    "rel_title": "Protection against symptomatic SARS-CoV-2 BA.5 infection conferred by the Pfizer-BioNTech Original/BA.4-5 bivalent vaccine compared to the mRNA Original (ancestral) monovalent vaccines - a matched cohort study in France",
     "rel_date": "2023-03-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.17.23287396",
-    "rel_abs": "BackgroundPrior studies have documented differences in the age, racial, and ethnic characteristics among patients with SARS-CoV-2 infection. However, little is known about how these characteristics changed over time during the pandemic and whether racial, ethnic, and age disparities evident early in the pandemic were persistent over time. This study reports on trends in SARS-CoV-2 infections among U.S. adults from March 1, 2020 to January, 31 2022, using data from electronic health records.\n\nMethods and FindingsWe captured repeated cross-sectional information from 43 large healthcare systems in 52 U.S. States and territories, participating in PCORnet(R), the National Patient-Centered Clinical Research Network. Using distributed queries executed at each participating institution, we acquired information for all patients [&ge;] 20 years of age who were tested for SARS-CoV-2 (both positive and negative results), including care setting, age, sex, race, and ethnicity by month as well as comorbidities (assessed with diagnostic codes).\n\nDuring this time period, 1,325,563 patients had positive (13% inpatient) and 6,705,868 patients had negative (25% inpatient) viral tests for SARS-CoV-2. Disparities in testing positive were present across racial and ethnic groups, especially in the inpatient setting. Compared to White patients, Black or African American and other race patients had relative risks for testing positive of 1.5 or greater in the inpatient setting for 12 of the 23-month study period. Compared to non-Hispanic patients, Hispanic patients had relative risks for testing positive in the inpatient setting of 1.5 or greater for 16 of 23. Ethnic and racial differences were present in emergency department and ambulatory settings but were less common across time than in inpatient settings. Trends in infections by age group demonstrated higher test positivity for older patients in the inpatient setting only for most months, except for June and July of 2020, April to August 2021, and January 2022. Comorbidities were common, with much higher rates among those hospitalized; hypertension (38% of patients SARS-CoV-2 positive vs. 29% for those negative) and type 2 diabetes mellitus (22% vs. 13%) were the most common.\n\nConclusion and RelevanceRacial and ethnic disparities changed over time among persons infected with SARS-CoV-2. These trends highlight potential underlying mechanisms, such as poor access to care and differential vaccination rates, that may have contributed to greater disparities, especially early in the pandemic. Monitoring data on characteristics of patients testing positive in real time could allow public health officials and policymakers to tailor interventions to ensure that patients and communities most in need are receiving adequate testing, mitigation strategies, and treatment.",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.17.23287411",
+    "rel_abs": "This cohort study aimed to evaluate the protection against symptomatic SARS-CoV-2 infection conferred by the Pfizer-BioNTech Original/BA.4-5 bivalent vaccine compared to mRNA Original (ancestral) monovalent vaccines. Individuals of [&ge;]60 years old who received a booster dose between 03/10/2022 and 06/11/2022, when both the bivalent and monovalent vaccines were used in France, were included. Individuals who received a booster dose with (1) a monovalent Original mRNA vaccine (Pfizer- BioNTech or Moderna) or (2) the bivalent Pfizer-BioNTech Original/BA.4-5 vaccine were matched. The outcome of interest was a positive SARS-CoV-2 RT-PCR or antigenic test associated to self-reported symptoms, at least seven days after receiving the booster dose. Data were analysed with a Cox Proportional-Hazards model adjusted for the presence of previous infection, age, sex, and the presence of medium risk comorbidities. A total of 136,852 individuals were included and followed for a median period of 77 days. The bivalent vaccine conferred an additional protection of 8% [95% CI: 0% - 16%, p=0.045] against symptomatic SARS-CoV-2 infection compared to the monovalent vaccines.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Jason  P Block",
-        "author_inst": "Harvard Medical School/Harvard Pilgrim Health Care Institute"
-      },
-      {
-        "author_name": "Keith  A. Marsolo",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "Kshema Nagavedu",
-        "author_inst": "Harvard Pilgrim Health Care Institute: Harvard Pilgrim Health Care"
-      },
-      {
-        "author_name": "L. Charles Bailey",
-        "author_inst": "The Children's Hospital of Philadelphia"
-      },
-      {
-        "author_name": "Tegan  K. Boehmer",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Julia Fearrington",
-        "author_inst": "Harvard Pilgrim Health Care Institute: Harvard Pilgrim Health Care"
-      },
-      {
-        "author_name": "Aaron  M. Harris",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Nedra Garrett",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Alyson  B Goodman",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Adi  V. Gundlapalli",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Rainu Kaushal",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Abel Kho",
-        "author_inst": "Northwestern University"
-      },
-      {
-        "author_name": "Kathleen  M. McTigue",
-        "author_inst": "University of Pittsburgh"
-      },
-      {
-        "author_name": "Vinit  P. Nair",
-        "author_inst": "PRACnet"
-      },
-      {
-        "author_name": "Jon Puro",
-        "author_inst": "OCHIN: Oregon Community Health Information Network"
+        "author_name": "Vincent Auvigne",
+        "author_inst": "Public Health France"
       },
       {
-        "author_name": "Elizabeth Shenkman",
-        "author_inst": "University of Florida College of Medicine"
+        "author_name": "Cynthia Tamandjou",
+        "author_inst": "Public Health France"
       },
       {
-        "author_name": "Mark  G. Weiner",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Justine Schaeffer",
+        "author_inst": "Public Health France"
       },
       {
-        "author_name": "Neely Williams",
-        "author_inst": "Community Partners Network, Inc"
+        "author_name": "Sophie Vaux",
+        "author_inst": "Public Health France"
       },
       {
-        "author_name": "Thomas  W. Carton",
-        "author_inst": "Louisiana Public Health Institute"
+        "author_name": "Isabelle Parent du Chatelet",
+        "author_inst": "Public Health France"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -65306,43 +65573,139 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2023.03.14.23287258",
-    "rel_title": "Left ventricular global longitudinal strain as a parameter of mild myocardial dysfunction in athletes after COVID-19",
+    "rel_doi": "10.1101/2023.03.15.23287292",
+    "rel_title": "Living alone and mental health: parallel analyses in longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic",
     "rel_date": "2023-03-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.14.23287258",
-    "rel_abs": "BackgroundWhether impaired left ventricular (LV) function contributes to persistent cardiopulmonary symptoms or decreased exercise capacity after COVID-19 remains unclear. The aim of this prospective study was to determine differences in LV global longitudinal strain (GLS) between athletes who did not have a history of LV dysfunction but had a positive COVID-19 test (PCAt) and healthy control (CON) athletes and relate them to symptoms during COVID-19.\n\nMethodsWe performed 151 transthoracic echocardiographies in our high-performance laboratory. GLS was determined in four-, two-, and three-chamber views and assessed offline by a blinded investigator in 88 PCAt (35% women) at a median of two months after COVID-19 who trained at least three times per week with more than 20 MET per week and 52 CONs from the German national squad (38% women).\n\nResultsGLS was significantly lower (GLS -18.53{+/-}1.94% vs. -19.94{+/-}1.42%, p<0.001) and diastolic function significantly reduced (E/A 1.54{+/-}0.52 vs. 1.66{+/-}0.43, p=0.020; El 0.15{+/-}0.04 vs. 0.17{+/-}0.04, p=0.009; E/El 5.74{+/-}1.74 vs. 5.22{+/-}1.36, p=0.024) in PCAt. There was no association between GLS and acute symptoms like resting dyspnea, exertional dyspnea during or after COVID-19, palpitations, chest pain or increased resting heart rate. However, there was a trend toward lower GLS in PCAt with subjectively perceived performance limitation (p=0.054).\n\nConclusionsIn a cohort of athletes at a median two months after COVID-19, significantly lower GLS and diastolic function were observed, suggesting mild myocardial dysfunction. GLS could be used as a screening element during return-to-sport examinations.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.15.23287292",
+    "rel_abs": "ObjectivesTo describe the mental health gap between those who live alone and those who live with others, and to examine whether the COVID-19 pandemic had an impact on this gap.\n\nDesignTen population based prospective cohort studies, and a retrospective descriptive cohort study based on electronic health records (EHRs).\n\nSettingUK Longitudinal population-based surveys (LPS), and primary and secondary care records within the OpenSAFELY-TPP database.\n\nParticipantsParticipants from the LPS were included if they had information on living status in early 2020, valid data on mental ill-health at the closest pre-pandemic assessment and at least once during the pandemic, and valid data on a key minimum set of covariates. The EHR dataset included 16 million adults registered with primary care practices in England using TPP SystmOne software on 1st February 2020, with at least three months of registration, valid address data, and living in households of <16 people.\n\nMain outcome measuresIn the LPS, self-reported survey measures of psychological distress and life satisfaction were assessed in the nearest pre-pandemic sweep and three periods during the pandemic: April-June 2020, July-October 2020, and November 2020-March 2021. In the EHR analyses, outcomes were morbidity codes recorded in primary or secondary care between March 2018 and January 2022 reflecting the diagnoses of depression, self-harm, anxiety, obsessive compulsive disorder, eating disorders, and severe mental illnesses.\n\nResultsThe LPS consisted of 37,544 participants (15.2% living alone) and we found greater psychological distress (SMD: 0.09 (95% CI: 0.04, 0.14) and lower life satisfaction (SMD: -0.22 (95% CI: -0.30, -0.15) in those living alone pre-pandemic, and the gap between the two groups stayed similar after the onset of the pandemic. In the EHR analysis of almost 16 million records (21.4% living alone), codes indicating mental health conditions were more common in those who lived alone compared to those who lived with others (e.g., depression 26 and severe mental illness 58 cases more per 100,000). Recording of mental health conditions fell during the pandemic for common mental health disorders and the gap between the two groups narrowed.\n\nConclusionsMultiple sources of data indicate that those who live alone experience greater levels of common and severe mental illnesses, and lower life satisfaction. During the pandemic this gap in need remained, however, there was a narrowing of the gap in service use, suggesting greater barriers to healthcare access for those who live alone.\n\nSummary BoxO_ST_ABSWhat is already known on the topic?C_ST_ABSHouseholds with one individual are an increasing demographic, comprising over a quarter of all households in the UK in 2021. However, the mental health gap between those who live alone compared to those who live with others is not well described and even less is known about the relative gaps in need and healthcare-seeking and access. The pandemic and associated restrictive measures further increased the likelihood of isolation for this group, which may have impacted mental health.\n\nWhat this study adds?We present comprehensive evidence from both population-based surveys and electronic health records regarding the greater levels of mental health symptoms and in recorded diagnoses for common (anxiety, depression) and less common (OCD, eating disorders, SMIs) mental health conditions for people living alone compared to those living with others.\n\nOur analyses indicate that mental health conditions are more common among those who live alone compared to those who live with others. Although levels of reported distress increased for both groups during the pandemic, healthcare-seeking dropped in both groups, and the rates of healthcare-seeking among those who live alone converged with those who live with others for common mental health conditions. This suggests greater barriers for treatment access among those that live alone.\n\nThe findings have implications for mental health service planning and efforts to reduce barriers to treatment access, especially for individuals who live on their own.",
+    "rel_num_authors": 30,
     "rel_authors": [
       {
-        "author_name": "Jana Schellenberg",
-        "author_inst": "University Hospital Ulm"
+        "author_name": "Eoin McElroy",
+        "author_inst": "School of Psychology, Ulster University, Coleraine, UK"
+      },
+      {
+        "author_name": "Emily Herrett",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
+      },
+      {
+        "author_name": "Kishan Patel",
+        "author_inst": "MRC Unit for Lifelong Health and Ageing, University College London, London, UK"
+      },
+      {
+        "author_name": "Dominik M Piehlmaier",
+        "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford; University of Sussex Business Sch"
+      },
+      {
+        "author_name": "Giorgio Di Gessa",
+        "author_inst": "Department of Epidemiology & Public Health, University College London, London, UK"
+      },
+      {
+        "author_name": "Charlotte Huggins",
+        "author_inst": "Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK"
+      },
+      {
+        "author_name": "Michael J Green",
+        "author_inst": "MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK"
+      },
+      {
+        "author_name": "Alex SF Kwong",
+        "author_inst": "MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; Division of Psychiatry, University of Edinburgh, Edinburgh, UK"
       },
       {
-        "author_name": "Magdalena Ahathaller",
-        "author_inst": "University Hospital of Ulm"
+        "author_name": "Ellen J Thompson",
+        "author_inst": "Department of Twin Research and Genetic Epidemiology, Kings College London"
       },
       {
-        "author_name": "Lynn Matits",
-        "author_inst": "University Hospital of Ulm"
+        "author_name": "Jingmin Zhu",
+        "author_inst": "Department of Epidemiology & Public Health, University College London, London, UK"
       },
       {
-        "author_name": "Johannes Kirsten",
-        "author_inst": "University Hospital of Ulm"
+        "author_name": "Kathryn E Mansfield",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
+      },
+      {
+        "author_name": "Richard J Silverwood",
+        "author_inst": "Centre for Longitudinal Studies, University College London, London, UK"
+      },
+      {
+        "author_name": "Rosie Mansfield",
+        "author_inst": "Centre for Longitudinal Studies, University College London, London, UK"
+      },
+      {
+        "author_name": "Jane Maddock",
+        "author_inst": "MRC Unit for Lifelong Health and Ageing, University College London, London, UK"
+      },
+      {
+        "author_name": "Rohini Mathur",
+        "author_inst": "Centre for Primary Care, Wolfson Insitute of Population Health, Queen Mary, University of London, London"
+      },
+      {
+        "author_name": "Ruth E Costello",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
+      },
+      {
+        "author_name": "Anthony A Matthews",
+        "author_inst": "Karolinska Institutet, Stockholm, Sweden"
       },
       {
-        "author_name": "Johannes Kersten",
-        "author_inst": "University Hospital of Ulm"
+        "author_name": "John Tazare",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
+      },
+      {
+        "author_name": "Alasdair Henderson",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
+      },
+      {
+        "author_name": "Kevin Wing",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
+      },
+      {
+        "author_name": "Lucy Bridges",
+        "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford"
+      },
+      {
+        "author_name": "Sebastian Bacon",
+        "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford"
+      },
+      {
+        "author_name": "Amir Mehrkar",
+        "author_inst": "Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford"
+      },
+      {
+        "author_name": "- OpenSafely Collaborative",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Richard John Shaw",
+        "author_inst": "MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK"
+      },
+      {
+        "author_name": "Jacques Wels",
+        "author_inst": "MRC Unit for Lifelong Health and Ageing, University College London, London, UK"
+      },
+      {
+        "author_name": "Srinivasa Vittal Katikireddi",
+        "author_inst": "MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK"
+      },
+      {
+        "author_name": "Nishi Chaturvedi",
+        "author_inst": "MRC Unit for Lifelong Health and Ageing, University College London, London, UK"
+      },
+      {
+        "author_name": "Laurie Tomlinson",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
       },
       {
-        "author_name": "Juergen Steinacker",
-        "author_inst": "University Hospital of Ulm"
+        "author_name": "Praveetha Patalay",
+        "author_inst": "MRC Unit for Lifelong Health and Ageing, University College London, London, UK; Centre for Longitudinal Studies, University College London, London, UK"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "cardiovascular medicine"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2023.03.15.23287298",
@@ -66816,41 +67179,61 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.03.09.23287033",
-    "rel_title": "Spatio-temporal distributions of COVID-19 vaccine doses uptake in the Netherlands: A Bayesian ecological modelling analysis",
+    "rel_doi": "10.1101/2023.03.09.23286855",
+    "rel_title": "Index Cases First Identified by Nasal-Swab Rapid COVID-19 Tests Had More Transmission to Household Contacts Than Cases Identified by Other Test Types",
     "rel_date": "2023-03-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.09.23287033",
-    "rel_abs": "BackgroundIn the transitioning era towards the COVID-19 endemic, there is still a sizable population that has never been vaccinated against COVID-19 in the Netherlands. To identify regions and populations that have a lower chance of vaccination uptake, this study provides a spatio-temporal estimation of the relative chance of COVID-19 vaccination uptake for the first, second, and the booster doses in the Netherlands on both municipality level and the public health services (regional) level.\n\nMethodsData on COVID-19 vaccination uptake were retrieved from the publicly available national COVID-19 surveillance dataset. We used a Bayesian spatio-temporal modelling technique with the integrated nested Laplace approximation to account for the spatial structure and the space-time interaction. Additionally, we used an ecological regression modelling technique which takes into account areal level socio-demographic characteristics to adjust for their potential impact on the chance of the regional vaccination uptake.\n\nResultsOur findings revealed a heterogenous spatio-temporal distribution of the relative chance of COVID-19 vaccination uptake with highly overlapping trends of all three vaccination doses. Internal heterogeneity of COVID-19 vaccination uptake within one public health services region on the municipality level was also identified. The Dutch main urban area and the most religiously conservative regions were identified to have a lower-than-average chance of COVID-19 vaccination uptake compared to the rest of the country. Ecological regression modelling analysis revealed that regions with a higher proportion of non-Western immigrants had a lower chance of COVID-19 vaccination uptake for all vaccination scenarios.\n\nConclusionThe obtained estimates should inform national and local COVID-19 vaccination policies and service strategies in the Netherlands for the ongoing COVID-19 campaign on the second booster. Namely, more regional efforts and services may be needed to close  vaccination gaps and optimise COVID-19 health-related outcomes, especially with regard to regions with a relatively higher proportion of marginalised populations.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.09.23286855",
+    "rel_abs": "ImportanceAt-home rapid COVID-19 tests utilize nasal-swab specimens and require high viral loads to reliably give positive results. Longitudinal studies from the onset of infection have found infectious virus can present in oral specimens days before nasal. Detection and initiation of infection-control practices may therefore be delayed when nasal-swab rapid tests are used, resulting in greater exposure and transmission to contacts.\n\nObjectiveWe assessed whether index cases first identified by rapid nasal-swab COVID-19 tests had more transmission to household contacts than index cases who used other test types (tests with higher analytical sensitivity but longer turnaround times, and/or that utilize non-nasal specimen types).\n\nDesignIn this observational cohort study, members of households with a recent COVID-19 case were screened for infection at least daily by RT-qPCR on one or more self-collected upper-respiratory specimen types. Participants reported demographic/medical information (including COVID-19 testing), symptom and exposure information, and household infection-control practices. A two-level random intercept model was used to assess the association between the infection outcome of household contacts and each covariable (household size, race/ethnicity, age, vaccination status, viral variant, infection-control practices, and whether a rapid nasal-swab test was used to initially identify the household index case).\n\nSettingSouthern California, September 2020--June 2021 and November 2021--March 2022.\n\nParticipantsCohort of 370 individuals from 85 households.\n\nMain Outcome(s) and Measure(s)Transmission was quantified by adjusted secondary attack rates (aSAR) and adjusted odds ratios (aOR).\n\nResultsAn aSAR of 53.6% (95% CI 38.8-68.3%) was observed among households where the index case first tested positive by a rapid nasal-swab COVID-19 test, which was significantly higher than the aSAR for households where the index case utilized another test type (27.2% 95% CI 19.5- 35.0%, P=0.003 pairwise comparisons of predictive margins). We observed an aOR of 4.90 (95% CI 1.65-14.56) for transmission to household contacts when a nasal-swab rapid test was used to identify the index case, compared to other test types.\n\nConclusions and RelevanceUse of nasal-swab rapid COVID-19 tests for initial detection of infection and initiation of infection control may not limit transmission as well as other test types.\n\nKey Points1. QuestionDoes identification of index cases by rapid nasal-swab tests limit household transmission of SARS-CoV-2 as well as other test types?\n\n2. FindingSignificantly higher adjusted secondary attack rates and adjusted odds ratios for transmission were observed in households where the index case used a nasal rapid COVID-19 test for initial detection versus other test types.\n\n3. MeaningThe use of nasal-swab rapid COVID-19 tests for initial detection of infection and initiation of infection control may not limit transmission as well as other test types.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Haoyi Wang",
-        "author_inst": "Maastricht University"
+        "author_name": "Jenny Ji",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Tugce Varol",
-        "author_inst": "Maastricht University"
+        "author_name": "Alexander Viloria Winnett",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Thomas Gultzow",
-        "author_inst": "Maastricht University"
+        "author_name": "Natasha Shelby",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Hanne M.L. Zimmermann",
-        "author_inst": "Maastricht University"
+        "author_name": "Jessica A. Reyes",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Robert A.C. Ruiter",
-        "author_inst": "Maastricht Univrsity"
+        "author_name": "Noah W. Schlenker",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Kai J. Jonas",
-        "author_inst": "Maastricht University"
+        "author_name": "Hannah Davich",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Saharai Caldera",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Colten Tognazzini",
+        "author_inst": "Pasadena Public Health Department"
+      },
+      {
+        "author_name": "Ying-Ying Goh",
+        "author_inst": "Pasadena Public Health Department"
+      },
+      {
+        "author_name": "Matthew Feaster",
+        "author_inst": "Pasadena Public Health Department"
+      },
+      {
+        "author_name": "Rustem F. Ismagilov",
+        "author_inst": "California Institute of Technology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -68650,29 +69033,53 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2023.03.06.23286877",
-    "rel_title": "Predictors of mortality among post-COVID-19 discharged patients in Northern India",
+    "rel_doi": "10.1101/2023.03.06.23286853",
+    "rel_title": "Oral SARS-CoV-2 host responses predict the early COVID-19 disease course",
     "rel_date": "2023-03-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.06.23286877",
-    "rel_abs": "BackgroundThe one-year post-discharge all-cause mortality rate of COVID-19 disease is 7.87 % with the majority of patients readmission and mortality occurring within the first 30 days post-discharge.\n\nObjectiveUnderstanding predictors of mortality will help in prioritising patient care and preventive approaches.\n\nMethodsOurs a single-centre unmatched case control study at a tertiary care centre in northern India, conducted from April 2020 to September 2022. The data was extracted retrospectively from the electronic hospital medical records of patients and by trained physicians using standardised data extraction sheet.\n\nResultsA total of 184 patients were enrolled with 92 cases and 92 controls. The mean age of patients was 49.3 {+/-} 17.53 years. The mortality group had a higher mean age (53.24 {+/-} 18.53 yrs) as compared to the control group (45.37 {+/-} 15.58 yrs) [p - 0.002]. Bivariate analysis revealed a significant difference in the two groups with respect to O2 saturation at admission [Case - 91.12 {+/-} 12.49 %, control - 95.46 {+/-} 5.01 %, p - 0.003); Maximum O2 flow rate [L/min] (Case - 11.01 {+/-} 22.2, Control - 6.41 {+/-} 13.31, P - 0.04); ICU need (p - 0.005), Cancer (p - 0.001), O2 need at discharge (p - 0.001) and AKI (p - 0.007). On multiple regression analysis, Cancer (aOR-2.469; 95% CI-1.183-5.150, p-0.016), ICU admission (aOR- 2.446; 95% CI-1.212-4.938, p- 0.013), Oxygen at discharge (aOR- 2.340; 95% CI-0.971-5.640, p-0.0586) and Acute kidney injury (aOR- 5.6; 95% CI-2.351-13.370, p-0.00) only found to be significant.\n\nConclusionOxygen requirement at discharge (2.3 times), Malignancy (2.4 times), ICU admission (2.4 times), and Acute Kidney Injury (5.6 times) were risks of death among COVID-19-recovered patients, post discharge. The presence of these variables would warrant a close follow up for these patients in order to decrease post COVID mortality.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.06.23286853",
+    "rel_abs": "ObjectivesOral fluids provide ready detection of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and host responses. This study sought to determine relationships between oral virus, oral anti-SARS-CoV-2-specific antibodies, and symptoms.\n\nMethodsSaliva/throat wash (saliva/TW) were collected from asymptomatic and symptomatic, nasopharyngeal (NP) SARS-CoV-2 RT-qPCR+, subjects (n=47). SARS-CoV-2 RT-qPCR, N-antigen detection by immunoblot and lateral flow assay (LFA) were performed. RT-qPCR targeting viral subgenomic RNA (sgRNA) was sequence confirmed. SARS-CoV-2-anti-S protein RBD LFA assessed IgM and IgG responses. Structural analysis identified host salivary molecules analogous to SARS-CoV-2-N-antigen. Statistical analyses were performed.\n\nResultsAt baseline, LFA-detected N-antigen was immunoblot-confirmed in 82% of TW. However, only 3/17 were saliva/TW qPCR+. Sixty percent of saliva and 83% of TW demonstrated persistent N-antigen at 4 weeks. N-antigen LFA signal in three negative subjects suggested potential cross-detection of 4 structurally analogous salivary RNA binding proteins (alignment 19-29aa, RMSD 1-1.5 Angstroms). At entry, symptomatic subjects demonstrated replication-associated sgRNA junctions, were IgG+ (94%/100% in saliva/TW), and IgM+ (75%/63%). At 4 weeks, SARS-CoV-2 IgG (100%/83%) and IgM (80%/67%) persisted. Oral IgG correlated 100% with NP+PCR status. Cough and fatigue severity (p=0.0008 and 0.016), and presence of nausea, weakness, and composite upper respiratory symptoms (p=0.005, 0.037 and 0.017) were negatively associated with oral IgM. Female oral IgM levels were higher than male (p=0.056).\n\nConclusionImportant to transmission and disease course, oral viral replication and persistence showed clear relationships with select symptoms, early Ig responses, and gender during early infection. N-antigen cross-reactivity may reflect mimicry of structurally analogous host proteins.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Arjun",
-        "author_inst": "AIIMS rishikesh"
+        "author_name": "William T Seaman",
+        "author_inst": "National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD"
       },
       {
-        "author_name": "Basavaraj Jatteppanavar",
-        "author_inst": "AIIMS rishikesh"
+        "author_name": "Olive Keener",
+        "author_inst": "University of North Carolina, Chapel Hill, NC"
       },
       {
-        "author_name": "Prasan Kumar Panda",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "Wenwen Me",
+        "author_inst": "University of North Carolina, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Katie R Mollan",
+        "author_inst": "University of North Carolina, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Corbin D Jones",
+        "author_inst": "University of North Carolina, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Audrey Pettifor",
+        "author_inst": "University of North Carolina, Chapel Hill, NC"
       },
       {
-        "author_name": "Pathik Dhanger",
-        "author_inst": "AIIMS rishikesh"
+        "author_name": "Natalie M Bowman",
+        "author_inst": "University of North Carolina, Chapel Hill, NC"
+      },
+      {
+        "author_name": "- UNC OBSc Working Group",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "Frank Wang",
+        "author_inst": "Biomedomics Inc, Morrisville, NC"
+      },
+      {
+        "author_name": "Jennifer Webster-Cyriaque",
+        "author_inst": "National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD"
       }
     ],
     "version": "1",
@@ -70392,39 +70799,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.03.06.23286832",
-    "rel_title": "Modeling Biases in SARS-CoV-2 infections Prediction using Genome Copies Concentration in Wastewater",
+    "rel_doi": "10.1101/2023.03.05.531213",
+    "rel_title": "The significant yet short-term influence of research covidization on journal citation metrics",
     "rel_date": "2023-03-06",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.06.23286832",
-    "rel_abs": "BackgroundSARS-CoV-2, the virus responsible for the COVID-19 pandemic, can be detected in stool samples and subsequently shed in the sewage system. The field of Wastewater-based epidemiology (WBE) aims to use this valuable source of data for epidemiological surveillance, as it has the potential to identify unreported infections and to anticipate the need for diagnostic tests.\n\nObjectivesThe objectives of this study were to analyze the absolute concentration of genome copies of SARS-CoV-2 shed in Catalonias wastewater during the Omicron peak in January 2022, and to develop a mathematical model capable of using wastewater data to estimate the actual number of infections and the temporal relationship between reported and unreported infections.\n\nMethodsWe collected twenty-four-hour composite 1-liter samples of wastewater from 16 wastewater treatment plants (WWTPs) in Catalonia on a weekly basis. We incorporated this data into a compartmental epidemiological model that distinguishes between reported and unreported infections and uses a convolution process to estimate the genome copies shed in sewage.\n\nResultsThe 16 WWTPs showed an average correlation of 0.88 {+/-} 0.08 (ranging from 0.96 to 0.71) and an average delay of 8.7 {+/-} 5.4 days (ranging from 0 to 20 days). Our model estimates that about 53% of the population in our study had been infected during the period under investigation, compared to the 19% of cases that were detected. This under-reporting was especially high between November and December 2021, with values up to 10. Our model also allowed us to estimate the maximum quantity of genome copies shed in a gram of feces by an infected individual, which ranged from 4.15 x 107 gc/g to 1.33 x 108 gc/g.\n\nDiscussionAlthough wastewater data can be affected by uncertainties and may be subject to fluctuations, it can provide useful insights into the current trend of an epidemic. As a complementary tool, WBE can help account for unreported infections and anticipate the need for diagnostic tests, particularly when testing rates are affected by human behavior-related biases.",
-    "rel_num_authors": 5,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.05.531213",
+    "rel_abs": "COVID-19 has emerged as a significant research hotspot in recent years, leading to a surge in production and citations received by COVID-19 papers. While concerns have been raised about the potential citation boost on journals associated with publishing COVID-19 papers, the extent and mechanisms of such gain remain unclear. This study uses a generalized difference-in-differences approach to examine the impact of publishing COVID-19 papers on journal citations and related metrics in four highly covidized fields. Our results demonstrate that journals starting publishing COVID-19 papers in health sciences fields in 2020 experienced a significant increase in citations compared with other journals. This trend continued in 2021, although to a lesser extent. However, such citation premiums became insignificant for journals starting to publish COVID-19 papers in 2021. In some fields, we also observed that COVID-19 papers increased the citations of non-COVID-19 papers in the same journals, but only for journals starting to publish COVID-19 papers in 2020. Our heterogeneity test indicates that COVID-19 papers published in prestigious journals brought more significant citation premiums to the journals and non-COVID-19 papers in most fields. We finally show that these citation premiums can affect various citation-based journal metrics. Our findings reveal a \"gold rush\" pattern in which early entrants are more likely to establish their citation advantage in research hotspots and caution against using such metrics to evaluate journal quality.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Mattia Mattei",
-        "author_inst": "Departament d'Enginyeria Informatica i Matematiques, Universitat Rovira i Virgili"
-      },
-      {
-        "author_name": "Rosa M. Pinto",
-        "author_inst": "Enteric Virus Laboratory, School of Biology, University of Barcelona"
-      },
-      {
-        "author_name": "Susana Guix",
-        "author_inst": "Enteric Virus Laboratory, School of Biology, University of Barcelona"
-      },
-      {
-        "author_name": "Albert Bosch",
-        "author_inst": "Enteric Virus Laboratory, School of Biology, University of Barcelona"
+        "author_name": "Xiang Zheng",
+        "author_inst": "University of Wisconsin-Madison"
       },
       {
-        "author_name": "Alex Arenas",
-        "author_inst": "Departament d'Enginyeria Informatica i Matematiques, Universitat Rovira i Virgili and Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland"
+        "author_name": "Chaoqun Ni",
+        "author_inst": "University of Wisconsin-Madison"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc",
+    "type": "new results",
+    "category": "scientific communication and education"
   },
   {
     "rel_doi": "10.1101/2023.03.03.23286122",
@@ -72058,43 +72453,79 @@
     "category": "obstetrics and gynecology"
   },
   {
-    "rel_doi": "10.1101/2023.02.26.23286471",
-    "rel_title": "The gray swan: model-based assessment of the risk of sudden failure of hybrid immunity to SARS-CoV-2",
+    "rel_doi": "10.1101/2023.02.27.23286501",
+    "rel_title": "Combining models to generate a consensus effective reproduction number R for the COVID-19 epidemic status in England",
     "rel_date": "2023-03-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.26.23286471",
-    "rel_abs": "In the fourth year of the COVID-19 pandemic, public health authorities worldwide have adopted a strategy of learning to live with SARS-CoV-2. This has involved the removal of measures for limiting viral spread, resulting in a large burden of recurrent SARS-CoV-2 infections. Crucial for managing this burden is the concept of the so-called wall of hybrid immunity, through repeated reinfections and vaccine boosters, to reduce the risk of severe disease and death. Protection against both infection and severe disease is provided by the induction of neutralizing antibodies (nAbs) against SARS-CoV-2. However, pharmacokinetic (PK) waning and rapid viral evolution both degrade nAb binding titers. The recent emergence of variants with strongly immune evasive potential against both the vaccinal and natural immune responses raises the question of whether the wall of population-level immunity can be maintained in the face of large jumps in nAb binding potency. Here we use an agent-based simulation to address this question. Our findings suggest large jumps in viral evolution may cause failure of population immunity resulting in sudden increases in mortality. As a rise in mortality will only become apparent in the weeks following a wave of disease, reactive public health strategies will not be able to provide meaningful risk mitigation. Learning to live with the virus could thus lead to large death tolls with very little warning. Our work points to the importance of proactive management strategies for the ongoing pandemic, and to the need for multifactorial approaches to COVID-19 disease control.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.27.23286501",
+    "rel_abs": "The effective reproduction number R was widely accepted as a key indicator during the early stages of the COVID-19 pandemic. In the UK, the R value published on the UK Government Dashboard has been generated as a combined value from an ensemble of fourteen epidemiological models via a collaborative initiative between academia and government. In this paper we outline this collaborative modelling approach and illustrate how, by using an established combination method, a combined R estimate can be generated from an ensemble of epidemiological models. We show that this R is robust to different model weighting methods and ensemble size and that using heterogeneous data sources for validation increases its robustness and reduces the biases and limitations associated with a single source of data. We discuss how R can be generated from different data sources and is therefore a good summary indicator of the current dynamics in an epidemic.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Madison Stoddard",
-        "author_inst": "Fractal Therapeutics"
+        "author_name": "Josie Park",
+        "author_inst": "UK Health Security Agency"
       },
       {
-        "author_name": "Lin Yuan",
-        "author_inst": "Fractal Therapeutics"
+        "author_name": "Luke Bevan",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Sharanya Sarkar",
-        "author_inst": "Dartmouth College"
+        "author_name": "Alberto Sanchez-Marroquin",
+        "author_inst": "UK Health Security Agency"
       },
       {
-        "author_name": "Debra Van Egeren",
-        "author_inst": "Stanford University School of Medicine"
+        "author_name": "Gabriel Danelian",
+        "author_inst": "UK Health Security Agency"
       },
       {
-        "author_name": "Laura White",
-        "author_inst": "Boston University"
+        "author_name": "Thomas Bayley",
+        "author_inst": "UK Health Security Agency"
       },
       {
-        "author_name": "Arijit Chakravarty",
-        "author_inst": "Fractal Therapeutics"
+        "author_name": "Harrison Manley",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "Veronica Bowman",
+        "author_inst": "Defence Science and Technology Laboratory"
+      },
+      {
+        "author_name": "Thomas Maishman",
+        "author_inst": "Defence Science and Technology Laboratory"
+      },
+      {
+        "author_name": "Thomas Finnie",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "Andre Charlett",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "- Nowcasts Models Contribution Group",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "Nicholas A Watkins",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "Johanna Hutchinson",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "Steven Riley",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "Jasmina Panovska-Griffiths",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.02.27.23286454",
@@ -73712,103 +74143,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.02.19.23286159",
-    "rel_title": "Durable reprogramming of neutralising antibody responses following breakthrough Omicron infection",
+    "rel_doi": "10.1101/2023.02.23.23286390",
+    "rel_title": "Was access and quality of healthcare affected during COVID-19 pandemic? A qualitative enquiry into healthcare access for non-communicable diseases in Central India",
     "rel_date": "2023-02-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.19.23286159",
-    "rel_abs": "SARS-CoV-2 breakthrough infection of vaccinated individuals is increasingly common with the circulation of highly immune evasive and transmissible Omicron variants. Here, we report the dynamics and durability of recalled spike-specific humoral immunity following BA.1 or BA.2 breakthrough infection, with longitudinal sampling up to 8 months post-infection. Both BA.1 and BA.2 infection robustly boosted neutralisation activity against the infecting strain while expanding breadth against other Omicron strains. Cross-reactive memory B cells against both ancestral and Omicron spike were predominantly expanded by infection, with limited recruitment of de novo Omicron-specific B cells or antibodies. Modelling of neutralisation titres predicts that protection from symptomatic reinfection against antigenically similar strains will be remarkably durable, but is undermined by novel emerging strains with further neutralisation escape.\n\nOne sentence summaryOmicron breakthrough infection elicits durable neutralising activity by recalling cross-reactive vaccine-elicited memory B cells.",
-    "rel_num_authors": 21,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.23.23286390",
+    "rel_abs": "ObjectiveCOVID-19 pandemic has had significant impacts on healthcare systems across the world. However, its impact on healthcare systems in Low- and Middle-Income Countries (LMICs) has been especially devastating, resulting in restricted access to healthcare. The present study was conducted to assess healthcare access for non-communicable diseases (NCDs) in Central India.\n\nDesignInductive and deductive thematic analysis of in-depth semi-structured interviews.\n\nSettingStudy was conducted in communities of two urban and rural districts of central India.\n\nParticipantsInterviewed participants included PLNCDs, their caregivers, community dwellers, CHWs such as, Accredited Social Health Activists (ASHAs) and Anganwadi Workers (AWWs), Medical Officers, and Community Leaders. Recruitment of the participants was done via purposive and convenience sampling.\n\nResultA total of fifty Key Informant Interviews were (KIIs) conducted. All participants reported facing considerable difficulties while trying to access care from both public as well as private healthcare facilities. Absence of staff, equipment and medicines, restricted commute, misconceptions regarding the spread of COVID-19, and the stigma attached to COVID-19 infection acted as major barriers to accessing care, while door-to-door visits by community health workers, community support, and presence of privately owned healthcare facilities in the vicinity acted as facilitators.\n\nConclusionIn our study, we found that continued functioning of primary healthcare centres, ensuring uninterrupted supply of medicine and effective dissemination of information regarding COVID-19 could have acted to ease access to healthcare. Going ahead, capacity building to offset the impact of future emergencies and pandemics should be a crucial consideration while developing resilient healthcare systems.\n\nStrengths and limitations of this studyO_LIOur study is the first study to explore the barriers faced by PLNCDs of low socio-economic status during the pandemic.\nC_LIO_LIWe explored the perspectives of both patients and healthcare workers before triangulating the data findings.\nC_LIO_LIThe study was conducted in the PLNCDs of lower socio-economic group and hence the perspectives and experiences of other socio-economic groups are yet to be explored.\nC_LI",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Wen Shi Lee",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Hyon-Xhi Tan",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Arnold Reynaldi",
-        "author_inst": "Kirby Institute, The University of New South Wales"
-      },
-      {
-        "author_name": "Robyn Esterbauer",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Marios Koutsakos",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Julie Nguyen",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Thakshila Amarasena",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Helen E Kent",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
-      },
-      {
-        "author_name": "Anupriya Aggarwal",
-        "author_inst": "Kirby Institute, The University of New South Wales"
-      },
-      {
-        "author_name": "Stuart G Turville",
-        "author_inst": "Kirby Institute, The University of New South Wales"
-      },
-      {
-        "author_name": "George Taiaroa",
-        "author_inst": "Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital at The Peter Doherty Institute for Infection and Immunity"
-      },
-      {
-        "author_name": "Paul Kinsella",
-        "author_inst": "Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital at The Peter Doherty Institute for Infection and Immunity"
-      },
-      {
-        "author_name": "Kwee Chin Liew",
-        "author_inst": "Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital at The Peter Doherty Institute for Infection and Immunity"
-      },
-      {
-        "author_name": "Thomas Tran",
-        "author_inst": "Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital at The Peter Doherty Institute for Infection and Immunity"
-      },
-      {
-        "author_name": "Deborah A Williamson",
-        "author_inst": "Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital at The Peter Doherty Institute for Infection and Immunity"
-      },
-      {
-        "author_name": "Deborah Cromer",
-        "author_inst": "Kirby Institute, The University of New South Wales"
-      },
-      {
-        "author_name": "Miles P Davenport",
-        "author_inst": "Kirby Institute, The University of New South Wales"
-      },
-      {
-        "author_name": "Stephen J Kent",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Raunaq Singh Nagi",
+        "author_inst": "All India Institute of Medical Sciences, Bhopal"
       },
       {
-        "author_name": "Jennifer A Juno",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Anirban Chatterjee",
+        "author_inst": "All India Institute of Medical Sciences-Bhopal"
       },
       {
-        "author_name": "David S Khoury",
-        "author_inst": "Kirby Institute, The University of New South Wales"
+        "author_name": "Kritika Singhal",
+        "author_inst": "All India Institute of Medical Sciences-Bhopal"
       },
       {
-        "author_name": "Adam K Wheatley",
-        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
+        "author_name": "Arun Mahadeo Kokane",
+        "author_inst": "All India Institute of Medical Sciences-Bhopal"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "primary care research"
   },
   {
     "rel_doi": "10.1101/2023.02.21.23286239",
@@ -75558,49 +75921,77 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2023.02.23.23286342",
-    "rel_title": "Multilevel determinants of Covid-19 vaccine hesitancy and undervaccination among marginalized populations in the United States: A scoping review",
+    "rel_doi": "10.1101/2023.02.17.23286049",
+    "rel_title": "Evidence of Leaky Protection Following COVID-19 Vaccination and SARS-CoV-2 Infection in a US Correctional Facility Population",
     "rel_date": "2023-02-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.23.23286342",
-    "rel_abs": "BackgroundAmid persistent disparities in Covid-19 vaccination, we conducted a scoping review to identify multilevel determinants of Covid-19 vaccine hesitancy (VH) and undervaccination among marginalized populations in the U.S.\n\nMethodsWe utilized the scoping review methodology developed by the Joanna Briggs Institute and report all findings according to PRISMA-ScR guidelines. We developed a search string and explored 7 databases to identify peer-reviewed articles published from January 1, 2020-October 31, 2021, the initial period of U.S. Covid-19 vaccine avails.comability. We combine frequency analysis and narrative synthesis to describe factors influencing Covid-19 vaccination among marginalized populations.\n\nResultsThe search captured 2,496 non-duplicated records, which were scoped to 50 peer-reviewed articles: 11 (22%) focused on African American/Black people, 9 (18%) people with disabilities, 4 (8%) justice-involved people, and 2 (4%) each on Latinx, people living with HIV/AIDS, people who use drugs, and LGBTQ+ people. Forty-four articles identified structural factors, 36 social/community, 27 individual, and 40 vaccine-specific factors. Structural factors comprised medical mistrust (of healthcare systems, government public health) and access barriers due to unemployment, unstable housing, lack of transportation, no/low paid sick days, low internet/digital technology access, and lack of culturally and linguistically appropriate information. Social/community factors including trust in a personal healthcare provider (HCP), altruism, family influence, and social proofing mitigated VH. At the individual level, low perceived Covid-19 threat and negative vaccine attitudes were associated with VH.\n\nDiscussionThis review indicates the importance of identifying and disaggregating structural factors underlying Covid-19 undervaccination among marginalized populations, both cross-cutting and population-specific--including multiple logistical and economic barriers in access, and systemic mistrust of healthcare systems and government public health--from individual and social/community factors, including trust in personal HCPs/clinics as reliable sources of vaccine information, altruistic motivations, and family influence, to effectively address individual decisional conflict underlying VH as well as broader determinants of undervaccination.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.17.23286049",
+    "rel_abs": "Whether SARS-CoV-2 infection and COVID-19 vaccines confer exposure-dependent (\"leaky\") protection against infection remains unknown. We examined the effect of prior infection, vaccination, and hybrid immunity on infection risk among residents of Connecticut correctional facilities during periods of predominant Omicron and Delta transmission. Residents with cell, cellblock, and no documented exposure to SARS-CoV-2 infected residents were matched by facility and date. During the Omicron period, prior infection, vaccination, and hybrid immunity reduced the infection risk of residents without a documented exposure (HR: 0.36 [0.25-0.54]; 0.57 [0.42-0.78]; 0.24 [0.15-0.39]; respectively) and with cellblock exposures (0.61 [0.49-0.75]; 0.69 [0.58-0.83]; 0.41 [0.31-0.55]; respectively) but not with cell exposures (0.89 [0.58-1.35]; 0.96 [0.64-1.46]; 0.80 [0.46-1.39]; respectively). Associations were similar during the Delta period and when analyses were restricted to tested residents. Although associations may not have been thoroughly adjusted due to dataset limitations, the findings suggest that prior infection and vaccination may be leaky, highlighting the potential benefits of pairing vaccination with non-pharmaceutical interventions in crowded settings.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Peter  A. Newman",
-        "author_inst": "University of Toronto"
+        "author_name": "Margaret L Lind",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Thabani Nyoni",
-        "author_inst": "University of Toronto"
+        "author_name": "Murilo Dorion",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Kate Allan",
-        "author_inst": "University of Toronto"
+        "author_name": "Amy J Houde",
+        "author_inst": "Connecticut Department of Correction"
       },
       {
-        "author_name": "Sophia Fantus",
-        "author_inst": "The University of Texas at Arlington"
+        "author_name": "Mary Lansing",
+        "author_inst": "Connecticut Department of Correction"
       },
       {
-        "author_name": "Duy Dinh",
-        "author_inst": "Queen's University"
+        "author_name": "Sarah Lapidus",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Suchon Tepjan",
-        "author_inst": "VOICES-Thailand Foundation"
+        "author_name": "Russell Thomas",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Luke Reid",
-        "author_inst": "University of Toronto"
+        "author_name": "Inci Yildirim",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Adrian Guta",
-        "author_inst": "University of Windsor"
+        "author_name": "Saad B Omer",
+        "author_inst": "Yale University"
+      },
+      {
+        "author_name": "Wade L Schulz",
+        "author_inst": "Yale University"
+      },
+      {
+        "author_name": "Jason R Andrews",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Matt DT Hitchings",
+        "author_inst": "University of Florida"
+      },
+      {
+        "author_name": "Byron S Kennedy",
+        "author_inst": "Connecticut Department of Correction"
+      },
+      {
+        "author_name": "Robert P Richeson",
+        "author_inst": "Connecticut Department of Correction"
+      },
+      {
+        "author_name": "Derek AT Cummings",
+        "author_inst": "University of Florida"
+      },
+      {
+        "author_name": "Albert I Ko",
+        "author_inst": "Yale University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -77308,71 +77699,39 @@
     "category": "hiv aids"
   },
   {
-    "rel_doi": "10.1101/2023.02.18.23286136",
-    "rel_title": "Comparative Effectiveness of BNT162b2 and NVX-CoV2373 Vaccines in Korean Adults",
+    "rel_doi": "10.1101/2023.02.17.528968",
+    "rel_title": "Speedy-PASEF: Analytical flow rate chromatography and trapped ion mobility for deep high-throughput proteomics",
     "rel_date": "2023-02-19",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.18.23286136",
-    "rel_abs": "BackgroundVarious types of vaccines against SARS-CoV-2 have reduced the burden of coronavirus diseases 2019 (COVID-19) across the world. We conducted an observational study to evaluate the effectiveness of NVX-CoV2373 and BNT162b2 in providing protection in Korean adults.\n\nMethodsThis study was a retrospective matched cohort study to emulate a target trial of three doses of NVX-CoV2373 (N-N-N) versus three doses of BNT162b2 (B-B-B) vaccines in presumed immune-naive adults. We used data from the Korea COVID-19 Vaccine Effectiveness (K-COVE) cohort, combining all COVID-19 laboratory-confirmed cases and all COVID-19 immunization registry, between February and November 2022. We calculated 40-week risk differences and risk ratios between the two vaccines.\n\nResultsA total of 3,019 recipients of NVX-CoV2373 vaccine and 3,027 recipients of BNT162b2 vaccine were eligible for the study. The 40-week risk ratios for recipients of the NVX-CoV2373 vaccine as compared with recipients of the BNT162b2 vaccine were 1.169 (95% CI, 1.015 to 1.347) for laboratory-confirmed SARS-CoV-2 infection, and 0.504 (95% CI, 0.126 to 2.014) for severe SARS-CoV-2 infection. Estimated risk of severe infection was 0.001 events per 1000 persons (95% CI, 0 to 0.003) for the NVX-CoV2373 vaccine and 0.002 events per 1000 persons (95% CI, 0.001 to 0.006) for BNT162b2 vaccine.\n\nConclusionThis study identifies reduced risk of SARS-CoV-2 infection and severe infection after receipt of three doses of either NVX-CoV2373 or BNT162b2 vaccines in Korean adults. Direct, vaccine-conferred protection may be of importance among high risk persons to mitigate from serious clinical outcome from COVID-19.",
-    "rel_num_authors": 13,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.17.528968",
+    "rel_abs": "Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs and facilitate new approaches in systems biology and biomedical research. Here we propose Speedy-PASEF, a combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition and data analysis with the DIA-NN software suite, for conducting fast, high-quality proteomic experiments that require only moderate sample amounts. For instance, using a 500-l/min flow rate and a 3-minute chromatographic gradient, Speedy-PASEF quantified 5,211 proteins from 2 g of a mammalian cell-line standard at high quantitative accuracy and precision. We further used Speedy-PASEF to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-minute chromatographic gradient and alternating column regeneration on a dual pump system, for processing 398 samples per day. Speedy-PASEF delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates. Speedy-PASEF thus facilitates acquisition of high-quality proteomes in large numbers.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Seon Kyeong Park",
-        "author_inst": "Korea Disease Control and Prevention Agency"
-      },
-      {
-        "author_name": "Young June Choe",
-        "author_inst": "Korea University Anam Hospital"
-      },
-      {
-        "author_name": "Seung Ah Choe",
-        "author_inst": "Korea University"
-      },
-      {
-        "author_name": "Benjamin J Cowling",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Ji Hae Hwang",
-        "author_inst": "Korea Disease Control and Prevention Agency"
-      },
-      {
-        "author_name": "Ju Hee Lee",
-        "author_inst": "Korea Disease Control and Prevention Agency"
-      },
-      {
-        "author_name": "Kil Hun Lee",
-        "author_inst": "Korea Disease Control and Prevention Agency"
-      },
-      {
-        "author_name": "Seonju Yi",
-        "author_inst": "Korea Disease Control and Prevention Agency"
+        "author_name": "Lukasz Szyrwiel",
+        "author_inst": "Department of Biochemistry, Charite, Universitaetsmedizin Berlin, Berlin, Germany"
       },
       {
-        "author_name": "Sang Won Lee",
-        "author_inst": "Korea Disease Control and Prevention Agency"
+        "author_name": "Christoph Gille",
+        "author_inst": "Department of Biochemistry, Charite, Universitaetsmedizin Berlin, Berlin, Germany"
       },
       {
-        "author_name": "Geun Yong Kwon",
-        "author_inst": "Korea Disease Control and Prevention Agency"
-      },
-      {
-        "author_name": "Eun Jung Jang",
-        "author_inst": "Korea Disease Control and Prevention Agency"
+        "author_name": "Michael Muelleder",
+        "author_inst": "Core Facility High-Throughput Mass Spectrometry, Charite Universitaetsmedizin Berlin, Berlin, Germany"
       },
       {
-        "author_name": "Ryu Kyung Kim",
-        "author_inst": "Korea Disease Control and Prevention Agency"
+        "author_name": "Vadim Demichev",
+        "author_inst": "Department of Biochemistry, Charite Universitaetsmedizin Berlin, Berlin, Germany"
       },
       {
-        "author_name": "Young Joon Park",
-        "author_inst": "Korea Disease Control and Prevention Agency"
+        "author_name": "Markus Ralser",
+        "author_inst": "Department of Biochemistry, Charite Universitaetsmedizin Berlin, Berlin, Germany"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "type": "new results",
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2023.02.18.23286126",
@@ -79022,53 +79381,229 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2023.02.16.23286008",
-    "rel_title": "COVID-19 Vaccine Acceptance in Nigeria: A Rapid Systematic Review and Meta-Analysis",
+    "rel_doi": "10.1101/2023.02.16.23285816",
+    "rel_title": "Estimates of protection against SARS-CoV-2 infection and severe COVID-19 in Germany before the 2022/2023 winter season - the IMMUNEBRIDGE project",
     "rel_date": "2023-02-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.16.23286008",
-    "rel_abs": "Widespread COVID-19 vaccination is essential to maintaining pandemic control. However, low- and lower-middle-income countries (LMICs) continue to face challenges to care due to unequal access and vaccine fear despite the introduction of safe and effective immunizations. This study aimed to collect information on Nigerias COVID-19 vaccine uptake rates and determinants. Science Direct, PubMed, Google Scholar, African Journal Online, Springer, and Hinari were all systematically searched through and completed in May 2022. Quality assessments of the listed studies were performed using the eight-item Joanna Briggs Institute Critical Appraisal tools for cross-sectional studies. In addition, we undertook a meta-analysis to calculate pooled acceptance rates with 95% confidence intervals (CI). Forty-two studies in total satisfied the inclusion criteria and were reviewed. A total of 24,533 respondents were studied. The total sample size of states in the Northern, Western and Southern parts of Nigeria are 3,206, 4,527 and 5,059, respectively, while 11,741 is the cumulative sample size of all the Nigeria-wide studies. The total COVID-19 vaccination acceptance rate among all the study groups was 52.4% (95% CI: 46.9-57.9%, I2 = 100%), while the total estimated COVID-19 vaccination hesitancy rates was 47.81% (95% CI: 42.2 - 53.4% I2 = 100%). In Nigeria-regions sub-group analyses, the Western region (58.90%, 95% CI: 47.12-70.27%) and Northern region (54.9%, 95% CI: 40.11%-69.4%) showed the highest rates of vaccine acceptance and vaccine hesitancy respectively. The COVID-19 vaccine acceptance rate was highest in 2020, with a pooled rate of 59.56% (46.34, 57.32%, I2 = 98.7%). The acceptance rate in 2021 was only 48.48 (40.78%, 56.22%), while for the studies in 2022, it increased to 52.04% (95% CI: 35.7%, 68.15 %). The sensitization of local authorities and the dissemination of more detailed information about the COVID-19 vaccine and its safety, could significantly increase the countrys vaccination rate.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.16.23285816",
+    "rel_abs": "Despite the need to generate valid and reliable estimates of protection against SARS-CoV-2 infection and severe course of COVID-19 for the German population in summer 2022, there was a lack of systematically collected population-based data allowing for the assessment of the protection level in real-time.\n\nIn the IMMUNEBRIDGE project, we harmonised data and biosamples for nine population-/hospital-based studies (total number of participants n=33,637) to provide estimates for protection levels against SARS-CoV-2 infection and severe COVID-19 between June and November 2022. Based on evidence synthesis, we formed a combined endpoint of protection levels based on the number of self-reported infections/vaccinations in combination with nucleocapsid/spike antibody responses (\"confirmed exposures\"). Four confirmed exposures represented the highest protection level, and no exposure represented the lowest.\n\nMost participants were seropositive against the spike antigen; 37% of the participants [&ge;]79 years had less than four confirmed exposures (highest level of protection) and 5% less than three. In the subgroup of participants with comorbidities, 46-56% had less than four confirmed exposures. We found major heterogeneity across federal states, with 4%-28% of participants having less than three confirmed exposures.\n\nUsing serological analyses, literature synthesis and infection dynamics during the survey period, we observed moderate to high levels of protection against severe COVID-19, whereas the protection against SARS-CoV-2 infection was low across all age groups. We found relevant protection gaps in the oldest age group and amongst individuals with comorbidities, indicating a need for additional protective measures in these groups.",
+    "rel_num_authors": 53,
     "rel_authors": [
       {
-        "author_name": "Victory Chizaram Nnaemeka",
-        "author_inst": "University of Nigeria, Nsukka."
+        "author_name": "Berit Lange",
+        "author_inst": "Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany; German Center for Infection Research (DZIF), TI BBD, Braunschw"
       },
       {
-        "author_name": "Nnenna Audrey Okafor",
-        "author_inst": "University of Nigeria, Nsukka"
+        "author_name": "Veronika K Jaeger",
+        "author_inst": "Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany"
       },
       {
-        "author_name": "Oluwatosin Qawiyy Orababa",
-        "author_inst": "University of Warwick"
+        "author_name": "Manuela Harries",
+        "author_inst": "Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany"
       },
       {
-        "author_name": "Ruth Anikwe",
-        "author_inst": "University of Nigeria, Nsukka"
+        "author_name": "Viktoria Ruecker",
+        "author_inst": "Institute of Clinical Epidemiology and Biometry, University Wuerzburg, Wuerzburg, Germany"
       },
       {
-        "author_name": "Reuben Ogba Onwe",
-        "author_inst": "University of Nigeria, Nsukka"
+        "author_name": "Hendrik Streeck",
+        "author_inst": "Institute of Virology, Medical Faculty, University of Bonn, Bonn, Germany; German Center for Infection Research (DZIF), partner site Bonn-Cologne, Braunschweig,"
+      },
+      {
+        "author_name": "Sabine Blaschke",
+        "author_inst": "Emergency Department, University Medical Center Goettingen, Goettingen, Germany"
+      },
+      {
+        "author_name": "Astrid Petersmann",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Oldenburg, Oldenburg, Germany; Institute of Clinical Chemistry and Laboratory Medic"
+      },
+      {
+        "author_name": "Nicole Toepfner",
+        "author_inst": "Department of Pediatrics, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden, Dresden, Germany"
+      },
+      {
+        "author_name": "Matthias Nauck",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany; DZHK (German Centre for Cardiovascular Research), "
+      },
+      {
+        "author_name": "Max J Hassenstein",
+        "author_inst": "Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany"
+      },
+      {
+        "author_name": "Marein Dreier",
+        "author_inst": "Institute for Epidemiology, Social Medicine and Health Systems Research, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Isabell von Holt",
+        "author_inst": "Institute for Epidemiology, Social Medicine and Health Systems Research, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Axel Budde",
+        "author_inst": "Institute of Virology, Medical Faculty, University of Bonn, Bonn, Germany; German Center for Infection Research (DZIF), partner site Bonn-Cologne, Braunschweig,"
+      },
+      {
+        "author_name": "Antonia Bartz",
+        "author_inst": "Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany"
+      },
+      {
+        "author_name": "Julia Ortmann",
+        "author_inst": "Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany"
+      },
+      {
+        "author_name": "Marc-Andre Kurosinski",
+        "author_inst": "Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany"
+      },
+      {
+        "author_name": "Reinhard Berner",
+        "author_inst": "Department of Pediatrics, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden, Dresden, Germany"
+      },
+      {
+        "author_name": "Max Borsche",
+        "author_inst": "Institute of Neurogenetics, University of Luebeck, Luebeck, Germany"
+      },
+      {
+        "author_name": "Gunnar Brandhorst",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Oldenburg, Oldenburg, Germany"
+      },
+      {
+        "author_name": "Melanie Brinkmann",
+        "author_inst": "Institute for Epidemiology, Social Medicine and Health Systems Research, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Kathrin Budde",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany"
+      },
+      {
+        "author_name": "Marek Deckena",
+        "author_inst": "Labor Krone, Bad Salzuflen, Germany"
+      },
+      {
+        "author_name": "Geraldine Engels",
+        "author_inst": "University Hospital Wuerzburg, Department of Pediatrics, Pediatric Infectiology, Wuerzburg, Germany"
       },
       {
-        "author_name": "Nneka Patricia Uzochukwu",
-        "author_inst": "University of Nigeria, Nsukka."
+        "author_name": "Marc Fenzlaff",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany"
       },
       {
-        "author_name": "Thomas Sambo Tsiterimam",
-        "author_inst": "Department of Obstetrics and Gynecology, University of Abuja Teaching Hospital"
+        "author_name": "Christoph Haertel",
+        "author_inst": "University Hospital Wuerzburg, Department of Pediatrics, Pediatric Infectiology, Wuerzburg, Germany"
+      },
+      {
+        "author_name": "Olga Hovardovska",
+        "author_inst": "Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany"
+      },
+      {
+        "author_name": "Alexander Katalinic",
+        "author_inst": "Institute of Social Medicine and Epidemiology, University of Luebeck, Luebeck, Germany"
       },
       {
-        "author_name": "Nkiru Nenye Nwokoye",
-        "author_inst": "KNCV TB Foundation, Abuja FCT"
+        "author_name": "Katja Kehl",
+        "author_inst": "Institute of Virology, Medical Faculty, University of Bonn, Bonn, Germany; German Center for Infection Research (DZIF), partner site Bonn-Cologne, Braunschweig,"
       },
       {
-        "author_name": "Anthony Chibuogwu Ike",
-        "author_inst": "University of Nigeria, Nsukka."
+        "author_name": "Mirjam Kohls",
+        "author_inst": "Institute of Clinical Epidemiology and Biometry, University Wuerzburg; Clinical Trial Center, University Hospital Wuerzburg; Institute for Medical Data Science,"
+      },
+      {
+        "author_name": "Stefan Krueger",
+        "author_inst": "dimap, das Institut fuer Markt- und Politikforschung GmbH, Germany"
+      },
+      {
+        "author_name": "Wolfgang Lieb",
+        "author_inst": "Institute of Epidemiology, Christian-Albrechts-University of Kiel, Kiel, Germany"
+      },
+      {
+        "author_name": "Kristin M Meyer-Schlinkmann",
+        "author_inst": "Labor Krone, Bad Salzuflen, Germany"
+      },
+      {
+        "author_name": "Tobias Pischon",
+        "author_inst": "Molecular Epidemiology Research Group, Max Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin; Biobank Technology Platform, Max Delbru"
+      },
+      {
+        "author_name": "Daniel Rosenkranz",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Oldenburg, Oldenburg, Germany"
+      },
+      {
+        "author_name": "Nicole Ruebsamen",
+        "author_inst": "Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany"
+      },
+      {
+        "author_name": "Jan Rupp",
+        "author_inst": "Department of Infectious Diseases and Microbiology, University Hospital Schleswig-Holstein, German Center for Infection Research (DZIF), Partner Site Hamburg-Lu"
+      },
+      {
+        "author_name": "Christian Schaefer",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany"
+      },
+      {
+        "author_name": "Mario Schattschneider",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany"
+      },
+      {
+        "author_name": "Anne Schlegtendal",
+        "author_inst": "University Children's Hospital, Ruhr University Bochum, Bochum, Germany"
+      },
+      {
+        "author_name": "Simon Schlinkert",
+        "author_inst": "dimap, das Institut fuer Markt- und Politikforschung GmbH, Germany"
+      },
+      {
+        "author_name": "Lena Schmidbauer",
+        "author_inst": "Institute of Clinical Epidemiology and Biometry, University Wuerzburg, Wuerzburg, Germany"
+      },
+      {
+        "author_name": "Kai Schulze-Wundling",
+        "author_inst": "Institute of Virology, Medical Faculty, University of Bonn, Bonn, Germany; German Center for Infection Research (DZIF), partner site Bonn-Cologne, Braunschweig,"
+      },
+      {
+        "author_name": "Stefan Stoerk",
+        "author_inst": "Department of Clinical Research & Epidemiology, Comprehensive Heart Failure Center (CHFC), and Department of Internal Medicine I, University Hospital Wuerzburg,"
+      },
+      {
+        "author_name": "Carsten Tiemann",
+        "author_inst": "Labor Krone, Bad Salzuflen, Germany"
+      },
+      {
+        "author_name": "Henry Voelzke",
+        "author_inst": "Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany"
+      },
+      {
+        "author_name": "Theresa Winter",
+        "author_inst": "Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany"
+      },
+      {
+        "author_name": "Christine Klein",
+        "author_inst": "Institute of Neurogenetics, University of Luebeck, Luebeck, Germany"
+      },
+      {
+        "author_name": "Johannes Liese",
+        "author_inst": "University Hospital Wuerzburg, Department of Pediatrics, Pediatric Infectiology, Wuerzburg, Germany"
+      },
+      {
+        "author_name": "Folke Brinkmann",
+        "author_inst": "University Children's Hospital, Ruhr University Bochum, Bochum, Germany"
+      },
+      {
+        "author_name": "Patrick F Ottensmeyer",
+        "author_inst": "Institute of Virology, Medical Faculty, University of Bonn, Bonn, Germany; German Center for Infection Research (DZIF), partner site Bonn-Cologne, Braunschweig,"
+      },
+      {
+        "author_name": "Jens-Peter Reese",
+        "author_inst": "Institute of Clinical Epidemiology and Biometry, University Wuerzburg, Wuerzburg, Germany"
+      },
+      {
+        "author_name": "Peter Heuschmann",
+        "author_inst": "Institute of Clinical Epidemiology and Biometry, University Wuerzburg; Clinical Trial Center, University Hospital Wuerzburg; Institute for Medical Data Science,"
+      },
+      {
+        "author_name": "Andre Karch",
+        "author_inst": "Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -80812,71 +81347,87 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2023.02.10.23285603",
-    "rel_title": "Relative effectiveness of BNT162b2, mRNA-1273, and Ad26.COV2.S vaccines and homologous boosting in preventing COVID-19 in adults in the US",
+    "rel_doi": "10.1101/2023.02.10.23285516",
+    "rel_title": "Epidemiological drivers of transmissibility and severity of SARS-CoV-2 in England",
     "rel_date": "2023-02-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.10.23285603",
-    "rel_abs": "BackgroundFew head-to-head comparisons have been performed on the real-world effectiveness of COVID-19 booster vaccines. We evaluated the relative effectiveness (rVE) of a primary series of mRNA-1273 versus BNT162b2 and Ad26.COV2.S and a homologous mRNA booster against medically-attended, outpatient, and hospitalized COVID-19.\n\nMethodsA dataset linking primary care electronic medical records with medical claims data was used for this retrospective cohort study of US patients [&ge;]18 years vaccinated with a primary series between February and October 2021 (Part 1) and a homologous mRNA booster between October 2021 and January 2022 (Part 2). Adjusted hazard ratios (HR) were derived from 1:1 matching adjusted across potential covariates. rVE was (1-HRadjusted) x 100. Additional analysis was performed across regions and age groups.\n\nResultsFollowing adjustment, Part 1 rVE for mRNA-1273 versus BNT162b2 was 23% (95% CI: 22%-25%), 23% (22%-25%), and 19% (14%-24%) whilst the rVE for mRNA-1273 versus Ad26.COV2.S was 50% (48%-51%), 50% (48%-52%), and 57% (53%-61%) against any medically-attended, outpatient, and hospitalized COVID-19, respectively. The adjusted rVE in Part 2 for mRNA-1273 versus BNT162b2 was 14% (10%-18%), 13% (8%- 17%), and 19% (1%-34%) against any medically-attended, outpatient, and hospitalized COVID-19, respectively. rVE against medically-attended COVID-19 was higher in adults [&ge;]65 years (35%; 24%-47%) than those 18-64 years (13%; 9%-17%) after the booster.\n\nConclusionsIn this study, mRNA-1273 was more effective than BNT162b2 or Ad26.COV2.S following primary series during a Delta-dominant period, and than BNT162b2 as a booster during an Omicron-dominant period.\n\nKey pointsmRNA-1273 was associated with a lower risk than BNT162b2 or Ad26.COV2.S of any medically-attended, outpatient, or hospitalized COVID-19 after primary series and of any medically-attended, outpatient, or hospitalized COVID-19 vs BNT162b2 after a homologous mRNA booster",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.10.23285516",
+    "rel_abs": "As the SARS-CoV-2 pandemic progressed, distinct variants emerged and dominated in England. These variants, Wildtype, Alpha, Delta, and Omicron were characterized by variations in transmissibility and severity. We used a robust mathematical model and Bayesian inference framework to analyse epidemiological surveillance data from England. We quantified the impact of non-pharmaceutical interventions (NPIs), therapeutics, and vaccination on virus transmission and severity. Each successive variant had a higher intrinsic transmissibility. Omicron (BA.1) had the highest basic reproduction number at 8.3 (95% credible interval (CrI) 7.7-8.8). Varying levels of NPIs were crucial in controlling virus transmission until population immunity accumulated. Immune escape properties of Omicron decreased effective levels of immunity in the population by a third. Furthermore, in contrast to previous studies, we found Alpha had the highest basic infection fatality ratio (2.9%, 95% CrI 2.7-3.2), followed by Delta (2.2%, 95% CrI 2.0-2.4), Wildtype (1.2%, 95% CrI 1.1-1.2), and Omicron (0.7%, 95% CrI 0.6-0.8). Our findings highlight the importance of continued surveillance. Long-term strategies for monitoring and maintaining effective immunity against SARS-CoV-2 are critical to inform the role of NPIs to effectively manage future variants with potentially higher intrinsic transmissibility and severe outcomes.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Van Hung Nguyen",
-        "author_inst": "VHN vonsulting"
+        "author_name": "Pablo N Perez-Guzman",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Catherine Boileau",
-        "author_inst": "VHN Consulting Inc."
+        "author_name": "Edward S Knock",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Alina Bogdanov",
-        "author_inst": "Veradigm"
+        "author_name": "Natsuko Imai",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Meg Sredl",
-        "author_inst": "Veradigm"
+        "author_name": "Thomas Rawson",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Mac Bonafede",
-        "author_inst": "Veradigm"
+        "author_name": "Yasin A Elmaci",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Thierry Ducruet",
-        "author_inst": "VHN Consulting Inc."
+        "author_name": "Joana Alcada",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Scott Chavers",
-        "author_inst": "Moderna, Inc."
+        "author_name": "Lilith K Whittles",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Andrew Rosen",
-        "author_inst": "Moderna, Inc."
+        "author_name": "Divya Thekke Kanapram",
+        "author_inst": "University of Cambridge"
       },
       {
-        "author_name": "David Martin",
-        "author_inst": "Moderna, Inc."
+        "author_name": "Raphael Sonabend",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Philip Buck",
-        "author_inst": "Moderna, Inc."
+        "author_name": "Katy A M Gaythorpe",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Diana Esposito",
-        "author_inst": "Moderna, Inc."
+        "author_name": "Wes R Hinsley",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Nicolas Van de Velde",
-        "author_inst": "Moderna, Inc."
+        "author_name": "Richard G FitzJohn",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "James A. Mansi",
-        "author_inst": "Moderna, Inc."
+        "author_name": "Erik Volz",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Robert Verity",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Neil M Ferguson",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Anne Cori",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Marc Baguelin",
+        "author_inst": "Imperial College London"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.02.07.23285380",
@@ -82482,53 +83033,33 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.02.06.23285542",
-    "rel_title": "Use of wastewater metrics to track COVID-19 in the U.S.: a national time-series analysis over the first three quarters of 2022",
+    "rel_doi": "10.1101/2023.02.06.23285411",
+    "rel_title": "Time series analysis of routine immunisation coverage during the COVID-19 pandemic in 2021 shows continued global decline and increases in Zero Dose children",
     "rel_date": "2023-02-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.06.23285542",
-    "rel_abs": "BackgroundWidespread use of at-home COVID-19 tests hampers determination of community COVID-19 incidence. Using nationwide data available through the US National Wastewater Surveillance System, we examined the performance of two wastewater metrics in predicting high case and hospitalizations rates both before and after widespread use of at-home tests.\n\nMethodsWe performed area under the receiver operating characteristic (ROC) curve analysis (AUC) for two wastewater metrics--viral concentration relative to the peak of January 2022 (\"wastewater percentile\") and 15-day percent change in SARS-CoV-2 (\"percent change\"). Dichotomized reported cases ([&ge;] 200 or <200 cases per 100,000) and new hospitalizations ([&ge;] 10 or <10 per 100,000) were our dependent variables, stratified by calendar quarter. Using logistic regression, we assessed the performance of combining wastewater metrics.\n\nResultsAmong 268 counties across 22 states, wastewater percentile detected high reported case and hospitalizations rates in the first quarter of 2022 (AUC 0.95 and 0.86 respectively) whereas the percent change did not (AUC 0.54 and 0.49 respectively). A wastewater percentile of 51% maximized sensitivity (0.93) and specificity (0.82) for detecting high case rates. A model inclusive of both metrics performed no better than using wastewater percentile alone. The predictive capability of wastewater percentile declined over time (AUC 0.84 and 0.72 for cases for second and third quarters of 2022).\n\nConclusionNationwide, county wastewater levels above 51% relative to the historic peak predicted high COVID rates and hospitalization in the first quarter of 2022, but performed less well in subsequent quarters. Decline over time in predictive performance of this metric likely reflects underreporting of cases, reduced testing, and possibly lower virulence of infection due to vaccines and treatments.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.06.23285411",
+    "rel_abs": "Whilst it is now widely recognised that routine immunisation (RI) was disrupted by the COVID-19 pandemic in 2020 compared to previous immunisation performance, the extent of continued interruptions in 2021 and/or rebounds to previous trends remains unclear, with sporadic surveys reporting signs of immunisation system recovery at the end of 2020.\n\nWe modelled country-specific RI trends using validated estimates of national coverage from the World Health Organisation and United Nation Childrens Fund for over 160 countries, to project expected diphtheria, tetanus, and pertussis-containing vaccine first-dose (DTP1), third-dose (DTP3) and measles-containing vaccine first-dose (MCV1) coverage for 2021 based on pre-pandemic trends (from 2000-2019).\n\nWe estimated a 3{middle dot}6% (95%CI: [2{middle dot}6%; 4{middle dot}6%]) decline in global DTP3 coverage in 2021 compared to 2000-2019 trends, from an expected 90{middle dot}1% to a reported 86{middle dot}5% across 164 reporting countries, and similar results for DTP1 (2{middle dot}8% decline; 95%CI: [2{middle dot}0%; 3{middle dot}6%]), and for MCV1 (3{middle dot}8% decline; 95%CI: [4{middle dot}8%; 2{middle dot}7%]). 86{middle dot}5% global coverage in 2021 represents a further decrease from that reported in 2020 and 2019, and translates to a 16-year setback in RI coverage, i.e., 2005 levels. Hypothesised and early signals of rebounds to pre-pandemic coverage were not seen in most countries. The Americas, Africa, and Asia were the most impacted regions, with low- and middle-income countries the most affected income groups.\n\nThe number of Zero Dose children also continued to increase in 2021. DTP1 coverage declined worldwide from an expected 93{middle dot}7% to a reported 90{middle dot}9% (2{middle dot}8% decline; 95%CI: [2{middle dot}0%; 3{middle dot}6%]) which translates into an additional 3.4 million Zero Dose children on top of an expected 11.0 million (30.9% increase) at the global level.\n\nWe hope this work will provide an objective baseline to inform future interventions and prioritisation aiming to facilitate rebounds in coverage to previous levels and catch-up of growing populations of under- and un-immunised children.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Meri Varkila",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Maria Montez-Rath",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Joshua Salomon",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Xue Yu",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Geoffrey Block",
-        "author_inst": "U.S. Renal Care"
-      },
-      {
-        "author_name": "Douglas Owens",
-        "author_inst": "Stanford University"
+        "author_name": "Beth Evans",
+        "author_inst": "University of Geneva"
       },
       {
-        "author_name": "Glenn Chertow",
-        "author_inst": "Stanford University"
+        "author_name": "Olivia Keiser",
+        "author_inst": "University of Geneva"
       },
       {
-        "author_name": "Julie Parsonnet",
-        "author_inst": "Stanford University"
+        "author_name": "Laurent Kaiser",
+        "author_inst": "University of Geneva Hospitals"
       },
       {
-        "author_name": "Shuchi Anand",
-        "author_inst": "Stanford University"
+        "author_name": "Thibaut Jombart",
+        "author_inst": "Imperial College London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -84156,47 +84687,51 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2023.02.05.527173",
-    "rel_title": "Taxonomical and ontological analysis of verified natural and laboratory human coronavirus hosts",
+    "rel_doi": "10.1101/2023.02.06.23285513",
+    "rel_title": "A Rapid review on the COVID-19 Pandemic's Global Impact on Breast Cancer Screening Participation Rates and Volumes from January-December 2020",
     "rel_date": "2023-02-06",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.05.527173",
-    "rel_abs": "To fully understand COVID-19, it is critical to identify and analyze all the possible hosts of SARS-CoV-2 (the pathogen of COVID-19) and compare them with the hosts of other human coronaviruses. In this study, we collected, annotated, and performed taxonomical and ontological analysis of all the reported and verified hosts for all human coronaviruses including SARS-CoV, MERS-CoV, SARS-CoV-2, and four others that cause the common cold. A total of 37 natural hosts and 19 laboratory animal hosts of host human coronaviruses were identified based on experimental or clinical evidence. Our taxonomical ontology-based analysis found that all the verified susceptible natural and laboratory animals belong to therian mammals. Specifically, these 37 natural therian hosts include one wildlife marsupial mammal (i.e., Didelphis virginiana) and 36 Eutheria mammals (a.k.a. placental mammals). The 19 laboratory animal hosts are also classified as placental mammals. While several non-therian animals (including snake, housefly, zebrafish) were reported to be likely SARS-CoV-2 hosts, our analysis excluded them due to the lack of convincing evidence. Genetically modified mouse models with human Angiotensin-converting enzyme 2 (ACE2) or dipeptidyl peptidase-4 (DPP4) protein were more susceptible to virulent human coronaviruses with clear symptoms. Coronaviruses often became more virulent and adaptive in the mouse hosts after a series of viral passages in the mice. To support knowledge standardization and analysis, we have also represented the annotated host knowledge in the Coronavirus Infectious Disease Ontology (CIDO) and provided ways to automatically query the knowledge.",
-    "rel_num_authors": 7,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.06.23285513",
+    "rel_abs": "BackgroundCOVID-19 has strained population breast mammography screening programs that aim to diagnose and treat breast cancers earlier. As the pandemic has affected countries differently, we aimed to quantify changes in breast screening volume and uptake during the first year of the COVID-19 pandemic.\n\nMethodsWe systematically searched Medline, the WHO (World Health Organization) COVID-19 database, and governmental databases. Studies covering January 2020 to March 2022 were included. We extracted and analyzed data regarding study methodology, screening volume and uptake. To assess for risk-of-bias, we used the Joanna Briggs Institute Critical Appraisal tool.\n\nResultsTwenty-six cross-sectional descriptive studies were included out of 935 independent records. Reductions in screening volume and uptake rates were observed among eight countries. Changes in screening participation volume in five countries with national population-based screening ranged from -13% to -31%. Among two countries with limited population-based programs the decline ranged from -61% to -41%. Within the USA, population participation volumes varied ranging from +18% to -39% with suggestion of differences by insurance status (HMO, Medicare, and low-income programs). Almost all studies had high risk-of-bias due to insufficient statistical analysis and confounding factors.\n\nDiscussion and ConclusionExtent of COVID-19-induced reduction in breast screening participation volume differed by region and data suggested potential differences by healthcare setting (e.g., national health insurance vs private health care). Recovery efforts should monitor access to screening and early diagnosis to determine if prevention services need strengthening to increase coverage of marginalized groups and reduce disparities.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Yang Wang",
-        "author_inst": "Guizhou University School of Medicine, Guiyang, Guizhou 550025, China."
+        "author_name": "Reagan Lee",
+        "author_inst": "University of Edinburgh"
       },
       {
-        "author_name": "Muhui Ye",
-        "author_inst": "Chinese University of Hong Kong (Shenzhen), Shenzhen, Guangdong, China."
+        "author_name": "- UNCOVER",
+        "author_inst": "-"
       },
       {
-        "author_name": "Fengwei Zhang",
-        "author_inst": "Guizhou University School of Medicine, Guiyang, Guizhou 550025, China."
+        "author_name": "Wei Xu",
+        "author_inst": "University of Edinburgh"
       },
       {
-        "author_name": "Zachary Thomas Freeman",
-        "author_inst": "Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA."
+        "author_name": "- International Partnership for Resilience in Cancer Systems (I-PaRCS), Breast Cancer Working Group 2",
+        "author_inst": "-"
       },
       {
-        "author_name": "Hong Yu",
-        "author_inst": "Guizhou University School of Medicine, Guiyang, Guizhou 550025, China."
+        "author_name": "Marshall Dozier",
+        "author_inst": "University of Edinburgh"
       },
       {
-        "author_name": "Xianwei Ye",
-        "author_inst": "Guizhou University School of Medicine, Guiyang, Guizhou 550025, China."
+        "author_name": "Ruth McQuillan",
+        "author_inst": "University of Edinburgh"
       },
       {
-        "author_name": "Yongqun He",
-        "author_inst": "Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA."
+        "author_name": "Evropi Theodoratou",
+        "author_inst": "The University of Edinburgh"
+      },
+      {
+        "author_name": "Jonine Figueroa",
+        "author_inst": "University of Edinburgh"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc0",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.02.02.23285377",
@@ -85978,65 +86513,137 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.01.31.23285248",
-    "rel_title": "Using publicly available data to identify priority communities for a SARS-CoV-2 testing intervention in a southern U.S. state",
+    "rel_doi": "10.1101/2023.01.31.23285232",
+    "rel_title": "Cohort profile: Virus Watch: Understanding community incidence, symptom profiles, and transmission of COVID-19 in relation to population movement and behaviour",
     "rel_date": "2023-02-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.31.23285248",
-    "rel_abs": "BackgroundThe U.S. Southeast has a high burden of SARS-CoV-2 infections and COVID-19 disease. We used public data sources and community engagement to prioritize county selections for a precision population health intervention to promote a SARS-CoV-2 testing intervention in rural Alabama during October 2020 and March 2021.\n\nMethodsWe modeled factors associated with county-level SARS-CoV-2 percent positivity using covariates thought to associate with SARS-CoV-2 acquisition risk, disease severity, and risk mitigation practices. Descriptive epidemiologic data were presented to scientific and community advisory boards to prioritize counties for a testing intervention.\n\nResultsIn October 2020, SARS-CoV-2 percent positivity was not associated with any modeled factors. In March 2021, premature death rate (aRR 1.16, 95% CI 1.07, 1.25), percent Black residents (aRR 1.00, 95% CI 1.00, 1.01), preventable hospitalizations (aRR 1.03, 95% CI 1.00, 1.06), and proportion of smokers (aRR 0.231, 95% CI 0.10, 0.55) were associated with average SARS-CoV-2 percent positivity. We then ranked counties based on percent positivity, case fatality, case rates, and number of testing sites using individual variables and factor scores. Top ranking counties identified through factor analysis and univariate associations were provided to community partners who considered ongoing efforts and strength of community partnerships to promote testing to inform intervention.\n\nConclusionsThe dynamic nature of SARS-CoV-2 proved challenging for a modelling approach to inform a precision population health intervention at the county level. Epidemiological data allowed for engagement of community stakeholders implementing testing. As data sources and analytic capacities expand, engaging communities in data interpretation is vital to address diseases locally.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.31.23285232",
+    "rel_abs": "Key FeaturesO_LIVirus Watch is a national community cohort study of COVID-19 in households in England and Wales, established in June 2020. The study aims to provide evidence on which public health approaches are most effective in reducing transmission, and investigate community incidence, symptoms, and transmission of COVID-19 in relation to population movement and behaviours.\nC_LIO_LI28,527 households and 58,628 participants of age (0-98 years, mean age 48), were recruited between June 2020 - July 2022\nC_LIO_LIData collected include demographics, details on occupation, co-morbidities, medications, and infection-prevention behaviours. Households are followed up weekly with illness surveys capturing symptoms and their severity, activities in the week prior to symptom onset and any COVID-19 test results. Monthly surveys capture household finance, employment, mental health, access to healthcare, vaccination uptake, activities and contacts. Data have been linked to Hospital Episode Statistics (HES), inpatient and critical care episodes, outpatient visits, emergency care contacts, mortality, virology testing and vaccination data held by NHS Digital.\nC_LIO_LINested within Virus Watch are a serology & PCR cohort study (n=12,877) and a vaccine evaluation study (n=19,555).\nC_LIO_LIStudy data are deposited in the Office of National Statistics (ONS) Secure Research Service (SRS). Survey data are available under restricted access upon request to ONS SRS.\nC_LI",
+    "rel_num_authors": 30,
     "rel_authors": [
       {
-        "author_name": "Lynn T. Matthews",
-        "author_inst": "Division of Infectious Disease, Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham"
+        "author_name": "Thomas Edward Byrne",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Dustin M. Long",
-        "author_inst": "Department of Biostatistics, School of Public Health, University of Alabama at Birmingham"
+        "author_name": "Jana Kovar",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Madeline C. Pratt",
-        "author_inst": "Division of Infectious Disease, Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham"
+        "author_name": "Sarah Beale",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Ya Yuan",
-        "author_inst": "Department of Biostatistics, School of Public Health, University of Alabama at Birmingham"
+        "author_name": "Isobel Braithwaite",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Sonya L. Heath",
-        "author_inst": "Division of Infectious Disease, Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham"
+        "author_name": "Ellen Fragaszy",
+        "author_inst": "UCL"
+      },
+      {
+        "author_name": "Wing Lam Erica Fong",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Cyril Geismar",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Susan J Hoskins",
+        "author_inst": "Univerity College London"
       },
       {
-        "author_name": "Emily B. Levitan",
-        "author_inst": "Department of Epidemiology, School of Public Health, University of Alabama at Birmingham"
+        "author_name": "Annalan Mathew Dwight Navaratnam",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Sydney Grooms",
-        "author_inst": "Center for AIDS Research, Heersink School of Medicine, University of Alabama at Birmingham"
+        "author_name": "Vincent Nguyen",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Thomas Creger",
-        "author_inst": "Center for AIDS Research, Heersink School of Medicine, University of Alabama at Birmingham"
+        "author_name": "Parth Patel",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Aadia Rana",
-        "author_inst": "Division of Infectious Disease, Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham"
+        "author_name": "Madhumita Shrotri",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Michael J Mugavero",
-        "author_inst": "Division of Infectious Disease, Department of Medicine, Heersink School of Medicine, University of Alabama at Birmingham; Center for AIDS Research, Heersink Sch"
+        "author_name": "Alexei Yavlinsky",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Suzanne E. Judd",
-        "author_inst": "Center for the Study of Community Health, School of Public Health, University of Alabama at Birmingham"
+        "author_name": "Pia Hardelid",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "- COVID COMET RADXUP Team",
-        "author_inst": ""
+        "author_name": "Linda Wijlaars",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Eleni Nastouli",
+        "author_inst": "UCLH"
+      },
+      {
+        "author_name": "Moira Spyer",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Anna Ayree",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Ingemar Cox",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Vasileios Lampos",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Rachel A McKendry",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Tao Cheng",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Anne M Johnson",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Susan Fiona Michie",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Jo Gibbs",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Richard Gilson",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Alison Rodger",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Ibrahim Abubakar",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Andrew Hayward",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Robert W Aldridge",
+        "author_inst": "UCL"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -87904,59 +88511,71 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2023.01.26.23285076",
-    "rel_title": "The impact of vaccination frequency on COVID-19 public health outcomes: A model-based analysis",
-    "rel_date": "2023-01-29",
+    "rel_doi": "10.1101/2023.01.24.23284947",
+    "rel_title": "What interventions or best practice are there to support people with Long COVID, or similar post-viral conditions or conditions characterised by fatigue, to return to normal activities: a rapid review",
+    "rel_date": "2023-01-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.26.23285076",
-    "rel_abs": "While the rapid deployment of SARS-CoV-2 vaccines had a significant impact on the ongoing COVID-19 pandemic, rapid viral immune evasion and waning neutralizing antibody titers have degraded vaccine efficacy. Nevertheless, vaccine manufacturers and public health authorities have a number of levers at their disposal to maximize the benefits of vaccination. Here, we use an agent-based modeling framework coupled with the outputs of a population pharmacokinetic model to examine the impact of boosting frequency and durability of vaccinal response on vaccine efficacy. Our work suggests that repeated dosing at frequent intervals (multiple times a year) may offset the degradation of vaccine efficacy, preserving their utility in managing the ongoing pandemic. Our work relies on assumptions about antibody accumulation and the tolerability of repeated vaccine doses. Given the practical significance of potential improvements in vaccinal utility, clinical research to better understand the effects of repeated vaccination would be highly impactful. These findings are particularly relevant as public health authorities worldwide seek to reduce the frequency of boosters to once a year or less. Our work suggests practical recommendations for vaccine manufacturers and public health authorities and draws attention to the possibility that better outcomes for SARS-CoV-2 public health remain within reach.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.24.23284947",
+    "rel_abs": "Previous research has categorised symptoms of COVID-19 / Long COVID into 12 thematic areas including: fever, myalgia, fatigue, impaired cognitive function, and that COVID-19 survivors had reduced levels of physical function, activities of daily living, and health-related quality of life. Our aim was to review the evidence for interventions or best practice to support people with Long COVID, or similar post-viral conditions characterised by fatigue, to return to normal activities.\n\nEvidence was included from guidelines, systematic reviews (SR), and primary studies. The primary studies focussed on Long COVID (LC) indicated that there should be a needs-based focus to care for those with LC. Consideration should be given to individuals living with LC in the same way as people with disabilities are accommodated in terms of workplace adjustment. Two SRs indicated that non-pharmaceutical interventions (NPIs) for patients with LC or chronic fatigue syndrome could help improve function for activities of daily life. However, the third, most recent SR, concluded that there is a lack of robust evidence for NPIs. LC fatigue management methods may be beneficial under certain conditions. One SR reported work capability as an outcome however they did not find any studies which evaluated the impact of interventions on return to work/ normal life. One primary study, on individuals with CFS, described a written self-management programme. Following this intervention there was an 18% increase in the number of patients in employment.\n\nPolicy and practice implications: Long COVID is still being established as a post-viral condition with many symptoms. Patient-centred treatment options such as occupational therapy, self-management therapy and talking therapy may be considered in the same way as for other debilitating conditions. Return-to-work accommodations are needed for all workers unable to return to full-time employment. Due to the nature of the studies included, there was little reported evidence of effectiveness of getting individuals back into their normal activities.\n\nFunding statementThe Bangor Institute for Health and Medical Research was funded for this work by the Wales COVID-19 Evidence Centre, itself funded by Health & Care Research Wales on behalf of Welsh Government.\n\nRapid Review DetailsO_ST_ABSReview conducted byC_ST_ABSBangor Institute for Health and Medical Research (BIHMR), Bangor University.\n\nReview Team{blacksquare} Dr Llinos Haf Spencer, l.spencer@bangor.ac.uk\n{blacksquare}Dr Annie Hendry, a.hendry@bangor.ac.uk\n{blacksquare}Mr Abraham Makanjuola, a.makanjuola@bangor.ac.uk\n{blacksquare}Ms Bethany Fern Anthony, b.anthony@bangor.ac.uk\n{blacksquare}Mr Jacob Davies, jacob.davies@bangor.ac.uk\n{blacksquare}Ms Kalpa Pisavadia, kalpa.pisavadia@bangor.ac.uk\n{blacksquare}Professor Dyfrig Hughes, d.a.hughes@bangor.ac.uk\n{blacksquare}Professor Deb Fitzsimmons, d.fitzsimmons@bangor.ac.uk\n{blacksquare}Professor Clare Wilkinson, c.wilkinson@bangor.ac.uk\n{blacksquare}Professor Rhiannon Tudor Edwards, r.t.edwards@bangor.ac.uk\n\n\nReview submitted to the WCEC on11 January 2023\n\nStakeholder consultation meeting8th November 2022\n\nRapid Review report issued by the WCEC inJanuary 2022\n\nWCEC TeamAdrian Edwards, Ruth Lewis, Alison Cooper and Micaela Gal involved in drafting the Topline Summary and editing.\n\nThis review should be cited asRR00042_ Wales COVID-19 Evidence Centre\n\nDisclaimerThe views expressed in this publication are those of the authors, not necessarily Health and Care Research Wales. The WCEC and authors of this work declare that they have no conflict of interest.\n\nTOPLINE SUMMARYO_ST_ABSWhat is a Rapid Review?C_ST_ABSOur rapid reviews (RR) use a variation of the systematic review (SR) approach, abbreviating or omitting some components to generate the evidence to inform stakeholders promptly whilst maintaining attention to bias. They follow the methodological recommendations and minimum standards for conducting and reporting RR, including a structured protocol, systematic search, screening, data extraction, critical appraisal, and evidence synthesis to answer a specific question and identify key research gaps. They take 1 to 2 months, depending on the breadth and complexity of the research topic/question(s), extent of the evidence base, and type of analysis required for synthesis.\n\nWho is this summary for?Policymakers in Welsh Government to plan and deliver services for individuals with Long COVID as they re-enter training, education, employment, and informal caring responsibilities.\n\nBackground / Aim of Rapid ReviewPrevious research has categorised symptoms of COVID-19/Long COVID into 12 thematic areas including: fever, myalgia, fatigue, impaired cognitive function, and that COVID-19 survivors had reduced levels of physical function, activities of daily living, and health-related quality of life (Amdal et al., 2021; de Oliveira Almeida et al., 2022). NICE guidelines highlight the impact of the condition on quality of life and the challenge of determining best practice based on the current evidence (National Institute for Health and Care Excellence et al., 2022). Treatments for other post-viral syndromes may also apply to people living with Long COVID (Wong and Weitzer, 2021). Our aim was to review the evidence for interventions or best practice to support people with Long COVID, or similar post-viral conditions characterised by fatigue, to return to normal activities (including return to the workforce, education, childcare, or housework).\n\nKey FindingsEvidence was included from guidelines (n=3), systematic reviews (SRs) (n=3), and primary studies (n=4).\n\nExtent of the evidence base{blacksquare} Two SRs included non-pharmacological interventions for Long COVID or post-viral syndromes, including Long COVID (Chandan et al., 2022; Fowler-Davis et al., 2021). The remaining SR focused on interventions for Chronic Fatigue Syndrome (CFS).\n{blacksquare}The four primary studies were conducted in the UK, USA, Norway, and Turkey. The SRs included studies from across Europe, Asia, Africa, and Australasia.\n{blacksquare}Included SRs and primary studies evaluated non-pharmaceutical interventions, including fatigue management, exercise therapy, Cognitive Behavioural Therapy (CBT), workplace support, self-management, sleep therapy, music therapy, and counselling.\n{blacksquare}Two relevant guidelines were identified for Long COVID and one for ME/CFS. The Long COVID guideline was aimed at employers, and the ME/CFS guideline was aimed at service providers and users.\n\n\nRecency of the evidence base{blacksquare} Included papers were from 2014 to 2022.\n\n\nEvidence of effectiveness{blacksquare} The primary studies focussed on Long COVID indicated that there should be a needs-based focus to care for those with Long COVID (Lunt et al., 2022; Skilbeck, 2022; Wong et al., 2022). Consideration should be given to individuals living with Long COVID in the same way as people with disabilities are accommodated in terms of workplace adjustment (e.g. part-time hours, working from home, or hybrid working).\n{blacksquare}Two SRs indicated that non-pharmaceutical interventions for patients with Long COVID or CFS could help improve function for activities of daily life (Fowler-Davis et al., 2021; Larun et al., 2019). However, the third and most recent SR concluded that there is a lack of robust evidence for non-pharmaceutical interventions (Chandan et al., 2022).\n{blacksquare}Long COVID fatigue management by exercise therapy, electrical nerve stimulation, sleep and touch therapy, and behavioural self-management may be beneficial when: physical and psychological support is delivered in groups, people can plan their functional response to fatigue, strengthening rather than endurance is used to prevent deconditioning, fatigue is regarded in the context of an individuals lifestyle and home-based activities are used (Fowler-Davis et al 2021).\n{blacksquare}One SR (Chandan et al 2022) reported work capability as an outcome however they did not find any studies which evaluated the impact of interventions on return to work/ normal life.\n{blacksquare}One primary study concentrated on individuals with CFS (Nyland et al., 2014). Nyland et al. (2014) described a written self-management programme featuring active coping (with CFS) strategies for daily life. Following this intervention, there was an 18% increase in the number of patients in employment (from baseline to follow-up) (Nyland et al., 2014).\n\n\nBest quality evidence{blacksquare} The three SRs (Chandan et al., 2022; Fowler-Davis et al., 2021; Larun et al., 2019) were of high quality, as was one of the cohort studies (Lunt et al., 2022).\n\n\nPolicy Implications{blacksquare} Long COVID is still being established as a post-viral condition with many symptoms. The Welsh Government may seek to consider patient-centred treatment options such as occupational therapy, self-management therapy and talking therapy (such as Cognitive Behavioural Therapy) in the same way as for other debilitating conditions including ME/CFS.\n{blacksquare}Return-to-work accommodations are needed for all workers unable to return to full-time employment.\n{blacksquare}Due to the nature of the studies included, there was little reported evidence of effectiveness of getting individuals back into their normal activities.\n\n\nStrength of EvidenceConfidence in the findings is low. Only four primary studies reported outcomes relating to work capacity and return to normal activities such as childcare and housework.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Madison Stoddard",
-        "author_inst": "Fractal Therapeutics"
+        "author_name": "Llinos Haf Spencer",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Lin Yuan",
-        "author_inst": "Fractal Therapeutics"
+        "author_name": "Annie Hendry",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Sharanya Sarkar",
-        "author_inst": "Dartmouth College"
+        "author_name": "Abraham Makanjuola",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Debra Van Egeren",
-        "author_inst": "Stanford University"
+        "author_name": "Bethany F Anthony",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Shruthi Mangalaganesh",
-        "author_inst": "Monash University"
+        "author_name": "Jacob Davies",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Ryan P. Nolan",
-        "author_inst": "Halozyme Therapeutics"
+        "author_name": "Kalpa Pisavadia",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Michael S. Rogers",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Dyfrig Hughes",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Greg Hather",
-        "author_inst": "Sage Therapeutics"
+        "author_name": "Deb Fitzsimmons",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Laura F. White",
-        "author_inst": "Boston University"
+        "author_name": "Clare Wilkinson",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
       },
       {
-        "author_name": "Arijit Chakravarty",
-        "author_inst": "Fractal Therapeutics"
+        "author_name": "Rhiannon Tudor Edwards",
+        "author_inst": "Bangor Institute for Health and Medical Research, Bangor University, Wales, UK"
+      },
+      {
+        "author_name": "Ruth Lewis",
+        "author_inst": "Wales COVID-19 Evidence Centre, Wales, UK"
+      },
+      {
+        "author_name": "Alison Cooper",
+        "author_inst": "Wales COVID-19 Evidence Centre, Wales, UK"
+      },
+      {
+        "author_name": "Adrian G Edwards",
+        "author_inst": "Wales COVID-19 Evidence Centre, Wales, UK"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2023.01.24.23284959",
@@ -89702,105 +90321,97 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.01.21.23284592",
-    "rel_title": "TONSILS ARE MAJOR SITES OF PROLONGED SARS-COV-2 INFECTION IN CHILDREN",
+    "rel_doi": "10.1101/2023.01.22.23284881",
+    "rel_title": "Second monovalent SARS-CoV-2 mRNA booster restores Omicron-specific neutralizing activity in both nursing home residents and health care workers",
     "rel_date": "2023-01-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.21.23284592",
-    "rel_abs": "In the present study, we show that SARS-CoV-2 can infect palatine tonsils and adenoids in children without symptoms of COVID-19, with no history of recent upper airway infection. We studied 48 children undergoing tonsillectomy due to snoring/OSA or recurrent tonsillitis between October 2020 and September 2021. Briefly, nasal cytobrush (NC), nasal wash (NW) and tonsillar tissue fragments obtained at surgery were tested by RT-PCR, immunohistochemistry (IHC), flow cytometry and neutralization assay. We detected the presence of SARS-CoV-2 in at least one specimen tested in 25% of patients (20% in palatine tonsils and 16.27% in adenoids, 10.41% of NC and 6.25% of NW). Importantly, in 2 of the children there was evidence of laboratory-confirmed acute infection 2 and 5 months before surgery. IHC revealed the presence of SARS-CoV-2 nucleoprotein in epithelial surface and in lymphoid cells in both extrafollicular and follicular regions, in adenoids and palatine tonsils. Flow cytometry showed that CD20+ B lymphocytes were the most infected phenotypes by SARS-CoV-2 NP, followed by CD4+ and CD8+ T lymphocytes, and CD14+ macrophages and dendritic cells. Additionally, IF indicated that SARS-CoV-2-infected tonsillar tissues had increased expression of ACE2 and TMPRSS2. NGS sequencing demonstrated the presence of different SARS CoV-2 variants in tonsils from different tissues. SARS-CoV-2 antigen detection was not restricted to tonsils, but was also detected in nasal cells from the olfactory region. In conclusion, palatine tonsils and adenoids are sites of prolonged infection by SARS-CoV-2 in children, even without COVID-19 symptoms.",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.22.23284881",
+    "rel_abs": "We examined whether the second monovalent SARS-CoV-2 mRNA booster increased antibody levels and their neutralizing activity to Omicron variants in nursing home residents (NH) residents and healthcare workers (HCW). We sampled 367 NH residents and 60 HCW after primary mRNA vaccination, first and second boosters, for antibody response and pseudovirus neutralization assay against SARS-CoV-2 wild-type (WT) (Wuhan-Hu-1) strain and Omicron BA1 variant. Antibody levels and neutralizing activity progressively increased with each booster but subsequently waned over weeks. NH residents, both those without and with prior infection, had a robust geometric mean fold rise (GMFR) of 10.2 (95% CI 5.1, 20.3) and 6.5 (95% CI 4.5, 9.3) respectively in Omicron-BA.1 subvariant specific neutralizing antibody levels following the second booster vaccination (p<0.001). These results support the ongoing efforts to ensure that both NH residents and HCW are up to date on recommended SARS-CoV-2 vaccine booster doses.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Thais Melquiades",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
-      },
-      {
-        "author_name": "Ronaldo Martins",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
-      },
-      {
-        "author_name": "Carol Miura",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Clare Nugent",
+        "author_inst": "Brown University Alpert Medical School, Division of Geriatric and Palliative Care Medicine"
       },
       {
-        "author_name": "Maria Vitoria Oliveira",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Yasin Abul",
+        "author_inst": "Brown Alpert Medical School Division of Geriatric and Palliative Care Medicine"
       },
       {
-        "author_name": "Murilo Cassiano",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Elizabeth White",
+        "author_inst": "Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI"
       },
       {
-        "author_name": "Tamara Rodrigues",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Fadi Shehadeh",
+        "author_inst": "Division of Infectious Diseases, Alpert Medical School of Brown University, Providence, RI"
       },
       {
-        "author_name": "Flavio Veras",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Matthew Kaczynski",
+        "author_inst": "Division of Infectious Diseases, Alpert Medical School of Brown University, Providence, RI"
       },
       {
-        "author_name": "Josane Freitas Souza",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Lewis Oscar Felix",
+        "author_inst": "Division of Infectious Diseases, Alpert Medical School of Brown University, Providence, RI"
       },
       {
-        "author_name": "Rogerio Gomes",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Narchonai Ganesan",
+        "author_inst": "Division of Infectious Diseases, Alpert Medical School of Brown University, Providence, RI"
       },
       {
-        "author_name": "Glaucia Almeida",
-        "author_inst": "Ribeirao Preto Medical Scholl - University of Sao Paulo"
+        "author_name": "Oladayo A. Oyebanji",
+        "author_inst": "Case Western Reserve University School of Medicine, Cleveland, OH"
       },
       {
-        "author_name": "Stella Rezende Melo",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Igor Vishnepolskiy",
+        "author_inst": "Brown University Alpert Medical School, Division of Geriatric and Palliative Care Medicine"
       },
       {
-        "author_name": "Gabriela Conde",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Elise M. Didion",
+        "author_inst": "Geriatric Research, Education and Clinical Center,  VA Northeast Ohio Healthcare System, Cleveland VA"
       },
       {
-        "author_name": "Matheus Dias",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Alexandra Paxitzis",
+        "author_inst": "Case Western Reserve University School of Medicine, Cleveland, OH"
       },
       {
-        "author_name": "Fabiano Capato",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Maegan L. Sheehan",
+        "author_inst": "Ragon Institute of MGH, MIT and Harvard, Cambridge, MA"
       },
       {
-        "author_name": "Maria Lucia Silva",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Eleftherios Mylonakis",
+        "author_inst": "Division of Infectious Diseases, Alpert Medical School of Brown University, Providence, RI"
       },
       {
-        "author_name": "Veridiana Barros",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Brigid M. Wilson",
+        "author_inst": "Case Western Reserve University School of Medicine, Cleveland, OH , Geriatric Research, Education and Clinical Center,  VA Northeast Ohio Healthcare System, Cle"
       },
       {
-        "author_name": "Lucas Carenzi",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Alejandro Benjamin Balazs",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Dario S Zamboni",
-        "author_inst": "Universidade de Sao Paulo, School of Medicine Ribeirao Preto"
+        "author_name": "Philip A. Chan",
+        "author_inst": "Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, RI, USA"
       },
       {
-        "author_name": "Daniel Macedo",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Christopher L King",
+        "author_inst": "Case Western Reserve University School of Medicine, Cleveland, OH"
       },
       {
-        "author_name": "Edwin Tamashiro",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Walther M. Pfeifer",
+        "author_inst": "East Side Clinical Laboratory, East Providence, RI"
       },
       {
-        "author_name": "Wilma Anselmo-Lima",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Evan Dickerson",
+        "author_inst": "Division of Geriatrics and Palliative Medicine, Alpert Medical School of Brown University, Providence, RI"
       },
       {
-        "author_name": "Fabiana Cardoso Valera",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "David H. Canaday",
+        "author_inst": "Case Western Reserve University"
       },
       {
-        "author_name": "Eurico Arruda",
-        "author_inst": "University of Sao Paulo School of Medicine, Ribeirao Preto, Brazil"
+        "author_name": "Stefan Gravenstein",
+        "author_inst": "Brown University Alpert Medical School, Division of Geriatric and Palliative Care Medicine"
       }
     ],
     "version": "1",
@@ -91536,39 +92147,35 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2023.01.20.23284607",
-    "rel_title": "Electronic data review, client reminders, and expanded clinic hours for improving cervical cancer screening rates after COVID19 pandemic shutdowns: a multi-component quality improvement program",
+    "rel_doi": "10.1101/2023.01.21.23284855",
+    "rel_title": "Safety of bivalent omicron-containing mRNA-booster vaccines: a nationwide cohort study",
     "rel_date": "2023-01-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.20.23284607",
-    "rel_abs": "ObjectiveTo improve cervical cancer screening (CCS) rates, the East Boston Neighborhood Health Center (EBNHC) implemented a Quality Improvement (QI) initiative from March to August 2021.\n\nMethodsStaff training was provided. A 21-provider team validated overdue CCS indicated by electronic medical record data. To improve screening, CCS-only sessions were created during regular clinic hours (n=5) and weekends/evenings (n=8). Patients were surveyed on their experience.\n\nResults6126 charts were reviewed. Of the list of overdue patients, outreach was performed to 1375 patients to schedule the 13 sessions. A total of 459 (33%) of patients completed screening, 622 (45%) could not be reached, and 203 (15%) canceled or missed appointments. The proportion of total active patients who were up to date with CCS increased from 68% in March to 73% in August 2021. Survey results indicated high patient satisfaction, and only 42% of patients would have scheduled CCS without outreach.\n\nConclusionsThe creation of a validated patient chart list and extra clinical sessions devoted entirely to CCS improved up-to-date CCS rates. However, high rates of unsuccessful outreach and cancelations limited sustainability. This information can be used by other community health centers to optimize clinical workflows for CCS.\n\nFundingAll funding was internal from EBNHC Adult Medicine, Family Medicine, and Womens Health Departments.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.21.23284855",
+    "rel_abs": "BackgroundSafety data to support bivalent omicron-containing mRNA-booster vaccination are lacking.\n\nMethodsIn a Danish nationwide cohort study from 1 January 2021 to 10 December 2022, we examined the association between bivalent omicron-containing mRNA-booster vaccination as a fourth Covid-19 vaccine dose and risk of adverse events in individuals aged [&ge;]50 years. Using incidence rate ratios estimated with Poisson regression, we compared the rates of hospital visits for 27 different adverse events in a 28-day main risk period following vaccination with a bivalent omicron-containing mRNA-booster vaccine as a fourth dose to reference period rates from day 29 after the third or fourth vaccine dose and onward. Secondary analyses included stratifying by sex, age, and vaccine type and assessing the associations using self-controlled case series and observed vs. expected cohort analyses.\n\nResults1,740,417 individuals (mean age 67.8 years, standard deviation 10.7) received a bivalent omicron-containing mRNA-booster vaccine as a fourth dose. Fourth dose vaccination with a bivalent omicron-containing booster did not statistically significantly increase the rate of any of the 27 adverse outcomes within 28 days, nor when analyzed according to age, sex, vaccine type, or using alternative analytical approaches. However, post-hoc analysis detected signals for myocarditis (statistically significantly so in females), although the outcome was very rare and findings were based on few cases. No risk of cerebrovascular infarction was found.\n\nConclusionsBivalent omicron-containing mRNA-booster vaccination as a fourth dose was not associated with an increased risk of 27 different adverse events in 50+-year-olds.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Sue Ghosh",
-        "author_inst": "East Boston Neighborhood Health Center"
-      },
-      {
-        "author_name": "Jackie Fantes",
-        "author_inst": "East Boston Neighborhood Health Center"
+        "author_name": "Niklas Worm Andersson",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Karin Leschly",
-        "author_inst": "East Boston Neighborhood Health Center"
+        "author_name": "Emilia Myrup Thiesson",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Julio Mazul",
-        "author_inst": "East Boston Neighborhood Health Center"
+        "author_name": "Joergen Vinsloev Hansen",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Rebecca B Perkins",
-        "author_inst": "Boston University"
+        "author_name": "Anders Hviid",
+        "author_inst": "Statens Serum Institut"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "obstetrics and gynecology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2023.01.20.524893",
@@ -93402,33 +94009,93 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2023.01.16.23284634",
-    "rel_title": "Prediction of Long COVID Based on Severity of Initial COVID-19 Infection: Differences in predictive feature sets between hospitalized versus non-hospitalized index infections",
+    "rel_doi": "10.1101/2023.01.14.23284558",
+    "rel_title": "Determinants of protection against SARS-CoV-2 Omicron BA.1 and Delta infections in fully vaccinated outpatients",
     "rel_date": "2023-01-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.16.23284634",
-    "rel_abs": "Long COVID is recognized as a significant consequence of SARS-COV2 infection. While the pathogenesis of Long COVID is still a subject of extensive investigation, there is considerable potential benefit in being able to predict which patients will develop Long COVID. We hypothesize that there would be distinct differences in the prediction of Long COVID based on the severity of the index infection, and use whether the index infection required hospitalization or not as a proxy for developing predictive models. We divide a large population of COVID patients drawn from the United States National Institutes of Health (NIH) National COVID Cohort Collaborative (N3C) Data Enclave Repository into two cohorts based on the severity of their initial COVID-19 illness and correspondingly trained two machine learning models: the Long COVID after Severe Disease Model (LCaSDM) and the Long COVID after Mild Disease Model (LCaMDM). The resulting models performed well on internal validation/testing, with a F1 score of 0.94 for the LCaSDM and 0.82 for the LCaMDM. There were distinct differences in the top 10 features used by each model, possibly reflecting the differences in type and amount of pathophysiological data between the hospitalized and non-hospitalized patients and/or reflecting different pathophysiological trajectories in the development of Long COVID. Of particular interest was the importance of Plant Hardiness Zone in the feature set for the LCaMDM, which may point to a role of climate and/or sunlight in the progression to Long COVID. Future work will involve a more detailed investigation of the potential role of climate and sunlight, as well as refinement of the predictive models as Long COVID becomes increasingly parsed into distinct clinical phenotypes.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.14.23284558",
+    "rel_abs": "ObjectivesWe aimed to evaluate the association between the humoral and cellular immune responses and symptomatic SARS-CoV-2 infection with Delta or Omicron BA.1 variants in fully vaccinated outpatients.\n\nMethodsAnti-RBD IgG levels and IFN-{gamma} release were evaluated at PCR-diagnosis of SARS-CoV-2 in 636 samples from negative and positive patients during Delta and Omicron BA.1 periods.\n\nResultsMedian levels of anti-RBD IgG in positive patients were significantly lower than in negative patients for both variants (p < 0.05). The risk of Delta infection was inversely correlated with anti-RBD IgG titres (aOR = 0.63, 95% CI [0.41; 0.95], p = 0.03) and it was lower in the hybrid immunity group compared to the homologous vaccination group (aOR = 0.22, 95% CI [0.05; 0.62], p = 0.01). In contrast, neither the vaccination scheme nor anti-RBD IgG titers were associated with the risk of BA.1 infection in multivariable analysis. IFN-{gamma} release post-SARS-CoV-2 peptide stimulation was not different between samples from patients infected (either with Delta or Omicron BA.1 variant) or not (p = 0.77).\n\nConclusionsOur results show that high circulating levels of anti-RBD IgG and hybrid immunity were independently associated with a lower risk of symptomatic SARS-CoV-2 infection in outpatients with differences according to the infecting variant.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Damien Socia",
-        "author_inst": "University of Vermont Larner College of Medicine"
+        "author_name": "Alvaro Roy",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
       },
       {
-        "author_name": "Dale Larie",
-        "author_inst": "University of Vermont Larner College of Medicine"
+        "author_name": "Carla Saade",
+        "author_inst": "CIRI, Centre International de Recherche en Infectiologie, Team VirPath, Univ Lyon, Inserm, U1111, Universite Claude Bernard Lyon 1, CNRS, Lyon 69364, France"
       },
       {
-        "author_name": "Solomon Feuerwerker",
-        "author_inst": "University of Vermont Larner College of Medicine"
+        "author_name": "Laurence Josset",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
       },
       {
-        "author_name": "Gary An",
-        "author_inst": "University of Vermont"
+        "author_name": "Benedicte Clement",
+        "author_inst": "Services des urgences, Hopital de la Croix-Rousse, Hospices Civils de Lyon, Lyon 69004, France"
       },
       {
-        "author_name": "Chase Cockrell",
-        "author_inst": "University of Vermont Larner College of Medicine"
+        "author_name": "Florence Morfin",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Gregory Destras",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Martine Valette",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Vinca Icard",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Antoine Oblette",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Marion Debombourg",
+        "author_inst": "Joint Research Unit Civils Hospices of Lyon-bioMerieux, Hopital Lyon Sud, Hospices Civils de Lyon, Pierre-Benite 69310, France"
+      },
+      {
+        "author_name": "Christine Garrigou",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Karen Brengel-Pesce",
+        "author_inst": "Joint Research Unit Civils Hospices of Lyon-bioMerieux, Hopital Lyon Sud, Hospices Civils de Lyon, Pierre-Benite 69310, France"
+      },
+      {
+        "author_name": "Laurence Generenaz",
+        "author_inst": "Joint Research Unit Civils Hospices of Lyon-bioMerieux, Hopital Lyon Sud, Hospices Civils de Lyon, Pierre-Benite 69310, France"
+      },
+      {
+        "author_name": "Kahina Saker",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Romain Hernu",
+        "author_inst": "Services des urgences, Hopital de la Croix-Rousse, Hospices Civils de Lyon, Lyon 69004, France"
+      },
+      {
+        "author_name": "Bruno Pozzetto",
+        "author_inst": "Laboratoire des Agents Infectieux, Centre Hospitalier Universitaire de Saint-Etienne, Saint-Etienne 42270, France"
+      },
+      {
+        "author_name": "Bruno Lina",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Mary Anne Trabaud",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Sophie Trouillet-Assant",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
+      },
+      {
+        "author_name": "Antonin Bal",
+        "author_inst": "Laboratoire de Virologie, Institut des Agents Infectieux, Laboratoire associe au Centre National de Reference des virus des infections respiratoires, Hospices C"
       }
     ],
     "version": "1",
@@ -95276,71 +95943,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.01.13.23284341",
-    "rel_title": "Long-term systemic and mucosal SARS-CoV-2 IgA response and its association with persistent smell and taste disorders.",
+    "rel_doi": "10.1101/2023.01.12.23284489",
+    "rel_title": "Cross-sectional Ct distributions from qPCR tests can provide an early warning signal for the spread of COVID-19 in communities",
     "rel_date": "2023-01-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.13.23284341",
-    "rel_abs": "Current approved COVID-19 vaccines, notably mRNA and adenoviral vectored technologies, still fail to fully protect against infection and transmission of various SARS-CoV-2 variants. The mucosal immunity at the upper respiratory tract represents the first line of defense against respiratory viruses such as SARS-CoV-2 and is thus critical to develop vaccine blocking human-to-human transmission. We measured systemic and mucosal Immunoglobulin A (IgA) response in serum and saliva from 133 healthcare workers from Percy teaching military hospital following a mild infection (SARS-CoV-2 Wuhan strain, n=58) or not infected (n=75), and after SARS-CoV-2 vaccination (Vaxzevria(R)/Astrazeneca and/or Comirnaty(R)/Pfizer). While serum anti-SARS-CoV-2 Spike IgA response lasted up to 16 months post-infection, IgA response in saliva had mostly fallen to baseline level at 6 months post-infection. Vaccination could reactivate the mucosal response generated by prior infection, but failed to induce a significant mucosal IgA response by itself. As breakthrough infections have been correlated with IgA levels, other vaccine platforms inducing a better mucosal immunity are needed to control COVID-19 infection in the future. Early post-COVID-19 serum anti-Spike-NTD IgA titer correlated with seroneutralization titers. Interestingly, its saliva counterpart positively correlated with persistent smell and taste disorders more than one year after mild COVID-19, and could potentially be used as an early prognosis biomarker.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.12.23284489",
+    "rel_abs": "BackgroundSARS-CoV-2 PCR testing data has been widely used for COVID-19 surveillance. Existing COVID-19 forecasting models mainly rely on case counts, even though the binary PCR results provide a limited picture of the pandemic trajectory. Most forecasting models have failed to accurately predict the COVID-19 waves before they occur. Recently a model utilizing cross-sectional population cycle threshold (Ct) values obtained from PCR tests (Ct-based model) was developed to overcome the limitations of using only binary PCR results. In this study, we aimed to improve on COVID-19 forecasting models using features derived from the Ct-based model, to detect epidemic waves earlier than case-based trajectories.\n\nMethodsPCR data was collected weekly at Northeastern University (NU) between August 2020 and January 2022. The NU campus epidemic trajectories were generated from the campus incidence rates. In addition, epidemic trajectories were generated for Suffolk County, where NU is located, based on publicly available case-counts. A novel forecasting approach was developed by enhancing a recent deep learning model with Ct-based features, along with the models default features. For this, cross-sectional Ct values from PCR data were used to generate Ct-based epidemic trajectories, including effective reproductive rate (Rt) and incidence. The improvement in forecasting performance was compared using absolute errors and residual squared errors with respect to actual observed cases at the 7-day and 14-day forecasting horizons. The model was also tested prospectively over the period January 2022 to April 2022.\n\nResultsRt estimates from the Ct-based model preceded NU campus and Suffolk County cases by 12 and 14 days respectively, with a three-way synched Spearman correlation of 0.57. Enhancing the forecasting models with Ct-based information significantly decreased absolute error and residual squared error compared to the original model without Ct features (p-value <0.001 for both 7 and 14-days forecasting horizons).\n\nConclusionCt-based epidemic trajectories can herald an earlier signal for impending epidemic waves in the community and forecast transmission peaks. Moreover, COVID-19 forecasting models can be enhanced using these Ct features to improve their forecasting accuracy.\n\nPolicy implicationsWe make the case that public health agencies should publish Ct values along with the binary positive/negative PCR results. Early and accurate forecasting of epidemic waves can inform public health policies and countermeasures which can mitigate spread.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Jessica Denis",
-        "author_inst": "Institut de Recherche Biomedicale des Armees"
-      },
-      {
-        "author_name": "Annabelle Garnier",
-        "author_inst": "Institut de Recherche Biomedicale des Armees"
-      },
-      {
-        "author_name": "Laurence Cheutin",
-        "author_inst": "Institut de Recherche Biomedicale des Armees"
-      },
-      {
-        "author_name": "Audrey Ferrier",
-        "author_inst": "Institut de Recherche Biomedicale des Armees"
-      },
-      {
-        "author_name": "Hawa Timera",
-        "author_inst": "Institut de Recherche Biomedicale des Armees"
-      },
-      {
-        "author_name": "Fanny Jarjaval",
-        "author_inst": "Institut de Recherche Biomedicale des Armees"
-      },
-      {
-        "author_name": "Carine Hejl",
-        "author_inst": "Hopital d'instruction des armees Percy, Ecole du Val-de-Grace"
+        "author_name": "Mahfuza Sharmin",
+        "author_inst": "Thermo Fisher Scientific"
       },
       {
-        "author_name": "Emmanuelle Billon-Denis",
-        "author_inst": "Institut de Recherche Biomedicale des Armees, Institut Pasteur de Paris"
+        "author_name": "Mani Manivannan",
+        "author_inst": "Thermo Fisher Scientific"
       },
       {
-        "author_name": "- Percy ImmunoCovid group",
-        "author_inst": ""
+        "author_name": "David Woo",
+        "author_inst": "Thermo Fisher Scientific"
       },
       {
-        "author_name": "Damien Ricard",
-        "author_inst": "Institut de Recherche Biomedicale des Armees, Ecole du Val-de-Grace, Centre Borelli ENS Paris-Saclay"
+        "author_name": "Oceane Sorel",
+        "author_inst": "Thermo Fisher Scientific"
       },
       {
-        "author_name": "Jean-Nicolas Tournier",
-        "author_inst": "Institut de Recherche Biomedicale des Armees, Ecole du Val-de-Grace, Institut Pasteur de Paris"
+        "author_name": "Jared Auclair",
+        "author_inst": "Northeastern University"
       },
       {
-        "author_name": "Aurelie Trignol",
-        "author_inst": "Institut de Recherche Biomedicale des Armees, Universite Paris Cite"
+        "author_name": "Manoj Gandhi",
+        "author_inst": "Thermo Fisher Scientific"
       },
       {
-        "author_name": "Marie Mura",
-        "author_inst": "Institut de Recherche Biomedicale des Armees, Institut Pasteur de Paris"
+        "author_name": "Imran Mujawar",
+        "author_inst": "Thermo Fisher Scientific"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2023.01.13.23284507",
@@ -96986,33 +97629,41 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.01.09.23284284",
-    "rel_title": "Using early detection data to estimate the date of emergence of an epidemic outbreak",
+    "rel_doi": "10.1101/2023.01.10.23284410",
+    "rel_title": "Addressing spatial misalignment in population health research: a case study of US congressional district political metrics and county health data",
     "rel_date": "2023-01-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.09.23284284",
-    "rel_abs": "While the first infection by an emerging disease is often unknown, information on early cases can be used to date it, which is of great interest to trace the diseases origin and understand early infection dynamics. In the context of the COVID-19 pandemic, previous studies have estimated the date of emergence (e.g., first human SARS-CoV-2 infection in Wuhan, emergence of the Alpha variant in the UK) using mainly genomic data. Another dating attempt only relied on case data, estimating a date of emergence using a non-Markovian stochastic model and considering the first case detection. Here, we extend this stochastic approach to use available data of the whole early case dynamics. Our model provides estimates of the delay from the first infection to the N th reported case. We first validate our model using data concerning the spread of the Alpha SARS-CoV-2 variant in the UK. Our results suggest that the first Alpha infection occurred on (median) August 20 (95% interquantile range across retained simulations, IqR: July 20-September 4), 2020. Next, we apply our model to data on the early reported cases of COVID-19. We used data on the date of symptom onset up to mid-January, 2020. We date the first SARS-CoV-2 infection in Wuhan at (median) November 26 (95%IqR: October 31-December 7), 2019. Our results fall within ranges previously estimated by studies relying on genomic data. Our population dynamics-based modelling framework is generic and flexible, and thus can be applied to estimate the starting time of outbreaks, in contexts other than COVID-19, as long as some key parameters (such as transmission and detection rates) are known.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.10.23284410",
+    "rel_abs": "Areal spatial misalignment, which occurs when data on multiple variables are collected using mismatched boundary definitions, is a ubiquitous obstacle to data analysis in public health and social science research. As one example, the emerging sub-field studying the links between political context and health in the United States faces significant spatial misalignment-related challenges, as the congressional districts (CDs) over which political metrics are measured and administrative units, e.g., counties, for which health data are typically released, have a complex misalignment structure. Standard population-weighted data realignment procedures can induce measurement error and invalidate inference, which has prompted the development of fully model-based approaches for analyzing spatially misaligned data. One such approach, atom-based regression models (ABRM), holds particular promise but has scarcely been used in practice due to the lack of appropriate software or examples of implementation. ABRM use \"atoms\", the areas created by intersecting all sets of units on which variables of interest are measured, as the units of analysis and build models for the atom-level data, treating the atom-level variables (generally unmeasured) as latent variables. In this paper, we demonstrate the feasibility and strengths of the ABRM in a case study of the association between political representatives voting behavior (CD-level) and COVID-19 mortality rates (county-level) in a post-vaccine period. The adjusted ABRM results suggest that more conservative voting record is associated with an increase in COVID-19 mortality rates, with estimated associations smaller in magnitude but consistent in direction with those of standard realignment methods. The results also indicate that ABRM may enable more robust confounding adjustment and more realistic uncertainty estimates, properly representing the uncertainties arising from all analytic procedures. We also implement the ABRM in modern optimized Bayesian computing programs and make our code publicly available, which may enable these methods to be more widely adopted.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Sof\u00eda Jij\u00f3n",
-        "author_inst": "Sorbonne Universit\u00e9"
+        "author_name": "Rachel C. Nethery",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "Peter Czuppon",
-        "author_inst": "University of M\u00fcnster"
+        "author_name": "Christian Testa",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "Fran\u00e7ois Blanquart",
-        "author_inst": "Coll\u00e8ge de France"
+        "author_name": "Loni P. Tabb",
+        "author_inst": "Drexel Dornsife School of Public Health"
       },
       {
-        "author_name": "Florence D\u00e9barre",
-        "author_inst": "CNRS"
+        "author_name": "William P. Hanage",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
+      },
+      {
+        "author_name": "Jarvis T. Chen",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
+      },
+      {
+        "author_name": "Nancy Krieger",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -98568,59 +99219,151 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2023.01.06.522349",
-    "rel_title": "Effects of Variants of Concern Mutations on the Force-Stability of the SARS-CoV-2:ACE2 Interface and Virus Transmissibility",
+    "rel_doi": "10.1101/2023.01.08.523127",
+    "rel_title": "Bivalent mRNA vaccine improves antibody-mediated neutralization of many SARS-CoV-2 Omicron lineage variants",
     "rel_date": "2023-01-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.06.522349",
-    "rel_abs": "Viruses mutate under a variety of selection pressures, allowing them to continuously adapt to their hosts. Mutations in SARS-CoV-2 have shown effective evasion of population immunity and increased affinity to host factors, in particular to the cellular receptor ACE2. However, in the dynamic environment of the respiratory tract forces act on the binding partners, which raises the question whether not only affinity, but also force-stability of the SARS-CoV-2:ACE2 bond, might be a selection factor for mutations. Here, we use magnetic tweezers (MT) to study the effect of amino acid substitutions in variants of concern (VOCs) on RBD:ACE2 bond kinetics with and without external load. We find higher affinity for all VOCs compared to wt, in good agreement with previous affinity measurements in bulk. In contrast, Alpha is the only VOC that shows significantly higher force stability compared to wt. Investigating the RBD:ACE2 interactions with molecular dynamics simulations, we are able to rationalize the mechanistic molecular origins of this increase in force-stability. Our study emphasizes the diversity of contributions to the assertiveness of variants and establishes force-stability as one of several factors for fitness. Understanding fitness-advantages opens the possibility for prediction of likely mutations allowing rapid adjustment of therapeutics, vaccination, and intervention measures.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.08.523127",
+    "rel_abs": "The early Omicron lineage variants evolved and gave rise to diverging lineages that fueled the COVID-19 pandemic in 2022. Bivalent mRNA vaccines, designed to broaden protection against circulating and future variants, were authorized by the U.S. Food and Drug Administration (FDA) in August 2022 and recommended by the U.S. Centers for Disease Control and Prevention (CDC) in September 2022. The impact of bivalent vaccination on eliciting neutralizing antibodies against homologous BA.4/BA.5 viruses as well as emerging heterologous viruses needs to be analyzed. In this study, we analyze the neutralizing activity of sera collected after a third dose of vaccination (2-6 weeks post monovalent booster) or a fourth dose of vaccination (2-7 weeks post bivalent booster) against 10 predominant/recent Omicron lineage viruses including BA.1, BA.2, BA.5, BA.2.75, BA.2.75.2, BN.1, BQ.1, BQ.1.1, XBB, and XBB.1. The bivalent booster vaccination enhanced neutralizing antibody titers against all Omicron lineage viruses tested, including a 10-fold increase in neutralization of BQ.1 and BQ.1.1 viruses that predominated in the U.S. during the last two months of 2022. Overall, the data indicate the bivalent vaccine booster strengthens protection against Omicron lineage variants that evolved from BA.5 and BA.2 progenitors.",
+    "rel_num_authors": 33,
     "rel_authors": [
       {
-        "author_name": "Magnus S. Bauer",
-        "author_inst": "Department of Physics and Center for NanoScience (CeNS), LMU Munich, 80799 Munich, Germany; Department of Chemical Engineering, Stanford University; Stanford, C"
+        "author_name": "Nannan Jiang",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Sophia Gruber",
-        "author_inst": "Department of Physics and Center for NanoScience (CeNS), LMU Munich, 80799 Munich, Germany;"
+        "author_name": "Li Wang",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Adina Hausch",
-        "author_inst": "Center for Protein Assemblies, TUM School of Natural Sciences, Technical University of Munich, Germany;"
+        "author_name": "Masato Hatta",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Marcelo C.R. Melo",
-        "author_inst": "Department of Physics, Auburn University, Auburn, AL 36849, USA;"
+        "author_name": "Chenchen Feng",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Priscila S.F.C. Gomes",
-        "author_inst": "Department of Physics, Auburn University, Auburn, AL 36849, USA;"
+        "author_name": "Michael Currier",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Thomas Nicolaus",
-        "author_inst": "Department of Physics and Center for NanoScience (CeNS), LMU Munich, 80799 Munich, Germany;"
+        "author_name": "Xudong Lin",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Lukas F. Milles",
-        "author_inst": "Institute for Protein Design, University of Washington, Seattle, WA 98195, USA; Institute for Protein Design, University of Washington, Seattle, WA 98195, USA;"
+        "author_name": "Jaber Hossain",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Rafael C. Bernardi",
-        "author_inst": "Department of Physics, Auburn University, Auburn, AL 36849, USA;"
+        "author_name": "Dan Cui",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Hermann E. Gaub",
-        "author_inst": "Department of Physics and Center for NanoScience (CeNS), LMU Munich, 80799 Munich, Germany;"
+        "author_name": "Brian R. Mann",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
       },
       {
-        "author_name": "Jan Lipfert",
-        "author_inst": "Department of Physics and Debye Institute for Nanomaterials Science, Utrecht University, 3584 CC Utrecht, The Netherlands;"
+        "author_name": "Nicolas A. Kovacs",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Wei Wang",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Ginger Atteberry",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Malania Wilson",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Reina Chau",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Kristine A. Lacek",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Clinton R. Paden",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Norman Hassell",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Benjamin Rambo-Martin",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "John R. Barnes",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Rebecca J. Kondor",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Wesley H. Self",
+        "author_inst": "Vanderbilt University Medical Center, Nashville, TN, USA"
+      },
+      {
+        "author_name": "Jillian P. Rhoads",
+        "author_inst": "Vanderbilt University Medical Center, Nashville, TN, USA"
+      },
+      {
+        "author_name": "Adrienne Baughman",
+        "author_inst": "Vanderbilt University Medical Center, Nashville, TN, USA"
+      },
+      {
+        "author_name": "James D. Chappell",
+        "author_inst": "Vanderbilt University Medical Center, Nashville, TN, USA"
+      },
+      {
+        "author_name": "Nathan I. Shapiro",
+        "author_inst": "Beth Israel Deaconess Medical Center,  Harvard University, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Kevin W. Gibbs",
+        "author_inst": "Wake Forest Baptist Medical Center, Winston-Salem, NC, USA"
+      },
+      {
+        "author_name": "David N. Hager",
+        "author_inst": "Johns Hopkins University, Baltimore, MD, USA"
+      },
+      {
+        "author_name": "Adam S. Lauring",
+        "author_inst": "University of Michigan, Ann Arbor, MI, USA"
+      },
+      {
+        "author_name": "Diya Surie",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Meredith L. McMorrow",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Natalie J. Thornburg",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "David E. Wentworth",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Bin Zhou",
+        "author_inst": "Centers for Disease Control and Prevention"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc0",
     "type": "new results",
-    "category": "biophysics"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2023.01.07.523115",
@@ -100754,35 +101497,75 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2023.01.04.522762",
-    "rel_title": "Urban birds become less fearful following COVID-19 reopenings",
+    "rel_doi": "10.1101/2023.01.04.522794",
+    "rel_title": "Targets and cross-reactivity of human T cell recognition of Common Cold Coronaviruses",
     "rel_date": "2023-01-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.04.522762",
-    "rel_abs": "Following the COVID-19 pandemic, many people around the world stayed home, drastically altering human activity in cities. This exceptional moment provided researchers the opportunity to test how urban animals respond to human disturbance, in some cases testing fundamental questions on the mechanistic impact of urban behaviors on animal behavior. However, at the end of this \"anthropause,\" human activity returned to cities. How might each of these strong shifts affect wildlife in the short and long term? We focused on fear response, a trait essential to tolerating urban life. We measured flight initiation distance--at both individual and population-levels--for an urban bird before, during, and after the anthropause to examine if birds experienced longer-term changes after a year of lowered human presence. Dark-eyed juncos did not change fear levels during the anthropause, but they became drastically less fearful afterwards. These surprising and counter-intuitive findings, made possible by following the behavior of individuals over time, has led to a novel understanding that fear response can be driven by plasticity, yet not habituation-like processes. The pandemic-caused changes in human activity have shown that there is great complexity in how humans modify a behavioral trait fundamental to urban tolerance in animals.",
-    "rel_num_authors": 4,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.04.522794",
+    "rel_abs": "The Coronavirus (CoV) family includes a variety of viruses able to infect humans. Endemic CoVs that can cause common cold belong to the alphaCoV and betaCoV genera, with the betaCoV genus also containing subgenera with zoonotic and pandemic concern, including sarbecoCoV (SARS-CoV and SARS-CoV-2) and merbecoCoV (MERS-CoV). It is therefore warranted to explore pan-CoV vaccine concepts, to provide adaptive immune protection against new potential CoV outbreaks, particularly in the context of betaCoV sub lineages. To explore the feasibility of eliciting CD4+ T cell responses widely cross-recognizing different CoVs, we utilized samples collected pre-pandemic to systematically analyze T cell reactivity against representative alpha (NL63) and beta (OC43) common cold CoVs (CCC). Similar to previous findings on SARS-CoV-2, the S, N, M, and nsp3 antigens were immunodominant for both viruses while nsp2 and nsp12 were immunodominant for NL63 and OC43, respectively. We next performed a comprehensive T cell epitope screen, identifying 78 OC43 and 87 NL63-specific epitopes. For a selected subset of 18 epitopes, we experimentally assessed the T cell capability to cross-recognize sequences from representative viruses belonging to alphaCoV, sarbecoCoV, and beta-non-sarbecoCoV groups. We found general conservation within the alpha and beta groups, with cross-reactivity experimentally detected in 89% of the instances associated with sequence conservation of >67%. However, despite sequence conservation, limited cross-reactivity was observed in the case of sarbecoCoV (50% of instances), indicating that previous CoV exposure to viruses phylogenetically closer to this subgenera is a contributing factor in determining cross-reactivity. Overall, these results provided critical insights in the development of future pan-CoV vaccines.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Eleanor Diamant",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Alison Tarke",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Ian MacGregor-Fors",
-        "author_inst": "University of Helsinki"
+        "author_name": "Yun Zhang",
+        "author_inst": "J. Craig Venter Institute"
       },
       {
-        "author_name": "Daniel T Blumstein",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Nils Methot",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Pamela J Yeh",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Tara N Narowski",
+        "author_inst": "University of North Carolina School of Medicine"
+      },
+      {
+        "author_name": "Elizabeth Phillips",
+        "author_inst": "VUMC: Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Simon Mallal",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "April Frazier",
+        "author_inst": "La Jolla Institute for Immunology"
+      },
+      {
+        "author_name": "Gilberto Filaci",
+        "author_inst": "University of Genoa"
+      },
+      {
+        "author_name": "Daniela Weiskopf",
+        "author_inst": "La Jolla Institute For Immunology"
+      },
+      {
+        "author_name": "Jennifer M Dan",
+        "author_inst": "La Jolla Institute for Immunology"
+      },
+      {
+        "author_name": "Prem Lakshmanane",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Richard H. Scheuermann",
+        "author_inst": "J. Craig Venter Institute"
+      },
+      {
+        "author_name": "Alessandro Sette",
+        "author_inst": "La Jolla Institute for immunology"
+      },
+      {
+        "author_name": "Alba Grifoni",
+        "author_inst": "La Jolla Institute for Immunology"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "animal behavior and cognition"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2023.01.05.522845",
@@ -102772,35 +103555,55 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2023.01.01.522328",
-    "rel_title": "SARS-CoV-2 protein NSP2 enhances microRNA-mediated translational repression",
+    "rel_doi": "10.1101/2023.01.02.522505",
+    "rel_title": "Nanoparticle-Conjugated TLR9 Agonists Improve the Potency, Durability, and Breadth of COVID-19 Vaccines",
     "rel_date": "2023-01-03",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.01.522328",
-    "rel_abs": "microRNAs (miRNAs) inhibit mRNA translation initiation by recruiting the GIGYF2/4EHP translation repressor complex to the mRNA 5 cap structure. Viruses utilise miRNAs to impair the host antiviral immune system and facilitate viral infection by expressing their own miRNAs or co-opting cellular miRNAs. We recently reported that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encoded non-structural protein 2 (NSP2) interacts with GIGYF2. This interaction is critical for blocking translation of the Ifn1-b mRNA that encodes the cytokine Interferon-{beta}, and thereby impairs the host antiviral immune response. However, it is not known whether NSP2 also affects miRNA-mediated silencing. Here, we demonstrate the pervasive augmentation of the miRNA-mediated translational repression of cellular mRNAs by NSP2. We show that NSP2 interacts with Argonaute 2, the core component of the miRNA-Induced Silencing Complex (miRISC) and enhances the translational repression mediated by natural miRNA binding sites in the 3 UTR of cellular mRNAs. Our data reveal an additional layer of the complex mechanism by which SARS-CoV-2 and likely other coronaviruses manipulate the host gene expression program through co-opting the host miRNA-mediated silencing machinery.",
-    "rel_num_authors": 4,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.02.522505",
+    "rel_abs": "Development of effective vaccines for infectious diseases has been one of the most successful global health interventions in history. Though, while ideal subunit vaccines strongly rely on antigen and adjuvant(s) selection, the mode and timescale of exposure to the immune system has often been overlooked. Unfortunately, poor control over the delivery of many adjuvants, which play a key role in enhancing the quality and potency of immune responses, can limit their efficacy and cause off-target toxicities. There is critical need for new adjuvant delivery technologies to enhance their efficacy and boost vaccine performance. Nanoparticles (NPs) have been shown to be ideal carriers for improving antigen delivery due to their shape and size, which mimic viral structures, but have been generally less explored for adjuvant delivery. Here, we describe the design of self-assembled poly(ethylene glycol)-b-poly(lactic acid) nanoparticles decorated with CpG, a potent TLR9 agonist, to increase adjuvanticity in COVID-19 vaccines. By controlling the surface density of CpG, we show that intermediate valency is a key factor for TLR9 activation of immune cells. When delivered with the SARS-CoV-2 spike protein, CpG NP adjuvants greatly improve the magnitude and duration of antibody responses when compared to free CpG, and result in overall greater breadth of immunity against variants of concern. Moreover, encapsulation of CpG NPs into injectable polymeric-nanoparticle (PNP) hydrogels enhance the spatiotemporal control over co-delivery of CpG NP adjuvant and spike protein antigen such that a single immunization of hydrogel-based vaccines generates comparable humoral responses as a typical prime-boost regimen of soluble vaccines. These delivery technologies can potentially reduce the costs and burden of clinical vaccination, both of which are key elements in fighting a pandemic.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Xu Zhang",
-        "author_inst": "McGill University"
+        "author_name": "Ben S. Ou",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Reese Jalal Ladak",
-        "author_inst": "McGill University"
+        "author_name": "Vittoria C.T.M. Picece",
+        "author_inst": "Stanford University, ETH Zurich"
       },
       {
-        "author_name": "Thomas Duchaine",
-        "author_inst": "McGill University"
+        "author_name": "Julie Baillet",
+        "author_inst": "Stanford University, University of Bordeaux"
       },
       {
-        "author_name": "Nahum Sonenberg",
-        "author_inst": "McGill University"
+        "author_name": "Emily C. Gale",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Abigail E. Powell",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Olivia M. Saouaf",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Jerry Yan",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Hector Lopez Hernandez",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Eric Appel",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "cell biology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2023.01.03.522427",
@@ -104378,31 +105181,71 @@
     "category": "transplantation"
   },
   {
-    "rel_doi": "10.1101/2022.12.23.22283884",
-    "rel_title": "Changes in depression and anxiety among people with cognitive impairment and dementia during the COVID-19 pandemic: Analysis of the English Longitudinal Study of Ageing",
+    "rel_doi": "10.1101/2022.12.21.22283740",
+    "rel_title": "Prior infection- and/or vaccine-induced protection against Omicron BA.1, BA.2 and BA.4/BA.5-related hospitalisations in older adults: a test-negative case-control study in Quebec, Canada",
     "rel_date": "2022-12-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.23.22283884",
-    "rel_abs": "BackgroundSome studies have identified declines in mental health over the course of the COVID-19 pandemic across the world and in different age groups, including older people. As anxiety and depression are common neuropsychiatric symptoms among people with dementia or mild cognitive impairment, the mental health experiences of older people during the pandemic should therefore take cognitive function into consideration. This should also be examined using quantitative measures that were assessed prior to the pandemic. This study addresses such gaps in the evidence base on depression and anxiety among older people with cognitive impairment before and throughout the COVID-19 pandemic.\n\nMethods and FindingsUsing data from the English Longitudinal Study of Ageing (ELSA) collected from 2018/19 to Nov/Dec 2020, we estimated changes in depression and anxiety for people aged 50+ in England across three cognitive function groups: no impairment, mild cognitive impairment, and dementia.\n\nWe found that depression (measured with CES-D score) worsened from 2018/19 to Nov/Dec 2020 for people with mild cognitive impairment (1.39 (95%CI: 1.29-1.49) to 2.16 (2.02-2.30)) or no impairment (1.17 (95%CI: 1.12-1.22) to 2.03 (1.96-2.10)). Anxiety, using a single-item rating of 0-10 also worsened among those with mild cognitive impairment (2.48 (2.30-2.66) to 3.14 (2.95-3.33)) or no impairment (2.20 (2.11-2.28) to 2.85 (2.77-2.95)). No statistically significant increases were found for those with dementia. Using a clinical cutoff for likely depression (CES-D[&ge;]4), we found statistically significant increases in the probability of likely clinical depression between 2018/19 and Nov/Dec 2020 for those with no impairment (0.110 (0.099-0.120) to 0.206 (0.191-0.222)) and those with mild impairment (0.139 (0.120-0.159) to 0.234 (0.204-0.263)).\n\nWe also found that differences according to cognitive function that existed before the pandemic were no longer present by June/July 2020, and there were no statistically significant differences in depression or anxiety among cognitive groups in Nov/Dec 2020.\n\nConclusionsOur findings on measures collected before and during the pandemic suggest a convergence in mental health across cognitive function groups during the pandemic. This suggests mental health services will need to meet an increased demand that will come from older adults, especially those not living with cognitive impairment or dementia. We also found little significant change in mental health outcomes among those with dementia; as their existing need for support will remain, policymakers and care practitioners will need to ensure this group continues to have equitable access to support for their mental health.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.21.22283740",
+    "rel_abs": "BackgroundDue to severe outcomes, elderly adults 60 years or older are prioritized for COVID-19 vaccination but accumulated SARS-CoV-2 infection and vaccination likely modifies their risk. We estimated vaccine effectiveness against omicron-associated hospitalisation among elderly adults, by number of doses, prior infection history and time since last immunological event.\n\nMethodsWe conducted a test-negative case-control study among symptomatic elderly adults tested for SARS-CoV-2 in Quebec, Canada during BA.1-, BA.2- and BA.4/5-dominant periods. Relative to unvaccinated, infection-naive participants, we compared COVID-19 hospitalisation risk by mRNA vaccine dose and/or prior infection (pre-omicron or omicron) history.\n\nFindingsDuring BA.1, BA.2 and BA.4/5 periods, two- vs. four-dose vaccine effectiveness alone against hospitalisation was: 78% (95%CI:75-80) vs. 96% (95%CI:93-98); 60% (95%CI:50-97) vs. 84% (95%CI:81-87); and 40% (95%CI:30-49) vs. 68% (95%CI:63-72), respectively, consistent with longer median time since second vs fourth dose. By respective period, effectiveness of pre-omicron vs. omicron infection alone against hospitalisation was: 93% (95%CI:80-97) vs. [not estimable]; 88% (95%CI:50-97) vs. 96% (95%CI:68-99); and 69% (95%CI:30-85) vs. 90% (95%CI:79-95). Regardless of doses (2-5) or prior infection type, hybrid protection was [&ge;]90%, lasting at least 6-8 months during the BA.4/5 period. Prior omicron infection alone reduced BA.4/5 hospitalisation risk by >80% for at least 6-8 months.\n\nInterpretationElderly adults with history of both prior SARS-CoV-2 infection and [&ge;]2 vaccine doses appear well-protected for a prolonged period against omicron hospitalisation, including BA.4/5. Ensuring infection-naive older adults remain up-to-date with vaccination may further reduce COVID-19 hospitalisations most efficiently.\n\nFundingMinistere de la Sante et des Services sociaux du Quebec.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Brian Beach",
-        "author_inst": "University College London"
+        "author_name": "Sara Carazo",
+        "author_inst": "Institut de sant\u00e9 publique du Qu\u00e9bec"
       },
       {
-        "author_name": "Andrew Steptoe",
-        "author_inst": "UCL: University College London"
+        "author_name": "Danuta M Skowronski",
+        "author_inst": "BC Centre for Disease Control"
       },
       {
-        "author_name": "Paola Zaninotto",
-        "author_inst": "University College London"
+        "author_name": "Marc Brisson",
+        "author_inst": "Centre Hospitalier Universitaire (CHU) de Qu\u00e9bec-Universit\u00e9 Laval Research Center"
+      },
+      {
+        "author_name": "Chantal Sauvageau",
+        "author_inst": "Institut de sant\u00e9 publique du Qu\u00e9bec"
+      },
+      {
+        "author_name": "Nicholas Brousseau",
+        "author_inst": "Institut de sant\u00e9 publique du Qu\u00e9bec"
+      },
+      {
+        "author_name": "Judith M Fafard",
+        "author_inst": "Laboratoire de Sant\u00e9 Publique du Qu\u00e9bec, Institut national de sant\u00e9 publique du Qu\u00e9bec"
+      },
+      {
+        "author_name": "Rodica Gilca",
+        "author_inst": "Institut de sant\u00e9 publique du Qu\u00e9bec"
+      },
+      {
+        "author_name": "Denis Talbot",
+        "author_inst": "Centre Hospitalier Universitaire (CHU) de Qu\u00e9bec-Universit\u00e9 Laval Research Center"
+      },
+      {
+        "author_name": "Manale Ouakki",
+        "author_inst": "Institut de sant\u00e9 publique du Qu\u00e9bec"
+      },
+      {
+        "author_name": "Yossi Febriani",
+        "author_inst": "Centre Hospitalier Universitaire (CHU) de Qu\u00e9bec-Universit\u00e9 Laval Research Center"
+      },
+      {
+        "author_name": "Genevi\u00e8ve Deceuninck",
+        "author_inst": "Centre Hospitalier Universitaire (CHU) de Qu\u00e9bec-Universit\u00e9 Laval Research Center"
+      },
+      {
+        "author_name": "Philippe De Wals",
+        "author_inst": "Institut de sant\u00e9 publique du Qu\u00e9bec"
+      },
+      {
+        "author_name": "Gaston De Serres",
+        "author_inst": "Institut de sant\u00e9 publique du Qu\u00e9bec"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.12.26.521940",
@@ -106209,7 +107052,7 @@
     "rel_date": "2022-12-26",
     "rel_site": "bioRxiv",
     "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.23.521761",
-    "rel_abs": "The coronavirus SARS-CoV-2 protects its RNA from being recognized by host immune responses by methylation of its 5 end, also known as capping. This process is carried out by two enzymes, non-structural protein 16 (NSP16) containing 2-O-methyltransferase and NSP14 through its N7 methyltransferase activity, which are essential for the replication of the viral genome as well as evading the hosts innate immunity. NSP10 acts as a crucial cofactor and stimulator of NSP14 and NSP16. To further understand the role of NSP10, we carried out a comprehensive analysis of >13 million globally collected whole-genome sequences (WGS) of SARS-CoV-2 obtained from the Global Initiative Sharing All Influenza Data (GISAID) and compared it with the reference genome Wuhan/WIV04/2019 to identify all currently known variants in NSP10. T12I, T102I, and A104V in NSP10 have been identified as the three most frequent variants and characterized using X-ray crystallography, biophysical assays and enhanced sampling simulations. In contrast to other proteins such as spike and NSP6, NSP10 is significantly less prone to mutation due to its crucial role in replication. The functional effects of the variants were examined for their impact on the binding affinity and stability of both NSP14-NSP10 and NSP16-NSP10 complexes. These results highlight the limited changes induced by variant evolution in NSP10 and reflect on the critical roles NSP10 plays during the SARS-CoV-2 life cycle. These results also indicate that there is limited capacity for the virus to overcome inhibitors targeting NSP10 via the generation of variants in inhibitor binding pockets.\n\nSignificance StatementThe SARS-CoV-2 proteins have constantly been evolving. These variants assist the virus to survive, adapt and evade the host immune responses. While the main focus has been on structural proteins like Spike, there is very limited structural and functional information on the effects of emerging mutations on other essential non-structural viral proteins. One such protein is NSP10, an essential cofactor for NSP14 and NSP16. This study demonstrates that NSP10 is more resistant to genetic variations than other SARS-CoV-2 non-structural proteins and that the presence of mutations conserve structural and dynamic changes in NSP10. The effects of naturally occurring mutations reflect the evolutionary relationship between structurally conserved essential cofactors, their function and the role they play in the survival of the virus.",
+    "rel_abs": "The coronavirus SARS-CoV-2 protects its RNA from being recognized by host immune responses by methylation of its 5' end, also known as capping. This process is carried out by two enzymes, non-structural protein 16 (NSP16) containing 2'-O-methyltransferase and NSP14 through its N7 methyltransferase activity, which are essential for the replication of the viral genome as well as evading the host's innate immunity. NSP10 acts as a crucial cofactor and stimulator of NSP14 and NSP16. To further understand the role of NSP10, we carried out a comprehensive analysis of >13 million globally collected whole-genome sequences (WGS) of SARS-CoV-2 obtained from the Global Initiative Sharing All Influenza Data (GISAID) and compared it with the reference genome Wuhan/WIV04/2019 to identify all currently known variants in NSP10. T12I, T102I, and A104V in NSP10 have been identified as the three most frequent variants and characterized using X-ray crystallography, biophysical assays, and enhanced sampling simulations. In contrast to other proteins such as spike and NSP6, NSP10 is significantly less prone to mutation due to its crucial role in replication. The functional effects of the variants were examined for their impact on the binding affinity and stability of both NSP14-NSP10 and NSP16-NSP10 complexes. These results highlight the limited changes induced by variant evolution in NSP10 and reflect on the critical roles NSP10 plays during the SARS-CoV-2 life cycle. These results also indicate that there is limited capacity for the virus to overcome inhibitors targeting NSP10 via the generation of variants in inhibitor binding pockets.",
     "rel_num_authors": 11,
     "rel_authors": [
       {
@@ -106436,99 +107279,79 @@
     "category": "pharmacology and toxicology"
   },
   {
-    "rel_doi": "10.1101/2022.12.25.521784",
-    "rel_title": "A ferritin-based COVID-19 nanoparticle vaccine that elicits robust, durable, broad-spectrum neutralizing antisera in non-human primates",
-    "rel_date": "2022-12-26",
+    "rel_doi": "10.1101/2022.12.22.521696",
+    "rel_title": "Omicron BA.5 infects human brain organoids and is neuroinvasive and lethal in K18-hACE2 mice",
+    "rel_date": "2022-12-25",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.25.521784",
-    "rel_abs": "While the rapid development of COVID-19 vaccines has been a scientific triumph, the need remains for a globally available vaccine that provides longer-lasting immunity against present and future SARS-CoV-2 variants of concern (VOCs). Here, we describe DCFHP, a ferritin-based, protein-nanoparticle vaccine candidate that, when formulated with aluminum hydroxide as the sole adjuvant (DCFHP-alum), elicits potent and durable neutralizing antisera in non-human primates against known VOCs, including Omicron BQ.1, as well as against SARS-CoV-1. Following a booster [~]one year after the initial immunization, DCFHP-alum elicits a robust anamnestic response. To enable global accessibility, we generated a cell line that can enable production of thousands of vaccine doses per liter of cell culture and show that DCFHP-alum maintains potency for at least 14 days at temperatures exceeding standard room temperature. DCFHP-alum has potential as a once-yearly booster vaccine, and as a primary vaccine for pediatric use including in infants.",
-    "rel_num_authors": 20,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.22.521696",
+    "rel_abs": "A frequently repeated premise is that viruses evolve to become less pathogenic. This appears also to be true for SARS-CoV-2, although the increased level of immunity in human populations makes it difficult to distinguish between reduced intrinsic pathogenicity and increasing protective immunity. The reduced pathogenicity of the omicron BA.1 sub-lineage compared to earlier variants is well described and appears to be due to reduced utilization of TMPRRS2. That this reduced pathogenicity remains true for omicron BA.5 was recently reported. In sharp contrast, we show that a BA.5 isolate was significantly more pathogenic in K18-hACE2 mice than a BA.1 isolate, with BA.5 infection showing increased neurovirulence, encephalitis and mortality, similar to that seen for an original ancestral isolate. BA.5 also infected human cortical brain organoids to a greater extent than a BA.1 and original ancestral isolate. Neurons were the target of infection, with increasing evidence of neuron infection in COVID-19 patients. These results argue that while omicron virus may be associated with reduced respiratory symptoms, BA.5 shows increased neurovirulence compared to earlier omicron sub-variants.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Payton A.-B. Weidenbacher",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Mrinmoy Sanyal",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Natalia Friedland",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Shaogeng Tang",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Prabhu S Arunachalam",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Mengyun Hu",
-        "author_inst": "Stanford University"
+        "author_name": "Romal Stewart",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Ozan S. Kumru",
-        "author_inst": "University of Kansas"
+        "author_name": "Sevannah A Ellis",
+        "author_inst": "Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia"
       },
       {
-        "author_name": "Mary Kate Morris",
-        "author_inst": "California Department of Public Health"
+        "author_name": "Kexin Yan",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Jane Fontenot",
-        "author_inst": "University of Louisiana at Lafayette"
+        "author_name": "Troy Dumenil",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Lisa Shirreff",
-        "author_inst": "University of Louisiana at Lafayette"
+        "author_name": "Bing Tang",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Jonathan Do",
-        "author_inst": "Stanford University"
+        "author_name": "Wilson Nguyen",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Ya-Chen Cheng",
-        "author_inst": "Stanford University"
+        "author_name": "Cameron R Bishop",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Gayathri Vasudevan",
-        "author_inst": "International AIDS Vaccine Initiative"
+        "author_name": "Thibaut Larcher",
+        "author_inst": "INRAE, Oniris, PAnTher, APEX, Nantes, France"
       },
       {
-        "author_name": "Mark B. Feinberg",
-        "author_inst": "International AIDS Vaccine Initiative"
+        "author_name": "Rhys Parry",
+        "author_inst": "University of Queensland"
       },
       {
-        "author_name": "Francois J. Villinger",
-        "author_inst": "University of Louisiana at Lafayette"
+        "author_name": "Robert K P Sullivan",
+        "author_inst": "Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia"
       },
       {
-        "author_name": "Carl Hanson",
-        "author_inst": "California Department of Public Health"
+        "author_name": "Mary Lor",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Sangeeta B. Joshi",
-        "author_inst": "University of Kansas"
+        "author_name": "Alexander A Khromykh",
+        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland Brisbane QLD Australia."
       },
       {
-        "author_name": "David B. Volkin",
-        "author_inst": "University of Kansas"
+        "author_name": "Frederic A Meunier",
+        "author_inst": "Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia."
       },
       {
-        "author_name": "Bali Pulendran",
-        "author_inst": "Stanford University"
+        "author_name": "Daniel J Rawle",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       },
       {
-        "author_name": "Peter S. Kim",
-        "author_inst": "Stanford University"
+        "author_name": "Andreas Suhrbier",
+        "author_inst": "QIMR Berghofer Medical Research Institute"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.12.21.22283753",
@@ -108170,21 +108993,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.12.21.521431",
-    "rel_title": "Mechanism of LLPS of SARS-CoV-2 N protein",
+    "rel_doi": "10.1101/2022.12.20.521221",
+    "rel_title": "Structure adaptation in Omicron SARS-CoV-2/hACE2:Biophysical origins of evolutionary driving forces",
     "rel_date": "2022-12-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.21.521431",
-    "rel_abs": "SARS-CoV-2 nucleocapsid (N) protein with low mutation rate is the only structural protein not only functioning to package viral genomic RNA, but also manipulating the host-cell machineries, thus representing a key target for drug development. Recent discovery of its liquid-liquid phase separation (LLPS) not only sheds light on previously-unknown mechanisms underlying the host-SARS-CoV-2 interaction and viral life cycle, but most importantly opens up a new direction for developing anti-SARS-CoV-2 strategies/drugs. However, so far the high-resolution mechanism of LLPS of N protein still remains unknown because it is not amenable for high-resolution biophysical investigations. Here we systematically dissected N protein into differential combinations of domains followed by DIC and NMR characterization. We successfully identified N (1-249), which not only gives high-quality NMR spectra, but phase separates as the full-length N protein. The results together decode for the first time: 1) nucleic acid modulates LLPS by dynamic but specific interactions multivalently over both folded NTD/CTD and Arg/Lys residues within IDRs. 2) ATP, mysteriously with concentrations >mM in all living cells but absent in viruses, not only specifically binds NTD/CTD, but also Arg residues within IDRs with Kd of 2.8 mM. 3) ATP dissolves LLPS by competitively displacing nucleic acid from binding the protein. Therefore, ATP and nucleic acid interplay in modulating LLPS by specific competitions for binding over the highly overlapped binding sites. Our study deciphers the mechanism of LLPS of N protein, which is targetable by small molecules. ATP is not only emerging as a cellular factor controlling the host-SARS-CoV-2 interaction, but also provides a lead for developing anti-SARS-CoV-2 drugs efficient for different variants of SARS-CoV-2. Fundamentally, our results imply that the mechanisms of LLPS of IDR-containing proteins mediated by ATP and nucleic acids appear to be highly conserved from human to virus.",
-    "rel_num_authors": 1,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.20.521221",
+    "rel_abs": "Since its emergence, the Covid19 pandemic has been sustained by a series of transmission waves initiated by new variants of the SARS-CoV-2 virus. Some of these arise with higher transmissivity and/or increased disease severity. Here we use molecular dynamics simulations to examine the modulation of the fundamental interactions between the receptor binding domain (RBD) of the spike glycoprotein and the host cell receptor (human angiotensin-converting enzyme 2: hACE2) arising from Omicron variant mutations (BA.1 and BA.2) relative to the original wild type strain. We find significant structural differences in the complexes which overall bring the spike protein and its receptor into closer proximity. These are consistent with and attributed to the higher positive charge on the RBD conferred by BA.1 and BA.2 mutations relative to the wild type. However, further differences between sub-variants BA.1 and BA.2 (which have equivalent RBD charges) are also evident: Mutations affect interdomain interactions between the up-chain and its clockwise neighbor chain, resulting in enhanced flexibility for BA.2. Consequently, additional close contacts arise in BA.2 which include binding to hACE2 by a second spike protein monomer, in addition to the up-chain - a motif not found in BA.1. Finally, the mechanism by which the glycans stabilize the up state of the Spike protein differs for the wild type and the Omicrons. We also found the glycan on N90 of hACE2 turns from inhibiting, to facilitating the binding to Omicron spike protein. These structural and electrostatic differences offer further insight into the mechanisms by which viral mutations modulate host cell binding and provide a biophysical basis for evolutionary driving forces.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Jianxing Song",
-        "author_inst": "National University of Singapore"
+        "author_name": "Ya-Wen Hsiao",
+        "author_inst": "The Hartree Centre, Daresbury Laboratory, STFC"
+      },
+      {
+        "author_name": "Tseden Taddese",
+        "author_inst": "The Hartree Centre, Daresbury Lab, STFC"
+      },
+      {
+        "author_name": "Guadalupe Jimenez-Serratos",
+        "author_inst": "The Hartree Centre, Daresbury Lab, STFC"
+      },
+      {
+        "author_name": "David J Bray",
+        "author_inst": "The Hartree Centre, Daresbury Lab, STFC"
+      },
+      {
+        "author_name": "Jason Crain",
+        "author_inst": "IBM Research Europe; University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
     "category": "biophysics"
   },
@@ -109992,47 +110831,103 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.12.16.22283554",
-    "rel_title": "Comparison of the mucosal and systemic antibody responses in Covid-19 recovered patients with one dose of mRNA vaccine and unexposed subjects with three doses of mRNA vaccines",
+    "rel_doi": "10.1101/2022.12.15.22283474",
+    "rel_title": "Bacillus Calmette-Guerin vaccine to reduce COVID-19 infections and hospitalisations in healthcare workers: a living systematic review and prospective ALL-IN meta-analysis of individual participant data from randomised controlled trials",
     "rel_date": "2022-12-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.16.22283554",
-    "rel_abs": "BackgroundImmunity acquired from natural SARS-CoV-2 infection and vaccine wanes overtime. This longitudinal prospective study compared the effect of a booster vaccine (BNT162b2) in inducing the mucosal (nasal) and serological antibody between Covid-19 recovered patients and healthy unexposed subjects with two dose of mRNA vaccine (vaccine-only group).\n\nMethodEleven recovered patients and eleven gender-and-age matched unexposed subjects who had mRNA vaccines were recruited. The SARS-CoV-2 spike 1 (S1) protein specific IgA, IgG and the ACE2 binding inhibition to the ancestral SARS-CoV-2 and omicron (BA.1) variant receptor binding domain were measured in their nasal epithelial lining fluid and plasma.\n\nResultIn the recovered group, the booster expanded the nasal IgA dominancy inherited from natural infection to IgA and IgG. They also had a higher S1-specific nasal and plasma IgA and IgG levels with a better inhibition against the omicron BA.1 variant and ancestral SARS-CoV-2 when compared with vaccine-only subjects. The nasal S1-specific IgA induced by natural infection lasted longer than those induced by vaccines while the plasma antibodies of both groups maintained at a high level for at least 21 weeks after booster.\n\nConclusionThe booster benefited all subjects to obtain neutralizing antibody (NAb) against omicron BA.1 variant in plasma while only the Covid-19 recovered subjects had an extra enrichment in nasal NAb against Omicron BA.1 variant.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22283474",
+    "rel_abs": "BACKGROUNDThe objective is to determine the impact of the Bacillus Calmette-Guerin (BCG) vaccine compared to placebo or no vaccine on COVID-19 infections and hospitalisations in healthcare workers. We are using a living and prospective approach to Individual-Participant-Data (IPD) meta-analysis of ongoing studies based on the Anytime Live and Leading Interim (ALL-IN) meta-analysis statistical methodology.\n\nMETHODSPlanned and ongoing randomised controlled trials were identified from trial registries and by snowballing (final elicitation: Oct 3 2022). The methodology was specified prospectively - with no trial results available - for trial inclusion as well as statistical analysis. Inclusion decisions were made collaboratively based on a risk-of-bias assessment by an external protocol review committee (Cochrane risk-of-bias tool adjusted for use on protocols), expected homogeneity in treatment effect, and agreement with the predetermined event definitions. The co-primary endpoints were incidence of COVID-19 infection and COVID-19-related hospital admission. Accumulating IPD from included trials was analysed sequentially using the exact e-value logrank test (at level  = 0.5% for infections and level  = 4.5% for hospitalisations) and anytime-valid 95%-confidence intervals (CIs) for the hazard ratio (HR) for a predetermined fixed-effects approach to meta-analysis (no measures of statistical heterogeneity). Infections were included if demonstrated by PCR tests, antigen tests or suggestive lung CTs. Participants were censored at date of first COVID-19-specific vaccination and two-stage analyses were performed in calendar time, with a stratification factor per trial.\n\nRESULTSSix trials were included in the primary analysis with 4 433 participants in total. The e-values showed no evidence of a favourable effect of minimal clinically relevance (HR < 0.8) in comparison to the null (HR = 1) for COVID-19 infections, nor for COVID-19 hospitalisations (HR < 0.7 vs HR = 1). COVID-19 infection was observed in 251 participants receiving BCG and 244 participants not receiving BCG, HR 1.02 (anytime-valid 95%-CI 0.78-1.35). COVID-19 hospitalisations were observed in 13 participants receiving BCG and 7 not receiving BCG, resulting in an uninformative estimate (HR 1.88; anytime-valid 95%-CI 0.26-13.40).\n\nDISCUSSIONIt is highly unlikely that BCG has a clinically relevant effect on COVID-19 infections in healthcare workers. With only limited observations, no conclusion could be drawn for COVID-19 related hospitalisation. Due to the nature of ALL-IN meta-analysis, emerging data from new trials can be included without violating type-I error rates or interval coverage. We intend to keep this meta-analysis alive and up-to-date, as more trials report. For COVID-19 related hospitalisations, we do not expect enough future observations for a meaningful analysis. For BCG-mediated protection against COVID-19 infections, on the other hand, more observations could lead to a more precise estimate that concludes the meta-analysis for futility, meaning that the current interval excludes the HR of 0.8 predetermined as effect size of minimal clinical relevance.\n\nOTHERNo external funding. Preregistered at PROSPERO: CRD42021213069.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Shaojun Liu",
-        "author_inst": "Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong"
+        "author_name": "Judith ter Schure",
+        "author_inst": "Amsterdam UMC/CWI, Amsterdam, the Netherlands"
       },
       {
-        "author_name": "Joseph GS Tsun",
-        "author_inst": "Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong"
+        "author_name": "Alexander Ly",
+        "author_inst": "University of Amsterdam/CWI, Amsterdam, the Netherlands"
       },
       {
-        "author_name": "Genevieve PG Fung",
-        "author_inst": "Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong"
+        "author_name": "Lisa Belin",
+        "author_inst": "Sorbonne Universite, INSERM, Institut Pierre Louis dEpidemiologie et de Santee Publique, AP-HP, Hoopital Pitiee Salpetriere, Deepartement de Santee Publique, Un"
       },
       {
-        "author_name": "Grace CY Lui",
-        "author_inst": "Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong"
+        "author_name": "Christine S. Benn",
+        "author_inst": "Bandim Health Project, Open Patient Data Explorative Network, Department of Clinical Research and Danish Institute for Advanced Study, University of Southern De"
       },
       {
-        "author_name": "Kathy YY Chan",
-        "author_inst": "Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong"
+        "author_name": "Marc J.M. Bonten",
+        "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands"
       },
       {
-        "author_name": "Paul KS Chan",
-        "author_inst": "Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong"
+        "author_name": "Jeffrey D. Cirillo",
+        "author_inst": "Center for Airborne Pathogen Research and Imaging, Texas A and M School of Medicine, Bryan, TX 77807"
       },
       {
-        "author_name": "Renee WY Chan",
-        "author_inst": "Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong; CUHK-Hong Kong Hub of Paediatric Excellence, The Chinese University of Hong"
+        "author_name": "Johanna A.A. Damen",
+        "author_inst": "Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands"
+      },
+      {
+        "author_name": "Ines Fronteira",
+        "author_inst": "Global Health and Tropical Medicine, Institute of Hygiene and Tropical Medicine, Universidade NOVA de Lisboa"
+      },
+      {
+        "author_name": "Kelly D. Hendriks",
+        "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands"
+      },
+      {
+        "author_name": "Anna Paula Junqueira-Kipnis",
+        "author_inst": "Federal University of Goias, Institute of Tropical Medicine and Public Health, Goiania, Brazil"
+      },
+      {
+        "author_name": "Andre Kipnis",
+        "author_inst": "Federal University of Goias, Institute of Tropical Medicine and Public Health, Goiania, Brazil"
+      },
+      {
+        "author_name": "Odile Launay",
+        "author_inst": "AP-HP"
+      },
+      {
+        "author_name": "Jose Euberto Mendez-Reyes",
+        "author_inst": "Global and Immigrant Health, Baylor College of Medicine, Houston, TX"
+      },
+      {
+        "author_name": "Judit Moldvay",
+        "author_inst": "National Koranyi Institute of Pulmonology, Budapest, Hungary"
+      },
+      {
+        "author_name": "Mihai G. Netea",
+        "author_inst": "Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands"
+      },
+      {
+        "author_name": "Sebastian Nielsen",
+        "author_inst": "Bandim Health Project, Open Patient Data Explorative Network, Department of Clinical Research, University of Southern Denmark, Denmark"
+      },
+      {
+        "author_name": "Caryn M. Upton",
+        "author_inst": "TASK, Parow, Cape Town, South Africa"
+      },
+      {
+        "author_name": "Gerben van den Hoogen",
+        "author_inst": "TASK, Parow, Cape Town, South Africa"
+      },
+      {
+        "author_name": "Jesper M. Weehuizen",
+        "author_inst": "Department of Internal Medicine and Infectious Diseases, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands"
+      },
+      {
+        "author_name": "Peter D. Grunwald",
+        "author_inst": "CWI, Amsterdam, the Netherlands"
+      },
+      {
+        "author_name": "Henri van Werkhoven",
+        "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.12.18.22283593",
@@ -111934,53 +112829,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.12.15.22282988",
-    "rel_title": "Streptococcus pneumoniae re-emerges as a cause of community-acquired pneumonia, including frequent co-infection with SARS-CoV-2, in Germany, 2021",
+    "rel_doi": "10.1101/2022.12.15.22283522",
+    "rel_title": "Estimating the transmission dynamics of Omicron in Beijing, November to December 2022",
     "rel_date": "2022-12-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22282988",
-    "rel_abs": "BackgroundThe COVID-19 pandemic and the associated containment measures had a substantial impact on pathogens causing pneumonia in adults. The objective of this study was to determine the etiology of hospitalized community-acquired pneumonia (CAP) among adults in Germany in 2021, the second year of the COVID-19 pandemic.\n\nMethodsSince January 2021, this on-going, prospective, population-based surveillances study enrolled adult patients with clinically and radiographically confirmed CAP at three hospitals in Thuringia, Germany, serving a population of approximately 280,000. Urine samples were collected from patients and tested for S. pneumoniae using the pneumococcal urinary antigen test (PUAT, BinaxNOW S. pneumoniae) and the proprietary serotype-specific urinary antigen detection (UAD) assays. Nasopharyngeal swabs were tested for 10 respiratory viruses by PCR.\n\nResultsA total of 797 patients were enrolled, of whom 760 were included in the analysis. The median age of patients with CAP was 67 years; in-hospital case-fatality rate was 8.4%. A respiratory pathogen was detected in 553 (72.8%) patients. The most common pathogen was SARS-CoV-2 (n=498, 68.2%), followed by S. pneumoniae (n=40, 6.4%). Serotypes contained in the 13-valent, 15-valent and 20-valent pneumococcal conjugate vaccine were detected in 42.5%, 45.0%, and 70.0% of the pneumococcal CAP cases. Between the first and second half of 2021, the proportion of CAP cases associated with S. pneumoniae increased from 1.1% to 5.6% in patients aged 18-59 years and from 2.5% to 12.4% in those aged [&ge;]60 years; coinfection of SARS-CoV-2 and S. pneumoniae among COVID-19 patients increased from 0.7% (2/283 cases) to 6.0% (13/215) in patients aged [&ge;]18 years, and from 1.0% (2/195) to 8.7% (11/127) in those aged [&ge;]60 years.\n\nConclusionIn Germany, the proportion of CAP cases associated with S. pneumoniae rebounded to a near-pandemic level in the second half of 2021 and many pneumococcal infections occurred in patients with COVID-19. Vaccination uptake against respiratory pathogens, including S. pneumoniae, should be strengthened.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22283522",
+    "rel_abs": "We tracked the effective reproduction number Rt of SARS-CoV-2 Omicron BF.7 in Beijing in November - December 2022 by fitting a transmission dynamic model parameterized with real-time mobility data to (i) the daily number of new symptomatic cases on November 1-11 (when the zero-covid interventions were still strictly enforced) and (ii) the proportion of individuals who participated in online polls on December 10-22 and self-reported to have been previously test-positive since November 1. After the announcement of \"20 measures\", we estimated that Rt increased to 3.44 (95% CrI: 2.82 - 4.14) on November 18 and the infection incidence peaked on December 11. The cumulative infection attack rate (i.e. the proportion of population who have been infected since November 1) was 43.1% (95% CrI: 25.6 - 60.9) on December 14 and 75.7% (95% CrI: 60.7 - 84.4) on December 22. Surveillance programmes should be rapidly set up to monitor the evolving epidemiology and evolution of SARS-CoV-2 across China.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Juliane Ankert",
-        "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany"
-      },
-      {
-        "author_name": "Stefan Hagel",
-        "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany"
-      },
-      {
-        "author_name": "Claudia Schwarz",
-        "author_inst": "Vaccines Medical Development, Scientific and Clinical Affairs, Pfizer, Collegeville, PA, USA"
-      },
-      {
-        "author_name": "Kaijie Pan",
-        "author_inst": "Vaccines Medical Development, Scientific and Clinical Affairs, Pfizer, Collegeville, PA, USA"
-      },
-      {
-        "author_name": "Liz Wang",
-        "author_inst": "Vaccines Medical Development, Scientific and Clinical Affairs, Pfizer, Collegeville, PA, USA"
+        "author_name": "Kathy Leung",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Christof von Eiff",
-        "author_inst": "Pfizer Pharma GmbH, Berlin, Germany"
+        "author_name": "Eric Lau",
+        "author_inst": "University of Hong Kong"
       },
       {
-        "author_name": "Bradford D. Gessner",
-        "author_inst": "Vaccines Medical Development, Scientific and Clinical Affairs, Pfizer, Collegeville, PA, USA"
+        "author_name": "Carlos Wong",
+        "author_inst": "University of Hong Kong"
       },
       {
-        "author_name": "Christian Theilacker",
-        "author_inst": "Vaccines Medical Development, Scientific and Clinical Affairs, Pfizer, Collegeville, PA, USA"
+        "author_name": "Gabriel M Leung",
+        "author_inst": "The University of Hong Kong"
       },
       {
-        "author_name": "Mathias W. Pletz",
-        "author_inst": "Institute for Infectious Diseases and Infection Control, Jena University Hospital, Friedrich Schiller University Jena, Jena, Germany"
+        "author_name": "Joseph Wu",
+        "author_inst": "The University of Hong Kong"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -112234,7 +113113,7 @@
     "rel_date": "2022-12-16",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.16.22283582",
-    "rel_abs": "The omicron variant is thought to cause less olfactory dysfunction than previous variants of SARS-CoV-2, but the reported prevalence differs greatly between populations and studies. Our systematic review and meta-analysis provide information about regional differences in prevalence as well as an estimate of the global prevalence of olfactory dysfunction based on 41 studies reporting on nearly 600,000 patients infected with the omicron variant. Our estimate of the omicron-induced prevalence of olfactory dysfunction in populations of European ancestry is 11.6%, while it is significantly lower in all other populations, at 2.9-5.4%. When ethnic differences and population sizes are taken into account, the global prevalence of omicron-induced hyposmia in adults is estimated at 5.2%. Omicrons effect on olfaction is 3-4fold lower than that of the alpha or delta variant, according to previous meta-analyses and our analysis of studies that directly compared prevalence of olfactory dysfunction between omicron and previous variants. The profile of prevalence differences between ethnicities mirrors the results of a recent genome-wide association study that implicated a gene locus encoding an odorant-metabolizing enzyme, UDP glycosyltransferase, to be linked to the extent of COVID-related loss of smell. Our analysis is consistent with the hypothesis that this enzyme contributes to the observed population differences.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC=\"FIGDIR/small/22283582v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (47K):\norg.highwire.dtl.DTLVardef@10e64b9org.highwire.dtl.DTLVardef@1f6b14dorg.highwire.dtl.DTLVardef@f25810org.highwire.dtl.DTLVardef@739877_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
+    "rel_abs": "The omicron variant is thought to cause less olfactory dysfunction than previous variants of SARS-CoV-2, but the reported prevalence differs greatly between populations and studies. Our systematic review and meta-analysis provide information about regional differences in prevalence as well as an estimate of the global prevalence of olfactory dysfunction based on 41 studies reporting on nearly 600,000 patients infected with the omicron variant. Our estimate of the omicron-induced prevalence of olfactory dysfunction in populations of European ancestry is 11.6%, while it is significantly lower in all other populations, at 2.9-5.4%. When ethnic differences and population sizes are taken into account, the global prevalence of omicron-induced hyposmia in adults is estimated at 5.2%. Omicrons effect on olfaction is 3-4fold lower than that of the alpha or delta variant, according to previous meta-analyses and our analysis of studies that directly compared prevalence of olfactory dysfunction between omicron and previous variants. The profile of prevalence differences between ethnicities mirrors the results of a recent genome-wide association study that implicated a gene locus encoding an odorant-metabolizing enzyme, UDP glycosyltransferase, to be linked to the extent of COVID-related loss of smell. Our analysis is consistent with the hypothesis that this enzyme contributes to the observed population differences.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC=\"FIGDIR/small/22283582v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (47K):\norg.highwire.dtl.DTLVardef@bfb960org.highwire.dtl.DTLVardef@1238c95org.highwire.dtl.DTLVardef@e2ab9corg.highwire.dtl.DTLVardef@1709145_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
     "rel_num_authors": 2,
     "rel_authors": [
       {
@@ -113948,75 +114827,27 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2022.12.12.22283367",
-    "rel_title": "Milk antibody response after 3rd dose of COVID-19 mRNA vaccine and SARS-CoV-2 breakthrough infection and implications for infant protection",
-    "rel_date": "2022-12-14",
+    "rel_doi": "10.1101/2022.12.12.22283388",
+    "rel_title": "The Impact of COVID-19 Pandemic on Mental Health: A Scoping Review",
+    "rel_date": "2022-12-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.12.22283367",
-    "rel_abs": "Anti-SARS-CoV-2 antibodies have been found in human-milk after COVID-19 infection and vaccination. However, little is known about their persistence in milk after booster vaccination and breakthrough infection. In this study, human-milk, saliva and blood samples were collected from 33 lactating individuals before and after mRNA-based vaccination and COVID-19 breakthrough infections. Antibody levels were measured using ELISA and symptoms were assessed using questionnaires. Evaluation of maternal and infant symptomatology revealed that infected mothers reported more symptoms than vaccinated mothers. We found that after vaccination, human-milk anti-SARS-CoV-2 antibodies persisted for up to 8 months. In addition, distinct patterns of human milk IgA and IgG production we observed after breakthrough infection compared to 3-dose vaccination series alone, indicating a differential central and mucosal immune profiles in hybrid compared with vaccine-induced immunity. To investigate passively-derived milk antibody protection in infants, we examined the persistence of these antibodies in infant saliva after breastfeeding. We found that IgA was more abundant in infant saliva compared to IgG and persist in infant saliva longer after feeding. Our results delineate the differences in milk antibody response to vaccination as compared to breakthrough infection and emphasize the importance of improving the secretion of IgA antibodies to human milk after vaccination to improve the protection of breastfeeding infants.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.12.22283388",
+    "rel_abs": "BackgroundThis scoping review assessed the COVID-19 impacts on mental health and associated risk factors.\n\nMethodsA systematic literature search for relevant articles published in the period March 2020 to July 2022, was conducted in the APA PsychInfo, JBI Evidence Synthesis, Epistemonikos, PubMed, and Cochrane databases.\n\nResultsA total of 72 studies met the inclusion criteria. Results showed that the commonly used mental health assessment tools were the Patient Health Questionnaire (41.7%), Generalized Anxiety Disorder Scale (36%), 21-item Depression, Anxiety, and Stress (13.9%), Impact of Event Scale (12.5%), Pittsburgh Sleep Quality Index (9.7%), Symptom Checklist and the General Health Questionnaire (6.9% each). The prevalence rate of depression ranged from 5-76.5%, 5.6-80.5% for anxiety, 9.1-65% for Post-Traumatic Stress Disorder, 8.3-61.7% for sleep disorders, 4.9-70.1% for stress, 7-71.5% for psychological distress, and 21.4-69.3% for general mental health conditions. The major risks included female gender, healthcare-related/frontline jobs, isolation/quarantine, poverty, lower education, COVID-19 risk, age, commodities, mental illness history, negative psychology, and higher social media exposure. The incidence of mental disorders increased along with the increasing cases of COVID-19 and the corresponding government restrictions.\n\nConclusionStandard assessment tools were used for mental health assessment by the reviewed studies which were conducted during COVID-19. Mental health disorders like depression, anxiety, and stress increased during the COVID-19 pandemic and lockdowns. Various factors impacted the prevalence of mental health disorders. Policymakers need to provide social protective measures to improve coping capacities during critical health events to avoid negative impacts on the population. Further studies should investigate the effectiveness of interventions for reducing the prevalence and risk factors for mental health conditions during a public health challenge.\n\nBackground",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Yarden Golan",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Mikias Ilala",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Caryl Gay",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Soumya Hunagund",
-        "author_inst": "University of California San Francisco, California"
-      },
-      {
-        "author_name": "Christine Y. Lin",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Arianna G. Cassidy",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Unurzul Jigmeddagva",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Lin Li",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Nida Ozarslan",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Ifeyinwa V. Asiodu",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Nadav Ahituv",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Valerie J. Flaherman",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Stephanie L. Gaw",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Blessing  O. Josiah",
+        "author_inst": "Turks and Caicos Islands Community College"
       },
       {
-        "author_name": "Mary Prahl",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "France Ncube",
+        "author_inst": "UNICAF University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.12.12.22283336",
@@ -115753,71 +116584,43 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.12.07.22283234",
-    "rel_title": "Machine learning identifies a COVID-19-specific phenotype in university students using a mental health app",
+    "rel_doi": "10.1101/2022.12.11.520008",
+    "rel_title": "Using machine learning to detect coronaviruses potentially infectious to humans",
     "rel_date": "2022-12-12",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.07.22283234",
-    "rel_abs": "Advances in smartphone technology have allowed people to access mental healthcare via digital apps from wherever and whenever they choose. University students experience a high burden of mental health concerns. Although these apps improve mental health symptoms, user engagement has remained low. Studies have shown that users can be subgrouped based on unique characteristics that just-in-time adaptive interventions (JITAIs) can use to improve engagement. To date, however, no studies have examined the effect of the COVID-19 pandemic on these subgroups. Here, we use machine learning to examine user subgroup characteristics across three COVID-19-specific timepoints: during lockdown, immediately following lockdown, and three months after lockdown ended. We demonstrate that there are three unique subgroups of university students who access mental health apps. Two of these, with either higher or lower mental well-being, were defined by characteristics that were stable across COVID-19 timepoints. The third, situational well-being, had characteristics that were timepoint-dependent, suggesting that they are highly influenced by traumatic stressors and stressful situations. This subgroup also showed feelings and behaviours consistent with burnout. Overall, our findings clearly suggest that user subgroups are unique: they have different characteristics and therefore likely have different mental healthcare goals. Our findings also highlight the importance of including questions and additional interventions targeting traumatic stress(ors), reason(s) for use, and burnout in JITAI-style mental health apps to improve engagement.",
-    "rel_num_authors": 13,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.11.520008",
+    "rel_abs": "Establishing the host range for novel viruses remains a challenge. Here, we address the challenge of identifying non-human animal coronaviruses that may infect humans by creating an artificial neural network model that learns from the binding of the spike protein of alpha and beta coronaviruses to their host receptor. The proposed method produces a human-Binding Potential (h-BiP) score that distinguishes, with high accuracy, the binding potential among human coronaviruses. Two viruses, previously unknown to bind human receptors, were identified: Bat coronavirus BtCoV/133/2005 (a MERS related virus) and Rhinolophus affinis coronavirus isolate LYRa3 a SARS related virus. We further analyze the binding properties of these viruses using molecular dynamics. To test whether this model can be used for surveillance of novel coronaviruses, we re-trained the model on a set that excludes SARS-COV-2 viral sequences. The results predict the binding of SARS-CoV-2 with a human receptor, indicating that machine learning methods are an excellent tool for the prediction of host expansion events.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Artur Shvetcov",
-        "author_inst": "Black Dog Institute"
-      },
-      {
-        "author_name": "Alexis Whitton",
-        "author_inst": "Black Dog Institute"
-      },
-      {
-        "author_name": "Suranga Kasturi",
-        "author_inst": "Black Dog Institute"
-      },
-      {
-        "author_name": "Wu-Yi Zheng",
-        "author_inst": "Black Dog Institute"
-      },
-      {
-        "author_name": "Joanne Beames",
-        "author_inst": "Black Dog Institute"
-      },
-      {
-        "author_name": "Omar Ibrahim",
-        "author_inst": "Black Dog Institute"
-      },
-      {
-        "author_name": "Jin Han",
-        "author_inst": "Black Dog Institute"
-      },
-      {
-        "author_name": "Leonard Hoon",
-        "author_inst": "Deakin University"
+        "author_name": "Georgina Gonzalez-Isunza",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Kon Mouzakis",
-        "author_inst": "Deakin University"
+        "author_name": "Muhammad- Zaki Jawaid",
+        "author_inst": "University of California Davis"
       },
       {
-        "author_name": "Sunil Gupta",
-        "author_inst": "Deakin University"
+        "author_name": "Pengyu Liu",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Svetha Venkatesh",
-        "author_inst": "Deakin University"
+        "author_name": "Daniel L Cox",
+        "author_inst": "UC Davis"
       },
       {
-        "author_name": "Helen Christensen",
-        "author_inst": "Black Dog Institute"
+        "author_name": "Mariel Vazquez",
+        "author_inst": "University of California, Davis"
       },
       {
-        "author_name": "Jill Newby",
-        "author_inst": "Black Dog Institute"
+        "author_name": "Javier Arsuaga",
+        "author_inst": "University of California, Davis"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.12.10.518819",
@@ -117607,61 +118410,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.12.06.519322",
-    "rel_title": "A Binary RNA and DNA Self-Amplifying Platform for Next Generation Vaccines and Therapeutics",
+    "rel_doi": "10.1101/2022.12.07.519460",
+    "rel_title": "Reduced SARS-CoV-2 mRNA vaccine immunogenicity and protection in mice with diet-induced obesity and insulin resistance.",
     "rel_date": "2022-12-07",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.06.519322",
-    "rel_abs": "Conventional mRNA-based vaccines were instrumental in lowering the burden of the pandemic on healthcare systems and in reducing mortality. However, such first-generation vaccines have significant weaknesses. Here, we describe a high-performance binary recombinant vectoral platform offering the flexibility to be used as a self-amplifying mRNA or a self-amplifying DNA. Both formats drive long-lasting expression and actuate robust antibody responses against SAR-CoV-2 spike, and neither format require encapsulation with lipid nanoparticles (LNP) in the generation immune responses. The platform combines the power of conventional mRNA with the low-dosage of self-amplifying vectors together with the simplicity, rapid creation, ease of storage, and convenience of distribution of plasmid DNA vectors. This platform promises to pave the way for more effective, less expensive, and truly democratized vaccines and therapeutics.\n\nOne-Sentence SummaryGemini: a versatile platform that improves on existing vaccine formats in terms of effectiveness, manufacturing, distribution, and cost.",
-    "rel_num_authors": 12,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.07.519460",
+    "rel_abs": "BackgroundObesity and Type 2 Diabetes Mellitus (T2DM) are associated with an increased risk of severe outcomes from infectious diseases, including COVID-19. These conditions are also associated with distinct responses to immunization, including an impaired response to widely used SARS-CoV-2 mRNA vaccines.\n\nObjectiveTo establish a connection between reduced immunization efficacy via modeling the effects of metabolic diseases on vaccine immunogenicity that is essential for the development of more effective vaccines for this distinct vulnerable population.\n\nMethodsWe utilized a murine model of diet-induced obesity and insulin resistance to model the effects of comorbid T2DM and obesity on vaccine immunogenicity and protection.\n\nResultsMice fed a high-fat diet (HFD) developed obesity, hyperinsulinemia, and glucose intolerance. Relative to mice fed a normal diet (ND), HFD mice vaccinated with a SARS-CoV-2 mRNA vaccine exhibited significantly lower anti-spike IgG titers, predominantly in the IgG2c subclass, associated with a lower type 1 response, along with a 3.83-fold decrease in neutralizing titers. Furthermore, enhanced vaccine-induced spike-specific CD8+ T cell activation and protection from lung infection against SARS-CoV-2 challenge were seen only in ND mice but not in HFD mice.\n\nConclusionWe demonstrate impaired immunity following SARS-CoV-2 mRNA immunization in a murine model of comorbid T2DM and obesity, supporting the need for further research into the basis for impaired anti-SARS-CoV-2 immunity in T2DM and investigation of novel approaches to enhance vaccine immunogenicity among those with metabolic diseases.\n\nCapsule summaryObesity and type 2 diabetes impair SARS-CoV-2 mRNA vaccine efficacy in a murine model.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Wilfred Jefferies",
-        "author_inst": "University of British Columbia"
-      },
-      {
-        "author_name": "Kyung Bok Choi",
-        "author_inst": "University of British Columbia"
-      },
-      {
-        "author_name": "Paolo Ribeca",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Suresh Kari",
-        "author_inst": "University of British Columbia"
-      },
-      {
-        "author_name": "Jay Young",
-        "author_inst": "University of British Columbia"
-      },
-      {
-        "author_name": "Elizabeth Hui",
-        "author_inst": "University of British Columbia"
-      },
-      {
-        "author_name": "Simon Yong Qi",
-        "author_inst": "University of British Columbia"
+        "author_name": "Marisa E. McGrath",
+        "author_inst": "University of Maryland School of Medicine"
       },
       {
-        "author_name": "Emmanuel Garrosvillas",
-        "author_inst": "University of British Columbia"
+        "author_name": "Carly Dillen",
+        "author_inst": "University of Maryland School of Medicine"
       },
       {
-        "author_name": "Pamela Lincez",
-        "author_inst": "University of British Columbia"
+        "author_name": "Hyuk-Soo Seo",
+        "author_inst": "Dana-Farber Cancer Institute"
       },
       {
-        "author_name": "Tracy Welch",
-        "author_inst": "University of British Columbia"
+        "author_name": "Sirano Dhe-Paganon",
+        "author_inst": "Dana-Farber Cancer Institute"
       },
       {
-        "author_name": "Iryna Saranchova",
-        "author_inst": "University of British Columbia"
+        "author_name": "Robert K. Ernst",
+        "author_inst": "University of Maryland School of Dentistry"
       },
       {
-        "author_name": "Cheryl G Pfeifer",
-        "author_inst": "University of British Columbia"
+        "author_name": "Matthew B. Frieman",
+        "author_inst": "University of Maryland School of Medicine"
       }
     ],
     "version": "1",
@@ -119289,57 +120068,37 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.12.03.518956",
-    "rel_title": "Bioinformatics techniques for efficient structure prediction of SARS-CoV-2 protein ORF7a via structure prediction approaches",
+    "rel_doi": "10.1101/2022.12.02.518937",
+    "rel_title": "Deep mutational scanning to predict antibody escape in SARS-CoV-2 Omicron subvariants",
     "rel_date": "2022-12-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.03.518956",
-    "rel_abs": "Protein is the building block for all organisms. Protein structure prediction is always a complicated task in the field of proteomics. DNA and protein databases can find the primary sequence of the peptide chain and even similar sequences in different proteins. Mainly, there are two methodologies based on the presence or absence of a template for Protein structure prediction. Template-based structure prediction (threading and homology modeling) and Template-free structure prediction (ab initio). Numerous web-based servers that either use templates or do not can help us forecast the structure of proteins. In this current study, ORF7a, a transmembrane protein of the SARS-coronavirus, is predicted using Phyre2, IntFOLD, and Robetta. The protein sequence is straightforwardly entered into the sequence bar on all three web servers. Their findings provided information on the domain, the region with the disorder, the global and local quality score, the predicted structure, and the estimated error plot. Our study presents the structural details of the SARS-CoV protein ORF7a. This immunomodulatory component binds to immune cells and induces severe inflammatory reactions.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.02.518937",
+    "rel_abs": "The major concern of COVID-19 therapeutic monoclonal antibodies is the loss of efficacy to continuously emerging SARS-CoV-2 variants. To predict the antibodies efficacy to the future Omicron subvariants, we conducted deep mutational scanning (DMS) encompassing all single mutations in the receptor binding domain of BA.2 strain. In case of bebtelovimab that preserves neutralization activity against BA.2 and BA.5, broad range of amino acid substitutions at K444, V445 and G446 and some substitutions at P499 and T500 were indicated to achieve the antibody escape. Among currently increasing subvariants, BA2.75 carrying G446S partly and XBB with V445P and BQ.1 with K444T completely evade the neutralization of bebtelovimab, consistent with the DMS results. DMS can comprehensively characterize the antibody escape for efficient and effective management of future variants.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Aleeza Kazmi",
-        "author_inst": "Shaheed Benazir Bhutto Women University"
-      },
-      {
-        "author_name": "Muhammad Kazim",
-        "author_inst": "Medical Officer, Tehsil Headquarter Hospital, Kallur Kot, Bhakkar, Punjab, Pakistan"
-      },
-      {
-        "author_name": "Faisal Aslam",
-        "author_inst": "Tehsil Headquarter Hospital, Ahmad Pur East, Bahawalpur, Punjab, Pakistan"
-      },
-      {
-        "author_name": "Syeda Mahreen-ul-Hassan Kazmi",
-        "author_inst": "Department of Microbiology, Shaheed Benazir Bhutto Women University (SBBWU), Peshawar, Pakistan"
-      },
-      {
-        "author_name": "Abdul Wahab",
-        "author_inst": "Shanghai Center for Plant Stress Biology, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China"
-      },
-      {
-        "author_name": "Rafid Magid Mikhlef",
-        "author_inst": "Department of Biotechnology, University of Samarra, Iraq"
+        "author_name": "Mellissa C Alcantara",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Chandni Khizar",
-        "author_inst": "Institute of Molecular Biology and Biotechnology, University of Lahore, Lahore, Pakistan"
+        "author_name": "Yusuke Higuchi",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Abeer Kazmi",
-        "author_inst": "Department of Genetics, Institute of Hydrobiology, University of Chinese Academy of Sciences (UCAS), Wuhan, China"
+        "author_name": "Yuhei Kirita",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Nadeem Ullah Wazir",
-        "author_inst": "Department of Pharmacy, COMSATS University Islamabad, Abbottabad Campus, KPK, Pakistan"
+        "author_name": "Satoaki Matoba",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Ram Parsad Mainali",
-        "author_inst": "National Agriculture Genetic Resource Center (National Genebank), NARC, Khumaltar, Nepal"
+        "author_name": "Atsushi Hoshino",
+        "author_inst": "KPUM"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "new results",
     "category": "microbiology"
   },
@@ -121371,45 +122130,89 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.12.01.518643",
-    "rel_title": "Immunopeptidome profiling of human coronavirus OC43-infected cells identifies CD4 T cell epitopes specific to seasonal coronaviruses or cross-reactive with SARS-CoV-2",
+    "rel_doi": "10.1101/2022.12.01.518149",
+    "rel_title": "SARS-CoV-2 mRNA vaccine is re-adenylated in vivo, enhancing antigen production and immune response",
     "rel_date": "2022-12-01",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.01.518643",
-    "rel_abs": "Seasonal \"common-cold\" human coronaviruses are widely spread throughout the world and are mainly associated with mild upper respiratory tract infections. The emergence of highly pathogenic coronaviruses MERS-CoV, SARS-CoV, and most recently SARS-CoV-2 has prompted increased attention to coronavirus biology and immunopathology, but identification and characterization of the T cell response to seasonal human coronaviruses remain largely uncharacterized. Here we report the repertoire of viral peptides that are naturally processed and presented upon infection of a model cell line with seasonal human coronavirus OC43. We identified MHC-I and MHC-II bound peptides derived from the viral spike, nucleocapsid, hemagglutinin-esterase, 3C-like proteinase, and envelope proteins. Only three MHC-I bound OC43-derived peptides were observed, possibly due to the potent MHC-I downregulation induced by OC43 infection. By contrast, 80 MHC-II bound peptides corresponding to 14 distinct OC43-derived epitopes were identified, including many at very high abundance within the overall MHC-II peptidome. These peptides elicited low-abundance recall T cell responses in most donors tested. In vitro assays confirmed that the peptides were recognized by CD4+ T cells and identified the presenting HLA alleles. T cell responses cross-reactive between OC43, SARS-CoV-2, and the other seasonal coronaviruses were confirmed in samples of peripheral blood and peptide-expanded T cell lines. Among the validated epitopes, S903-917 presented by DPA1*01:03/DPB1*04:01 and S1085-1099 presented by DRB1*15:01 shared substantial homology to other human coronaviruses, including SARS-CoV-2, and were targeted by cross-reactive CD4 T cells. N54-68 and HE128-142 presented by DRB1*15:01 and HE259-273 presented by DPA1*01:03/DPB1*04:01 are immunodominant epitopes with low coronavirus homology that are not cross-reactive with SARS-CoV-2. Overall, the set of naturally processed and presented OC43 epitopes comprise both OC43-specific and human coronavirus cross-reactive epitopes, which can be used to follow T cell cross-reactivity after infection or vaccination and could aid in the selection of epitopes for inclusion in pan-coronavirus vaccines.\n\nAuthor SummaryThere is much current interest in cellular immune responses to seasonal common-cold coronaviruses because of their possible role in mediating protection against SARS-CoV-2 infection or pathology. However, identification of relevant T cell epitopes and systematic studies of the T cell responses responding to these viruses are scarce. We conducted a study to identify naturally processed and presented MHC-I and MHC-II epitopes from human cells infected with the seasonal coronavirus HCoV-OC43, and to characterize the T cell responses associated with these epitopes. We found epitopes specific to the seasonal coronaviruses, as well as epitopes cross-reactive between HCoV-OC43 and SARS-CoV-2. These epitopes should be useful in following immune responses to seasonal coronaviruses and identifying their roles in COVID-19 vaccination, infection, and pathogenesis.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.01.518149",
+    "rel_abs": "Though mRNA vaccines against COVID-19 have revolutionized vaccinology and have been administered in billions of doses, we know incredibly little about how mRNA vaccines are metabolized in vivo. Here we implemented enhanced nanopore Direct RNA sequencing (eDRS), to enable the analysis of single Modernas mRNA-1273 molecules, giving in vivo information about the sequence and poly(A) tails.\n\nWe show that mRNA-1273, with all uridines replaced by N1-methylpseudouridine (m{Psi}), is terminated by a long poly(A) tail (~100 nucleotides) followed by an m{Psi}Cm{Psi}AG sequence. In model cell lines, mRNA-1273 is swiftly degraded in a process initiated by the removal of m{Psi}Cm{Psi}AG, followed by CCR4-NOT-mediated deadenylation. In contrast, intramuscularly inoculated mRNA-1273 undergoes more complex modifications. Notably, mRNA-1273 molecules are re-adenylated after m{Psi}Cm{Psi}AG removal. Detailed analysis of immune cells involved in antigen production revealed that in macrophages, after m{Psi}Cm{Psi}AG removal, vaccine mRNA is very efficiently re-adenylated, and poly(A) tails can reach up to 200A. In contrast, in dendritic cells, vaccine mRNA undergoes slow deadenylation-dependent decay. We further demonstrate that enhancement of mRNA stability in macrophages is mediated by TENT5 poly(A) polymerases, whose expression is induced by the vaccine itself. Lack of TENT5-mediated re-adenylation results in lower antigen production and severely compromises specific immunoglobulin production following vaccination.\n\nTogether, our findings provide an unexpected principle for the high efficacy of mRNA vaccines and open new possibilities for their improvement. They also emphasize that, in addition to targeting a protein of interest, the design of mRNA therapeutics should be customized to its cellular destination.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Aniuska Becerra-Artiles",
-        "author_inst": "UMass Chan: University of Massachusetts Medical School"
+        "author_name": "Pawel S Krawczyk",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland"
       },
       {
-        "author_name": "Padma  P Nanaware",
-        "author_inst": "UMass Chan Medical School: University of Massachusetts Medical School"
+        "author_name": "Olga Gewartowska",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland"
       },
       {
-        "author_name": "Khaja Muneeruddin",
-        "author_inst": "UMass Chan: University of Massachusetts Medical School"
+        "author_name": "Michal Mazur",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland"
       },
       {
-        "author_name": "Grant  C Weaver",
-        "author_inst": "UMass Chan: University of Massachusetts Medical School"
+        "author_name": "Wiktoria Orzel",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland;  Faculty of Biology, University of Warsaw, 5a Pawinskiego, 02-106,"
       },
       {
-        "author_name": "Scott  A Shaffer",
-        "author_inst": "UMass Chan Medical School: University of Massachusetts Medical School"
+        "author_name": "Katarzyna Matylla-Kulinska",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland;  Faculty of Biology, University of Warsaw, 5a Pawinskiego, 02-106,"
       },
       {
-        "author_name": "Jaime  Mauricio Calvo-Calle",
-        "author_inst": "UMass Chan Medical School: University of Massachusetts Medical School"
+        "author_name": "Sebastian Jelen",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland;  Faculty of Biology, University of Warsaw, 5a Pawinskiego, 02-106,"
       },
       {
-        "author_name": "Lawrence  J. Stern",
-        "author_inst": "University of Massachusetts Medical School"
+        "author_name": "Pawel Turowski",
+        "author_inst": "ExploRNA Therapeutics, 101 Zwirki i Wigury, 02-089, Warsaw, Poland"
+      },
+      {
+        "author_name": "Tomasz Spiewla",
+        "author_inst": "Faculty of Physics, University of Warsaw, Pasteura 5, 02-093, Warsaw, Poland"
+      },
+      {
+        "author_name": "Bartosz Tarkowski",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland"
+      },
+      {
+        "author_name": "Agnieszka Tudek",
+        "author_inst": "Institute of Biochemistry and Biophysics, 5A Pawinskiego, 02-106 Warsaw, Poland"
+      },
+      {
+        "author_name": "Aleksandra Brouze",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland;  Faculty of Biology, University of Warsaw, 5a Pawinskiego, 02-106,"
+      },
+      {
+        "author_name": "Aleksandra Wesolowska",
+        "author_inst": "Laboratory of Human Milk and Lactation Research at Regional Human Milk Bank in Holy Family Hospital, Department of Medical Biology, Medical University of Warsaw"
+      },
+      {
+        "author_name": "Dominika Nowis",
+        "author_inst": "Laboratory of Experimental Medicine, Medical University of Warsaw, 5 Nielubowicza St., 02-097 Warsaw, Poland"
+      },
+      {
+        "author_name": "Jakub Golab",
+        "author_inst": "Department of Immunology, Medical University of Warsaw, 5 Nielubowicza Str., 02-097, Warsaw, Poland"
+      },
+      {
+        "author_name": "Joanna Kowalska",
+        "author_inst": "Faculty of Physics, University of Warsaw, Pasteura 5, 02-093, Warsaw, Poland"
+      },
+      {
+        "author_name": "Jacek Jemielity",
+        "author_inst": "Centre of New Technologies, University of Warsaw, Banacha 2c, 02-097, Warsaw, Poland"
+      },
+      {
+        "author_name": "Andrzej Dziembowski",
+        "author_inst": "International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 Warsaw, Poland; Faculty of Biology, University of Warsaw, Miecznikowa 1, 02-096, W"
+      },
+      {
+        "author_name": "Seweryn Mroczek",
+        "author_inst": "Faculty of Biology, University of Warsaw, 5a Pawinskiego, 02-106, Warsaw, Poland; International Institute of Molecular and Cell Biology, 4 Ks. Trojdena, 02-106 "
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "new results",
     "category": "immunology"
   },
@@ -122985,75 +123788,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.11.25.22282676",
-    "rel_title": "The influence of COVID-19 risk perception and vaccination status on the number of social contacts across Europe: insights from the CoMix study",
+    "rel_doi": "10.1101/2022.11.29.22282856",
+    "rel_title": "The Detection of COVID-19 in Chest X-Rays Using Ensemble CNN Techniques",
     "rel_date": "2022-11-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.25.22282676",
-    "rel_abs": "BackgroundThe SARS-CoV-2 transmission dynamics have been greatly modulated by human contact behaviour. To curb the spread of the virus, global efforts focused on implementing both Non-Pharmaceutical Interventions (NPIs) and pharmaceutical interventions such as vaccination. This study was conducted to explore the influence of COVID-19 vaccination status and risk perceptions related to SARS-CoV-2 on the number of social contacts of individuals in 16 European countries. This is important since insights derived from the study could be utilized in guiding the formulation of risk communication strategies.\n\nMethodsWe used data from longitudinal surveys conducted in the 16 European countries to measure social contact behaviour in the course of the pandemic. The data consisted of representative panels of participants in terms of gender, age and region of residence in each country. The surveys were conducted in several rounds between December 2020 and September 2021. We employed a multilevel generalized linear mixed effects model to explore the influence of risk perceptions and COVID-19 vaccination status on the number of social contacts of individuals.\n\nResultsThe results indicated that perceived severity played a significant role in social contact behaviour during the pandemic after controlling for other variables. More specifically, participants who perceived COVID-19 to be a serious illness made fewer contacts compared to those who had low or neutral perceptions of the COVID-19 severity. Additionally, vaccinated individuals reported significantly higher number of contacts than the non-vaccinated. Further-more, individual-level factors played a more substantial role in influencing contact behaviour than country-level factors.\n\nConclusionOur multi-country study yields significant insights on the importance of risk perceptions and vaccination in behavioral changes during a pandemic emergency. The apparent increase in social contact behaviour following vaccination would require urgent intervention in the event of emergence of an immune escaping variant. Hence, insights derived from this study could be taken into account when designing, implementing and communicating COVID-19 interventions.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.29.22282856",
+    "rel_abs": "Advances in the field of image classification using convolutional neural networks (CNNs) have greatly improved the accuracy of medical image diagnosis by radiologists. Numerous research groups have applied CNN methods to diagnose respiratory illnesses from chest x-rays, and have extended this work to prove the feasibility of rapidly diagnosing COVID-19 to high degrees of accuracy. One issue in previous research has been the use of datasets containing only a few hundred images of chest x-rays containing COVID-19, causing CNNs to overfit the image data. This leads to a lower accuracy when the model attempts to classify new images, as would be clinically expected of it. In this work, we present a model trained on the COVID-QU-Ex dataset, overall containing 33,920 chest x-ray images, with an equal share of COVID-19, Non-COVID pneumonia, and Normal images. The model itself is an ensemble of pre-trained CNNs (ResNet50, VGG19, VGG16) and GLCM textural features. It achieved a 98.34% binary classification accuracy (COVID-19/no COVID-19) on a balanced test dataset of 6581 chest x-rays, and 94.68% for distinguishing between COVID-19, Non-COVID pneumonia and normal chest x-rays. Also, we herein discuss the effects of dataset size, demonstrating that a 98.82% 3-class accuracy can be achieved using the model if the training dataset only contains a few thousand images, but that generalisability of the model suffers with such small datasets.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "James Wambua",
-        "author_inst": "Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium."
-      },
-      {
-        "author_name": "Neilshan Loedy",
-        "author_inst": "Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium."
-      },
-      {
-        "author_name": "Christopher I Jarvis",
-        "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel "
-      },
-      {
-        "author_name": "Kerry LM Wong",
-        "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel "
-      },
-      {
-        "author_name": "Christel Faes",
-        "author_inst": "Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium."
-      },
-      {
-        "author_name": "Rok Grah",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden."
-      },
-      {
-        "author_name": "Bastian Prasse",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden."
-      },
-      {
-        "author_name": "Frank Sandmann",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden."
-      },
-      {
-        "author_name": "Rene Niehus",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden."
-      },
-      {
-        "author_name": "Helen Johnson",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden. Current address (Health Emergency Preparedness and R"
-      },
-      {
-        "author_name": "W.John Edmunds",
-        "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel "
-      },
-      {
-        "author_name": "Philippe Beutels",
-        "author_inst": "Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium. AND The"
-      },
-      {
-        "author_name": "Niel Hens",
-        "author_inst": "Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium. AND Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & I"
+        "author_name": "Domantas Kuzinkovas",
+        "author_inst": "The University of Sydney"
       },
       {
-        "author_name": "Pietro Coletti",
-        "author_inst": "Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium."
+        "author_name": "Sandhya Clement",
+        "author_inst": "The University of Sydney"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2022.11.26.22282782",
@@ -124943,79 +125698,67 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.11.23.22282478",
-    "rel_title": "Population Pharmacokinetics and Exposure-Response Analysis of Sotrovimab in the Early Treatment of COVID-19",
+    "rel_doi": "10.1101/2022.11.23.22282463",
+    "rel_title": "Heterogeneity of treatment effect of higher dose dexamethasone by geographic region in patients with COVID-19 and severe hypoxemia - A post hoc evaluation of the COVID STEROID 2 trial",
     "rel_date": "2022-11-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.23.22282478",
-    "rel_abs": "Sotrovimab is a recombinant human monoclonal antibody that has been shown to prevent progression to hospitalization or death from severe disease in non-hospitalized high-risk patients with mild-to-moderate COVID-19 following either intravenous (IV) or intramuscular (IM) administration. Population pharmacokinetic (popPK) and exposure-response (ER) analyses were performed to characterize sotrovimab PK and the relationship between exposure and response (probability of progression), as well as covariates that may contribute to between-participant variability in sotrovimab PK and efficacy following IV or IM administration. Sotrovimab PK was described by a two-compartment model with linear elimination; IM absorption was characterized by a sigmoid absorption model. PopPK covariate analysis led to the addition of the effect of body weight on systemic clearance and peripheral volume of distribution, sex on IM bioavailability and first-order absorption rate (KA), and body mass index on KA. However, the magnitude of covariate effect was not pronounced and was therefore not expected to be clinically relevant based on available data to date. For ER analysis, sotrovimab exposure measures were predicted using the final popPK model. An ER model was developed using the exposure measure of sotrovimab concentration at 168 hours that described the relationship between exposure and probability of progression within the ER dataset for COMET-TAIL. The number of risk factors ([&le;]1 vs >1) was incorporated as an additive shift on the model-estimated placebo response but had no impact on overall drug response. Limitations in the ER model may prevent generalization of these results to describe the sotrovimab exposure-progression relationship across SARS-COV-2 variants.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.23.22282463",
+    "rel_abs": "BackgroundThe COVID-STEROID 2 trial found high probability of benefit with dexamethasone 12 mg vs. 6 mg daily among patients with COVID-19 and severe hypoxemia. There was suggestion of heterogeneity of treatment effects (HTE)between patients enrolled from Europe vs. India on the primary outcome. Whether there was HTE by geographical region for the remaining prespecified patient-important outcomes is unclear.\n\nMethodsWe evaluated HTE by geographical region (Europe vs. India) for all secondary outcomes assessed in the trial with analyses adjusted for stratification variables. The results are presented as risk differences (RDs) or mean differences (MDs) with 99% confidence intervals (CIs) and P-values from interaction tests.\n\nResultsWe found HTE for mortality at day 28 (RD for Europe -8.3% (99 % CI: -17.7 to 1.0) vs. RD for India 0.1% (99% CI: -10.0 to 10.0)), mortality at day 90 (RD for Europe -7.4% (99% CI: -17.1 to 2.0) vs. RD for India -1.4% (99% CI:-12.8 to 9.8)), mortality at day 180 (RD for Europe -6.7% (99%CI:-16.4 to 2.9) vs. RD for India -1.0% (99%CI:-12.3 to 10.3)), and number of days alive without life support at day 90 (MD for Europe 6.1 days (99% CI:-1.3 to 13.4) vs. MD for India 1.7 days (99% CI:-8.4 to11.8)). For serious adverse reactions, the direction was reversed (RD for Europe -1.0% (99% CI:-7.1 to 5.2) vs. RD for India -5.3% (99% CI: -16.2 to 5.0). For HRQoL outcomes, MD in EQ-5D-5L index values was 0.08(99%CI: -0.01 to 0.16) for Europe and 0.02(99%CI:-0.10 to 0.14) for India. For EQ VAS, MD was 4.4(95%CI:-3.1 to 11.9) for Europe and 2.6(99%CI:-9.0 to 14.2) for India. P values for all tests of interaction were [&ge;]0.12.\n\nConclusionsIn this post hoc exploratory analysis, we found that higher dose dexamethasone may have lower beneficial effects for patients in India as compared with those in Europe without an increase in serious adverse reactions.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Jennifer Sager",
-        "author_inst": "Vir Biotechnology"
-      },
-      {
-        "author_name": "Asma El-Zailik",
-        "author_inst": "Vir Biotechnology, Inc"
-      },
-      {
-        "author_name": "Julie Passarell",
-        "author_inst": "Cognigen Division, Simulations Plus, Inc."
-      },
-      {
-        "author_name": "Stefan Roepcke",
-        "author_inst": "Cognigen Division, Simulations Plus, Inc."
+        "author_name": "Bharath Kumar Tirupakuzhi Vijayaraghavan",
+        "author_inst": "Apollo Hospitals Chennai"
       },
       {
-        "author_name": "Xiaobin Li",
-        "author_inst": "GSK, Upper Providence"
+        "author_name": "Anders Granholm",
+        "author_inst": "Copenhagen University Hospital: Rigshospitalet"
       },
       {
-        "author_name": "Melissa Aldinger",
-        "author_inst": "Vir Biotechnology, Inc."
+        "author_name": "Sheila  N Myatra",
+        "author_inst": "TMH: Tata Memorial Hospital"
       },
       {
-        "author_name": "Ahmed Nader",
-        "author_inst": "GSK, Upper Providence"
+        "author_name": "Vivekanand Jha",
+        "author_inst": "The George Institute for Global Health India"
       },
       {
-        "author_name": "Andrew Skingsley",
-        "author_inst": "GSK, Brentford"
+        "author_name": "Naomi Hammond",
+        "author_inst": "The George Institute for Global Health"
       },
       {
-        "author_name": "Elizabeth L. Alexander",
-        "author_inst": "Vir Biotechnology, Inc."
+        "author_name": "Sharon Micallef",
+        "author_inst": "The George Institute for Global Health"
       },
       {
-        "author_name": "Wendy W. Yeh",
-        "author_inst": "Vir Biotechnology, Inc."
+        "author_name": "Marie  Warrer Munch",
+        "author_inst": "Copenhagen University Hospital: Rigshospitalet"
       },
       {
-        "author_name": "Erik Mogalian",
-        "author_inst": "Vir Biotechnology, Inc."
+        "author_name": "Maj-Brit  N Kj\u00e6r",
+        "author_inst": "Copenhagen University Hospital: Rigshospitalet"
       },
       {
-        "author_name": "Chad Garner",
-        "author_inst": "Vir Biotechnology, Inc."
+        "author_name": "Morten  Hylander M\u00f8ller",
+        "author_inst": "Copenhagen University Hospital: Rigshospitalet"
       },
       {
-        "author_name": "Amanda Peppercorn",
-        "author_inst": "GSK, Cambridge"
+        "author_name": "Theis Lange",
+        "author_inst": "University of Copenhagen Department of Public Health: Kobenhavns Universitet Institut for Folkesundhedsvidenskab"
       },
       {
-        "author_name": "Adrienne E Shapiro",
-        "author_inst": "University of Washington"
+        "author_name": "Anders Perner",
+        "author_inst": "Copenhagen University Hospital: Rigshospitalet"
       },
       {
-        "author_name": "Maribel Reyes",
-        "author_inst": "Vir Biotechnology, Inc."
+        "author_name": "Balasubramanian Venkatesh",
+        "author_inst": "The George Institute for Global Health"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pharmacology and therapeutics"
+    "category": "respiratory medicine"
   },
   {
     "rel_doi": "10.1101/2022.11.24.22282735",
@@ -126813,79 +127556,47 @@
     "category": "oncology"
   },
   {
-    "rel_doi": "10.1101/2022.11.21.22282569",
-    "rel_title": "COVID-19-related testing, knowledge and behaviors among severe and chronic non-communicable disease patients in Neno District, Malawi: A prospective cohort study.",
+    "rel_doi": "10.1101/2022.11.21.517390",
+    "rel_title": "Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England",
     "rel_date": "2022-11-22",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.21.22282569",
-    "rel_abs": "ObjectiveTo assess changes over time in COVID-19 knowledge, risks, symptoms, testing, and infection prevention practices among patients with complex non-communicable disease (NCD) receiving care at Neno District and Lisungwi Community Hospitals, Malawi.\n\nDesign and participantsWe conducted a prospective open cohort study using telephone-based data collection among patients enrolled in NCD clinics. We conducted four rounds of data collection between November 2020 and October 2021.\n\nSettingRural southwestern Malawi in Neno District which has a population of 150, 211 persons.\n\nPrimary and secondary outcome measuresWe used descriptive statistics to characterize the population and assess COVID-19-related knowledge and behaviors. Linear and logistic regression models were used to assess significant changes over time.\n\nResultsAcross four rounds of data collection, the most commonly reported COVID-19-related risks among patients included visiting health facilities (range: 35-49%), attending mass gatherings (range: 33-36%), and travelling outside the district (range: 14-19%). Patients reporting having ever experienced COVID-like symptoms increased from 30% in December 2020 to 41% in October 2021, however, as of the end of study period, only 13% of patients had ever received a COVID-19 test. Overall, respondents answered about two thirds (range: 67-70%) of the COVID-19 knowledge questions correctly with no significant changes over time. Hand washing, wearing of face masks and maintaining safe distance were the most frequently reported strategies used to prevent spreading of COVID-19. Wearing of facemask significantly improved from 63% to 96% over time (p<0.001).\n\nConclusionsHouseholds of advanced chronic disease patients reported accurate knowledge about COVID-19 and improved adherence to wearing of face masks over time. However, patients commonly visit locations where they could be exposed to COVID-19 and often experience COVID-like symptoms but are rarely tested for COVID-19. We urge the government and other stakeholders to increase COVID-19 testing accessibility to primary facility and community levels.\n\nStrengths and limitations of this studyO_LIAssessed COVID-19-related outcomes among a highly vulnerable group of patients in a rural African setting\nC_LIO_LILongitudinal follow-up allowed us to assess changes over time from December 2020 to September 2021\nC_LIO_LIData can inform COVID-19 infection preventive measures in a setting with persistently poor access to COVID-19 vaccines\nC_LIO_LIThe telephone survey was conducted among severe and chronic NCD patients in rural Malawi and is not generalizable to urban areas or rural populations without cellular service\nC_LIO_LIData was self-reported data and vulnerable to social desirability bias\nC_LI",
-    "rel_num_authors": 15,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.21.517390",
+    "rel_abs": "Random genetic drift in the population-level dynamics of an infectious disease outbreak results from the randomness of inter-host transmission and the randomness of host recovery or death. The strength of genetic drift has been found to be high for SARS-CoV-2 due to superspreading, and this is expected to substantially impact the disease epidemiology and evolution. Noise that results from the measurement process, such as biases in data collection across time, geographical areas, etc., can potentially confound estimates of genetic drift as both processes contribute \"noise\" to the data. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude. Corrections taking into account epidemiological dynamics (susceptible-infected-recovered or susceptible-exposed-infected-recovered models) do not explain the discrepancy. Moreover, the levels of genetic drift that we observe are higher than the estimated levels of superspreading found by modeling studies that incorporate data on actual contact statistics in England. We discuss how even in the absence of superspreading, high levels of genetic drift can be generated via community structure in the host contact network. Our results suggest that further investigations of heterogeneous host contact structure may be important for understanding the high levels of genetic drift observed for SARS-CoV-2 in England.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Haules Robbins Zaniku",
-        "author_inst": "Neno District Health Office"
-      },
-      {
-        "author_name": "Moses Banda Aron",
-        "author_inst": "Partners in Health, Malawi"
-      },
-      {
-        "author_name": "Kaylin Vrkljan",
-        "author_inst": "Harvard College, Harvard University, USA"
-      },
-      {
-        "author_name": "Kartik Tyagi",
-        "author_inst": "Gillings School of Global Public Health, University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "Myness Kasanda Ndambo",
-        "author_inst": "Malawi Epidemiology and Intervention Research Unit (MEIRU), Malawi"
-      },
-      {
-        "author_name": "Gladys Mtalimanja Banda",
-        "author_inst": "Neno District Health Office, Malawi"
-      },
-      {
-        "author_name": "Revelation Nyirongo",
-        "author_inst": "Partners in Health, Malawi"
-      },
-      {
-        "author_name": "Isaac Mphande",
-        "author_inst": "Partners in Health, Malawi"
-      },
-      {
-        "author_name": "Bright Mailosi",
-        "author_inst": "Partners in Health, Malawi"
+        "author_name": "QinQin Yu",
+        "author_inst": "University of California Berkeley"
       },
       {
-        "author_name": "George Talama",
-        "author_inst": "Partners in Hope, Malawi"
+        "author_name": "Joao A Ascensao",
+        "author_inst": "University of California Berkeley"
       },
       {
-        "author_name": "Fabien Munyaneza",
-        "author_inst": "Partners in Health, Malawi"
+        "author_name": "Takashi Okada",
+        "author_inst": "University of California Berkeley, Kyoto University, RIKEN"
       },
       {
-        "author_name": "Emilia Connolly",
-        "author_inst": "Partners in Health, Malawi"
+        "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium",
+        "author_inst": ""
       },
       {
-        "author_name": "Luckson Dullie",
-        "author_inst": "Partners in Health, Malawi"
+        "author_name": "Olivia Boyd",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Dale A. Barnhart",
-        "author_inst": "Partners in Health, Rwanda"
+        "author_name": "Erik Volz",
+        "author_inst": "Imperial College London; The COVID-19 Genomics UK Consortium"
       },
       {
-        "author_name": "Todd Ruderman",
-        "author_inst": "Partners in Health, Malawi"
+        "author_name": "Oskar Hallatschek",
+        "author_inst": "University of California Berkeley; Leipzig University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "license": "cc_by_nc",
+    "type": "new results",
+    "category": "evolutionary biology"
   },
   {
     "rel_doi": "10.1101/2022.11.19.22282451",
@@ -128527,61 +129238,45 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2022.11.17.22282473",
-    "rel_title": "Perceptions and compliance with COVID-19 preventive measures in Southern and Central regions of Mozambique: a quantitative in-person household survey in the districts of Manhica and Quelimane",
+    "rel_doi": "10.1101/2022.11.17.22282452",
+    "rel_title": "Association between long COVID symptoms and employment status",
     "rel_date": "2022-11-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.17.22282473",
-    "rel_abs": "BackgroundThe COVID-19 pandemic has led countries into urgent implementation of stringent preventive measures at the population level. However, implementing these measures in low-income countries like Mozambique was incredibly difficult, coupled with lack of scientific evidence on the community understanding and compliance with these measures. This study assessed the perceptions and implementation of COVID-19 preventive measures recommended by Mozambican authorities in Manhica and Quelimane districts, taking confinement, social distancing, frequent handwashing, mask wearing, and quarantine as the key practices to evaluate.\n\nMethodsA quantitative survey interviewing households heads in-person was conducted in October 2020 and February 2021; collecting data on perceptions of COVID-19, symptoms, means of transmission/prevention; including self-evaluation of compliance with the key measures, existence of handwashing facilities, and the ratio of face-masks per person. The analysis presents descriptive statistics on perceptions and compliance with anti-COVID-19 measures at individual and household levels, comparing by district and other variables. T-test was performed to assess the differences on proportions between the districts or categories of respondents in the same district.\n\nResultsThe study interviewed 770 individuals of which 62.3% were heads of households, 18.6% their spouses, and 11.0% sons/daughters. Most participants (98.7%) had heard of COVID-19 disease. The most difficult measure to comply with was staying at home (35.8% of respondents said they could not comply with it at all); followed by avoiding touching the month/nose/eyes (28.7%), and social distancing at home (27.3%). Mask wearing in public places was the measure that more respondents (48.8%) thought they complied 100% with it, followed by avoiding unnecessary traveling (40.0%), avoiding crowed places (34.0%), and social distancing outside home (29.0%). Only 30.4% of households had handwashing devices or disinfectant (36.7% in Manhica and 24.1% in Quelimane); and of those with devices, only 41.0% had water in the device, 37.6% had soap, and 22.6% had other disinfectant. The ratio of masks per person was only 1, which suggests that people may have used the same mask for longer periods than recommended.\n\nConclusionsCommunity members in Manhica and Quelimane were aware of COVID-19 but they lacked understanding for implementing the preventive measures. This, together with socio-economic constraints, led to lower levels of compliance with the key measures. Understanding and addressing the factors affecting proper implementation of these measures is crucial for informing decision-makers about ways to improve community knowledge and practices to prevent infectious diseases with epidemic potential.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.17.22282452",
+    "rel_abs": "BackgroundSymptoms of Coronavirus-19 (COVID-19) infection persist beyond 2 months in a subset of individuals, a phenomenon referred to as long COVID, but little is known about its functional correlates and in particular the relevance of neurocognitive symptoms.\n\nMethodWe analyzed a previously-reported cohort derived from 8 waves of a nonprobability-sample internet survey called the COVID States Project, conducted every 4-8 weeks between February 2021 and July 2022. Primary analyses examined associations between long COVID and lack of full employment or unemployment, adjusted for age, sex, race and ethnicity, education, urbanicity, and region, using multiple logistic regression with interlocking survey weights.\n\nResultsThe cohort included 15,307 survey respondents ages 18-69 with test-confirmed COVID-19 at least 2 months prior, of whom 2,236 (14.6%) reported long COVID symptoms, including 1,027/2,236 (45.9%) reporting either  brain fog or impaired memory. Overall, 1,418/15,307 (9.3%) reported being unemployed, including 276/2,236 (12.3%) of those with long COVID and 1,142/13,071 (8.7%) of those without; 8,228 (53.8%) worked full-time, including 1,017 (45.5%) of those with long COVID and 7,211 (55.2%) without. In survey-weighted regression models, presence of long COVID was associated with being unemployed (crude OR 1.44, 95% CI 1.20-1.72; adjusted OR 1.23, 95% CI 1.02-1.48), and with lower likelihood of working full-time (crude OR 0.73, 95% CI 0.64-0.82; adjusted OR 0.79, 95% CI 0.70 -0.90). Among individuals with long COVID, the presence of cognitive symptoms - either brain fog or impaired memory - was associated with lower likelihood of working full time (crude OR 0.71, 95% CI 0.57-0.89, adjusted OR 0.77, 95% CI 0.61-0.97).\n\nConclusionLong COVID was associated with a greater likelihood of unemployment and lesser likelihood of working full time in adjusted models. Presence of cognitive symptoms was associated with diminished likelihood of working full time. These results underscore the importance of developing strategies to respond to long COVID, and particularly the associated neurocognitive symptoms.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Ariel Nhacolo",
-        "author_inst": "CISM: Centro de Investigacao em Saude de Manhica"
-      },
-      {
-        "author_name": "Amilcar Maga\u00e7o",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
-      },
-      {
-        "author_name": "Felizarda Amosse",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
-      },
-      {
-        "author_name": "Aura Hunguana",
-        "author_inst": "Centro de Investigacao em Saude de Manhica"
-      },
-      {
-        "author_name": "Teodomiro Matsena",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
+        "author_name": "Kristin Lunz Trujillo",
+        "author_inst": "Harvard Kennedy School of Government"
       },
       {
-        "author_name": "Arsenio Nhacolo",
-        "author_inst": "Centro de Investigacao em Saude de Manhica"
+        "author_name": "Roy H Perlis",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Elisio Xerinda",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
+        "author_name": "Alauna Safarpour",
+        "author_inst": "Harvard Kennedy School of Government"
       },
       {
-        "author_name": "Quique Bassat",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
+        "author_name": "Mauricio Santillana",
+        "author_inst": "Northeastern University"
       },
       {
-        "author_name": "Charfudin Sacoor",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
+        "author_name": "Katherine Ognyanova",
+        "author_inst": "Rutgers University"
       },
       {
-        "author_name": "Inacio Mandomando",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
+        "author_name": "James Druckman",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Khatia Munguambe",
-        "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Manhi\u00e7a: Centro de Investigacao em Saude de Manhica"
+        "author_name": "David Lazer",
+        "author_inst": "Northeastern University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -130265,99 +130960,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.11.15.516323",
-    "rel_title": "The SARS-CoV-2 protein ORF3c is a mitochondrial modulator of innate immunity",
+    "rel_doi": "10.1101/2022.11.14.22282297",
+    "rel_title": "Using Genome Sequence Data to Predict SARS-CoV-2 Detection Cycle Threshold Values",
     "rel_date": "2022-11-15",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.15.516323",
-    "rel_abs": "The SARS-CoV-2 genome encodes a multitude of accessory proteins. Using comparative genomic approaches, an additional accessory protein, ORF3c, has been predicted to be encoded within the ORF3a sgmRNA. Expression of ORF3c during infection has been confirmed independently by ribosome profiling. Despite ORF3c also being present in the 2002-2003 SARS-CoV, its function has remained unexplored. Here we show that ORF3c localises to mitochondria during infection, where it inhibits innate immunity by restricting IFN-{beta} production, but not NF-{kappa}B activation or JAK-STAT signalling downstream of type I IFN stimulation. We find that ORF3c acts after stimulation with cytoplasmic RNA helicases RIG-I or MDA5 or adaptor protein MAVS, but not after TRIF, TBK1 or phospho-IRF3 stimulation. ORF3c co-immunoprecipitates with the antiviral proteins MAVS and PGAM5 and induces MAVS cleavage by caspase-3. Together, these data provide insight into an uncharacterised mechanism of innate immune evasion by this important human pathogen.",
-    "rel_num_authors": 20,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.14.22282297",
+    "rel_abs": "The continuing emergence of SARS-CoV-2 variants of concern (VOCs) presents a serious public health threat, exacerbating the effects of the COVID19 pandemic. Although millions of genomes have been deposited in public archives since the start of the pandemic, predicting SARS-CoV-2 clinical characteristics from the genome sequence remains challenging. In this study, we used a collection of over 29,000 high quality SARS-CoV-2 genomes to build machine learning models for predicting clinical detection cycle threshold (Ct) values, which correspond with viral load. After evaluating several machine learning methods and parameters, our best model was a random forest regressor that used 10-mer oligonucleotides as features and achieved an R2 score of 0.521 {+/-} 0.010 (95% confidence interval over 5 folds) and an RMSE of 5.7 {+/-} 0.034, demonstrating the ability of the models to detect the presence of a signal in the genomic data. In an attempt to predict Ct values for newly emerging variants, we predicted Ct values for Omicron variants using models trained on previous variants. We found that approximately 5% of the data in the model needed to be from the new variant in order to learn its Ct values. Finally, to understand how the model is working, we evaluated the top features and found that the model is using a multitude of k-mers from across the genome to make the predictions. However, when we looked at the top k-mers that occurred most frequently across the set of genomes, we observed a clustering of k-mers that span spike protein regions corresponding with key variations that are hallmarks of the VOCs including G339, K417, L452, N501, and P681, indicating that these sites are informative in the model and may impact the Ct values that are observed in clinical samples.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Hazel Stewart",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Yongxu Lu",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Anusha Valpadashi",
-        "author_inst": "University Medical Center Goettingen"
-      },
-      {
-        "author_name": "Luis Daniel Cruz-Zaragoza",
-        "author_inst": "University Medical Center Goettingen"
-      },
-      {
-        "author_name": "Hendrik A Michel",
-        "author_inst": "Harvard Graduate Program in Virology"
-      },
-      {
-        "author_name": "Samantha K Nguyen",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "George W Carnell",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Nina Lukhovitskaya",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Rachel Milligan",
-        "author_inst": "University of Bristol"
-      },
-      {
-        "author_name": "Irwin Jungreis",
-        "author_inst": "MIT"
-      },
-      {
-        "author_name": "Valeria Lulla",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Andrew D Davidson",
-        "author_inst": "University of Bristol"
-      },
-      {
-        "author_name": "David A Matthews",
-        "author_inst": "University of Bristol"
+        "author_name": "Lea Duesterwald",
+        "author_inst": "Horace Greeley High School, Chappaqua, NY, USA"
       },
       {
-        "author_name": "Stephen High",
-        "author_inst": "University of Manchester"
-      },
-      {
-        "author_name": "Peter Rehling",
-        "author_inst": "Univ. Goettingen"
+        "author_name": "Marcus Nguyen",
+        "author_inst": "Argonne National Laboratory"
       },
       {
-        "author_name": "Edward Emmott",
-        "author_inst": "University of Liverpool"
+        "author_name": "Paul Christensen",
+        "author_inst": "Houston Methodist Hospital"
       },
       {
-        "author_name": "Jonathan Luke Heeney",
-        "author_inst": "University of Cambridge"
+        "author_name": "Scott Wesley Long",
+        "author_inst": "Houston Methodist Hospital"
       },
       {
-        "author_name": "James R Edgar",
-        "author_inst": "University of Cambridge"
+        "author_name": "Randall J. Olsen",
+        "author_inst": "Houston Methodist Hospital"
       },
       {
-        "author_name": "Geoffrey  L. Smith",
-        "author_inst": "University of Cambridge"
+        "author_name": "James M. Musser",
+        "author_inst": "Houston Methodist Hospital"
       },
       {
-        "author_name": "Andrew E Firth",
-        "author_inst": "University of Cambridge"
+        "author_name": "James J. Davis",
+        "author_inst": "Argonne National Laboratory"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc0",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.11.14.22282295",
@@ -132235,55 +132878,111 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2022.11.09.22282120",
-    "rel_title": "Selection of long COVID symptoms influences prevalence estimates in a prospective cohort",
+    "rel_doi": "10.1101/2022.11.11.516114",
+    "rel_title": "A broad-spectrum macrocyclic peptide inhibitor of the SARS-CoV-2 spike protein",
     "rel_date": "2022-11-11",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.09.22282120",
-    "rel_abs": "BackgroundStudies on long COVID differ in the selection of symptoms used to define the condition. We aimed to assess to what extent symptom selection impacts prevalence estimates of long COVID.\n\nMethodsIn a prospective cohort of patients who experienced mild to critical coronavirus disease 2019 (COVID-19), we used longitudinal data on the presence of 20 different symptoms to evaluate changes in the prevalence of long COVID over time when altering symptom selection.\n\nResultsChanging symptom selection resulted in wide variation in long COVID prevalence, even within the same study population. Long COVID prevalence at 12 months since illness onset ranged from 39.6% (95%CI=33.4-46.2) when using a limited selection of symptoms to 80.6% (95%CI=74.8-85.4) when considering any reported symptom to be relevant.\n\nConclusionsComparing the occurrence of long COVID is already complex due to heterogeneity in study design and population. Disparate symptom selection may further hamper comparison of long COVID estimates between populations. Harmonised data collection tools could be one means to achieve greater reproducibility and comparability of results.",
-    "rel_num_authors": 9,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.11.516114",
+    "rel_abs": "The ongoing COVID-19 pandemic has had great societal and health consequences. Despite the availability of vaccines, infection rates remain high due to immune evasive Omicron sublineages. Broad-spectrum antivirals are needed to safeguard against emerging variants and future pandemics. We used mRNA display under a reprogrammed genetic code to find a spike-targeting macrocyclic peptide that inhibits SARS-CoV-2 Wuhan strain infection and pseudoviruses containing spike proteins of SARS-CoV-2 variants or related sarbecoviruses. Structural and bioinformatic analyses reveal a conserved binding pocket between the receptor binding domain, N-terminal domain and S2 region, distal to the ACE2 receptor-interaction site. Our data reveal a hitherto unexplored site of vulnerability in sarbecoviruses that peptides and potentially other drug-like molecules can target.\n\nSignificance statementThis study reports on the discovery of a macrocyclic peptide that is able to inhibit SARS-CoV-2 infection by exploiting a new vulnerable site in the spike glycoprotein. This region is highly conserved across SARS-CoV-2 variants and the subgenus sarbecovirus. Due to the inaccessability and mutational contraint of this site, it is anticipated to be resistant to the development of resistance through antibody selective pressure. In addition to the discovery of a new molecule for development of potential new peptide or biomolecule therapeutics, the discovery of this broadly active conserved site can also stimulate a new direction of drug development, which together may prevent future outbreaks of related viruses.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Elke Wynberg",
-        "author_inst": "Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, the Netherlands"
+        "author_name": "Vito Thijssen",
+        "author_inst": "Utrecht University, Vrije Universiteit Amsterdam"
       },
       {
-        "author_name": "Godelieve J. de Bree",
-        "author_inst": "Department of Infectious Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands"
+        "author_name": "Daniel L. Hurdiss",
+        "author_inst": "Utrecht University"
       },
       {
-        "author_name": "Tjalling Leenstra",
-        "author_inst": "National Institute for Public Health and the Environment (Rijksinstituut voor Volksgezondheid en Milieu; RIVM), Bilthoven, Netherlands"
+        "author_name": "Oliver J Debski-Antoniak",
+        "author_inst": "Utrecht University"
       },
       {
-        "author_name": "Anouk Verveen",
-        "author_inst": "Department of Medical Psychology, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, the Netherlands"
+        "author_name": "Matthew A Spence",
+        "author_inst": "Australian National University"
       },
       {
-        "author_name": "Hugo D.G. van Willigen",
-        "author_inst": "Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, th"
+        "author_name": "Charlotte Franck",
+        "author_inst": "University of Sydney"
       },
       {
-        "author_name": "Menno de  Jong",
-        "author_inst": "Department of Medical Microbiology & Infection Prevention, Amsterdam UMC, University of Amsterdam, Amsterdam Institute for Infection and Immunity, Amsterdam, th"
+        "author_name": "Alexander Norman",
+        "author_inst": "University of Sydney"
       },
       {
-        "author_name": "Maria Prins",
-        "author_inst": "Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, the Netherlands"
+        "author_name": "Anupriya Aggarwal",
+        "author_inst": "Kirby Institute"
       },
       {
-        "author_name": "Anders Boyd",
-        "author_inst": "Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, the Netherlands; Stichting hiv monitoring, Amsterdam, the Netherlands"
+        "author_name": "Nadia J Mokiem",
+        "author_inst": "Utrecht University"
       },
       {
-        "author_name": "- the RECoVERED Study Group",
-        "author_inst": ""
+        "author_name": "David A A van Dongen",
+        "author_inst": "Utrecht University, Vrije Universiteit Amsterdam"
+      },
+      {
+        "author_name": "Stein W Vermeir",
+        "author_inst": "Universiteit Utrecht, Vrije Universiteit Amsterdam"
+      },
+      {
+        "author_name": "Minglong Liu",
+        "author_inst": "Utrecht University, Vrije Universiteit Amsterdam"
+      },
+      {
+        "author_name": "Wentao Li",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Marianthi Chatziandreou",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Tim Donselaar",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Wenjuan Du",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Ieva Drulyte",
+        "author_inst": "Thermo Fisher Scientific"
+      },
+      {
+        "author_name": "Berend Jan Bosch",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Joost Snijder",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Stuart Grant Turville",
+        "author_inst": "Kirby Institute"
+      },
+      {
+        "author_name": "Richard J Payne",
+        "author_inst": "The University of Sydney"
+      },
+      {
+        "author_name": "Colin J Jackson",
+        "author_inst": "Australian National University"
+      },
+      {
+        "author_name": "Frank J.M. van Kuppeveld",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Seino A K Jongkees",
+        "author_inst": "Vrije Universiteit Amsterdam"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "type": "new results",
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2022.11.10.22282181",
@@ -133825,71 +134524,163 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.11.07.22282054",
-    "rel_title": "Durability and determinants of anti-SARS-CoV-2 spike antibodies following the second and third doses of mRNA COVID-19 vaccine",
+    "rel_doi": "10.1101/2022.11.08.515436",
+    "rel_title": "Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection.",
     "rel_date": "2022-11-08",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.07.22282054",
-    "rel_abs": "BackgroundEpidemiological data regarding differences in durability and its determinants of humoral immunity following 2- and 3-dose COVID-19 vaccination are scarce.\n\nMethodsWe repeatedly assessed the anti-spike IgG antibody titers of 2- and 3-dose mRNA vaccine recipients among the staff of a medical and research center in Tokyo. Linear mixed models were used to estimate trajectories of antibody titers from 14 to 180 days after the last immune-conferred event (vaccination or infection) and compare antibody waning rates across prior infection and vaccination status, and across background factors in infection-naive participants.\n\nResultsA total of 6901 measurements from 2964 participants (median age, 35 years; 30% male) were analyzed. Antibody waning rate (per 30 days [95% CI]) was slower after 3-dose (25% [23-26]) than 2-dose (36% [35-37]). Participants with hybrid immunity (vaccination and infection) had further slower waning rates: 2-dose plus infection (16% [9-22]); 3-dose plus infection (21% [17-25]). Older age, male sex, obesity, coexisting diseases, immunosuppressant use, smoking, and alcohol drinking were associated with lower antibody titers, whereas these associations disappeared after 3-dose, except for sex (lower in female participants) and immunosuppressant use. Antibody waning was faster in older participants, females, and alcohol drinkers after 2-dose, whereas it did not differ after 3-dose across except sex.\n\nConclusionsThe 3-dose mRNA vaccine conferred higher durable antibody titers, and previous infection further enhanced its durability. The antibody levels at a given time point and waning speed after 2-dose differed across background factors; however, these differences mostly diminished after 3-dose.",
-    "rel_num_authors": 13,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.08.515436",
+    "rel_abs": "We analyzed the dynamics of the earliest T cell response to SARS-COV-2. A wave of TCRs strongly but transiently expand during infection, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Most epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains, but not with circulating human coronaviruses. Many expanding CDR3s were also present at high precursor frequency in pre-pandemic TCR repertoires. A similar set of early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the pre-infection naive repertoire. High frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection.\n\nOne-Sentence SummaryHigh frequency naive precursors underly the rapid T cell response during the crucial early phases of acute viral infection.",
+    "rel_num_authors": 36,
     "rel_authors": [
       {
-        "author_name": "Shohei Yamamoto",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Martina Milighetti",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Yusuke Oshiro",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Yanchun Peng",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Natsumi Inamura",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Cedric C.S. Tan",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Takashi Nemoto",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Michal Mark",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Kumi Horii",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Gayathri Nageswaran",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Kaori Okudera",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Suzanne Byrne",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Maki Konishi",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Tahel Ronel",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Mitsuru Ozeki",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Thomas Peacock",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Tetsuya Mizoue",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Andreas Mayer",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Haruhito Sugiyama",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Aneesh Chandran",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Nobuyoshi Aoyanagi",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Joshua Rosenheim",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Wataru Sugiura",
-        "author_inst": "Naional Center for Global Health and Medicine"
+        "author_name": "Matthew Wheelan",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Norio Ohmagari",
-        "author_inst": "Kokuritsu Kenkyu Kaihatsu Hojin Kokuritsu Kokusai Iryo Kenkyu Center"
+        "author_name": "Xuan Yao",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Guihai Liu",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Suet Ling Felce",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Tao Dong",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alexander J Mentzer",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Julian Charles Knight",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Francois Balloux",
+        "author_inst": "Imperial College Faculty of Medicine"
+      },
+      {
+        "author_name": "Erez Greenstein",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Shlomit Reich-Zeliger",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Corinna Pade",
+        "author_inst": "Queen Mary University of London"
+      },
+      {
+        "author_name": "Joseph  M Gibbons",
+        "author_inst": "Queen Mary University of London"
+      },
+      {
+        "author_name": "Amanda Semper",
+        "author_inst": "Queen Mary University of London"
+      },
+      {
+        "author_name": "Tim Brooks",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "Ashley Otter",
+        "author_inst": "UK Health Security Agency"
+      },
+      {
+        "author_name": "Daniel M Altmann",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Rosemary J Boyton",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Mala K Maini",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Aine McKnight",
+        "author_inst": "Queen Mary University of London"
+      },
+      {
+        "author_name": "Charlotte Manisty",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Thomas A Treibel",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "James C Moon",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "- COVIDsortium Investigators",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "Mahdad Noursadeghi",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Benny Chain",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by",
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2022.11.08.515567",
@@ -135375,65 +136166,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.11.02.22281822",
-    "rel_title": "Augmenting vaccine efficacy against delta variant with Mycobacterium-w mediated modulation of NK-ADCC and TLR-MYD88 pathways",
+    "rel_doi": "10.1101/2022.11.04.22281910",
+    "rel_title": "Surveillance of COVID-19 vaccine safety among elderly persons aged 65 years and older",
     "rel_date": "2022-11-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.02.22281822",
-    "rel_abs": "Mycobacterium-w (Mw), was shown to boost adaptive natural killer (ANK) cells and protect against COVID-19 during the first wave of the pandemic. As a follow-up of the trial, 50 healthcare workers (HCW) who had received Mw in September 2020 and subsequently received at least one dose of ChAdOx1 nCoV-19 vaccine (Mw+ChAdOx1 group) were monitored for symptomatic COVID-19, during a major outbreak with the delta variant of SARS-CoV-2 (April-June, 2021), along with 201 HCW receiving both doses of the vaccine without Mw (ChAdOx1 group). Despite 48% having received just a single dose of the vaccine in Mw+ChAdOx1 group, only 2 had mild COVID-19, compared to 36 infections in the ChAdOx1 group (HR-0.46, p=0.009). Transcriptomic studies revealed an enhanced adaptive NK cell-dependent ADCC in the Mw+ChAdOx1 group, along with downregulation of TLR2-MYD88 pathway and concomitant attenuation of downstream inflammatory pathways. This might have resulted in robust protection during the pandemic with the delta variant.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.04.22281910",
+    "rel_abs": "BackgroundMonitoring safety outcomes following COVID-19 vaccination is critical for understanding vaccine safety especially when used in key populations such as elderly persons age 65 years and older who can benefit greatly from vaccination. We present new findings from a nationally representative early warning system that may expand the safety knowledge base to further public trust and inform decision making on vaccine safety by government agencies, healthcare providers, interested stakeholders, and the public.\n\nMethodsWe evaluated 14 outcomes of interest following COVID-19 vaccination using the US Centers for Medicare & Medicaid Services (CMS) data covering 30,712,101 elderly persons. The CMS data from December 11, 2020 through Jan 15, 2022 included 17,411,342 COVID-19 vaccinees who received a total of 34,639,937 doses. We conducted weekly sequential testing and generated rate ratios (RR) of observed outcome rates compared to historical (or expected) rates prior to COVID-19 vaccination.\n\nFindingsFour outcomes met the threshold for a statistical signal following Pfizer-BioNTech vaccination including pulmonary embolism (PE; RR=1.54), acute myocardial infarction (AMI; RR=1.42), disseminated intravascular coagulation (DIC; RR=1.91), and immune thrombocytopenia (ITP; RR=1.44). After further evaluation, only the RR for PE still met the statistical threshold for a signal; however, the RRs for AMI, DIC, and ITP no longer did. No statistical signals were identified following vaccination with either the Moderna or Janssen vaccines.\n\nInterpretationThis early warning system is the first to identify temporal associations for PE, AMI, DIC, and ITP following Pfizer-BioNTech vaccination in the elderly. Because an early warning system does not prove that the vaccines cause these outcomes, more robust epidemiologic studies with adjustment for confounding factors, including age and nursing home residency, are underway to further evaluate these signals. FDA strongly believes the potential benefits of COVID-19 vaccination outweigh the potential risks of COVID-19 infection.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Sarita Rani Jaiswal",
-        "author_inst": "Dharamshila Narayana Superspeciality Hospital, New Delhi-96"
+        "author_name": "Hui-Lee Wong",
+        "author_inst": "U.S. Food and Drug Administration"
       },
       {
-        "author_name": "Ashraf Saifullah",
-        "author_inst": "Dharamshila Narayana Superspeciality Hospital, New Delhi-96"
+        "author_name": "Ellen Tworkoski",
+        "author_inst": "Acumen, LLC"
       },
       {
-        "author_name": "Jaganath Arunachalam",
-        "author_inst": "Manashi Chakrabarti Foundation, New Delhi-96"
+        "author_name": "Cindy Zhou",
+        "author_inst": "U.S. Food and Drug Administration"
       },
       {
-        "author_name": "Rohit Lakhchaura",
-        "author_inst": "Dharamshila Narayana Superspeciality Hospital, New Delhi-96"
+        "author_name": "Mao Hu",
+        "author_inst": "Acumen, LLC"
       },
       {
-        "author_name": "Dhanir Tailor",
-        "author_inst": "Oregon Health & Science University, USA"
+        "author_name": "Deborah Thompson",
+        "author_inst": "U.S. Food and Drug Administration"
       },
       {
-        "author_name": "Anupama Mehta",
-        "author_inst": "Dharamshila Narayana Superspeciality Hospital, New Delhi-96"
+        "author_name": "Bradley Lufkin",
+        "author_inst": "Acumen, LLC"
       },
       {
-        "author_name": "Gitali bhagawati",
-        "author_inst": "Dharamshila Narayana Superspeciality Hospital, New Delhi-96"
+        "author_name": "Rose Do",
+        "author_inst": "Acumen, LLC"
       },
       {
-        "author_name": "Hemamalini Iyer",
-        "author_inst": "Dharamshila Narayana Superspeciality Hospital, New Delhi-96"
+        "author_name": "Laurie Feinberg",
+        "author_inst": "Acumen, LLC"
       },
       {
-        "author_name": "Subhrajit Biswas",
-        "author_inst": "Amity University, Uttar Pradesh, INDIA"
+        "author_name": "Rositsa Dimova",
+        "author_inst": "U.S. Food and Drug Administration"
       },
       {
-        "author_name": "Bakulesh M Khamar",
-        "author_inst": "Cadila Pharmaceuticals Limited"
+        "author_name": "Patricia Lloyd",
+        "author_inst": "U.S. Food and Drug Administration"
       },
       {
-        "author_name": "Sanjay V Malhotra",
-        "author_inst": "Oregon Health & Science University"
+        "author_name": "Thomas MaCurdy",
+        "author_inst": "Acumen, LLC"
       },
       {
-        "author_name": "Suparno Chakrabarti",
-        "author_inst": "Manashi Chakrabarti Foundation, New Delhi-96"
+        "author_name": "Richard Forshee",
+        "author_inst": "U.S. Food and Drug Administration"
+      },
+      {
+        "author_name": "Jeffrey Kelman",
+        "author_inst": "Centers for Medicare & Medicaid Services"
+      },
+      {
+        "author_name": "Azadeh Shoaibi",
+        "author_inst": "U.S. Food and Drug Administration"
+      },
+      {
+        "author_name": "Steven Anderson",
+        "author_inst": "U.S. Food and Drug Administration"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -136977,71 +137780,18 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.10.31.514483",
-    "rel_title": "An optimised method for recovery and quantification of laboratory generated SARS-CoV-2 aerosols by plaque assay.",
+    "rel_doi": "10.1101/2022.10.27.22281585",
+    "rel_title": "Phase-wise Impact Analysis of the Indian National Lockdown against COVID-19 Outcomes",
     "rel_date": "2022-11-01",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.31.514483",
-    "rel_abs": "We present an optimised method for the recovery of laboratory generated SARS-CoV-2 virus by plaque assay. This method allows easy incorporation into existing standard operating procedures of biological containment level 3 (BCL3) laboratories.",
-    "rel_num_authors": 13,
-    "rel_authors": [
-      {
-        "author_name": "Rachel L Byrne",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      },
-      {
-        "author_name": "Susan Gould",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      },
-      {
-        "author_name": "Thomas Edwards",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      },
-      {
-        "author_name": "Dominic Wooding",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      },
-      {
-        "author_name": "Barry Atkinson",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Ginny Moore",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Kieran Collings",
-        "author_inst": "University of Liverpool"
-      },
-      {
-        "author_name": "Cedric Boisdon",
-        "author_inst": "University of Liverpool"
-      },
-      {
-        "author_name": "Simon Maher",
-        "author_inst": "University of Liverpool"
-      },
-      {
-        "author_name": "Giancarlo Biagini",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      },
-      {
-        "author_name": "Emily R Adams",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      },
-      {
-        "author_name": "Tom Fletcher",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      },
-      {
-        "author_name": "Shaun H Pennington",
-        "author_inst": "Liverpool School of Tropical Medicine"
-      }
-    ],
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.27.22281585",
+    "rel_abs": "India was one of the most vulnerable countries to the COVID-19 pandemic considering the high transmissibility of the virus, exploding population, and fragile healthcare infrastructure. As an early counter, India implemented a country-wide lockdown and we aimed to study the impact of 4 lockdowns and 2 unlock phases on 6 outcomes: case growth, death count, effective reproduction number, mobility, hospitalization, and infection growth by two methods: interrupted time series (ITR) analysis and Bayesian causal impact analysis (BCIA) for nationals and sub-national levels. We observed that the effects are heterogeneous across outcomes and phases. For example, ITR revealed the effect to be significant for all the outcomes across all phases except for case growth in phase 1. BCIA revealed that the causal effect of all four lockdown phases was positive for deaths. At the state level, Maharashtra benefited from the lockdown in comparison to Tripura. Effects of lockdown phases 3 and 4 on death count were correlated (R=0.70, p<0.05) depicting the  extended impact of phase-wise interventions. We observed the highest impact on mobility followed by hospitalization, infection growth, effective reproduction number, case growth, and death count. For optimal impact, lockdown needs to be implemented at the sub-national level considering various demographic variations between states.",
+    "rel_num_authors": 0,
+    "rel_authors": null,
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "molecular biology"
+    "license": "",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.10.31.22281748",
@@ -138407,23 +139157,23 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.10.27.22281632",
-    "rel_title": "Application of a Multiplicative Cascade Model to Detect the Early Signs of SARS-CoV-2 Infection Using Heart Rate Data",
-    "rel_date": "2022-10-30",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.27.22281632",
-    "rel_abs": "BackgroundWrist-worn devices can keep track of a persons daily health status, including those likely to become infected with the SARS-CoV-2 virus. Technological solutions using mobile devices are being developed to predict the time course of COVID-19.\n\nObjectiveIn this proof-of-concept study, we use heart rate data to detect the first sign of infection in people who have been diagnosed with COVID-19 and to monitor the time-course of the illness.\n\nMethodsThe heart-rate data were analysed using a multiplicative cascade driven by a Gaussian process. This provides two parameters, mean and standard deviation, which when combined with similar parameters estimated from control series, provide a Health Index.\n\nResultsFor 90% of 31 cases, the Health Index tracked COVID-19 infection with the virus and subsequent recovery. The first-sign of COVID-19 was detected on average nine days before symptoms were reported.\n\nConclusionsEarly detection of COVID-19 may lead to a reduction in the spread of the virus. The Heath Indexs potential use for the early detection of complications arising from Long COVID would be an important innovation.",
+    "rel_doi": "10.1101/2022.10.27.514012",
+    "rel_title": "Vitamin D deficiency and SARS-CoV-2 infection: Big-data analysis from March 2020 to March 2021. D-COVID study",
+    "rel_date": "2022-10-28",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.27.514012",
+    "rel_abs": "BackgroundVitamin D has been proposed to have immunomodulatory functions and therefore play a role in coronavirus infection (COVID-19). However, there is no conclusive evidence on its impact on COVID-19 infection and evolution.\n\nObjectiveTo study the association between COVID-19 infection and vitamin D deficiency in patients of a terciary university hospital. To investigate the clinical evolution and prognosis of patients with COVID-19 and vitamin D deficiency.\n\nMethodsUsing big-data analytics and artificial intelligence through the SAVANA Manager clinical platform, we analysed clinical data from patients with COVID-19 atended in a terciary university hospital from March 2020 to March 2021.\n\nResultsOf the 143.157 analysed patients, 36.261 subjects had COVID-19 infection (25.33%); during this period; of these 2588 had vitamin D deficiency (7.14%). Among subjects with COVID-19 and vitamin D deficiency, there was a higher proportion of women OR 1.45 [95% CI 1.33-1.57], adults older than 80 years OR 2.63 [95%CI 2.38-2.91], people living in nursing homes OR 2.88 [95%CI 2.95-3.45] and walking dependence OR 3.45 [95%CI 2.85-4.26]. Regarding clinical course, a higher number of subjects with COVID-19 and vitamin D deficiency required hospitalitation OR 2.41 [95%CI 2.22-2-61], intensive unit care (ICU) OR 2.22 [95% CI 1.64-3.02], had a longer mean hospital stay 3.94 (2.29) p=0.02 and higher mortality OR 1.82 [95%CI 1.66-2.01].)\n\nConclusionLow serum 25 (OH) Vitamin-D level was significantly associated with a worse clinical evolution and prognosis of COVID-19 infection. We found a higher proportion of institutionalised and dependent people over 80 years of age among patients with COVID-19 and vitamin D deficiency.",
     "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Rachel Ann Heath",
-        "author_inst": "School of Psychological Sciences, University of Newcastle, Australia"
+        "author_name": "Noemi Anguita",
+        "author_inst": "Hospital Infanta Sofia: Hospital Universitario Infanta Sofia"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by",
+    "type": "new results",
+    "category": "pathology"
   },
   {
     "rel_doi": "10.1101/2022.10.25.22281469",
@@ -140785,71 +141535,47 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2022.10.25.22281247",
-    "rel_title": "Occupational risk of SARS-CoV-2 infection: a nationwide register-based study of the Danish workforce during the Covid-19 pandemic 2020-21",
+    "rel_doi": "10.1101/2022.10.24.22281104",
+    "rel_title": "Which curve are we flattening? The disproportionate impact of COVID-19 among economically marginalized communities in Ontario, Canada, was unchanged from wild-type to omicron",
     "rel_date": "2022-10-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.25.22281247",
-    "rel_abs": "ObjectivesMost earlier studies on occupational risk of Covid-19 covering the entire workforce are based on relatively rare outcomes such as hospital admission and mortality. This study examines the incidence of SARS-CoV-2 infection by occupational group based upon real-time polymerase chain reaction tests (RT-PCR).\n\nMethodsThe cohort includes 2.4 million Danish employees, 20-69 years of age. All data were retrieved from public registries. The sex-specific incidence rate ratios (IRR) of first-occurring positive RT-PCR test from week 8 of 2020 through week 50 of 2021 were computed by Poisson regression for each 4-digit DISCO-08 job code with more than 100 employees (337 in men; 297 in women). Occupational groups with low risk of workplace infection according to a job exposure matrix constituted the reference group. Risk estimates were adjusted by demographic, social and health characteristics including household size, completed Covid-19 vaccination, pandemic wave and occupation-specific frequency of testing.\n\nResultsIRRs of SARS-CoV-2 infection were elevated in 34 occupations comprising 12 % of male employees and 45 occupations comprising 41 % of female employees. All IRR estimates were below 2.0. Decreased IRRs were observed in 85 occupations in men but none in women.\n\nDiscussionWe observed a modestly increased risk of SARS-CoV-2 infection among employees in numerous occupations indicating a large potential for preventive actions, especially in the female workforce. Cautious interpretation of observed risk in specific occupations is needed because of methodological issues inherent in analyses of RT-PCR-test results and because of multiple statistical tests.\n\nWHAT IS ALREADY KNOW ABOUT THIS TOPIC?O_LIEpidemiological studies suggest that the workplace contribute to the Covid-19 pandemic\nC_LIO_LIResults are mostly based upon studies of less frequent outcomes as Covid-19 morbidity or mortality which limits inference about risk in specific occupations\nC_LI\n\nWHAT THIS STUDY ADDSO_LIThe risk of Covid-19 infection was increased in 34 of 337 occupations in men and in 45 of 297 occupations in women\nC_LIO_LISome 12% of the Danish male workforce and 41% of the female workforce are at increased risk of Covid-19 infection\nC_LI\n\nHOW THIS RESEARCH MIGHT AFFECT RESEARCH, PRACTICE OR POLICY?O_LIPreventive actions targeting the workplace may contribute substantially to alleviate disease occurrence in the ongoing Covid-19 and similar future pandemics.\nC_LI",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.24.22281104",
+    "rel_abs": "Economically marginalized communities have faced disproportionately higher risks for infection and death from COVID-19 across Canada. It was anticipated that health disparities would dissipate over time and during subsequent waves. We used person-level surveillance and neighbourhood-level income data to explore, using Lorenz curves and Gini coefficients, magnitude of inequalities in COVID-19 hospitalizations and deaths over five waves of COVID-19 in Ontario, Canada (population 14 million) between February 26, 2020 and February 28, 2022. We found that despite attempts at equity-informed policies alongside fluctuating levels of public health measures, inequalities in hospitalizations and deaths by income remained at levels observed during the first wave - prior to vaccination, discussion or implementation of equity-informed policies - and despite rising levels of hybrid immunity. There was no change in the magnitude of inequalities across all waves evaluated. Our findings indicate that interventions did not sufficiently address differential exposure risks amplified at the intersections of household crowding and size, workplace exposures, and systemic barriers to prevention and care (including access to therapeutics). Equity and effectiveness of programs are inherently linked and ongoing evaluation of both is central to inform the public health response to future waves of COVID-19 and other rapidly emergent pandemics.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Jens Peter Ellekilde Bonde",
-        "author_inst": "Department of Occupational and Environmental Medicine, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Luise Moelenberg Begtrup",
-        "author_inst": "Department of Occupational and Environmental Medicine, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Johan Hoej Jensen",
-        "author_inst": "Department of Occupational and Environmental Medicine, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Esben Meulengracht Flachs",
-        "author_inst": "Department of Occupational and Environmental Medicine, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Vivi Schlunssen",
-        "author_inst": "Department of Public Health, Research Unit for Environment, Occupation and Health, Danish Ramazzini Centre, Aarhus University, Aarhus, Denmark"
-      },
-      {
-        "author_name": "Henrik Albert Kolstad",
-        "author_inst": "Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Denmark"
-      },
-      {
-        "author_name": "Kristina Jakobsson",
-        "author_inst": "School of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Sweden"
+        "author_name": "Huiting Ma",
+        "author_inst": "Unity Health Toronto"
       },
       {
-        "author_name": "Christel Nielsen",
-        "author_inst": "Division of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden"
+        "author_name": "Adrienne K Chan",
+        "author_inst": "Sunnybrook Health Sciences"
       },
       {
-        "author_name": "Kerstin Nielsson",
-        "author_inst": "Division of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden"
+        "author_name": "Stefan Baral",
+        "author_inst": "JHSPH"
       },
       {
-        "author_name": "Lars Rylander",
-        "author_inst": "Division of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden"
+        "author_name": "Christine Fahim",
+        "author_inst": "Unity Health Toronto"
       },
       {
-        "author_name": "Andreas Vilhelmsson",
-        "author_inst": "Division of Occupational and Environmental Medicine, Department of Laboratory Medicine, Lund University, Lund, Sweden"
+        "author_name": "Sharon Straus",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Kajsa Kirstine Ugelvig Petersen",
-        "author_inst": "Department of Occupational and Environmental Medicine, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark"
+        "author_name": "Beate Sander",
+        "author_inst": "University Health Network"
       },
       {
-        "author_name": "Sandra Soegaard Toettenborg",
-        "author_inst": "Department of Occupational and Environmental Medicine, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark"
+        "author_name": "Sharmistha Mishra",
+        "author_inst": "University of Toronto"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.10.25.513760",
@@ -143087,83 +143813,79 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.10.21.22281171",
-    "rel_title": "Comparison of the risk of hospitalisation among BA.1 and BA.2 COVID-19 cases treated with Sotrovimab in the community in England",
-    "rel_date": "2022-10-22",
+    "rel_doi": "10.1101/2022.10.19.22281256",
+    "rel_title": "Changes in Treatment and Severity of Multisystem Inflammatory Syndrome in Children: An EHR-based cohort study from the RECOVER program",
+    "rel_date": "2022-10-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.21.22281171",
-    "rel_abs": "ObjectivesSotrovimab is one of several therapeutic agents that have been licensed to treat people at risk of severe outcomes following COVID-19 infection. However, there are concerns that it has reduced efficacy to treat people with the BA.2 sub-lineage of the Omicron (B.1.1.529) SARS-CoV-2 variant. We compared individuals with the BA.1 or BA.2 sub-lineage of the Omicron variant treated Sotrovimab in the community to assess their risk of hospital admission.\n\nMethodsWe performed a retrospective cohort study of individuals treated with Sotrovimab in the community and either had BA.1 or BA.2 variant classification.\n\nResultsUsing a Stratified Cox regression model it was estimated that the hazard ratios (HR) of hospital admission with a length of stay of two or more days was 1.17 for BA.2 compared to BA.1 (95% CI 0.74-1.86) and for such admissions where COVID-19 ICD-10 codes was recorded the HR was 0.98 (95% CI 0.58-1.65).\n\nConclusionThese results suggest that the risk of hospital admission is similar between BA.1 and BA.2 cases treated with Sotrovimab in the community.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.19.22281256",
+    "rel_abs": "ObjectivesThe purpose of this study was to examine how the treatment and severity of multisystem inflammatory syndrome in children (MIS-C) has changed over more than two years of the COVID-19 pandemic in the United States.\n\nMethodsElectronic health record data were retrieved from the PEDSnet network as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative. The study included data for children ages 0 to 20 years hospitalized for MIS-C from March 1, 2020 through July 20, 2022. Descriptive statistics for MIS-C treatments and laboratory results were computed for three time periods of interest: March 1, 2020 - May 31, 2021 (pre-Delta); June 1 - December 31, 2021 (primarily Delta); January 1 - July 20, 2022 (primarily Omicron). Standardized differences measured the effect size of the difference between Omicron and pre-Omicron cohorts.\n\nResultsThe study included 946 children with a diagnosis of MIS-C. The largest differences in the Omicron period compared to prior years were decreases in the percentage of children with abnormal troponin (effect size = 0.40), abnormal lymphocytes (effect size = 0.33), and intensive care unit (ICU) visits (effect size = 0.34). There were small decreases in the Omicron period for the majority of treatments and abnormal laboratory measurements examined, including infliximab, anticoagulants, furosemide, aspirin, IVIG without steroids, echocardiograms, mechanical ventilation, platelets, ferritin, and sodium.\n\nConclusionsThis study provides the first evidence that the severity of MIS-C declined in the first half of the year 2022 relative to prior years of the COVID-19 pandemic in the United States.\n\nArticle SummaryUsing electronic health record data for 946 children, we found evidence that the severity of MIS-C declined during the first half of the year 2022.\n\nWhats Known on This SubjectThe clinical management of multisystem inflammatory syndrome in children (MIS-C) has commonly included intravenous immune globulin, steroids, and non-steroidal anti-inflammatory agents. Many children with MIS-C have required intravenous fluids, inotropes and vasopressors, and in some cases, mechanical ventilation.\n\nWhat This Study AddsRecent decreases in the percentage of children with MIS-C that have abnormal troponin, abnormal lymphocytes, or intensive care unit visits provide evidence that the severity of MIS-C has declined in the first half of the year 2022.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Katie Harman",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Sophie G Nash",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Julia Schuchard",
+        "author_inst": "Children's Hospital of Philadelphia"
       },
       {
-        "author_name": "Harriet H Webster",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Deepika Thacker",
+        "author_inst": "Nemours Childrens Health"
       },
       {
-        "author_name": "Natalie Groves",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Ryan Webb",
+        "author_inst": "Children's Hospital of Philadelphia"
       },
       {
-        "author_name": "Jo Hardstaff",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Charles Bailey",
+        "author_inst": "Children's Hospital of Philadelphia"
       },
       {
-        "author_name": "Jessica Bridgen",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Tellen D Bennett",
+        "author_inst": "University of Colorado School of Medicine"
       },
       {
-        "author_name": "Paula B Blomquist",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Jonathan D Cogen",
+        "author_inst": "Seattle Childrens Hospital"
       },
       {
-        "author_name": "Russell Hope",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Ravi Jhaveri",
+        "author_inst": "Ann & Robert H. Lurie Childrens Hospital of Chicago"
       },
       {
-        "author_name": "Efejiro Ashano",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Pei-Ni Jone",
+        "author_inst": "Childrens Hospital Colorado"
       },
       {
-        "author_name": "Richard Myers",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Grace M Lee",
+        "author_inst": "Stanford University School of Medicine"
       },
       {
-        "author_name": "Sakib Rokadiya",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Mitchell Maltenfort",
+        "author_inst": "Children's Hospital of Philadelphia"
       },
       {
-        "author_name": "Susan Hopkins",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Asuncion Mejias",
+        "author_inst": "Nationwide Childrens Hospital"
       },
       {
-        "author_name": "Colin S Brown",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Colin M Rogerson",
+        "author_inst": "Indiana University School of Medicine"
       },
       {
-        "author_name": "Meera Chand",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Grant S Schulert",
+        "author_inst": "Cincinnati Childrens Hospital Medical Center"
       },
       {
-        "author_name": "Gavin Dabrera",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Eneida A Mendonca",
+        "author_inst": "Cincinnati Childrens Hospital Medical Center"
       },
       {
-        "author_name": "Simon Thelwall",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "- RECOVER consortium",
+        "author_inst": "-"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2022.10.20.22281298",
@@ -145133,115 +145855,75 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.10.20.512999",
-    "rel_title": "Altered infective competence of the human gut microbiome in COVID-19",
+    "rel_doi": "10.1101/2022.10.19.512957",
+    "rel_title": "SARS-CoV-2 infected cells sprout actin-rich filopodia that facilitate viral invasion",
     "rel_date": "2022-10-20",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.20.512999",
-    "rel_abs": "ObjectivesInfections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19.\n\nDesignWe used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group.\n\nResultsWe found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19 positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19 positive individuals compared to healthy controls.\n\nConclusionOur analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients.",
-    "rel_num_authors": 24,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.19.512957",
+    "rel_abs": "Emerging COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a great threat to human health and economics. Although SARS-CoV-2 entry mechanism has been explored, little is known about how SARS-CoV-2 regulates the host cell remodeling to facilitate virus invasion process. Here we unveil that SARS-CoV-2 boosts and repurposes filopodia for entry to the target cells. Using SARS-CoV-2 virus-like particle (VLP), real-time live-cell imaging and simulation of active gel model, we reveal that VLP-induced Cdc42 activation leads to the formation of filopodia, which reinforce the viral entry to host cells. By single-particle tracking and sparse deconvolution algorithm, we uncover that VLP particles utilize filopodia to reach the entry site in two patterns,  surfing and  grabbing, which are more efficient and faster than entry via flat plasma membrane regions. Furthermore, the entry process via filopodia is dependent on the actin cytoskeleton and actin-associated proteins fascin, formin, and Arp2/3. Importantly, either inhibition the actin cross-linking protein fascin or the active level of Cdc42 could significantly hinders both the VLP and the authentic SARS-CoV-2 entry. Together, our results highlight that the spatial-temporal regulation of the actin cytoskeleton by SARS-CoV-2 infection makes filopodia as a  highway for virus entry, which emerges as an antiviral target.\n\nSignificance StatementRevealing the mechanism of SARS-CoV-2 invasion is of great significance to explain its high pathogenic and rapid transmission in the world. We discovered a previously unknown route of SARS-CoV-2 entry. SARS-CoV-2 virus-like particles boost cellular filopodia formation by activating Cdc42. Using state-of-art-technology, we spatial-temporally described how virus utilize filopodia to enter the target cell in two modes:  surfing and  grabbing. Filopodia can directly transport the virus to endocytic hot spots to avoid the virus from disorderly searching on the plasma membrane. Our study complements current knowledge of SARS-CoV-2 that filopodia and its components not only play an important role in virus release and cell-cell transmission, but also in the entry process, and provides several potential therapeutic targets for SARS-CoV-2.\n\nHighlightsO_LISARS-CoV-2 VLP infection promotes filopodia formation by activating Cdc42\nC_LIO_LISARS-CoV-2 VLP utilizes filopodia to enter target cell via two modes,  surfing and  grabbing\nC_LIO_LIFilopodia disruption compromises the invasion of both VLP and authentic SARS-CoV-2\nC_LI",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Laura de Nies",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Valentina Galata",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Camille Martin-Gallausiaux",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Milena Despotovic",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Susheel Bhanu Busi",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Chantal J. Snoeck",
-        "author_inst": "Luxembourg Institute of Health"
-      },
-      {
-        "author_name": "Lea Delacour",
-        "author_inst": "University of Luxembourg"
+        "author_name": "Yaming Jiu",
+        "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences, China"
       },
       {
-        "author_name": "Deepthi Poornima Budagavi",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Cedric Christian Laczny",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Janine Habier",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Paula-Cristina Lupu",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Rashi Halder",
-        "author_inst": "University of Luxembourg"
+        "author_name": "Yue Zhang",
+        "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Joelle V. Fritz",
-        "author_inst": "Luxembourg Institute of Health"
+        "author_name": "Xiaowei Zhang",
+        "author_inst": "Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Taina Marques",
-        "author_inst": "University of Luxembourg"
+        "author_name": "Zhongyi Li",
+        "author_inst": "Tsinghua University"
       },
       {
-        "author_name": "Estelle Sandt",
-        "author_inst": "Luxembourg Institute of Health"
+        "author_name": "Hui Yang",
+        "author_inst": "Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Soumyabrata Ghosh",
-        "author_inst": "University of Luxembourg"
+        "author_name": "Daijiao Tang",
+        "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Venkata Satagopam",
-        "author_inst": "University of Luxembourg"
+        "author_name": "Shuangshuang Zhao",
+        "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences"
       },
       {
-        "author_name": "- CON-VINCE Consortium",
-        "author_inst": "-"
+        "author_name": "Qian Zhang",
+        "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Rejko Kruger",
-        "author_inst": "Luxembourg Institute of Health"
+        "author_name": "Bo Li",
+        "author_inst": "Tsinghua University"
       },
       {
-        "author_name": "Guy Fagherazzi",
-        "author_inst": "Luxembourg Institute of Health"
+        "author_name": "Pekka Lappalainen",
+        "author_inst": "University of Helsinki"
       },
       {
-        "author_name": "Markus Ollert",
-        "author_inst": "Luxembourg Institute of Health"
+        "author_name": "Zongqiang Cui",
+        "author_inst": "Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Feng Q. Hefeng",
-        "author_inst": "Luxembourg Institute of Health"
+        "author_name": "Huisheng Liu",
+        "author_inst": "Guangzhou Laboratory"
       },
       {
-        "author_name": "Patrick May",
-        "author_inst": "University of Luxembourg"
+        "author_name": "Haoyu Li",
+        "author_inst": "Harbin Institute of Technology"
       },
       {
-        "author_name": "Paul Wilmes",
-        "author_inst": "University of Luxembourg"
+        "author_name": "Weisong Zhao",
+        "author_inst": "Harbin Institute of Technology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "cell biology"
   },
   {
     "rel_doi": "10.1101/2022.10.18.22281202",
@@ -147219,73 +147901,69 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.10.17.22281168",
-    "rel_title": "A systematic review on outbreaks of COVID-19 among children within households in the European region",
+    "rel_doi": "10.1101/2022.10.17.22281175",
+    "rel_title": "Reconstruction of SARS-CoV-2 outbreaks in a primary school using epidemiological and genomic data",
     "rel_date": "2022-10-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.17.22281168",
-    "rel_abs": "ObjectivesThis systematic review aims to identify the secondary attack rates (SAR) to adults and other children when children are the index cases within household settings.\n\nMethodsThis literature review assessed European-based studies published in Medline and Embase between January 2020 and January 2022 that assessed the secondary transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within household settings. The inclusion criteria were based on the PEO framework (P-Population, E-Exposure, O-Outcome) for systematic reviews. Thus, the study population was restricted to humans within the household setting in Europe (population), in contact with pediatric index cases 1-17 years old (exposure) that led to the transmission of SARS-CoV-2 reported as either a SAR or the probability of onward infection (outcome).\n\nResultsOf 1,819 studies originally identified, 25 met the inclusion criteria. Overall, the SAR ranged from 13% to 75% in 23 studies, while there was no evidence of secondary transmission from children to other household members in two studies. Evidence indicated that asymptomatic SARS-CoV-2 index cases also have a lower SAR than those with symptoms and that younger children may have a lower SAR than adolescents (>12 years old) within household settings.\n\nConclusionsSARS-CoV-2 secondary transmission from paediatric index cases ranged from 0% to 75%, within household settings between January 2020 and January 2022, with differences noted by age and by symptomatic/asymptomatic status of the index case. Given the anticipated endemic circulation of SARS-CoV-2, continued monitoring and assessment of household transmission is necessary.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.17.22281175",
+    "rel_abs": "Mathematical modeling studies have shown that repetitive screening can be used to mitigate SARS-CoV-2 transmission in primary schools while keeping schools open. However, not much is known about how transmission progresses within schools and whether there is a risk of importation to households. In this study, we reconstructed outbreaks observed during a prospective study in a primary school and associated households in Liege (Belgium) during the academic year 2020-2021. In addition we performed a simulation study to investigate how the accuracy of estimated weekly positivity rates in a school depends on the proportion of a school that is sampled in a repetitive screening strategy. We found that transmission occurred mainly within the school environment and that observed positivity rates are a good approximation to the true positivity rate, especially in children. This study shows that it is worthwile to implement repetitive testing in school settings, which in addition to reducing infections can lead to a better understanding of the extent of transmission in schools during a pandemic and importation risk at the community level.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Constantine Vardavas",
-        "author_inst": "School of Medicine, University of Crete, Heraklion, Crete, Greece"
-      },
-      {
-        "author_name": "Katerina Nikitara",
-        "author_inst": "University of Crete"
+        "author_name": "C\u00e9cile Kremer",
+        "author_inst": "I-BioStat, Data Science Institute, Hasselt University"
       },
       {
-        "author_name": "Katerina Aslanoglou",
-        "author_inst": "School of Medicine, University of Crete, Heraklion, Crete, Greece"
+        "author_name": "Andrea Torneri",
+        "author_inst": "I-BioStat, Data Science Institute, Hasselt University"
       },
       {
-        "author_name": "Apostolos Kamekis",
-        "author_inst": "School of Medicine, University of Crete, Heraklion, Crete, Greece"
+        "author_name": "Pieter Jules Karel Libin",
+        "author_inst": "I-BioStat, Data Science Institute, Hasselt University"
       },
       {
-        "author_name": "Nithya Ramesh",
-        "author_inst": "Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Harvard University, Boston, MA, USA"
+        "author_name": "C\u00e9cile Meex",
+        "author_inst": "Department of Clinical Microbiology, University of Liege"
       },
       {
-        "author_name": "Emmanouil Symvoulakis",
-        "author_inst": "School of Medicine, University of Crete, Heraklion, Crete, Greece"
+        "author_name": "Marie-Pierre Hayette",
+        "author_inst": "Department of Clinical Microbiology, University of Liege"
       },
       {
-        "author_name": "Israel Agaku",
-        "author_inst": "Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Harvard University, Boston, MA, USA"
+        "author_name": "S\u00e9bastien Bontems",
+        "author_inst": "Department of Clinical Microbiology, University of Liege"
       },
       {
-        "author_name": "Revati Phalkey",
-        "author_inst": "Centre for Evidence Based Healthcare, Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, UK"
+        "author_name": "Keith Durkin",
+        "author_inst": "Laboratory of Human Genetics, GIGA-Institute, University of Liege"
       },
       {
-        "author_name": "Jo Leonardi-Bee",
-        "author_inst": "Centre for Evidence Based Healthcare, Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, UK"
+        "author_name": "Maria Artesi",
+        "author_inst": "Laboratory of Human Genetics, GIGA-Institute, University of Liege"
       },
       {
-        "author_name": "Esteve Fernandez",
-        "author_inst": "Catalan Institute of Oncology, Barcelona, Spain"
+        "author_name": "Vincent Bours",
+        "author_inst": "Laboratory of Human Genetics, GIGA-Institute, University of Liege"
       },
       {
-        "author_name": "Orla Condell",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Solna, Sweden"
+        "author_name": "Philippe Lemey",
+        "author_inst": "Department of Microbiology, Immunology and Transplantation, REGA Institute, KU Leuven"
       },
       {
-        "author_name": "Favelle Lamb",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Solna, Sweden"
+        "author_name": "Gilles Darcis",
+        "author_inst": "Department of Infectious Diseases, Liege University Hospital"
       },
       {
-        "author_name": "Charlotte Deogan",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Solna, Sweden"
+        "author_name": "Niel Hens",
+        "author_inst": "I-BioStat, Data Science Institute, Hasselt University"
       },
       {
-        "author_name": "Jonathan E Suk",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC), Solna, Sweden"
+        "author_name": "Christelle Meuris",
+        "author_inst": "Department of Infectious Diseases, Liege University Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -149105,169 +149783,233 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.10.11.22280868",
-    "rel_title": "High titers of infectious SARS-CoV-2 in COVID-19 corpses",
+    "rel_doi": "10.1101/2022.10.10.22280850",
+    "rel_title": "Anti-SARS-CoV-2 antibody containing plasma improves outcome in patients with hematologic or solid cancer and severe COVID-19 via increased neutralizing antibody activity. A randomized clinical trial",
     "rel_date": "2022-10-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.11.22280868",
-    "rel_abs": "BackgroundThe prolonged presence of infectious severe acute respiratory syndrome coronavirus (SARS-CoV-2) in deceased coronavirus disease 2019 (COVID-19) patients has been reported. However, infectious virus titers have not been determined. Such information is important for public health, death investigation, and handling corpses.\n\nAimThe aim of this study was to assess the level of SARS-CoV-2 infectivity in COVID-19 corpses.\n\nMethodsWe collected 11 nasopharyngeal swabs and 19 lung tissue specimens from 11 autopsy cases with COVID-19 in 2021. We then investigated the viral genomic copy number by real-time reverse transcription-polymerase chain reaction and infectious titers by cell culture and virus isolation.\n\nResultsInfectious virus was present in 6 of 11 (55%) cases, 4 of 11 (36%) nasopharyngeal swabs, and 9 of 19 (47%) lung specimens. The virus titers ranged from 6.00E + 01 plaque-forming units (PFU)/mL to 2.09E + 06 PFU/g. In all cases in which an infectious virus was found, the time from death to discovery was within 1 day and the longest postmortem interval was 13 days.\n\nConclusionCOVID-19 corpses may have high titers of infectious virus after a long postmortem interval (up to 13 days). Therefore, appropriate infection control measures must be taken when handling corpses.",
-    "rel_num_authors": 38,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.10.22280850",
+    "rel_abs": "Cancer patients are at high risk of severe COVID-19 with high morbidity and mortality. Further, impaired humoral response renders SARS-CoV-2 vaccines less effective and treatment options are scarce. Randomized trials using convalescent plasma are missing for high-risk patients. Here, we performed a multicenter trial (https://www.clinicaltrialsregister.eu/ctr-search/trial/2020-001632-10/DE) in hospitalized patients with severe COVID-19 within four risk groups (1, cancer; 2, immunosuppression; 3, lab-based risk factors; 4, advanced age) randomized to standard of care (CONTROL) or standard of care plus convalescent/vaccinated anti-SARS-CoV-2 plasma (PLASMA). For the four groups combined, PLASMA did not improve clinically compared to CONTROL (HR 1.29; p=0.205). However, cancer patients experienced shortened median time to improvement (HR 2.50, p=0.003) and superior survival in PLASMA vs. CONTROL (HR 0.28; p=0.042). Neutralizing antibody activity increased in PLASMA but not in CONTROL cancer patients (p=0.001). Taken together, convalescent/vaccinated plasma may improve COVID-19 outcome in cancer patients unable to intrinsically generate an adequate immune response.",
+    "rel_num_authors": 54,
     "rel_authors": [
       {
-        "author_name": "Hisako Saitoh",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Claudia M Denkinger",
+        "author_inst": "Division of Infectious Disease and Tropical Medicine, Department of Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany, German Center for "
       },
       {
-        "author_name": "Yuko Tagawa Sakai",
-        "author_inst": "Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, The University of Tokyo"
+        "author_name": "Maike Janssen",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Sayaka Nagasawa",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Ulrike Schaekel",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Suguru Torimitsu",
-        "author_inst": "Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Julia Gall",
+        "author_inst": "NCT-Trial Center, National Center of Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany"
       },
       {
-        "author_name": "Kazumi Kubota",
-        "author_inst": "Department of Healthcare Information Management, The University of Tokyo Hospital"
+        "author_name": "Albrecht Leo",
+        "author_inst": "Institute for Clinical Transfusion Medicine and Cell Therapy Heidelberg, Heidelberg"
       },
       {
-        "author_name": "Yuichiro Hirata",
-        "author_inst": "Department of Pathology, National Institute of Infectious Diseases"
+        "author_name": "Patrick Stelmach",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Kiyoko Horimoto Iwatsuki",
-        "author_inst": "Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, The University of Tokyo"
+        "author_name": "Stefan Fabian Weber",
+        "author_inst": "Division of Infectious Disease and Tropical Medicine, Department of Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Ayumi Motomura",
-        "author_inst": "Department of Legal Medicine, International University of Health and Welfare"
+        "author_name": "Johannes Krisam",
+        "author_inst": "Institute for Medical Biometry and Informatics, Ruprecht-Karls University Heidelberg, Heidelberg, Germany"
       },
       {
-        "author_name": "Namiko Ishii",
-        "author_inst": "Department of Legal Medicine, International University of Health and Welfare"
+        "author_name": "Lukas Baumann",
+        "author_inst": "Institute for Medical Biometry and Informatics, Ruprecht-Karls University Heidelberg, Heidelberg, Germany"
       },
       {
-        "author_name": "Keisuke Okaba",
-        "author_inst": "Department of Legal Medicine, International University of Health and Welfare"
+        "author_name": "Jacek Stermann",
+        "author_inst": "Institute for Medical Biometry and Informatics, Ruprecht-Karls University Heidelberg, Heidelberg, Germany"
       },
       {
-        "author_name": "Kie Horioka",
-        "author_inst": "Department of Legal Medicine, International University of Health and Welfare"
+        "author_name": "Uta Merle",
+        "author_inst": "Department of Internal Medicine IV, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Hiroyuki Abe",
-        "author_inst": "Department of Pathology, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Markus A Weigand",
+        "author_inst": "Department of Anaesthesiology, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Masako Ikemura",
-        "author_inst": "Department of Pathology, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Christian Nusshag",
+        "author_inst": "Department of Nephrology, University of Heidelberg, Heidelberg, Germany"
       },
       {
-        "author_name": "Hirofumi Rokutan",
-        "author_inst": "Department of Pathology, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Lars Bullinger",
+        "author_inst": "Department of Hematology, Oncology and Tumor Immunology, Charite University Medicine, Campus Virchow Clinic, Berlin, Germany"
       },
       {
-        "author_name": "Munetoshi Hinata",
-        "author_inst": "Department of Pathology, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Jens-Florian Schrezenmeier",
+        "author_inst": "Department of Hematology, Oncology and Tumor Immunology, Charite University Medicine, Campus Virchow Clinic, Berlin, Germany"
       },
       {
-        "author_name": "Akiko Iwasaki",
-        "author_inst": "Department of Pathology, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Martin Bornhaeuser",
+        "author_inst": "Department of Internal Medicine I, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden, Germany"
+      },
+      {
+        "author_name": "Nael Alakel",
+        "author_inst": "Department of Internal Medicine I, University Hospital and Faculty of Medicine Carl Gustav Carus of TU Dresden, Dresden, Germany"
       },
       {
-        "author_name": "Yoichi Yasunaga",
-        "author_inst": "Department of Pathology, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Oliver Witzke",
+        "author_inst": "Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Germany"
       },
       {
-        "author_name": "Makoto Nakajima",
-        "author_inst": "Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Timo Wolf",
+        "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany"
       },
       {
-        "author_name": "Rutsuko Yamaguchi",
-        "author_inst": "Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Maria JGT Vehreschild",
+        "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany"
       },
       {
-        "author_name": "Shigeki Tsuneya",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Stefan Schmiedel",
+        "author_inst": "I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany"
       },
       {
-        "author_name": "Kei Kira",
-        "author_inst": "Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Marylyn M Addo",
+        "author_inst": "I. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; University Medical Center Hamburg-Eppendorf, Institute for Infection R"
       },
       {
-        "author_name": "Susumu Kobayashi",
-        "author_inst": "Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Felix Herth",
+        "author_inst": "Pneumology and Critical Care Medicine, Thoraxklinik, University of Heidelberg, Heidelberg, Germany"
       },
       {
-        "author_name": "Go Inokuchi",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Michael Kreuter",
+        "author_inst": "Center for Interstitial and Rare Lung Diseases, Thoraxklinik, University of Heidelberg, German Center for Lung Research (DZL), Heidelberg, Germany"
       },
       {
-        "author_name": "Fumiko Chiba",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Phil-Robin Tepasse",
+        "author_inst": "Department of Medicine B, Gastroenterology and Hepatology, University Hospital Muenster, Muenster, Germany"
       },
       {
-        "author_name": "Yumi Hoshioka",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Bernd Hertenstein",
+        "author_inst": "Medical Department I, Klinikum Bremen-Mitte, Bremen, Germany"
       },
       {
-        "author_name": "Aika Mori",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Mathias Haenel",
+        "author_inst": "Department of Internal Medicine III, Klinikum Chemnitz gGmbH, Chemnitz, Germany"
       },
       {
-        "author_name": "Isao Yamamoto",
-        "author_inst": "Department of Forensic Medicine, Kanagawa Dental University"
+        "author_name": "Anke Morgner",
+        "author_inst": "Department of Internal Medicine III, Klinikum Chemnitz gGmbH, Chemnitz, Germany"
       },
       {
-        "author_name": "Kimiko Nakagawa",
-        "author_inst": "Department of Forensic Medicine, Kanagawa Dental University"
+        "author_name": "Michael Kiehl",
+        "author_inst": "Department I of Internal Medicine, Frankfurt (Oder) General Hospital, Frankfurt/Oder, Germany"
       },
       {
-        "author_name": "Harutaka Katano",
-        "author_inst": "Department of Pathology, National Institute of Infectious Diseases"
+        "author_name": "Olaf Hopfer",
+        "author_inst": "Department I of Internal Medicine, Frankfurt (Oder) General Hospital, Frankfurt/Oder, Germany"
       },
       {
-        "author_name": "Shun Iida",
-        "author_inst": "Department of Pathology, National Institute of Infectious Diseases"
+        "author_name": "Mohammad-Amen Wattad",
+        "author_inst": "Department of Hematology, Oncology, Palliative Care and Stem Cell Transplantation, Klinikum Hochsauerland GmbH, Meschede, Germany"
       },
       {
-        "author_name": "Tadaki Suzuki",
-        "author_inst": "Department of Pathology, National Institute of Infectious Diseases"
+        "author_name": "Carl C Schimanski",
+        "author_inst": "Department of Internal Medicine II, Klinikum Darmstadt GmbH, Darmstadt, Germany"
       },
       {
-        "author_name": "Shinji Akitomi",
-        "author_inst": "Japan Medical Association Research Institute"
+        "author_name": "Cihan Celik",
+        "author_inst": "Department of Internal Medicine II, Klinikum Darmstadt GmbH, Darmstadt, Germany"
       },
       {
-        "author_name": "Iwao Hasegawa",
-        "author_inst": "Department of Forensic Medicine, Kanagawa Dental University"
+        "author_name": "Thorsten Pohle",
+        "author_inst": "Department of Internal Medicine I, Klinikum Herford, Germany"
       },
       {
-        "author_name": "Tetsuo Ushiku",
-        "author_inst": "Department of Pathology, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Matthias Ruhe",
+        "author_inst": "Department of Internal Medicine I, Klinikum Herford, Germany"
+      },
+      {
+        "author_name": "Winfried V Kern",
+        "author_inst": "Department of Medicine II, Division of Infectious Diseases and Travel Medicine, University Medical Centre Freiburg, Freiburg, Germany"
       },
       {
-        "author_name": "Daisuke Yajima",
-        "author_inst": "Department of Legal Medicine, International University of Health and Welfare"
+        "author_name": "Anita Schmitt",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Hirotaro Iwase",
-        "author_inst": "Department of Legal Medicine, Graduate School of Medicine, Chiba University"
+        "author_name": "Hanns-Martin Lorenz",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Yohsuke Makino",
-        "author_inst": "Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Margarida Souto-Carneiro",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
       },
       {
-        "author_name": "Yoshihiro Kawaoka",
-        "author_inst": "University of Wisconsin-Madison"
+        "author_name": "Mary Gaeddert",
+        "author_inst": "Division of Tropical Medicine, Department of Infectious Diseases, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Niels Halama",
+        "author_inst": "Department of Medical Oncology, National Center for Tumor Diseases, Heidelberg University Hospital, Heidelberg, Germany; Department of Translational Immunothera"
+      },
+      {
+        "author_name": "Stefan Meuer",
+        "author_inst": "Institute for Clinical Transfusion Medicine and Cell Therapy Heidelberg, Heidelberg"
+      },
+      {
+        "author_name": "Hans-Georg Kraeusslich",
+        "author_inst": "Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Barbara Mueller",
+        "author_inst": "Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Paul Schnitzler",
+        "author_inst": "Barbara.Mueller@med.uni-heidelberg.de"
+      },
+      {
+        "author_name": "Sylvia Parthe",
+        "author_inst": "Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Ralf Bartenschlager",
+        "author_inst": "Department of Infectious Diseases, Molecular Virology, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Martina Gronkowski",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Jennifer Klemmer",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Michael Schmitt",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Peter Dreger",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Katharina Kriegsmann",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
+      },
+      {
+        "author_name": "Richard F Schlenk",
+        "author_inst": "NCT-Trial Center, National Center of Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany Department of Interna"
+      },
+      {
+        "author_name": "Carsten Mueller-Tidow",
+        "author_inst": "Department of Internal Medicine V, Heidelberg University Hospital, Heidelberg, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -150987,67 +151729,39 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.10.10.22280915",
-    "rel_title": "Infection-induced immunity is associated with protection against SARS-CoV-2 infection, but not decreased infectivity during household transmission",
+    "rel_doi": "10.1101/2022.10.11.22280942",
+    "rel_title": "Impact of the COVID-19 pandemic on exercise habits and overweight in Japan: a nation-wide panel survey",
     "rel_date": "2022-10-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.10.22280915",
-    "rel_abs": "BackgroundUnderstanding the impact of infection-induced immunity on SARS-CoV-2 transmission will provide insight into the transition of SARS-CoV-2 to endemicity. Here we estimate the effects of prior infection induced immunity and children on SARS-CoV-2 transmission in households.\n\nMethodsWe conducted a household cohort study between March 2020-June 2022 in Managua, Nicaragua where when one household member tests positive for SARS-CoV-2, household members are closely monitored for SARS-CoV-2 infection. Using a pairwise survival model, we estimate the association of infection period, age, symptoms, and infection-induced immunity with secondary attack risk.\n\nResultsOverall transmission occurred in 72.4% of households, 42% of household contacts were infected and the secondary attack risk was 13.0% (95% CI: 11.7, 14.6). Prior immunity did not impact the probability of transmitting SARS-CoV-2. However, participants with pre-existing infection-induced immunity were half as likely to be infected compared to naive individuals (RR 0.53, 95% CI: 0.39, 0.72), but this reduction was not observed in children. Likewise, symptomatic infected individuals were more likely to transmit (RR 24.4, 95% CI: 7.8, 76.1); however, symptom presentation was not associated with infectivity of young children. Young children were less likely to transmit SARS-CoV-2 than adults. During the omicron era, infection-induced immunity remained protective against infection.\n\nConclusionsInfection-induced immunity is associated with protection against infection for adults and adolescents. While young children are less infectious, prior infection and asymptomatic presentation did not reduce their infectivity as was seen in adults. As SARS-CoV-2 transitions to endemicity, children may become more important in transmission dynamics.\n\nArticle summaryInfection-induced immunity protects against SARS-CoV-2 infection for adolescents and adults; however, there was no protection in children. Prior immunity in an infected individual did not impact the probability they will spread SARS-CoV-2 in a household setting.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.11.22280942",
+    "rel_abs": "IntroductionA catastrophic disaster may cause distant health impacts like immobility and obesity. This research aims at analysing the impact of the COVID-19 pandemic on exercise habit and overweight in the Japanese population.\n\nMethodsNation-wide online questionnaires were conducted five times from October 2020 to October 2021. The change in exercise habit, body mass index (BMI) and status of overweight (BMI>25kg/m2) were compared between the first questionnaire and later ones. Risk factors of losing exercise habit or developing overweight were analysed using multiple regression.\n\nResultsData was obtained from 16,642 participants. In the early phase of the pandemic, people with high income and elderly females showed higher risk of decreased exercise days. Proportion of overweight was increased from 22.2% to 26.6% in males and from 9.3% to 10.8% in females. Middle aged males, elderly females, males who experienced SARS-CoV-2 infection were at higher risks of developing overweight.\n\nConclusionOur findings suggest that risks of immobility and overweight are homogeneous. Continuous intervention for elderly females and long-term intervention for males who were infected might be especially needed. As most disasters can cause similar social transformation, research and evaluation of immobility and obesity should be addressed in future disaster preparation/ mitigation plans.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Aaron M Frutos",
-        "author_inst": "University of Michigan"
-      },
-      {
-        "author_name": "Guillermina Kuan",
-        "author_inst": "Health Center Socrates Flores Vivas, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua, Nicaragua"
-      },
-      {
-        "author_name": "Roger Lopez",
-        "author_inst": "Laboratorio Nacional de Virologia, Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua,"
-      },
-      {
-        "author_name": "Sergio Ojeda",
-        "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua"
-      },
-      {
-        "author_name": "Abigail Shotwell",
-        "author_inst": "Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA"
-      },
-      {
-        "author_name": "Nery Sanchez",
-        "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua"
-      },
-      {
-        "author_name": "Saira Saborio",
-        "author_inst": "Laboratorio Nacional de Virologia, Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua,"
+        "author_name": "Sae Ochi",
+        "author_inst": "Tokyo Jikeikai Ika Daigaku"
       },
       {
-        "author_name": "Miguel Plazaola",
-        "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua"
+        "author_name": "So Mirai",
+        "author_inst": "Tokyo Dental College: Tokyo Shika Daigaku"
       },
       {
-        "author_name": "Carlos Barilla",
-        "author_inst": "Sustainable Sciences Institute, Managua, Nicaragua"
+        "author_name": "Sora Hashimoto",
+        "author_inst": "United Health Communications"
       },
       {
-        "author_name": "Eben Kenah",
-        "author_inst": "Biostatistics Division, College of Public Health, The Ohio State University, Columbus, OH, USA"
+        "author_name": "Yuki Hashimoto",
+        "author_inst": "Research Institute of Economy Trade and Industry: Dokuritsu Gyosei Hojin Keizai Sangyo Kenkyujo"
       },
       {
-        "author_name": "Angel Balmaseda",
-        "author_inst": "Laboratorio Nacional de Virologia, Centro Nacional de Diagnostico y Referencia, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua,"
-      },
-      {
-        "author_name": "Aubree Gordon",
-        "author_inst": "University of Michigan"
+        "author_name": "Yoichi Sekizawa",
+        "author_inst": "Research Institute of Economy Trade and Industry: Dokuritsu Gyosei Hojin Keizai Sangyo Kenkyujo"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.10.09.22280877",
@@ -152869,79 +153583,83 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.10.06.22280798",
-    "rel_title": "Impact of vaccination on post-acute sequelae of SARS CoV-2 infection in patients with rheumatic diseases",
+    "rel_doi": "10.1101/2022.10.06.22280795",
+    "rel_title": "Long COVID Risk and Pre-COVID Vaccination: An EHR-Based Cohort Study from the RECOVER Program",
     "rel_date": "2022-10-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.06.22280798",
-    "rel_abs": "ObjectiveVaccination decreases the risk of severe COVID-19 but its impact on post-acute sequelae of COVID-19 (PASC) is unclear among patients with systemic autoimmune rheumatic diseases (SARDs) who may have blunted vaccine immunogenicity and be vulnerable to PASC.\n\nMethodsWe prospectively enrolled SARD patients from a large healthcare system who survived acute infection to complete surveys. The symptom-free duration and the odds of PASC (any symptom lasting [&ge;] 28 or 90 days) were evaluated using restricted mean survival time and multivariable logistic regression, respectively, among those with and without breakthrough infection ([&ge;] 14 days after initial vaccine series).\n\nResultsAmong 280 patients, the mean age was 53 years, 80% were female, and 82% were white. The most common SARDs were inflammatory arthritis (59%) and connective tissue disease (24%). Those with breakthrough infection had more upper respiratory symptoms, and those with non-breakthrough infection had more anosmia, dysgeusia, and joint pain. Compared to those with non-breakthrough COVID-19 infection (n=164), those with breakthrough infection (n=116) had significantly more symptom-free days over the follow-up period (+28.9 days, 95% CI: 8.83, 48.89; p=0.005) and lower odds of PASC at 28 and 90 days (aOR 0.49, 95% CI: 0.29, 0.83 and aOR 0.10, 95% CI: 0.04, 0.22, respectively).\n\nConclusionVaccinated patients with SARDs were less likely to experience PASC compared to those not fully vaccinated. These findings support the benefits of vaccination for patients with SARDs and suggest that the immune response to acute infection is important in the pathogenesis of PASC in SARD patients.\n\nKey MessagesO_ST_ABSWhat is already known on this topic?C_ST_ABSO_LIPost-acute sequelae of COVID-19 (PASC) affects 20-50% of COVID-19 survivors, though the impact of vaccination on the risk and severity of PASC is unclear, especially among those with systemic autoimmune rheumatic diseases (SARDs) who may have impaired responses to vaccines and be particularly vulnerable to PASC.\nC_LI\n\nWhat this study adds?O_LIIn this prospective cohort of SARD patients recovering from COVID-19, we found that those with breakthrough vs non-breakthrough infection had more symptom-free days over the follow-up period (adjusted difference +28.9 days, 95% CI: 8.38, 48.89; p=0.005) and a lower odds of PASC at 28 days (aOR 0.49, 95% CI: 0.29, 0.83) and at 90 days (aOR 0.10, 95% CI: 0.04, 0.22).\nC_LIO_LIPatient-reported pain and fatigue scores were lower, reflecting less severe pain and fatigue, in those with breakthrough infection compared to those with non-breakthrough infection.\nC_LI\n\nHow this study might affect research, practice, or policy?O_LIThis study extends our understanding of the benefits of vaccination against COVID-19 in patients living with SARDs and reinforces the importance of vaccinating this vulnerable population.\nC_LIO_LIOur findings suggest that the initial immune response to acute SARS-CoV-2, as influenced by vaccination, affects PASC risk but this requires further study.\nC_LI",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.06.22280795",
+    "rel_abs": "ImportanceCharacterizing the effect of vaccination on long COVID allows for better healthcare recommendations.\n\nObjectiveTo determine if, and to what degree, vaccination prior to COVID-19 is associated with eventual long COVID onset, among those a documented COVID-19 infection.\n\nDesign, Settings, and ParticipantsRetrospective cohort study of adults with evidence of COVID-19 between August 1, 2021 and January 31, 2022 based on electronic health records from eleven healthcare institutions taking part in the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative, a project of the National Covid Cohort Collaborative (N3C).\n\nExposuresPre-COVID-19 receipt of a complete vaccine series versus no pre-COVID-19 vaccination.\n\nMain Outcomes and MeasuresTwo approaches to the identification of long COVID were used. In the clinical diagnosis cohort (n=47,752), ICD-10 diagnosis codes or evidence of a healthcare encounter at a long COVID clinic were used. In the model-based cohort (n=199,498), a computable phenotype was used. The association between pre-COVID vaccination and long COVID was estimated using IPTW-adjusted logistic regression and Cox proportional hazards.\n\nResultsIn both cohorts, when adjusting for demographics and medical history, pre-COVID vaccination was associated with a reduced risk of long COVID (clinic-based cohort: HR, 0.66; 95% CI, 0.55-0.80; OR, 0.69; 95% CI, 0.59-0.82; model-based cohort: HR, 0.62; 95% CI, 0.56-0.69; OR, 0.70; 95% CI, 0.65-0.75).\n\nConclusions and RelevanceLong COVID has become a central concern for public health experts. Prior studies have considered the effect of vaccination on the prevalence of future long COVID symptoms, but ours is the first to thoroughly characterize the association between vaccination and clinically diagnosed or computationally derived long COVID. Our results bolster the growing consensus that vaccines retain protective effects against long COVID even in breakthrough infections.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDoes vaccination prior to COVID-19 onset change the risk of long COVID diagnosis?\n\nFindingsFour observational analyses of EHRs showed a statistically significant reduction in long COVID risk associated with pre-COVID vaccination (first cohort: HR, 0.66; 95% CI, 0.55-0.80; OR, 0.69; 95% CI, 0.59-0.82; second cohort: HR, 0.62; 95% CI, 0.56-0.69; OR, 0.70; 95% CI, 0.65-0.75).\n\nMeaningVaccination prior to COVID onset has a protective association with long COVID even in the case of breakthrough infections.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Naomi J Patel",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "M Daniel Brannock",
+        "author_inst": "RTI International"
       },
       {
-        "author_name": "Claire Cook",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Robert F Chew",
+        "author_inst": "RTI International"
       },
       {
-        "author_name": "Kathleen MM Vanni",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Alexander J Preiss",
+        "author_inst": "RTI International"
       },
       {
-        "author_name": "Xiaoqing Fu",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Emily C Hadley",
+        "author_inst": "RTI International"
       },
       {
-        "author_name": "Xiaosong Wang",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Julie A McMurry",
+        "author_inst": "University of Colorado Anschutz Medical Campus"
       },
       {
-        "author_name": "Yumeko Kawano",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Peter J Leese",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Grace Qian",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Andrew T Girvin",
+        "author_inst": "Palantir Technologies"
       },
       {
-        "author_name": "Buuthien Hang",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Miles Crosskey",
+        "author_inst": "CoVar Applied Technologies"
       },
       {
-        "author_name": "Shruthi Srivatsan",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Andrea G Zhou",
+        "author_inst": "University of Virginia"
       },
       {
-        "author_name": "Emily Banasiak",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Richard A Moffitt",
+        "author_inst": "Stony Brook University"
       },
       {
-        "author_name": "Emily Kowalski",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Michele Jonsson Funk",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Katarina Bade",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Emily Pfaff",
+        "author_inst": "UNC Chapel Hill"
       },
       {
-        "author_name": "Yuqing Zhang",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Melissa Haendel",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Jeffrey A. Sparks",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Christopher G Chute",
+        "author_inst": "Johns Hopkins University"
       },
       {
-        "author_name": "Zachary S Wallace",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "- N3C Consortium",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "- RECOVER Consortium",
+        "author_inst": "-"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "rheumatology"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.10.06.511203",
@@ -154707,131 +155425,199 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.10.05.22280716",
-    "rel_title": "Kinetics of naturally induced binding and neutralizing anti-SARS-CoV-2 antibody levels and potencies among Kenyan patients with diverse grades of COVID-19 severity",
+    "rel_doi": "10.1101/2022.10.04.22280459",
+    "rel_title": "Association between COVID-19 mRNA vaccination and COVID-19 illness and severity during Omicron BA.4 and BA.5 sublineage periods",
     "rel_date": "2022-10-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.05.22280716",
-    "rel_abs": "BackgroundGiven the low levels of COVID-19 vaccine coverage in Sub-Saharan Africa, despite high levels of natural SARS-CoV-2 exposures, strategies for extending the breadth and longevity of naturally acquired immunity are warranted. Designing such strategies will require a good understanding of natural immunity.\n\nMethodsWe used ELISA to measure whole-spike IgG and spike-receptor binding domain (RBD) total immunoglobulins (Igs) on 585 plasma samples collected longitudinally over five successive time points within six months of COVID-19 diagnosis in 309 COVID-19 patients. We measured antibody neutralizing potency against the wild-type (Wuhan) SARS-CoV-2 pseudo-virus in a subset of 51 patients over three successive time points. Binding and neutralizing antibody levels and potencies were then tested for correlations with COVID-19 severities, graded according to the National Institute of Health (NIH), USA criteria.\n\nResultsRates of sero-conversion increased from Day 0 (day of PCR testing) to Day 180 (six months) (63.6% to 100 %) and (69.3 % to 97%) for anti-spike IgG and anti-spike-RBD binding Igs, respectively. Levels of these binding antibodies peaked at Day 28 (P<0.0001) and were subsequently maintained for six months without significant decay (p>0.99). Similarly, antibody neutralizing potencies peaked at Day 28 (p<0.0001) but had decreased by three-folds, six months after COVID-19 diagnosis (p<0.0001). Binding antibodies levels were highly correlated with neutralizing antibody potencies at all the time points analyzed (r>0.6, P<0.0001). Levels and potencies of binding and neutralizing antibodies increased with disease severity.\n\nConclusionMost COVID-19 patients from Sub-Saharan Africa generate SARS-CoV-2 specific binding antibodies that remain stable during the first six months of infection. Although antibody binding levels and neutralizing potencies were directly correlated, the respective neutralizing antibodies decayed three-fold by the sixth month of COVID-19 diagnosis suggesting that they are short-lived, consistent with what has been observed elsewhere. Thus, just like for other populations, regular vaccination boosters will be required to broaden and sustain the high levels of predominantly naturally acquired anti-SARS-CoV-2 neutralizing antibodies.",
-    "rel_num_authors": 28,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.04.22280459",
+    "rel_abs": "ImportanceRecent sublineages of the SARS-CoV-2 Omicron variant, including BA.4 and BA.5, may be associated with greater immune evasion and less protection against COVID-19 following vaccination.\n\nObjectiveTo evaluate the association between COVID-19 mRNA vaccination with 2, 3, or 4 doses among immunocompetent adults and the risk of medically attended COVID-19 illness during a period of BA.4/BA.5 predominant circulation; to evaluate the relative severity of COVID-19 in hospitalized cases across Omicron BA.1, BA.2/BA.2.12.1, and BA.4/BA.5 sublineage periods.\n\nSetting, Design and ParticipantsTest-negative study of adults with COVID-19-like illness (CLI) and molecular testing for SARS-CoV-2 conducted in 10 states from December 16, 2021, to August 20, 2022.\n\nExposuremRNA COVID-19 vaccination.\n\nMain Outcomes and MeasuresEmergency department/urgent care encounters, hospitalizations, and admission to the intensive care unit (ICU) or in-hospital death. The adjusted odds ratio (OR) for the association between prior vaccination and medically attended COVID-19 was used to estimate VE, stratified by care setting and vaccine doses (2, 3, or 4 doses vs 0 doses as reference group). Among hospitalized case-patients, demographic and clinical characteristics and in-hospital outcomes including ICU admission and death were compared across sublineage periods.\n\nResultsBetween June 19 - August 20, 2022, 82,229 ED/UC and 21,007 hospital encounters were included for the BA.4/BA.5 vaccine effectiveness analysis. Among adults hospitalized with CLI, the adjusted odds ratio (OR) was 0.75 (95% CI: 0.68-0.83) for receipt of 2 vaccine doses at [&ge;]150 days after receipt, 0.32 (95% CI: 0.20-0.50) for a third dose 7-119 days after receipt, and 0.64 (95% CI: 0.58-0.71) for a third dose [&ge;]120 days (median 235 days) after receipt for cases vs controls. For COVID-19-associated hospitalization, among patients ages [&ge;]65 years 7-59 and [&ge;]60 days (median 88 days) after a fourth dose, ORs were 0.34 (95% CI: 0.25-0.47) and 0.43 (95% CI: 0.34-0.56), respectively. Among hospitalized cases, ICU admission and/or in-hospital death occurred in 21.4% during the BA.1 vs 14.7% during the BA.4/BA.5 period (standardized mean difference: 0.17).\n\nConclusionVE against medically attended COVID-19 illness decreased over time since last dose; receipt of one or two booster doses increased effectiveness over a primary series alone.\n\nKEY POINTS\n\nQuestionWhat is the association between receipt of first-generation COVID-19 mRNA vaccines and medically attended COVID-19 during Omicron BA.4/BA.5 sublineage predominance?\n\nFindingsThis test-negative analysis included 82,229 emergency department or urgent care encounters and 21,007 hospitalizations for COVID-19-like illness. Among hospitalized patients, the likelihood of recent vaccination (7-119 days) with 3 mRNA vaccine doses (vs unvaccinated) was significantly lower (odds ratio, 0.32) in cases than SARS-CoV-2-negative controls, but with lower associated protection [&ge;]120 days post-vaccination (odds ratio, 0.64).\n\nMeaningFirst-generation COVID-19 vaccines were associated with protection against COVID-19 during the Omicron BA.4/BA.5 sublineage-predominant periods but this declined over time.",
+    "rel_num_authors": 45,
     "rel_authors": [
       {
-        "author_name": "John Kimotho",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Ruth Link-Gelles",
+        "author_inst": "Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia"
       },
       {
-        "author_name": "Yiakon Sein",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Matthew E. Levy",
+        "author_inst": "Westat, Rockville, Maryland"
       },
       {
-        "author_name": "Shahin M Sayed",
-        "author_inst": "Aga Khan University - Kenya"
+        "author_name": "Karthik Natarajan",
+        "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York; New York Presbyterian Hospital, New York, NY"
       },
       {
-        "author_name": "Reena Shah",
-        "author_inst": "Aga Khan University - Kenya"
+        "author_name": "Sarah E. Reese",
+        "author_inst": "Westat, Rockville, Maryland"
       },
       {
-        "author_name": "Kennedy Mwai",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Allison L. Naleway",
+        "author_inst": "Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon"
       },
       {
-        "author_name": "Mansoor Saleh",
-        "author_inst": "Aga Khan University-Kenya"
+        "author_name": "Shaun J. Grannis",
+        "author_inst": "Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana"
       },
       {
-        "author_name": "Perpetual Wanjiku",
-        "author_inst": "KEMRI Wellcome"
+        "author_name": "Nicola P. Klein",
+        "author_inst": "Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California"
       },
       {
-        "author_name": "Jedida Mwacharo",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Malini B. DeSilva",
+        "author_inst": "HealthPartners Institute, Minneapolis, Minnesota"
       },
       {
-        "author_name": "James Nyangwange",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Toan C. Ong",
+        "author_inst": "School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado"
       },
       {
-        "author_name": "Henry Karanja",
-        "author_inst": "KEMRI Wellcome"
+        "author_name": "Manjusha Gaglani",
+        "author_inst": "Baylor Scott & White Health, Temple, Texas Texas A&M University College of Medicine, Temple, Texas"
       },
       {
-        "author_name": "Bernadette Kutima",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Emily Hartmann",
+        "author_inst": "Paso del Norte Health Information Exchange (PHIX), El Paso, Texas"
       },
       {
-        "author_name": "John Gitonga",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Monica E. Dickerson",
+        "author_inst": "Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia"
       },
       {
-        "author_name": "Daisy Mugo",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Edward Stenehjem",
+        "author_inst": "Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah"
       },
       {
-        "author_name": "Ann Karanu",
-        "author_inst": "Aga Khan University-Kenya"
+        "author_name": "Anupam B. Kharbanda",
+        "author_inst": "Children's Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Linda Moranga",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Jungmi Han",
+        "author_inst": "Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York"
       },
       {
-        "author_name": "Viviane Oluoch",
-        "author_inst": "Aga Khan University-Kenya"
+        "author_name": "Talia L. Spark",
+        "author_inst": "Westat, Rockville, Maryland"
       },
       {
-        "author_name": "Jasmit Shah",
-        "author_inst": "Aga Khan University-Kenya"
+        "author_name": "Stephanie A. Irving",
+        "author_inst": "Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon"
       },
       {
-        "author_name": "Julius Mutiso",
-        "author_inst": "Aga Khan University-Kenya"
+        "author_name": "Brian E. Dixon",
+        "author_inst": "Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana"
       },
       {
-        "author_name": "Afred G Mburu",
-        "author_inst": "Aga Khan University-Kenya"
+        "author_name": "Ousseny Zerbo",
+        "author_inst": "Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California"
       },
       {
-        "author_name": "Zaitun Nneka",
-        "author_inst": "Aga Khan University-Kenya"
+        "author_name": "Charlene E. McEvoy",
+        "author_inst": "HealthPartners Institute, Minneapolis, Minnesota"
       },
       {
-        "author_name": "Peter Betti",
-        "author_inst": "Agha Khan University-Kenya"
+        "author_name": "Suchitra Rao",
+        "author_inst": "School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado"
       },
       {
-        "author_name": "Wanzila U Mutinda",
-        "author_inst": "Pwani University-Kenya"
+        "author_name": "Chandni Raiyani",
+        "author_inst": "Baylor Scott & White Health, Temple, Texas"
       },
       {
-        "author_name": "Abdirahman I Abdi",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Chantel Sloan-Aagard",
+        "author_inst": "Paso del Norte Health Information Exchange (PHIX), El Paso, Texas; Brigham Young University Department of Public Health, Provo, Utah"
       },
       {
-        "author_name": "Philip Bejon",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Palak Patel",
+        "author_inst": "Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia"
+      },
+      {
+        "author_name": "Kristin Dascomb",
+        "author_inst": "Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah"
       },
       {
-        "author_name": "Isabella L Ochola",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Anne-Catrin Uhlemann",
+        "author_inst": "Department of Internal Medicine, Division of Infectious Disease, Columbia University Irving Medical Center, New York, New York, United States"
       },
       {
-        "author_name": "George M Warimwe",
-        "author_inst": "KEMRI-Wellcome Trust Research Programme - Kenya"
+        "author_name": "Margaret M. Dunne",
+        "author_inst": "Westat, Rockville, Maryland"
+      },
+      {
+        "author_name": "William F. Fadel",
+        "author_inst": "Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana"
+      },
+      {
+        "author_name": "Ned Lewis",
+        "author_inst": "Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California"
+      },
+      {
+        "author_name": "Michelle A. Barron",
+        "author_inst": "School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado"
+      },
+      {
+        "author_name": "Kempapura Murthy",
+        "author_inst": "Baylor Scott & White Health, Temple, Texas"
+      },
+      {
+        "author_name": "Juan Nanez",
+        "author_inst": "Paso del Norte Health Information Exchange (PHIX), El Paso, Texas"
+      },
+      {
+        "author_name": "Eric P. Griggs",
+        "author_inst": "Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia"
+      },
+      {
+        "author_name": "Nancy Grisel",
+        "author_inst": "Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah"
+      },
+      {
+        "author_name": "Medini Annavajhala",
+        "author_inst": "Department of Internal Medicine, Division of Infectious Disease, Columbia University Irving Medical Center, New York, New York, United States"
+      },
+      {
+        "author_name": "Akintunde Akinseye",
+        "author_inst": "Westat, Rockville, Maryland"
+      },
+      {
+        "author_name": "Nimish R. Valvi",
+        "author_inst": "Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana"
+      },
+      {
+        "author_name": "Kristin Goddard",
+        "author_inst": "Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California"
+      },
+      {
+        "author_name": "Mufaddal Mamawala",
+        "author_inst": "Baylor Scott & White Health, Temple, Texas"
+      },
+      {
+        "author_name": "Julie Arndorfer",
+        "author_inst": "Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah"
+      },
+      {
+        "author_name": "Duck-Hye Yang",
+        "author_inst": "Westat, Rockville, Maryland"
       },
       {
-        "author_name": "Eunice Nduati",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Peter J. Embi",
+        "author_inst": "Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana;  Vanderbilt University Medical Center, Nashville, Tennessee"
+      },
+      {
+        "author_name": "Bruce Fireman",
+        "author_inst": "Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California"
       },
       {
-        "author_name": "Francis M Ndungu",
-        "author_inst": "KEMRI - Wellcome Research Programme - Kenya"
+        "author_name": "Sarah W. Ball",
+        "author_inst": "Westat, Rockville, Maryland"
+      },
+      {
+        "author_name": "Mark W. Tenforde",
+        "author_inst": "Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.09.30.510319",
@@ -156889,49 +157675,65 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.09.30.22280586",
-    "rel_title": "COVID treatment and in-hospital length of stay inequalities between race in the US over time",
-    "rel_date": "2022-10-01",
+    "rel_doi": "10.1101/2022.09.29.22280522",
+    "rel_title": "A simple non-invasive C reactive protein-based score can predict outcome in patients with COVID-19",
+    "rel_date": "2022-09-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.30.22280586",
-    "rel_abs": "IntroductionDemonstrated health inequalities persist in the United States. SARS-CoV-2 (COVID) has been no exception, with access to treatment and hospitalization differing across race or ethnic group. Here we aim to assess differences in treatment with remdesivir and hospital length of stay across four waves of the pandemic.\n\nMethodsUsing a subset of the Truveta data we examine odds ratios (OR) of in-hospital remdesivir treatment and risk ratios (RR) of in-hospital length of stay between Black or African American (Black) to white patients. We adjusted for confounding factors such as age, sex, and comorbidity status.\n\nResultsThere were statically significant lower rates of remdesivir treatment and longer in-hospital lengths of stay comparing Black patients to white patients early in the pandemic (OR for treatment: 0.88, 95% confidence interval [CI]: 0.80, 0.96; RR for length of stay: 1.17, CI: 1.06, 1.21). Rates became close to parity between groups as the pandemic progressed.\n\nConclusionsWhile inpatient remdesivir treatment rates increased and length of stay decreased over the beginning course of the pandemic, there are still inequalities in patient care.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.29.22280522",
+    "rel_abs": "BackgroundWe evaluated the role of CRP and other laboratory parameters in predicting the worsening of clinical conditions during hospitalization, ICU admission and fatal outcome among patients with COVID-19.\n\nMethodsWe enrolled consecutive adult inpatients with SARS-CoV-2 infection and respiratory symptoms treated in three different COVID centres. We looked for laboratory parameters collected within 48 hours from hospital admission as predictors of clinical condition.\n\nResultsThree-hundred ninety patients were included in the study. At the correlation and regression analysis, age, baseline CRP and LDH were associated with a P/F ratio<200 during hospitalization. At the multivariate analysis, male gender and CRP > 60 mg/l at admission showed to be independently associated with ICU admission. Lymphocytes<1000 cell/L at admission were associated with worst P/F ratio. The only laboratory predictor of fatal outcome was CRP>60 mg/l at admission. Based on these results, we devised an 11-points numeric ordinary score based on age, sex, CRP and LDH at admission (ASCL score). Patients with ASCL score of 0 or 2 showed to be protected against a P/F ratio<200, while patients with ASCL score of 6, 7 and 8 showed to be at risk for P/F ratio<200. Patients with ASCL score[&ge;]7 had a significant increase to die during the hospitalization.\n\nConclusionsPatients with CRP>60 mg/l or LDH>300 IU/l at hospital admission, as well as patients with an ASCL score>6 at hospital admission, should be prioritized for careful respiratory function monitoring and early treatment to prevent a progression of the disease.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Benjamin Muir Althouse",
-        "author_inst": "Truveta"
+        "author_name": "Riccardo Scotto",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Charlotte Baker",
-        "author_inst": "Truveta"
+        "author_name": "Amedeo Lanzardo",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Peter D Smits",
-        "author_inst": "Truveta"
+        "author_name": "Antonio Riccardo Buonomo",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Samuel Gratzl",
-        "author_inst": "Truveta"
+        "author_name": "Biagio Pinchera",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Ryan H Lee",
-        "author_inst": "Truveta"
+        "author_name": "Letizia Cattaneo",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Brianna M Goodwin Cartwright",
-        "author_inst": "Truveta"
+        "author_name": "Alessia Sardanelli",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Michael Siminov",
-        "author_inst": "Truveta"
+        "author_name": "Simona Mercinelli",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Michael D Wang",
-        "author_inst": "Truveta"
+        "author_name": "Giulio Viceconte",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
       },
       {
-        "author_name": "Nicholas Stucky",
-        "author_inst": "Truveta"
+        "author_name": "Emanuela Zappulo",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
+      },
+      {
+        "author_name": "Riccardo Villari",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
+      },
+      {
+        "author_name": "Maria Foggia",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
+      },
+      {
+        "author_name": "Ivan Gentile",
+        "author_inst": "Department of Clinical Medicine and Surgery - Section of Infectious Diseases. University of Naples Federico II. Italy"
+      },
+      {
+        "author_name": "- Federico II COVID-team",
+        "author_inst": ""
       }
     ],
     "version": "1",
@@ -158687,121 +159489,85 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.09.26.22280387",
-    "rel_title": "Duration of viral infectiousness and correlation with symptoms and diagnostic testing in non-hospitalized adults during acute SARS-CoV-2 infection: A longitudinal cohort study",
+    "rel_doi": "10.1101/2022.09.26.22280362",
+    "rel_title": "Household transmission of SARS-CoV-2 during the Omicron wave in Shanghai, China: a case-ascertained study",
     "rel_date": "2022-09-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.26.22280387",
-    "rel_abs": "BackgroundGuidelines for SARS-CoV-2 have relied on limited data on duration of viral infectiousness and correlation with COVID-19 symptoms and diagnostic testing.\n\nMethodsWe enrolled ambulatory adults with acute SARS-CoV-2 infection and performed serial measurements of COVID-19 symptoms, nasal swab viral RNA, nucleocapsid (N) and spike (S) antigens, and replication-competent SARS-CoV-2 by culture. We determined average time from symptom onset to a first negative test result and estimated risk of infectiousness, as defined by a positive viral culture.\n\nResultsAmong 95 adults, median [interquartile range] time from symptom onset to first negative test result was 9 [5] days, 13 [6] days, 11 [4] days, and >19 days for S antigen, N antigen, viral culture growth, and viral RNA by RT-PCR, respectively. Beyond two weeks, viral cultures and N antigen titers were rarely positive, while viral RNA remained detectable among half (26/51) of participants tested 21-30 days after symptom onset. Between 6-10 days from symptom onset, N antigen was strongly associated with viral culture positivity (relative risk=7.61, 95% CI: 3.01-19.2), whereas neither viral RNA nor symptoms were associated with culture positivity. During the 14 days following symptom onset, presence of N antigen (adjusted relative risk=7.66, 95% CI: 3.96-14.82), remained strongly associated with viral culture positivity, regardless of COVID-19 symptoms.\n\nConclusionsMost adults have replication-competent SARS-CoV-2 for 10-14 after symptom onset, and N antigen testing is a strong predictor of viral infectiousness. Within two weeks from symptom onset, N antigen testing, rather than absence of symptoms or viral RNA, should be used to safely discontinue isolation.\n\nFundingBill and Melinda Gates Foundation",
-    "rel_num_authors": 26,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.26.22280362",
+    "rel_abs": "BackgroundSince late 2021, the highly transmissible SARS-CoV-2 Omicron variant has driven a new surge of infections across the world. We used a case-ascertained study to determine the features of household transmission of SARS-CoV-2 Omicron variant in Shanghai, China.\n\nMethodsWe collected detailed information on 323 pediatric cases and their 951 household members in April 2022 during the Omicron outbreak. All household members received consecutively intensive RT-PCR testing for SARS-CoV-2 and routine symptom monitoring within 14 days after exposure to a confirmed case. We described the characteristics of study participants and estimated the transmission parameters. Both secondary infection attack rates (SARI) and secondary clinical attack rates (SARC) among adult household contacts were computed, through which the transmission heterogeneities in infectivity and susceptibility were characterized and the vaccine effectiveness were estimated.\n\nResultsWe estimated the mean incubation period of SARS-CoV-2 Omicron variant to be 4.6 (median: 4.4, IQR: 3.1-6.0) days and the mean serial interval to be 3.9 (median:4.0, IQR: 1.4-6.5) days. The overall SARI and SARC among adult household contacts were 77.11% (95% confidence interval [CI]: 73.58%-80.63%) and 67.03% (63.09%-70.98%). We found higher household susceptibility in females, while infectivity was not significantly different in primary cases by age, sex, vaccination status and clinical severity. The estimated VEs of full vaccination was 14.8% (95% CI: 5.8%-22.9%) against Omicron infection and 21.5% (95% CI: 10.4%-31.2%) against symptomatic disease. The booster vaccination was 18.9% (95% CI: 9.0%-27.7%) and 24.3% (95% CI: 12.3%-34.7%) effective against infection and symptomatic disease, respectively.\n\nConclusionsWe found high household transmission during the Omicron wave in Shanghai due to asymptomatic and pre-symptomatic transmission in the context of city-wide lockdown, indicating the importance of early detection and timely isolation of SARS-CoV-2 infections and quarantine of close contacts. Marginal effectiveness of inactivated vaccines against Omicron infection poses great challenge for prevention and control of the SARS-CoV-2 Omicron variant.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Paul K Drain",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Ronit R Dalmat",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "LINHUI HAO",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Meagan J Bemer",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Elvira Budiawan",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Jennifer F Morton",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Renee C Ireton",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Tien-Ying Hsiang",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Zarna Marfatia",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Roshni Prabhu",
-        "author_inst": "University of Washington"
+        "author_name": "Zhongqiu Wei",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Claire Woosley",
-        "author_inst": "University of Washington"
+        "author_name": "Wenjie Ma",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Adenech Gichamo",
-        "author_inst": "University of Washington"
+        "author_name": "Zhonglin Wang",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Elena Rechkina",
-        "author_inst": "University of Washington"
+        "author_name": "Jingjing Li",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Daphne Hamilton",
-        "author_inst": "University of Washington"
+        "author_name": "Xiaomin Fu",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Michalina Montano",
-        "author_inst": "University of Washington"
+        "author_name": "Hailing Chang",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Jason L Cantera",
-        "author_inst": "Global Health Labs"
+        "author_name": "Yue Qiu",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Alexey Ball",
-        "author_inst": "Global Health Labs"
+        "author_name": "He Tian",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Inah Golez",
-        "author_inst": "University of Washington"
+        "author_name": "Yanling Ge",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Elise Smith",
-        "author_inst": "University of Washington"
+        "author_name": "Yanfeng Zhu",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Alex Greninger",
-        "author_inst": "University of Washington"
+        "author_name": "Aimei Xia",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "M Juliana McElrath",
-        "author_inst": "Fred Hutch Cancer Research Center"
+        "author_name": "Qianhui Wu",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education"
       },
       {
-        "author_name": "Matthew Thompson",
-        "author_inst": "University of Washington"
+        "author_name": "Gongbao Liu",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Benjamin D Grant",
-        "author_inst": "Global Health Labs"
+        "author_name": "Xiaowen Zhai",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Allison Meisner",
-        "author_inst": "Fred Hutch Cancer Research Center"
+        "author_name": "Xiaobo Zhang",
+        "author_inst": "Children's Hospital of Fudan University"
       },
       {
-        "author_name": "Geoffrey S Gottlieb",
-        "author_inst": "University of Washington"
+        "author_name": "Yan Wang",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education"
       },
       {
-        "author_name": "Michael J Gale Jr.",
-        "author_inst": "University of Washington"
+        "author_name": "Mei Zeng",
+        "author_inst": "Children's Hospital of Fudan University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -160609,35 +161375,79 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.09.26.509459",
-    "rel_title": "Nanobodies for the treatment of SARS-CoV-2 in animals: a meta-analysis",
+    "rel_doi": "10.1101/2022.09.25.509344",
+    "rel_title": "Comprehensive structural analysis reveals broad-spectrum neutralizing antibodies against Omicron",
     "rel_date": "2022-09-26",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.26.509459",
-    "rel_abs": "This meta-analysis aimed to find the effect of variable domain of heavy-chain antibodies (VHHs) for the treatment of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in animals. The databases of the PubMed, China National Knowledge Infrastructure (CNKI), Wan fang data, Cochrane Library, and Embase were searched for articles published before August 2022 on the protective effects of VHHs in animals. The articles retrieved were screened using inclusion and exclusion criteria. The data were analyzed using Review Manager 5.4. Six articles were selected from 667 articles based on the inclusion and exclusion criteria in VHHs. A forest plot showed that VHHs could offer protection against SARS-CoV-2 infection in animals [Mantel-Haenszel (MH) = 172.94, 95% confidence interval (CI) = (43.96, 678.42), P < 0.00001]. There was almost no heterogeneity in this study (I2 = 0). A funnel plot showed that the bias of the data analysis was small. This is a special meta-analysis proved that VHHs could treat and prevent SARS-CoV-2 in animals.",
-    "rel_num_authors": 4,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.25.509344",
+    "rel_abs": "The pandemic of COVID-19 caused by SARS-CoV-2 continues to spread around the world. Mutant strains of SARS-CoV-2 are constantly emerging. At present, Omicron variants have become mainstream. In this work, we carried out a systematic and comprehensive analysis of the reported spike protein antibodies, counting the antibodies epitopes and genotypes. We further comprehensively analyzed the impact of Omicron mutations on antibody epitopes and classified these antibodies according to their binding patterns. We found that the epitopes of one class of antibodies were significantly less affected by Omicron mutations than other classes. Binding and virus neutralization experiments show that such antibodies can effectively inhibit the immune escape of Omicron. Cryo-EM results show that this class of antibodies utilizes a conserved mechanism to neutralize SARS-CoV-2. Our results greatly help us deeply understand the impact of Omicron mutations. At the same time, it also provides guidance and insights for developing Omicron antibodies and vaccines.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "jiao jiao",
-        "author_inst": "shihezi university"
+        "author_name": "Xiangyang Chi",
+        "author_inst": "Institute of Biotechnology"
       },
       {
-        "author_name": "shu lan lin",
-        "author_inst": "shihezi university"
+        "author_name": "Lingyun Xia",
+        "author_inst": "Westlake University"
       },
       {
-        "author_name": "zhen qi liang",
-        "author_inst": "shihezi university"
+        "author_name": "Guanying Zhang",
+        "author_inst": "Institute of Biotechnology"
       },
       {
-        "author_name": "Peng Wu",
-        "author_inst": "Shehezi University"
+        "author_name": "Ximin Chi",
+        "author_inst": "Westlake University"
+      },
+      {
+        "author_name": "Bangdong Huang",
+        "author_inst": "Westlake University"
+      },
+      {
+        "author_name": "Yuanyuan Zhang",
+        "author_inst": "Westlake University"
+      },
+      {
+        "author_name": "Zhengshan Chen",
+        "author_inst": "Institute of Biotechnology"
+      },
+      {
+        "author_name": "Jin Han",
+        "author_inst": "Institute of Biotechnology"
+      },
+      {
+        "author_name": "Liushu Wu",
+        "author_inst": "Westlake University"
+      },
+      {
+        "author_name": "Zeya Li",
+        "author_inst": "Institute of Biotechnology"
+      },
+      {
+        "author_name": "Hancong Sun",
+        "author_inst": "Institute of Biotechnology"
+      },
+      {
+        "author_name": "Ping Huang",
+        "author_inst": "Institute of Biotechnology"
+      },
+      {
+        "author_name": "Changming Yu",
+        "author_inst": "Institute of Biotechnology"
+      },
+      {
+        "author_name": "Wei Chen",
+        "author_inst": "Institute of Biotechnology"
+      },
+      {
+        "author_name": "Qiang Zhou",
+        "author_inst": "Westlake University"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "confirmatory results",
-    "category": "immunology"
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.09.26.509529",
@@ -163295,47 +164105,31 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2022.09.22.22280222",
-    "rel_title": "Effects of SARS-CoV-2 Infection on Attention, Memory, and Sensorimotor Performance",
+    "rel_doi": "10.1101/2022.09.21.22280219",
+    "rel_title": "Excess death estimates from multiverse analysis in 2009-2021",
     "rel_date": "2022-09-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.22.22280222",
-    "rel_abs": "BackgroundRecovery after SARS-CoV-2 infection is extremely variable, with some individuals recovering quickly, and others experiencing persistent long-term symptoms or developing new symptoms after the acute phase of infection, including fatigue, poor concentration, impaired attention, or memory deficits. Many existing studies reporting cognitive deficits associated with SARS-CoV-2 infection are limited by the exclusive use of self-reported measures or a lack of adequate comparison groups.\n\nMethodsForty-five participants, ages 18-70, (11 Long-COVID, 14 COVID, and 20 No-COVID) underwent behavioral testing with the NIH Toolbox Neuro-Quality of Life survey and selected psychometric tests, including a flanker interference task and the d2 Test of Attention.\n\nResultsWe found greater self-reported anxiety, apathy, fatigue, emotional dyscontrol, sleep disturbance and cognitive dysfunction in COVID compared No-COVID groups. After categorizing COVID patients according to self-reported concentration problems, we observed declining performance patterns in multiple attention measures across No-COVID controls, COVID and Long-COVID groups. COVID participants, compared to No-COVID controls, exhibited worse performance on NIH Toolbox assessments, including the Eriksen Flanker, Nine-Hole Pegboard and Auditory Verbal Learning tests.\n\nConclusionThis study provides convergent evidence that previous SARS-CoV-2 infection is associated with impairments in sustained attention, processing speed, self-reported fatigue and concentration. The finding that some patients have cognitive and visuomotor dysfunction in the absence of self-reported problems suggests that SARS-CoV-2 infection can have unexpected and persistent subclinical consequences.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.21.22280219",
+    "rel_abs": "Excess death estimates have great value in public health, but they can be sensitive to analytical choices. Here we propose a multiverse analysis approach that considers all possible different time periods for defining the reference baseline and a range of 1 to 4 years for the projected time period for which excess deaths are calculated. We used data from the Human Mortality Database on 33 countries with detailed age-stratified death information on an annual basis during the period 2009-2021. The use of different time periods for reference baseline led to large variability in the absolute magnitude of the exact excess death estimates. However, the relative ranking of different countries compared to others for specific years remained largely unaltered. The relative ranking of different years for the specific country was also largely independent of baseline. Averaging across all possible analyses, distinct time patterns were discerned across different countries. Countries had declines between 2009 and 2019, but the steepness of the decline varied markedly. There were also large differences across countries on whether the COVID-19 pandemic years 2020-2021 resulted in an increase of excess deaths and by how much. Consideration of longer projected time windows resulted in substantial shrinking of the excess deaths in many, but not all countries. Multiverse analysis of excess deaths over long periods of interest can offer a more unbiased approach to understand comparative mortality trends across different countries, the range of uncertainty around estimates, and the nature of observed mortality peaks.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Erin O'Connor",
-        "author_inst": "University of Maryland School of Medicine"
-      },
-      {
-        "author_name": "Nikita Rednam",
-        "author_inst": "univrsity of Marylnd School of Medicine"
-      },
-      {
-        "author_name": "Rory OBrien",
-        "author_inst": "Lantern Laboratory"
-      },
-      {
-        "author_name": "Shea OBrien",
-        "author_inst": "Lantern Laboratory"
-      },
-      {
-        "author_name": "Peter Rock",
-        "author_inst": "University of Maryland School of Medicine"
+        "author_name": "Michael Levitt",
+        "author_inst": "Stanford School of Medicine"
       },
       {
-        "author_name": "Andrea Levine",
-        "author_inst": "University of Maryland School of Medicine"
+        "author_name": "Francesco Zonta",
+        "author_inst": "ShanghaiTech University"
       },
       {
-        "author_name": "Thomas A Zeffiro",
-        "author_inst": "University of Maryland School of Medicine"
+        "author_name": "John Ioannidis",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.09.23.22280263",
@@ -165245,85 +166039,61 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2022.09.20.22280135",
-    "rel_title": "Host immunological responses facilitate development of SARS-CoV-2 mutations in patients receiving monoclonal antibody treatments",
+    "rel_doi": "10.1101/2022.09.20.22280138",
+    "rel_title": "Prevalence of SARS-CoV-2 and co-occurrence/co-infection with malaria during the first wave of the pandemic (the Burkina Faso case)",
     "rel_date": "2022-09-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.20.22280135",
-    "rel_abs": "The role of host immunity in emergence of evasive SARS-CoV-2 Spike mutations under therapeutic monoclonal antibody (mAb) pressure remains to be explored. Here, we show that patients treated with various anti-SARS-CoV-2 mAb regimens develop evasive Spike mutations with remarkable speed and high specificity to the targeted mAb-binding sites. Mutations develop more frequently in immunocompromised patients and strongly correlate not only with the neutralizing capacity of the therapeutic mAbs, but also with an anti-inflammatory and healing-promoting host milieu. Machine-learning models based on soluble host-derived biomarkers identified patients at high risk of developing escape mutations against therapeutic mAbs with high accuracy. While our data demonstrate that host-driven immune and non-immune responses are essential for development of mutant SARS-CoV-2, these data could also support point-of-care decision making in reducing the risk of mAb treatment failure and improving mitigation strategies for possible dissemination of escape SARS-CoV-2 mutants.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.20.22280138",
+    "rel_abs": "Africa accounts for 1.5% of the global coronavirus disease 2019 (COVID-19) cases and 2.7% of deaths, but this low incidence has been partly attributed to the limited testing capacity in most countries. In addition, the population in many African countries is at high risk of infection with endemic infectious diseases such as malaria. Our aim is to determine the prevalence and circulation of SARS-CoV-2 variants, and the frequency of co-infection with the malaria parasite. We conducted serological tests and microscopy examinations on 998 volunteers of different ages and sexes in a random and stratified population sample in Burkina-Faso. In addition, nasopharyngeal samples were taken for RT-qPCR of SARS-COV-2 and for whole viral genome sequencing. Our results show a 3.2% and a 2.5% of SARS-CoV-2 seroprevalence and PCR positivity; and 22% of malaria incidence, over the sampling period, with marked differences linked to age. Importantly, we found 2 cases of confirmed co-infection and 8 cases of suspected co-infection mostly in children. Finally, we report the genome sequences of 13 SARS-CoV-2 isolates circulating in Burkina Faso at the time of analysis, assigned to lineages A.19, A.21, B.1.1.404, B.1.1.118, B.1 and grouped into clades; 19B, 20A and 20B. This is the first population-based study about SARS-CoV-2 and malaria in Burkina Faso during the first wave of the pandemic, providing a relevant estimation of the real prevalence of SARS-CoV-2 and variants circulating in this Sub-Saharan African country. Besides, it highlights the low frequency of co-infection with malaria in African communities.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Akshita Gupta",
-        "author_inst": "University of Antwerp"
-      },
-      {
-        "author_name": "Angelina Konnova",
-        "author_inst": "University of Antwerp"
-      },
-      {
-        "author_name": "Mathias Smet",
-        "author_inst": "University of Antwerp"
-      },
-      {
-        "author_name": "Matilda Berkell",
-        "author_inst": "University of Antwerp"
-      },
-      {
-        "author_name": "Alessia Savoldi",
-        "author_inst": "University of Verona"
-      },
-      {
-        "author_name": "Matteo Morra",
-        "author_inst": "University of Verona"
-      },
-      {
-        "author_name": "Vincent Van averbeke",
-        "author_inst": "University of Antwerp"
+        "author_name": "Diana Carolina L\u00f3pez-Farf\u00e1n",
+        "author_inst": "Institute of Parasitology and Biomedicine L\u00f3pez-Neyra (IPBLN-CSIC)"
       },
       {
-        "author_name": "Fien De Winter",
-        "author_inst": "University of Antwerp"
+        "author_name": "Rakiswend\u00e9 Serge Yerbanga",
+        "author_inst": "Institut de Recherche en Sciences de la Sante"
       },
       {
-        "author_name": "Denise Peserico",
-        "author_inst": "University of Verona"
+        "author_name": "Marina Parres-Mercader",
+        "author_inst": "Institute of Parasitology and Biomedicine L\u00f3pez-Neyra (IPBLN-CSIC)"
       },
       {
-        "author_name": "Elisa Danese",
-        "author_inst": "University of Verona"
+        "author_name": "Manuela Torres-Puente",
+        "author_inst": "Institute of Biomedicine of Valencia (IBV-CSIC)"
       },
       {
-        "author_name": "An Hotterbeekx",
-        "author_inst": "University of Antwerp"
+        "author_name": "Inmaculada G\u00f3mez-Navarro",
+        "author_inst": "Institute of Biomedicine of Valencia (IBV-CSIC)"
       },
       {
-        "author_name": "Elda Righi",
-        "author_inst": "University of Verona"
+        "author_name": "Do Malick Soufiane Sanou",
+        "author_inst": "Institut de Recherche en Sciences de la Sant\u00e9"
       },
       {
-        "author_name": "- mAb ORCHESTRA working group",
-        "author_inst": "-"
+        "author_name": "Adama Franck Yao",
+        "author_inst": "Institut de Recherche en Sciences de la Sant\u00e9"
       },
       {
-        "author_name": "Pasquale De Nardo",
-        "author_inst": "University of Verona"
+        "author_name": "Jean Bosco Ou\u00e9draogo",
+        "author_inst": "Institut de Recherche en Sciences de la Sant\u00e9"
       },
       {
-        "author_name": "Evelina Tacconelli",
-        "author_inst": "University of Verona"
+        "author_name": "I\u00f1aki Comas",
+        "author_inst": "Institute of Biomedicine of Valencia (IBV-CSIC)"
       },
       {
-        "author_name": "Surbhi Malhotra-Kumar",
-        "author_inst": "University of Antwerp"
+        "author_name": "Nerea Irigoyen",
+        "author_inst": "Division of Virology, Department of Pathology, University of Cambridge"
       },
       {
-        "author_name": "Samir Kumar-Singh",
-        "author_inst": "University of Antwerp"
+        "author_name": "Elena G\u00f3mez-D\u00edaz",
+        "author_inst": "Institute of Parasitology and Biomedicine L\u00f3pez-Neyra (IPBLN-CSIC)"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -167019,123 +167789,107 @@
     "category": "neuroscience"
   },
   {
-    "rel_doi": "10.1101/2022.09.15.507787",
-    "rel_title": "Imprinted SARS-CoV-2 humoral immunity induces converging Omicron RBD evolution",
+    "rel_doi": "10.1101/2022.09.15.508120",
+    "rel_title": "SARS-CoV-2 and HSV-1 Induce Amyloid Aggregation in Human CSF",
     "rel_date": "2022-09-16",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.15.507787",
-    "rel_abs": "Continuous evolution of Omicron has led to a rapid and simultaneous emergence of numerous variants that display growth advantages over BA. 5. Despite their divergent evolutionary courses, mutations on their receptor-binding domain (RBD) converge on several hotspots. The driving force and destination of such convergent evolution and its impact on humoral immunity remain unclear. Here, we demonstrate that these convergent mutations can cause striking evasion of neutralizing antibody (NAb) drugs and convalescent plasma, including those from BA.5 breakthrough infection, while maintaining sufficient ACE2 binding capability. BQ.1.1.10, BA.4.6.3, XBB, and CH. 1.1 are the most antibody-evasive strain tested, even exceeding SARS-CoV-1 level. To delineate the origin of the convergent evolution, we determined the escape mutation profiles and neutralization activity of monoclonal antibodies (mAbs) isolated from BA.2 and BA.5 breakthrough-infection convalescents. Importantly, due to humoral immune imprinting, BA.2 and especially BA.5 breakthrough infection caused significant reductions in the epitope diversity of NAbs and increased proportion of non-neutralizing mAbs, which in turn concentrated humoral immune pressure and promoted convergent evolution. Moreover, we showed that the convergent RBD mutations could be accurately inferred by integrated deep mutational scanning (DMS) profiles, and the evolution trends of BA.2.75/BA.5 subvariants could be well-simulated through constructed convergent pseudovirus mutants. Together, our results suggest current herd immunity and BA.5 vaccine boosters may not provide good protection against infection. Broad-spectrum SARS-CoV-2 vaccines and NAb drugs development should be highly prioritized, and the constructed mutants could help to examine their effectiveness in advance.",
-    "rel_num_authors": 26,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.15.508120",
+    "rel_abs": "The corona virus (SARS-CoV-2) pandemic and the resulting long-term neurological complications in patients, known as long COVID, have renewed the interest in the correlation between viral infections and neurodegenerative brain disorders. While many viruses can reach the central nervous system (CNS) causing acute or chronic infections (such as herpes simplex virus 1, HSV-1), the lack of a clear mechanistic link between viruses and protein aggregation into amyloids, a characteristic of several neurodegenerative diseases, has rendered such a connection elusive. Recently, we showed that viruses can induce aggregation of purified amyloidogenic proteins via the direct physicochemical mechanism of heterogenous nucleation (HEN). In the current study, we show that the incubation of HSV-1 and SARS-CoV-2 with human cerebrospinal fluid (CSF) leads to the amyloid aggregation of several proteins known to be involved in neurodegenerative diseases, such as: APLP1 (amyloid beta precursor like protein 1), ApoE, clusterin, 2-macroglobulin, PGK-1 (phosphoglycerate kinase 1), ceruloplasmin, nucleolin, 14-3-3, transthyretin and vitronectin. Importantly, UV-inactivation of SARS-CoV-2 does not affect its ability to induce amyloid aggregation, as amyloid formation is dependent on viral surface catalysis via HEN and not its ability to replicate. Our results show that viruses can physically induce amyloid aggregation of proteins in human CSF, and thus providing a potential mechanism that may account for the association between persistent and latent/reactivating brain infections and neurodegenerative diseases.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Yunlong Cao",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University; Changping Laboratory"
-      },
-      {
-        "author_name": "Fanchong Jian",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
-      },
-      {
-        "author_name": "Jing Wang",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
-      },
-      {
-        "author_name": "Yuanling Yu",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
-      },
-      {
-        "author_name": "Weiliang Song",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+        "author_name": "Wanda Christ",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Ayijiang Yisimayi",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+        "author_name": "Sebastian Kapell",
+        "author_inst": "Stockholm University"
       },
       {
-        "author_name": "Jing Wang",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Georgios Mermelekas",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Ran An",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Bjorn Evertsson",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Xiaosu Chen",
-        "author_inst": "Institute for Immunology, College of Life Sciences, Nankai University"
+        "author_name": "Helena Sork",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Na Zhang",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Safa Bazaz",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Yao Wang",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Oskar Gustafsson",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Peng Wang",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Michal J. Sobkowiak",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Lijuan Zhao",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Eduardo I. Cardenas",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Haiyan Sun",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Viviana Villa",
+        "author_inst": "University of Genoa"
       },
       {
-        "author_name": "Lingling Yu",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Roberta Ricciarelli",
+        "author_inst": "University of Genoa"
       },
       {
-        "author_name": "Sijie Yang",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+        "author_name": "Johan K Sandberg",
+        "author_inst": "Karolinska Institutet"
       },
       {
-        "author_name": "Xiao Niu",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+        "author_name": "Jonas Bergquist",
+        "author_inst": "Uppsala University"
       },
       {
-        "author_name": "Tianhe Xiao",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+        "author_name": "Andrea Sturchio",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Qingqing Gu",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Per Svenningsson",
+        "author_inst": "Karolinska Institutet"
       },
       {
-        "author_name": "Fei Shao",
-        "author_inst": "Changping Laboratory, Beijing, P.R. China."
+        "author_name": "Tarja Malm",
+        "author_inst": "University of Eastern Finland"
       },
       {
-        "author_name": "Xiaohua Hao",
-        "author_inst": "Beijing Ditan Hospital, Capital Medical University, Beijing, P.R. China."
+        "author_name": "Alberto J. Espay",
+        "author_inst": "University of Cincinnati"
       },
       {
-        "author_name": "Yanli Xu",
-        "author_inst": "Beijing Ditan Hospital, Capital Medical University, Beijing, P.R. China."
+        "author_name": "Maria Pernemalm",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Ronghua Jin",
-        "author_inst": "Beijing Ditan Hospital, Capital Medical University, Beijing, P.R. China."
+        "author_name": "Anders Linden",
+        "author_inst": "Karolinska Institute"
       },
       {
-        "author_name": "Zhongyang Shen",
-        "author_inst": "Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University"
+        "author_name": "Jonas Klingstrom",
+        "author_inst": "Center for Infectious Medicine, Department of Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden"
       },
       {
-        "author_name": "Youchun Wang",
-        "author_inst": "Changping Laboratory; Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug C"
+        "author_name": "Samir EL Andaloussi",
+        "author_inst": "Karolinska Institutet"
       },
       {
-        "author_name": "Xiaoliang Sunney Xie",
-        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University; Changping Laboratory"
+        "author_name": "Kariem Ezzat",
+        "author_inst": "Karolinska Institute"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.09.16.507742",
@@ -169041,47 +169795,103 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.09.14.507948",
-    "rel_title": "HLA variants and TCR diversity against SARS-CoV-2 in the pre-COVID-19 era",
+    "rel_doi": "10.1101/2022.09.14.507904",
+    "rel_title": "The SARS-CoV-2 spike N-terminal domain engages 9-O-acetylated \u03b12-8-linked sialic acids",
     "rel_date": "2022-09-14",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.14.507948",
-    "rel_abs": "HLA antigen presentation and T-cell immunity are critical to control viral infection such as SARS-CoV-2. This study performed on samples collected in the pre-COVID-19 era demonstrates that individuals are fully equiped at the genetic level in terms of TCR repertoire and HLA variants to recognize and kill SARS-CoV-2 infected cells. HLA diversity, heterologous immunity and random somatic TCR recombination could explain these observations.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.14.507904",
+    "rel_abs": "SARS-CoV-2 viruses engage ACE2 as a functional receptor with their spike protein. The S1 domain of the spike protein contains a C-terminal receptor-binding domain (RBD) and an N-terminal domain (NTD). The NTD of other coronaviruses includes a glycan-binding cleft. However, for the SARS-CoV-2 NTD protein-glycan binding was only observed weakly for sialic acids with highly sensitive methods. Amino acid changes in the NTD of Variants of Concern (VoC) shows antigenic pressure, which can be an indication of NTD-mediated receptor binding. Trimeric NTD proteins of SARS-CoV-2, Alpha, Beta, Delta, and Omicron did not reveal a receptor binding capability. Unexpectedly, the SARS-CoV-2 Beta subvariant strain (501Y.V2-1) NTD binding to Vero E6 cells was sensitive to sialidase pretreatment. Glycan microarray analyses identified a putative 9-O-acetylated sialic acid as a ligand, which was confirmed by catch-and-release ESI-MS, STD-NMR analyses, and a graphene-based electrochemical sensor. The Beta (501Y.V2-1) variant attained an enhanced glycan binding modality in the NTD with specificity towards 9-O-acetylated structures, suggesting a dual-receptor functionality of the SARS-CoV-2 S1 domain, which was quickly selected against. These results indicate that SARS-CoV-2 can probe additional evolutionary space, allowing binding to glycan receptors on the surface of target cells.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=76 HEIGHT=200 SRC=\"FIGDIR/small/507904v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (31K):\norg.highwire.dtl.DTLVardef@1f98a70org.highwire.dtl.DTLVardef@1efc119org.highwire.dtl.DTLVardef@16e8bc6org.highwire.dtl.DTLVardef@9a74e6_HPS_FORMAT_FIGEXP  M_FIG C_FIG SynopsisCoronaviruses utilize their N-terminal domain (NTD) for initial reversible low-affinity interaction to (sialylated) glycans. This initial low-affinity/high-avidity engagement enables viral surfing on the target membrane, potentially followed by a stronger secondary receptor interaction. Several coronaviruses, such as HKU1 and OC43, possess a hemagglutinin-esterase for viral release after sialic acid interaction, thus allowing viral dissemination. Other coronaviruses, such as MERS-CoV, do not possess a hemagglutinin-esterase, but interact reversibly to sialic acids allowing for viral surfing and dissemination. The early 501Y.V2-1 subvariant of the Beta SARS-CoV-2 Variant of Concern has attained a receptor-binding functionality towards 9-O-acetylated sialic acid using its NTD. This binding functionality was selected against rapidly, most likely due to poor dissemination. Ablation of sialic acid binding in more recent SARS-CoV-2 Variants of Concern suggests a fine balance of sialic acid interaction of SARS-CoV-2 is required for infection and/or transmission.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Stephane Buhler",
-        "author_inst": "Geneva University Hospitals"
+        "author_name": "Ilhan Tomris",
+        "author_inst": "Utrecht University"
       },
       {
-        "author_name": "Zuleika Calderin Sollet",
-        "author_inst": "Geneva University Hospitals"
+        "author_name": "Luca Unione",
+        "author_inst": "CICbioGUNE Basque Research & Technology Alliance"
       },
       {
-        "author_name": "Florence Bettens",
-        "author_inst": "Geneva University Hospitals"
+        "author_name": "Linh Nguyen",
+        "author_inst": "University of Alberta"
       },
       {
-        "author_name": "Antonia Schaefer",
-        "author_inst": "Geneva University Hospitals"
+        "author_name": "Pouya Zaree",
+        "author_inst": "Utrecht University"
       },
       {
-        "author_name": "Marc Ansari",
-        "author_inst": "Geneva University Hospitals"
+        "author_name": "Kim M. Bouwman",
+        "author_inst": "Utrecht University"
       },
       {
-        "author_name": "Sylvie Ferrari-Lacraz",
-        "author_inst": "Geneva University Hospitals"
+        "author_name": "Lin Liu",
+        "author_inst": "University of Georgia"
       },
       {
-        "author_name": "Jean Villard",
-        "author_inst": "Geneva University Hospitals"
+        "author_name": "Zeshi Li",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Jelle A. Fok",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Mar\u00eda R\u00edos Carrasco",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Roosmarijn van der Woude",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Anne L.M. Kimpel",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Mirte W. Linthorst",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Enrico C.J.M. Verpalen",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Tom G. Caniels",
+        "author_inst": "Amsterdam UMC"
+      },
+      {
+        "author_name": "Rogier W. Sanders",
+        "author_inst": "Amsterdam UMC"
+      },
+      {
+        "author_name": "Balthasar A. Heesters",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Roland J. Pieters",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Jes\u00fas Jim\u00e9nez-Barbero",
+        "author_inst": "CICbioGUNE Basque Research & Technology Alliance"
+      },
+      {
+        "author_name": "John S. Klassen",
+        "author_inst": "University of Alberta"
+      },
+      {
+        "author_name": "Geert-Jan Boons",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Robert P. de Vries",
+        "author_inst": "Utrecht University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2022.09.13.22279846",
@@ -170751,31 +171561,39 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.09.09.507303",
-    "rel_title": "Expression profiling of immune-response-genes common in SARS-CoV-1 and influenza A virus disease, viz-a-viz neutropenia disorder, using integrated bioinformatics tools",
+    "rel_doi": "10.1101/2022.09.09.22279725",
+    "rel_title": "Effectiveness of incentivized peer referral to increase enrollment in a community-based chlamydia screening and treatment study among young Black men",
     "rel_date": "2022-09-10",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.09.507303",
-    "rel_abs": "Viral diseases have proven to be an existential threat to man due to its fatality and its consistent emergence and re-emergence, so the need for novel ideas in combating this menace. Advances in genetic studies has proven to be indispensable in this fight as knowledge of organismal genetic variability has been useful in therapy development, as well as in mounting defense against the treacherous infectious agents. However, there are still fallow grounds needing to be explored in this war which informed this study, with focus on expression profiling of similar immune-responsegenes in SARS-COV-1 and influenza A virus (AIV) in respect to neutropenia (NP), using integrated bioinformatics techniques such as extraction of microarray dataset in the gene expression omnibus (GEO) database, generation of DEGs using GEO2R tool, construction of protein-protein interaction (PPI) network using string and Cytoscape software, Venn diagram analysis and then gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) for enrichment and pathway analysis respectively. Ten genes which includes ELANE, ITGA2B, CXCR1, CSF3R, SPI1, MS4A3, MMP8, CEACAM8, RNASE3, and DEFA4 were identified, with ELANE gene moreover identified as a key gene, which might be responsible in the regulation of immune response during viral infection, based on its characteristic feature in the PPI network.",
-    "rel_num_authors": 3,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.09.22279725",
+    "rel_abs": "PurposeIncentivized peer referral (IPR) has been shown to be an effective method of recruitment for men who have sex with men but has not been studied extensively in men who have sex with women (MSW), particularly among Black MSW. We aimed to determine if IPR was more effective than uncompensated peer referral for recruiting young Black men into a community STI screening study.\n\nMethodsWe used data from the Check It study, a chlamydia (Ct) screening and treatment program for young Black men ages 15-26 in New Orleans, LA. Enrollment was compared before and after IPR was implemented using Multiple Series Analysis (MTSA). IPR was introduced to increase recruitment that had been severely diminished because of the COVID-19 shutdown.\n\nResultsOf 1527 men enrolled, 1399 (91.6%) were enrolled pre-IPR and 128 (8.4%) were enrolled post-IPR. The percentage of men referred by a friend or peer was higher in the post-IPR period than in the pre-IPR period (45.7% vs. 19.7%, p<0.001). Post-pandemic, we observed a statistically significant increase of 2.007 more recruitments (p=0.044, 95% CI (0.0515, 3.964)) at the start of the post-IPR era, compared to the pre-IPR era. Overall, we also observed a trending increase in recruitments in the IPR era relative to the pre-IPR era (0.0174 recruitments/week, p=0.285, 95% CI (-0.0146, 0.0493)) with less recruitment decay in the post-IPR compared to pre-IPR.\n\nConclusionsIPR may be an effective means of engaging young Black men in community based STI research and prevention programs, particularly when clinic access is limited.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Ayinde Charles Olaniyi",
-        "author_inst": "Ladoke Akintola University of Technology"
+        "author_name": "Mary Beth Campbell",
+        "author_inst": "Tulane University School of Public Health and Tropical Medicine - Department of Epidemiology"
       },
       {
-        "author_name": "Obasanmi Dorcas Oluwadamilola",
-        "author_inst": "university of Lagos"
+        "author_name": "Aneeka Ratnayake",
+        "author_inst": "Tulane University School of Public Health and Tropical Medicine - Department of Epidemiology"
       },
       {
-        "author_name": "Alabi Temitope Oluwabunmi",
-        "author_inst": "Ladoke Akintola University of Technology"
+        "author_name": "G\u00e9rard Gomes",
+        "author_inst": "Tulane School of Public Health and Tropical Medicine - Department of Epidemiology"
+      },
+      {
+        "author_name": "Charles Stoecker",
+        "author_inst": "Tulane University School of Public Health and Tropical Medicine -Department of Health Policy and Management"
+      },
+      {
+        "author_name": "Patricia J Kissinger",
+        "author_inst": "Tulane University School of Public Health and Tropical Medicine - Department of Epidemiology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "genetics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "sexual and reproductive health"
   },
   {
     "rel_doi": "10.1101/2022.09.09.22279787",
@@ -173037,23 +173855,51 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.09.05.22279623",
-    "rel_title": "Modeling vaccine allocation and equity implications of COVID-19 containment strategies",
+    "rel_doi": "10.1101/2022.09.09.22279760",
+    "rel_title": "Parental experiences of the impacts of COVID-19 on the care of young children; qualitative interview findings from the Nairobi Early Childcare in Slums (NECS) Project",
     "rel_date": "2022-09-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.05.22279623",
-    "rel_abs": "Given the shortage of global COVID-19 vaccines, a critical public concern is whether the strategy of allocation exerts a heterogeneous effect on settings that have imbalanced accessibility. Exacerbated by the mutational characteristics of the pathogen, traits of immunity protection of vaccines, and diversification of human behaviors, the pathway to the full eradication of the COVID-19 pandemic is becoming increasingly complicated and indeterminate. Population-wide evaluation of public interventions remains crucial to evaluate the performance of epidemiology policies. This study employs a mathematical compartmental model combined with the observational data of the United States to examine the potential effect of vaccine allocation on the trajectory of COVID-19 transmission and the elicited equity implications. The outcomes imply that allocation strategies substantially impact the cumulative equilibrium size of a pandemic controlling for confounding factors. Under a framework of a two-dose primary vaccination strategy aiming to curb the total infections for high-accessibility settings (HAS) and low-accessibility settings(LAS), the traits of vaccination, pathogen, and human effort integrally affect the equilibrium of the COVID-19 pandemic in the medium perspective (i.e., up to 5 years). Vaccine allocation increases the healthcare and cost burden for HAS temporarily, in contrast, it reduces the risk of COVID-19 transmission for the LAS. The effects are consistent across a variety of profiles. By enhancing the administration rates of primary doses (i.e., mainly through dose 1 and dose 2), the magnitude of the COVID-19 pandemic decreases contingent on confounding factors. To minimize the magnitude of infection, it is of importance to dynamically monitor the immunity protection of vaccines, the dynamics of virus transmission, and the gap in the human effort.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.09.22279760",
+    "rel_abs": "IntroductionThe Covid-19 pandemic, and societal attempts to control it, have touched almost every aspect of peoples lives around the world, albeit in unequal ways. In particular, there is considerable concern about the way that stringent  lockdowns, as implemented in Kenya and many other countries, affected young children, especially those living in informal settlements. However, to date, there has been little research attempting to unpack and understand how the pandemic has impacted on the care of young children.\n\nMethodsIn-depth telephone interviews were conducted with 21 parents/carers of children aged under five years living in three Nairobi slums between May and September 2021 exploring the ways in which covid-19, and policies to control the pandemic, impacted on their household and the care of their child/children.\n\nResultsThe impacts of covid-19 control measures on the care of children have been widely felt, deep and multiple. The impact of economic hardship has been significant, reportedly undermining food security and access to services including healthcare and childcare. Respondents reported an associated increase in domestic and community violence. Many people relied on help from others; this was most commonly reported to be in the form of variable levels of flexibility from landlords and help from other community members. No direct harms from covid-19 disease were reported by respondents.\n\nConclusionThe impacts of covid-19 control measures on the care of young children in informal settlements have been indirect but dramatic. Given the breadth and depth of these reported impacts, and the particular vulnerability of young children, deeper consideration ought to inform decisions about approaches to implementation of stringent disease control measures in future. In addition, these findings imply a need for both short- and long-term policy responses to ameliorate the impacts described.\n\nKey messages O_TEXTBOXO_LIYoung children living in slums, while at low direct risk from Covid-19, are highly vulnerable to early childhood adversity, so may be at great risk from economic and other hardships that are a likely  side effect of blunt pandemic control measures like stringent  lockdowns.\nC_LIO_LIParent/carers described a set of indirect impacts of covid-19 control efforts that were broad, deep and protracted. Core to these impacts was widespread economic hardship, with knock on effects on household food security, wellbeing and community safety.\nC_LIO_LIConsidering the particular risks and vulnerability that blunt pandemic control measures present to young children, especially those in slums, needs to be central to policy discussions about if and how to implement stringent disease-control measures. In addition, more research is required to quantify the issues identified in this qualitative inquiry.\nC_LI\n\nC_TEXTBOX",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Ichiro Nakamoto",
-        "author_inst": "Fujian University of Technology, School of Internet Economics and Business"
+        "author_name": "Robert  C Hughes",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "Ruth Muendo",
+        "author_inst": "APHRC: African Population and Health Research Center"
+      },
+      {
+        "author_name": "Sunil  S Bhopal",
+        "author_inst": "Newcastle University School of Population and Health Sciences: Newcastle University Population Health Sciences Institute"
+      },
+      {
+        "author_name": "Silas Onyango",
+        "author_inst": "African Population and Health Research Center"
+      },
+      {
+        "author_name": "Elizabeth Kimani-Murage",
+        "author_inst": "African Population and Health Research Center"
+      },
+      {
+        "author_name": "Betty  R Kirkwood",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "Zelee Hill",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Patricia Kitsao-Wekulo",
+        "author_inst": "African Population and Health Research Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2022.09.07.22279692",
@@ -174847,59 +175693,147 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.09.05.506626",
-    "rel_title": "Immune dynamics at single cell protein level after delta/omicron infection in COVID-19 vaccinated convalescent individuals",
+    "rel_doi": "10.1101/2022.09.06.506714",
+    "rel_title": "Heterologous boost with mRNA vaccines against SARS-CoV-2 Delta/Omicron variants following an inactivated whole-virus vaccine",
     "rel_date": "2022-09-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.05.506626",
-    "rel_abs": "Both COVID-19 mRNA or recombinant Adenovirus vector (rAdVV) based vaccines have shown a great efficacy in generating humoral and cellular immune responses. Two doses of the COVID-19 vaccines generate enough antibodies and generate spike-specific T cell responses. However, after 6-8 months there is a decline in antibody production and T cell responses. Due to the rise of new SARS-CoV-2 variants of concern, a third or even fourth dose of vaccine was recommended for the elderly, immune comprised and frontline medical health care workers. However, despite additional booster doses given, those who were infected with either delta or omicron (during December 2021 - March 2022) had symptoms of illness. By what means these COVID-19 vaccines provide immunity against the SARS-CoV-2 virus at the molecular level is not explored extensively yet and, it is an emerging research field as to how the SARS-CoV-2 virus is able to evade the host immunity. Most of the infected people had mild symptoms whilst some were asymptomatic. Many of the people had developed nucleocapsid antibodies against the SARS-CoV-2 delta/omicron variants confirming a humoral immune response against viral infection. Furthermore, cellular analysis shows that post-vaccinated recovered COVID-19 individuals have significantly reduced NK cells and increased T naive CD4+, TEM CD8+ and B cells. This decrease in cellular immunity corresponds to individuals who recovered from alpha variants infection and had mild symptoms. Our results highlight that booster doses clearly reduce the severity of infection against delta/omicron infection. Furthermore, our cellular and humoral immune system is trained by vaccines and ready to deal with breakthrough infections in the future.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.06.506714",
+    "rel_abs": "The coronavirus SARS-CoV-2 has mutated quickly and caused significant global damage. This study characterizes two mRNA vaccines ZSVG-02 (Delta) and ZSVG-02-O (Omicron BA.1), and associating heterologous prime-boost strategy following the prime of a most widely administrated inactivated whole-virus vaccine (BBIBP-CorV). The ZSVG-02-O induces neutralizing antibodies that effectively cross-react with Omicron subvariants following an order of BA.1>BA.2>BA.4/5. In naive animals, ZSVG-02 or ZSVG-02-O induce humoral responses skewed to the vaccines targeting strains, but cellular immune responses cross-react to all variants of concern (VOCs) tested. Following heterologous prime-boost regimes, animals present comparable neutralizing antibody levels and superior protection across all VOCs. Single-boost only generated ancestral and omicron dual-responsive antibodies, probably by \"recall\" and \"reshape\" the prime immunity. New Omicron-specific antibody populations, however, appeared only following the second boost with ZSVG-02-O. Overall, our results support a heterologous boost with ZSVG-02-O, providing the best protection against current VOCs in inactivated virus vaccine- primed populations.",
+    "rel_num_authors": 32,
     "rel_authors": [
       {
-        "author_name": "Rimpi Bajaj",
-        "author_inst": "Tuebingen University"
+        "author_name": "Changrui Lu",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin)"
       },
       {
-        "author_name": "Zhiqi Yang",
-        "author_inst": "FK, Tuebingen University, Tuebingen"
+        "author_name": "Yuntao Zhang",
+        "author_inst": "China National Biotec Group (CNBG)"
       },
       {
-        "author_name": "Vincent Hammer",
-        "author_inst": "IMGAG Tuebingen University"
+        "author_name": "Xiaohu Liu",
+        "author_inst": "Virogin Biotech (Shanghai) Ltd (Virogin)"
       },
       {
-        "author_name": "Simone Poeschel",
-        "author_inst": "Tuebingen University Hospital"
+        "author_name": "Fujun Hou",
+        "author_inst": "Virogin Biotech (Shanghai) Ltd (Virogin)"
       },
       {
-        "author_name": "Kristin Beiber",
-        "author_inst": "Tuebingen University Hospital"
+        "author_name": "Rujie Cai",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin)"
       },
       {
-        "author_name": "Madhuri S Salker",
-        "author_inst": "FK Tuebingen University"
+        "author_name": "Zhibin Yu",
+        "author_inst": "Virogin Biotech (Shanghai) Ltd (Virogin)"
       },
       {
-        "author_name": "Nicolas Casadei",
-        "author_inst": "Tuebingen University"
+        "author_name": "Fei Liu",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin)"
       },
       {
-        "author_name": "Stephan Ossowski",
-        "author_inst": "University of Tuebingen"
+        "author_name": "Guohuan Yang",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin)"
       },
       {
-        "author_name": "Olaf Riess",
-        "author_inst": "Tuebingen University"
+        "author_name": "Jun Ding",
+        "author_inst": "Virogin Biotech (Shanghai) Ltd (Virogin)"
       },
       {
-        "author_name": "Yogesh Singh",
-        "author_inst": "Tuebingen University"
+        "author_name": "Jiang Xu",
+        "author_inst": "Virogin Biotech (Shanghai) Ltd (Virogin)"
+      },
+      {
+        "author_name": "Xianwu Hua",
+        "author_inst": "Virogin Biotech (Shanghai) Ltd (Virogin)"
+      },
+      {
+        "author_name": "Xinping Pan",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin)"
+      },
+      {
+        "author_name": "Lianxiao Liu",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin)"
+      },
+      {
+        "author_name": "Kang Lin",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin)"
+      },
+      {
+        "author_name": "Zejun Wang",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Xinguo Li",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Jia Lu",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Qiu Zhang",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Yuwei Li",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Chunxia Hu",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Huifeng Fan",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Xiaoke Liu",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Hui Wang",
+        "author_inst": "Wuhan Institute of Biological Products Co., LTD (WIBP)"
+      },
+      {
+        "author_name": "Rui Jia",
+        "author_inst": "China National Biotec Group (CNBG)"
+      },
+      {
+        "author_name": "Fangjingwei Xu",
+        "author_inst": "China National Biotec Group (CNBG)"
+      },
+      {
+        "author_name": "Xuewei Wang",
+        "author_inst": "China National Biotec Group (CNBG)"
+      },
+      {
+        "author_name": "Hongwei Huang",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin); Virogin Biotech (Shanghai) Ltd (Virogin)"
+      },
+      {
+        "author_name": "Ronghua Zhao",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin); Virogin Biotech (Shanghai) Ltd (Virogin)"
+      },
+      {
+        "author_name": "Jing Li",
+        "author_inst": "Shuimu BioSciences Ltd."
+      },
+      {
+        "author_name": "Hang Cheng",
+        "author_inst": "Shuimu BioSciences Ltd."
+      },
+      {
+        "author_name": "William Jia",
+        "author_inst": "China National Biological Group-Virogin Biotech (Shanghai) Ltd (CNBG-Virogin); Virogin Biotech (Shanghai) Ltd (Virogin)"
+      },
+      {
+        "author_name": "Xiaoming Yang",
+        "author_inst": "China National Biotec Group (CNBG)"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2022.09.06.506814",
@@ -176809,99 +177743,71 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.09.02.506305",
-    "rel_title": "Novel monoclonal antibodies showing broad neutralizing activity for SARS-CoV-2 variants including Omicrons BA.5 and BA.2.75",
+    "rel_doi": "10.1101/2022.09.01.506266",
+    "rel_title": "Neutrophil extracellular traps have auto-catabolic activity and produce mononucleosome-associated circulating DNA",
     "rel_date": "2022-09-02",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.02.506305",
-    "rel_abs": "We identified novel neutralizing monoclonal antibodies against SARS-CoV-2 variants (including Omicron) from individuals received two doses of mRNA vaccination after they had been infected with wildtype. We named them MO1, MO2 and MO3. MO1 shows high neutralizing activity against authentic variants: D614G, Delta, BA.1, BA.1.1, BA.2, and BA.2.75 and BA.5. Our findings confirm that the wildtype-derived vaccination can induce neutralizing antibodies that recognize the epitopes conserved among the SARS-CoV-2 variants (including BA.5 and BA.2.75). The monoclonal antibodies obtained herein could serve as novel prophylaxis and therapeutics against not only current SARS-CoV-2 viruses but also future variants that may arise.",
-    "rel_num_authors": 20,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.01.506266",
+    "rel_abs": "BackgroundBecause circulating DNA (cirDNA) are mainly detected as mononucleosome-associated circulating DNA (mono-N cirDNA) in blood apoptosis has until now been considered as the main source of cirDNA. The mechanism of cirDNA release into the circulation, however, is still not fully understood. This work addresses that knowledge gap, working from the postulate that neutrophil extracellular traps (NET) may be a source of cirDNA, and by investigating whether NET may directly produce mono-N cirDNA\n\nMethodsWe used the synergistic analytical information provided by specifically quantifying DNA by qPCR, and analyzing fragment size analysis by shallow WGS, and capillary electrophoresis to unequivocally study the following: the in vitro kinetics of cell derived genomic high molecular weight (gHMW) DNA degradation in serum; the production of extracellular DNA and NET markers such as neutrophil elastase (NE) and myeloperoxidase (MPO) by ex vivo activated neutrophils; in vitro NET degradation in serum. We also performed an in vivo study in knockout mice, and an in vitro study of gHMW DNA degradation, to elucidate the role of NE and MPO in effecting DNA degradation and fragmentation. We then compared the NET associated markers and fragmentation size profiles of cirDNA in plasma obtained from patients with inflammatory diseases found to be associated with NET formation and high levels of cirDNA (COVID-19, N= 28; systemic lupus erythematosus, N= 10; metastatic colorectal cancer, N= 10; and from healthy individuals, N= 114).\n\nResultsOur studies reveal that: gHMW DNA degradation in serum results in the accumulation of mono-N DNA (81.3% of the remaining DNA following 24H incubation in serum corresponded to mono-N DNA); \"ex vivo\" NET formation, as demonstrated by a concurrent 5-, 5- and 35-fold increase of NE, MPO, and cell-free DNA (cfDNA) concentration in PMA-activated neutrophil culture supernatant, leads to the release of high molecular weight DNA that degrades down to mono-N in serum; NET mainly in the form of gHMW DNA generate mono-N cirDNA (2% and 41% of the remaining DNA after 2 hours in serum corresponded to 1-10 kbp fragments and mono-N, respectively) independent of any cellular process when degraded in serum; NE and MPO may contribute synergistically to NET autocatabolism, resulting in a 25-fold decrease in total DNA concentration and a DNA fragment size profile similar to that observed from cirDNA following 8h incubation with both NE and MPO; the cirDNA size profile of NE KO mice significantly differed from that of the WT, suggesting NE involvement in DNA degradation; and a significant increase in the levels of NE, MPO and cirDNA was detected in plasma samples from lupus, COVID-19 and mCRC, showing a high correlation with these inflammatory diseases, while no correlation of NE and MPO with cirDNA was found in HI.\n\nConclusionsOur work thus describes the mechanisms by which NET and cirDNA are linked, by demonstrating that NET are a major source of mono-N cirDNA independent of apoptosis, and thus establishing a new paradigm of the mechanisms of cirDNA release in normal and pathological conditions, as well as demonstrating a link between immune response and cirDNA.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Hanako Ishimaru",
-        "author_inst": "Kobe  University Graduate School of Medicine School of Medicine:"
-      },
-      {
-        "author_name": "Mitsuhiro Nishimura",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
-      },
-      {
-        "author_name": "Lidya Handayani Tjan",
-        "author_inst": "Kobe university Graduate School of Medicine School of Medicine:"
-      },
-      {
-        "author_name": "Silvia Sutandhio",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
-      },
-      {
-        "author_name": "Maria Istiqomah Marini",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
-      },
-      {
-        "author_name": "Gema Barlian Effendi",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
-      },
-      {
-        "author_name": "Hideki Shigematsu",
-        "author_inst": "Japan Synchrotron Radiation Research Institute SPring-8"
-      },
-      {
-        "author_name": "Koji Kato",
-        "author_inst": "Japan Synchrotron Radiation Research Institute SPring-8"
+        "author_name": "Ekaterina PISAREVA",
+        "author_inst": "IRCM"
       },
       {
-        "author_name": "Natsumi Hasegawa",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Lucia Mihalovicova",
+        "author_inst": "IRCM"
       },
       {
-        "author_name": "Kaito Aoki",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Brice Pastor",
+        "author_inst": "IRCM"
       },
       {
-        "author_name": "Yukiya Kurahashi",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Andrei Kudriavstev",
+        "author_inst": "IRCM"
       },
       {
-        "author_name": "Koichi Furukawa",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Alexia Mirandola",
+        "author_inst": "IRCM"
       },
       {
-        "author_name": "Mai Shinohara",
-        "author_inst": "Kobe university Graduate School of Medicine School of Medicine:"
+        "author_name": "Thibault Mazard",
+        "author_inst": "ICM"
       },
       {
-        "author_name": "Tomoka Nakamura",
-        "author_inst": "kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Stephanie Badiou",
+        "author_inst": "CHU Montpellier"
       },
       {
-        "author_name": "Jun Arii",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Ulrich Maus",
+        "author_inst": "Hannover"
       },
       {
-        "author_name": "Tatsuya Nagno",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Lena Ostermann",
+        "author_inst": "Hannover"
       },
       {
-        "author_name": "Sachiko Nakamura",
-        "author_inst": "Hyogo Prefectural Kakogawa Medical Center"
+        "author_name": "Julia Weinmann-Menke",
+        "author_inst": "universitat medizine, mainz"
       },
       {
-        "author_name": "Shigeru Sano",
-        "author_inst": "Hyogo Prefectural Kakogawa Medical Center"
+        "author_name": "Elmo neuberger",
+        "author_inst": "universitat mainz"
       },
       {
-        "author_name": "Sachiyo Iwata",
-        "author_inst": "Hyogo Prefectural Kakogawa Medical Center"
+        "author_name": "Perikles simon",
+        "author_inst": "universitat mainz"
       },
       {
-        "author_name": "Yasuko Mori",
-        "author_inst": "Kobe University Graduate School of Medicine School of Medicine:"
+        "author_name": "Alain THIERRY",
+        "author_inst": "IRCM INSERM U1194"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2022.09.02.22279398",
@@ -178559,33 +179465,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.08.29.22279354",
-    "rel_title": "Coverage and correlates of COVID-19 vaccination among children aged 5-11 years in Alberta, Canada",
+    "rel_doi": "10.1101/2022.08.26.22279283",
+    "rel_title": "An effective volunteer community-based COVID-19 response program: the Vashon, WA Medical Reserve Corp experience",
     "rel_date": "2022-08-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.29.22279354",
-    "rel_abs": "Background and ObjectivesIn Alberta, Canada, the COVID-19 vaccination program for children aged 5-11 years opened on November 26, 2021. Our objectives were to determine the cumulative vaccine coverage, stratified by age, during the first seven months of vaccine availability, and investigate factors associated with vaccine uptake.\n\nMethodsThis retrospective cohort study used population-based administrative health data to assess COVID-19 vaccination coverage among children aged 5-11 years in Alberta, Canada. We determined cumulative vaccine coverage since the time of vaccine availability and used a modified Poisson regression to evaluate factors associated with vaccine uptake.\n\nResultsOf 377,753 eligible children, 43.8 % (n=165,429) received one or more doses of COVID-19 vaccine during the study period (11.2% received only one dose, while 32.5 % received 2 doses). Almost 90% of initial doses were received within the first two months of vaccine availability. Of those eligible for a second dose, only 75.1% (n=122,973) received it during the study time period. We found a step-wise relationship between increasing child age and higher vaccine coverage. Other factors associated with higher vaccine coverage included living in a neighborhood with higher income, in a more densely populated area, and in certain geographic health zones. Registration in a private school was associated with lower vaccine coverage.\n\nConclusionsMessaging around COVID-19 vaccine safety and need should be tailored to child age, rather than uniform across the 5-11 year age range. Opportunities for targeted vaccination interventions should be considered.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.26.22279283",
+    "rel_abs": "BackgroundVashon, WA is a rural community at risk from COVID-19 due to advanced age and limited access to acute care. Medical Reserve Corps are a national network of 800 volunteer healthcare organizations that have contributed to the pandemic response in many communities. Here we evaluate the effectiveness of the Vashon Medical Reserve Corps (VMRC) volunteer, community-based COVID-19 response program that integrated public engagement, SARS-CoV2 testing, contact tracing, vaccination and material support in reducing COVID-19 transmission and severe disease.\n\nMethodsThis observational cross-sectional study compares cumulative COVID-19 case, hospitalization and death rates on Vashon with other King County zip codes and the county at large from February 2020 through November 2021. We developed multiple linear regression models of COVID-19 rates using metrics of age, race/ethnicity, wealth and educational attainment across King County zip codes. Effectiveness of contact tracing was evaluated by timeliness and success of case investigations, and identification and testing of named contacts. Vaccination effectiveness was estimated by comparing time to reach vaccination milestones. We examined vehicle traffic on Vashon ferries and King County highways to understand whether reduced mobility contributed to Vashons reduced COVID-19 rates.\n\nResultsVashons cumulative COVID-19 case rate was 29% that of King County overall and was lower across all age groups and races/ethnicities (both p<.01). A multiple linear regression model showed Vashon to be a significant outlier among King County zip codes with an observed rate 38% of predicted (p<.05), the lowest of any King County zip code. Vashons observed COVID-19 hospitalization and death rates were 22% and 32% of those predicted by parallel regression models. Hence, Vashons demographics do not explain its reduced COVID rates. Traffic reductions on King County highways and Vashon ferries were nearly identical throughout the study period suggesting altered mobility also does not explain Vashons low COVID-19 rates. Effectiveness of VMRCs COVID-19 response program was demonstrated by 1) highly effective contact tracing that rapidly interviewed 93% of cases and subsequently tested 96% of named contacts, and 2) attainment of vaccination milestones 1-4 months earlier than comparable King County zip codes (p<.01).\n\nConclusionVMRCs volunteer, COVID-19 response program was associated with significantly fewer COVID-19 cases than predicted from its demographics. VMRCs contact tracing and vaccination efforts were highly successful and likely contributed to reduced COVID-19 rates. The VMRC experience suggests that a decentralized community-based public health program can be highly effective in implementing epidemic control strategies when focused on an at-risk community. We suggest that MRCs can be particularly effective in extending the reach of county public health departments and should be included in ongoing pandemic planning.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Shannon E MacDonald",
-        "author_inst": "University of Alberta"
+        "author_name": "James Bristow",
+        "author_inst": "Lawrence Berkeley Laboratory: E O Lawrence Berkeley National Laboratory"
       },
       {
-        "author_name": "Laura Reifferscheid",
-        "author_inst": "University of Alberta"
+        "author_name": "Clayton  J. Olney",
+        "author_inst": "Madigan Army Medical Center"
       },
       {
-        "author_name": "Yuba Raj Paudel",
-        "author_inst": "University of Alberta"
+        "author_name": "- Vashon MRC COVID-19 Steering Committee",
+        "author_inst": "-"
       },
       {
-        "author_name": "JOAN ROBINSON",
-        "author_inst": "University of Alberta"
+        "author_name": "John Weinshel",
+        "author_inst": "Vashon Medical Reserve Corps"
+      },
+      {
+        "author_name": "Robert Rovig",
+        "author_inst": "Atlas Genomics"
+      },
+      {
+        "author_name": "Rick Wallace",
+        "author_inst": "VashonBePrepared"
+      },
+      {
+        "author_name": "Karla  J Lindquist",
+        "author_inst": "University of California San Francisco"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -180445,81 +181363,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.08.26.22279242",
-    "rel_title": "A survey of patient and public perceptions and awareness of SARS-CoV-2-related risks among participants in India and South Africa",
+    "rel_doi": "10.1101/2022.08.25.22279238",
+    "rel_title": "Evaluation of Secondary Chemistry due to Disinfection of Indoor Air with Germicidal Ultraviolet Lamps",
     "rel_date": "2022-08-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.26.22279242",
-    "rel_abs": "A cross-sectional survey was performed among the adult population of participating countries, India and South Africa. The purpose of this study was to explore perceptions and awareness of SARS-CoV-2-related risks in the relevant countries. The main outcome measures were the proportion of participants aware of SARS-CoV-2, and their perception of infection risks.\n\nSelf-administered questionnaires were used to collect data via a web- and paper-based survey over three months. For data capturing, Microsoft Excel was employed, and descriptive statistics used for presenting data. Pearsons Chi-squared test was used to assess relationships between variables, and a p-value less than 0.05 was considered significant.\n\nThere were 844 respondents (India: n=660, South Africa: n=184; response rate 87.6%), with a 61.1% vs 38.3% female to male ratio. Post-high-school or university education was the lowest qualification reported by most respondents in India (77.3%) and South Africa (79.3%). Sources of information about the pandemic were usually media and journal publications (73.2%), social media (64.6%), family and friends (47.7%) and government websites (46.2%). Most respondents correctly identified infection prevention measures (such as physical distancing, mask use), with 90.0% reporting improved hand hygiene practices since the pandemic. Hesitancy or refusal to accept the SARS-CoV-2 vaccine was reported among 17.9% and 50.9% of respondents in India and South Africa, respectively. Reasons cited included rushed vaccine development and the futility of vaccines for what respondents considered a self-limiting flu-like illness.\n\nRespondents identified public health promotion measures for SARS-CoV-2. Reported hesitancy to the up-take of SARS-CoV-2 vaccines was much higher in South Africa. Vaccination campaigns should consider robust public engagement and contextually fit communication strategies with multimodal, participatory online and offline initiatives to address public concerns, specifically towards vaccines developed for this pandemic and general vaccine hesitancy.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.25.22279238",
+    "rel_abs": "Air disinfection using Germicidal Ultraviolet light (GUV) has received increasing attention during the COVID-19 pandemic. GUV uses UVC lamps to inactivate microorganisms, but it also initiates photochemistry in air. However, GUVs indoor-air-quality impact has not been investigated in detail. Here, we model the chemistry initiated by GUV at 254 (\"GUV254\") or 222 nm (\"GUV222\") in a typical indoor setting for different ventilation levels. Our analysis showed that GUV254, usually installed in the upper room, can significantly photolyze O3, generating OH radicals that oxidize indoor volatile organic compounds (VOCs) into more oxidized VOCs. Secondary organic aerosol (SOA) is also formed as a VOC-oxidation product. GUV254-induced SOA formation is of the order of 0.1-1 g/m3 for the cases studied here. GUV222 (described by some as harmless to humans and thus applicable for the whole room) with the same effective virus-removal rate makes a smaller indoor-air-quality impact at mid-to-high ventilation rates. This is mainly because of the lower UV irradiance needed and also less efficient OH-generating O3 photolysis than GUV254. GUV222 has a higher impact than GUV254 under poor ventilation due to a small but significant photochemical production of O3 at 222 nm, which does not occur with GUV254.\n\nSynopsisGermicidal ultraviolet light initiates indoor oxidation chemistry, potentially forming indoor air pollutants. The amount is not negligible and depends on both the wavelength of light and the ventilation level.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Oluchi  N Mbamalu",
-        "author_inst": "University of Cape Town Faculty of Health Sciences"
-      },
-      {
-        "author_name": "Surya Surendran",
-        "author_inst": "The George Institute for Global Health India"
-      },
-      {
-        "author_name": "Vrinda Nampoothiri",
-        "author_inst": "Amrita Institute of Medical Sciences"
-      },
-      {
-        "author_name": "Candice Bonaconsa",
-        "author_inst": "University of Cape Town Faculty of Health Sciences"
-      },
-      {
-        "author_name": "Fabia Edathadathil",
-        "author_inst": "Amrita Institute of Medical Sciences"
-      },
-      {
-        "author_name": "Nina Zhu",
-        "author_inst": "Imperial College London Faculty of Medicine - South Kensington Campus: Imperial College London Faculty of Medicine"
-      },
-      {
-        "author_name": "Vanessa Carter",
-        "author_inst": "Health Communication and Social Media"
-      },
-      {
-        "author_name": "Helen Lambert",
-        "author_inst": "University of Bristol Medical School"
-      },
-      {
-        "author_name": "Carolyn Tarrant",
-        "author_inst": "University of Leicester Department of Health Sciences"
-      },
-      {
-        "author_name": "Raheelah Ahmad",
-        "author_inst": "City University of London"
-      },
-      {
-        "author_name": "Adrian Brink",
-        "author_inst": "University of Cape Town Faculty of Health Sciences"
-      },
-      {
-        "author_name": "Ebrahim Steenkamp",
-        "author_inst": "University of Cape Town Department of Statistical Sciences"
-      },
-      {
-        "author_name": "Alison Holmes",
-        "author_inst": "Imperial College London Faculty of Medicine - South Kensington Campus: Imperial College London Faculty of Medicine"
-      },
-      {
-        "author_name": "Sanjeev Singh",
-        "author_inst": "Amrita Institute of Medical Sciences"
+        "author_name": "Zhe Peng",
+        "author_inst": "University of Colorado Boulder"
       },
       {
-        "author_name": "Esmita Charani",
-        "author_inst": "Imperial College London Faculty of Medicine - South Kensington Campus: Imperial College London Faculty of Medicine"
+        "author_name": "Shelly Miller",
+        "author_inst": "University of Colorado Boulder"
       },
       {
-        "author_name": "Marc Mendelson",
-        "author_inst": "University of Cape Town Faculty of Health Sciences"
+        "author_name": "Jose L Jimenez",
+        "author_inst": "University of Colorado Boulder"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -182231,39 +183097,75 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.08.23.505031",
-    "rel_title": "New Insights into How JUUL Electronic Cigarette Aerosols and Aerosol Constituents Affect SARS-CoV-2 Infection of Human Bronchial Epithelial Cells",
+    "rel_doi": "10.1101/2022.08.24.22279160",
+    "rel_title": "Comparing the Safety and Immunogenicity of homologous (Sputnik V) and heterologous (BNT162B2) COVID-19 prime-boost vaccination",
     "rel_date": "2022-08-24",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.23.505031",
-    "rel_abs": "BackgroundThe relationship between the use of tobacco products and SARS-CoV-2 infection is poorly understood and controversial. Most studies have been done with tobacco cigarettes, while few have examined the effect of electronic cigarettes (ECs) on SARS-CoV-2 infection. We tested the hypothesis that EC fluids and aerosols with high concentrations of nicotine promote SARS-COV-2 infection by increasing viral entry into human respiratory epithelial cells.\n\nMethodsResponses of BEAS-2B cells to authentic JUUL aerosols or their individual constituents (propylene glycol (PG)/vegetable glycerin (VG) and nicotine) were compared using three exposure platforms: submerged culture, air-liquid-interface (ALI) exposure in a cloud chamber, and ALI exposure in a Cultex(R) system, which produces authentic heated EC aerosols. SARS-CoV-2 infection machinery was assessed using immunohistochemistry and Western blotting. Specifically, the levels of the SARS-CoV-2 receptor ACE2 (angiotensin converting enzyme 2) and a spike modifying enzyme, TMPRSS2 (transmembrane serine protease 2), were evaluated. Following each exposure, lentivirus pseudoparticles with spike protein and a green-fluorescent reporter were used to test viral penetration and the susceptibility of BEAS-2B cells to infection.\n\nResultsNicotine, EC fluids, and authentic JUUL aerosols increased both ACE2 levels and TMPRSS2 activity, which in turn increased viral particle entry into cells. While most data were in good agreement across the three exposure platforms, cells were more responsive to treatments when exposed at the ALI in the Cultex system, even though the exposures were brief and intermittent. In the Cultex system, PG/VG, PG/VG/nicotine, and JUUL aerosols significantly increased infection above clean air controls. However, both the PG/VG and JUUL treatments were significantly lower than nicotine/PG/VG. PG/VG increased infection only in the Cultex(R) system, which produces heated aerosol.\n\nConclusionOur data are consistent with the conclusion that authentic JUUL aerosols or their individual constituents (nicotine or PG/VG) increase SARS-CoV-2 infection. The strong effect produced by nicotine was modulated in authentic JUUL aerosols, demonstrating the importance of studying mixtures and aerosols from actual EC products. These data support the idea that vaping increases the likelihood of contracting COVID-19.",
-    "rel_num_authors": 5,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.24.22279160",
+    "rel_abs": "Studies have shown increased immunogenicity from heterologous boosting. This study specifically assessed boosting with Pfizer-BioNTech in Sputnik V vaccination regimens. Reactogenicity was assessed through adverse events. Immunogenicity was assessed by comparing serum anti-Spike (Anti-S) protein antibody and neutralizing antibody titers before booster administration and after 30 days. A total of 428 participants were recruited in the heterologous arm and 351 in the homologous arm. Adverse events were more frequent in the heterologous arm (p<0.001). No serious adverse events were reported in either arm. Amongst 577 individuals who completed the study, Anti-S antibodies were 14.8 times higher after heterologous boosting, and 3.1 times higher after homologous boosting (p<0.001). Similarly, heterologous boosting showed a 2 fold increase in neutralizing antibodies, compared to a 1.6 fold increase in homologous boosting (p<0.001). In conclusion, both boosting regimens elicited an immunological response, nonetheless heterologous Pfizer-BioNTech showed a higher immunological response, with more adverse effects.\n\nARTICLE SUMMARY LINEBoth homologous and heterologous boosting are effective in eliciting an immunological response, however heterologous boosting with Pfizer-BioNTech elicited a higher immunological response, with more adverse effects.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Rattapol Phandthong",
-        "author_inst": "University of California, Riverside"
+        "author_name": "Marwa Almadhi",
+        "author_inst": "University of Manchester"
       },
       {
-        "author_name": "Man Wong",
-        "author_inst": "University of California, Riverside"
+        "author_name": "Abdulla AlAwadhi",
+        "author_inst": "Bahrain Defence Force Hospital, Bahrain"
       },
       {
-        "author_name": "Ann Song",
-        "author_inst": "University of California, Riverside"
+        "author_name": "Nigel Stevenson",
+        "author_inst": "Royal College of surgeons in Ireland, Ireland"
       },
       {
-        "author_name": "Teresa Martinez",
-        "author_inst": "University of California, Riverside"
+        "author_name": "Khalid Greish",
+        "author_inst": "Arabian Gulf University, Bahrain"
       },
       {
-        "author_name": "Prue Talbot",
-        "author_inst": "University of California, Riverside"
+        "author_name": "Jaleela Jawad",
+        "author_inst": "Ministry of Health, Bahrain"
+      },
+      {
+        "author_name": "Adel Alsayyad",
+        "author_inst": "Ministry of Health, Bahrain"
+      },
+      {
+        "author_name": "Afaf Mirza",
+        "author_inst": "Ministry of Health, Bahrain"
+      },
+      {
+        "author_name": "Basma Alsaffar",
+        "author_inst": "Ministry of Health, Bahrain"
+      },
+      {
+        "author_name": "Ejlal AlAlawi",
+        "author_inst": "Ministry of Health, Bahrain"
+      },
+      {
+        "author_name": "Khulood Fakhroo",
+        "author_inst": "Ministry of Health, Bahrain"
+      },
+      {
+        "author_name": "Batool AlAlawi",
+        "author_inst": "Public Health Directorate Laboratory, Bahrain"
+      },
+      {
+        "author_name": "Lana Alabbasi",
+        "author_inst": "Royal College of Surgeons in Ireland, Bahrain"
+      },
+      {
+        "author_name": "Noora Aljalahma",
+        "author_inst": "Royal College of Surgeons in Ireland, Bahrain"
+      },
+      {
+        "author_name": "Manaf AlQahtani",
+        "author_inst": "Royal College of Surgeons in Ireland, Bahrain"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "cell biology"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.08.23.22279120",
@@ -184077,49 +184979,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.08.21.22279044",
-    "rel_title": "SARS-CoV-2 IgM and IgG serology and clinical outcomes in COVID-19 patients",
+    "rel_doi": "10.1101/2022.08.19.22278986",
+    "rel_title": "Increased adverse events following third dose of BNT162b2/Pfizer vaccine in those with previous COVID-19, but not with concurrent influenza vaccine.",
     "rel_date": "2022-08-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.21.22279044",
-    "rel_abs": "BackgroundThe SARS-CoV-2 virus has become pandemic for the last 2 years. Inflammatory response to the virus leads to organ dysfunction and death. Predicting the severity of inflammatory response helps in managing critical patients using serology tests IgG and IgM. We conducted a longitudinal study to correlate serum SARS-CoV-2 IgM and IgG serology with clinical outcomes in COVID-19 patients.\n\nMethodsWe analyzed patient data from March to December of 2020 for those who were admitted at AIIMS Rishikesh. Clinical and laboratory data of these patients were collected from the e-hospital portal and analysed. Correlation was seen with clinical outcomes and was assessed using MS Excel 2010 and SPSS software.\n\nResultsOut of 494 patients, the mean age of patients was 48.95 {+/-} 16.40 years and there were more male patients in the study (66.0%). The patients were classified into 4 groups; mild-moderate 328 (67.1%), severe 131 (26.8%) and critical 30 (6.1%). The mean duration from symptom onset to serology testing was 19.87 {+/-} 30.53 days. In-hospital mortality was observed in 25.1% patients. The seropositivity rate (i.e., either IgG or IgM >10 AU) was 50%. There was a significant difference between the 2 groups in terms of IgM Levels (AU/mL) (W = 33428.000, p = <0.001) and IgG Levels (AU/mL) (W = 39256.500, p = <0.001), with the median IgM/ IgG Levels (AU/mL) being highest in the RT-PCR-Positive group. There was no significant difference between the groups in terms of IgM Levels and IgG levels with all other clinical outcomes (disease severity, septic shock, Intensive care admission, mechanical ventilation and mortality).\n\nConclusionSerology (IgM and IgG) levels are high in RTPCR positive group compared to clinical COVID-19. However, serology cannot be useful for the prediction of disease outcomes except few situations. The study also highlights the importance of doing serology at a particular time as antibody titres vary with the duration of the disease.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.19.22278986",
+    "rel_abs": "Prior studies suggest that adverse events (AEs) following doses one and two of BNT162b2/Pfizer vaccine are worse in those with a prior history of COVID-19. To establish whether this outcome applies to a third/booster dose, we conducted a survey with 534 healthcare workers (HCW) in Northeast England, who reported AEs following all three doses of BNT162b2/Pfizer vaccine. We also explored AEs associated with concurrent seasonal influenza immunisation. For all doses of BNT162b2/Pfizer vaccine there was a cluster of systemic AEs that were consistently worse in HCWs with a prior history of COVID-19. AEs were no worse in HCWs who received their third/booster dose within 7 days of the influenza jab, rather than further apart. Gender and the presence of ongoing COVID-19 symptoms (OCS) had no effect on AEs associated with COVID-19 or influenza vaccination, though younger HCWs experienced more AEs overall. Our findings have implications for vaccine hesitancy and immunisation protocols.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Mohan S",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Pratap Kumar",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Prasan Kumar Panda",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Vikram Jain",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Rohit Raina",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Sarama Saha",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "Rachael Raw",
+        "author_inst": "Newcastle University"
       },
       {
-        "author_name": "Vivekandan S",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "Jon Rees",
+        "author_inst": "University of Sunderland"
       },
       {
-        "author_name": "Balram J Omar",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "David  R. Chadwick",
+        "author_inst": "James Cook University Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -185875,41 +186757,69 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2022.08.17.504362",
-    "rel_title": "Ancestral lineage of SARS-CoV-2 is more stable in human biological fluids than Alpha, Beta and Omicron variants of concern",
+    "rel_doi": "10.1101/2022.08.17.504313",
+    "rel_title": "Epistasis lowers the genetic barrier to SARS-CoV-2 neutralizing antibody escape",
     "rel_date": "2022-08-19",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.17.504362",
-    "rel_abs": "SARS-CoV-2 is a zoonotic virus which was first identified in 2019, and has quickly spread worldwide. The virus is primarily transmitted through respiratory droplets from infected persons; however, the virus-laden excretions can contaminate surfaces which can serve as a potential source of infection. Since the beginning of the pandemic, SARS-CoV-2 has continued to evolve and accumulate mutations throughout its genome leading to the emergence of variants of concern (VOCs) which exhibit increased fitness, transmissibility, and/or virulence. However, the stability of SARS-CoV-2 VOCs in biological fluids has not been thoroughly investigated so far. The aim of this study was to determine and compare the stability of different SARS-CoV-2 strains in human biological fluids. Here, we demonstrate that the ancestral strain of Wuhan-like lineage A was more stable than the Alpha VOC B.1.1.7, and the Beta VOC B.1.351 strains in human liquid nasal mucus and sputum. In contrast, there was no difference in stability among the three strains in dried biological fluids. Furthermore, we also show that the Omicron VOC B.1.1.529 strain was less stable than the ancestral Wuhan-like strain in liquid nasal mucus. These studies provide insight into the effect of the molecular evolution of SARS-CoV-2 on environmental virus stability, which is important information for the development of countermeasures against SARS-CoV-2.\n\nImportanceGenetic evolution of SARS-CoV-2 leads to the continuous emergence of novel variants, posing a significant concern to global public health. Five of these variants have been classified so far into variants of concern (VOCs); Alpha, Beta, Gamma, Delta, and Omicron. Previous studies investigated the stability of SARS-CoV-2 under various conditions, but there is a gap of knowledge on the survival of SARS-CoV-2 VOCs in human biological fluids which are clinically relevant. Here, we present evidence that Alpha, Beta, and Omicron VOCs were less stable than the ancestral Wuhan-like strain in human biological fluids. Our findings highlight the potential risk of contaminated human biological fluids in SARS-CoV-2 transmission and contribute to the development of countermeasures against SARS-CoV-2.",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.17.504313",
+    "rel_abs": "Consecutive waves of SARS-CoV-2 infection have been driven in part by the repeated emergence of variants with mutations that confer resistance to neutralizing antibodies Nevertheless, prolonged or repeated antigen exposure generates diverse memory B-cells that can produce affinity matured receptor binding domain (RBD)-specific antibodies that likely contribute to ongoing protection against severe disease. To determine how SARS-CoV-2 omicron variants might escape these broadly neutralizing antibodies, we subjected chimeric viruses encoding spike proteins from ancestral, BA.1 or BA.2 variants to selection pressure by a collection of 40 broadly neutralizing antibodies from individuals with various SARS-CoV-2 antigen exposures. Notably, pre-existing substitutions in the BA.1 and BA.2 spikes facilitated acquisition of resistance to many broadly neutralizing antibodies. Specifically, selection experiments identified numerous RBD substitutions that did not confer resistance to broadly neutralizing antibodies in the context of the ancestral Wuhan-Hu-1 spike sequence, but did so in the context of BA.1 and BA.2. A subset of these substitutions corresponds to those that have appeared in several BA.2 daughter lineages that have recently emerged, such as BA.5. By including as few as 2 or 3 of these additional changes in the context of BA.5, we generated spike proteins that were resistant to nearly all of the 40 broadly neutralizing antibodies and were poorly neutralized by plasma from most individuals. The emergence of omicron variants has therefore not only allowed SARS-CoV-2 escape from previously elicited neutralizing antibodies but also lowered the genetic barrier to the acquisition of resistance to the subset of antibodies that remained effective against early omicron variants.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Taeyong Kwon",
-        "author_inst": "Kansas State University"
+        "author_name": "Leander Witte",
+        "author_inst": "Rockefeller University"
       },
       {
-        "author_name": "Natasha N Gaudreault",
-        "author_inst": "Kansas State University"
+        "author_name": "Viren Baharani",
+        "author_inst": "Rockefeller University"
       },
       {
-        "author_name": "David Meekins",
-        "author_inst": "Kansas State University"
+        "author_name": "Fabian Schmidt",
+        "author_inst": "Rockefeller University"
       },
       {
-        "author_name": "Chester McDowell",
-        "author_inst": "Kansas State Univeristy"
+        "author_name": "Zijun Wang",
+        "author_inst": "Rockefeller University"
       },
       {
-        "author_name": "Konner Cool",
-        "author_inst": "Kansas State University"
+        "author_name": "Alice Cho",
+        "author_inst": "Rockefeller University"
       },
       {
-        "author_name": "Juergen A Richt",
-        "author_inst": "Kansas State University"
+        "author_name": "Raphael Raspe",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Maria C Guzman-Cardozo",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Frauke Muecksch",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Christian Gaebler",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Marina Caskey",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Michel C Nussenzweig",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Theodora Hatziioannou",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Paul D Bieniasz",
+        "author_inst": "Rockefeller University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by",
     "type": "new results",
     "category": "microbiology"
   },
@@ -187525,57 +188435,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.08.13.22278740",
-    "rel_title": "Demographic and Viral-Genetic Analyses of COVID-19 Severity in Bahrain Identify Local Risk Factors and a Protective Effect of Polymerase Mutations",
+    "rel_doi": "10.1101/2022.08.12.22278726",
+    "rel_title": "BNT162b2 induced neutralizing and non-neutralizing antibody functions against SARS-CoV-2 diminish with age",
     "rel_date": "2022-08-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.13.22278740",
-    "rel_abs": "A multitude of demographic, health, and genetic factors are associated with the risk of developing severe COVID-19 following infection by the SARS-CoV-2. There is a need to perform studies across human societies and to investigate the full spectrum of genetic variation of the virus. Using data from 869 COVID-19 patients in Bahrain between March 2020 and March 2021, we analyzed paired viral sequencing and non-genetic host data to understand host and viral determinants of severe COVID-19. We estimated the effects of demographic variables specific to the Bahrain population and found that the impact of health factors are largely consistent with other populations. To extend beyond the common variants of concern in the Spike protein analyzed by previous studies, we used a viral burden approach and detected a protective effect of low-frequency missense viral mutations in the RNA-dependent RNA polymerase (Pol) gene on disease severity. Our results contribute to the survey of severe COVID-19 in diverse populations and highlight the benefits of studying rare viral mutations.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.12.22278726",
+    "rel_abs": "Each novel SARS-CoV-2 variant renews concerns about decreased vaccine efficacy caused by evasion of vaccine induced neutralizing antibodies. However, accumulating epidemiological data show that while vaccine prevention of infection varies, protection from severe disease and death remains high. Thus, immune responses beyond neutralization could contribute to vaccine efficacy. Polyclonal antibodies function through their Fab domains that neutralize virus directly, and Fc domains that induce non-neutralizing host responses via engagement of Fc receptors on immune cells. To understand how vaccine induced neutralizing and non-neutralizing activities synergize to promote protection, we leverage sera from 51 SARS-CoV-2 uninfected health-care workers after two doses of the BNT162b2 mRNA vaccine. We show that BNT162b2 elicits antibodies that neutralize clinical isolates of wildtype and five variants of SARS-CoV-2, including Omicron BA.2, and, critically, induce Fc effector functions. Fc{gamma}RIIIa/CD16 activity is linked to neutralizing activity and associated with post-translational afucosylation and sialylation of vaccine specific antibodies. Further, neutralizing and non-neutralizing functions diminish with age, with limited polyfunctional breadth, magnitude and coordination observed in those [&ge;]65 years old compared to <65. Thus, studying Fc functions in addition to Fab mediated neutralization provides greater insight into vaccine efficacy for vulnerable populations such as the elderly against SARS-CoV-2 and novel variants.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Evan M Koch",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Timothy A Bates",
+        "author_inst": "Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR"
       },
       {
-        "author_name": "Justin Du",
-        "author_inst": "Yale University"
+        "author_name": "Pei Lu",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX"
       },
       {
-        "author_name": "Michelle Dressner",
-        "author_inst": "Harvard T.H. Chan School of Public Health"
+        "author_name": "Ye jin Kang",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX"
       },
       {
-        "author_name": "Hashmeya Erahim Alwasti",
-        "author_inst": "Bahrain Ministry of Health"
+        "author_name": "Devin Schoen",
+        "author_inst": "Department of Occupational Health, Oregon Health & Science University, Portland, OR"
       },
       {
-        "author_name": "Zahra Al Taif",
-        "author_inst": "Bahrain Ministry of Health"
+        "author_name": "Micah Thornton",
+        "author_inst": "Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX"
       },
       {
-        "author_name": "Fatima Shehab",
-        "author_inst": "Bahrain Ministry of Health"
+        "author_name": "Savannah K McBride",
+        "author_inst": "Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR"
       },
       {
-        "author_name": "Afaf Merza Mohamed",
-        "author_inst": "Bahrain Ministry of Health"
+        "author_name": "Chanhee Park",
+        "author_inst": "Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX"
       },
       {
-        "author_name": "Amjad Ghanem",
-        "author_inst": "Bahrain Ministry of Health"
+        "author_name": "Daehwan Kim",
+        "author_inst": "Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX"
       },
       {
-        "author_name": "Alireza Haghighi",
-        "author_inst": "Brigham and Womens Hospital"
+        "author_name": "William B Messer",
+        "author_inst": "Department of Molecular Microbiology and Immunology, Oregon Health and Sciences University, Portland, OR"
       },
       {
-        "author_name": "Shamil Sunyaev",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Marcel E Curlin",
+        "author_inst": "Department of Occupational Health, Oregon Health and Sciences University, Portland, OR"
       },
       {
-        "author_name": "Maha Farhat",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Fikadu G Tafesse",
+        "author_inst": "Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, OR"
+      },
+      {
+        "author_name": "Lenette L Lu",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX"
       }
     ],
     "version": "1",
@@ -189367,175 +190281,43 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2022.08.08.22278550",
-    "rel_title": "Cohort Study Protocol of the Brazilian Collaborative Research Network on COVID-19: strengthening WHO global data",
+    "rel_doi": "10.1101/2022.08.05.22278487",
+    "rel_title": "Excess mortality in Cyprus during the COVID-19 pandemic and its lack of association with vaccination rates",
     "rel_date": "2022-08-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.08.22278550",
-    "rel_abs": "IntroductionWith the COVID-19 pandemic, hospitals in low-income countries were faced with a triple challenge. First, a large number of patients required hospitalization because of the infections more severe symptoms. Second, there was a lack of systematic and broad testing policies for early identification of cases. Third, there were weaknesses in the integration of information systems, which led to the need to search for available information from the hospital information systems. Accordingly, it is also important to state that relevant aspects of COVID-19s natural history had not yet been fully clarified. The aim of this research protocol is to present the strategies of a Brazilian network of hospitals to perform systematized data collection on COVID-19 through the World Health Organization (WHO) Platform.\n\nMethods and AnalysisThis is a multicenter project among Brazilian hospitals to provide data on COVID-19 through the WHO global platform, which integrates patient care information from different countries. From October 2020 to March 2021, a committee worked on defining a flowchart for this platform, specifying the variables of interest, data extraction standardization and analysis.\n\nEthics and DisseminationThis protocol was approved by the Research Ethics Committee (CEP) of the Research Coordinating Center of Brazil (CEP of the Hospital Nossa Senhora da Conceicao), on January 29, 2021, under approval No. 4.515.519 and by the National Research Ethics Commission (CONEP), on February 5, 2021, under approval No. 4.526.456. The project results will be explained in WHO reports and published in international peer-reviewed journals, and summaries will be provided to the funders of the study.\n\nStrengths and limitations of this studyAs the study involves a convenience and non-probabilistic sample of patients hospitalized in health units, it may not represent the population of patients with COVID-19 hospitalized in the country. However, the information generated by this research can serve as a basis for the development of maps of the evolution of SARS-CoV-2 infection and public policies to face pandemics. It is a study that uses secondary data, and therefore, information bias may occur, but on the other hand, it has a low cost and facilitates a population-based study with national coverage.\n\nArticle SummaryThis is a multicenter project among Brazilian hospitals to provide data on COVID-19 through the WHO global platform.\n\nIt is expected to deepen knowledge about the pandemic scenario and help hospital institutions to develop preventive measures, health service protocols and strengthen the training of teams in the existing complications.",
-    "rel_num_authors": 39,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.05.22278487",
+    "rel_abs": "BackgroundIt has been claimed that COVID-19 vaccination is associated with excess mortality during the COVID-19 pandemic, a claim that contributes to vaccine hesitancy. We examined whether all-cause mortality has actually increased in Cyprus during the first two pandemic years, and whether any increases are associated with vaccination rates.\n\nMethodsWe calculated weekly excess mortality for Cyprus between January 2020 and June 2022, overall and by age group, using both a Distributed Lag Nonlinear Model (DLNM) adjusted for mean daily temperature, and the EuroMOMO algorithm. Excess deaths were regressed on the weekly number of confirmed COVID-19 deaths and on weekly first-dose vaccinations, also using a DLNM to explore the lag-response dimension.\n\nResults552 excess deaths were observed in Cyprus during the study period (95%CI: 508-597) as opposed to 1306 confirmed COVID-19 deaths. No association between excess deaths and vaccination rates was found overall and for any age group except 18-49 years, among whom 1.09 excess deaths (95%CI: 0.27-1.91) per 10,000 vaccinations were estimated during the first 8 weeks post-vaccination. However, detailed cause-of-death examination identified just two such deaths potentially linked to vaccination, therefore this association is spurious and attributable to random error.\n\nConclusionsExcess mortality was moderately increased in Cyprus during the COVID-19 pandemic, primarily as a result of laboratory-confirmed COVID-19 deaths. No relationship was found between vaccination rates and all-cause mortality, demonstrating the excellent safety profile of COVID-19 vaccines.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Fernando Anschau",
-        "author_inst": "Conceicao Hospitalar Group"
-      },
-      {
-        "author_name": "Natalia Del' Angelo Aredes",
-        "author_inst": "Universidade Federal de Goias, Nursing School Goiania, Goias, BR"
-      },
-      {
-        "author_name": "Ludovic Reveiz",
-        "author_inst": "Pan American Health Organization, DC, USA"
-      },
-      {
-        "author_name": "Monica Padilla",
-        "author_inst": "Pan American Health Organization Brazil Brasilia, DF, BR"
-      },
-      {
-        "author_name": "Rosane de Mendonca Gomes",
-        "author_inst": "Pan American Health Organization Brazil Brasilia, DF, BR"
-      },
-      {
-        "author_name": "Wellington Mendes Carvalho",
-        "author_inst": "Pan American Health Organization Brazil Brasilia, DF, BR"
-      },
-      {
-        "author_name": "Fernando Antonio Gomes Leles",
-        "author_inst": "Pan American Health Organization Brazil Brasilia, DF, BR"
-      },
-      {
-        "author_name": "Fernanda Baeumle Reese",
-        "author_inst": "Complexo Hospitalar do Trabalhador Curitiba, PR, BR"
-      },
-      {
-        "author_name": "Andre Hostilio Hubert",
-        "author_inst": "Complexo Hospitalar do Trabalhador Curitiba, Parana, BR"
-      },
-      {
-        "author_name": "Elisandrea Sguario Kemper",
-        "author_inst": "Hospital da Crianca de Brasilia Distrito Federal, BR"
-      },
-      {
-        "author_name": "Renilson Rehem de Souza",
-        "author_inst": "Hospital da Crianca de Brasilia, Distrito Federal, BR"
-      },
-      {
-        "author_name": "Cristiane Feitosa Salviano",
-        "author_inst": "Hospital da Crianca de Brasilia, DF, BR"
-      },
-      {
-        "author_name": "Hevelin Silveira e Silva",
-        "author_inst": "Hospital da Crianca de Brasilia, DF, BR"
-      },
-      {
-        "author_name": "Eduardo Barbosa Coelho",
-        "author_inst": "Brazilian Company of Hospital Services Belo Horizonte, Minas Gerais, BR"
-      },
-      {
-        "author_name": "Giuseppe Cesare Gatto",
-        "author_inst": "Brazilian Company of Hospital Services Belo Horizonte, Minas Gerais, BR"
-      },
-      {
-        "author_name": "Rafael Freitas de Morais",
-        "author_inst": "Brazilian Company of Hospital Services Brasilia, Distrito Federal, BR"
-      },
-      {
-        "author_name": "Leonardo Nunes Alegre",
-        "author_inst": "Brazilian Company of Hospital Services Porto Alegre, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Rodrigo Citton Padilha dos Reis",
-        "author_inst": "Universidade Federal do Rio Grande do Sul, Graduate Program in Epidemiology Porto Alegre, RS, BR"
-      },
-      {
-        "author_name": "Joaquim Francisco dos Santos Neto",
-        "author_inst": "Universidade Federal do Rio Grande do Sul, Graduate Program in Epidemiology Porto Alegre, RS, BR"
-      },
-      {
-        "author_name": "Cesar Perdomo Purper",
-        "author_inst": "Grupo Hospitalar Conceicao, Gerencia de Ensino e Pesquisa Porto Alegre, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Veridian Baldon dos Santos",
-        "author_inst": "Grupo Hospitalar Conceicao, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Andressa Fontoura Garbini",
-        "author_inst": "Grupo Hospitalar Conceicao, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Rafaela dos Santos Charao de Almeida,",
-        "author_inst": "Grupo Hospitalar Conceicao, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Bruna Donida",
-        "author_inst": "Grupo Hospitalar Conceicao, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Rogerio Farias Bitencourt",
-        "author_inst": "Grupo Hospitalar Conceicao, Gerencia de Ensino e Pesquisa Porto Alegre, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Luciane Kopittke",
-        "author_inst": "Grupo Hospitalar Conceicao, Gerencia de Ensino e Pesquisa Porto Alegre, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Fernanda Costa dos Santos",
-        "author_inst": "Grupo Hospitalar Conceicao Porto Alegre, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Raquel Lutkmeier",
-        "author_inst": "Grupo Hospitalar Conceicao Porto Alegre, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Daniela dos Reis Carazai",
-        "author_inst": "Grupo Hospitalar Conceicao Porto Alegre, Rio Grande do Sul, BR"
-      },
-      {
-        "author_name": "Virginia Angelica Silveira Reis",
-        "author_inst": "Instituto de Saude e Gestao Hospitalar Fortaleza, CE, BR"
-      },
-      {
-        "author_name": "Flavio Clemente Deulefeu,",
-        "author_inst": "Instituto de Saude e Gestao Hospitalar Fortaleza, CE, BR"
-      },
-      {
-        "author_name": "Fernanda Gadelha Severino",
-        "author_inst": "Instituto de Saude e Gestao Hospitalar Fortaleza, CE, BR"
-      },
-      {
-        "author_name": "Jose Gustavo da Costa Neto",
-        "author_inst": "Instituto de Saude e Gestao Hospitalar Fortaleza, CE, BR"
-      },
-      {
-        "author_name": "Nirvania do Vale Carvalho",
-        "author_inst": "Health Department of the State of Piaui, Hospital Getulio Vargas Teresina, Piaui, BR"
+        "author_name": "Theodore Lytras",
+        "author_inst": "School of Medicine, European University Cyprus, Nicosia, Cyprus"
       },
       {
-        "author_name": "Andre Jamson Rocha de Andrade",
-        "author_inst": "Health Department of the State of Piaui, Hospital Getulio Vargas Teresina, Piaui, BR"
+        "author_name": "Maria Athanasiadou",
+        "author_inst": "Health Monitoring Unit, Ministry of Health, Nicosia, Cyprus"
       },
       {
-        "author_name": "Adriana Melo Teixeira",
-        "author_inst": "Brazilian Ministry of Health, Department of Hospital, Home, and Emergency Care (DAHU) of the Specialized Health Care Office (SAES) Brasilia, Distrito Federal, B"
+        "author_name": "Anna Demetriou",
+        "author_inst": "Health Monitoring Unit, Ministry of Health, Nicosia, Cyprus"
       },
       {
-        "author_name": "Olavo Braga Neto",
-        "author_inst": "Brazilian Ministry of Health, Department of Hospital, Home, and Emergency Care (DAHU) of the Specialized Health Care Office (SAES) Brasilia, Distrito Federal, B"
+        "author_name": "Despina Stylianou",
+        "author_inst": "Health Monitoring Unit, Ministry of Health, Nicosia, Cyprus"
       },
       {
-        "author_name": "Gabriel Cardozo Muller",
-        "author_inst": "Universidade Federal do Rio Grande do Sul, Graduate Program in Epidemiology Porto Alegre, RS, BR"
+        "author_name": "Alexandros Heraclides",
+        "author_inst": "School of Sciences, European University Cyprus, Nicosia, Cyprus"
       },
       {
-        "author_name": "Ricardo de Souza Kuchenbecker",
-        "author_inst": "Universidade Federal do Rio Grande do Sul, Graduate Program in Epidemiology Porto Alegre, RS, BR"
+        "author_name": "Olga Kalakouta",
+        "author_inst": "Health Monitoring Unit, Ministry of Health, Nicosia, Cyprus"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.08.10.22278639",
@@ -191889,51 +192671,63 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.08.08.503231",
-    "rel_title": "Vitamin B12 attenuates leukocyte inflammatory signature in COVID-19 via methyl-dependent changes in epigenetic marks",
+    "rel_doi": "10.1101/2022.08.09.503270",
+    "rel_title": "Acetylsalicylic acid and Salicylic acid inhibit SARS-CoV-2 replication in precision-cut lung slices",
     "rel_date": "2022-08-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.08.503231",
-    "rel_abs": "COVID-19 induces chromatin remodeling in host immune cells, and it had previously been shown that vitamin B12 downregulates some inflammatory genes via methyl-dependent epigenetic mechanisms. In this work, whole blood cultures from moderate or severe COVID-19 patients were used to assess the potential of B12 as adjuvant drug. The vitamin normalized the expression of a panel of inflammatory genes still dysregulated in the leukocytes despite glucocorticoid therapy during hospitalization. B12 also increased the flux of the sulfur amino acid pathway, raising the bioavailability of methyl. Accordingly, B12-induced downregulation of CCL3 strongly and negatively correlated with the hypermethylation of CpGs in its regulatory regions. Transcriptome analysis revealed that B12 attenuates the effects of COVID-19 on most inflammation-related pathways affected by the disease. As far as we are aware, this is the first study to demonstrate that pharmacological modulation of epigenetic marks in leukocytes favorably regulates central components of COVID-19 physiopathology.\n\nTeaserB12 has great potential as an adjuvant drug for alleviating inflammation in COVID-19.",
-    "rel_num_authors": 8,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.09.503270",
+    "rel_abs": "Aspirin, with its active compound acetylsalicylic acid (ASA), shows antiviral activity against rhino- and influenza viruses and at high concentrations. We sought to investigate whether ASA and its metabolite salicylic acid (SA) inhibit SARS-CoV-2 since it might use similar pathways to influenza viruses. The compound-treated cells were infected with SARS-CoV-2. Viral replication was analyzed by RTqPCR. The compounds suppressed SARS-CoV-2 replication in cell culture cells and in a patient-near replication system using human precision-cut lung slices by two orders of magnitude. The compounds did not interfere with viral entry but led to lower viral RNA expression after 24 h.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Vanessa C Silva",
-        "author_inst": "Universidade Federal de Sao Paulo"
+        "author_name": "Nina Geiger",
+        "author_inst": "Universit\u00e4t W\u00fcrzburg: Julius-Maximilians-Universitat Wurzburg"
       },
       {
-        "author_name": "Marina S Oliveira",
-        "author_inst": "FIOCRUZ"
+        "author_name": "Eva-Maria K\u00f6nig",
+        "author_inst": "Universit\u00e4t W\u00fcrzburg: Julius-Maximilians-Universitat Wurzburg"
       },
       {
-        "author_name": "Barbara V O Prado",
-        "author_inst": "Hospital Metropolitano Dr. Celio de Castro"
+        "author_name": "Heike Oberwinkler",
+        "author_inst": "University Hospital Wuerzburg, Chair of Tissue Engineering and Regenerative Medicine, Germany"
       },
       {
-        "author_name": "Cristianne G Cardoso",
-        "author_inst": "Hospital Metropolitano Dr. Celio de Castro"
+        "author_name": "Valeria Roll",
+        "author_inst": "Julius-Maximilians-University of Wuerzburg, Institute for Virology and Immunobiology, Versbacher Strasse 7, 97078 Wuerzburg, Germany"
       },
       {
-        "author_name": "Anna C M Salim",
-        "author_inst": "FIOCRUZ"
+        "author_name": "Viktoria Diesendorf",
+        "author_inst": "Julius-Maximilians-University of Wuerzburg, Institute for Virology and Immunobiology, Versbacher Strasse 7, 97078 Wuerzburg, Germany"
       },
       {
-        "author_name": "Gloria R Franco",
-        "author_inst": "Universidade Federal de Minas Gerais"
+        "author_name": "Sofie Faehr",
+        "author_inst": "Julius-Maximilians-University of Wuerzburg, Institute for Virology and Immunobiology, Versbacher Strasse 7, 97078 Wuerzburg, Germany"
       },
       {
-        "author_name": "Saionara C Francisco",
-        "author_inst": "Hospital Metropolitano Dr. Celio de Castro"
+        "author_name": "Helena Obernolte",
+        "author_inst": "Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Member of Fraunhofer international Consortium for Anti-Infective Research (iCAIR), Member of"
       },
       {
-        "author_name": "Roney S Coimbra",
-        "author_inst": "FIOCRUZ"
+        "author_name": "Katherina Sewald",
+        "author_inst": "Fraunhofer Institute for Toxicology and Experimental Medicine"
+      },
+      {
+        "author_name": "Sabine Wronski",
+        "author_inst": "Fraunhofer Institute for Toxicology and Experimental Medicine ITEM, Member of Fraunhofer international Consortium for Anti-Infective Research (iCAIR), Member of"
+      },
+      {
+        "author_name": "Maria Steinke",
+        "author_inst": "University Hospital Wuerzburg, Chair of Tissue Engineering and Regenerative Medicine, Germany"
+      },
+      {
+        "author_name": "Jochen Bodem",
+        "author_inst": "Julius-Maximilians-University of Wuerzburg, Institute for Virology and Immunobiology, Versbacher Strasse 7, 97078 Wuerzburg, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.08.08.503267",
@@ -193831,67 +194625,79 @@
     "category": "medical ethics"
   },
   {
-    "rel_doi": "10.1101/2022.08.06.22278449",
-    "rel_title": "Severity Predictors of COVID-19 in SARS-CoV-2 Variant, Delta and Omicron Period; Single Center Study",
+    "rel_doi": "10.1101/2022.08.07.499047",
+    "rel_title": "Multiple pathways for SARS-CoV-2 resistance to nirmatrelvir",
     "rel_date": "2022-08-08",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.06.22278449",
-    "rel_abs": "BackgroundThe outcomes of coronavirus disease 2019 (COVID-19) treatment have improved due to vaccination and the establishment of better treatment regimens. However, the emergence of variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, and the corresponding changes in the characteristics of the disease present new challenges in patient management. This study aimed to analyze predictors of COVID-19 severity caused by the delta and omicron variants of SARS-CoV-2.\n\nMethodsWe retrospectively analyzed the data of patients who were admitted for COVID-19 at Yokohama City University Hospital from August 2021 to March 2022.\n\nResultsA total of 141 patients were included in this study. Of these, 91 had moderate COVID-19, whereas 50 had severe COVID-19. There were significant differences in sex, vaccination status, dyspnea, sore throat symptoms, and body mass index (BMI) (p <0.0001, p <0.001, p <0.001, p=0.02, p< 0.0001, respectively) between the moderate and severe COVID-19 groups. Regarding comorbidities, smoking habit and renal dysfunction were significantly different between the two groups (p=0.007 and p=0.01, respectively). Regarding laboratory data, only LDH level on the first day of hospitalization was significantly different between the two groups (p<0.001). Multiple logistic regression analysis revealed that time from the onset of COVID-19 to hospitalization, BMI, smoking habit, and LDH level were significantly different between the two groups (p<0.03, p=0.039, p=0.008, p<0.001, respectively). The cut-off value for the time from onset of COVID-19 to hospitalization was four days (sensitivity, 0.73; specificity, 0.70).\n\nConclusionsTime from the onset of COVID-19 to hospitalization is the most important factor in the prevention of the aggravation of COVID-19 caused by the delta and omicron SARS-CoV-2 variants. Appropriate medical management within four days after the onset of COVID-19 is essential for preventing the progression of COVID-19, especially in patients with smoking habits.",
-    "rel_num_authors": 12,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.07.499047",
+    "rel_abs": "Nirmatrelvir, an oral antiviral targeting the 3CL protease of SARS-CoV-2, has been demonstrated to be clinically useful in reducing hospitalization or death due to COVID-191,2. However, as SARS-CoV-2 has evolved to become resistant to other therapeutic modalities3-9, there is a concern that the same could occur for nirmatrelvir. Here, we have examined this possibility by in vitro passaging of SARS-CoV-2 in increasing concentrations of nirmatrelvir using two independent approaches, including one on a large scale in 480 wells. Indeed, highly resistant viruses emerged from both, and their sequences revealed a multitude of 3CL protease mutations. In the experiment done at a larger scale with many replicates, 53 independent viral lineages were selected with mutations observed at 23 different residues of the enzyme. Yet, several common mutational pathways to nirmatrelvir resistance were preferred, with a majority of the viruses descending from T21I, P252L, or T304I as precursor mutations. Construction and analysis of 13 recombinant SARS-CoV-2 clones, each containing a unique mutation or a combination of mutations showed that the above precursor mutations only mediated low-level resistance, whereas greater resistance required accumulation of additional mutations. E166V mutation conferred the strongest resistance (~100-fold), but this mutation resulted in a loss of viral replicative fitness that was restored by compensatory changes such as L50F and T21I. Structural explanations are discussed for some of the mutations that are proximal to the drug-binding site, as well as cross-resistance or lack thereof to ensitrelvir, another clinically important 3CL protease inhibitor. Our findings indicate that SARS-CoV-2 resistance to nirmatrelvir does readily arise via multiple pathways in vitro, and the specific mutations observed herein form a strong foundation from which to study the mechanism of resistance in detail and to inform the design of next generation protease inhibitors.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Fumihiro Ogawa",
-        "author_inst": "Yokohama City University"
+        "author_name": "Sho Iketani",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Yasufumi Oi",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Hiroshi Mohri",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Hiroshi Honzawa",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Bruce Culbertson",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Naho Misawa",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Seo Jung Hong",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Tomoaki Takeda",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Yinkai Duan",
+        "author_inst": "ShanghaiTech University"
       },
       {
-        "author_name": "Yushi Kikuchi",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Maria I. Luck",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Ryosuke Fukui",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Medini K. Annavajhala",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Katsushi Tanaka",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Yicheng Guo",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Daiki Kano",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Zizhang Sheng",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Hideaki Kato",
-        "author_inst": "Yokohama City University Hospital, Infection prevention and control department"
+        "author_name": "Anne-Catrin Uhlemann",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Takeru Abe",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Stephen P. Goff",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       },
       {
-        "author_name": "Ichiro Takeuchi",
-        "author_inst": "Yokohama City University Hospital: Yokohama Shiritsu Daigaku Fuzoku Byoin"
+        "author_name": "Yosef Sabo",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
+      },
+      {
+        "author_name": "Haitao Yang",
+        "author_inst": "ShanghaiTech University"
+      },
+      {
+        "author_name": "Alejandro Chavez",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
+      },
+      {
+        "author_name": "David D. Ho",
+        "author_inst": "Columbia University Vagelos College of Physicians and Surgeons"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.08.05.22278480",
@@ -196061,85 +196867,105 @@
     "category": "geriatric medicine"
   },
   {
-    "rel_doi": "10.1101/2022.08.03.22278363",
-    "rel_title": "Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is common in post-acute sequelae of SARS-CoV-2 infection (PASC): Results from a post-COVID-19 multidisciplinary clinic.",
+    "rel_doi": "10.1101/2022.08.03.22278386",
+    "rel_title": "SARS-CoV-2 BA.4/5 Spike recognition and neutralization elicited after the third dose of mRNA vaccine",
     "rel_date": "2022-08-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.03.22278363",
-    "rel_abs": "BackgroundThe global prevalence of PASC is estimated to be present in 0{middle dot}43 and based on the WHO estimation of 470 million worldwide COVID-19 infections, corresponds to around 200 million people experiencing long COVID symptoms. Despite this, its clinical features are not well defined.\n\nMethodsWe collected retrospective data from 140 patients with PASC in a post-COVID-19 clinic on demographics, risk factors, illness severity (graded as one-mild to five-severe), functional status, and 29 symptoms and principal component symptoms cluster analysis. The Institute of Medicine (IOM) 2015 criteria were used to determine the ME/CFS phenotype.\n\nFindingsThe median age was 47 years, 59{middle dot}0% were female; 49{middle dot}3% White, 17{middle dot}2% Hispanic, 14{middle dot}9% Asian, and 6{middle dot}7% Black. Only 12{middle dot}7% required hospitalization. Seventy-two (53{middle dot}5%) patients had no known comorbid conditions. Forty-five (33{middle dot}9%) were significantly debilitated. The median duration of symptoms was 285{middle dot}5 days, and the number of symptoms was 12. The most common symptoms were fatigue (86{middle dot}5%), post-exertional malaise (82{middle dot}8%), brain fog (81{middle dot}2%), unrefreshing sleep (76{middle dot}7%), and lethargy (74{middle dot}6%). Forty-three percent fit the criteria for ME/CFS.\n\nInterpretationsMost PASC patients evaluated at our clinic had no comorbid condition and were not hospitalized for acute COVID-19. One-third of patients experienced a severe decline in their functional status. About 43% had the ME/CFS subtype.\n\nFundingThe study did not received funding.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.03.22278386",
+    "rel_abs": "Several SARS-CoV-2 Omicron subvariants have recently emerged, becoming the dominant circulating strains in many countries. These variants contain a large number of mutations in their Spike glycoprotein, raising concerns about vaccine efficacy. In this study, we evaluate the ability of plasma from a cohort of individuals that received three doses of mRNA vaccine to recognize and neutralize these Omicron subvariant Spikes. We observed that BA.4/5 and BQ.1.1 Spikes are markedly less recognized and neutralized compared to the D614G and the other Omicron subvariant Spikes tested. Also, individuals who have been infected before or after vaccination present better humoral responses than SARS-CoV-2 naive vaccinated individuals, thus indicating that hybrid immunity generates better humoral responses against these subvariants.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Hector Bonilla",
-        "author_inst": "Stanford University"
+        "author_name": "Alexandra Tauzin",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Tom Quach",
-        "author_inst": "Stanford University"
+        "author_name": "Alexandre Nicolas",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Anushri Tiwari",
-        "author_inst": "Stanford University"
+        "author_name": "Shilei Ding",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Andres Bonilla",
-        "author_inst": "University of Michigan"
+        "author_name": "Mehdi Benlarbi",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Mitchell G Miglis",
-        "author_inst": "Stanford University"
+        "author_name": "Halima Medjahed",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Phillip Yang",
-        "author_inst": "Stanford University"
+        "author_name": "Debashree Chatterjee",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Lauren Eggert",
-        "author_inst": "Stanford University"
+        "author_name": "Katrina Dionne",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Husham Sharifi",
-        "author_inst": "Stanford University"
+        "author_name": "Shang Yu Gong",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Audra Horomanski",
-        "author_inst": "Stanford University"
+        "author_name": "Gabrielle Gendron-Lepage",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Aruna K Subramanian",
-        "author_inst": "Stanford University School of Medicine"
+        "author_name": "Yuxia Bo",
+        "author_inst": "University of Ottawa"
       },
       {
-        "author_name": "Liza Smirnoff",
-        "author_inst": "Stanford University"
+        "author_name": "Josee Perreault",
+        "author_inst": "Hema-Quebec"
       },
       {
-        "author_name": "Norah Simpson",
-        "author_inst": "Stanford University"
+        "author_name": "Guillaume Goyette",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Houssam Halawi",
-        "author_inst": "Stanford University"
+        "author_name": "Laurie Gokool",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Oliver Sum-Ping",
-        "author_inst": "Stanford University"
+        "author_name": "Pascale Arlotto",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Agnieszka Kalinowski",
-        "author_inst": "Stanford University"
+        "author_name": "Chantal Morrisseau",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Zara Patel",
-        "author_inst": "Stanford University"
+        "author_name": "Cecile Tremblay",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Robert William Shafer",
-        "author_inst": "Stanford University"
+        "author_name": "Valerie Martel-Laferriere",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Linda Geng",
-        "author_inst": "Stanford University"
+        "author_name": "Gaston De Serres",
+        "author_inst": "INSPQ"
+      },
+      {
+        "author_name": "Ines Levade",
+        "author_inst": "INSPQ"
+      },
+      {
+        "author_name": "Daniel E. Kaufmann",
+        "author_inst": "Centre de Recherche du Centre Hospitalier de l'Universite de Montreal (CRCHUM)"
+      },
+      {
+        "author_name": "Marceline Cote",
+        "author_inst": "University of Ottawa"
+      },
+      {
+        "author_name": "Renee Bazin",
+        "author_inst": "Hema-Quebec"
+      },
+      {
+        "author_name": "Andres Finzi",
+        "author_inst": "CRCHUM"
       }
     ],
     "version": "1",
@@ -197723,117 +198549,105 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.08.02.502439",
-    "rel_title": "Serological surveillance for wild rodent infection with SARS-CoV-2 in Europe",
+    "rel_doi": "10.1101/2022.08.02.502100",
+    "rel_title": "NF-\u03baB inhibitor alpha has a cross-variant role during SARS-CoV-2 infection in ACE2-overexpressing human airway organoids",
     "rel_date": "2022-08-02",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.02.502439",
-    "rel_abs": "We report serological surveillance for exposure to SARS-CoV-2 in 1,237 wild rodents and other small mammals across Europe. All samples were negative with the possible exception of one. Given the ongoing circulation of this virus in humans and potential host jumps, we suggest such surveillance be continued.",
-    "rel_num_authors": 26,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.02.502100",
+    "rel_abs": "As SARS-CoV-2 continues to spread worldwide, tractable primary airway cell models that accurately recapitulate the cell-intrinsic response to arising viral variants are needed. Here we describe an adult stem cell-derived human airway organoid model overexpressing the ACE2 receptor that supports robust viral replication while maintaining 3D architecture and cellular diversity of the airway epithelium. ACE2-OE organoids were infected with SARS-CoV-2 variants and subjected to single-cell RNA-sequencing. NF-{kappa}B inhibitor alpha was consistently upregulated in infected epithelial cells, and its mRNA expression positively correlated with infection levels. Confocal microscopy showed more I{kappa}B expression in infected than bystander cells, but found concurrent nuclear translocation of NF-{kappa}B that I{kappa}B usually prevents. Overexpressing a nondegradable I{kappa}B mutant reduced NF-{kappa}B translocation and increased viral infection. These data demonstrate the functionality of ACE2-OE organoids in SARS-CoV-2 research and identify an incomplete NF-{kappa}B feedback loop as a rheostat of viral infection that may promote inflammation and severe disease.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Vincent Bourret",
-        "author_inst": "University of Helsinki, INRAE"
-      },
-      {
-        "author_name": "Lara Dutra",
-        "author_inst": "University of Helsinki"
-      },
-      {
-        "author_name": "Hussein Alburkat",
-        "author_inst": "University of Helsinki"
-      },
-      {
-        "author_name": "Sanna Maki",
-        "author_inst": "University of Helsinki"
+        "author_name": "Camille R. Simoneau",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Ella Lintunen",
-        "author_inst": "University of Helsinki"
+        "author_name": "Pei-Yi Chen",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Marine Wasniewski",
-        "author_inst": "ANSES"
+        "author_name": "Galen X. Xing",
+        "author_inst": "University of California, Berkeley"
       },
       {
-        "author_name": "Ravi Kant",
-        "author_inst": "University of Helsinki"
+        "author_name": "Mir M Khalid",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Maciej Grzybek",
-        "author_inst": "Medical University of Gdansk"
+        "author_name": "Nathan L. Meyers",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Vinaya Venkat",
-        "author_inst": "University of Helsinki"
+        "author_name": "Jennifer M. Hayashi",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Hayder Asad",
-        "author_inst": "University of Helsinki"
+        "author_name": "Taha Y Taha",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Julien Pradel",
-        "author_inst": "INRAE"
+        "author_name": "Kristoffer E Leon",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Marie Bouilloud",
-        "author_inst": "IRD"
+        "author_name": "Tal Ashuach",
+        "author_inst": "University of California, Berkeley"
       },
       {
-        "author_name": "Herwig Leirs",
-        "author_inst": "University of Antwerp"
+        "author_name": "Krystal A. Fontaine",
+        "author_inst": "Gladstone Institute of Virology"
       },
       {
-        "author_name": "Valeria Carolina Colombo",
-        "author_inst": "University of Antwerp, CONICET"
+        "author_name": "Lauren Rodriguez",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Vincent Sluydts",
-        "author_inst": "University of Antwerp"
+        "author_name": "Bastian Joehnk",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Peter Stuart",
-        "author_inst": "Munster Technological University"
+        "author_name": "Keith Walcott",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Andrew McManus",
-        "author_inst": "Munster Technological University"
+        "author_name": "Sreelakshmi Vasudevan",
+        "author_inst": "Medical Service, San Francisco VA Healthcare System"
       },
       {
-        "author_name": "Jana A. Eccard",
-        "author_inst": "University of Potsdam"
+        "author_name": "Xiaohui Fang",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Jasmin Firozpoor",
-        "author_inst": "University of Potsdam"
+        "author_name": "Mazharul Maishan",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Christian Imholt",
-        "author_inst": "Julius Kuhn Institute"
+        "author_name": "Shawn Schultz",
+        "author_inst": "University of California, Berkeley"
       },
       {
-        "author_name": "Joanna Nowicka",
-        "author_inst": "Medical University of Gdansk"
+        "author_name": "Jeroen Roose",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Aleksander Goll",
-        "author_inst": "Medical University of Gdansk"
+        "author_name": "Michael A. Matthay",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Nathan Ranc",
-        "author_inst": "INRAE"
+        "author_name": "Anita Sil",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Guillaume Castel",
-        "author_inst": "INRAE"
+        "author_name": "Mehrdad Arjomandi",
+        "author_inst": "San Francisco VA Healthcare System"
       },
       {
-        "author_name": "Nathalie Charbonnel",
-        "author_inst": "INRAE"
+        "author_name": "Nir Yosef",
+        "author_inst": "UC Berkeley"
       },
       {
-        "author_name": "Tarja Sironen",
-        "author_inst": "University of Helsinki"
+        "author_name": "Melanie Ott",
+        "author_inst": "Gladstone Institute of Virology"
       }
     ],
     "version": "1",
@@ -199549,71 +200363,83 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.07.30.22278213",
-    "rel_title": "Higher Perceived Stress during the COVID-19 pandemic increased Menstrual Dysregulation and Menopause Symptoms",
-    "rel_date": "2022-07-31",
+    "rel_doi": "10.1101/2022.07.29.22278186",
+    "rel_title": "Comparative effectiveness of BNT162b2 versus mRNA-1273 boosting in England: a cohort study in OpenSAFELY-TPP",
+    "rel_date": "2022-07-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.30.22278213",
-    "rel_abs": "ObjectiveThe increased stress the globe has experienced with the COVID-19 pandemic has affected mental health, disproportionately affecting women. However, how perceived stress in the first year affected menstrual and menopausal symptoms has not yet been investigated.\n\nMethodsResidents in British Columbia, Canada, were surveyed online as part of the COVID-19 Rapid Evidence Study of a Provincial Population-Based Cohort for Gender and Sex (RESPPONSE). A subgroup (n=4171) who were assigned female sex at birth (age 25-69) and were surveyed within the first 6-12 months of the pandemic (August 2020-February 2021), prior to the widespread rollout of vaccines, were retrospectively asked if they noticed changes in their menstrual or menopausal symptoms, as well as completing validated measures of stress, depression, and anxiety.\n\nResultsWe found that 27.8% reported menstrual cycle disturbances and 6.7% reported increased menopause symptoms. Those who scored higher on perceived stress, depression, and anxiety scales were more likely to have reproductive cycle disturbances. Free text responses revealed that reasons for disturbances were perceived to be related to the pandemic.\n\nConclusionsThe COVID-19 pandemic has highlighted the need to research womens health issues, such as menstruation. Our data indicates that in the first year of the pandemic, almost a third of the menstruating population reported disturbances in their cycle, which is approximately two times higher than in non-pandemic situations and four times higher than any reported changes in menopausal symptoms across that first year of the pandemic.\n\nSummary SentencesWomen+ with higher anxiety, depression or perceived stress scores during the first year of the pandemic were more likely to have experienced menstrual cycle phase disturbance or menopausal status disruption. Younger women were particularly prone to disturbances in their reproductive cycles.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.29.22278186",
+    "rel_abs": "IntroductionThe COVID-19 booster vaccination programme in England used both BNT162b2 and mRNA-1273 vaccines. Direct comparisons of the effectiveness against severe COVID-19 of these two vaccines for boosting have not been made in trials or observational data.\n\nMethodsOn behalf of NHS England, we used the OpenSAFELY-TPP database to match adult recipients of each vaccine type on date of vaccination, primary vaccine course, age, and other characteristics. Recipients were eligible if boosted between 29 October 2021 and 31 January 2022, and followed up for 12 weeks. Outcomes were positive SARS-CoV-2 test, COVID-19 hospitalisation, and COVID-19 death. We estimated the cumulative incidence of each outcome, and quantified comparative effectiveness using risk differences (RD) and hazard ratios (HRs).\n\nResults1,528,431 people were matched in each group, contributing a total 23,150,504 person-weeks of follow-up. The 12-week risks per 1,000 people of positive SARS-CoV-2 test were 103.2 (95%CI 102.4 to 104.0) for BNT162b2 and 96.0 (95.2 to 96.8) for mRNA-1273: the HR comparing mRNA-1273 with BNT162b2 was 0.92 (95%CI 0.91 to 0.92). For COVID-19 hospitalisations the 12-week risks per 1,000 were 0.65 (95%CI 0.56 to 0.75) and 0.44 (0.36 to 0.54): HR 0.67 (95%CI 0.58 to 0.78). COVID-19 deaths were rare: the 12-week risks per 1,000 were 0.03 (95%CI 0.02 to 0.06) and 0.01 (0.01 to 0.02): HR 1.23 (95%CI 0.59 to 2.56). Comparative effectiveness was generally similar within subgroups defined by the primary course vaccine brand, age, prior SARS-CoV-2 infection and clinical vulnerability.\n\nConclusionBooster vaccination with mRNA-1273 COVID-19 vaccine was more effective than BNT162b2 in preventing SARS-CoV-2 infection and COVID-19 hospitalisation during the first 12 weeks after vaccination, during a period of Delta followed by Omicron variant dominance.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Romina Garcia de Leon",
-        "author_inst": "University of British Columbia"
+        "author_name": "WIlliam J Hulme",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
       },
       {
-        "author_name": "Alexandra Baaske",
-        "author_inst": "Women's Health Research Institute"
+        "author_name": "Elsie M F Horne",
+        "author_inst": "Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK"
       },
       {
-        "author_name": "Arianne Albert",
-        "author_inst": "Women's Health Research Institute"
+        "author_name": "Edward P K Parker",
+        "author_inst": "London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK"
       },
       {
-        "author_name": "Amy Booth",
-        "author_inst": "University of British Columbia"
+        "author_name": "Ruth H Keogh",
+        "author_inst": "London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK"
       },
       {
-        "author_name": "C. Sarai Racey",
-        "author_inst": "University of British Columbia"
+        "author_name": "Elizabeth J Williamson",
+        "author_inst": "London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK"
       },
       {
-        "author_name": "Shanlea Gordon",
-        "author_inst": "Womens Health Research Institute"
+        "author_name": "Venexia Walker",
+        "author_inst": "Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit, Bristol Medical Scho"
       },
       {
-        "author_name": "Laurie Smith",
-        "author_inst": "BC Cancer"
+        "author_name": "Tom Palmer",
+        "author_inst": "Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit, Bristol Medical Scho"
       },
       {
-        "author_name": "Anna Gottschlich",
-        "author_inst": "University of British Columbia"
+        "author_name": "Helen J Curtis",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
       },
       {
-        "author_name": "Manish Sadarangani",
-        "author_inst": "University of British Columbia"
+        "author_name": "Alex Walker",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
       },
       {
-        "author_name": "Angela Kaida",
-        "author_inst": "Simon Fraser University"
+        "author_name": "Amir Mehrkar",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
       },
       {
-        "author_name": "Gina Ogilvie",
-        "author_inst": "University of British Columbia"
+        "author_name": "Jessica Morley",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
       },
       {
-        "author_name": "Lori Brotto",
-        "author_inst": "University of British Columbia"
+        "author_name": "Brian MacKenna",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
       },
       {
-        "author_name": "Liisa A.M Galea",
-        "author_inst": "University of British Columbia"
+        "author_name": "Sebastian C J Bacon",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
+      },
+      {
+        "author_name": "Ben Goldacre",
+        "author_inst": "The Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG, UK"
+      },
+      {
+        "author_name": "Miguel A Hernan",
+        "author_inst": "CAUSALab, Harvard T.H. Chan School of Public Health, Boston, MA 02115; Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health,"
+      },
+      {
+        "author_name": "Jonathan A C Sterne",
+        "author_inst": "Population Health Sciences, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; H"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "sexual and reproductive health"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.07.29.22278191",
@@ -201383,107 +202209,183 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2022.07.27.501719",
-    "rel_title": "Development of Equine Polyclonal Antibodies as a Broad-Spectrum Therapy Against SARS-CoV-2 Variants",
+    "rel_doi": "10.1101/2022.07.27.501708",
+    "rel_title": "Molecular basis for antiviral activity of pediatric neutralizing antibodies targeting SARS-CoV-2 Spike receptor binding domain",
     "rel_date": "2022-07-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.27.501719",
-    "rel_abs": "The Coronavirus disease 19 (COVID-19) pandemic has accumulated over 550 million confirmed cases and more than 6.34 million deaths worldwide. Although vaccinations has largely protected the population through the last two years, the effect of vaccination has been increasingly challenged by the emerging SARS-CoV-2 variants. Although several therapeutics including both monoclonal antibodies and small molecule drugs have been used clinically, high cost, viral escape mutations, and potential side effects have reduced their efficacy. There is an urgent need to develop a low cost treatment with wide-spectrum effect against the novel variants of SARS-CoV-2.\n\nHere we report a product of equine polyclonal antibodies that showed potential broad spectrum neutralization effect against the major variants of SARS-CoV-2. The equine polyclonal antibodies were generated by horse immunization with the receptor binding domain (RBD) of SARS-CoV-2 spike protein and purified from equine serum. A high binding affinity between the generated equine antibodies and the RBD was observed. Although designed against the RBD of the early wild type strain sequenced in 2020, the equine antibodies also showed a highly efficient neutralization capacity against the major variants of SARS-CoV-2, including the recent BA.2 Omicron variant (IC50 =1.867g/ml) in viral neutralization assay in Vero E6 cells using live virus cultured. The broad-spectrum neutralization capacity of the equine antibodies was further confirmed using pseudovirus neutralization assay covering the major SARS-CoV-2 variants including wild type, alpha, beta, delta, and omicron, showing effective neutralization against all the tested strains. Ex vivo reconstructed human respiratory organoids representing nasal, bronchial, and lung epitheliums were employed to test the treatment efficacy of the equine antibodies. Antibody treatment protected the human nasal, bronchial, and lung epithelial organoids against infection of the novel SARS-CoV-2 variants challenging public health, the Delta and Omicron BA.2 isolates, by reducing >95% of the viral load. The equine antibodies were further tested for potential side effects in a mouse model by inhalation and no significant pathological feature was observed.\n\nEquine antibodies, as a mature medical product, have been widely applied in the treatment of infectious diseases for more than a century, which limits the potential side effects and are capable of large scale production at a low cost. A cost-effective, wide-spectrum equine antibody therapy effective against the major SARS-CoV-2 variants can contribute as an affordable therapy to cover a large portion of the world population, and thus potentially reduce the transmission and mutation of SARS-CoV-2.",
-    "rel_num_authors": 22,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.27.501708",
+    "rel_abs": "Neutralizing antibodies (NAbs) hold great promise for clinical interventions against SARS-CoV- 2 variants of concern (VOCs). Understanding NAb epitope-dependent antiviral mechanisms is crucial for developing vaccines and therapeutics against VOCs. Here we characterized two potent NAbs, EH3 and EH8, isolated from an unvaccinated pediatric patient with exceptional plasma neutralization activity. EH3 and EH8 cross-neutralize the early VOCs and mediate strong Fc-dependent effector activity in vitro. Structural analyses of EH3 and EH8 in complex with the receptor-binding domain (RBD) revealed the molecular determinants of the epitope-driven protection and VOC-evasion. While EH3 represents the prevalent IGHV3-53 NAb whose epitope substantially overlaps with the ACE2 binding site, EH8 recognizes a narrow epitope exposed in both RBD-up and RBD-down conformations. When tested in vivo, a single-dose prophylactic administration of EH3 fully protected stringent K18-hACE2 mice from lethal challenge with Delta VOC. Our study demonstrates that protective NAbs responses converge in pediatric and adult SARS-CoV-2 patients.",
+    "rel_num_authors": 41,
     "rel_authors": [
       {
-        "author_name": "Shumin Liao",
-        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China; The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China"
+        "author_name": "Yaozong Chen",
+        "author_inst": "Uniformed Service University of the Health Sciences"
       },
       {
-        "author_name": "Yunjiao He",
-        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+        "author_name": "Jeremie Prevost",
+        "author_inst": "CRCHUM / Universite de Montreal"
       },
       {
-        "author_name": "Jing Qu",
-        "author_inst": "Shenzhen Center for Disease Control and Prevention, No. 8, Longyuan Road, Nanshan District, Shenzhen, Guangdong Province, China"
+        "author_name": "Irfan Ullah",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Yue Shi",
-        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+        "author_name": "Hugo Romero",
+        "author_inst": "CHU Sainte-Justine"
       },
       {
-        "author_name": "Yingzi Liu",
-        "author_inst": "Peking University Shenzhen Hospital, No. 1120, Lianhua Road, Futian District, Shenzhen, China; School of Medicine, Southern University of Science and Technology"
+        "author_name": "Veronique Lisi",
+        "author_inst": "CHU Sainte-Justine"
       },
       {
-        "author_name": "Keli Zhao",
-        "author_inst": "Peking University Shenzhen Hospital, No. 1120, Lianhua Road, Futian District, Shenzhen, China"
+        "author_name": "William D Tolbert",
+        "author_inst": "Uniformed Services University of the Health Sciences"
       },
       {
-        "author_name": "Junhui Chen",
-        "author_inst": "Peking University Shenzhen Hospital, No. 1120, Lianhua Road, Futian District, Shenzhen, China"
+        "author_name": "Jonathan R Grover",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Yue Jing",
-        "author_inst": "Jiangxi Institute of Biological Products Co. Ltd., Jiangxi, China; Jiangxi Institute of Biological Products Shenzhen R&D Center Co. Ltd., Shenzhen, China; Haina"
+        "author_name": "Shilei Ding",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Clifton Kwang-Fu Shen",
-        "author_inst": "Jiangxi Institute of Biological Products Co. Ltd.Jiangxi; Jiangxi Institute of Biological Products Shenzhen R&D Center Co. Ltd., Shenzhen; Hainan Institute of P"
+        "author_name": "Shang Yu Gong",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Chong Ji",
-        "author_inst": "Jiangxi Institute of Biological Products Co. Ltd., Jiangxi, China; Jiangxi Institute of Biological Products Shenzhen R&D Center Co. Ltd., Shenzhen, China; Haina"
+        "author_name": "Guillaume Beaudoin-Bussieres",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Guxun Luo",
-        "author_inst": "Jiangxi Institute of Biological Products Co. Ltd., Jiangxi, China; Jiangxi Institute of Biological Products Shenzhen R&D Center Co. Ltd., Shenzhen, China; Haina"
+        "author_name": "Romain Gasser",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Xusheng Zhao",
-        "author_inst": "Jiangxi Institute of Biological Products Co. Ltd., Jiangxi, China; Jiangxi Institute of Biological Products Shenzhen R&D Center Co. Ltd., Shenzhen, China; Haina"
+        "author_name": "Mehdi Benlarbi",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Shuo Li",
-        "author_inst": "Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China; The Sixth Affiliated Hospital of Shenzhen University Health Science Cent"
+        "author_name": "Dani Vezina",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Yunping Fan",
-        "author_inst": "Department of Otolaryngology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China"
+        "author_name": "Sai Priya Anand",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Ziquan Lv",
-        "author_inst": "Shenzhen Center for Disease Control and Prevention, No. 8, Longyuan Road, Nanshan District, Shenzhen, Guangdong Province, China"
+        "author_name": "Debashree Chatterjee",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Shisong Fang",
-        "author_inst": "Shenzhen Center for Disease Control and Prevention, No. 8, Longyuan Road, Nanshan District, Shenzhen, Guangdong Province, China"
+        "author_name": "Guillaume Goyette",
+        "author_inst": "CRCHUM"
       },
       {
-        "author_name": "Yaqing He",
-        "author_inst": "Shenzhen Center for Disease Control and Prevention, No. 8, Longyuan Road, Nanshan District, Shenzhen, Guangdong Province, China"
+        "author_name": "Michael W Grunst",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Chunli Wu",
-        "author_inst": "Shenzhen Center for Disease Control and Prevention, No. 8, Longyuan Road, Nanshan District, Shenzhen, Guangdong Province, China"
+        "author_name": "Ziwei Yang",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Renli Zhang",
-        "author_inst": "Shenzhen Center for Disease Control and Prevention, No. 8, Longyuan Road, Nanshan District, Shenzhen, Guangdong Province, China"
+        "author_name": "Yuxia Bo",
+        "author_inst": "University of Ottawa"
       },
       {
-        "author_name": "Xuan Zou",
-        "author_inst": "Shenzhen Center for Disease Control and Prevention, No. 8, Longyuan Road, Nanshan District, Shenzhen, Guangdong Province, China"
+        "author_name": "Fei Zhou",
+        "author_inst": "National Institutes of Health"
       },
       {
-        "author_name": "Peng Wang",
-        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+        "author_name": "Kathie Beland",
+        "author_inst": "CHU Sainte-Justine"
       },
       {
-        "author_name": "Liang Li",
-        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China; Institute of Biomedicine and Biotechnology, Shenzhen Institute of Advanced T"
+        "author_name": "Xiaoyun Bai",
+        "author_inst": "National Institutes of Health"
+      },
+      {
+        "author_name": "Allison R Zeher",
+        "author_inst": "National Institutes of Health"
+      },
+      {
+        "author_name": "Rick K Huang",
+        "author_inst": "National Institutes of Health"
+      },
+      {
+        "author_name": "Dung N Nguyen",
+        "author_inst": "Uniformed Services University of the Health Sciences"
+      },
+      {
+        "author_name": "Rebekah Sherburn",
+        "author_inst": "Uniformed Services University of the Health Sciences"
+      },
+      {
+        "author_name": "Di Wu",
+        "author_inst": "National Institutes of Health"
+      },
+      {
+        "author_name": "Grzegorz Piszczek",
+        "author_inst": "National Institutes of Health"
+      },
+      {
+        "author_name": "Bastien Pare",
+        "author_inst": "Universite de Montreal"
+      },
+      {
+        "author_name": "Doreen Matthies",
+        "author_inst": "National Institutes of Health"
+      },
+      {
+        "author_name": "Di Xia",
+        "author_inst": "National Institutes of Health"
+      },
+      {
+        "author_name": "Jonathan Richard",
+        "author_inst": "CRCHUM"
+      },
+      {
+        "author_name": "Priti Kumar",
+        "author_inst": "Yale University"
+      },
+      {
+        "author_name": "Walther Mothes",
+        "author_inst": "Yale University"
+      },
+      {
+        "author_name": "Marceline Cote",
+        "author_inst": "University of Ottawa"
+      },
+      {
+        "author_name": "Pradeep D Uchil",
+        "author_inst": "Yale University"
+      },
+      {
+        "author_name": "Vincent-Philippe Lavallee",
+        "author_inst": "CHU Sainte-Justine"
+      },
+      {
+        "author_name": "Martin A Smith",
+        "author_inst": "CHU Sainte-Justine"
+      },
+      {
+        "author_name": "Marzena Pazgier",
+        "author_inst": "Uniformed Services University of the Health Sciences"
+      },
+      {
+        "author_name": "Elie Haddad",
+        "author_inst": "CHU Sainte-Justine"
+      },
+      {
+        "author_name": "Andres Finzi",
+        "author_inst": "Universite de Montreal"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.07.28.501852",
@@ -203037,31 +203939,59 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.07.24.22277968",
-    "rel_title": "Effects of wearing FFP2 masks on SARS-CoV-2 infection rates in classrooms",
+    "rel_doi": "10.1101/2022.07.20.22277718",
+    "rel_title": "Biomarkers and Outcomes in Hospitalized Covid-19 Patients: A Prospective Registry",
     "rel_date": "2022-07-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.24.22277968",
-    "rel_abs": "ImportanceDifferent mitigation measures are mandated in schools worldwide to control the spread of SARS-CoV-2. The efficacy of most measures, however, has not been investigated thus far.\n\nObjectiveTo investigate the usefulness of FFP-2 masks in classrooms to prevent the spread of SARS-CoV-2.\n\nDesignA retrospective comparative cohort study of infection rates (evaluated by PCR screening in school) in students wearing FFP-2 masks continuously and students in sports classes with limited face mask use.\n\nSettingA single-center evaluation comparing classes (middle school: age 10-16 years, 4-year high school: age 14-20 years) with a high sports focus (SF), with regular classes during the Delta and Omicron waves (September 2021-April 2022).\n\nParticipantsIn total, 616 children/families were invited to participate in the comparative evaluation, and 614 (99.7%) followed this invitation by providing relevant information concerning their SARS-CoV-2 infection status. A total of 213 legal guardians (for children < 14 years) and 401 adolescents ([&ge;]14 years) reported SARS-CoV-2 infections during the 2021/22 school year.\n\nMain Outcomes and MeasuresA comparative analysis of cumulative SARS-CoV-2 infection rates in sports and non-sports classes (the 7-day classroom incidence of SARS-CoV-2 infections, and potential secondary infections among school classmates).\n\nResultsCumulative SARS-CoV-2 infection rates were clearly higher in sports classes (with limited mask use) than in non-sports classes (continuous mask use). After the relaxation of the mitigation measures, students in non-sports classes, however, showed a clear \"catch-up\" of infections, leading to a higher incidence of infections during this phase. By the end of the observation period (April 30, 2022), only a small difference in cumulative SARS-CoV-2 infection rates (p=0.037, {varphi}=0.09) was detected between classes with a sports focus and those without a sports focus.\n\nConclusions and RelevanceWearing FFP2 face masks reduces the risk of SARS-CoV-2 infection if strict mitigation measures are applied. Following the relaxation of strict measures, previously \"protected\" students show a significant \"catch-up\" infection rate. Thus, continuous face mask use postpones rather than avoids SARS-CoV-2 infection in many cases. Therefore, the advantage of reduced transmission must be carefully balanced against the disadvantages associated with mask wearing throughout schools.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.20.22277718",
+    "rel_abs": "ObjectivesTo determine association of biomarkers high sensitivity C-reactive protein (hsCRP), D-dimer, interleukin-6 (IL-6), lactic dehydrogenase (LDH), ferritin and neutrophil-lymphocyte ratio (NLR) at hospital admission with clinical features and outcomes in Covid-19.\n\nMethodsSuccessive virologically confirmed Covid-19 patients hospitalized from April 2020 to July 2021 were recruited in a prospective registry. Details of clinical presentation, investigations, management and outcomes were recorded. All the biomarkers were divided into tertiles to determine associations with clinical features and outcomes. Numerical data are presented in median and interquartile range (IQR 25-75). Univariate and multivariate (age, sex, risk factor, comorbidity adjusted) odds ratio (OR) and 95% confidence intervals (CI) were calculated to determine association of deaths with each biomarker.\n\nResultsWe identified 3036 virologically confirmed Covid-19 patients during the study period, 1215 were hospitalized and included in the present study. Men were 70.0%, aged >60y 44.8%, hypertension 44.8% diabetes 39.6% and cardiovascular disease 18.9%. Median symptom duration was 5 days (IQR 4-7) and SpO2 95% (90-97). Total white cell count was 6.9x103/{micro}l, (5.0-9.8), neutrophils 79.2% (68.1-88.2) and lymphocytes 15.8% (8.7-25.5). Medians (IQR) for biomarkers were hsCRP 6.9 mg/dl (2.2-18.9), D-dimer 464 ng/dl (201-982), IL-6 20.1 ng/dl (6.5-60.4), LDH 284 mg/dl (220-396) and ferritin 351 mg/dl (159-676). Oxygen support at admission was in 38.6%, and non-invasive or invasive ventilatory support in 11.0% and 11.6% respectively. 173 (13.9%) patients died and 15 (1.2%) transferred to hospice care. For each biomarker, those in the second and third tertiles, compared to the first, had worse clinical and laboratory abnormalities, and greater oxygen and ventilatory support. Multivariate adjusted OR (95% CI) for deaths in second and third vs first tertiles, respectively, were for hsCRP 2.29(1.14-4.60) and 13.39(7.23-24.80); D-dimer 3.26(1.31-7.05) and 13.89(6.87-28.27); IL-6 2.61(1.31-5.18) and 10.96(5.88-20.43); ferritin 3.19(1.66-6.11) and 9.13(4.97-16.78); LDH 1.85(0.87-3.97) and 10.51(5.41-20.41); and NLR 3.34(1.62-6.89) and 17.52(9.03-34.00) (p<0.001).\n\nConclusionsIn Covid-19, high levels of biomarkers-hsCRP, D-dimer, IL-6, LDH, ferritin and NLR are associated with more severe illness and significantly greater in-hospital mortality. NLR, a simple, widely available and inexpensive investigation provides prognostic information similar to the more expensive biomarkers.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Gerald Jarnig",
-        "author_inst": "Institute of Human Movement Science, Sport and Health, University of Graz, Graz, Austria"
+        "author_name": "Raghubir S Khedar",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur, India"
       },
       {
-        "author_name": "Reinhold Kerbl",
-        "author_inst": "Department of Pediatrics and Adolescent Medicine, LKH Hochsteiermark/Leoben, Austria"
+        "author_name": "Rajeev Gupta",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur"
       },
       {
-        "author_name": "Mireille van Poppel",
-        "author_inst": "Institute of Human Movement Science, Sport and Health, University of Graz, Graz, Austria"
+        "author_name": "Krishna Kumar Sharma",
+        "author_inst": "LBS College of Pharmacy, Rajasthan University of Health Sciences, Jaipur, India"
+      },
+      {
+        "author_name": "Kartik Mittal",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur, India"
+      },
+      {
+        "author_name": "Harshad C Ambaliya",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur"
+      },
+      {
+        "author_name": "Jugal B Gupta",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur"
+      },
+      {
+        "author_name": "Surendra Singh",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur, India"
+      },
+      {
+        "author_name": "Swati Sharma",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur, India"
+      },
+      {
+        "author_name": "Yogendra Singh",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur, India"
+      },
+      {
+        "author_name": "Alok Mathur",
+        "author_inst": "Eternal Heart Care Centre & Research Institute, Jaipur"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.07.23.501235",
@@ -204727,59 +205657,51 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.07.21.501010",
-    "rel_title": "Durability of the Neutralizing Antibody Response to mRNA Booster Vaccination Against SARS-CoV-2 BA.2.12.1 and BA.4/5 Variants",
+    "rel_doi": "10.1101/2022.07.21.501023",
+    "rel_title": "Learning from pre-pandemic data to forecast viral antibody escape",
     "rel_date": "2022-07-22",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.21.501010",
-    "rel_abs": "The recent emergence of the SARS-CoV-2 BA.4/5 and BA.2.12.1 variants has led to rising COVID-19 case numbers and concerns over the continued efficacy of mRNA booster vaccination. Here we examine the durability of neutralizing antibody (nAb) responses against these SARS-CoV-2 Omicron subvariants in a cohort of health care workers 1-40 weeks after mRNA booster dose administration. Neutralizing antibody titers fell by [~]1.5-fold 4-6 months and by [~]2.5-fold 7-9 months after booster dose, with average nAb titers falling by 11-15% every 30 days, far more stable than two dose induced immunity. Notably, nAb titers from booster recipients against SARS-CoV-2 BA.1, BA.2.12.1, and BA.4/5 variants were [~]4.7-, 7.6-, and 13.4-fold lower than against the ancestral D614G spike. However, the rate of waning of booster dose immunity was comparable across variants. Importantly, individuals reporting prior infection with SARS-CoV-2 exhibited significantly higher nAb titers compared to those without breakthrough infection. Collectively, these results highlight the broad and stable neutralizing antibody response induced by mRNA booster dose administration, implicating a significant role of virus evolution to evade nAb specificity, versus waning humoral immunity, in increasing rates of breakthrough infection.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.21.501023",
+    "rel_abs": "Effective pandemic preparedness relies on anticipating viral mutations that are able to evade host immune responses in order to facilitate vaccine and therapeutic design. However, current strategies for viral evolution prediction are not available early in a pandemic - experimental approaches require host polyclonal antibodies to test against and existing computational methods draw heavily from current strain prevalence to make reliable predictions of variants of concern. To address this, we developed EVEscape, a generalizable, modular framework that combines fitness predictions from a deep learning model of historical sequences with biophysical structural information. EVEscape quantifies the viral escape potential of mutations at scale and has the advantage of being applicable before surveillance sequencing, experimental scans, or 3D structures of antibody complexes are available. We demonstrate that EVEscape, trained on sequences available prior to 2020, is as accurate as high-throughput experimental scans at anticipating pandemic variation for SARS-CoV-2 and is generalizable to other viruses including Influenza, HIV, and understudied viruses with pandemic potential such as Lassa and Nipah. We provide continually updated escape scores for all current strains of SARS-CoV-2 and predict likely additional mutations to forecast emerging strains as a tool for ongoing vaccine development (evescape.org).",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "PANKE QU",
-        "author_inst": "The Ohio State University"
+        "author_name": "Nicole N Thadani",
+        "author_inst": "Marks Group, Department of Systems Biology, Harvard Medical School, Boston, MA, USA"
       },
       {
-        "author_name": "Julia N. Faraone",
-        "author_inst": "The Ohio State University"
+        "author_name": "Sarah Gurev",
+        "author_inst": "Marks Group, Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Department of Electrical Engineering and Computer Science, MIT, Cambridge, "
       },
       {
-        "author_name": "John P. Evans",
-        "author_inst": "The Ohio State University"
+        "author_name": "Pascal Notin",
+        "author_inst": "OATML Group, Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK."
       },
       {
-        "author_name": "Yi-Min Zheng",
-        "author_inst": "The Ohio State University"
-      },
-      {
-        "author_name": "Claire Carlin",
-        "author_inst": "The Ohio State University"
-      },
-      {
-        "author_name": "Gerard Lozanski",
-        "author_inst": "The Ohio State University"
+        "author_name": "Noor Youssef",
+        "author_inst": "Marks Group, Department of Systems Biology, Harvard Medical School, Boston, MA, USA"
       },
       {
-        "author_name": "Linda J. Saif",
-        "author_inst": "The Ohio State University"
+        "author_name": "Nathan J Rollins",
+        "author_inst": "Marks Group, Department of Systems Biology, Harvard Medical School, Boston, MA, USA (Currently at Seismic Therapeutic)"
       },
       {
-        "author_name": "Eugene M. Oltz",
-        "author_inst": "The Ohio State University"
+        "author_name": "Chris Sander",
+        "author_inst": "Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA, USA"
       },
       {
-        "author_name": "Richard J. Gumina",
-        "author_inst": "The Ohio State University"
+        "author_name": "Yarin Gal",
+        "author_inst": "OATML Group, Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK"
       },
       {
-        "author_name": "Shan-Lu Liu",
-        "author_inst": "The Ohio State University"
+        "author_name": "Debora Marks",
+        "author_inst": "Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2022.07.21.501031",
@@ -206537,39 +207459,91 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2022.07.18.22277694",
-    "rel_title": "Determinants of healthcare employee preference to continue teleworking after the COVID-19 pandemic: a cross-sectional study using hierarchical regression",
+    "rel_doi": "10.1101/2022.07.19.22277747",
+    "rel_title": "Cumulative incidence of SARS-CoV-2 infection in the general population of the Valencian Community (Spain) after the surge of the Omicron BA.1 variant",
     "rel_date": "2022-07-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.18.22277694",
-    "rel_abs": "Employees post-pandemic telework preference is an important consideration for navigating post-pandemic work arrangements and can inform organizational planning and workforce management. A cross-sectional survey of employees (n=400, participation rate =36.4%) of a regional health authority who teleworked during the COVID-19 pandemic was conducted. The most common post-pandemic telework preference was all the time (52%) followed by over half but not all the time (32%) and less than half the time or not at all (16%). Using hierarchical multinomial logistic regression models and less than half the time or not at all as the reference outcome, being a provider of direct patient care and productivity while teleworking were strong determinants of post-pandemic telework preference while two or more weekly teleconference hours, work-life balance and having one or more people over five years of age in the home while teleworking were moderate determinants.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.19.22277747",
+    "rel_abs": "BackgroundStudies investigating the cumulative incidence of and immune status against SARS-CoV-2 infection provide valuable information for shaping public health decision-making.\n\nMethodsThe current cross-sectional, population-based study, conducted in April 2022 in the Valencian Community (VC), recruited 935 participants of all ages. Anti-SARS-CoV-2-Receptor Binding Domain-RBD-total antibodies and anti-Nucleocapsid (N)- IgGs were measured by electrochemiluminescence assays. To account for past SARS-CoV-2 infection the VC microbiology registry (RedMiVa) was interrogated. |Quantitation of neutralizing antibodies (NtAb) against the ancestral and Omicron BA.1 and BA.2 (sub)variants by an S-pseudotyped neutralization assay and for enumeration of SARS-CoV-2-S specific-IFN{gamma}-producing CD4+ and CD8+ T cells by Intracellular Cytokine Staining assay was performed in a subset of participants (n=100 and 137, respectively).\n\nFindingsThe weighted cumulative incidence was 51{square}9% (95% CI, 48{square}7-55{square}1), and was inversely related to age. Anti-RBD total antibodies were detected in 906/931 (97{square}3%) participants, those vaccinated and SARS-CoV-2-experienced (VAC-ex;=442) displaying higher levels (P<0.001) than vaccinated/naive (VAC-n;(n=472) and non-vaccinated/experienced (UNVAC-ex; n(n=63). Antibody levels correlated inversely with the time elapsed since receipt of last vaccine dose in VAC-n (Rho, -0{square}52; 95% CI, -0{square}59 to -0{square}45; P<0.001) but not in VAC-ex. NtAbs against Omicron BA.1 were detected in 94%, 75% and 50% of VAC-ex, VAC-n and UNVAC-ex groups, respectively, while in 97%, 84% and 40%, against Omicron BA.2. SARS-CoV-2-S-reactive IFN-{gamma} T cells were detected in 73%, 75%, and 64% for VAC-ex, VAC-n, UNVAC-ex, respectively.\n\nInterpretationBy April 2022 around half of the VC population had been infected with SARS-CoV-2 and due to extensive vaccination display hybrid immunity. The large percentage of participants with detectable functional antibody and T-cell responses against SARS-CoV-2, which may be cross-reactive to some extent, points towards lower expected severity than in previous waves.\n\nFundingThis research was supported in part by the European Commission NextGenerationEU fund (CSICs Global Health Platform).",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Andrea Marie Jones",
-        "author_inst": "University of British Columbia"
+        "author_name": "Jorge Camacho",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain"
       },
       {
-        "author_name": "Jonathan Fan",
-        "author_inst": "University of British Columbia"
+        "author_name": "Estela Gimenez",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain"
       },
       {
-        "author_name": "Leah Thomas-Olson",
-        "author_inst": "Fraser Health Authority"
+        "author_name": "Eliseo Albert",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain"
       },
       {
-        "author_name": "Wei Zhang",
-        "author_inst": "University of British Columbia/ Centre for Health Evaluation and Outcome Sciences"
+        "author_name": "Joao Zulaica",
+        "author_inst": "Institute for Integrative Systems Biology (I2SysBio), Universitat de Valencia-CSIC, 46980, Valencia, Spain"
       },
       {
-        "author_name": "Christopher B McLeod",
-        "author_inst": "University of British Columbia"
+        "author_name": "Beatriz Alvarez-Rodriguez",
+        "author_inst": "Institute for Integrative Systems Biology (I2SysBio), Universitat de Valencia-CSIC, 46980, Valencia, Spain"
+      },
+      {
+        "author_name": "Ignacio Torres",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain"
+      },
+      {
+        "author_name": "Luciana Rusu",
+        "author_inst": "Institute for Integrative Systems Biology (I2SysBio), Universitat de Valencia-CSIC, 46980, Valencia, Spain"
+      },
+      {
+        "author_name": "Javier Burgos",
+        "author_inst": "General Directorate of Research and Healthcare Supervision, Department of Health, Valencia Government, Valencia, Spain"
+      },
+      {
+        "author_name": "Salvador Peiro",
+        "author_inst": "Foundation for the promotion of health and biomedical research of the Valencian Community (FISABIO), Valencia, Spain"
+      },
+      {
+        "author_name": "Hermelinda Vanaclocha",
+        "author_inst": "Subdireccion General de Epidemiologia y Vigilancia de la Salud y Sanidad Ambiental de Valencia (DGSP)"
+      },
+      {
+        "author_name": "Ramon Limon",
+        "author_inst": "General Directorate of Healthcare. Department of Health, Valencian Government, Valencia, Spain"
+      },
+      {
+        "author_name": "Maria Jesus Alcaraz",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain"
+      },
+      {
+        "author_name": "Jose Paya",
+        "author_inst": "Preventive Medicine Service, Alicante General and University Hospital, Alicante, Spain"
+      },
+      {
+        "author_name": "Javier Domingo",
+        "author_inst": "Foundation for the promotion of health and biomedical research of the Valencian Community (FISABIO), Valencia, Spain"
+      },
+      {
+        "author_name": "Inaki Comas",
+        "author_inst": "Institute of Biomedicine of Valencia IBV-CSIC"
+      },
+      {
+        "author_name": "Fernando Gonzalez-Candelas",
+        "author_inst": "Universitat de Valencia"
+      },
+      {
+        "author_name": "Ron Geller",
+        "author_inst": "Institute for Integrative Systems Biology (I2SysBio), Universitat de Valencia-CSIC, 46980, Valencia, Spain"
+      },
+      {
+        "author_name": "David Navarro",
+        "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.07.18.500565",
@@ -208311,43 +209285,51 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.07.15.22277497",
-    "rel_title": "Global patterns and drivers of influenza decline during the COVID-19 pandemic",
+    "rel_doi": "10.1101/2022.07.16.22277705",
+    "rel_title": "Attitudes toward COVID-19 pandemic among fully vaccinated individuals: evidence from Greece two years after the pandemic",
     "rel_date": "2022-07-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.15.22277497",
-    "rel_abs": "Influenza circulation declined during the COVID-19 pandemic. The timing and extent of decline and its association with interventions against COVID-19 were described for some regions. Here, we provide a global analysis of the influenza decline between March 2020 and September 2021 and investigate its potential drivers. We computed influenza change by country and trimester relative to the 2014-2019 period using the number of samples in the FluNet database. We used random forests to determine important predictors in a list of 20 covariates including demography, weather, pandemic preparedness, COVID-19 incidence, and COVID-19 pandemic response. With a regression tree we then classified observations according to these predictors. We found that influenza circulation decreased globally, with COVID-19 incidence and pandemic preparedness being the two most important predictors of this decrease. The regression tree showed interpretable groups of observations by country and trimester: Europe and North America clustered together in spring 2020, with limited influenza decline despite strong COVID-19 restrictions; in the period afterwards countries of temperate regions, with high pandemic preparedness, high COVID-19 incidence and stringent social restrictions grouped together having strong influenza decline. Conversely, countries in the tropics, with altogether low pandemic preparedness, low reported COVID-19 incidence and low strength of COVID-19 response showed low influenza decline overall. A final group singled out four \"zero-Covid\" countries, with the lowest residual influenza levels. The spatiotemporal decline of influenza during the COVID-19 pandemic was global, yet heterogeneous. The sociodemographic context and stage of the COVID-19 pandemic showed non-linear associations with this decline. Zero-Covid countries maintained the lowest levels of reduction with strict border controls and despite close-to-normal social activity. These results suggest that the resurgence of influenza could take equally diverse paths. It also emphasises the importance of influenza reseeding in driving countries seasonal influenza epidemics.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.16.22277705",
+    "rel_abs": "BackgroundConsidering the major effects of COVID-19 pandemic on health, social, economic, and political dimensions of all countries, positive attitudes toward COVID-19 pandemic are essential to control the pandemic. In our study, we investigated attitudes toward COVID-19 pandemic among fully COVID-19 vaccinated individuals two years after the pandemic and we identified predictors of attitudes.\n\nMaterials and MethodsWe conducted an on-line cross-sectional study with 815 fully COVID-19 vaccinated individuals in Greece during May 2022. A self-administered and valid questionnaire was disseminated through social media platforms. We measured socio-demographic variables and COVID-19-related variables as potential predictors of attitudes toward COVID-19 pandemic. The outcome variable was attitudes toward COVID-19 pandemic (compliance with hygiene measures, trust in COVID-19 vaccination, fear of COVID-19, and information regarding the COVID-19 pandemic and vaccination).\n\nResultsWe found a very high level of compliance with hygiene measures, a high level of trust and information about the COVID-19 pandemic and vaccination, and a moderate level of fear of COVID-19. Also, we identified that females, participants with a higher educational level, those with a chronic disease, those with a better self-perceived physical health, and those without a previous COVID-19 diagnosis adhered more in hygiene measures. Trust in COVID-19 vaccination was higher among females, older participants, those with a higher educational level, those with a better self-perceived physical health, and those without a previous COVID-19 diagnosis. Moreover, females, older participants, those with a higher educational level, those with a chronic disease, those with a better self-perceived physical health, those that received a flu vaccine in previous season, and those without a previous COVID-19 diagnosis experienced more fear of the COVID-19. Finally, level of information regarding COVID-19 pandemic and vaccination was higher for participants with a higher educational level, those without a chronic disease, those with a better self-perceived physical health, and those that received a flu vaccine in previous season.\n\nConclusionsUnderstanding predictors of attitudes toward COVID-19 pandemic among fully vaccinated individuals is crucial for developing appropriate public health campaigns in the future. Vaccination should be accompanied by positive attitudes in order to decrease the frequency of negative outcomes of COVID-19, such as hospitalization, complications and mortality.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Francesco Bonacina",
-        "author_inst": "Sorbonne Universit\u00e9"
+        "author_name": "Petros A Galanis",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Pierre-Yves Bo\u00eblle",
-        "author_inst": "Sorbonne Universit\u00e9"
+        "author_name": "Irene Vraka",
+        "author_inst": "Department of Radiology, P. A. Kyriakou Children Hospital"
       },
       {
-        "author_name": "Vittoria Colizza",
-        "author_inst": "INSERM"
+        "author_name": "Aglaia Katsiroumpa",
+        "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Olivier Lopez",
-        "author_inst": "Sorbonne Universit\u00e9"
+        "author_name": "Olga Siskou",
+        "author_inst": "University of Piraeus"
       },
       {
-        "author_name": "Maud Thomas",
-        "author_inst": "Sorbonne Universit\u00e9"
+        "author_name": "Olympia Konstantakopoulou",
+        "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Chiara Poletto",
-        "author_inst": "INSERM and Sorbonne Universit\u00e9"
+        "author_name": "Theodoros Katsoulas",
+        "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Theodoros Mariolis-Sapsakos",
+        "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Daphne Kaitelidou",
+        "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.07.15.22277675",
@@ -210537,57 +211519,29 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.07.13.22277575",
-    "rel_title": "SARS-CoV-2 infections during Omicron (BA.1) dominant wave and subsequent population immunity in Gauteng, South Africa",
+    "rel_doi": "10.1101/2022.07.14.22277647",
+    "rel_title": "Estimating waning vaccine effectiveness from population-level surveillance data in multi-variant epidemics",
     "rel_date": "2022-07-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.13.22277575",
-    "rel_abs": "BackgroundThe B.1.1.529 (Omicron BA.1) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global resurgence of coronavirus disease 2019 (Covid-19). The contribution of BA.1 infection to population immunity and its effect on subsequent resurgence of B.1.1.529 sub-lineages warrant investigation.\n\nMethodsWe conducted an epidemiologic survey to determine the sero-prevalence of SARS-CoV-2 IgG from March 1 to April 11, 2022, after the BA.1-dominant wave had subsided in Gauteng (South Africa), and prior to a resurgence of Covid-19 dominated by the BA.4 and BA.5 (BA.4/BA.5) sub-lineages. Population-based sampling included households in an earlier survey from October 22 to December 9, 2021 preceding the BA.1 dominant wave. Dried-blood-spot samples were quantitatively tested for IgG against SARS-CoV-2 spike protein and nucleocapsid protein. Epidemiologic trends in Gauteng for cases, hospitalizations, recorded deaths, and excess deaths were evaluated from the inception of the pandemic to the onset of the BA.1 dominant wave (pre-BA.1), during the BA.1 dominant wave, and for the BA.4/BA.5 dominant wave through June 6, 2022.\n\nResultsThe 7510 participants included 2420 with paired samples from the earlier survey. Despite only 26.7% (1995/7470) of individuals having received a Covid-19 vaccine, the overall sero-prevalence was 90.9% (95% confidence interval [CI], 90.2 to 91.5), including 89.5% in Covid-19 unvaccinated individuals. Sixty-four percent (95%CI, 61.8-65.9) of individuals with paired samples had serological evidence of SARS-CoV-2 infection during the BA.1 dominant wave. Of all cumulative recorded hospitalisations and deaths, 14.1% and 5.9% were contributed by the BA.1 dominant wave, and 5.1% and 1.6% by the BA.4/BA.5 dominant wave. The SARS-CoV-2 infection fatality risk was lower in the BA.1 compared with pre-BA.1 waves for recorded deaths (0.02% vs. 0.33%) and Covid-19 attributable deaths based on excess mortality estimates (0.03% vs. 0.67%).\n\nConclusionsGauteng province experienced high levels of infections in the BA.1 -dominant wave against a backdrop of high (73%) sero-prevalence. Covid-19 hospitalizations and deaths were further decoupled from infections during BA.4/BA.5 dominant wave than that observed during the BA.1 dominant wave.\n\n(Funded by the Bill and Melinda Gates Foundation.)",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.14.22277647",
+    "rel_abs": "Monitoring time-varying vaccine effectiveness (e.g., due to waning of immunity and the emergence of novel variants) provides crucial information for outbreak control. Existing studies of time-varying vaccine effectiveness have used individual-level data, most importantly dates of vaccination and variant classification, which are often not available in a timely manner or from a wide range of population groups. We present a novel Bayesian framework for estimating the waning of variant-specific vaccine effectiveness in the presence of multi-variant circulation from population-level surveillance data. Applications to simulated outbreak and COVID-19 epidemic in Japan are also presented. Our results show that variant-specific waning vaccine effectiveness estimated from population-level surveillance data could approximately reproduce the estimates from previous test-negative design studies, allowing for rapid, if crude, assessment of the epidemic situation before fine-scale studies are made available.\n\nAuthor summaryThe emergence of immunity-escaping SARS-CoV-2 variants and the waning of vaccine effectiveness have highlighted the need for near-real-time monitoring of variant-specific protection in the population to guide control efforts. However, standard epidemiological studies to this end typically require access to detailed individual-level dataset, which may not be timely available in an ongoing outbreak. A more convenient and less resource-intensive approach using routinely-collected data could complement such studies by providing tentative estimates of waning vaccine effectiveness until the conclusive evidence becomes available. In this paper, we propose a novel Bayesian framework for estimating waning vaccine effectiveness against multiple co-circulating variants that requires only population-level surveillance data. Using simulated outbreak data of multiple variants,we showed that the proposed method can plausibly recover the ground truth from population-level data. We also applied the proposed method to empirical COVID-19 data in Japan, which yielded estimates that are overall in line with those derived from studies using individual-level data.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Shabir Madhi",
-        "author_inst": "University of the Witwatersrand"
-      },
-      {
-        "author_name": "Gaurav Kwatra",
-        "author_inst": "University of the Witwatersrand"
-      },
-      {
-        "author_name": "Jonathan E. Myers",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Waasila Jassat",
-        "author_inst": "National institute for communicable diseases of South Africa"
-      },
-      {
-        "author_name": "Nisha Dhar",
-        "author_inst": "University of the Witwatersrand"
-      },
-      {
-        "author_name": "Christian K. Mukendi",
-        "author_inst": "University of the Witwatersrand"
-      },
-      {
-        "author_name": "Lucille Blumberg",
-        "author_inst": "National institute for communicable diseases of South Africa"
-      },
-      {
-        "author_name": "Richard Welch",
-        "author_inst": "National institute for communicable diseases of South Africa"
+        "author_name": "Hiroaki Murayama",
+        "author_inst": "School of Medicine, International University of Health and Welfare"
       },
       {
-        "author_name": "Alane Izu",
-        "author_inst": "University of the Witwatersrand"
+        "author_name": "Akira Endo",
+        "author_inst": "Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Portia C. Mutevedzi",
-        "author_inst": "University of the Witwatersrand"
+        "author_name": "Shouto Yonekura",
+        "author_inst": "Graduate School of Social Sciences, Chiba University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -212247,47 +213201,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.07.10.22277467",
-    "rel_title": "Development of an Accurate and Rapid Antigen Assay for COVID-19 Diagnostics Using Saliva",
+    "rel_doi": "10.1101/2022.07.11.22277511",
+    "rel_title": "Effect of Stay-at-Home Orders and Other COVID-Related Policies on Trauma Hospitalization Rates and Disparities in the United States: A Statewide Time-Series Analysis",
     "rel_date": "2022-07-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.10.22277467",
-    "rel_abs": "The global outbreak of COVID-19 highlighted the need for rapid and accurate diagnostic testing to control the spread of this highly contagious disease (1-5). Here, we describe the nCoVega COVID-19 antigen rapid test ([~] 15min) that can detect the presence of the SARS-COV-2 virus particles from saliva sample on a portable device. The portable reader instrument, the Vega-200, has a small footprint and is designed for use at point of care settings. The test detects the fluorescence signal using wide-field illumination from antigen-antibody complexes captured on a special filter matrix (6). Results of this clinical evaluation of 183 subjects demonstrates that the nCoVega COVID-19 test performs at par with qRT-PCR tests (7) (gold standard) for both symptomatic and asymptomatic patients, with a strong inverse correlation between RFU (relative fluorescence units) and Ct counts (from RT-PCR) maintaining detection accuracy even at very low viral loads. The test has an analytical performance of 15.3 TCID50/mL, and 100% specificity for COVID-19 as compared to other human respiratory viruses, including other human coronaviruses. The working principle of this assay and test system can be used for developing other rapid, inexpensive antigen assays and it can offer an end-to-end, point-of-care solution to meet the continuous demand in tackling existing and emerging infectious diseases across the globe.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.11.22277511",
+    "rel_abs": "BackgroundTo combat the coronavirus pandemic, states implemented several public health policies to reduce infection and transmission. Increasing evidence suggests that these prevention strategies also have had a profound impact on non-COVID healthcare utilization. The goal of this study was to determine the impact of a statewide Stay-at-Home and other COVID-related policies on trauma hospitalizations, stratified by race/ethnicity, age, and sex.\n\nMethodsWe used the North Carolina Trauma Registry, a statewide registry of trauma hospitalizations to 18 hospitals across North Carolina, including all North Carolina trauma centers, to calculate weekly assault, self-inflicted, unintentional motor vehicle collision (MVC), and other unintentional injury hospitalization rates between January 1, 2019 and December 31, 2020. Interrupted time-series design and segmented linear regression were used to estimate changes in hospitalizations rates after several COVID-related executive orders, overall and stratified by race/ethnicity, age, and gender. Hospitalization rates were compared after 1) U.S. declaration of a public health emergency; 2) North Carolina statewide Stay-at-Home order; 3) Stay-at-Home order lifted with restrictions (Phase 2: Safer-at-Home); and 4) further lifting of restrictions (Phase 2.5: Safer-at-Home).\n\nResultsThere were 70,478 trauma hospitalizations in North Carolina from 2019-2020. In 2020, median age was 53 years old and 59% were male. Assault hospitalization rates (per 1,000,000 NC residents) increased after the Stay-at-Home order, but only among Black/African American residents (incidence rate difference [IRD]=7.9; other racial/ethnic groups IRDs ranged 0.9 to 1.7) and 18-44 year-old males (IRD=11.9; other sex/age groups IRDs ranged -0.5 to 3.6). After major restrictions were lifted, assault rates returned to pre-COVID levels. Unintentional injury hospitalizations decreased after the public health emergency, especially among older adults, but returned to 2019 levels within several months.\n\nConclusionsStatewide Stay-at-Home orders put Black/African American residents at higher risk for assault hospitalizations, exacerbating pre-existing disparities. Fear of COVID-19 may have also led to decreases in unintentional non-MVC hospitalization rates, particularly among older adults. Policy makers must anticipate possible negative effects and develop approaches for mitigating harms that may disproportionately affect already disadvantaged communities.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Camille Troup",
-        "author_inst": "Kaya17 Inc"
+        "author_name": "Paula D Strassle",
+        "author_inst": "National Institute on Minority Health and Health Disparitites"
+      },
+      {
+        "author_name": "Alan C Kinlaw",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Debnath Mukhopadhyay",
-        "author_inst": "Kaya17 Inc"
+        "author_name": "Jamie S Ko",
+        "author_inst": "National Institute on Minority Health and Health Disparities"
       },
       {
-        "author_name": "Tania Chakrabarty",
-        "author_inst": "Kaya17 Inc"
+        "author_name": "Stephanie Quintero",
+        "author_inst": "National Institute on Minority Health and Health Disparities"
       },
       {
-        "author_name": "Anup Madan",
-        "author_inst": "Kaya17 Inc"
+        "author_name": "Jackie Bonilla",
+        "author_inst": "Emory University"
       },
       {
-        "author_name": "Sri Satyanarayana",
-        "author_inst": "Kaya17, inc"
+        "author_name": "Madison Ponder",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Shreefal Mehta",
-        "author_inst": "Kaya17 Inc"
+        "author_name": "Anna Mar\u00eda N\u00e1poles",
+        "author_inst": "National Institute on Minority Health and Health Disparities"
       },
       {
-        "author_name": "Sulatha Dwarakanath",
-        "author_inst": "Kaya17 Inc"
+        "author_name": "Sharon E Schiro",
+        "author_inst": "University of North Carolina at Chapel Hill"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "emergency medicine"
   },
   {
     "rel_doi": "10.1101/2022.07.07.22277315",
@@ -214305,105 +215263,89 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.07.05.22277189",
-    "rel_title": "Class switch towards non-inflammatory IgG isotypes after repeated SARS-CoV-2 mRNA vaccination",
+    "rel_doi": "10.1101/2022.07.07.22277364",
+    "rel_title": "Altered affinity to ACE2 and reduced Fc functional antibodies to SARS-CoV-2 RBD variants",
     "rel_date": "2022-07-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.05.22277189",
-    "rel_abs": "Repeated mRNA vaccinations are an efficient tool to combat the SARS-CoV-2 pandemic. High levels of neutralizing SARS-CoV-2-antibodies are an important component of vaccine-induced immunity. Shortly after the first or second mRNA vaccine dose, the IgG response mainly consists of the pro-inflammatory isotypes IgG1 and IgG3 and is driven by T helper (Th) 1 cells. Here, we report that several months after the second vaccination, SARS-CoV-2-specific antibodies were increasingly composed of non-inflammatory IgG2 and particularly IgG4, which were further boosted by a third mRNA vaccination and/or SARS-CoV-2 variant breakthrough infections. While IgG antibodies were affinity matured and of high neutralization capacity, the switch in constant domains caused changes in fragment crystallizable (Fc)-receptor mediated effector functions, including a decreased capacity to facilitate phagocytosis. IgG4 induction was neither induced by Th2 cells nor observed after homologous or heterologous SARS-CoV-2 vaccination with adenoviral vectors. In addition, IgG2- and IgG4-producing memory B cells were phenotypically indistinguishable from IgG1- or IgG3-producing cells. Since Fc-mediated effector functions are critical for antiviral immunity, the described class switch towards non-inflammatory IgG isotypes, which otherwise rarely occurs after vaccination or viral infection, may have consequences for the choice and timing of vaccination regimens using mRNA vaccines.",
-    "rel_num_authors": 22,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.07.22277364",
+    "rel_abs": "The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants remains a formidable challenge to worldwide public health. The receptor binding domain (RBD) of the SARS-CoV-2 spike protein is a hotspot for mutations, reflecting its critical role at the ACE2 interface during viral entry. We comprehensively investigated the impact of RBD mutations, including 6 variants of concern (VOC) or interest (Alpha, Beta, Gamma, Delta, Kappa and Omicron) and 33 common point mutations, on IgG recognition, Fc{gamma}R-engagement, and ACE2-binding inhibition in plasma from BNT162b2-vaccine recipients (two-weeks following second dose) and mild-to-moderate COVID-19 convalescent subjects using our custom bead-based 39-plex array. We observed that IgG-recognition and Fc{gamma}R-binding antibodies were most profoundly decreased against Beta and Omicron RBDs, as well as point mutations G446S, found in Omicron, and N501T, a key mutation found in animal adapted SARS-CoV-2 viruses. Measurement of RBD-ACE2 binding affinity via Biolayer Interferometry showed all VOC RBDs have enhanced affinity to human ACE2. Furthermore we demonstrate that human ACE2 polymorphisms, E35K (rs1348114695), K26R (rs4646116) and S19P (rs73635825), have altered binding kinetics to the RBD of VOCs potentially affecting virus-host interaction and thereby host susceptibility.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Pascal Irrgang",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
-      },
-      {
-        "author_name": "Juliane Gerling",
-        "author_inst": "Department of Biology, Division of Genetics, Nikolaus-Fiebiger-Center for Molecular Medicine, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen,"
-      },
-      {
-        "author_name": "Katharina Kocher",
-        "author_inst": "Mikrobiologisches Institut - Klinische Mikrobiologie, Immunologie und Hygiene, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlange"
-      },
-      {
-        "author_name": "Dennis Lapuente",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
-      },
-      {
-        "author_name": "Philipp Steininger",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
+        "author_name": "Ebene R Haycroft",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Monika Wytopil",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
+        "author_name": "Samantha K Davis",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Simon Sch\u00e4fer",
-        "author_inst": "Department of Biology, Division of Genetics, Nikolaus-Fiebiger-Center for Molecular Medicine, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen,"
+        "author_name": "Pradhipa Ramanathan",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Katharina Habenicht",
-        "author_inst": "Department of Biology, Division of Genetics, Nikolaus-Fiebiger-Center for Molecular Medicine, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen,"
+        "author_name": "Ester Lopez",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Jahn Zhong",
-        "author_inst": "Department of Biology, Division of Genetics, Nikolaus-Fiebiger-Center for Molecular Medicine, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen,"
+        "author_name": "Ruth A Purcell",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "George Ssebyatika",
-        "author_inst": "Center of Structural and Cell Biology in Medicine, Institute of Biochemistry, University of Luebeck, Luebeck, Germany"
+        "author_name": "Li Lynn Tan",
+        "author_inst": "WEHI"
       },
       {
-        "author_name": "Thomas Krey",
-        "author_inst": "Center of Structural and Cell Biology in Medicine, Institute of Biochemistry, University of Luebeck, Luebeck, Germany"
+        "author_name": "Phillip Pymm",
+        "author_inst": "WEHI"
       },
       {
-        "author_name": "Valeria Falcone",
-        "author_inst": "Institute of Virology, Freiburg University Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany"
+        "author_name": "Bruce D Wines",
+        "author_inst": "Burnet Institute"
       },
       {
-        "author_name": "Christine Sch\u00fclein",
-        "author_inst": "Mikrobiologisches Institut - Klinische Mikrobiologie, Immunologie und Hygiene, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlange"
+        "author_name": "P Mark Hogarth",
+        "author_inst": "Burnet Institute"
       },
       {
-        "author_name": "Antonia Sophia Peter",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
+        "author_name": "Adam K Wheatley",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Krystelle Nganou-Makamdop",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
+        "author_name": "Jennifer A Juno",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Hartmut Hengel",
-        "author_inst": "Institute of Virology, Freiburg University Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany"
+        "author_name": "Samuel Redmond",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "J\u00fcrgen Held",
-        "author_inst": "Mikrobiologisches Institut - Klinische Mikrobiologie, Immunologie und Hygiene, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlange"
+        "author_name": "Nicholas A Gheradin",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Christian Bogdan",
-        "author_inst": "Mikrobiologisches Institut - Klinische Mikrobiologie, Immunologie und Hygiene, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlange"
+        "author_name": "Dale Godfrey",
+        "author_inst": "Peter Doherty Institute"
       },
       {
-        "author_name": "Klaus \u00dcberla",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
+        "author_name": "Wai-Hong Tham",
+        "author_inst": "WEHI"
       },
       {
-        "author_name": "Kilian Schober",
-        "author_inst": "Mikrobiologisches Institut - Klinische Mikrobiologie, Immunologie und Hygiene, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlange"
+        "author_name": "Kevin John Selva",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Thomas H Winkler",
-        "author_inst": "Department of Biology, Division of Genetics, Nikolaus-Fiebiger-Center for Molecular Medicine, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen,"
+        "author_name": "Stephen Kent",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Matthias Tenbusch",
-        "author_inst": "Institut fuer klinische und molekulare Virologie, Universitaetsklinikum Erlangen und Friedrich-Alexander-Universitaet (FAU) Erlangen-Nuernberg, Schlossgarten 4,"
+        "author_name": "Amy W Chung",
+        "author_inst": "University of Melbourne"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -216491,27 +217433,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.07.06.22277303",
-    "rel_title": "Quantifying the impact of vaccines and booster doses on COVID-19 in the U.S.",
-    "rel_date": "2022-07-07",
+    "rel_doi": "10.1101/2022.07.02.22277181",
+    "rel_title": "Integrative analysis of viral entry networks and clinical outcomes identifies a protective role for spironolactone in severe COVID-19",
+    "rel_date": "2022-07-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.06.22277303",
-    "rel_abs": "The COVID-19 pandemic continues to have a devastating impact on health systems and economies across the globe. Implementing public health measures in tandem with effective vaccination strategies have been instrumental in curtailing the burden of the pandemic. With the three vaccines authorized for use in the U.S. having varying efficacies and waning effects against major COVID-19 strains, understanding the impact of these vaccines on COVID-19 incidence and fatalities is critical. Here, we formulate and use mathematical models to assess the impact of vaccine type, vaccination and booster uptake, and waning of natural and vaccine-induced immunity on the incidence and fatalities of COVID-19 and to predict future trends of the disease in the U.S. when existing control measures are reinforced or relaxed. Results of the study show a 5, 1.8, and 2 times reduction in the reproduction number during the period in which vaccination, first booster, and second booster uptake started, respectively, compared to the previous period. Due to waning of vaccine-induced immunity, vaccinating up to 96% of the U.S. population might be required to attain herd immunity, if booster uptake is low. Additionally, vaccinating and boosting more people from the onset of vaccination and booster uptake, especially with mRNA vaccines (which confer superior protection than the Johnson & Johnson vaccine) would have led to a significant reduction in COVID-19 cases and deaths in the U.S. Furthermore, adopting natural immunity-boosting measures is important in fighting COVID-19 and transmission rate reduction measures such as mask-use are critical in combating COVID-19. The emergence of a more transmissible COVID-19 variant, or early relaxation of existing control measures can lead to a more devastating wave, especially if transmission rate reduction measures and vaccination are relaxed simultaneously, while chances of containing the pandemic are enhanced if both vaccination and transmission rate reduction measures are reinforced simultaneously. We conclude that maintaining or improving existing control measures and boosting with mRNA vaccines are critical in curtailing the burden of the pandemic in the U.S.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.02.22277181",
+    "rel_abs": "Treatment strategies that target host entry factors have proven an effective means of impeding viral entry in HIV and may be more robust to viral evolution than drugs targeting viral proteins directly. High-throughput functional screens provide an unbiased means of identifying genes that influence the infection of host cells, while retrospective cohort analysis can measure the real-world, clinical potential of repurposing existing therapeutics as antiviral treatments. Here, we combine these two powerful methods to identify drugs that alter the clinical course of COVID-19 by targeting host entry factors. We demonstrate that integrative analysis of genome-wide CRISPR screening datasets enables network-based prioritization of drugs modulating viral entry, and we identify three common medications (spironolactone, quetiapine, and carvedilol) based on their network proximity to putative host factors. To understand the drugs real-world impact, we perform a propensity-score-matched, retrospective cohort study of 64,349 COVID-19 patients and show that spironolactone use is associated with improved clinical prognosis, measured by both ICU admission and mechanical ventilation rates. Finally, we show that spironolactone exerts a dose-dependent inhibitory effect on viral entry in a human lung epithelial cell line. Our results suggest that spironolactone may improve clinical outcomes in COVID-19 through tissue-dependent inhibition of viral entry. Our work further provides a potential approach to integrate functional genomics with real-world evidence for drug repurposing.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Calistus N. Ngonghala",
-        "author_inst": "Department of Mathematics, University of Florida, Gainesville, FL 32611, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA."
+        "author_name": "Henry Cousins",
+        "author_inst": "Stanford University School of Medicine"
       },
       {
-        "author_name": "Michael Asare-Baah",
-        "author_inst": "Department of Epidemiology, University of Florida, 2004 Mowry Road, Gainesville, FL 32610, USA; Emerging Pathogens Institute, University of Florida, Gainesville"
+        "author_name": "Adrienne Sarah Kline",
+        "author_inst": "Feinberg School of Medicine, Northwestern University"
+      },
+      {
+        "author_name": "Chengkun Wang",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Yuanhao Qu",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Mengdi Wang",
+        "author_inst": "Princeton University"
+      },
+      {
+        "author_name": "Russ Altman",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Yuan Luo",
+        "author_inst": "Feinberg School of Medicine, Northwestern University"
+      },
+      {
+        "author_name": "Le Cong",
+        "author_inst": "Stanford University School of Medicine"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.07.03.22277169",
@@ -219429,47 +220395,83 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.07.03.22277196",
-    "rel_title": "Leveraging Serosurveillance and Postmortem Surveillance to Quantify the Impact of COVID-19 in Africa",
+    "rel_doi": "10.1101/2022.06.29.498117",
+    "rel_title": "COVID-19 Neuropathology: evidence for SARS-CoV-2 invasion of Human Brainstem Nuclei",
     "rel_date": "2022-07-05",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.03.22277196",
-    "rel_abs": "BackgroundThe COVID-19 pandemic has had a devastating impact on global health, the magnitude of which appears to differ intercontinentally: for example, reports suggest 271,900 per million people have been infected in Europe versus 8,800 per million people in Africa. While Africa is the second largest continent by population, its reported COVID-19 cases comprise <3% of global cases. Although social, environmental, and environmental explanations have been proposed to clarify this discrepancy, systematic infection underascertainment may be equally responsible.\n\nMethodsWe seek to quantify magnitude of underascertainment in COVID-19s cumulative incidence in Africa. Using serosurveillance and postmortem surveillance, we constructed multiplicative factors estimating ratios of true infections to reported cases in African nations since March 2020.\n\nResultsMultiplicative factors derived from serology data - in a subset of 12 nations - suggested a range of COVID-19 reporting rates, from 1 in 630 infections reported in Kenya (May 2020) to 1 in 15 infections reported in South Africa (November 2021). The largest multiplicative factor, 3,795, corresponded to Malawi (June 2020), suggesting <0.05% of infections captured. A similar set of multiplicative factors for all nations derived from postmortem data points toward the same conclusion: reported COVID-19 cases are unrepresentative of true infections, suggesting a key reason for low case burden in many African nations is significant underdetection and underreporting.\n\nConclusionsWhile estimating COVID-19s exact burden is challenging, the multiplicative factors we present provide incidence curves reflecting likely-to-worst-case ranges of infection. Our results stress the need for expansive surveillance to allocate resources in areas experiencing severe discrepancies between reported cases, projected infections, and deaths.\n\nSummaryHere we present a range of estimates quantifying the extent of underascertainment of COVID-19 cumulative incidence in Africa. These estimates, constructed from serology and mortality data, suggest that systematic underdetection and underreporting may be contributing to the seemingly low burden of COVID-19 reported in Africa.",
-    "rel_num_authors": 7,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.29.498117",
+    "rel_abs": "Neurological manifestations are common in COVID-19, the disease caused by SARS-CoV-2. Despite reports of SARS-CoV-2 detection in the brain and cerebrospinal fluid of COVID-19 patients, its still unclear whether the virus can infect the central nervous system, and which neuropathological alterations can be ascribed to viral tropism, rather than immune-mediated mechanisms.\n\nHere, we assess neuropathological alterations in 24 COVID-19 patients and 18 matched controls who died due to pneumonia / respiratory failure. Aside from a wide spectrum of neuropathological alterations, SARS-CoV-2-immunoreactive neurons were detected in specific brainstem nuclei of 5 COVID-19 subjects. Viral RNA was also detected by real-time RT-PCR. Quantification of reactive microglia revealed an anatomically segregated pattern of inflammation within affected brainstem regions, and was higher when compared to controls. While the results of this study support the neuroinvasive potential of SARS-CoV-2, the role of SARS-CoV-2 neurotropism in COVID-19 and its long-term sequelae require further investigation.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Nicole Kogan",
-        "author_inst": "Harvard T. H. Chan School of Public Health | Northeastern University"
+        "author_name": "Aron Emmi",
+        "author_inst": "Institute of Human Anatomy, Department of Neuroscience, University of Padova, Italy"
       },
       {
-        "author_name": "Shae Gantt",
-        "author_inst": "Harvard T. H. Chan School of Public Health"
+        "author_name": "Stefania Rizzo",
+        "author_inst": "Department of Cardio-Thoracic-Vascular Sciences & Public Health, University of Padova, Italy"
       },
       {
-        "author_name": "David Swerdlow",
-        "author_inst": "Harvard T.H. Chan School of Public Health"
+        "author_name": "Luisa Barzon",
+        "author_inst": "Department of Molecular Medicine, University of Padova, Padova, Italy"
       },
       {
-        "author_name": "Cecile Viboud",
-        "author_inst": "National Institutes of Health"
+        "author_name": "Michele Sandre",
+        "author_inst": "Movement Disorders Unit, Neurology Clinic, Department of Neuroscience, University of Padova"
       },
       {
-        "author_name": "Muhammed Semakula",
-        "author_inst": "Rwanda Biomedical Centre"
+        "author_name": "Elisa Carturan",
+        "author_inst": "Department of Cardio-Thoracic-Vascular Sciences & Public Health, University of Padova, Italy"
       },
       {
-        "author_name": "Marc Lipsitch",
-        "author_inst": "Harvard T. H. Chan School of Public Health | CDC"
+        "author_name": "Alessandro Sinigaglia",
+        "author_inst": "Department of Molecular Medicine, University of Padova, Padova, Italy"
       },
       {
-        "author_name": "Mauricio Santillana",
-        "author_inst": "Northeastern University | Harvard T. H. Chan School of Public Health"
+        "author_name": "Silvia Riccetti",
+        "author_inst": "Department of Molecular Medicine, University of Padova, Padova, Italy"
+      },
+      {
+        "author_name": "Mila della Barbera",
+        "author_inst": "Department of Cardio-Thoracic-Vascular Sciences & Public Health, University of Padova, Italy"
+      },
+      {
+        "author_name": "Rafael Boscolo-Berto",
+        "author_inst": "Institute of Human Anatomy, Department of Neuroscience, University of Padova, Italy"
+      },
+      {
+        "author_name": "Patrizia Cocco",
+        "author_inst": "Pathology and Histopathology Unit, Ospedali Riuniti Padova Sud, Padova, Italy"
+      },
+      {
+        "author_name": "Veronica Macchi",
+        "author_inst": "Institute of Human Anatomy, Department of Neuroscience, University of Padova, Italy"
+      },
+      {
+        "author_name": "Angelo Antonini",
+        "author_inst": "Movement Disorders Unit, Neurology Clinic, Department of Neuroscience, University of Padova"
+      },
+      {
+        "author_name": "Monica De Gaspari",
+        "author_inst": "Department of Cardio-Thoracic-Vascular Sciences & Public Health, University of Padova, Italy"
+      },
+      {
+        "author_name": "Cristina Basso",
+        "author_inst": "Department of Cardio-Thoracic-Vascular Sciences & Public Health, University of Padova, Italy"
+      },
+      {
+        "author_name": "Raffaele De Caro",
+        "author_inst": "Institute of Human Anatomy, Department of Neuroscience, University of Padova, Italy"
+      },
+      {
+        "author_name": "Andrea Porzionato",
+        "author_inst": "Institute of Human Anatomy, Department of Neuroscience, University of Padova, Italy"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "type": "new results",
+    "category": "neuroscience"
   },
   {
     "rel_doi": "10.1101/2022.07.05.498834",
@@ -221431,91 +222433,51 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.07.01.22277163",
-    "rel_title": "Phase 2 randomised placebo-controlled trial of spironolactone and dexamethasone versus dexamethasone in COVID-19 hospitalised patients in Delhi",
-    "rel_date": "2022-07-02",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.01.22277163",
-    "rel_abs": "BackgroundIn this phase 2 randomised placebo-controlled clinical trial, we hypothesised that blocking mineralocorticoid receptors with spironolactone in patients with COVID-19 is safe and may reduce illness severity.\n\nMethodsHospitalised patients with confirmed COVID-19 were randomly allocated to low dose oral spironolactone (50mg day 1, then 25mg once daily for 21 days) or standard care in a 2:1 ratio. Both groups received dexamethasone 6mg for 10 days. Group allocation was blinded to the patient and research team. Primary outcomes were time to recovery, defined as the number of days until patients achieved WHO Ordinal Scale (OS) category [&le;] 3, and the effect of spironolactone on aldosterone, D-dimer, angiotensin II and Von Willebrand Factor (VWF).\n\nResults120 patients were recruited in Delhi from 01 February to 30 April 2021. 74 were randomly assigned to spironolactone and dexamethasone (SpiroDex), and 46 to dexamethasone alone (Dex). There was no significant difference in the time to recovery between SpiroDex and Dex groups (SpiroDex median 4.5 days, Dex median 5.5 days, p = 0.055). SpiroDex patients had lower aldosterone levels on day 7 and lower D-dimer levels on days 4 and 7 (day 7 D-dimer mean SpiroDex 1.15{micro}g/mL, Dex 3.15 {micro}g/mL, p = 0.0004). There was no increase in adverse events in patients receiving SpiroDex. Post hoc analysis demonstrated reduced clinical deterioration (pre specified as escalating to WHO OS category >4) in the SpiroDex group vs Dex group (5.4% vs 19.6%).\n\nConclusionLow dose oral spironolactone in addition to dexamethasone was safe and reduced D-Dimer and aldosterone. Although time to recovery was not significantly reduced, fewer patients progressed to severe disease. Phase 3 randomised controlled trials with spironolactone should be considered.",
-    "rel_num_authors": 18,
+    "rel_doi": "10.1101/2022.06.30.498338",
+    "rel_title": "Transcriptional Profiles Analysis of COVID-19 and Malaria Patients Reveals Potential Biomarkers in Children",
+    "rel_date": "2022-07-01",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.30.498338",
+    "rel_abs": "The clinical presentation overlap between malaria and COVID-19 poses special challenges for rapid diagnosis in febrile children. In this study, we collected RNA-seq data of children with malaria and COVID-19 infection from the public databases as raw data in fastq format paired end files. A group of six, five and two biological replicates of malaria, COVID-19 and healthy donors respectively were used for the study. We conducted differential gene expression analysis to visualize differences in the expression profiles. Using edgeR, we explored particularly gene expression levels in different phenotype groups and found that 1084 genes and 2495 genes were differentially expressed in the malaria samples and COVID-19 samples respectively when compared to healthy controls. The highly expressed gene in the COVID-19 group we found CD151 gene which is facilitates in T cell proliferation, while in the malaria group, among the highly expressed gene we identified GBP5 gene which involved in inflammatory response and response to bacterium. By comparing both malaria and COVID-19 infections, the overlap of 62 differentially expressed genes patterns were identified. Among them, three genes (ENSG00000234998, H2AC19 and TXNDC5) were highly upregulated in both infections. Strikingly, we observed 13 genes such as HBQ1, HBM, SLC7A5, SERINC2, ATP6V0C, ST6GALNAC4, RAD23A, PNPLA2, GAS2L1, TMEM86B, SLC6A8, UBALD1, RNF187 were downregulated in children with malaria and uniquely upregulated in children with COVID-19, thus may be further validated as potential biomarkers to delineate COVID-19 from malaria-related febrile infection. The hemoglobin complexes and lipid metabolism biological pathways are highly expressed in both infections. Our study provided new insights for further investigation of the biological pattern in hosts with malaria and COVID-19 coinfection.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Bharti Wadhwa",
-        "author_inst": "Department of Anaesthesia, Maulana Azad Medical College, New Delhi, India"
-      },
-      {
-        "author_name": "Vikas Malhotra",
-        "author_inst": "Department of ENT & Head and Neck Surgery, Maulana Azad Medical College & Associated Hospitals, New Delhi, India"
-      },
-      {
-        "author_name": "Sukhyanti Kerai",
-        "author_inst": "Department of Anaesthesia, Maulana Azad Medical College, New Delhi, India"
-      },
-      {
-        "author_name": "Farah Husain",
-        "author_inst": "Department of Anaesthesia, Maulana Azad Medical College, New Delhi, India"
-      },
-      {
-        "author_name": "Nalini Bala Pandey",
-        "author_inst": "Department of Anaesthesia, Maulana Azad Medical College, New Delhi, India"
-      },
-      {
-        "author_name": "Kirti N Saxena",
-        "author_inst": "Department of Anaesthesia, Maulana Azad Medical College, New Delhi, India"
-      },
-      {
-        "author_name": "Vinay Singh",
-        "author_inst": "Department of Anaesthesia, Maulana Azad Medical College, New Delhi, India"
-      },
-      {
-        "author_name": "Tom Michael Quinn",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
-      },
-      {
-        "author_name": "Feng Li",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
+        "author_name": "Nzungize Lambert",
+        "author_inst": "Liverpool School of Tropical Medicine Research Unit, Centre for Research in Infectious Diseases (CRID), P.O. Box 13591  Cameroon."
       },
       {
-        "author_name": "Erin Gaughan",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
+        "author_name": "Kengne-Ouafo A. Jonas",
+        "author_inst": "Liverpool School of Tropical Medicine Research Unit, Centre for Research in Infectious Diseases (CRID), P.O. Box 13591, Cameroon."
       },
       {
-        "author_name": "Manu Shankar-Hari",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
+        "author_name": "Wesonga Makokha Rissy",
+        "author_inst": "African institute of Biomedical science and technology(AiBST), Zimbabwe"
       },
       {
-        "author_name": "Bethany Mills",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
+        "author_name": "Umuhoza Diane",
+        "author_inst": "Rwanda Agriculture and Animal Ressources Board (RAB), Rwanda"
       },
       {
-        "author_name": "Jean Antonelli",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
+        "author_name": "Ken Murithi",
+        "author_inst": "International Center of Insect Physiology and Ecology, Kenya"
       },
       {
-        "author_name": "Annya Bruce",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
+        "author_name": "Kimani Peter",
+        "author_inst": "International Center of Insect Physiology and Ecology, Kenya"
       },
       {
-        "author_name": "Keith Finlayson",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
+        "author_name": "Olaitan I. Awe",
+        "author_inst": "University of Ibadan, Ibadan, Oyo State, Nigeria"
       },
       {
-        "author_name": "Anne Moore",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
-      },
-      {
-        "author_name": "Kevin Dhaliwal",
-        "author_inst": "Centre for Inflammation Research, The Queens Medical Research Institute, The University of Edinburgh,UK"
-      },
-      {
-        "author_name": "Christopher Edwards",
-        "author_inst": "Imperial College, Hammersmith Campus, UK"
+        "author_name": "Allissa Dillman",
+        "author_inst": "National Institutes of Health, Bethesda, MD, U.S.A."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "respiratory medicine"
+    "license": "cc_by_nc",
+    "type": "new results",
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2022.07.01.496571",
@@ -223145,35 +224107,83 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.06.29.22277010",
-    "rel_title": "Exploring the Role of Superspreading Events in SARS-CoV-2 Outbreaks",
-    "rel_date": "2022-06-29",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.29.22277010",
-    "rel_abs": "The novel coronavirus SARS-CoV-2 emerged in 2019 and subsequently spread throughout the world, causing over 529 million cases and 6 million deaths thus far. In this study, we formulate a continuous-time Markov chain model to investigate the influence of superspreading events (SSEs), defined here as public or social events that result in multiple infections over a short time span, on SARS-CoV-2 outbreak dynamics. Using Gillespies direct algorithm, we simulate a continuous-time Markov chain model for SARS-CoV-2 spread under multiple scenarios: first, with neither hospitalisation nor quarantine; second, with hospitalisation, quarantine, premature hospital discharge, and quarantine violation; and third, with hospitalisation and quarantine but neither premature hospital discharge nor quarantine violation. We also vary quarantine violation rates. Results indicate that, in most cases, SSE-dominated outbreaks are more variable but less severe than non-SSE-dominated outbreaks, though the most severe SSE-dominated outbreaks are more severe than the most severe non-SSE-dominated outbreaks. SSE-dominated outbreaks are outbreaks with relatively higher SSE rates. In all cases, SSE-dominated outbreaks are more sensitive to control measures, with premature hospital discharge and quarantine violation substantially reducing control measure effectiveness.",
-    "rel_num_authors": 4,
+    "rel_doi": "10.1101/2022.06.27.497749",
+    "rel_title": "The RNA demethylase FTO controls m6A marking on SARS-CoV-2 and classifies COVID-19 severity in patients",
+    "rel_date": "2022-06-28",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.27.497749",
+    "rel_abs": "The RNA modification N6-methyladenosine (m6A) plays a key role in the life cycles of several RNA viruses. Whether this applies to SARS-CoV-2 and whether m6A affects the outcome of COVID-19 disease is still poorly explored. Here we report that the RNA demethylase FTO strongly affects both m6A marking of SARS-CoV-2 and COVID-19 severity. By m6A profiling of SARS-CoV-2, we confirmed in infected cultured cells and showed for the first time in vivo in hamsters that the regions encoding TRS_L and the nucleocapsid protein are multiply marked by m6A, preferentially within RRACH motifs that are specific to {beta}-coronaviruses and well conserved across SARS-CoV-2 variants. In cells, downregulation of the m6A demethylase FTO, occurring upon SARS-CoV-2 infection, increased m6A marking of SARS-CoV-2 RNA and slightly promoted viral replication. In COVID-19 patients, a negative correlation was found between FTO expression and both SARS-CoV-2 expression and disease severity. FTO emerged as a classifier of disease severity and hence a potential stratifier of COVID-19 patients.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Jordan Bramble",
-        "author_inst": "University of Kansas"
+        "author_name": "Lionel Malbec",
+        "author_inst": "University of Brussels"
       },
       {
-        "author_name": "Alexander Fulk",
-        "author_inst": "University of Kansas"
+        "author_name": "Margot Celerier",
+        "author_inst": "University of Brussels"
       },
       {
-        "author_name": "Raul Saenz",
-        "author_inst": "University of Kansas Medical Center"
+        "author_name": "Martin Bizet",
+        "author_inst": "University of Brussels"
       },
       {
-        "author_name": "Folashade Agusto",
-        "author_inst": "University of Kansas"
+        "author_name": "Emilie Calonne",
+        "author_inst": "University of Brussels"
+      },
+      {
+        "author_name": "Heike Hofmann-Winkler",
+        "author_inst": "German Primate Center"
+      },
+      {
+        "author_name": "Bram Boeckx",
+        "author_inst": "University of Leuven"
+      },
+      {
+        "author_name": "Rana Abdelnabi",
+        "author_inst": "University of Leuven"
+      },
+      {
+        "author_name": "Pascale Putmans",
+        "author_inst": "University of Brussels"
+      },
+      {
+        "author_name": "Bouchra Hassabi",
+        "author_inst": "University of Brussels"
+      },
+      {
+        "author_name": "Lieve Naesens",
+        "author_inst": "University of Leuven"
+      },
+      {
+        "author_name": "Diether Lambrechts",
+        "author_inst": "University of Leuven"
+      },
+      {
+        "author_name": "Stefan P\u00f6hlmann",
+        "author_inst": "German Primate Center"
+      },
+      {
+        "author_name": "Rachel Deplus",
+        "author_inst": "University of Brussels"
+      },
+      {
+        "author_name": "Leen Delang",
+        "author_inst": "University of Leuven"
+      },
+      {
+        "author_name": "Jana Jeschke",
+        "author_inst": "University of Brussels"
+      },
+      {
+        "author_name": "Francois Fuks",
+        "author_inst": "University of Brussels"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2022.06.24.22276872",
@@ -224927,43 +225937,99 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.06.24.22276852",
-    "rel_title": "Compliant citizens, defiant rebels or neither? Exploring changing COVID-19 vaccine attitudes and decisions in Bradford, UK: Findings from a follow-up qualitative study",
+    "rel_doi": "10.1101/2022.06.22.22276744",
+    "rel_title": "Vaccination saves lives: How do patients with chronic diseases and severe COVID-19 fare? Analysis from Indias National Clinical registry for COVID-19",
     "rel_date": "2022-06-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.24.22276852",
-    "rel_abs": "BackgroundCOVID-19 vaccines have been the central pillar of the public health response to the pandemic, intended to enable us to  live with Covid. It is important to understand COVID-19 vaccines attitudes and decisions in order to maximise uptake through an empathetic lens.\n\nObjectiveTo explore the factors that influenced peoples COVID-19 vaccines decisions and how attitudes towards the vaccines had changed in an eventful year.\n\nDesign and participantsThis is a follow up study that took place in Bradford, UK one year after the original study, between October 2021 and January 2022. In-depth phone interviews were conducted with 12 (of the 20 originally interviewed) people from different ethnic groups and areas of Bradford. Reflexive thematic analysis was conducted.\n\nResults11 of the 12 participants interviewed had received both doses of the COVID-19 vaccine and most intended to have a booster dose. Participants described a variety of reasons why they had decided to have the vaccines, including: feeling at increased risk at work; protecting family and others in their communities, unrestricted travel and being influenced by the vaccine decisions of family, friends and colleagues. All participants discussed ongoing interaction with COVID-19 misinformation and for some this meant they were uneasy about their decision to have the vaccine. They described feeling overloaded by and disengaged from COVID-19 information, which they often found contradictory and some felt mistrustful of the UK governments motives and decisions during the pandemic.\n\nConclusionsThe majority of participants had managed to navigate an overwhelming amount of circulating COVID-19 misinformation and chosen to have two or more COVID-19 vaccines, even if they had been previously said they were unsure. However, these decisions were complicated, and demonstrate the continuum of vaccine hesitancy and acceptance. This follow up study underlines that vaccine attitudes are changeable and contextual.\n\nPatient or Public ContributionThe original study was developed through a rapid community and stakeholder engagement process in 2020. Discussion with the Bradford Council Public Health team and the public through the Bradford COVID-19 Community Insights Group was undertaken in 2021 to identify important priorities for this follow up study.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.22.22276744",
+    "rel_abs": "ObjectivesThis study aims to describe the demographic and clinical profile and ascertain the determinants of outcome among hospitalised COVID-19 adult patients enrolled in the National Clinical Registry for COVID-19 (NCRC).\n\nMethodsNCRC is an on-going data collection platform operational in 42 hospitals across India. Data of hospitalized COVID-19 patients enrolled in NCRC between 1st September 2020 to 26th October 2021 were examined.\n\nResultsAnalysis of 29,509 hospitalised, adult COVID-19 patients [mean (SD) age: 51.1 (16.2) year; male: 18752 (63.6%)] showed that 15678 (53.1%) had at least one comorbidity. Among 25715 (87.1%) symptomatic patients, fever was the commonest symptom (72.3%) followed by shortness of breath (48.9%) and dry cough (45.5%). In-hospital mortality was 14.5% (n=3957). Adjusted odds of dying were significantly higher in age-group [&ge;]60 years, males, with diabetes, chronic kidney diseases, chronic liver disease, malignancy, and tuberculosis, presenting with dyspnea and neurological symptoms. WHO ordinal scale 4 or above at admission carried the highest odds of dying [5.6 (95% CI: 4.6, 7.0)]. Patients receiving one [OR: 0.5 (95% CI: 0.4, 0.7)] or two doses of anti-SARS CoV-2 vaccine [OR: 0.4 (95% CI: 0.3, 0.7)] were protected from in-hospital mortality.\n\nConclusionsWHO ordinal scale at admission is the most important independent predictor for in-hospital death in COVID-19 patients. Anti-SARS-CoV2 vaccination provides significant protection against mortality.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Bridget Lockyer",
-        "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust"
+        "author_name": "Aparna Mukherjee",
+        "author_inst": "Indian Council of Medical Research"
       },
       {
-        "author_name": "Rachael H Moss",
-        "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust"
+        "author_name": "Gunjan Kumar",
+        "author_inst": "Indian Council of Medical Research"
       },
       {
-        "author_name": "Charlotte Endacott",
-        "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust"
+        "author_name": "Alka Turuk",
+        "author_inst": "Indian Council of Medical Research"
       },
       {
-        "author_name": "Shahid Islam",
-        "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals Foundation Trust"
+        "author_name": "Ashish Bhalla",
+        "author_inst": "PGIMER: Post Graduate Institute of Medical Education and Research"
       },
       {
-        "author_name": "Laura Sheard",
-        "author_inst": "Bradford Teaching Hospitals Foundation Trust"
+        "author_name": "Thrilok  Chander Bingi",
+        "author_inst": "Gandhi Medical College and Hospital"
       },
       {
-        "author_name": "- Bradford Institute for Health Research Covid-19 Scientific Advisory Group",
-        "author_inst": ""
+        "author_name": "Pankaj Bhardwaj",
+        "author_inst": "All India Institute of Medical Sciences - Jodhpur"
+      },
+      {
+        "author_name": "Tridip  Dutta Baruah",
+        "author_inst": "All India Institute of Medical Sciences - Raipur"
+      },
+      {
+        "author_name": "Subhasis Mukherjee",
+        "author_inst": "College of Medicine and Sagore Dutta Hospital"
+      },
+      {
+        "author_name": "Arunansu Talukdar",
+        "author_inst": "Medical College and Hospital Kolkata"
+      },
+      {
+        "author_name": "Yogiraj Ray",
+        "author_inst": "Infectious Disease And Beliaghata Hospital"
+      },
+      {
+        "author_name": "Mary John",
+        "author_inst": "Christian Medical College and Hospital Ludhiana"
+      },
+      {
+        "author_name": "Janakkumar  R Khambholja",
+        "author_inst": "Smt NHL Municipal Medical College"
+      },
+      {
+        "author_name": "Amit  H Patel",
+        "author_inst": "CIMS Hospital"
+      },
+      {
+        "author_name": "Sourin Bhuniya",
+        "author_inst": "All India Institute of Medical Sciences - Bhubaneswar"
+      },
+      {
+        "author_name": "Rajnish Joshi",
+        "author_inst": "All India Institute of Medical Science - Bhopal"
+      },
+      {
+        "author_name": "Geetha  R Menon",
+        "author_inst": "National Institute of Medical Statistics"
+      },
+      {
+        "author_name": "Damodar Sahu",
+        "author_inst": "National Institute of Medical Statistics"
+      },
+      {
+        "author_name": "Vishnu  Vardhan Rao",
+        "author_inst": "National Institute of Medical Statistics"
+      },
+      {
+        "author_name": "Balram Bhargava",
+        "author_inst": "Indian Council of Medical Research"
+      },
+      {
+        "author_name": "Samiran Panda",
+        "author_inst": "Indian Council of Medical Research"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.06.26.497669",
@@ -226545,49 +227611,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.06.23.497376",
-    "rel_title": "Monitoring SARS-CoV-2 infection using a double reporter-expressing virus",
+    "rel_doi": "10.1101/2022.06.23.497404",
+    "rel_title": "The Functional Landscape of SARS-CoV-2 3CL Protease",
     "rel_date": "2022-06-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.23.497376",
-    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the highly contagious agent responsible for the coronavirus disease 2019 (COVID-19) pandemic. An essential requirement for understanding SARS-CoV-2 fundamental biology and the impact of anti-viral therapeutics are robust methods to detect for the presence of the virus in infected cells or animal models. Despite the development and successful generation of recombinant (r)SARS-CoV-2 expressing fluorescent or luciferase reporter genes, knowledge acquired from their use in in vitro assays and/or in live animals are limited to the properties of the fluorescent or luciferase reporter genes. Herein, for the first time, we engineered a replication-competent rSARS-CoV-2 that expresses both fluorescent (mCherry) and luciferase (Nluc) reporter genes (rSARS-CoV-2/mCherry-Nluc) to overcome limitations associated with the use of a single reporter gene. In cultured cells, rSARS-CoV-2/mCherry-Nluc displayed similar viral fitness as rSARS-CoV-2 expressing single reporter fluorescent and luciferase genes (rSARS-CoV-2/mCherry and rSARS-CoV-2/Nluc, respectively), or wild-type (WT) rSARS-CoV-2, while maintaining comparable expression levels of both reporter genes. In vivo, rSARS-CoV-2/mCherry-Nluc has similar pathogenicity in K18 human angiotensin converting enzyme 2 (hACE2) transgenic mice than rSARS-CoV-2 expressing individual reporter genes, or WT rSARS-CoV-2. Importantly, rSARS-CoV-2/mCherry-Nluc facilitates the assessment of viral infection and transmission in golden Syrian hamsters using in vivo imaging systems (IVIS). Altogether, this study demonstrates the feasibility of using this novel bireporter-expressing rSARS-CoV-2 for the study SARS-CoV-2 in vitro and in vivo.\n\nIMPORTANCEDespite the availability of vaccines and antivirals, the coronavirus disease 2019 (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to ravage health care institutions worldwide. Previously, we have generated replication-competent recombinant (r)SARS-CoV-2 expressing fluorescent or luciferase reporter proteins to track viral infection in vitro and/or in vivo. However, these rSARS-CoV-2 are restricted to express only a single fluorescent or a luciferase reporter gene, limiting or preventing their use to specific in vitro assays and/or in vivo studies. To overcome this limitation, we have engineered a rSARS-CoV-2 expressing both fluorescent (mCherry) and luciferase (Nluc) genes and demonstrated its feasibility to study the biology of SARS-CoV-2 in vitro and/or in vivo, including the identification and characterization of neutralizing antibodies and/or antivirals. Using rodent models, we visualize SARS-CoV-2 infection and transmission through in vivo imaging systems (IVIS).",
-    "rel_num_authors": 9,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.23.497404",
+    "rel_abs": "SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) as the etiologic agent of COVID-19 (coronavirus disease 2019) has drastically altered life globally. Numerous efforts have been placed on the development of therapeutics to treat SARS-CoV-2 infection. One particular target is the 3CL protease (3CLpro), which holds promise as it is essential to the virus and highly conserved among coronaviruses, suggesting that it may be possible to find broad inhibitors that treat not just SARS-CoV-2 but other coronavirus infections as well. While the 3CL protease has been studied by many groups for SARS-CoV-2 and other coronaviruses, our understanding of its tolerance to mutations is limited, knowledge which is particularly important as 3CL protease inhibitors become utilized clinically. Here, we develop a yeast-based deep mutational scanning approach to systematically profile the activity of all possible single mutants of the SARS-CoV-2 3CLpro, and validate our results both in yeast and in authentic viruses. We reveal that the 3CLpro is highly malleable and is capable of tolerating mutations throughout the protein, including within the substrate binding pocket. Yet, we also identify specific residues that appear immutable for function of the protease, suggesting that these interactions may be novel targets for the design of future 3CLpro inhibitors. Finally, we utilize our screening results as a basis to identify E166V as a resistance-conferring mutation against the therapeutic 3CLpro inhibitor, nirmatrelvir, in clinical use. Collectively, the functional map presented herein may serve as a guide for further understanding of the biological properties of the 3CL protease and for drug development for current and future coronavirus pandemics.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Kevin Chiem",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Sho Iketani",
+        "author_inst": "Columbia University Irving Medical Center"
       },
       {
-        "author_name": "Jun-Gyu Park",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Seo Jung Hong",
+        "author_inst": "Columbia University Irving Medical Center"
       },
       {
-        "author_name": "Desarey Morales Vasquez",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Jenny Sheng",
+        "author_inst": "Columbia University Irving Medical Center"
       },
       {
-        "author_name": "Richard K. Plemper",
-        "author_inst": "Georgia State University"
+        "author_name": "Farideh Bahari",
+        "author_inst": "University of Tehran"
       },
       {
-        "author_name": "Jordi B Torrelles",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Bruce Culbertson",
+        "author_inst": "Columbia University Irving Medical Center"
       },
       {
-        "author_name": "James Kobie",
-        "author_inst": "University of Alabama at Birmingham"
+        "author_name": "Fereshteh Fallah Atanaki",
+        "author_inst": "University of Tehran"
       },
       {
-        "author_name": "Mark R Walter",
-        "author_inst": "University of Alabama at Birmingham"
+        "author_name": "Arjun K. Aditham",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Chengjin Ye",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Alexander F. Kratz",
+        "author_inst": "Columbia University Irving Medical Center"
       },
       {
-        "author_name": "Luis Martinez-Sobrido",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Maria I. Luck",
+        "author_inst": "Columbia University Irving Medical Center"
+      },
+      {
+        "author_name": "Ruxiao Tian",
+        "author_inst": "Columbia University Irving Medical Center"
+      },
+      {
+        "author_name": "Stephen P. Goff",
+        "author_inst": "Columbia University Irving Medical Center"
+      },
+      {
+        "author_name": "Hesam Montazeri",
+        "author_inst": "University of Tehran"
+      },
+      {
+        "author_name": "Yosef Sabo",
+        "author_inst": "Columbia University Irving Medical Center"
+      },
+      {
+        "author_name": "David D. Ho",
+        "author_inst": "Columbia University Irving Medical Center"
+      },
+      {
+        "author_name": "Alejandro Chavez",
+        "author_inst": "Columbia University Irving Medical Center"
       }
     ],
     "version": "1",
@@ -228295,41 +229385,145 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.06.21.22276724",
-    "rel_title": "COVID-19 rebound after Paxlovid and Molnupiravir during January-June 2022",
+    "rel_doi": "10.1101/2022.06.21.22276660",
+    "rel_title": "Evidence of recent Epstein-Barr virus reactivation in individuals experiencing Long COVID",
     "rel_date": "2022-06-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.21.22276724",
-    "rel_abs": "ImportanceRecent case reports document that some patients who were treated with Paxlovid experienced rebound COVID-19 infections and symptoms 2 to 8 days after completing a 5-day course of Paxlovid. The Centers for Disease Control and Prevention (CDC) has recently issued a Health Alert Network Health Advisory to update the public on the potential for COVID-19 rebound after Paxlovid treatments. However, the rates of COVID-19 rebound in a real-world population or whether rebound is unique to Paxlovid remains unknown.\n\nObjectivesTo examine the rates and relative risks of COVID-19 rebound in patients treated with Paxlovid or with Molnupiravir and to compare characteristics of patients who experienced COVID-19 rebound to those who did not.\n\nDesign, Setting, and ParticipantsRetrospective cohort study of electronic health records (EHRs) of 92 million patients from a multicenter and nationwide database in the US. The study population comprised 13,644 patients age [&ge;] 18 years who contracted COVID-19 between 1/1/2022-6/8/2022 and were treated with Paxlovid (n =11,270) or with Molnupiravir (n =2,374) within 5 days of their COVID-19 infection.\n\nExposuresPaxlovid or Molnupiravir.\n\nMain Outcomes and MeasuresThree types of COVID-19 rebound outcomes (COVID-19 infections, COVID-19 related symptoms, and hospitalizations) were examined. Hazard ratios and 95% confidence interval (CI) of 7-day and 30-day risk for COVID-19 rebound between patients treated with Paxlovid and patients treated with Molnupiravir were calculated before and after propensity-score matching.\n\nResultsThe 7-day and 30-day COVID-19 rebound rates after Paxlovid treatment were 3.53% and 5.40% for COVID-19 infection, 2.31% and 5.87% for COVID-19 symptoms, and 0.44% and 0.77% for hospitalizations. The 7-day and 30-day COVID-19 rebound rates after Molnupiravir treatment were 5.86% and 8.59% for COVID-19 infection, 3.75% and 8.21% for COVID-19 symptoms, and 0.84% and 1.39% for hospitalizations. After propensity-score matching, there were no significant differences in COVID-19 rebound risks between Paxlovid and Molnupiravir: infection (HR 0.90, 95% CI: 0.73-1.11), COVID-19 symptoms (HR: 1.03, 95% CI: 0.83-1.27), or hospitalizations (HR: 0.92, 95% CI: 0.56-1.55). Patients with COVID-19 rebound had significantly higher prevalence of underlying medical conditions than those without.\n\nConclusions and RelevanceCOVID-19 rebound occurred both after Paxlovid and Molnupiravir, especially in patients with underlying medical conditions. This indicates that COVID-19 rebound is not unique to Paxlovid and the risks were similar for Paxlovid and Molnupiravir. For both drugs the rates of COVID-19 rebound increased with time after treatments. Our results call for continuous surveillance of COVID-19 rebound after Paxlovid and Molnupiravir treatments. Studies are necessary to determine the mechanisms underlying COVID-19 rebounds and to test dosing and duration regimes that might prevent such rebounds in vulnerable patients.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.21.22276660",
+    "rel_abs": "The presence and reactivation of chronic viral infections such as Epstein-Barr virus (EBV), cytomegalovirus (CMV) and human immunodeficiency virus (HIV) have been proposed as potential contributors to Long COVID (LC), but studies in well-characterized post-acute cohorts of individuals with COVID-19 over a longer time course consistent with current case definitions of LC are limited. In a cohort of 280 adults with prior SARS-CoV-2 infection, we observed that LC symptoms such as fatigue and neurocognitive dysfunction at a median of 4 months following initial diagnosis were independently associated with serological evidence of recent EBV reactivation (early antigen-D [EA-D] IgG positivity) or high nuclear antigen IgG levels, but not with ongoing EBV viremia. Evidence of EBV reactivation (EA-D IgG) was most strongly associated with fatigue (OR 2.12). Underlying HIV infection was also independently associated with neurocognitive LC (OR 2.5). Interestingly, participants who had serologic evidence of prior CMV infection were less likely to develop neurocognitive LC (OR 0.52) and tended to have less severe (>5 symptoms reported) LC (OR 0.44). Overall, these findings suggest differential effects of chronic viral co-infections on the likelihood of developing LC and predicted distinct syndromic patterns. Further assessment during the acute phase of COVID-19 is warranted.\n\nSUMMARYThe authors found that Long COVID symptoms in a post-acute cohort were associated with serological evidence of recent EBV reactivation and pre-existing HIV infection when adjusted for participant factors, sample timing, comorbid conditions and prior hospitalization, whereas underlying CMV infection was associated with a decreased risk of Long COVID.",
+    "rel_num_authors": 32,
     "rel_authors": [
       {
-        "author_name": "Lindsey Wang",
-        "author_inst": "Case Western Reserve University"
+        "author_name": "Michael J Peluso",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Nathan A Berger",
-        "author_inst": "Case Western Reserve University"
+        "author_name": "Tyler-Marie Deveau",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Pamela B Davis",
-        "author_inst": "Case Western Reserve University"
+        "author_name": "Sadie E Munter",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "David C Kaelber",
-        "author_inst": "MetroHealth"
+        "author_name": "Dylan Ryder",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Nora Volkow",
-        "author_inst": "NIH/NIDA"
+        "author_name": "Amanda Buck",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Rong Xu",
-        "author_inst": "Case Western Reserve University"
+        "author_name": "Gabrielle Beck-Engeser",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Fay Chan",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Scott Lu",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Sarah A Goldberg",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Rebecca Hoh",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Viva Tai",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Leonel Torres",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Nikita S Iyer",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Monika Deswal",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Lynn H Ngo",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Melissa Buitrago",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Antonio Rodriguez",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jessica Y Chen",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Brandon C Yee",
+        "author_inst": "Monogram Biosciences"
+      },
+      {
+        "author_name": "Ahmed Chenna",
+        "author_inst": "Monogram Biosciences"
+      },
+      {
+        "author_name": "John W Winslow",
+        "author_inst": "Monogram Biosciences"
+      },
+      {
+        "author_name": "Christos J Petropoulos",
+        "author_inst": "Monogram Biosciences"
+      },
+      {
+        "author_name": "Amelia N Deitchman",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Joanna Hellmuth",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Matthew A Spinelli",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Matthew S Durstenfeld",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Priscilla Y Hsue",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "J Daniel Kelly",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jeffrey N Martin",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Steven G Deeks",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Peter W Hunt",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Timothy J Henrich",
+        "author_inst": "University of California, San Francisco"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -230141,115 +231335,63 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2022.06.20.22276596",
-    "rel_title": "Kinetics of neutralising antibodies against Omicron variant in Vietnamese healthcare workers after primary immunisation with ChAdOx1-S and booster with BNT162b2",
+    "rel_doi": "10.1101/2022.06.14.22276397",
+    "rel_title": "Association between Bisphosphonate use and COVID-19 related outcomes: a retrospective cohort study",
     "rel_date": "2022-06-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.20.22276596",
-    "rel_abs": "We studied the development and persistence of neutralising antibodies against SARS-CoV-2 ancestral strain, and Delta and Omicron (BA.1 and BA.2) variants in Vietnamese healthcare workers (HCWs) up to 15 weeks after booster vaccination. We included 47 HCWs with different pre-existing immune statuses (group 1 (G1): n=21, and group 2 (G2): n=26 without and with prior breakthrough Delta variant infection, respectively). The study participants had completed primary immunisation with ChAdOx1-S and booster vaccination with BNT162b2. Neutralising antibodies were measured using a surrogate virus neutralisation assay. Of the 21 study participants in G1, neutralising antibodies against ancestral strain, Delta variant, BA.1 and BA.2 were (almost) abolished at month 8 after the second dose, but all had detectable neutralising antibodies to the study viruses at week two post booster dose. Of the 26 study participants in G2, neutralising antibody levels to BA.1 and BA.2 were significantly higher than those to the corresponding viruses measured at week 2 post breakthrough infection and before the booster dose. At week 15 post booster vaccination, neutralising antibodies to BA.1 and BA.2 dropped significantly, with more profound changes observed in those without breakthrough Delta variant infection. Booster vaccination enhanced neutralising activities against ancestral strain and Delta variant, as compared to those induced by primary vaccination. These responses were maintained at high levels for at least 15 weeks. Our findings emphasise the importance of the first booster dose in producing cross-neutralising antibodies against Omicron variant. A second booster dose might be needed to maintain long-term protection against Omicron variant.",
-    "rel_num_authors": 24,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.14.22276397",
+    "rel_abs": "BackgroundAlthough there are several efficacious vaccines against COVID-19, vaccination rates in many regions around the world remain insufficient to prevent continued high disease burden and emergence of viral variants. Repurposing of existing therapeutics that prevent or mitigate severe COVID-19 could help to address these challenges. The objective of this study was to determine whether prior use of bisphosphonates is associated with reduced incidence and/or severity of COVID-19.\n\nMethodsA retrospective cohort study utilizing payer-complete health insurance claims data from 8,239,790 patients with continuous medical and prescription insurance from 1-1-2019 to 6-30-2020 was performed. The primary exposure of interest was use of any bisphosphonate from 1-1-2019 to 2-29-2020. Outcomes of interest included: (a) testing for SARS-CoV-2 infection; (b) COVID-19 diagnosis; and (c) hospitalization with COVID-19 diagnosis between 3-1-2020 and 6-30-2020.\n\nResults7,906,603 patients for whom continuous medical and prescription insurance information was available were selected. 450,366 bisphosphonate users were identified and 1:1 propensity score-matched to bisphosphonate non-users by age, gender, insurance type, primary-care-provider visit in 2019, and comorbidity burden. Bisphosphonate users had lower odds ratios (OR) of testing for SARS-CoV-2 infection (OR=0.22; 95%CI:0.21-0.23; p<0.001), COVID-19 diagnosis (OR=0.23; 95%CI:0.22-0.24; p<0.001), and COVID-19-related hospitalization (OR=0.26; 95%CI:0.24-0.29; p<0.001). Sensitivity analyses yielded results consistent with the primary analysis. Bisphosphonate-use was also associated with decreased odds of acute bronchitis (OR=0.23; 95%CI:0.22-0.23; p<0.001) or pneumonia (OR=0.32; 95%CI:0.31-0.34; p<0.001) in 2019, suggesting that bisphosphonates may protect against respiratory infections by a variety of pathogens, including but not limited to SARS-CoV-2.\n\nConclusionsPrior bisphosphonate-use was associated with dramatically reduced odds of SARS-CoV-2 testing, COVID-19 diagnosis, and COVID-19-related hospitalizations. Prospective clinical trials will be required to establish a causal role for bisphosphonate-use in COVID-19-related outcomes.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Nguyen Van Vinh Chau",
-        "author_inst": "Department of Health, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Lam Anh Nguyet",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Nguyen Thanh Dung",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Vo Minh Quang",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Nguyen Thanh Truong",
-        "author_inst": "Tan Phu Hospital, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Le Mau Toan",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Le Manh Hung",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Dinh Nguyen Huy Man",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Dao Bach Khoa",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Nguyen Thanh Phong",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Nghiem My Ngoc",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Huynh Phuong Thao",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Dinh Thi Bich Ty",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
-      },
-      {
-        "author_name": "Pham Ba Thanh",
-        "author_inst": "Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam"
+        "author_name": "Ulrich H von Andrian",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Nguyen Thi Han Ny",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Jeffrey Thompson",
+        "author_inst": "Cerner Enviza"
       },
       {
-        "author_name": "Le Kim Thanh",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Yidi Wang",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Cao Thu Thuy",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Tobias Dreischulte",
+        "author_inst": "Ludwig-Maximilians-University"
       },
       {
-        "author_name": "Nguyen To Anh",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Olga Barreiro",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Nguyen Thi Thu Hong",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Rodrigo J Gonzalez",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Le Nguyen Truc Nhu",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Colette Matysiak",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Lam Minh Yen",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Harold R Neely",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Guy Thwaites",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Marietta Rottenkolber",
+        "author_inst": "Ludwig-Maximilians-University"
       },
       {
-        "author_name": "Tran Tan Thanh",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam"
+        "author_name": "Thmoas Haskell",
+        "author_inst": "Cerner Enviza"
       },
       {
-        "author_name": "Le Van Tan",
-        "author_inst": "OUCRU-VN"
+        "author_name": "Stefan Endres",
+        "author_inst": "Ludwig-Maximilians-University"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.06.20.22276641",
@@ -232135,107 +233277,75 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.06.16.22276392",
-    "rel_title": "COVID-19 redux: clinical, virologic, and immunologic evaluation of clinical rebound after nirmatrelvir/ritonavir",
+    "rel_doi": "10.1101/2022.06.17.22276478",
+    "rel_title": "The prevalence, incidence and longevity of antibodies against SARS-CoV-2 among primary healthcare providers in Belgium: a prospective cohort study with 12 months of follow-up",
     "rel_date": "2022-06-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.16.22276392",
-    "rel_abs": "Clinical rebound of COVID-19 after nirmatrelvir/ritonavir treatment has been reported. We performed clinical, virologic, and immune measurements in seven patients with symptomatic rebound, six after nirmatrelvir/ritonavir treatment and one without previous treatment. There was no evidence of severe disease or impaired antibody and T-cell responses in people with rebound symptoms.",
-    "rel_num_authors": 22,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.17.22276478",
+    "rel_abs": "ObjectivesTo estimate the prevalence, incidence, and longevity of antibodies against SARS-CoV-2 among primary healthcare providers (PHCPs).\n\nDesignProspective cohort study with 12 months of follow-up.\n\nSettingPrimary care in Belgium\n\nParticipantsAny general practitioner (GP) working in primary care in Belgium and any other PHCP from the same GP practice who physically manages (examines, tests, treats) patients were eligible. A convenience sample of 3,648 eligible PHCPs from 2,001 GP practices registered for this study (3,044 and 604 to start in December 2020 and January 2021, respectively). 3,390 PHCPs (92,9%) participated in their first testing timepoint (2,820 and 565, respectively) and 2,557 PHCPs (70,1%) in the last testing timepoint (December 2021).\n\nInterventionsParticipants were asked to perform a rapid serological test (RST) targeting IgM and IgG against the receptor binding domain (RBD) of SARS-CoV-2 and to complete an online questionnaire at each of maximum 8 testing timepoints.\n\nPrimary and secondary outcome measuresThe prevalence, incidence, and longevity of antibodies against SARS-CoV-2 both after natural infection and after vaccination.\n\nResultsAmong all participants, 67% were women and 77% GPs. Median age was 43 years. The seroprevalence in December 2020 (before vaccination availability) was 15.1% (95% CI: 13.5% to 16.6%), increased to 84.2% (95% CI: 82.9% to 85.5%) in March 2021 (after vaccination availability) and reached 93.9% (95% CI: 92.9% to 94.9%) in December 2021 (during booster vaccination availability and fourth (delta variant dominant) covid wave). Among not (yet) vaccinated participants the first monthly incidence of antibodies against SARS-CoV-2 was estimated to be 2.91% (95% CI: 1.80% to 4.01%). The longevity of antibodies is higher in PHCPs with self-reported COVID-19 infection.\n\nConclusionsThis study confirms that occupational health measures provided sufficient protection when managing patients. High uptake of vaccination resulted in high seroprevalence of SARS-CoV-2 antibodies in PHCPs in Belgium. Longevity of antibodies was supported by booster vaccination and virus circulation.\n\nRegistrationTrial registration number: NCT04779424\n\nStrengths and limitations of this studyO_LIThis large cohort study with 12 months follow-up could provide precise estimates of the prevalence and incidence of antibodies against SARS-CoV-2 among primary health care providers (PHCPs) at national and regional level in Belgium.\nC_LIO_LIThe rapid serological test (RST) used targets IgM and IgG against the receptor binding domain of SARS-CoV-2 and could therefore also assess the antibody response after vaccination, and longevity of antibodies against SARS-CoV-2 both after natural infection and after vaccination, but cannot distinguish between both.\nC_LIO_LIThe results in PHCPs could be compared to that of the general population and other population groups, e.g. health care workers in hospitals and nursing homes.\nC_LIO_LIThe use of a convenience sample, missing data points and reduced RST accuracy when performed and interpreted by many different participants could limit the validity of the study results.\nC_LI",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Brian P Epling",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
-      },
-      {
-        "author_name": "Joseph M Rocco",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
-      },
-      {
-        "author_name": "Kristin L Boswell",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
-      },
-      {
-        "author_name": "Elizabeth Laidlaw",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
-      },
-      {
-        "author_name": "Frances Galindo",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
-      },
-      {
-        "author_name": "Anela Kellogg",
-        "author_inst": "Leidos Biomedical Research"
-      },
-      {
-        "author_name": "Sanchita Das",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Allison Roder",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
-      },
-      {
-        "author_name": "Elodie Ghedin",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Niels Adriaenssens",
+        "author_inst": "University of Antwerp"
       },
       {
-        "author_name": "Allie Kreitman",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Beatrice Scholtes",
+        "author_inst": "University of Liege"
       },
       {
-        "author_name": "Robin L Dewar",
-        "author_inst": "Frederick National Laboratory"
+        "author_name": "Robin Bruyndonckx",
+        "author_inst": "University of Antwerp"
       },
       {
-        "author_name": "Sophie E. M. Kelly",
-        "author_inst": "National Institute of Biomedical Imaging and Bioengineering"
+        "author_name": "Pauline Van Ngoc",
+        "author_inst": "University of Liege"
       },
       {
-        "author_name": "Heather Kalish",
-        "author_inst": "National Institute of Biomedical Imaging and Bioengineering"
+        "author_name": "Jan Y Verbakel",
+        "author_inst": "KU Leuven"
       },
       {
-        "author_name": "Tauseef Rehman",
-        "author_inst": "Frederick National Laboratory"
+        "author_name": "An De Sutter",
+        "author_inst": "Ghent University"
       },
       {
-        "author_name": "Jeroen Highbarger",
-        "author_inst": "Frederick National Laboratory"
+        "author_name": "Stefan Heytens",
+        "author_inst": "Ghent University"
       },
       {
-        "author_name": "Adam Rupert",
-        "author_inst": "Frederick National Laboratory"
+        "author_name": "Ann Van den Bruel",
+        "author_inst": "KU Leuven"
       },
       {
-        "author_name": "Gregory Kocher",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Isabelle Desombere",
+        "author_inst": "Sciensano"
       },
       {
-        "author_name": "Michael R Holbrook",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Pierre Van Damme",
+        "author_inst": "University of Antwerp"
       },
       {
-        "author_name": "Andrea Lisco",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Herman Goossens",
+        "author_inst": "University of Antwerp"
       },
       {
-        "author_name": "Maura Manion",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Laetitia Buret",
+        "author_inst": "University of Liege"
       },
       {
-        "author_name": "Richard A Koup",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Els Duysburgh",
+        "author_inst": "Sciensano"
       },
       {
-        "author_name": "Irini Sereti",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Samuel Coenen",
+        "author_inst": "University of Antwerp"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "primary care research"
   },
   {
     "rel_doi": "10.1101/2022.06.16.22276503",
@@ -232369,7 +233479,7 @@
     "rel_date": "2022-06-17",
     "rel_site": "bioRxiv",
     "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.17.496544",
-    "rel_abs": "Phylodynamic analyses can generate important and timely data to optimise public health response to SARS-CoV-2 outbreaks and epidemics. However, their implementation is hampered by the massive amount of sequence data and the difficulty to parameterise dedicated software packages. We introduce the COVFlow pipeline, accessible at https://gitlab.in2p3.fr/ete/CoV-flow, which allows a user to select sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID) database according to user-specified criteria, to perform basic phylogenetic analyses, and to produce an XML file to be run in the Beast2 software package. We illustrate the potential of this tool by studying two sets of sequences from the Delta variant in two French regions. This pipeline can facilitate the use of virus sequence data at the local level, for instance, to track the dynamics of a particular lineage or variant in a region of interest.",
+    "rel_abs": "Phylodynamic analyses generate important and timely data to optimise public health response to SARS-CoV-2 outbreaks and epidemics. However, their implementation is hampered by the massive amount of sequence data and the difficulty to parameterise dedicated software packages. We introduce the COVFlow pipeline, accessible at https://gitlab.in2p3.fr/ete/CoV-flow, which allows a user to select sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID) database according to user-specified criteria, to perform basic phylogenetic analyses, and to produce an XML file to be run in the Beast2 software package. We illustrate the potential of this tool by studying two sets of sequences from the Delta variant in two French regions. This pipeline can facilitate the use of virus sequence data at the local level, for instance, to track the dynamics of a particular lineage or variant in a region of interest.",
     "rel_num_authors": 8,
     "rel_authors": [
       {
@@ -233997,61 +235107,33 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2022.06.13.22276339",
-    "rel_title": "Effects of hydrometeorological and other factors on SARS-CoV-2 reproduction number in three contiguous countries of Tropical Andean South America: a spatiotemporally disaggregated time series analysis.",
+    "rel_doi": "10.1101/2022.06.15.22276436",
+    "rel_title": "Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron",
     "rel_date": "2022-06-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.13.22276339",
-    "rel_abs": "BackgroundThe COVID-19 pandemic has caused societal disruption globally and South America has been hit harder than other lower-income regions. This study modeled effects of 6 weather variables on district-level SARS-CoV-2 reproduction numbers (Rt) in three contiguous countries of Tropical Andean South America (Colombia, Ecuador, and Peru), adjusting for environmental, policy, healthcare infrastructural and other factors.\n\nMethodsDaily time-series data on SARS-CoV-2 infections were sourced from health authorities of the three countries at the smallest available administrative level. Rt values were calculated and merged by date and unit ID with variables from a Unified COVID-19 dataset and other publicly available sources for May - December 2020. Generalized additive mixed effects models were fitted.\n\nFindingsRelative humidity and solar radiation were inversely associated with SARS-CoV-2 Rt. Days with radiation above 1,000 KJ/m2 saw a 1.3%, and those with humidity above 50%, a 1.0% reduction in Rt. Transmission was highest in densely populated districts, and lowest in districts with poor healthcare access and on days with least population mobility. Temperature, region, aggregate government policy response and population age structure had little impact. The fully adjusted model explained 3.9% of Rt variance.\n\nInterpretationDry atmospheric conditions of low humidity increase, and higher solar radiation decrease district-level SARS-CoV-2 reproduction numbers, effects that are comparable in magnitude to population factors like lockdown compliance. Weather monitoring could be incorporated into disease surveillance and early warning systems in conjunction with more established risk indicators and surveillance measures.\n\nFundingNASAs Group on Earth Observations Work Programme (16-GEO16-0047).",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.15.22276436",
+    "rel_abs": "New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness both over time and space. In this paper we extend a previously published model for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to globally estimate selection effects at different spatial levels while controlling for complex patterns of transmission and jointly inferring the effects of unit-level covariates in the spatial heterogeneity of SARS-CoV-2 selection effects. Applying this model to the spread of Omicron in 40 counties finding evidence for very strong (64%) but very heterogeneous selection effects at the country level. We further considered different measures of vaccination levels and measures of recent population-level infection as possible explanations. However, none of those variables were found to explain a significant proportion of the heterogeneity in country-level selection effects. We did find a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard commercial-grade computing resources, and should be straightforward to apply to future variants.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Josh M Colston",
-        "author_inst": "University of Virginia School of Medicine"
-      },
-      {
-        "author_name": "Patrick Hinson",
-        "author_inst": "University of Virginia"
-      },
-      {
-        "author_name": "Nhat-Lan H Nguyen",
-        "author_inst": "University of Virginia"
-      },
-      {
-        "author_name": "Yen Ting Chen",
-        "author_inst": "Chi-Mei Medical Center"
-      },
-      {
-        "author_name": "Hamada S. Badr",
-        "author_inst": "Johns Hopkins University"
-      },
-      {
-        "author_name": "Gaige H Kerr",
-        "author_inst": "George Washington University"
-      },
-      {
-        "author_name": "Lauren Marie Gardner",
-        "author_inst": "Johns Hopkins University"
-      },
-      {
-        "author_name": "David N Martin",
-        "author_inst": "University of Virginia School of Medicine"
+        "author_name": "Christiaan H van Dorp",
+        "author_inst": "Columbia University Irving Medical Center"
       },
       {
-        "author_name": "Antonio M Quispe",
-        "author_inst": "Universidad Continental"
+        "author_name": "Emma E Goldberg",
+        "author_inst": "Los Alamos National Laboratory"
       },
       {
-        "author_name": "Francesca Schiaffino",
-        "author_inst": "Universidad Peruana Cayetano Heredia"
+        "author_name": "Nick Hengartner",
+        "author_inst": "Los Alamos National Laboratory"
       },
       {
-        "author_name": "Margaret N Kosek",
-        "author_inst": "University of Virginia"
+        "author_name": "Ruian Ke",
+        "author_inst": "Los Alamos National Laboratory"
       },
       {
-        "author_name": "Benjamin F Zaitchik",
-        "author_inst": "Johns Hopkins University"
+        "author_name": "Ethan O Romero-Severson",
+        "author_inst": "Los Alamos National Laboratory"
       }
     ],
     "version": "1",
@@ -236219,77 +237301,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.06.09.22276030",
-    "rel_title": "Immunogenicity and safety of coadministration of COVID-19 and influenza vaccination among healthcare workers",
+    "rel_doi": "10.1101/2022.06.09.22276150",
+    "rel_title": "Antigen test swabs are comparable to nasopharyngeal swabs for sequencing of SARS-CoV-2",
     "rel_date": "2022-06-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.09.22276030",
-    "rel_abs": "BackgroundA third dose of COVID-19 vaccination ( COVID booster vaccination) has become established as an important measure to strengthen the immune response against SARS-CoV-2. In contrast, seasonal influenza vaccination has been an important infection prevention measure for years, especially among highly exposed healthcare workers (HCWs). Coadministration of vaccines against COVID-19 and seasonal influenza could be an efficient strategy to protect HCWs from two major viral respiratory infections. Yet, the immunogenicity and safety of coadministration remains to be evaluated.\n\nMethodsThis study examines the differences in Anti-SARS-CoV-2-Spike IgG antibody formation as well as side effects based on a digital questionnaire after a third COVID-19 vaccination with or without coadministration of a seasonal quadrivalent influenza vaccine (Influvac Tetra vaccine 2021/2022). 1,231 HCWs were recruited who received a mRNA-based booster COVID-19 vaccination (mRNA-1273 or BNT162b2mRNA) after basic immunisation with BNT162b2mRNA twice. Anti-SARS-CoV-2-Spike IgG levels were determined at least 14 days after vaccination by SERION ELISA agile SARS-CoV-2 IgG.\n\nFindingsAnti-SARS-CoV-2-Spike IgG concentrations were by 25{middle dot}4% lower in individuals with coadministration of the seasonal quadrivalent influenza vaccination than without (p<0{middle dot}01). There was no statistically significant difference in the reported side effects. The concentration of Anti-SARS-CoV-2-Spike IgG was higher in HCWs who had received the influenza vaccine concomitantly with mRNA-1273 than with BNT162b2mRNA as third COVID-19 vaccine (p<0{middle dot}0001).\n\nInterpretationCoadministration of the seasonal quadrivalent influenza vaccine significantly limits the levels in Anti-SARS-CoV-2-Spike IgG levels, with a more restricted elevation in case of a BNT162b2mRNA booster vaccination compared with mRNA-1273 vaccine. The reduced humoral immune response in case of coadministration needs to be considered in seasonal vaccination recommendations, although the consequences of lower Anti-SARS-CoV-2-Spike IgG levels for the protection against SARS-CoV-2 infection and severe COVID-19 disease course are currently unknown. An augmented mRNA-based COVID-19 vaccine dosage may compensate for the restricted immunogenicity in case of coadministration.\n\nFundingThis study was funded by the Federal Ministry for Education and Science (BMBF) through a grant provided to the University Hospital of Wuerzburg by the Network University Medicine on COVID-19 (B-FAST, grant-No 01KX2021) as well as by the Free State of Bavaria with COVID-research funds provided to the University of Wuerzburg, Germany. Nils Petri is supported by the German Research Foundation (DFG) funded scholarship UNION CVD.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSFor evaluation of the previously published evidence, PubMed and medRxiv were searched for the terms \"influenza vaccination\", \"influenza vaccine\", \"influenza\", \"flu\", \"seasonality\", combined with \"coadministration\", \"concomitant\", \"COVID-19 vaccination\", \"COVID-19 vaccine\", \"SARS-CoV-2\", in title or abstract, published between 1st of January 2020 and 18th of May 2022.\n\nTo date, it is unclear if coadministration of COVID-19 and influenza vaccine is effective and safe, particularly in the cohort of healthcare workers (HCWs) as key public health stakeholders. For the subunit COVID-19 vaccine NVX-CoV2373, an impairment of Anti-SARS-CoV-2-Spike IgG levels has been shown in individuals coadministered with a seasonal influenza vaccine. The two previously published studies on coadministration of a mRNA-based COVID-19 and a seasonal quadrivalent influenza vaccine have reported a restriction of humoral Anti-SARS-CoV-2-Spike immune response in the coadministration group. These examinations were conducted with limited correspondence to real-life conditions and in smaller cohorts. Additionally, these former studies do not consider the important aspect of side effects as a possible direct effect of the prevention measure on the availability of public health care in combination with Anti-SARS-CoV-2-Spike IgG levels. In summary, the humoral immunogenicity and side effects of a coadministered third COVID-19 and a seasonal influenza vaccine are still unclear and the limited available data is not transferable to the general public.\n\nAdded value of this studyWe performed the first large-scale real-life evaluation of humoral immunogenicity and side effects of COVID-19 and influenza vaccine coadministration in HCWs. Anti-SARS-CoV-2-Spike IgG levels were significantly lower in the coadministered cohort compared to the not coadministered control group, stratified by third COVID-19 vaccine (BNT162b2mRNA or mRNA-1273). Anti-SARS-CoV-2-Spike IgG post-vaccine elevation was lower among BNT162b2mRNA vaccinated HCWs than in those vaccinated with mRNA-1273 as a third COVID-19 vaccination. The influence of the seasonal quadrivalent influenza vaccine is evaluated in a cohort including 1,231 HCWs in total, covering a broad age range. Coadministration did not lead to an increase in side effects, which is a central requirement for considering the option of coadministration, given the role of HCWs as key personnel in maintaining health care capacities.\n\nImplications of all the available evidenceOur data suggest, that coadministration of third mRNA-based COVID-19 and quadrivalent seasonal influenza vaccine is safe and immunogenic, although it leads to a slightly reduced Anti-SARS-CoV-2-Spike antibody formation. While the clinical impact of the observed reduction in humoral Anti-SARS-CoV-2-Spike immune response for protection against SARS-CoV-2 infection and severe COVID-19 disease is still unclear, influenza vaccination remains an important infection prevention measure, especially among highly exposed HCWs. The coadministration does not increase side effects but may improve vaccination rate. A higher-dosed mRNA-based COVID-19 vaccine may compensate for the restricted immunogenicity in case of seasonal influenza vaccine coadministration. Our results will support the development of public health recommendations for coadministration of COVID-19 and influence vaccines in anticipation of the imminent infection waves in the coming winter season.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.09.22276150",
+    "rel_abs": "Viral genomic surveillance has been integral in the global response to the SARS-CoV-2 pandemic. Surveillance efforts rely on the availability of representative clinical specimens from ongoing testing activities. However, testing practices have recently shifted due to the widespread availability and use of rapid antigen tests, which could lead to gaps in future monitoring efforts. As such, genomic surveillance strategies must adapt to include laboratory workflows that are robust to sample type. To that end, we compare the results of RT-qPCR and viral genome sequencing using samples from positive BinaxNOW COVID-19 Antigen Card swabs (N=555) to those obtained from previously collected nasopharyngeal (NP) swabs used for nucleic acid amplification testing (N=135). We show that swabs obtained from antigen cards are comparable in performance to clinical excess samples from NP swabs, providing a viable alternative. This validation permits the reliable expansion of viral genomic surveillance to cases identified in the clinic or home setting where rapid antigen tests are used.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Isabell Wagenh\u00e4user",
-        "author_inst": "Infection Control and Antimicrobial Stewardship Unit, Department of Internal Medicine I, University Hospital Wuerzburg, Wuerzburg, Germany"
-      },
-      {
-        "author_name": "Julia Reusch",
-        "author_inst": "Infection Control and Antimicrobial Stewardship Unit, Department of Internal Medicine I, University Hospital Wuerzburg, Wuerzburg, Germany"
-      },
-      {
-        "author_name": "Alexander Gabel",
-        "author_inst": "Infection Control and Antimicrobial Stewardship Unit, University Hospital Wuerzburg, Wuerzburg, Germany"
-      },
-      {
-        "author_name": "Anna H\u00f6hn",
-        "author_inst": "Infection Control and Antimicrobial Stewardship Unit, University Hospital Wuerzburg, Wuerzburg, Germany"
-      },
-      {
-        "author_name": "Thi\u00ean-Tr\u00ed L\u00e2m",
-        "author_inst": "Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg, Germany"
-      },
-      {
-        "author_name": "Giovanni Almanzar",
-        "author_inst": "Paediatric Rheumatology/Special Immunology, Department of Paediatrics, University Hospital Wuerzburg, Wuerzburg, Germany"
-      },
-      {
-        "author_name": "Martina Prelog",
-        "author_inst": "Paediatric Rheumatology/Special Immunology, Department of Paediatrics, University Hospital Wuerzburg, Wuerzburg, Germany"
-      },
-      {
-        "author_name": "Lukas B. Krone",
-        "author_inst": "Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK; University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern,"
-      },
-      {
-        "author_name": "Anna Frey",
-        "author_inst": "Department of Internal Medicine I, University Hospital Wuerzburg, Wuerzburg, Germany"
+        "author_name": "Sayf Al-Deen Hassouneh",
+        "author_inst": "University of Central Florida, Orlando, FL"
       },
       {
-        "author_name": "Alexandra Schubert-Unkmeir",
-        "author_inst": "Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg, Germany"
+        "author_name": "Alexa Trujillo",
+        "author_inst": "University of Central Florida, Orlando, FL"
       },
       {
-        "author_name": "Lars D\u00f6lken",
-        "author_inst": "Institute for Virology and Immunobiology, University of Wuerzburg, Wuerzburg, Germany"
+        "author_name": "Sobur Ali",
+        "author_inst": "University of Central Florida, Orlando, FL"
       },
       {
-        "author_name": "Stefan Frantz",
-        "author_inst": "Department of Internal Medicine I, University Hospital Wuerzburg, Wuerzburg, Germany"
+        "author_name": "Eleonora Cella",
+        "author_inst": "University of Central Florida, Orlando, FL"
       },
       {
-        "author_name": "Oliver Kurzai",
-        "author_inst": "Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg; Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knoell-I"
+        "author_name": "Catherine G Johnston",
+        "author_inst": "University of Central Florida, Orlando, FL"
       },
       {
-        "author_name": "Ulrich Vogel",
-        "author_inst": "Infection Control and Antimicrobial Stewardship Unit, University Hospital Wuerzburg; Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg,"
+        "author_name": "Katherine C DeRuff",
+        "author_inst": "2Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA"
       },
       {
-        "author_name": "Nils Petri",
-        "author_inst": "Department of Internal Medicine I, University Hospital Wuerzburg, Wuerzburg, Germany"
+        "author_name": "Pardis C Sabeti",
+        "author_inst": "Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA"
       },
       {
-        "author_name": "Manuel Krone",
-        "author_inst": "Infection Control and Antimicrobial Stewardship Unit, University Hospital Wuerzburg; Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg,"
+        "author_name": "Taj Azarian",
+        "author_inst": "University of Central Florida, Orlando, FL"
       }
     ],
     "version": "1",
@@ -238157,107 +239207,39 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2022.06.12.495779",
-    "rel_title": "An attenuated vaccinia vaccine encoding the SARS-CoV-2 spike protein elicits broad and durable immune responses, and protects cynomolgus macaques and human ACE2 transgenic mice from SARS-CoV-2 and its variants",
+    "rel_doi": "10.1101/2022.06.13.495912",
+    "rel_title": "Accurate and Fast Clade Assignment via Deep Learning and Frequency Chaos Game Representation",
     "rel_date": "2022-06-13",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.12.495779",
-    "rel_abs": "As long as the coronavirus disease 2019 (COVID-19) pandemic continues, new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with altered antigenicity will emerge. The development of vaccines that elicit robust, broad, and durable protection against SARS-CoV-2 variants is urgently needed. We have developed a vaccine (rDIs-S) consisting of the attenuated vaccinia virus DIs strain platform carrying the SARS-CoV-2 S gene. rDIs-S induced neutralizing antibody and T-lymphocyte responses in cynomolgus macaques and human angiotensin converting enzyme 2 (hACE2) transgenic mice, and showed broad protection against SARS-CoV-2 isolates ranging from the early-pandemic strain (WK-521) to the recent Omicron BA. 1 variant (TY38-839). Using a tandem mass tag (TMT) -based quantitative proteomic analysis of lung homogenates from hACE2 transgenic mice, we found that, among mice subjected to challenge infection with WK-521, vaccination with rDIs-S prevented protein expression related to the severe pathogenic effects of SARS-CoV-2 infection (tissue destruction, inflammation, coagulation, fibrosis, and angiogenesis) and restored protein expression related to immune responses (antigen presentation and cellular response to stress). Furthermore, long-term studies in mice showed that rDIs-S maintains S protein-specific antibody titers for at least 6 months after a 1st vaccination. Thus, rDIs-S appears to provide broad and durable protective immunity against SARS-CoV-2, including current and possibly future variants.",
-    "rel_num_authors": 22,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.13.495912",
+    "rel_abs": "BackgroundSince the beginning of the COVID-19 pandemic there has been an explosion of sequencing of the SARS-CoV-2 virus, making it the most widely sequenced virus in the history. Several databases and tools have been created to keep track of genome sequences and variants of the virus, most notably the GISAID platform hosts millions of complete genome sequences, and it is continuously expanding every day. A challenging task is the development of fast and accurate tools that are able to distinguish between the different SARS-CoV-2 variants and assign them to a clade.\n\nResultsIn this paper, we leverage the Frequency Chaos Game Representation (FCGR) and Convolutional Neural Networks (CNNs) to develop an original method that learns how to classify genome sequences that we implement into CouGaR-g, a tool for the clade assignment problem on SARS-CoV-2 sequences. On a testing subset of the GISAID, CouGaR-g achieves an 96.29% overall accuracy, while a similar tool, Covidex, obtained a 77, 12% overall accuracy. As far as we know, our method is the first using Deep Learning and FCGR for intra-species classification. Furthermore, by using some feature importance methods CouGaR-g allows to identify k-mers that matches SARS-CoV-2 marker variants.\n\nConclusionsBy combining FCGR and CNNs, we develop a method that achieves a better accuracy than Covidex (which is based on Random Forest) for clade assignment of SARS-CoV-2 genome sequences, also thanks to our training on a much larger dataset, with comparable running times. Our method implemented in CouGaR-g is able to detect k-mers that capture relevant biological information that distinguishes the clades, known as marker variants.\n\nAvailabilityThe trained models can be tested online providing a FASTA file (with one or multiple sequences) at https://huggingface.co/spaces/BIASLab/sars-cov-2-classification-fcgr. CouGaR-g is also available at https://github.com/AlgoLab/CouGaR-g under the GPL.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Hirohito Ishigaki",
-        "author_inst": "Division of Pathogenesis and Disease Regulation, Department of Pathology, Shiga University of Medical Science"
-      },
-      {
-        "author_name": "Fumihiko Yasui",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Misako Nakayama",
-        "author_inst": "Division of Pathogenesis and Disease Regulation, Department of Pathology, Shiga University of Medical Science"
-      },
-      {
-        "author_name": "Akinori Endo",
-        "author_inst": "Protein Metabolism Project, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Naoki Yamamoto",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Kenzaburo Yamaji",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Cong Thanh Nguyen",
-        "author_inst": "Division of Pathogenesis and Disease Regulation, Department of Pathology, Shiga University of Medical Science"
-      },
-      {
-        "author_name": "Yoshinori Kitagawa",
-        "author_inst": "Division of Microbiology and Infectious Diseases, Department of Pathology, Shiga University of Medical Science"
-      },
-      {
-        "author_name": "Takahiro Sanada",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Tomoko Honda",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
+        "author_name": "Jorge Avila Cartes",
+        "author_inst": "Department of Computer Science, Systems and Communications. University of Milano--Bicocca, Italy"
       },
       {
-        "author_name": "Tsubasa Munakata",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Masahiko Higa",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Sakiko Toyama",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Risa Kono",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Asako Takagi",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Yusuke Matsumoto",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
-      },
-      {
-        "author_name": "Kaori Hayashi",
-        "author_inst": "Division of Pathogenesis and Disease Regulation, Department of Pathology, Shiga University of Medical Science"
-      },
-      {
-        "author_name": "Masanori Shiohara",
-        "author_inst": "Division of Pathogenesis and Disease Regulation, Department of Pathology, Shiga University of Medical Science"
+        "author_name": "Santosh Anand",
+        "author_inst": "Department of Computer Science, Systems and Communications. University of Milano--Bicocca, Italy"
       },
       {
-        "author_name": "Koji Ishii",
-        "author_inst": "Department of Quality Assurance and Radiological Protection, National Institute of Infectious Diseases"
+        "author_name": "Simone Ciccolella",
+        "author_inst": "Department of Computer Science, Systems and Communications. University of Milano--Bicocca, Italy"
       },
       {
-        "author_name": "Yasushi Saeki",
-        "author_inst": "Protein Metabolism Project, Tokyo Metropolitan Institute of Medical Science"
+        "author_name": "Paola Bonizzoni",
+        "author_inst": "Department of Computer Science, Systems and Communications. University of Milano--Bicocca, Italy"
       },
       {
-        "author_name": "Yasushi Itoh",
-        "author_inst": "Division of Pathogenesis and Disease Regulation, Department of Pathology, Shiga University of Medical Science"
-      },
-      {
-        "author_name": "Michinori Kohara",
-        "author_inst": "Department of Microbiology and Cell Biology, Tokyo Metropolitan Institute of Medical Science"
+        "author_name": "Gianluca Della Vedova",
+        "author_inst": "Department of Computer Science, Systems and Communications. University of Milano--Bicocca, Italy"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "microbiology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2022.06.12.495856",
@@ -239803,27 +240785,115 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2022.06.07.495170",
-    "rel_title": "Single-cell Multi-omics Integration for Unpaired Data by a Siamese Network with Graph-based Contrastive Loss",
+    "rel_doi": "10.1101/2022.06.07.495149",
+    "rel_title": "SARS-CoV-2 spike protein induces long-term TLR4-mediated synapse and cognitive loss recapitulating Post-COVID syndrome",
     "rel_date": "2022-06-08",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.07.495170",
-    "rel_abs": "Single-cell omics technology is being rapidly developed to measure the epigenome, genome, and transcriptome across a range of cell types. However, integrating omics data from different modalities is still challenging. Here, we propose a variation of the Siamese neural network framework called MinNet, which is trained to integrate multi-omics data on the single-cell resolution by utilizing graph-based contrastive loss. By training the model and testing it on several benchmark datasets, we showed its accuracy and generalizability in integrating scRNA-seq with scATAC-seq, and scRNA-seq with epitopes data. Further evaluation demonstrated our models unique capacity in removing the batch effect, which is a common problem in actual practice. To show how the integration impacts downstream analysis, we established model-based smoothing and cis-regulatory element inferring method and validated it with external pcHi-C evidence. Finally, the framework was applied to a COVID-19 dataset to compensate the original work with integration-based analysis, showing its necessity in single-cell multi-omics research.",
-    "rel_num_authors": 2,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.07.495149",
+    "rel_abs": "Cognitive dysfunction is often reported in post-COVID patients, but its underlying mechanisms remain unknown. While some evidence indicate that SARS-CoV-2 can reach and directly impact the brain, others suggest viral neuroinvasion as a rare event. Independently of brain viral infection, the ability of SARS-CoV-2 spike (S) protein to cross the BBB and reach memory-related brain regions has already been shown. Here, we demonstrate that brain infusion of S protein in mice induces late cognitive impairment and increases serum levels of neurofilament light chain (NFL), which recapitulates post-COVID features. Neuroinflammation, hippocampal microgliosis and synapse loss are induced by S protein. Increased engulfment of hippocampal presynaptic terminals late after S protein brain infusion were found to temporally correlate with cognitive deficit in mice. Blockage of TLR4 signaling prevented S-associated detrimental effects on synapse and memory loss. In a cohort of 86 patients recovered from mild COVID-19, genotype GG TLR4 -2604G>A (rs10759931) was associated with poor cognitive outcome. Collectively, these findings indicate that S protein directly impacts the brain and suggest that TLR4 is a potential target to prevent post-COVID cognitive dysfunction.\n\nOne Sentence SummaryTLR4 mediates long-term cognitive impairment in mice and its genetic variant increases the risk of poor cognitive outcome in post-COVID patients.",
+    "rel_num_authors": 24,
     "rel_authors": [
       {
-        "author_name": "Chaozhong Liu",
-        "author_inst": "Baylor College of Medicine"
+        "author_name": "Fabricia Lima Fontes-Dantas",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil; Department of Pharmacology, Institute of Biology, Rio de Janeiro State Uni"
       },
       {
-        "author_name": "Linhua Wang",
-        "author_inst": "Baylor College of Medicine"
+        "author_name": "Gabriel G Fernandes",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Elisa G. Gutman",
+        "author_inst": "Translational Neuroscience Laboratory (LabNet), Post-Graduate Program in Neurology, Federal University of Rio de Janeiro State, RJ, Brazil."
+      },
+      {
+        "author_name": "Emanuelle V. De Lima",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil."
+      },
+      {
+        "author_name": "Leticia S. Antonio",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil."
+      },
+      {
+        "author_name": "Mariana B. Hammerle",
+        "author_inst": "Clinical Medicine post-graduation program, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Hannah P. Mota-Araujo",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Lilian C. Colodeti",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Suzana M. B. Araujo",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Talita N. da Silva",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Larissa A. Duarte",
+        "author_inst": "Translational Neuroscience Laboratory (LabNet), Post-Graduate Program in Neurology, Federal University of Rio de Janeiro State, RJ, Brazil"
+      },
+      {
+        "author_name": "Andreza L. Salvio",
+        "author_inst": "Translational Neuroscience Laboratory (LabNet), Post-Graduate Program in Neurology, Federal University of Rio de Janeiro State, RJ, Brazil"
+      },
+      {
+        "author_name": "Karina L. Pires",
+        "author_inst": "Neurology Department of Federal University of the State of Rio de Janeiro (UNIRIO), Rio de Janeiro, Brazil"
+      },
+      {
+        "author_name": "Luciane A. A. Leon",
+        "author_inst": "Laboratorio de Desenvolvimento Tecnologico em Virologia. IOC/FIOCRUZ, Rio de Janeiro, Brasil"
+      },
+      {
+        "author_name": "Claudia C. F. Vasconcelos",
+        "author_inst": "Neurology Department of Federal University of the State of Rio de Janeiro (UNIRIO), Rio de Janeiro, Brazil"
+      },
+      {
+        "author_name": "Luciana Romao",
+        "author_inst": "Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, RJ 21944-590, Brazil"
+      },
+      {
+        "author_name": "Luiz E.B. Savio",
+        "author_inst": "Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, RJ 21944-590, Brazil"
+      },
+      {
+        "author_name": "Jerson L. Silva",
+        "author_inst": "Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ 21944-590, Brazil"
+      },
+      {
+        "author_name": "Robson da Costa",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Julia R. Clarke",
+        "author_inst": "Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, RJ 21944-590, Brazil"
+      },
+      {
+        "author_name": "Andrea T. Da Poian",
+        "author_inst": "Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ 21944-590, Brazil"
+      },
+      {
+        "author_name": "Soniza V. Alves-Leon",
+        "author_inst": "Division of Neurology, Hospital Clementino Fraga Filho, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Giselle F. Passos",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
+      },
+      {
+        "author_name": "Claudia P. Figueiredo",
+        "author_inst": "School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "neuroscience"
   },
   {
     "rel_doi": "10.1101/2022.06.07.495215",
@@ -241829,39 +242899,59 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2022.06.05.494856",
-    "rel_title": "A uniquely stable trimeric model of SARS-CoV-2 spike transmembrane domain",
+    "rel_doi": "10.1101/2022.06.05.493249",
+    "rel_title": "Pathogen-Host Adhesion between SARS-CoV-2 S Proteins from Different Variants and Human ACE2 Probed at Single-Molecule and Single-Cell Levels",
     "rel_date": "2022-06-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.05.494856",
-    "rel_abs": "The spike (S) protein of SARS-CoV-2 effectuates membrane fusion and virus entry into target cells. Its transmembrane domain (TMD) represents a homotrimer of -helices anchoring the spike in the viral envelope. Although S-protein models available to date include the TMD, its precise configuration was given brief consideration. Understanding viral fusion entails realistic TMD models, while no reliable approaches towards predicting the 3D structure of transmembrane (TM) trimers exist. Here, we propose a comprehensive computational framework to model the spike TMD (S-TMD) based solely on its primary structure. First, we performed amino acid sequence pattern matching and compared molecular hydrophobicity potential (MHP) distribution on the helix surface against TM homotrimers with known 3D structures and thus selected the TMD of the tumour necrosis factor receptor 1 (TNFR-1) for subsequent template-based modelling. We then iteratively built an all-atom homotrimer model of S-TMD based on \"dynamic MHP portraits\" and residue variability motifs. In this model each helix possessed two overlapping interfaces interacting with either of the remaining helices, which include conservative residues I1216, F1220, I1227, M1229, and M1233. Finally, the stability of this and several alternative models (including a recent NMR structure) and a set of mutant forms was tested in all-atom molecular dynamics (MD) simulations in a POPC bilayer mimicking the viral envelope membrane. Unlike other configurations, our model trimer remained extraordinarily tightly packed over a microsecond-range MD and retained its stability when palmitoylated in accordance with experimental data. Palmitoylation had no significant impact on the TMD conformation nor the way in which the lipid bilayer was perturbed in the presence of the trimer. Overall, the resulting model of S-TMD conforms to known basic principles of TM helix packing and will be further used to explore the complex machinery of membrane fusion from a broader perspective beyond the TMD.",
-    "rel_num_authors": 5,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.05.493249",
+    "rel_abs": "Pathogen-Host adhesion is considered the first step of infection for many pathogens such as bacteria and virus. The binding of the receptor binding domain (RBD) of SARS-CoV-2 Spike protein (S protein) onto human angiotensin-converting enzyme 2 (ACE2) is considered as the first step for the SARS-CoV-2 to adhere onto the host cells during the infection. Within three years, a number of variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been found all around the world. Here, we investigated the adhesion of S Proteins from different variants and ACE2 using atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS) and single-cell force spectroscopy (SCFS). We found that the unbinding force and binding probability of the S protein from Delta variant to the ACE2 was the highest among the variants tested in our study at both single-molecule and single-cell levels. Molecular dynamics simulation showed that ACE2-RBD (Omicron) complex is destabilized by the E484A and Y505H mutations and stabilized by S477N and N501Y mutations, when compared with Delta variant. In addition, a neutralizing antibody, produced by immunization with wild type RBD of S protein, could effectively inhibit the binding of S proteins from wild type, Delta and Omicron variants onto ACE2. Our results provide new insight for the molecular mechanism of the adhesive interactions between S protein and ACE2 and suggest that effective monoclonal antibody can be prepared using wild type S protein against the different variants.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Elena T. Aliper",
-        "author_inst": "MM Shemyakin and Yu A Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Miklukho-Maklaya, 16/10, 117997 Moscow, Russia"
+        "author_name": "Xiaoxu Zhang",
+        "author_inst": "Beijing University of Chemical Technology"
       },
       {
-        "author_name": "Nikolay A. Krylov",
-        "author_inst": "MM Shemyakin and Yu A Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Miklukho-Maklaya, 16/10, 117997 Moscow, Russia"
+        "author_name": "Jialin Chen",
+        "author_inst": "Beijing University of Chemical Technology"
       },
       {
-        "author_name": "Dmitry E. Nolde",
-        "author_inst": "MM Shemyakin and Yu A Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Miklukho-Maklaya, 16/10, 117997 Moscow, Russia"
+        "author_name": "Bixia Hong",
+        "author_inst": "Beijing University of Chemical Technology"
       },
       {
-        "author_name": "Anton A. Polyansky",
-        "author_inst": "Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Campus Vienna Biocenter 5, A-1030, Vienna, Austria"
+        "author_name": "Haifeng Xu",
+        "author_inst": "Beijing University of Chemical Technology"
       },
       {
-        "author_name": "Roman G. Efremov",
-        "author_inst": "MM Shemyakin and Yu A Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Miklukho-Maklaya, 16/10, 117997 Moscow, Russia"
+        "author_name": "Pengfei Pei",
+        "author_inst": "Beijing University of Chemical Technology"
+      },
+      {
+        "author_name": "Long Chen",
+        "author_inst": "Beijing University of Chemical Technology"
+      },
+      {
+        "author_name": "Yigang Tong",
+        "author_inst": "Beijing University of Chemical Technology"
+      },
+      {
+        "author_name": "Shi-Zhong Luo",
+        "author_inst": "Beijing university of chemcial technology"
+      },
+      {
+        "author_name": "Huahao Fan",
+        "author_inst": "Beijing University of Chemical Technology"
+      },
+      {
+        "author_name": "Chengzhi He",
+        "author_inst": "Beijing University of Chemical Technology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2022.06.05.22276008",
@@ -243579,41 +244669,45 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.06.03.22275964",
-    "rel_title": "Indian Female Migrants Face Greater Barriers to Post-Covid Recovery than Males: Evidence from a Panel Study",
+    "rel_doi": "10.1101/2022.06.02.22275918",
+    "rel_title": "Delays in COVID-19 Diagnosis and Hospitalization and Outcomes -- New York City, New York, USA, October 2020-November 2021",
     "rel_date": "2022-06-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.03.22275964",
-    "rel_abs": "BackgroundIndias abrupt nationwide Covid-19 lockdown internally displaced millions of urban migrants, who made arduous journeys to distant rural homes. Documenting their labor market reintegration is a critical aspect of understanding the economic costs of the pandemic for Indias poor. In a country marked by low and declining female labor force participation, identifying gender gaps in labor market reintegration - as a marker of both womens vulnerability at times of crisis and setbacks in womens agency - is especially important. Yet most studies of pandemic-displaced Indian migrants are small, rely on highly selected convenience samples, and lack a gender focus.\n\nMethodsBeginning in April 2020 we enrolled roughly 4,600 displaced migrants who had returned to two of Indias poorest states into a panel survey, which tracked enrollees through July 2021. Survey respondents were randomly selected from the states official databases of return migrants, with sampling stratified by state and gender. 85 percent of enrollees (3,950) were working in urban areas prior to the pandemic. Our analysis focuses on a balanced panel of 1,780 workers who were interviewed three times through July 2021, considering labor market re-entry, earnings, and measures of vulnerability by gender.\n\nFindingsBoth men and women struggle to remigrate - by July 2021 (over a year after the nationwide lockdown ended), no more than 63 percent (95% CI [60,66]) of men and 55 percent [51,59] of women had left their home villages since returning. Initially, returning migrants transition from non-agricultural urban employment into agriculture and unemployment in rural areas. Alongside, incomes plummet, with both genders earning roughly 17 percent of their pre-lockdown incomes in July 2020. Remigration is critical to regaining income - male re-migrants report earnings on par with their pre-lockdown incomes by January 2021, while men remaining in rural areas earn only 23 percent [19,27] of their pre-pandemic income. Remigration benefits women to a lesser extent - female remigrants regain no more than 65 percent [57,73] of their pre-pandemic income at any point. This contrast reflects significantly higher rates of unemployment among women, both among those remaining in rural areas (9 percentage points [6,13] higher than men across waves) and among those who remigrate (13 percentage points [9,17] higher than men across waves). As a result, we observe gender gaps in well-being: female migrants were 7 percentage points [4,10] more likely to report reduced consumption of essential goods and fare 6 percentage points [4,7] worse on a food security index.\n\nInterpretationReturn migrants of both genders experienced persistent hardships for over a year after the initial pandemic lockdown. Female migrants fare worse, driven by both lower rates of remigration and lower rates of labor market re-entry both inside and outside home villages. Some women drop out of the labor force entirely, but most unemployed report seeking or being available to work. In short, pandemic-induced labor market displacement has far-reaching, long-term consequences for migrant workers, especially women.\n\nFundingSurvey costs were funded by research grants from IZA/FCDO Gender, Growth, and Labour Markets in Low Income Countries Programme, J-PAL Jobs and Opportunity Initiative, and the Evidence-based Measures of Empowerment for Research on Gender Equality (EMERGE) program at University of California San Diego. Funders had no role in study design, study implementation, data analysis, or manuscript preparation.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSMost research documenting the experience of displaced domestic migrants during the pandemic is focused on difficulties faced in returning to their home villages and the immediate consequences of this displacement. Existing evidence has found high levels of short-run economic and psychological distress, especially among women and children, and under-coverage of government programs designed to ease the lockdowns sudden economic shock.\n\nAdded value of this studyThis study contributes to existing literature by surveying a large sample of male and female workers, designed to be broadly representative of returned migrants in two of Indias poorest states. Our work takes a longer-term view, tracking study participants efforts to remigrate and reintegrate into the labor force over 15 months. We document sustained difficulties attaining pre-pandemic levels of income and consumption insecurity, especially among women, who struggle even after remigrating.\n\nImplications of all the available evidenceTaken as a whole, the evidence underscores that displaced Indian migrants are a vulnerable and underserved social group, who have faced (and will likely continue to face) lasting negative effects of the Covid-19 pandemic. Displaced migrants - and especially women - would likely benefit from programs designed to facilitate re-entry into urban labor markets; wrap around services that address other effects of the pandemic (e.g. psychological distress) may be particularly valuable.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.02.22275918",
+    "rel_abs": "COVID-19 patients diagnosed [&ge;]3 days after symptom onset had increased odds of hospitalization. The 75th percentile for diagnosis delay was 5 days for residents of low-privilege areas and Black and Hispanic people diagnosed before SARS-CoV-2 Delta predominance, compared with 4 days for other patients, indicating inequities in prompt diagnosis.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Jenna Allard",
-        "author_inst": "MacMillan Center, Yale University"
+        "author_name": "Laura E Graf",
+        "author_inst": "New York City Department of Health and Mental Hygiene"
       },
       {
-        "author_name": "Maulik Jagnani",
-        "author_inst": "University of Colorado Denver"
+        "author_name": "Eric R Peterson",
+        "author_inst": "New York City Department of Health and Mental Hygiene"
       },
       {
-        "author_name": "Yusuf Neggers",
-        "author_inst": "University of Michigan"
+        "author_name": "Jennifer Baumgartner",
+        "author_inst": "New York City Department of Health and Mental Hygiene"
       },
       {
-        "author_name": "Rohini Pande",
-        "author_inst": "Economic Growth Center, Yale University"
+        "author_name": "Anne Fine",
+        "author_inst": "New York City Department of Health and Mental Hygiene"
       },
       {
-        "author_name": "Simone Schaner",
-        "author_inst": "Center for Economic and Social Research, University of Southern California"
+        "author_name": "Corinne N Thompson",
+        "author_inst": "New York City Department of Health and Mental Hygiene"
+      },
+      {
+        "author_name": "Kathleen Blaney",
+        "author_inst": "New York City Department of Health and Mental Hygiene"
       },
       {
-        "author_name": "Charity Troyer Moore",
-        "author_inst": "MacMillan Center, Yale University"
+        "author_name": "Sharon K Greene",
+        "author_inst": "New York City Department of Health and Mental Hygiene"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -245425,49 +246519,33 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.05.31.22274501",
-    "rel_title": "Severe acute respiratory syndrome coronavirus 2 breakthrough infections in healthcare workers vaccinees with BNT162b2 (Pfizer-BioNtech) in Bogota, Colombia",
+    "rel_doi": "10.1101/2022.05.31.22275746",
+    "rel_title": "Symptom variation, correlations, and relationship to physical activity in Long Covid: intensive longitudinal study",
     "rel_date": "2022-06-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.31.22274501",
-    "rel_abs": "The healthcare workers are considered as a high-risk group for infection with SARS-CoV-2, so they were included in the first stage of the National Plan for Vaccination against COVID-19 in Colombia.\n\nAn ongoing prospective cohort study to evaluate immune response to vaccination included 490 workers from health institutions in Bogota, Colombia, vaccinated between March and June 2021 with BNT162b2 (Pfizer-BioNtech). Multiple samples were collected during a follow-up period of 6 months after immunization. We report cases of asymptomatic and symptomatic SARS-CoV-2 infections detected in this cohort. For each participant demographic data, vaccination dates, results for SARS-CoV-2 RT-PCR, and detection of antibody (IgG) tests during the follow-up period were collected.\n\nSARS-CoV-2 infection was detected in 38 (7.7 %) volunteers. Of these, 81.6% had a positive RT-PCR for SARS-CoV-2, and 18.4% were confirmed by detection of IgG anti-SARS-CoV-2 nucleoprotein; 76.3% of infections occurred after 7 days of second dose. A total of 57.9% of the cases were asymptomatic. No hospitalizations or deaths were registered. When infection occurred, 81.6% of infected participants had presence of IgG anti-S antibodies. In 12 samples in which genomic characterization was achieved, 83.4% corresponded to the variant Mu, 8.3% Gamma, and 8.3% Delta.\n\nAll findings agree with other reports in different studies that show the benefit of COVID-19 vaccines, protecting specially against severe disease but not against infection or re-infection.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.31.22275746",
+    "rel_abs": "BackgroundPeople with Long Covid (Post-Acute Sequelae of Covid-19) describe multiple symptoms which vary between and within individuals over relatively short time intervals. We aimed to describe the real-time associations between different symptoms and between symptoms and physical activity at the individual patient level.\n\nMethods and FindingsIntensive longitudinal study of 82 adults with self-reported Long Covid (median duration 12-18 months). Data collection involved a smartphone app with 5 daily entries over 14 days and continuous wearing of a wrist accelerometer. Data items included 7 symptoms (Visual Analog Scales) and perceived demands in the preceding period (Likert scales). Activity was measured using mean acceleration in the 3-hour periods preceding and following app data entry. Analysis used within-person correlations of symptoms pairs and both pooled and individual symptom networks derived from graphical vector autoregression.\n\nApp data was suitable for analysis from 74 participants (90%) comprising 4022 entries representing 77.6% of possible entries. Symptoms varied substantially within individuals and were only weakly auto-correlated. The strongest between-subject symptom correlations were of fatigue with pain (partial coefficient 0.5) and cognitive difficulty with light-headedness (0.41). Pooled within-subject correlations showed fatigue correlated with cognitive difficulty (partial coefficient 0.2) pain (0.19) breathlessness (0.15) and light-headedness (0.12) but not anxiety. Cognitive difficulty was correlated with anxiety and light-headedness (partial coefficients 0.16 and 0.17). Individual participant correlation heatmaps and symptom networks showed no clear patterns indicative of distinct phenotypes.\n\nSymptoms, including fatigue, were inconsistently correlated with prior or subsequent physical activity: this may reflect adjustment of activity in response to symptoms. Delayed worsening of symptoms after the highest activity peak was observed in 7 participants.\n\nConclusionSymptoms of Long Covid vary within individuals over short time scales, with heterogenous patterns of symptom correlation. The findings are compatible with altered central symptom processing as an additional factor in Long Covid.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Pilar Tavera-Rodriguez",
-        "author_inst": "Instituto Nacional de Salud Colombia"
-      },
-      {
-        "author_name": "Juliana Barbosa-Ramirez",
-        "author_inst": "Instituto Nacional de Salud"
-      },
-      {
-        "author_name": "Andrea Bermudez-Forero",
-        "author_inst": "Instituto Nacional de Salud"
-      },
-      {
-        "author_name": "Diego Prada-Cardozo",
-        "author_inst": "Instituto Nacional de Salud"
-      },
-      {
-        "author_name": "Jhonnatan Reales-Gonzalez",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Christopher Burton",
+        "author_inst": "University of Sheffield"
       },
       {
-        "author_name": "Dioselina Pelaez-Carvajal",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Helen Dawes",
+        "author_inst": "University of Exeter"
       },
       {
-        "author_name": "Diana Malo-Sanchez",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Simon Goodwill",
+        "author_inst": "Sheffield Hallam University"
       },
       {
-        "author_name": "Maria-Ximena Meneses-Gil",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Michael Thelwell",
+        "author_inst": "Sheffield Hallam University"
       },
       {
-        "author_name": "Marcela Mercado-Reyes",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Caroline Dalton",
+        "author_inst": "Sheffield Hallam University"
       }
     ],
     "version": "1",
@@ -247063,73 +248141,45 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.05.29.22275277",
-    "rel_title": "Investigation of a SARS-CoV-2 outbreak in a Texas summer camp resulting from a single introduction",
+    "rel_doi": "10.1101/2022.05.29.22275262",
+    "rel_title": "Incidence of Post-Covid Syndrome and Associated Symptoms in Outpatient Care in Bavaria, Germany",
     "rel_date": "2022-05-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.29.22275277",
-    "rel_abs": "SARS-CoV-2 is the etiological agent responsible for the COVID-19 pandemic. It is estimated that only 10 aerosol-borne virus particles are sufficient to establish a secondary infection with SARS-CoV-2. However, the dispersal pattern of SARS-CoV-2 is highly variable and only 10- 20% of cases are responsible for up 80% of secondary infections. The heterogeneous nature of SARS-CoV-2 transmission suggests that super-spreader events play an important role in viral transmission. Super-spreader events occur when a single person is responsible for an unusually high number of secondary infections due to a combination of biological, environmental, and/or behavioral factors. While super-spreader events have been identified as a significant factor driving SARS-CoV-2 transmission, epidemiologic studies have consistently shown that education settings do not play a major role in community transmission. However, an outbreak of SARS-CoV-2 was recently reported among 186 children (aged 10-17) and adults (aged 18 +) after attending an overnight summer camp in Texas in June 2021. To understand the transmission dynamics of the outbreak, RNA was isolated from 36 nasopharyngeal swabs collected from patients that attended the camp and 19 control patients with no known connection to the outbreak. Genome sequencing on the Oxford Nanopore platform was performed using the ARTIC approaches for library preparation and bioinformatic analysis. SARS-CoV-2 amplicons were produced from all RNA samples and >70% of the viral genome was successfully reconstructed with >10X coverage for 46 samples. Phylogenetic methods were used to estimate the transmission history and suggested that the outbreak was the result of a single introduction. We also found evidence for secondary transmission from campers to the community. Together, these findings demonstrate that super-spreader events may occur during large gatherings of children.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.29.22275262",
+    "rel_abs": "ObjectivesTo estimate the treatment incidence of Post-Covid Syndrome in the context of office-based care in Bavaria, Germany, and to establish whether related diagnoses occur more frequently than in patients with no known history of COVID-19.\n\nDesignRetrospective analysis of routinely collected claims data.\n\nSettingOffice-based care in Bavaria, Germany.\n\nParticipants391,990 patients with confirmed COVID-19 diagnosis, 62,659 patients with other respiratory infection, and a control group of 659,579 patients with no confirmed or suspected diagnosis COVID-19.\n\nPrimary and Secondary Outcome MeasuresPrimary outcome is diagnosis of a Post-COVID Syndrome by an office-based physician. Secondary outcomes are: Chronic Fatigue Syndrome (CFS), psychological disorder, fatigue, mild cognitive impairment, disturbances of taste and smell, dyspnea, pulmonary embolism and myalgia.\n\nResultsAmong all patients with confirmed COVID-19 infection, 14.2% (95% CI: 14.0-14.5) received a diagnosis of a Post-COVID Syndrome, and 6.7% (6.5-6.9) received the diagnosis in at least two quarterly periods during a two-year follow-up. Compared with patients with other respiratory infections and with controls, patients with COVID-19 more frequently received a variety of diagnoses including CFS (1.6% vs. 0.6% and 0.3%, respectively), fatigue (13.3% vs. 9.2% and 6.0%), dyspnea (9.9% vs. 5.1% and 3.2%) and disturbances of taste and smell (3.2% vs. 1.2% and 0.5%). The treatment incidence of Post-COVID Syndrome was highest among adults aged 40-59 (19.0%) and lowest among children aged below 12 years (2.6%).\n\nConclusionsOur results demonstrate a moderately high incidence of Post-COVID Syndrome two years after infection with COVID-19. There is an urgent need to find efficient and effective solutions to help patients with mental disorders, dyspnea, fatigue and loss of smell. Guidelines and treatment algorithms, including referral criteria, occupational and physical therapy, require promptly and coherent implementation. Further research is required both to find new therapeutic options and to assess the implications of Post-COVID Syndrome for health services.\n\nStrengths and Limitations of the Study\n\nO_LIThe data cover all statutory health insurance companies in Bavaria and have high generalisability to the general population.\nC_LIO_LIBy considering the proportion of COVID-19 patients consulting a physician, our results are better able to differentiate between everyday complaints and medically significant illness than data from a self-reported questionnaire.\nC_LIO_LIFollow-up of up to two years enables first assessment of the proportion requiring continuous care for a Post-COVID Syndrome.\nC_LIO_LIThe routinely collected data are not audited and contain little information regarding the severity of the symptoms.\nC_LI",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Daniele Michele Swetnam",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Ewan Donnachie",
+        "author_inst": "Bavarian Association of Statutory Health Insurance Physicians"
       },
       {
-        "author_name": "Rojelio Elias Alvarado",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Stephanea Sotcheff",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Brooke M Mitchell",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Allan McConnell",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Rafael R.G. Machado",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Nehad Saada",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Florence P Haseltine",
-        "author_inst": "University of Texas at Arlington"
-      },
-      {
-        "author_name": "Sara Maknojia",
-        "author_inst": "Galveston County Health District"
+        "author_name": "Alexander Hapfelmeier",
+        "author_inst": "Technical University Munich"
       },
       {
-        "author_name": "Anajane Smith",
-        "author_inst": "University of Texas at Arlington"
+        "author_name": "Klaus Linde",
+        "author_inst": "Technical University Munich"
       },
       {
-        "author_name": "Ping Ren",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Martin Tauscher",
+        "author_inst": "Bavarian Association of Statutory Health Insurance Physicians"
       },
       {
-        "author_name": "Philip Keiser",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Roman Gerlach",
+        "author_inst": "Bavarian Association of Statutory Health Insurance Physicians"
       },
       {
-        "author_name": "Scott Weaver",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Anna Greissel",
+        "author_inst": "Technical University Munich"
       },
       {
-        "author_name": "Andrew L Routh",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Antonius Schneider",
+        "author_inst": "Technical University Munich"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -248801,119 +249851,55 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.05.27.493682",
-    "rel_title": "Structural basis of a two-antibody cocktail exhibiting highly potent and broadly neutralizing activities against SARS-CoV-2 variants including diverse Omicron sublineages",
+    "rel_doi": "10.1101/2022.05.27.493400",
+    "rel_title": "The Glycan-Specificity of the Pineapple Lectin AcmJRL and its Carbohydrate-Dependent Binding of the SARS-CoV-2 Spike Protein",
     "rel_date": "2022-05-27",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.27.493682",
-    "rel_abs": "SARS-CoV-2 variants of concern (VOCs), especially the latest Omicron, have exhibited severe antibody evasion. Broadly neutralizing antibodies with high potency against Omicron are urgently needed for understanding working mechanisms and developing therapeutic agents. In this study, we characterized previously reported F61, which was isolated from convalescent patients infected with prototype SARS-CoV-2, as a broadly neutralizing antibody against all VOCs including Omicron BA.1, BA.1.1, BA.2, BA.3 and BA.4 sublineages by utilizing antigen binding and cell infection assays. We also identified and characterized another broadly neutralizing antibody D2 with epitope distinct from that of F61. More importantly, we showed that a combination of F61 with D2 exhibited synergy in neutralization and protecting mice from SARS-CoV-2 Delta and Omicron BA.1 variants. Cryo-EM structures of the spike-F61 and spike-D2 binary complexes revealed the distinct epitopes of F61 and D2 at atomic level and the structural basis for neutralization. Cryo-EM structure of the Omicron-spike-F61-D2 ternary complex provides further structural insights into the synergy between F61 and D2. These results collectively indicated F61 and F61-D2 cocktail as promising therapeutic antibodies for combating SARS-CoV-2 variants including diverse Omicron sublineages.",
-    "rel_num_authors": 25,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.27.493400",
+    "rel_abs": "The current SARS-CoV-2 pandemic has become one of the most challenging global health threats, with over 530 million reported infections by May 2022. In addition to vaccines, research and development have also been directed towards novel drugs. Since the highly glycosylated spike protein of SARS-CoV-2 is essential for infection, it constitutes a prime target for antiviral agents. The pineapple-derived jacalin-related lectin (AcmJRL) is present in the medication bromelain in significant quantities and has previously been described to bind mannosides. Here, we elucidated its ligand specificity by glycan array analysis, quantified the interaction with carbohydrates and validated high-mannose glycans as preferred ligands. Because the SARS-CoV-2 spike protein was previously reported to carry a high proportion of high-mannose N-glycans, we tested the binding of AcmJRL to recombinantly produced spike protein. We could demonstrate that AcmJRL binds the spike protein with a low micromolar KD in a carbohydrate-dependent fashion, suggesting its use as a potential SARS-CoV-2 neutralising agent.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Xiaoman Li",
-        "author_inst": "The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Bio"
-      },
-      {
-        "author_name": "Yongbing Pan",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
-      },
-      {
-        "author_name": "Qiangling Yin",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
-      },
-      {
-        "author_name": "Zejun Wang",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
-      },
-      {
-        "author_name": "Sisi Shan",
-        "author_inst": "NexVac Research Center, Comprehensive AIDS Research Center, Center for Infectious Disease Research, Department of Basic Medical Sciences, School of Medicine, Ts"
-      },
-      {
-        "author_name": "Laixing Zhang",
-        "author_inst": "The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Bio"
-      },
-      {
-        "author_name": "Jinfang Yu",
-        "author_inst": "The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Bio"
-      },
-      {
-        "author_name": "Yuanyuan Qu",
-        "author_inst": "Institution of Infectious Diseases, Shenzhen Bay Laboratory, Shenzhen 518107, China"
+        "author_name": "Joscha Meiers",
+        "author_inst": "Helmholtz Institute  for Pharmaceutical Research Saarland (HIPS)"
       },
       {
-        "author_name": "Lina Sun",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
+        "author_name": "Jan Dastbaz",
+        "author_inst": "Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)"
       },
       {
-        "author_name": "Fang Gui",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
+        "author_name": "Sebastian Adam",
+        "author_inst": "Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)"
       },
       {
-        "author_name": "Jia Lu",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
+        "author_name": "Sari Rasheed",
+        "author_inst": "Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)"
       },
       {
-        "author_name": "Zhaofei Jing",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
+        "author_name": "Susanne H Kirsch",
+        "author_inst": "Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)"
       },
       {
-        "author_name": "Wei Wu",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
-      },
-      {
-        "author_name": "Tao Huang",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
-      },
-      {
-        "author_name": "Xuanling Shi",
-        "author_inst": "NexVac Research Center, Comprehensive AIDS Research Center, Center for Infectious Disease Research, Department of Basic Medical Sciences, School of Medicine, Ts"
-      },
-      {
-        "author_name": "Jiandong Li",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
-      },
-      {
-        "author_name": "Xinguo Li",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
+        "author_name": "Peter Meiser",
+        "author_inst": "Ursapharm"
       },
       {
-        "author_name": "Dexin Li",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
-      },
-      {
-        "author_name": "Shiwen Wang",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
-      },
-      {
-        "author_name": "Maojun Yang",
-        "author_inst": "The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Bio"
-      },
-      {
-        "author_name": "Linqi Zhang",
-        "author_inst": "NexVac Research Center, Comprehensive AIDS Research Center, Center for Infectious Disease Research, Department of Basic Medical Sciences, School of Medicine, Ts"
-      },
-      {
-        "author_name": "Kai Duan",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
-      },
-      {
-        "author_name": "Mifang Liang",
-        "author_inst": "State Key Laboratory for Molecular Virology and Genetic Engineering, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Con"
+        "author_name": "Peter Gross",
+        "author_inst": "Hochschule Kaiserslautern"
       },
       {
-        "author_name": "Xiaoming Yang",
-        "author_inst": "National Engineering Technology Research Center for Combined Vaccines, Wuhan Institute of Biological Products Co. Ltd., Wuhan 430070, China"
+        "author_name": "Rolf Mueller",
+        "author_inst": "Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)"
       },
       {
-        "author_name": "Xinquan Wang",
-        "author_inst": "The Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, Beijing Frontier Research Center for Bio"
+        "author_name": "Alexander Titz",
+        "author_inst": "Helmholtz-Institut fuer Pharmazeutische Forschung Saarland"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2022.05.27.22275675",
@@ -251235,47 +252221,27 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.05.26.493529",
-    "rel_title": "The emergence of variants with increased fitness accelerates the slowdown of genome sequence heterogeneity in the SARS CoV 2 coronavirus",
-    "rel_date": "2022-05-26",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.26.493529",
-    "rel_abs": "Since the outbreak of the COVID-19 pandemic, the SARS-CoV-2 coronavirus has accumulated an important amount of genetic and genomic variability through mutation and recombination events. To test evolutionary trends that could inform us on the adaptive process of the virus to its human host, we summarize all this sequence variability by computing the Sequence Compositional Complexity (SCC) in more than 23,000 high-quality coronavirus genome sequences from across the globe, covering the period spanning from the start of the pandemic in December 2019 to March 2022. In early samples, we found no statistical support for any trend in SCC values over time, although the virus as a whole appears to evolve faster than Brownian Motion expectation. However, in samples taken after the first Variant of Concern (VoC) with higher transmissibility (Alpha) emerges, and controlling for phylogenetic and sampling effects, we were able to detect a statistically significant trend for decreased SCC values over time. SARS-CoV-2 evolution towards lower values of genome heterogeneity is further intensified by the emergence of successive, widespread VoCs. Concomitantly to the temporal reduction in SCC, its absolute evolutionary rate kept increasing toward the present, meaning that the SCC decrease itself accelerated over time. As compared to Alpha or Delta variants, the currently dominant VoC, Omicron, shows much stronger trends in both SCC values and rates over time. These results indicate that the increases in fitness of variant genomes associated to a higher transmissibility leads to a reduction of their genome sequence heterogeneity, thus explaining the general slowdown of SCC along with the pandemic course.",
-    "rel_num_authors": 7,
+    "rel_doi": "10.1101/2022.05.21.22275421",
+    "rel_title": "Analysis of the genetic diversity of SARS-CoV-2 genomes carrying the Omicron B.1.1.529 mutation",
+    "rel_date": "2022-05-25",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.21.22275421",
+    "rel_abs": "In this work, we evaluated the levels of genetic diversity in 95 genomes of the carriers of the Omicron B.1.1.529 mutation in SARS-CoV-2 from South Africa, Asia, Massachusetts-USA, Rhode Island-USA, United Kingdom and Germany. All with 29,996pb extension and recovered from GENBANK and publicly available at the National Center for Biotechnology and Information (NCBI). All gaps and conserved sites were extracted for the construction of a phylogenetic tree and for specific methodologies of estimates of paired FST, Molecular Variance (AMOVA), Genetic Distance, Incompatibility, demographic expansion analyses, molecular diversity and of evolutionary divergence time analyses, always with 20,000 random permutations. The results revealed the presence of only 75 parsimony-informative sites, sites among the 29,996bp analyzed. The analyses based on FST values, confirmed the absence of distinct genetic structuring with fixation index of 98% and with a greater component of population variation (6%) for a \"p\" 0.05. Tau variations (related to the ancestry of the groups), did not reveal significant moments of divergence, supported by the incompatible analysis of the observed distribution ({tau} = 0%). It is safe to say that the large number of existing polymorphisms reflects major changes in the protein products of viral populations in all countries and especially In South Africa. This consideration provides the safety that, because there are large differences between the haplotypes studied, these differences are minimal within the populations analyzed geographically and, therefore, it does not seem safe to extrapolate the results of polymorphism and molecular diversity levels found in the Variant Omicron B.1.529 of SARS-CoV-2 for wild genomes or other mutants. This warns us that, due to their higher transmission speed and infection, possible problems of molecular adjustments in vaccines already in use may be necessary in the near future.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Jos\u00e9 L. Oliver",
-        "author_inst": "Professor of Genetics, Facultad de Ciencias, Universidad de Granada, Spain"
+        "author_name": "Br\u00e1ulio Wagner Correia da Silva",
+        "author_inst": "Laboratory of Population Genetics and Computational Evolutionary Biology - LaBECom, UNIVISA, Vit\u00f3ria de Santo Ant\u00e3o, Pernambuco, Brazil"
       },
       {
-        "author_name": "Pedro Bernaola-Galv\u00e1n",
-        "author_inst": "Professor of Applied Physics, E.T.S. de Ingenieria de Telecomunicacion, Universidad de Malaga, Spain"
-      },
-      {
-        "author_name": "Francisco Perfectti",
-        "author_inst": "Professor of Genetics, Grupo de Genetica Evolutiva, Departamento de Genetica and  Research Unit Modeling Nature Evoflor, Unidad Asociada al CSIC, Universidad de"
-      },
-      {
-        "author_name": "Cristina G\u00f3mez-Mart\u00edn",
-        "author_inst": "Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Center Amsterdam, Amsterdam, Netherlands"
-      },
-      {
-        "author_name": "Pasquale Raia",
-        "author_inst": "Dip.to DiSTAR, Napoli Universita di Napoli Federico II, Dipartimento di Scienze della Terra, dell Ambiente e delle Risorse, Italy"
-      },
-      {
-        "author_name": "Miguel Verd\u00fa",
-        "author_inst": "Centro de Investigaciones sobre Desertificacion, Consejo Superior de Investigaciones Cientificas (CSIC), University of Valencia and Generalitat Valenciana, 4611"
-      },
-      {
-        "author_name": "Andr\u00e9s Moya",
-        "author_inst": "Professor of Genetics, University of Valencia Chair, Institutional Professorship FISABIO - University of Valencia, Spain"
+        "author_name": "Pierre Teodosio Felix Sr.",
+        "author_inst": "Laboratory of Population Genetics and Computational Evolutionary Biology - LaBECom, UNIVISA, Vit\u00f3ria de Santo Ant\u00e3o, Pernambuco, Brazil"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "genomics"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.05.23.22275445",
@@ -253157,27 +254123,151 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.05.20.22275407",
-    "rel_title": "Social divisions and risk perception can drive divergent epidemic dynamics and large second and third waves",
+    "rel_doi": "10.1101/2022.05.22.22275417",
+    "rel_title": "Comparative effectiveness of sotrovimab and molnupiravir for prevention of severe COVID-19 outcomes in non-hospitalised patients: an observational cohort study using the OpenSAFELY platform",
     "rel_date": "2022-05-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.20.22275407",
-    "rel_abs": "During infectious disease outbreaks, individuals may adopt protective measures like vaccination and physical distancing in response to awareness of disease burden. Prior work showed how feedback between epidemic intensity and awareness-based behavior shapes disease dynamics (e.g., producing plateaus and oscillations). These models often overlook social divisions, where population subgroups may be disproportionately impacted by a disease and more responsive to the effects of disease within their group. We hypothesize that socially divided awareness-based behavior could fundamentally alter epidemic dynamics and shift disease burden between groups.\n\nWe develop a compartmental model of disease transmission in a population split into two groups to explore the impacts of awareness separation (relatively greater in-versus out-group awareness of epidemic severity) and mixing separation (relatively greater in-versus out-group contact rates). Protective measures are adopted based on awareness of recent disease-linked mortality. Using simulations, we show that groups that are more separated in awareness have smaller differences in mortality. Fatigue-driven abandonment of protective behavior can drive additional infection waves that can even exceed the size of the initial wave, particularly if uniform awareness drives early protection in one group, leaving that group largely susceptible to future infection. Finally, vaccine or infection-acquired immunity that is more protective against transmission and mortality may indirectly lead to more infections by reducing perceived risk of infection, and thereby reducing vaccine uptake. The dynamics of awareness-driven protective behavior, including relatively greater awareness of epidemic conditions in ones own group, can dramatically impact protective behavior uptake and the course of epidemics.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.22.22275417",
+    "rel_abs": "ObjectiveTo compare the effectiveness of sotrovimab (a neutralising monoclonal antibody) vs. molnupiravir (an antiviral) in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients.\n\nDesignWith the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform.\n\nSettingPatient-level electronic health record data were obtained from 24 million people registered with a general practice in England that uses TPP software. The primary care data were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death within the OpenSAFELY-TPP platform, covering a period where both medications were frequently prescribed in community settings.\n\nParticipantsNon-hospitalised adult COVID-19 patients at high risk of severe outcomes treated with sotrovimab or molnupiravir since December 16, 2021.\n\nInterventionsSotrovimab or molnupiravir administered in the community by COVID-19 Medicine Delivery Units.\n\nMain outcome measureCOVID-19 related hospitalisation or COVID-19 related death within 28 days after treatment initiation.\n\nResultsBetween December 16, 2021 and February 10, 2022, 3331 and 2689 patients were treated with sotrovimab and molnupiravir, with no substantial differences in their baseline characteristics. The mean age of all 6020 patients was 52 (SD=16) years; 59% were female, 89% White and 88% had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 87 (1.4%) COVID-19 related hospitalisations/deaths were observed (32 treated with sotrovimab and 55 with molnupiravir). Cox proportional hazards models stratified by area showed that after adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, treatment with sotrovimab was associated with a substantially lower risk than treatment with molnupiravir (hazard ratio, HR=0.54, 95% CI: 0.33 to 0.88; P=0.014). Consistent results were obtained from propensity score weighted Cox models (HR=0.50, 95% CI: 0.31 to 0.81; P=0.005) and when restricted to fully vaccinated people (HR=0.53, 95% CI: 0.31 to 0.90; P=0.019). No substantial effect modifications by other characteristics were detected (all P values for interaction>0.10). Findings were similar in an exploratory analysis of patients treated between February 16 and May 1, 2022 when the Omicron BA.2 variant was dominant in England.\n\nConclusionIn routine care of non-hospitalised high-risk adult patients with COVID-19 in England, those who received sotrovimab were at lower risk of severe COVID-19 outcomes than those receiving molnupiravir.",
+    "rel_num_authors": 33,
     "rel_authors": [
       {
-        "author_name": "Mallory J Harris",
-        "author_inst": "Biology Department, Stanford University, Stanford, CA 94301"
+        "author_name": "Bang Zheng",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Amelia CA Green",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "John Tazare",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Helen J Curtis",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Louis Fisher",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Linda Nab",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Anna Schultze",
+        "author_inst": "London School of Hygiene and Trop. Med."
+      },
+      {
+        "author_name": "Viyaasan Mahalingasivam",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Edward Parker",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "William J Hulme",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Sebastian CJ Bacon",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Nicholas J DeVito",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Christopher Bates",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "David Evans",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Peter Inglesby",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Henry Drysdale",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Simon Davy",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Erin A. Mordecai",
-        "author_inst": "Biology Department, Stanford University, Stanford, CA 94301"
+        "author_name": "Jonathan Cockburn",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Caroline E Morton",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "George Hickman",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Tom Ward",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Rebecca M Smith",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "John Parry",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Frank Hester",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Sam Harper",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Amir Mehrkar",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Rosalind M Eggo",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "Alex J Walker",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Stephen JW Evans",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Ian J Douglas",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Brian MacKenna",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ben Goldacre",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Laurie A Tomlinson",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.05.20.22275396",
@@ -255191,59 +256281,35 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2022.05.18.22275283",
-    "rel_title": "BNT162b2 induces robust cross-variant SARS-CoV-2 immunity in children",
+    "rel_doi": "10.1101/2022.05.18.22275240",
+    "rel_title": "Exploring barriers and facilitators to physical activity during the COVID-19 pandemic: a qualitative study",
     "rel_date": "2022-05-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.18.22275283",
-    "rel_abs": "Currently available mRNA vaccines are extremely safe and effective to prevent severe SARS-CoV-2 infections. However, the emergence of novel variants of concerns has highlighted the importance of high population-based vaccine rates to effectively suppress viral transmission and breakthrough infections. While initially left out from vaccine efforts, children have become one of the most affected age groups and are key targets to stop community and household spread. Antibodies are central for vaccine induced protection and emerging data points to the importance of additional Fc effector functions like opsononophagocytosis or cytotoxicity, particularly in the context of variants of concern that escape neutralizing antibodies. Here, we observed delayed induction and reduced magnitude of vaccine induced antibody titers in children 5-11 years receiving two doses of the age recommended 10 g dose of the Pfizer SARS-CoV-2 BNT162b2 vaccine compared to adolescents (12-15 years) or adults receiving the 30 g dose. Conversely, children mounted equivalent or more robust neutralization and opsonophagocytic functions at peak immunogenicity, pointing to a qualitatively more robust humoral functional response in children. Moreover, broad cross-variants of concern responses were observed across children, with enhanced IgM and parallel IgG cross-reactivity to variants of concern (VOCs) in children compared to adults. Collectively, these data argue that despite the lower magnitude of the BNT162b2 induced antibody response in children, vaccine induced immunity in children target VOCs broadly and exhibit enhanced functionality that may contribute to attenuation of disease.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.18.22275240",
+    "rel_abs": "ObjectivesQuantitative data show that physical activity (PA) reduced during the COVID-19 pandemic, with differential impacts across demographic groups. Qualitative research is limited, so reasons for this have not been explored in-depth. This study aimed to understand barriers and facilitators to PA during the pandemic, focusing on groups more likely to have been affected by restrictions, and to map these onto the Capability, Opportunity, Motivation Model of Behaviour (COM-B).\n\nDesignSemi-structured qualitative interview study.\n\nMethodsOne-to-one telephone/videocall interviews were conducted with younger (aged 18-24) and older adults (aged 70+), those with long-term physical health conditions or mental health conditions, and parents of young children, probing about their experiences of PA. Barriers and facilitators were identified using reflexive thematic analysis, and themes were mapped onto COM-B dimensions.\n\nResults116 participants were included (18-93 years old, 61% female, 71% White British). Key themes were the importance of the outdoor environment, impact of COVID-19 restrictions, fear of contracting COVID-19, and level of engagement with home exercise. Caring responsibilities and conflicting priorities were a barrier. PA as a method of socialising, establishing new routines, and the importance of PA for protecting mental health were motivators. Most themes mapped onto the physical opportunity (environmental factors) and reflective motivation (evaluations and plans) COM-B domains.\n\nConclusionsFuture interventions should increase physical opportunity and reflective motivation for PA during pandemics, to avoid further negative health outcomes following periods of lockdown. Strategies could include tailoring PA guidance depending on location and giving education on the health benefits of PA.\n\nStatement of ContributionO_ST_ABSWhat is already known on this subject?C_ST_ABSO_LIPhysical activity (PA) levels reduced during the COVID-19 pandemic.\nC_LIO_LIThe extent of this reduction varied across demographic groups.\nC_LIO_LIVery few qualitative studies have explored reasons for these changes.\nC_LI\n\nWhat does this study add?O_LINovel interview data, giving context to existing quantitative data.\nC_LIO_LIInsight into which themes were important for different demographic groups.\nC_LIO_LISuggestions for increasing PA in future pandemics, by mapping findings to a theoretical framework.\nC_LI",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Yannic C Bartsch",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
-      },
-      {
-        "author_name": "Jessica W Chen",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
-      },
-      {
-        "author_name": "Jaewon Kang",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
-      },
-      {
-        "author_name": "Madeline D Burns",
-        "author_inst": "Massachusetts General Hospital Department of Pediatrics"
-      },
-      {
-        "author_name": "Kerri J St.Denis",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
-      },
-      {
-        "author_name": "Maegan L Sheehan",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
-      },
-      {
-        "author_name": "Jameson P Davis",
-        "author_inst": "Massachusetts General Hospital Department of Pediatrics"
+        "author_name": "Charlotte Roche",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Alejandro B Balazs",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
+        "author_name": "Abigail Fisher",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Lael M Yonker",
-        "author_inst": "Massachusetts General Hospital Department of Pediatrics"
+        "author_name": "Daisy Fancourt",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Galit Alter",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
+        "author_name": "Alexandra Burton",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.05.20.22275313",
@@ -257093,47 +258159,87 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2022.05.14.22275075",
-    "rel_title": "Self-medication practices and associated factors among COVID-19 recovered patients to prevent future infections: A web-based survey in Bangladesh",
+    "rel_doi": "10.1101/2022.05.17.22275154",
+    "rel_title": "COVID-19 booster dose antibody response in pregnant, lactating, and nonpregnant women",
     "rel_date": "2022-05-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.14.22275075",
-    "rel_abs": "BackgroundHuman health is largely affected by self-medication in both ways, adversely and favorably, as evidenced by the COVID-19 pandemic. The fear of spreading COVID-19 among health workers and hospital environments has led many Bangladeshi people to practice self-medicate for as a preventive strategy against this disease. Consequently, this practice entails an improper and injudicious use of medicine to cure self-recognized symptoms. To date, the COVID-19 has no effective treatment. The lack of a cure for COVID-19 and the continual progression of the diseases in educational settings induce a substantial population to practice self-medication. Therefore a study of self-medication practices is necessary for the framework of the pandemic. This study aimed to estimate the prevalence and factors associated with self-medication to prevent or manage future COVID-19 infections among recovered COVID-19 patients.\n\nMethodsThis cross-sectional study was conducted from September 2020 to February 2021 using an e-survey along with 360 participants. Data were collected using a pre-tested self-reported questionnaire. Descriptive statistics and correlations analysis were performed in the study.\n\nResultsAmong 360 participants, males were 69.7%, and females 30.3%. The prevalence of self-medication is 11%, and monthly family income, residence, education, occupation, and previous history of SM are the associated factors. Among the participants, 29.7% use antibiotics, and 30% use herbal products or drugs as medication.\n\nConclusionThe present study found SMP is moderately prevalent among COVID-19 recovered patients. To minimize the rate of SMP, adequate health care access systems and public education should be introduced, and media & community should be engaged in rational use of medication.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.17.22275154",
+    "rel_abs": "BACKGROUNDWhile emerging data during the SARS-CoV-2 pandemic have demonstrated robust mRNA vaccine-induced immunogenicity across populations, including pregnant and lactating individuals, the rapid waning of vaccine-induced immunity and the emergence of variants of concern motivated the use of mRNA vaccine booster doses. Whether all populations, including pregnant and lactating individuals, will mount a comparable response to a booster dose is not known.\n\nOBJECTIVEWe sought to profile the humoral immune response to a COVID-19 mRNA booster dose in a cohort of pregnant, lactating, and age-matched nonpregnant women.\n\nSTUDY DESIGNWe characterized the antibody response against ancestral Spike and Omicron in a cohort of 31 pregnant, 12 lactating and 20 nonpregnant age-matched controls who received a BNT162b2 or mRNA-1273 booster dose after primary COVID-19 vaccination. We also examined the vaccine-induced antibody profiles of 15 maternal:cord dyads at delivery.\n\nRESULTSReceipt of a booster dose during pregnancy resulted in increased IgG1 against Omicron Spike (post-primary vaccination vs post-booster, p = 0.03). Pregnant and lactating individuals exhibited equivalent Spike-specific total IgG1, IgM and IgA levels and neutralizing titers against Omicron compared to nonpregnant women. Subtle differences in Fc-receptor binding and antibody subclass profiles were observed in the immune response to a booster dose in pregnant compared to nonpregnant individuals. Analysis of maternal and cord antibody profiles at delivery demonstrated equivalent total Spike-specific IgG1 in maternal and cord blood, yet higher Spike-specific Fc{gamma}R3a-binding antibodies in the cord relative to maternal blood (p = 0.002), consistent with preferential transfer of highly functional IgG. Spike-specific IgG1 levels in the cord were positively correlated with time elapsed since receipt of the booster dose (Spearman R 0.574, p = 0.035).\n\nCONCLUSIONSThese data suggest that receipt of a booster dose during pregnancy induces a robust Spike-specific humoral immune response, including against Omicron. If boosting occurs in the third trimester, higher Spike-specific cord IgG1 levels are achieved with greater time elapsed between receipt of the booster and delivery. Receipt of a booster dose has the potential to augment maternal and neonatal immunity.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Md. Safaet Hossain Sujan",
-        "author_inst": "Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh"
+        "author_name": "Caroline Atyeo PhD",
+        "author_inst": "Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; PhD Program in Virology, Division of Medical Sciences, Harvard University, Boston, MA, USA"
       },
       {
-        "author_name": "Atefehsadat Haghighathoseini",
-        "author_inst": "Department of Health Administration and Policy, George Mason University"
+        "author_name": "Lydia L Shook MD",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Vincent Center for Reproductive Biology, Massach"
       },
       {
-        "author_name": "Rafia Tasnim",
-        "author_inst": "Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh; Centre for Advanced Research Excellence in Public Health, "
+        "author_name": "Nadege Nziza PhD",
+        "author_inst": "Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA"
       },
       {
-        "author_name": "Md. Saiful Islam",
-        "author_inst": "Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh"
+        "author_name": "Elizabeth A DeRiso PhD",
+        "author_inst": "Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA"
       },
       {
-        "author_name": "Sarif Mahammad Salauddin",
-        "author_inst": "Sir Salimullah Medical College, Dhaka-1212, Bangladesh"
+        "author_name": "Cordelia Muir",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"
       },
       {
-        "author_name": "Mohammad Mohiuddin Hasan",
-        "author_inst": "Hospital Services Management, DGHS, Mohakhali, Dhaka-1212, Bangladesh"
+        "author_name": "Arantxa Medina Baez",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA"
       },
       {
-        "author_name": "Muhammad Ramiz Uddin",
-        "author_inst": "Department of Chemistry and Biochemistry, The university of Oklahoma, Norman, USA"
+        "author_name": "Rosiane S Lima",
+        "author_inst": "Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA"
+      },
+      {
+        "author_name": "Stepan Demidkin",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Vincent Center for Reproductive Biology, Massach"
+      },
+      {
+        "author_name": "Sara Brigida",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Vincent Center for Reproductive Biology, Massach"
+      },
+      {
+        "author_name": "Rose M De Guzman PhD",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Vincent Center for Reproductive Biology, Massach"
+      },
+      {
+        "author_name": "Madeleine D Burns",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatrics, Massachusetts General "
+      },
+      {
+        "author_name": "Alejandro B Balazs PhD",
+        "author_inst": "Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Alessio Fasano MD",
+        "author_inst": "Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA"
+      },
+      {
+        "author_name": "Lael M Yonker MD",
+        "author_inst": "Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA"
+      },
+      {
+        "author_name": "Kathryn J Gray MD PhD",
+        "author_inst": "Department of Obstetrics and Gynecology, Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA"
+      },
+      {
+        "author_name": "Galit Alter PhD",
+        "author_inst": "Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Andrea G Edlow MD MSc",
+        "author_inst": "Department of Obstetrics & Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Vincent Center for Reproductive Biology, Massach"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "obstetrics and gynecology"
   },
   {
     "rel_doi": "10.1101/2022.05.15.22275071",
@@ -258655,65 +259761,77 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2022.05.17.22275027",
-    "rel_title": "A Randomized Phase 2/3 Study of Ensitrelvir, a Novel Oral SARS-CoV-2 3C-like Protease Inhibitor, in Japanese Patients With Mild-to-Moderate COVID-19 or Asymptomatic SARS-CoV-2 Infection: Results of the Phase 2a Part",
+    "rel_doi": "10.1101/2022.05.16.22275163",
+    "rel_title": "Performance and validation of an adaptable multiplex assay for detection of serologic response to SARS-CoV-2 infection or vaccination.",
     "rel_date": "2022-05-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.17.22275027",
-    "rel_abs": "For the treatment of coronavirus disease 2019 (COVID-19), antiviral agents that can achieve rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reduction are warranted. This double-blind, phase 2a part of a phase 2/3 study assessed the efficacy and safety of ensitrelvir, a novel oral SARS-CoV-2 3C-like protease inhibitor, in Japanese patients with mild-to-moderate COVID-19 or asymptomatic SARS-CoV-2 infection. Sixty-nine patients enrolled from 56 sites were randomized (1:1:1) to orally receive 5-day ensitrelvir fumaric acid (375 mg on day 1 followed by 125 mg daily or 750 mg on day 1 followed by 250 mg daily) or placebo and followed up until day 28. The primary outcome was change from baseline in SARS-CoV-2 viral titer. A total of 16, 14, and 17 patients in the ensitrelvir 125 mg, ensitrelvir 250 mg, and placebo groups, respectively, were included in the intention-to-treat population (mean age: 38.8, 40.4, and 38.0 years, respectively). On day 4, the change from baseline in SARS-CoV-2 viral titer (log10 50% tissue culture infectious dose/mL) in patients with positive viral titer and viral RNA at baseline was greater with ensitrelvir 125 mg (mean [standard deviation], -2.42 [1.42]; P = 0.0712) and 250 mg (-2.81 [1.21]; P = 0.0083) versus placebo (-1.54 [0.74]), and ensitrelvir treatment reduced SARS-CoV-2 RNA by -1.4 to -1.5 log10 copies/mL versus placebo. All adverse events were mild to moderate. Ensitrelvir treatment demonstrated rapid SARS-CoV-2 clearance and was well tolerated in patients with mild-to-moderate COVID-19 or asymptomatic SARS-CoV-2 infection (Japan Registry of Clinical Trials identifier: jRCT2031210350).",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.16.22275163",
+    "rel_abs": "Measurement of quantitative antibody responses are increasingly important in evaluating the immune response to infection and vaccination. In this study we describe the validation of a quantitative, multiplex serologic assay utilising an electrochemiluminescence platform, which measures IgG against the receptor binding domain (RBD), spike S1 and S2 subunits and nucleocapsid antigens of SARS-CoV-2. The assay displayed a sensitivity ranging from 73-91% and specificity from 90 to 96% in detecting previous infection with SARS-CoV-2 depending on antigenic target and time since infection, and this assay highly correlated with commercially available assays. The within-plate coefficient of variation ranged from 3.8-3.9% and the inter-plate coefficient of variation from 11-13% for each antigen.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Hiroshi Mukae",
-        "author_inst": "Nagasaki University Graduate School of Biomedical Sciences"
+        "author_name": "Grace Kenny",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
       },
       {
-        "author_name": "Hiroshi Yotsuyanagi",
-        "author_inst": "The University of Tokyo"
+        "author_name": "Riya Negi",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
       },
       {
-        "author_name": "Norio Ohmagari",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Sophie O'Reilly",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
       },
       {
-        "author_name": "Yohei Doi",
-        "author_inst": "University of Pittsburgh School of Medicine/Fujita Health University School of Medicine"
+        "author_name": "Alejandro Abner Garcia Leon",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
       },
       {
-        "author_name": "Takumi Imamura",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Dana Alalwan",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
       },
       {
-        "author_name": "Takuhiro Sonoyama",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Colette Marie Gaillard",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
       },
       {
-        "author_name": "Takahiro Fukuhara",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Gurvin Saini",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
       },
       {
-        "author_name": "Genki Ichihashi",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Rosanna Inzitari",
+        "author_inst": "School of Medicine, University College Dublin, Ireland"
       },
       {
-        "author_name": "Takao Sanaki",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Eoin Feeney",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland; Department of Infectious Diseases,  St Vincent's University Hospital, Irelan"
       },
       {
-        "author_name": "Keiko Baba",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Aoife G Cotter",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland; Department of Infectious Diseases,  Mater Misericordiae University Hospital,"
       },
       {
-        "author_name": "Yosuke Takeda",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Eoghan de Barra",
+        "author_inst": "Department of Infectious Diseases, Beaumont Hospital, Ireland, Department of International Health and Tropical Medicine, Royal College of Surgeons in Ireland"
       },
       {
-        "author_name": "Yuko Tsuge",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Corinna Sadlier",
+        "author_inst": "Department of Infectious Diseases, Cork University Hospital, Ireland"
       },
       {
-        "author_name": "Takeki Uehara",
-        "author_inst": "Shionogi & Co., Ltd."
+        "author_name": "Fiona Crispie",
+        "author_inst": "Teagasc Food Research Centre and APC Microbiome Ireland"
+      },
+      {
+        "author_name": "Virginie Gautier",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
+      },
+      {
+        "author_name": "Patrick Mallon",
+        "author_inst": "Centre for Experimental Pathogen Host Research, University College Dublin, Ireland"
+      },
+      {
+        "author_name": "- All Ireland Infectious Diseases Cohort Study",
+        "author_inst": ""
       }
     ],
     "version": "1",
@@ -260345,103 +261463,39 @@
     "category": "geriatric medicine"
   },
   {
-    "rel_doi": "10.1101/2022.05.14.491911",
-    "rel_title": "SARS-CoV-2 Omicron Variant Wave in India: Advent, Phylogeny and Evolution",
+    "rel_doi": "10.1101/2022.05.13.491763",
+    "rel_title": "AI-based search for convergently expanding, advantageous mutations in SARS-CoV-2 by focusing on oligonucleotide frequencies",
     "rel_date": "2022-05-16",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.14.491911",
-    "rel_abs": "SARS-CoV-2 evolution has continued to generate variants, responsible for new pandemic waves locally and globally. Varying disease presentation and severity has been ascribed to inherent variant characteristics and vaccine immunity. This study analyzed genomic data from 305 whole genome sequences from SARS-CoV-2 patients before and through the third wave in India. Delta variant was responsible for disease in patients without comorbidity(97%), while Omicron BA.2 caused disease primarily in those with comorbidity(77%). Tissue adaptation studies brought forth higher propensity of Omicron variants to bronchial tissue than lung, contrary to observation in Delta variants from Delhi. Study of codon usage pattern distinguished the prevalent variants, clustering them separately, Omicron BA.2 isolated in February grouped away from December strains, and all BA.2 after December acquired a new mutation S959P in ORF1b (44.3% of BA.2 in the study) indicating ongoing evolution. Loss of critical spike mutations in Omicron BA.2 and gain of immune evasion mutations including G142D, reported in Delta but absent in BA.1, and S371F instead of S371L in BA.1 could possibly be due to evolutionary trade-off and explain very brief period of BA.1 in December 2021, followed by complete replacement by BA.2.",
-    "rel_num_authors": 21,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.13.491763",
+    "rel_abs": "Among mutations that occur in SARS-CoV-2, efficient identification of mutations advantageous for viral replication and transmission is important to characterize and defeat this rampant virus. Mutations rapidly expanding frequency in a viral population are candidates for advantageous mutations, but neutral mutations hitchhiking with advantageous mutations are also likely to be included. To distinguish these, we focus on mutations that appear to occur independently in different lineages and expand in frequency in a convergent evolutionary manner. Batch-learning SOM (BLSOM) can separate SARS-CoV-2 genome sequences according by lineage from only providing the oligonucleotide composition. Focusing on remarkably expanding 20-mers, each of which is only represented by one copy in the viral genome, allows us to correlate the expanding 20-mers to mutations. Using visualization functions in BLSOM, we can efficiently identify mutations that have expanded remarkably both in the Omicron lineage, which is phylogenetically distinct from other lineages, and in other lineages. Most of these mutations involved changes in amino acids, but there were a few that did not, such as an intergenic mutation.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Urvashi B Singh",
-        "author_inst": "All India Institute of Medical Sciences"
-      },
-      {
-        "author_name": "Sushanta Deb",
-        "author_inst": "All India institute of medical sciences"
-      },
-      {
-        "author_name": "Rama Chaudhry",
-        "author_inst": "All India Institute of Medical Sciences"
-      },
-      {
-        "author_name": "Kiran Bala",
-        "author_inst": "All India Institute of Medical Sciences"
-      },
-      {
-        "author_name": "Lata Rani",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Ritu Gupta",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Lata Kumari",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Jawed Ahmed",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Sudesh Gaurav",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Sowjanya Perumalla",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Md. Nizam",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Anwita Mishra",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "J. Stephenraj",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Jyoti Shukla",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Deepika Bhardwaj",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Jamshed Nayer",
-        "author_inst": "All India Institute Of Medical Sciences"
-      },
-      {
-        "author_name": "Praveen Aggarwal",
-        "author_inst": "All India Institute Of Medical Sciences"
+        "author_name": "Toshimichi Ikemura",
+        "author_inst": "Nagahama Institute of Bio-Science and Technology"
       },
       {
-        "author_name": "Madhulika Kabra",
-        "author_inst": "All India Institute Of Medical Sciences"
+        "author_name": "Yuki Iwasaki",
+        "author_inst": "Nagahama Institute of Bio-Science and Technology"
       },
       {
-        "author_name": "Vineet Ahuja",
-        "author_inst": "All India Institute Of Medical Sciences"
+        "author_name": "Kennosuke Wada",
+        "author_inst": "Nagahama Institute of Bio-Science and Technology"
       },
       {
-        "author_name": "Subrata Sinha",
-        "author_inst": "All India Institute of Medical Sciences"
+        "author_name": "Yoshiko Wada",
+        "author_inst": "Nagahama Institute of Bio-Science and Technology"
       },
       {
-        "author_name": "Randeep Guleria",
-        "author_inst": "All India Institute of Medical Sciences"
+        "author_name": "Takashi Abe",
+        "author_inst": "Niigata University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "new results",
-    "category": "genomics"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2022.05.13.491916",
@@ -261979,47 +263033,75 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.05.10.491351",
-    "rel_title": "The SARS-CoV-2 Spike Protein Activates the Epidermal Growth Factor Receptor-Mediated Signaling",
+    "rel_doi": "10.1101/2022.05.12.491597",
+    "rel_title": "Delivery of Circular mRNA via Degradable Lipid Nanoparticles against SARS-COV-2 Delta Variant",
     "rel_date": "2022-05-12",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.10.491351",
-    "rel_abs": "ObjectivesThe coronavirus disease-19 (COVID-19) pandemic is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At the molecular and cellular levels, the SARS-Cov-2 uses its envelope glycoprotein, the spike S protein, to infect the target cells in the lungs via binding with their transmembrane receptor, the angiotensin-converting enzyme 2 (ACE2). Here, we wanted to invesitgate if other molecular targets and pathways may be used by SARS-Cov-2.\n\nMethodsWe investigated the possibility for the spike 1 S protein and its receptor-binding domain (RBD) to target the epidermal growth factor receptor (EGFR) and its downstream signaling pathway in vitro using the lung cancer cell line (A549 cells). Protein expression and phosphorylation was examined upon cell treatment with the recombinant full spike 1 S protein or RBD.\n\nResultsWe demonstrate for the first time the activation of EGFR by the Spike 1 protein associated with the phosphorylation of the canonical ERK1/2 and AKT kinases and an increase of survivin expression controlling the survival pathway.\n\nConclusionsOur study suggests the putative implication of EGFR and its related signaling pathways in SARS-CoV-2 infectivity and Covid-19 pathology. This may open new perspectives in the treatment of Covid-19 patients by targeting EGFR.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.12.491597",
+    "rel_abs": "mRNA vaccines have emerged as a most promising and potent platform in the fight against various diseases including the COVID-19 pandemic. However, the intrinsic instability, varying side effects associated with the delivery systems, and continuous emergence of virus variants highlight the urgent need for the development of stable, safe and efficacious mRNA vaccines. In this study, by screening a panel of proprietary biodegradable ionizable lipidoids, we reported on a novel mRNA vaccine (cmRNA-1130) formed from a biodegradable lipidoid with eight ester bonds in the branched tail (AX4) and synthetic circular mRNA (cmRNA) encoding the trimeric Delta receptor binding domain (RBD) of SARS-CoV-2 spike protein for the induction of robust immune activation. The AX4-based lipid nanoparticles (AX4-LNP) revealed much faster elimination rate from liver and spleen in comparison with commercialized MC3-based LNP (MC3-LNP) and afforded normal level of alanine transferase (ALT), aspartate aminotransferase (AST), and creatinine (CRE) in BALB/c mice. Following intramuscular (IM) administration in BALB/c mice, cmRNA-1130 elicited potent and sustained neutralizing antibodies, RBD-specific CD4+ and CD8+ T effector memory cells (Tem), and Th1-biased T cell activations. cmRNA-1130 vaccine showed excellent stability against 6-month storage at 4 {degrees}C and freezing-thawing cycles. In brief, our study highlights mRNA vaccines based on cmRNA and biodegradable AX4 lipids hold great potential as superb therapeutic platforms for the treatment of varying diseases.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Abdulrasheed Palakkott",
-        "author_inst": "The United Arab Emirates University"
+        "author_name": "Ke Huang",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
       },
       {
-        "author_name": "Aysha Alneyadi",
-        "author_inst": "The United Arab Emirates University"
+        "author_name": "Na Li",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
       },
       {
-        "author_name": "Khalid Muhammad",
-        "author_inst": "The United Arab Emirates University"
+        "author_name": "Yingwen Li",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
       },
       {
-        "author_name": "Eid H Ali",
-        "author_inst": "Qatar University"
+        "author_name": "Jiafeng Zhu",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
+      },
+      {
+        "author_name": "Qianyi Fan",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
       },
       {
-        "author_name": "Khaled Amiri",
-        "author_inst": "The United Arab Emirates University"
+        "author_name": "Jiali Yang",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
       },
       {
-        "author_name": "Mohammed Akli Ayoub",
-        "author_inst": "The United Arab Emirates University"
+        "author_name": "Yinjia Gao",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
       },
       {
-        "author_name": "Rabah Iratni",
-        "author_inst": "The United Arab Emirates University"
+        "author_name": "Yuping Liu",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
+      },
+      {
+        "author_name": "Qiangbo Hou",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
+      },
+      {
+        "author_name": "Shufeng Gao",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
+      },
+      {
+        "author_name": "Ke Wei",
+        "author_inst": "Hunan University of Chinese Medicine"
+      },
+      {
+        "author_name": "Chao Deng",
+        "author_inst": "Soochow University"
+      },
+      {
+        "author_name": "Chijian Zuo",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
+      },
+      {
+        "author_name": "Zhenhua Sun",
+        "author_inst": "Suzhou CureMed Biopharma Technology Co., Ltd."
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "cell biology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2022.05.10.22274813",
@@ -263985,51 +265067,79 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.05.09.22274714",
-    "rel_title": "Mental-health before and during the COVID-19 pandemic in adults with neurodevelopmental disorders.",
+    "rel_doi": "10.1101/2022.05.10.22272976",
+    "rel_title": "Have the COVID-19 Pandemic and Lockdown Affected Children's Mental Health in Long Term? A Repeated Cross-Sectional Study.",
     "rel_date": "2022-05-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.09.22274714",
-    "rel_abs": "The COVID-19 pandemic negatively impacted mental health globally. Individuals with neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), are at elevated risk of mental health difficulties. Therefore, we investigated the impact of the pandemic on anxiety, depression and mental wellbeing in adults with NDDs using longitudinal data from the Avon Longitudinal Study of Parents and Children study (n=3,058). Mental health data were collected pre-pandemic (age 21-25) and at three timepoints during the pandemic (ages 27-28) using the Short Mood and Feelings Questionnaire, Generalised Anxiety Disorder Assessment-7, and Warwick Edinburgh Mental Wellbeing Scale. ADHD and ASD were defined using validated cut-points of the Strengths and Difficulties Questionnaire and Autism Spectrum Quotient, self-reported at age 25. We used multi-level mixed-effects models to investigate changes in mental health in those with ADHD and ASD compared to those without. Prevalences of depression, anxiety and poor mental wellbeing were higher at all timepoints (pre-pandemic and during pandemic) in those with ADHD and ASD compared to those without. Anxiety increased to a greater extent in those with ADHD ({beta}=0.8 [0.2,1.4], p=0.01) and ASD ({beta}=1.2 [-0.1,2.5], p=0.07), while depression symptoms decreased, particularly in females with ASD ({beta}=-3.1 [-4.6,-1.5], p=0.0001). On average, mental wellbeing decreased in all, but to a lesser extent in those with ADHD ({beta}=1.3 [0.2,2.5], p=0.03) and females with ASD ({beta}=3.0 [0.2,5.9], p=0.04). To conclude, anxiety disproportionately increased in adults with NDDs during the pandemic, however, the related lockdowns may have provided a protective environment for depressive symptoms in the same individuals.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.10.22272976",
+    "rel_abs": "ObjectiveThe study aimed to evaluate the impact of the COVID-19 pandemic on levels of anxiety and depressive symptoms in children and adolescents.\n\nDesignCross-sectional surveys were carried out on the mental health of children; one survey was conducted before the COVID-19 pandemic and one into the pandemic, 15 months after the implementation of lockdown, social distancing, and school closures. Demographic data and COVID-19 pandemic-related data were collected from specific parent-report and self-report questionnaires.\n\nParticipantsParticipants included children and adolescents between ages 6-16 years, attending a tertiary care hospital without any diagnosed major psychiatric disorder or chronic disorder.\n\nAnalysisData was collected at two points (before the COVID-19 pandemic and during it) and compared. Levels of anxiety and depressive symptoms were compared and tested for statistically significant differences between these two points using appropriate statistical tests. Regression models were constructed to predict the factors affecting increased anxiety levels and depressive symptoms in the COVID-19 period.\n\nResults832 and 1255 children/adolescents were included in the study during the pre-COVID-19 and COVID-19 times, respectively. The median age of the participants was 10 years [Interquartile Range (IQR) = 4 years). The median (IQR) Spence Childrens Anxiety Scale score was 24 (12) at the pre-COVID-19 point and 31 (13) during the COVID-19 pandemic (p<0.001, r=-0.27). 11% and 16% of children reported being depressed at these two-time points, respectively (p=0.004, {varphi}c=-0.063). Regression analysis showed that many factors, including the duration of smartphone use, female gender, and only child status, were associated with increased anxiety or depression levels.\n\nConclusionA large proportion of children had elevated anxiety and depressive symptoms during the pandemic relative to before the pandemic, suggesting a need for measures to engage children in healthy habits to protect childrens mental health and continuous monitoring of children during such scenarios.\n\nSTRENGTHS AND LIMITATIONSO_LIWith the availability of pre-pandemic data, the repeated cross-sectional study design allowed us to compare the anxiety symptoms and prevalence of depression in children and adolescents during and before the COVID-19 lockdown and school closures.\nC_LIO_LIThe study is one of the few studies from low-to-middle income countries on this topic with large sample size.\nC_LIO_LIThe data was collected hospital setting, and all of the participants were attending a hospital, which could have resulted in a sampling bias. Although it is a tertiary care hospital, all of the patients included in the study came to us for primary care and were not referred.\nC_LIO_LIWe used standardised scales that are usually used for screening and evaluation purposes and not for diagnostic purposes.\nC_LIO_LIWe were unable to perform a longitudinal study with a follow-up that would offer clear evidence of any fluctuation in mental health during the course of the pandemic.\nC_LI",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Amy Shakeshaft",
-        "author_inst": "Cardiff University"
+        "author_name": "Manas Pustake",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
       },
       {
-        "author_name": "Rachel Blakey",
-        "author_inst": "University of Bristol"
+        "author_name": "Sushant Mane",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
       },
       {
-        "author_name": "Alex Siu Fung Kwong",
-        "author_inst": "University of Bristol"
+        "author_name": "Mohammad Arfat Ganiyani",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
       },
       {
-        "author_name": "Lucy Riglin",
-        "author_inst": "Cardiff University"
+        "author_name": "Sayan Mukherjee",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
       },
       {
-        "author_name": "George Davey Smith",
-        "author_inst": "University of Bristol"
+        "author_name": "Misba Sayed",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
       },
       {
-        "author_name": "Evie Stergiakouli",
-        "author_inst": "University of Bristol"
+        "author_name": "Varada Mithbavkar",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
       },
       {
-        "author_name": "Kate Tilling",
-        "author_inst": "University of Bristol"
+        "author_name": "Zaid Memon",
+        "author_inst": "Department of Community Medicine, Mahatma Gandhi Mission Medical College, Navi Mumbai, 410 219, India."
       },
       {
-        "author_name": "Anita Thapar",
-        "author_inst": "Cardiff University"
+        "author_name": "Abdus Samad Momin",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
+      },
+      {
+        "author_name": "Krishna Deshmukh",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
+      },
+      {
+        "author_name": "Ayush Chordia",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
+      },
+      {
+        "author_name": "Sabyasachi Parida",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
+      },
+      {
+        "author_name": "Ajit Bhagwat",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
+      },
+      {
+        "author_name": "Alan Johnson",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
+      },
+      {
+        "author_name": "Deepankar Varma",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
+      },
+      {
+        "author_name": "Sanket Warghade",
+        "author_inst": "Department of Pediatrics, Grant Government Medical College and Sir J.J. Group of Hospitals, Mumbai, 400008, India"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2022.05.09.22274842",
@@ -265739,59 +266849,175 @@
     "category": "health systems and quality improvement"
   },
   {
-    "rel_doi": "10.1101/2022.05.06.22274782",
-    "rel_title": "Post-acute health care burden after SARS-CoV-2 infection: A retrospective cohort study among 530,892 adults",
+    "rel_doi": "10.1101/2022.05.05.22273234",
+    "rel_title": "Changes in English medication safety indicators throughout the COVID-19 pandemic: a federated analysis of 57 million patients' primary care records in situ using OpenSAFELY",
     "rel_date": "2022-05-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.06.22274782",
-    "rel_abs": "ImportanceThe SARS-CoV-2 pandemic portends a significant increase in health care use related to post-acute COVID sequelae, but the magnitude is not known.\n\nObjectiveTo assess the burden of post-acute health care use after a positive versus negative polymerase chain reaction (PCR) test for SARS-CoV-2.\n\nDesign, Setting, and ParticipantsRetrospective cohort study of community-dwelling adults January 1, 2020 to March 31, 2021 in Ontario, Canada, using linked population-based health data. Follow-up began 56 days after PCR testing.\n\nExposuresIndividuals with a positive SARS-CoV-2 PCR test were matched 1:1 to individuals who tested negative based on hospitalization, test date, public health unit, sex, and a propensity score of socio-demographic and clinical characteristics.\n\nMain Outcomes and MeasuresThe health care utilization rate was the number of outpatient clinical encounters, homecare encounters, emergency department visits, days hospitalized, and days in long-term care per person-year. Mean health care utilization for test-positive versus negative individuals was compared using negative binomial regression, and rates at 95th and 99th percentiles were compared. Outcomes were also stratified by sex.\n\nResultsAmong 530,232 unique, matched individuals, mean age was 44 years (sd 17), 51% were female, and 0.6% had received [&ge;]1 COVID-19 vaccine dose. The mean rate of health care utilization was 11% higher in test-positive individuals (RR 1.11, 95% confidence interval [CI] 1.10-1.13). At the 95th percentile, test-positive individuals had 2.1 (95% CI 1.5-2.6) more health care encounters per person-year, and at the 99th percentile 71.9 (95% CI 57.6-83.2) more health care encounters per person-year. At the 95th percentile, test-positive women had 3.8 (95% CI 2.8-4.8) more health care encounters per person-year while there was no difference for men. At the 99th percentile, test-positive women had 76.7 (95% CI 56.3-89.6) more encounters per person-year, compared to 37.6 (95% CI 16.7-64.3) per person-year for men.\n\nConclusions and RelevancePost-acute health care utilization after a positive SARS-CoV-2 PCR test is significantly higher compared to matched test-negative individuals. Given the number of infections worldwide, this translates to a tremendous increase in use of health care resources. Stakeholders can use these findings to prepare for health care demand associated with long COVID.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSHow does the burden of health care use [&ge;]56 days after a positive SARS-CoV-2 polymerase chain reaction (PCR) test compare to matched individuals who tested negative?\n\nFindingsAfter accounting for multiple factors, the mean burden of post-acute health care use was 11% higher among those who tested positive, with higher rates of outpatient encounters, days hospitalized, and days in long-term care. Rates of homecare use were higher for test-positive women but lower for men.\n\nFor perspective, for every day in January 2022 with 100,000 or more infections, this translates to an estimated 72,000 additional post-acute health care encounters per year for the 1% of people who experienced the most severe complications of SARS-CoV-2; among those in the top 50% of health care use, this translates to 245,000 additional health care encounters per year. This increase will occur in the context of an ongoing pandemic and, in many health care systems, a depleted workforce and backlogs of care. Unless addressed, this increase is likely to exacerbate existing health inequities.\n\nMeaningGiven the large number of people infected, stakeholders can use these findings to plan for health care use associated with long COVID.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.05.22273234",
+    "rel_abs": "ObjectiveTo describe the impact of the COVID-19 pandemic on safe prescribing, using the PINCER prescribing indicators; to implement complex prescribing indicators at national scale using GP data.\n\nDesignPopulation based cohort study, with the approval of NHS England using the OpenSAFELY platform.\n\nSettingElectronic health record data from 56.8 million NHS patients general practice records.\n\nParticipantsAll NHS patients registered at a GP practice using TPP or EMIS computer systems and recorded as at risk of at least one potentially hazardous PINCER indicator between September 2019 and September 2021.\n\nMain outcome measureMonthly trends and between-practice variation for compliance with 13 PINCER measures between September 2019 and September 2021.\n\nResultsThe indicators were successfully implemented across GP data in OpenSAFELY. Hazardous prescribing remained largely unchanged during the COVID-19 pandemic, with only small reductions in achievement of the PINCER indicators. There were transient delays in blood test monitoring for some medications, particularly ACE inhibitors. All indicators exhibited substantial recovery by September 2021. We identified 1,813,058 patients at risk of at least one hazardous prescribing event.\n\nConclusionGood performance was maintained during the COVID-19 pandemic across a diverse range of widely evaluated measures of safe prescribing.\n\nSummary box O_TEXTBOXWHAT IS ALREADY KNOWN ON THIS TOPICO_LIPrimary care services were substantially disrupted by the COVID-19 pandemic.\nC_LIO_LIDisruption to safe prescribing during the pandemic has not previously been evaluated.\nC_LIO_LIPINCER is a nationally adopted programme of activities that aims to identify and correct hazardous prescribing in GP practices, by conducting manual audit on subgroups of practices.\nC_LI\n\nWHAT THIS STUDY ADDSO_LIFor the first time, we were able to successfully generate data on PINCER indicators for almost the whole population of England, in a single analysis.\nC_LIO_LIOur study is the most comprehensive assessment of medication safety during the COVID-19 pandemic in England, covering 95% of the population using well-validated measures.\nC_LIO_LIGood performance was maintained across many PINCER indicators throughout the pandemic.\nC_LIO_LIDelays in delivering some medication-related blood test monitoring were evident though considerable recovery was made by the end of the study period.\nC_LI\n\nC_TEXTBOX",
+    "rel_num_authors": 39,
     "rel_authors": [
       {
-        "author_name": "Candace D McNaughton",
-        "author_inst": "ICES, Sunnybrook Research Institute, and University of Toronto"
+        "author_name": "Louis Fisher",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
       },
       {
-        "author_name": "Peter C Augstin",
-        "author_inst": "ICES, Sunnybrook Research Institute, Institute of Health Policy, Management and Evaluation, University of Toronto"
+        "author_name": "Lisa E M Hopcroft",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
       },
       {
-        "author_name": "Atul Sivaswamy",
-        "author_inst": "ICES"
+        "author_name": "Sarah Rodgers",
+        "author_inst": "PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK"
       },
       {
-        "author_name": "Jiming Fang",
-        "author_inst": "ICES"
+        "author_name": "James Barrett",
+        "author_inst": "PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK"
       },
       {
-        "author_name": "Husam Abdel-Qadir",
-        "author_inst": "ICES, Institute of Health Policy, Management and Evaluation, University of Toronto, Peter Munk Cardiac Centre, Toronto General Hospital, Division of Cardiology,"
+        "author_name": "Kerry Oliver",
+        "author_inst": "PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK"
       },
       {
-        "author_name": "Nick Daneman",
-        "author_inst": "ICES, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto"
+        "author_name": "Anthony J Avery",
+        "author_inst": "Centre for Academic Primary Care, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK"
       },
       {
-        "author_name": "Jacob Allan Udell",
-        "author_inst": "Women's College Hospital"
+        "author_name": "Dai Evans",
+        "author_inst": "PRIMIS, School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK"
       },
       {
-        "author_name": "Walter Wodchis",
-        "author_inst": "ICES, Sunnybrook Research Institute"
+        "author_name": "Helen Curtis",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
       },
       {
-        "author_name": "Ivona Mostarac",
-        "author_inst": "Sunnybrook Research Institute"
+        "author_name": "Richard Croker",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Orla Macdonald",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Jessica Morley",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
       },
       {
-        "author_name": "Clare L Atzema",
-        "author_inst": "ICES, Sunnybrook Research Institute, Institute of Health Policy, Management and Evaluation, University of Toronto"
+        "author_name": "Amir Mehrkar",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Seb Bacon",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Simon Davy",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Iain Dillingham",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "David Evans",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "George Hickman",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Peter Inglesby",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Caroline E Morton",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Becky Smith",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Tom Ward",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "William Hulme",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Amelia Green",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Jon Massey",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Alex J Walker",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Chris Bates",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX"
+      },
+      {
+        "author_name": "Jonathan Cockburn",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX"
+      },
+      {
+        "author_name": "John Parry",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX"
+      },
+      {
+        "author_name": "Frank Hester",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX"
+      },
+      {
+        "author_name": "Sam Harper",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX"
+      },
+      {
+        "author_name": "Shaun O'Hanlon",
+        "author_inst": "EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA"
+      },
+      {
+        "author_name": "Alex Eavis",
+        "author_inst": "EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA"
+      },
+      {
+        "author_name": "Richard Jarvis",
+        "author_inst": "EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA"
+      },
+      {
+        "author_name": "Dima Avramov",
+        "author_inst": "EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA"
+      },
+      {
+        "author_name": "Paul Griffiths",
+        "author_inst": "EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA"
+      },
+      {
+        "author_name": "Aaron Fowles",
+        "author_inst": "EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA"
+      },
+      {
+        "author_name": "Nasreen Parkes",
+        "author_inst": "EMIS Health, Fulford Grange, Micklefield Lane, Rawdon, Leeds, LS19 6BA"
+      },
+      {
+        "author_name": "Ben Goldacre",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
+      },
+      {
+        "author_name": "Brian MacKenna",
+        "author_inst": "Bennett Institute of Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "primary care research"
   },
   {
     "rel_doi": "10.1101/2022.05.04.22274667",
@@ -267333,51 +268559,59 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.05.02.22274456",
-    "rel_title": "Change in stroke presentations during COVID-19 pandemic in South-Western Sydney.",
+    "rel_doi": "10.1101/2022.05.04.22274657",
+    "rel_title": "Have infection control and prevention measures resulted in any adverse outcomes for care home and domiciliary care residents and staff?",
     "rel_date": "2022-05-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.02.22274456",
-    "rel_abs": "BackgroundAustralia managed relatively well during the global COVID-19 pandemic owing to our swift mandated public health response. During the NSW lockdown restrictions, we noted a decrease in acute stroke presentations at our institution, similar to what was subsequently reported worldwide.\n\nAimsWe aimed to test our hypothesis that (i) the true numbers of ischaemic strokes did not change, however patients were presenting later and (ii) the proportion of TIAs decreased.\n\nMethodsWe conducted a retrospective audit of all stroke and TIA presentations in 2020 and compared these with data from 2019. We collected information about stroke subtype, severity, time from stroke/TIA onset to presentation and acute reperfusion therapies.\n\nResultsBetween January-February and April-March 2020, there was a 15% drop in acute stroke presentations (128 vs. 109). In the same period \"stroke mimic\" presentations dropped by 22%. The proportion of patients attending the emergency department within 4.5hrs was only 36% compared with 48% over the similar period in 2019.\n\nConclusionsAlthough the raw numbers of ischemic stroke presentations remained stable during NSW Covid lockdown, the proportion of patients presenting within time window for acute reperfusion therapies fell. The number of TIAs similarly fell suggesting COVID-19 discouraged patients from presenting to hospital which placed them at higher risk of disabling stroke. The opportunity cost of lockdown restrictions on stroke outcome should be considered in future policy directives.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.04.22274657",
+    "rel_abs": "TOPLINE SUMMARYO_ST_ABSWhat is a Rapid Review?C_ST_ABSOur rapid reviews use a variation of the systematic review approach, abbreviating or omitting some components to generate the evidence to inform stakeholders promptly whilst maintaining attention to bias. They follow the methodological recommendations and minimum standards for conducting and reporting rapid reviews, including a structured protocol, systematic search, screening, data extraction, critical appraisal and evidence synthesis to answer a specific question and identify key research gaps. They take 1-2 months, depending on the breadth and complexity of the research topic/question(s), the extent of the evidence base and type of analysis required for synthesis.\n\nBackground / Aim of Rapid ReviewCare for older and vulnerable people must sustain core infection prevention and control (IPC) practices and remain vigilant for COVID-19 transmission to prevent virus spread and protect residents and healthcare professionals from severe infections, hospitalisations and death.\n\nHowever, these measures could potentially lead to adverse outcomes such as decreased mental wellbeing in patients and staff. A recent publication by Public Health England examines the effectiveness of IPC practices for reducing COVID-19 transmission in care homes (Duval et al., 2021). We explore evidence relating to adverse outcomes from IPC practices to help inform policy recommendations and identify gaps within the literature where further research can be prioritised.\n\nKey FindingsO_ST_ABSExtent of the evidence baseC_ST_ABSO_LI15 studies were identified: 14 primary studies and one rapid review\nC_LI\n\nRecency of the evidence baseO_LIOf the primary studies, six were published in 2020 and eight were published in 2021\nC_LIO_LIThe rapid review was published in 2021.\nC_LI\n\nSummary of findingsThis rapid review focuses on adverse outcomes resulting from increased IPC measures put in place during the COVID-19 pandemic. Whilst there is some evidence to show that there may be a link between IPC measures and adverse outcomes, causation cannot be assumed.\n\nO_LIDuring the COVID-19 restrictions, the cognition, mental wellbeing and behaviour of residents in care homes were negatively affected\nC_LIO_LIIncreased IPC procedures during the COVID-19 pandemic increased stress and burden among care staff because of increased workload and dilemmas between adhering well to IPC procedures and providing the best care for the care recipients\nC_LIO_LICOVID-19 IPC procedures were not well developed at the beginning of the COVID-19 pandemic, but evidence from 2021 suggests that good adherence to IPC measures can enable visitations by family members and medical professionals into care homes\nC_LIO_LIOnly one study investigating domiciliary care was found. Therefore, it is difficult to make conclusions related specifically to this care setting\nC_LIO_LINo published studies have reported on the costs or cost-effectiveness of IPC measures or have explored the cost implications of adverse outcomes associated with IPC measures\nC_LI\n\nBest quality evidenceOnly one study was deemed as high quality based on the quality appraisal checklist ranking. This was a mixed methods study design (Tulloch et al., 2021).\n\nPolicy ImplicationsSince March 2020, there have been many changes to government guidelines relating to procedures to keep the population safe from COVID-19 harm. Policies vary according to country, even within the UK. Important issues such as care home visitation policies have changed in such a way that care home staff have felt it difficult to keep up with the changes, which in itself increased the burden on those staff. The following implications were identified from this work:\n\nO_LIIPC policies should be clear, concise and tailored to care homes and domiciliary care settings\nC_LIO_LIIncreased attention to workforce planning is needed to ensure adequate staffing and to reduce individual burden\nC_LIO_LIRestrictions (e.g. visitation) for care home residents needs to be balanced by additional psychological support\nC_LIO_LIFurther research with robust methods in this area is urgently needed especially in the domiciliary care setting\nC_LI\n\nStrength of EvidenceOne limitation is the lack of high-quality evidence from the included studies. Confidence in the strength of evidence about adverse outcomes of COVID-19 IPC procedures was rated as  low overall. Whilst the majority of studies achieved a  moderate score based on the quality appraisal tools used, due to the nature of the methods used, the overall quality of evidence is low.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "James Thomas",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Llinos Haf Spencer",
+        "author_inst": "Bangor University"
       },
       {
-        "author_name": "Dennis Cordato",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Ned Hartfiel",
+        "author_inst": "Bangor University"
       },
       {
-        "author_name": "David Manser",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Annie Hendry",
+        "author_inst": "Bangor University"
       },
       {
-        "author_name": "Paul M Middleton",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Bethany Fern Anthony",
+        "author_inst": "Bangor University"
       },
       {
-        "author_name": "Cecilia Cappelen-Smith",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Abraham Makanjuola",
+        "author_inst": "Bangor University"
       },
       {
-        "author_name": "Alan McDougall",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Nathan Bray",
+        "author_inst": "Bangor University"
       },
       {
-        "author_name": "Peter Thomas",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Dyfrig A. Hughes",
+        "author_inst": "Bangor University"
       },
       {
-        "author_name": "Nicholas Moore",
-        "author_inst": "Liverpool Hospital"
+        "author_name": "Clare Wilkinson",
+        "author_inst": "Bangor University"
+      },
+      {
+        "author_name": "Deborah Fitzsimmons",
+        "author_inst": "Swansea University"
+      },
+      {
+        "author_name": "Rhiannon Tudor Edwards",
+        "author_inst": "Bangor University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "neurology"
+    "category": "health systems and quality improvement"
   },
   {
     "rel_doi": "10.1101/2022.05.03.22274592",
@@ -269495,23 +270729,199 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.05.01.490203",
-    "rel_title": "SARS-CoV-2 Main Protease: a Kinetic Approach",
+    "rel_doi": "10.1101/2022.04.30.489997",
+    "rel_title": "BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by Omicron infection",
     "rel_date": "2022-05-02",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.01.490203",
-    "rel_abs": "In this article, I present a new model of the interaction of the main protease (Mpro) from SARS-CoV-2 virus with its substrate. The reaction scheme used to describe this mechanism is an extension of the well-known Michaelis-Menten model proposed in 1913 by Leonor Michaelis and Maud Menten [1]. The model I present here takes into account that one Mpro enzyme monomer interacts with another Mpro monomer in the presence of the substrate, leading to the formation of an enzyme dimer bound to one substrate molecule. Indeed, this dimer is formed by the sequentially binding of one Mpro enzyme monomer to one molecule of substrate, followed by another Mpro enzyme monomer binding to this Mpro-substrate complex. This reaction mechanism is also known in the literature as substrate-induced dimerization [3]. Starting from this new reaction scheme established for this catalytic mechanism, I derived a mathematical expression describing the catalytic rate of the active Mpro enzyme dimer as a function of the substrate concentration [S]. The plot corresponding to this substrate-induced dimerization reaction shows a function f ([S]) that is not monotonic, i.e. not strictly increasing or decreasing, but with a second derivative initially negative and then becoming positive after having passed the Vmax point. This is typically a type of curve showing a phenomenon like the one of substrate inhibition (for instance, inhibition by excess-substrate [7]). The graphical representation of this process shows an interesting behaviour: from zero M/s, the reaction rate increases progressively, similar to the kind of curve described by the Michaelis-Menten model. However, after having reached its maximum catalytic rate, Vmax, the reaction rate decreases progressively as we continue to increase the substrate concentration. I propose an explanation to this interesting behavior. At the moment where Vcat is maximum, we can assume that, in theory, every single substrate molecule in solution is bound to two enzyme monomers (i.e. to one active dimer). The catalytic rate is thus theoretically maximized. At the time where the reaction rate begins to decrease, we observe a new phenomenon that appears: the enzyme monomers begin to be \"diluted\" in the solution containing the excess substrate. The dimers begin to dissociate and to bind increasingly to the substrate as inactive monomers instead of active dimers. Hence, it is more and more unlikely for the enzyme monomers to sequentially bind twice to the same substrate molecule (here, [E] << [S]). Thus, at this stage, the substrate-induced dimerization occurs less often. At the limit, when the substrate is in high excess, there is virtually no more dimerization which occurs. This is one example of excess-substrate inhibition. Furthermore, after having established this fact, I wanted to see if this catalytic behavior was also observed in vitro. Therefore, I conducted an experiment where I measured the catalytic rate of the Mpro dimer for different substrate concentrations. The properties of my substrate construct were such, that I could determine the catalytic rate of the enzyme dimer by directly measuring the spectrophotometric absorbance of the cleaved substrate at{lambda} = 405 nm. The results show explicitly -- within a margin of error -- that the overall shape of the experimental curve looks like the one of the theoretical curve. I thus conclude that the biochemical behavior of the Mpro in vitro follows a new path when it is in contact with its substrate: an excess substrate concentration decreases the activity of the enzyme by the phenomenon of a type of excess-substrate inhibition. This finding could open a new door in the discovery of drugs directed against the Mpro enzyme of the SARS-CoV-2 virus, acting on the inhibition by excess-substrate of the Mpro enzyme, this protein being a key component in the metabolism of the virus. Furthermore, I have established that the maximum of the fitted curve, Vmax, depends only on [E]T and not on [S]. [Formula] exhibits the same dependence pattern. Therefore, if I keep [E]T close to zero, the catalytic rate of the enzyme will also be greatly reduced, which can be understood intuitively. Finally, if we dilute the enzyme sufficiently in the host cell by injecting a suitably high concentration of the octapeptide substrate AVLQSGFR (an inhibitor of the original substrate), this artificial substrate will bind to the \"intermediate\" dimer from the polypeptide and prevent the precursor Mpro from auto-cleaving and dimerizing due to the \"distorted key\" effect of the octapeptide on the \"intermediate\" dimer. The precursor peptide Mpro will auto-cleave to a lesser extent than in the absence of the artificial octapeptide and thus the concentration of the total enzyme [E]T will be lowered in the cell. It would therefore be possible to control the virulence of the virus by adjusting the concentration of the artificial inhibitory octapeptide. However, this is only speculation and has yet to be verified in practice.",
-    "rel_num_authors": 1,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.30.489997",
+    "rel_abs": "SARS-CoV-2 Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility over BA.21. The new variants receptor binding and immune evasion capability require immediate investigation. Here, coupled with Spike structural comparisons, we show that BA.2.12.1 and BA.4/BA.5 exhibit comparable ACE2-binding affinities to BA.2. Importantly, BA.2.12.1 and BA.4/BA.5 display stronger neutralization evasion than BA.2 against the plasma from 3-dose vaccination and, most strikingly, from post-vaccination BA.1 infections. To delineate the underlying antibody evasion mechanism, we determined the escaping mutation profiles2, epitope distribution3 and Omicron neutralization efficacy of 1640 RBD-directed neutralizing antibodies (NAbs), including 614 isolated from BA.1 convalescents. Interestingly, post-vaccination BA.1 infection mainly recalls wildtype-induced humoral memory. The resulting elicited antibodies could neutralize both wildtype and BA.1 and are enriched on non-ACE2-competing epitopes. However, most of these cross-reactive NAbs are heavily escaped by L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1; nevertheless, these NAbs are largely escaped by BA.2/BA.4/BA.5 due to D405N and F486V, and react weakly to pre-Omicron variants, exhibiting poor neutralization breadths. As for therapeutic NAbs, Bebtelovimab4 and Cilgavimab5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, while the S371F, D405N and R408S mutations would undermine most broad sarbecovirus NAbs. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants.",
+    "rel_num_authors": 45,
     "rel_authors": [
       {
-        "author_name": "Thierry Rebetez",
-        "author_inst": "ETHZ"
+        "author_name": "Yunlong Richard Cao",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Ayijiang Yisimayi",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Fanchong Jian",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Weiliang Song",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Tianhe Xiao",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Lei Wang",
+        "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Shuo Du",
+        "author_inst": "School of Life Sciences, Peking University"
+      },
+      {
+        "author_name": "Jing Wang",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Qianqian Li",
+        "author_inst": "Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC)"
+      },
+      {
+        "author_name": "Xiaosu Chen",
+        "author_inst": "Institute for Immunology, College of Life Sciences, Nankai University"
+      },
+      {
+        "author_name": "Yuanling Yu",
+        "author_inst": "Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijin"
+      },
+      {
+        "author_name": "Peng Wang",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Zhiying Zhang",
+        "author_inst": "School of Life Sciences, Peking University"
+      },
+      {
+        "author_name": "Pulan Liu",
+        "author_inst": "School of Life Sciences, Peking University"
+      },
+      {
+        "author_name": "Ran An",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Xiaohua Hao",
+        "author_inst": "Beijing Ditan Hospital, Capital Medical University"
+      },
+      {
+        "author_name": "Yao Wang",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Jing Wang",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Rui Feng",
+        "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Haiyan Sun",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Lijuan Zhao",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Wen Zhang",
+        "author_inst": "Beijing Ditan Hospital, Capital Medical University"
+      },
+      {
+        "author_name": "Dong Zhao",
+        "author_inst": "Beijing Ditan Hospital, Capital Medical University"
+      },
+      {
+        "author_name": "Jiang Zheng",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Lingling Yu",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Can Li",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Na Zhang",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Rui Wang",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Xiao Niu",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Sijie Yang",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
+      },
+      {
+        "author_name": "Xuetao Song",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Yangyang Chai",
+        "author_inst": "Institute for Immunology, College of Life Sciences, Nankai University"
+      },
+      {
+        "author_name": "Ye Hu",
+        "author_inst": "Institute for Immunology, College of Life Sciences, Nankai University"
+      },
+      {
+        "author_name": "Yansong Shi",
+        "author_inst": "Institute for Immunology, College of Life Sciences, Nankai University"
+      },
+      {
+        "author_name": "Linlin Zheng",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Zhiqiang Li",
+        "author_inst": "Peking-Tsinghua Center for Life Sciences, Peking University"
+      },
+      {
+        "author_name": "Qingqing Gu",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Fei Shao",
+        "author_inst": "Changping Laboratory"
+      },
+      {
+        "author_name": "Weijin Huang",
+        "author_inst": "Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC)"
+      },
+      {
+        "author_name": "Ronghua Jin",
+        "author_inst": "Beijing Ditan Hospital, Capital Medical University"
+      },
+      {
+        "author_name": "Zhongyang Shen",
+        "author_inst": "Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University"
+      },
+      {
+        "author_name": "Youchun Wang",
+        "author_inst": "Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC)"
+      },
+      {
+        "author_name": "Xiangxi Wang",
+        "author_inst": "CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Junyu Xiao",
+        "author_inst": "School of Life Sciences, Peking University"
+      },
+      {
+        "author_name": "Xiaoliang Sunney Xie",
+        "author_inst": "Biomedical Pioneering Innovation Center (BIOPIC), Peking University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "biophysics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2022.04.30.486882",
@@ -271357,103 +272767,47 @@
     "category": "bioengineering"
   },
   {
-    "rel_doi": "10.1101/2022.04.28.489942",
-    "rel_title": "Immediate myeloid depot for SARS-CoV-2 in the human lung",
-    "rel_date": "2022-04-29",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.28.489942",
-    "rel_abs": "In the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, considerable focus has been placed on a model of viral entry into host epithelial populations, with a separate focus upon the responding immune system dysfunction that exacerbates or causes disease. We developed a precision-cut lung slice model to investigate very early host-viral pathogenesis and found that SARS-CoV-2 had a rapid and specific tropism for myeloid populations in the human lung. Infection of alveolar macrophages was partially dependent upon their expression of ACE2, and the infections were productive for amplifying virus, both findings which were in contrast with their neutralization of another pandemic virus, Influenza A virus (IAV). Compared to IAV, SARS-CoV-2 was extremely poor at inducing interferon-stimulated genes in infected myeloid cells, providing a window of opportunity for modest titers to amplify within these cells. Endotracheal aspirate samples from humans with the acute respiratory distress syndrome (ARDS) from COVID-19 confirmed the lung slice findings, revealing a persistent myeloid depot. In the early phase of SARS-CoV-2 infection, myeloid cells may provide a safe harbor for the virus with minimal immune stimulatory cues being generated, resulting in effective viral colonization and quenching of the immune system.",
-    "rel_num_authors": 21,
+    "rel_doi": "10.1101/2022.04.26.22274264",
+    "rel_title": "Pilot study on the use of low molecular weight heparins in the prevention of thromboembolic disease during pregnancy and puerperium.",
+    "rel_date": "2022-04-28",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.26.22274264",
+    "rel_abs": "A pregnant woman is 4 to 5 times more likely to suffer a thromboembolic event than a non-pregnant woman. Furthermore, an increase in these episodes has been observed in women infected with SARS-CoV-2. Consequently, the prophylactic prescription of low-molecular-weight heparins (LMWH) in pregnant women is undergoing an increase that has not been evaluated yet. The aim of this study was to determine the prevalence of LMWH prescription in pregnant women at the Hospital Universitario Puerta de Hierro Majadahonda (HUPHM), according to their level of risk and its variation due to SARS-CoV-2 infection. To answer this question, a retrospective cohort of 113 women who gave birth during the month of February at the HUPHM was designed. The level of individual risk of thromboembolism, according to the Royal College guidelines (37a), was calculated with an interview to complete a questionnaire and the analysis of their clinical records. 53.6% of the women were prescribed LMWH as indicated in the guidelines. This high prevalence is explained by the high age of the pregnant women (over 35 years), the wave of the omicron variant (December 2021) and a high rate of cesarean sections (25%). On the other hand, the percentage of patients with COVID-19 was 17.6% but only 53% of them had received LMWH. In conclusion, LMWH is a very common prescription in obstetrics, mostly during puerperium, and has become even more relevant due to the COVID-19 pandemic",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Melia Magnen",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Ran You",
-        "author_inst": "UCSF"
+        "author_name": "Paloma Anchustegui-Mendizabal",
+        "author_inst": "UNIVERSIDAD AUTONOMA MADRID"
       },
       {
-        "author_name": "Arjun A Rao",
-        "author_inst": "UCSF"
+        "author_name": "Patricia Anchustegui-Mendizabal",
+        "author_inst": "UNIVERSIDAD AUTONOMA MADRID"
       },
       {
-        "author_name": "Ryan T Davis",
-        "author_inst": "UCSF"
+        "author_name": "Laura Arechabala-Palacios",
+        "author_inst": "UNIVERSIDAD AUTONOMA DE MADRID"
       },
       {
-        "author_name": "Lauren Rodriguez",
-        "author_inst": "UCSF"
+        "author_name": "Laura Fernandez-Gonzalez",
+        "author_inst": "UNIVERSIDAD AUTONOMA DE MADRID"
       },
       {
-        "author_name": "Camille R Simoneau",
-        "author_inst": "UCSF"
+        "author_name": "Clara Garcia-Gil",
+        "author_inst": "UNIVERSIDAD AUTONOMA DE MADRID"
       },
       {
-        "author_name": "Lisiena Hysenaj",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Kenneth H Hu",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "- The UCSF COMET Consortium",
-        "author_inst": "-"
+        "author_name": "Jesus Miguel Hernandez-Guijo",
+        "author_inst": "UNIVERSIDAD.AUTONOMA DE MADRID"
       },
       {
-        "author_name": "Christina Love",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Prescott G Woodruff",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "David J Erle",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Carolyn M Hendrickson",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Carolyn S Calfee",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Michael A Matthay",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Jeroen P Roose",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Anita Sil",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Melanie Ott",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Charles R Langelier",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Matthew F Krummel",
-        "author_inst": "UCSF"
-      },
-      {
-        "author_name": "Mark R Looney",
-        "author_inst": "UCSF"
+        "author_name": "Oscar Martinez Perez",
+        "author_inst": "Puerta de Hierro University Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "immunology"
+    "license": "cc_by_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "obstetrics and gynecology"
   },
   {
     "rel_doi": "10.1101/2022.04.27.22274357",
@@ -273367,59 +274721,63 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.04.28.489850",
-    "rel_title": "GM-CSF-activated human dendritic cells promote type1 T follicular helper cells (Tfh1) polarization in a CD40-dependent manner",
+    "rel_doi": "10.1101/2022.04.28.489772",
+    "rel_title": "Structural and functional characteristics of SARS-CoV-2 Omicron subvariant BA.2 spike",
     "rel_date": "2022-04-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.28.489850",
-    "rel_abs": "T follicular helper (Tfh) cells are specialized CD4+ T cells that regulate humoral immunity by providing B cell help. Tfh1 sub-population was recently identified and associated with severity in infection and autoimmune diseases. The cellular and molecular requirements to induce human Tfh1 differentiation are unknown. Our work investigated the role of human dendritic cells (DC) in promoting Tfh1 differentiation and their physiopathological implication in mycobacterium tuberculosis and mild COVID-19 infection.\n\nActivated human blood CD1c+ DC were cocultured with allogeneic naive CD4+ T cells. Single-cell RNA sequencing was then used alongside protein validation to define the induced Tfh lineage. DC signature and correlation with Tfh1 cells in infected patients was established through bioinformatic analysis.\n\nOur results show that GM-CSF-activated DC drove the differentiation of Tfh1 cells, displaying typical Tfh molecular features, including 1) high levels of PD-1, CXCR5, and ICOS expression; 2) BCL6 and TBET co-expression; 3) IL-21 and IFN-{gamma} secretion. Mechanistically, GM-CSF triggered the emergence of two distinct DC sub-populations defined by their differential expression of CD40 and ICOS-ligand (ICOS-L), and distinct phenotype, morphology, transcriptomic signature, and function. We showed that Tfh1 differentiation was efficiently and specifically induced by CD40highICOS-Llow DC in a CD40-dependent manner. Tfh1 cells were positively associated with a CD40highICOS-LLow DC signature in patients with latent mycobacterium tuberculosis and mild COVID-19 infection.\n\nOur study uncovers a novel CD40-dependent human Tfh1 axis. Immunotherapy modulation of Tfh1 activity might contribute to control diseases where Tfh1 are known to play a key role, such as infections.\n\nSignificance StatementDendritic cells (DC) play a central role in triggering the adaptive immune response due to their T cell priming functions. Among different T cell subsets, it is still not clear how human type1 T follicular helper cells (Tfh1) differentiate. Tfh1 cells are implicated in several physiopathological conditions, including infections. Here we show that GM-CSF induces diversification of human DC. Only CD40highICOS-LLow DC were able to drive Tfh1 cell differentiation. We found that CD40highICOS-LLow DC signature was associated to Tfh1 cells in mycobacterium tuberculosis and COVID-19 patients. Our data reveal a previously undescribed pathway leading to human Tfh1 cell differentiation and highlight the importance of GM-CSF and CD40 as potential targets for the design of anti-infective therapies.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.28.489772",
+    "rel_abs": "The Omicron subvariant BA.2 has become the dominant circulating strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in many countries. We have characterized structural, functional and antigenic properties of the full-length BA.2 spike (S) protein and compared replication of the authentic virus in cell culture and animal model with previously prevalent variants. BA.2 S can fuse membranes more efficiently than Omicron BA.1, mainly due to lack of a BA.1-specific mutation that may retard the receptor engagement, but still less efficiently than other variants. Both BA.1 and BA.2 viruses replicated substantially faster in animal lungs than the early G614 (B.1) strain in the absence of pre-existing immunity, possibly explaining the increased transmissibility despite their functionally compromised spikes. As in BA.1, mutations in the BA.2 S remodel its antigenic surfaces leading to strong resistance to neutralizing antibodies. These results suggest that both immune evasion and replicative advantage may contribute to the heightened transmissibility for the Omicron subvariants.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Sarantis Korniotis",
-        "author_inst": "University of Paris, Inserm U976 HIPI Unit, Institut de Recherche Saint-Louis, F-75010, Paris, France"
+        "author_name": "Tang Weichun",
+        "author_inst": "United States Food and Drug Administration"
       },
       {
-        "author_name": "Melissa Saichi",
-        "author_inst": "University of Paris, Inserm U976 HIPI Unit, Institut de Recherche Saint-Louis"
+        "author_name": "Christy Lavine",
+        "author_inst": "Beth Israel Deaconess Medical Center"
       },
       {
-        "author_name": "Coline Trichot",
-        "author_inst": "University of Paris, Inserm U976 HIPI Unit, Institut de Recherche Saint-Louis"
+        "author_name": "Haisun Zhu",
+        "author_inst": "Institute for Protein Innovation"
       },
       {
-        "author_name": "Caroline Hoffmann",
-        "author_inst": "Institut Curie, INSERM U932 Research Unit, Immunity and Cancer, F-75005 Paris, France"
+        "author_name": "Krishna Anand",
+        "author_inst": "Institute for Protein Innovation"
       },
       {
-        "author_name": "Elise Amblard",
-        "author_inst": "University of Paris, Inserm U976 HIPI Unit, Institut de Recherche Saint-Louis"
+        "author_name": "Martina Kosikova",
+        "author_inst": "United States Food and Drug Administration"
       },
       {
-        "author_name": "Annick Viguier",
-        "author_inst": "Institut Curie, INSERM U932 Research Unit, Immunity and Cancer, F-75005 Paris, France"
+        "author_name": "Hyung Joon Kwon",
+        "author_inst": "United States Food and Drug Administration"
       },
       {
-        "author_name": "Sophie Grondin",
-        "author_inst": "Institut Curie, INSERM U932 Research Unit, Immunity and Cancer, F-75005 Paris, France"
+        "author_name": "Shaowei Wang",
+        "author_inst": "Codex BioSolutions, Inc."
       },
       {
-        "author_name": "Floriane Noel",
-        "author_inst": "University of Paris, Inserm U976 HIPI Unit, Institut de Recherche Saint-Louis"
+        "author_name": "Megan L. Mayer",
+        "author_inst": "The Harvard Cryo-EM Center for Structural Biology"
       },
       {
-        "author_name": "Hamid Mattoo",
-        "author_inst": "Immunology and Inflammation Therapeutic Area, Sanofi, Cambridge MA, USA"
+        "author_name": "Michael S. Seaman",
+        "author_inst": "Beth Israel Deaconess Medical Center"
       },
       {
-        "author_name": "Vassili Soumelis",
-        "author_inst": "University of Paris, Inserm U976 HIPI Unit, Institut de Recherche Saint-Louis"
+        "author_name": "Jianming Lu",
+        "author_inst": "Codex BioSolutions, Inc."
+      },
+      {
+        "author_name": "Hang Xie",
+        "author_inst": "Center for Biologics Evaluation and Research, US Food and Drug Administration"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.04.28.489537",
@@ -275073,61 +276431,25 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.04.23.22274192",
-    "rel_title": "Excess all-cause mortality across counties in the United States, March 2020 to December 2021",
+    "rel_doi": "10.1101/2022.04.22.22274058",
+    "rel_title": "Coronavirus and incomes: the COVID-19 pandemic dynamics in Africa in February 2022",
     "rel_date": "2022-04-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.23.22274192",
-    "rel_abs": "Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the overall impact of the Covid-19 pandemic that is not biased by differences in testing or cause-of-death assignment. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating and mitigating factors, and inform response efforts, including allocating resources to affected communities. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,159,580 excess deaths occurred during the first two years of the pandemic (first: 620,872; second: 538,708). Overall, excess mortality decreased in large metropolitan counties, but increased in nonmetro counties, between the first and second years of the pandemic. Despite the initial concentration of mortality in large metropolitan Northeast counties, beginning in February 2021, nonmetro South counties had the highest cumulative relative excess mortality. These results highlight the need for investments in rural health as the pandemics disproportionate impact on rural areas continues to grow.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.22.22274058",
+    "rel_abs": "The relative accumulated and daily characteristics of the COVID-19 pandemic dynamics in Africa were used to find links with the gross domestic product per capita (GDP), percentages of fully vaccinated people and daily numbers of tests per case. A simple statistical analysis of datasets corresponding to February 1, 2022 showed that accumulated and daily numbers of cases per capita, daily numbers of deaths per capita and vaccination levels increase with the increase of GDP. As in the case of Europe, the smoothed daily numbers of new cases per capita in Africa increase with the increasing of the vaccination level. But the increase of the accumulated numbers of cases and daily number of deaths with increasing the vaccination level was revealed in Africa. In comparison with Europe, no significant correlation was revealed between the vaccination level and the number of deaths per case. As in the case of Europe, African countries demonstrate no statistically significant links between the pandemic dynamics characteristics and the daily number of tests per case. It looks that countries with very small GDP are less affected by the COVID-19 pandemic. The cause of this phenomenon requires further research, but it is possible that low incomes limit the mobility of the population and reduce the number of contacts with infected people. In order to overcome the pandemic, quarantine measures and social distance should not be neglected (this also applies to countries with a high level of income and vaccination).",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Eugenio Paglino",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Dielle J. Lundberg",
-        "author_inst": "Boston University School of Public Health"
-      },
-      {
-        "author_name": "Zhenwei Zhou",
-        "author_inst": "Boston University School of Public Health"
-      },
-      {
-        "author_name": "Joe A. Wasserman",
-        "author_inst": "RTI International"
-      },
-      {
-        "author_name": "Rafeya Raquib",
-        "author_inst": "Boston University School of Public Health"
-      },
-      {
-        "author_name": "Anneliese N. Luck",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Katherine Hempstead",
-        "author_inst": "The Robert Wood Johnson Foundation"
-      },
-      {
-        "author_name": "Jacob Bor",
-        "author_inst": "Boston University School of Public Health"
-      },
-      {
-        "author_name": "Samuel H. Preston",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Irma T. Elo",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Igor Nesteruk",
+        "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine"
       },
       {
-        "author_name": "Andrew C. Stokes",
-        "author_inst": "Boston University School of Public Health"
+        "author_name": "Oleksii Rodionov",
+        "author_inst": "Private consulting office, Kyiv, Ukraine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -276867,25 +278189,97 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.04.21.22274155",
-    "rel_title": "Usage and awareness of antiviral medications for COVID-19",
+    "rel_doi": "10.1101/2022.04.21.22274082",
+    "rel_title": "COVID-19 patients share common, corticosteroid-independent features of impaired host immunity to pathogenic molds",
     "rel_date": "2022-04-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.21.22274155",
-    "rel_abs": "We surveyed people that recently tested positive for SARS-CoV-2 to assess the frequency and correlates of early treatment seeking behavior. Among high risk respondents, 66.0% were aware of treatment for COVID-19 and 36.3% had sought treatment, however only 1.7% reported use of an antiviral for SARS-CoV-2 infection. More public outreach is needed to raise awareness of the benefits of treatment for COVID-19.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.21.22274082",
+    "rel_abs": "Patients suffering from coronavirus disease-2019 (COVID-19) are at high risk for deadly secondary fungal infections such as COVID-19-associated pulmonary aspergillosis (CAPA) and COVID-19-associated mucormycosis (CAM). Despite this clinical observation, direct experimental evidence for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-driven alterations of antifungal immunity is scarce. Using an ex-vivo whole blood (WB) stimulation assay, we challenged blood from twelve COVID-19 patients with Aspergillus fumigatus and Rhizopus arrhizus antigens and studied the expression of activation, maturation, and exhaustion markers, as well as cytokine secretion. Compared to healthy controls, T-helper cells from COVID-19 patients displayed increased expression levels of the exhaustion marker PD-1 and weakened A. fumigatus- and R. arrhizus-induced activation. While baseline secretion of proinflammatory cytokines was massively elevated, WB from COVID-19 patients elicited diminished release of T-cellular (e.g., IFN-{gamma}, IL-2) and innate immune cell-derived (e.g., CXCL9, CXCL10) cytokines in response to A. fumigatus and R. arrhizus antigens. Additionally, samples from COVID-19 patients showed deficient granulocyte activation by mold antigens and reduced fungal killing capacity of neutrophils. These features of weakened anti-mold immune responses were largely decoupled from COVID-19 severity, the time elapsed since diagnosis of COVID-19, and recent corticosteroid uptake, suggesting that impaired anti-mold defense is a common denominator of the underlying SARS-CoV-2 infection. Taken together, these results expand our understanding of the immune predisposition to post-viral mold infections and could inform future studies of immunotherapeutic strategies to prevent and treat fungal superinfections in COVID-19 patients.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Noah Kojima",
-        "author_inst": "UCLA"
+        "author_name": "Beeke Tappe",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
       },
       {
-        "author_name": "Jeffrey D Klausner",
-        "author_inst": "USC"
+        "author_name": "Chris David Lauruschkat",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Lea Strobel",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Jezreel Pantaleon Garcia",
+        "author_inst": "Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, USA."
+      },
+      {
+        "author_name": "Oliver Kurzai",
+        "author_inst": "Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg, Germany. Leibniz Institute for Natural Product Research and Infection Biology Hans K"
+      },
+      {
+        "author_name": "Silke Rebhan",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Sabrina Kraus",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Elena Pfeuffer-Jovic",
+        "author_inst": "Missionsaerztliche Klinik Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Lydia Bussemer",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Lotte Possler",
+        "author_inst": "Main-Klinik Ochsenfurt, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Matthias Held",
+        "author_inst": "Missionsaerztliche Klinik Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Kerstin Huenniger",
+        "author_inst": "Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg, Germany. Leibniz Institute for Natural Product Research and Infection Biology Hans K"
+      },
+      {
+        "author_name": "Olaf Kniemeyer",
+        "author_inst": "Leibniz Institute for Natural Product Research and Infection Biology Hans Knoell Institute, Jena, Germany."
+      },
+      {
+        "author_name": "Sascha Schaeuble",
+        "author_inst": "Leibniz Institute for Natural Product Research and Infection Biology Hans Knoell Institute, Jena, Germany."
+      },
+      {
+        "author_name": "Axel Brakhage",
+        "author_inst": "Leibniz Institute for Natural Product Research and Infection Biology Hans Knoell Institute, Jena, Germany. Department of Microbiology and Molecular Biology, Ins"
+      },
+      {
+        "author_name": "Gianni Panagiotou",
+        "author_inst": "Leibniz Institute for Natural Product Research and Infection Biology Hans Knoell Institute, Jena, Germany."
+      },
+      {
+        "author_name": "Lewis P. White",
+        "author_inst": "Public Health Wales, Microbiology Cardiff, Wales, UK."
+      },
+      {
+        "author_name": "Hermann Einsele",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Juergen Loeffler",
+        "author_inst": "Department of Internal Medicine II, University Hospital of Wuerzburg, Wuerzburg, Germany."
+      },
+      {
+        "author_name": "Sebastian Wurster",
+        "author_inst": "Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, USA."
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -280233,75 +281627,87 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.04.20.488873",
-    "rel_title": "Uncovering the structural flexibility of SARS-CoV-2 glycoprotein spike variants",
+    "rel_doi": "10.1101/2022.04.20.22274061",
+    "rel_title": "Vaccine effectiveness against SARS-CoV-2 infection and COVID-19-related hospitalization with the Alpha, Delta and Omicron SARS-CoV-2 variants: a nationwide Danish cohort study",
     "rel_date": "2022-04-20",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.20.488873",
-    "rel_abs": "The severe acute respiratory syndrome CoV-2 rapidly spread worldwide, causing a pandemic. After a period of evolutionary stasis, a set of SARS-CoV-2 mutations has arisen in the spike, the leading glycoprotein at the viral envelope and the primary antigenic candidate for vaccines against the 2019 CoV disease (COVID-19). Here, we present comparative biochemical data of the glycosylated full-length ancestral and D614G spike together with three other highly transmissible strains classified by the World Health Organization as variants of concern (VOC): beta, gamma, and delta. By showing that only D614G early variant has less hydrophobic surface exposure and trimer persistence at mid-temperatures, we place D614G with features that support a model of temporary fitness advantage for virus spillover worldwide. Further, during the SARS-CoV-2 adaptation, the spike accumulates alterations leading to less structural rigidity. The decreased trimer stability observed for the ancestral and the gamma strain and the presence of D614G uncoupled conformations mean higher ACE-2 affinities when compared to the beta and delta strains. Mapping the energetic landscape and flexibility of spike variants is necessary to improve vaccine development.",
-    "rel_num_authors": 14,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.20.22274061",
+    "rel_abs": "BackgroundThe continued occurrence of more contagious SARS-CoV-2 variants and waning immunity over time require ongoing re-evaluation of the vaccine effectiveness (VE). This study aimed to estimate the effectiveness in two age groups (12-59 and 60 years or above) of two and three vaccine doses (BNT162b2 mRNA or mRNA-1273 vaccine) by time since vaccination against SARS-CoV-2 infection and COVID-19-related hospitalization in an Alpha, Delta and Omicron dominated period.\n\nMethodsA Danish nationwide cohort study design was used to estimate VE against SARS-CoV-2 infection and COVID-19-related hospitalization with the Alpha, Delta and Omicron variants. Information was obtained from nationwide registries and linked using a unique personal identification number. The study included all residents in Denmark aged 12 years or above (18 years or above for the analysis of three doses) in the Alpha (February 20 to June 15, 2021), Delta (July 4 to November 20, 2021) and Omicron (December 21, 2021 to January 31, 2022) dominated periods. VE estimates including 95% confidence intervals (CIs) were calculated using Cox proportional hazard regression models with adjustments for age, sex and geographical region. Vaccination status was included as a time-varying exposure.\n\nFindingsIn the oldest age group, VE against infection after two doses was 91.0% (95% CI: 88.5; 92.9) for the Alpha variant, 82.2% (95% CI: 75.3; 87.1) for the Delta variant and 39.9% (95% CI: 26.4; 50.9) for the Omicron variant 14-30 days since vaccination. The VE waned over time and was 71.5% (95% CI: 54.7; 82.8), 49.8% (95% CI: 46.5; 52.8) and 4.7% (95% CI: 0.2; 8.9) >120 days since vaccination against the three variants, respectively. Higher estimates were observed after the third dose with VE estimates against infection of 86.0% (Delta, 95% CI: 83.3; 88.3) and 57.6% (Omicron, 95% CI: 55.8; 59.4) 14-30 days since vaccination. Among both age groups, VE against COVID-19-related hospitalization 14-30 days since vaccination with two or three doses was 94.8% or above for the Alpha and Delta variants, whereas among the youngest age group, VE estimates against the Omicron variant after two and three doses were 62.4% (95% CI: 46.3; 73.6) and 89.8% (95% CI: 87.9; 91.3), respectively.\n\nConclusionsTwo vaccine doses provided high protection against SARS-CoV-2 infection and COVID-19-related hospitalization with the Alpha and Delta variants with protection waning over time. Two vaccine doses provided only limited protection against SARS-CoV-2 infection and COVID-19-related hospitalization with the Omicron variant. The third vaccine dose substantially increased the protection against Delta and Omicron.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Hiam  R. S. Arruda",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Mie  Agermose Gram",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Tulio  M. Lima",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Hanne-Dorthe Emborg",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Renata  G. F. Alvim",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Astrid  Blicher Schelde",
+        "author_inst": "SSI: Statens Serum Institut"
+      },
+      {
+        "author_name": "Nikolaj  Ulrik Friis",
+        "author_inst": "SSI: Statens Serum Institut"
+      },
+      {
+        "author_name": "Katrine  Finderup Nielsen",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Fernanda  B. A. Victorio",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Ida  Rask Moustsen-Helms",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Daniel  P. B. Abreu",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Rebecca Legarth",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Federico  F. Marsili",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Janni  Uyen Hoa Lam",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Karen  D. Cruz",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Manon Chaine",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Patricia Sosa-Acosta",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Aisha  Zahoor Malik",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Mauricio Quinones-Vega",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Morten Rasmussen",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Jessica  S. Guedes",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Jannik Fonager",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "F\u00e1bio  C. S. Nogueira",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Raphael  Niklaus Sieber",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Jerson  L. Silva",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Marc Stegger",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Leda  R. Castilho",
-        "author_inst": "Federal University of Rio de Janeiro: Universidade Federal do Rio de Janeiro"
+        "author_name": "Steen Ethelberg",
+        "author_inst": "SSI: Statens Serum Institut"
       },
       {
-        "author_name": "Guilherme  A. P. de Oliveira",
-        "author_inst": "Federal University of Rio de Janeiro"
+        "author_name": "Palle Valentiner-Branth",
+        "author_inst": "SSI: Statens Serum Institut"
+      },
+      {
+        "author_name": "Christian  Holm Hansen",
+        "author_inst": "SSI: Statens Serum Institut"
       }
     ],
     "version": "1",
     "license": "cc_by",
-    "type": "new results",
-    "category": "biochemistry"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.04.14.22273903",
@@ -281839,49 +283245,21 @@
     "category": "cardiovascular medicine"
   },
   {
-    "rel_doi": "10.1101/2022.04.14.22273868",
-    "rel_title": "Effectiveness of Four Vaccines in Preventing SARS-CoV-2 Infection in Kazakhstan",
+    "rel_doi": "10.1101/2022.04.13.22273837",
+    "rel_title": "How did the COVID-19 Pandemic impact self-reported cancer screening rates in 12 Midwestern states?",
     "rel_date": "2022-04-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.14.22273868",
-    "rel_abs": "BACKGROUNDIn February 2021 Kazakhstan began offering COVID-19 vaccines to adults. Breakthrough SARS-CoV-2 infections raised concerns about real-world vaccine effectiveness. We aimed to evaluate effectiveness of four vaccines against SARS-CoV-2 infection.\n\nMETHODSWe conducted a retrospective cohort analysis among adults in Almaty using aggregated vaccination data and individual-level breakthrough COVID-19 cases ([&ge;]14 days from 2nd dose) using national surveillance data. We ran time-adjusted Cox-proportional-hazards model with sensitivity analysis accounting for varying entry into vaccinated cohort to assess vaccine effectiveness for each vaccine (measured as 1-adjusted hazard ratios) using the unvaccinated population as reference (N=565,390). We separately calculated daily cumulative hazards for COVID-19 breakthrough among vaccinated persons by age and vaccine month.\n\nRESULTSFrom February 22 to Sept 1, 2021 in Almaty, 747,558 (57%) adults were fully vaccinated (received 2 doses) and 108,324 COVID-19 cases (11,472 breakthrough) were registered. Vaccine effectiveness against infection was 78% (sensitivity estimates: 74-82%) for QazVac, 77% (72- 81%) for Sputnik V, 71% (69-72%) for Hayat-Vax, and 69% (64-72%) for CoronaVac. Among vaccinated persons, the 90-day follow-up cumulative hazard for breakthrough infection was 2.2%. Cumulative hazard was 2.9% among people aged [&ge;]60 years versus 1.9% among persons aged 18-39 years (p<0.001), and 1.2% for people vaccinated in February-May versus 3.3% in June-August (p<0.001).\n\nCONCLUSIONOur analysis demonstrates high effectiveness of COVID-19 vaccines against infection in Almaty similar to other observational studies. Higher cumulative hazard of breakthrough among people >60 years of age and during variant surges warrants targeted booster vaccination campaigns.\n\nWhat is already known on this topicO_LIPlenty of data are published on effectiveness of mRNA vaccines; however, these vaccines were not widely available in many low- and middle-income countries in 2021.\nC_LIO_LIThere are no real-world effectiveness studies on several vaccines available in the Central Asia region, including QazVac vaccine, an inactivated vaccine developed by Kazakhstan.\nC_LIO_LIUnderstanding how these vaccines are performing outside of clinical trials is critical for the COVID-19 response and lack of published data can contribute to vaccine hesitancy.\nC_LI\n\nWhat this study addsO_LIOur study demonstrated that at the population-level the four vaccines against COVID-19 used in Kazakhstan were effective at preventing SARS-CoV-2 infection.\nC_LIO_LIVaccination reduced the risk of infection by 76% and prevented over 100,000 cases of SARS-CoV-2 infection in Almaty, the countrys most populous city.\nC_LIO_LIThis is also the first study that demonstrated high vaccine effectiveness in real-world conditions of QazVac, developed in Kazakhstan.\nC_LI\n\nHow this study might affect research, practice or policyO_LIPolicy makers in Kazakhstan and the Central Asia region need data on vaccines provided in the region to update evidence-based vaccine guidelines for different populations.\nC_LI",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.13.22273837",
+    "rel_abs": "ObjectiveIn the early months of the COVID-19 pandemic, the U.S. healthcare system reallocated resources to emergency response and mitigation. This reallocation impacted essential healthcare services, including cancer screenings.\n\nMethodsTo examine how the pandemic impacted cancer screenings at the population-level, this study analyzes 2018 and 2020 Behavioral Risk Factor Surveillance System (BRFSS) data to estimate the change in the proportion of eligible adults reporting a recent cancer screen (mammogram, pap smear, colon/sigmoidoscopy, blood stool test). All analyses accounted for response rates and sampling weights, and explored differences by gender and region across 12 Midwestern states.\n\nResultsWe found that the proportion of adult women completing a mammogram declined across all states (-0.9% to -18.1%). The change in colon/sigmoidoscopies, pap smears, and blood stool tests were mixed, ranging from a 9.7% decline in pap smears to a 7.1% increase in blood stool tests. Declines varied considerably between states and within states by gender or metro/urban/rural status.\n\nConclusionsThe COVID-19 pandemic led to delayed breast, cervical, and colorectal cancer detection services. Policymakers should aim to advance cancer control efforts by implementing targeted screening initiatives.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Dilyara NABIROVA",
-        "author_inst": "U.S. Centers for Disease Control and Prevention, Central Asia Regional Office"
-      },
-      {
-        "author_name": "Roberta Horth",
-        "author_inst": "U.S. Centers for Disease Control and Prevention, Central Asia Regional Office"
-      },
-      {
-        "author_name": "Manar Smagul",
-        "author_inst": "Scientific and practical center of sanitary-epidemiological examination and monitoring, branch of the National Center for Public Health, Almaty, Kazakhstan"
-      },
-      {
-        "author_name": "Gaukhar Nukenova",
-        "author_inst": "Scientific and practical center of sanitary-epidemiological examination and monitoring, branch of the National Center for Public Health, Almaty, Kazakhstan"
-      },
-      {
-        "author_name": "Aizhan Yesmagambetova",
-        "author_inst": "Ministry of Healthcare of the Republic of Kazakhstan"
-      },
-      {
-        "author_name": "Daniel Singer",
-        "author_inst": "U.S. Centers for Disease Control and Prevention, Central Asia Regional Office"
-      },
-      {
-        "author_name": "Alden Henderson",
-        "author_inst": "U.S. Centers for Disease Control and Prevention, Atlanta, USA"
-      },
-      {
-        "author_name": "Alexey Tsoy",
-        "author_inst": "Ministry of Healthcare of the Republic of Kazakhstan"
+        "author_name": "Jason Semprini",
+        "author_inst": "University of Iowa"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -283565,51 +284943,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.04.18.22273970",
-    "rel_title": "A comparative analysis of pediatric mental health-related emergency department utilization in Montreal, Canada before and during the COVID-19 pandemic",
-    "rel_date": "2022-04-18",
+    "rel_doi": "10.1101/2022.04.15.22273460",
+    "rel_title": "Coronavirus infection in neonates: Neurodevelopmental outcomes at 18 months of age",
+    "rel_date": "2022-04-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.18.22273970",
-    "rel_abs": "BackgroundReports on longitudinal trends in mental health-related (MHR) emergency department (ED) utilization spanning the pre- and post-pandemic periods are lacking, along with evidence comparing healthcare services utilization by sociodemographic subgroups. The aim of this study was to evaluate COVID-19-associated changes in MHR ED utilization among youth overall and by age, sex, and socioeconomic status (SES).\n\nMethodsThis retrospective cross-sectional study analyzed MHR ED utilization before and during the COVID-19 pandemic at a large urban pediatric tertiary care hospital in Montreal, Canada. All ED visits for children (5-11 years) and adolescents (12-17 years) between April 1, 2016 and November 30, 2021 were included. The main outcome was the monthly count of MHR ED visits. Pre-pandemic and pandemic periods were compared using an interrupted time series design. The effect of seasonality (in months), age (in years), sex (male or female), and SES (low, average, high) were compared using a generalized additive model.\n\nResultsThere were a total of 437,147 ED visits (204,215 unique patients) during the five-year study period of which 9,748 (5.8%) were MHR visits (7,686 unique patients). We observed an increase of 69% (95% CI, +53% to +85%; p = .001) in the mean monthly count of MHR ED visits during the pandemic period, which remained significant after adjusting for seasonality (44% increase, 95% CI, +38% to +51%; p = .001). The chance of presenting for a MHR ED visit increased non-linearly with age. There were increased odds of presenting for a MHR ED visit among girls between the pre-pandemic and pandemic periods (OR 1.42, 95% CI 1.29-1.56). No difference by SES group during and before the COVID-19 pandemic was found (OR 1.01, 95% CI 0.89-1.15 [low]; OR 1.09, 95% CI 0.96-1.25 [high]).\n\nConclusionsOur study shows important increases in MHR ED utilization among youth, and especially among girls, during the first 20 months of the COVID-19 pandemic, highlighting the need for sustained, targeted and scalable mental health resources to support youth mental health during the current and future crises.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.15.22273460",
+    "rel_abs": "BackgroundAlthough most neonates with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections have mild disease, the impact on neurodevelopmental outcomes is unknown. This study aimed to assess 18-month neurodevelopmental outcomes of neonates infected with SARS-CoV-2 infection.\n\nMethodsWe conducted a prospective cohort study of neonates diagnosed with SARS-CoV-2 infection between June 2020-August 2020 through nasopharyngeal coronavirus disease 2019 (COVID-19) PCR testing. A total of 58 neonates were identified from the Kuwait national COVID-19 registry and were enrolled. Historical controls were selected from the neonatal follow-up registry and matched 2:1 based on sex and gestational age. At 18 months of age, neurodevelopmental outcomes were assessed using Bayley Scales of Infant and Toddler Development-3rd Edition (BSID-III) by two trained assessors.\n\nResultsA total of 40 children were diagnosed with SARS-CoV-2 infection and included in the final analysis. The median age at infection was 18 days (range: 10-26 days). Eighteen (45%) were asymptomatic, 15 (37.5%) had a sepsis-like presentation, 5 (12.5%) had respiratory distress and 2 (5%) had a multisystem inflammatory syndrome in children (MIS-C)-like presentation. At 18 months follow up, only one child had severe developmental delay, and one child had a language delay. BSID-III outcomes did not significantly differ between the SARS-CoV-2 infected group and the control group.\n\nConclusionsThere is no difference in neurodevelopmental outcomes in children infected with SARS-CoV-2 infection at 18 months compared to controls, although longer neurodevelopmental follow-up studies are required.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Gabrielle Beaudry",
-        "author_inst": "Department of Psychiatry, University of Oxford, Oxford (UK)"
+        "author_name": "Mariam Ayed",
+        "author_inst": "Farwaniya Hospital"
       },
       {
-        "author_name": "Olivier Drouin",
-        "author_inst": "Sainte-Justine Hospital Research Center, Montreal, Quebec (Canada)"
+        "author_name": "Zainab Alsaffar",
+        "author_inst": "Farwaniya Hospital"
       },
       {
-        "author_name": "Jocelyn Gravel",
-        "author_inst": "Sainte-Justine Hospital Research Center, Montreal, Quebec (Canada)"
+        "author_name": "Zainab Bahzad",
+        "author_inst": "Farwaniya Hospital"
       },
       {
-        "author_name": "Anna Smyrnova",
-        "author_inst": "Sainte-Justine Hospital Research Center, Montreal, Quebec (Canada)"
+        "author_name": "Yasmin Buhamad",
+        "author_inst": "Farwaniya Hospital"
       },
       {
-        "author_name": "Andreas Bender",
-        "author_inst": "Department of Statistics, LMU Munich, Munich (Germany)"
+        "author_name": "Ali Abdulkareem",
+        "author_inst": "Farwaniya Hospital"
       },
       {
-        "author_name": "Massimiliano Orri",
-        "author_inst": "McGill Group for Suicide Studies, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec (Canada)"
+        "author_name": "Alaa AlQattan",
+        "author_inst": "Farwaniya Hospital"
       },
       {
-        "author_name": "Marie-Claude Geoffroy",
-        "author_inst": "McGill Group for Suicide Studies, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec (Canada)"
+        "author_name": "Alia Embaireeg",
+        "author_inst": "Farwaniya Hospital"
       },
       {
-        "author_name": "Nicholas Chadi",
-        "author_inst": "Sainte-Justine Hospital Research Center, Montreal, Quebec (Canada)"
+        "author_name": "Mais Kartam",
+        "author_inst": "Farwaniya Hospital"
+      },
+      {
+        "author_name": "Hessa Alkandari",
+        "author_inst": "Population Health Department, Dasman Diabetes Institute, Kuwait"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2022.04.14.22273413",
@@ -285203,51 +286585,67 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.04.11.22273702",
-    "rel_title": "Making maternity and neonatal care personalised in the COVID-19 pandemic: results from the Babies Born Better Survey in the UK and the Netherlands",
+    "rel_doi": "10.1101/2022.04.15.22273412",
+    "rel_title": "COVID-19 vaccine effectiveness against SARS-CoV-2 infection in the United States prior to the Delta and Omicron-associated surges: a retrospective cohort study of repeat blood donors",
     "rel_date": "2022-04-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.11.22273702",
-    "rel_abs": "Structured abstractO_ST_ABSBackgroundC_ST_ABSThe COVID-19 pandemic had a severe impact on womens birth experiences. To date, there are no studies that use both quantitative and qualitative data to compare womens birth experiences before and during the pandemic, across more than one country.\n\nAimTo examine womens birth experiences during the COVID-19 pandemic and to compare the experiences of women who gave birth in the United Kingdom (UK) or the Netherlands (NL) either before or during the pandemic.\n\nMethodThis study is based on analyses of quantitative and qualitative data from the online Babies Born Better survey. Responses recorded by women giving birth in the UK and the NL between June and December 2020 have been used, encompassing women who gave birth between 2017 and 2020. Quantitative data were analysed descriptively, and chi-squared tests were performed to compare women who gave birth pre- versus during pandemic and separately by country. Qualitative data was analysed by inductive thematic analysis.\n\nFindingsRespondents in both the UK and the NL who gave birth during the pandemic were as likely, or, if they had a self-reported above average standard of life, more likely to rate their labour and birth experience positively when compared to women who gave birth pre-pandemic. This was despite the fact that those labouring in the pandemic reported less support and choice. Two potential explanatory themes emerged from the qualitative data: respondents had lower expectations during the pandemic, and they appreciated that care providers tried hard to personalise care.\n\nConclusionOur study implies that many women labouring during the COVID-19 pandemic experienced restrictions, but their experience was mitigated by staff actions. However, personalised care should not be maintained by the good will of care providers, but should be a priority in maternity care policy to benefit all service users equitably.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.15.22273412",
+    "rel_abs": "To inform public health policy, it is critical to monitor COVID-19 vaccine effectiveness (VE), including against acquiring infection. We estimated VE using a retrospective cohort study among repeat blood donors who donated during the first half of 2021, demonstrating a viable approach for monitoring of VE via serological surveillance. Using Poisson regression, we estimated overall VE was 88.8% (95% CI: 86.2-91.1), adjusted for demographic covariates and variable baseline risk. Time since first reporting vaccination, age, race-ethnicity, region, and calendar time were statistically significant predictors of incident infection. Studies of VE during periods of Delta and Omicron spread are underway.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Lauri  M.M. van den Berg",
-        "author_inst": "Amsterdam UMC Locatie VUmc"
+        "author_name": "Eduard Grebe",
+        "author_inst": "Vitalant Research Institute"
       },
       {
-        "author_name": "Naseerah Akooji",
-        "author_inst": "University of Central Lancashire"
+        "author_name": "Elaine A. Yu",
+        "author_inst": "Vitalant Research Institute"
       },
       {
-        "author_name": "Gill Thomson",
-        "author_inst": "University of Central Lancashire"
+        "author_name": "Marjorie D. Bravo",
+        "author_inst": "Vitalant"
       },
       {
-        "author_name": "Ank de Jonge",
-        "author_inst": "Amsterdam UMC Locatie VUmc"
+        "author_name": "Alex Welte",
+        "author_inst": "Stellenbosch University"
       },
       {
-        "author_name": "Marie-Clare Balaam",
-        "author_inst": "University of Central Lancashire"
+        "author_name": "Roberta L. Bruhn",
+        "author_inst": "Vitalant Research Institute"
       },
       {
-        "author_name": "Anastasia Topalidou",
-        "author_inst": "University of Central Lancashire"
+        "author_name": "Mars Stone",
+        "author_inst": "Vitalant Research Institiute"
       },
       {
-        "author_name": "Soo Downe",
-        "author_inst": "University of Central Lancashire"
+        "author_name": "Valerie Green",
+        "author_inst": "Creative Testing Solutions"
       },
       {
-        "author_name": "the ASPIRE COVID-19 research team",
-        "author_inst": ""
+        "author_name": "Phillip C. Williamson",
+        "author_inst": "Creative Testing Solutions"
+      },
+      {
+        "author_name": "Leora R. Feldstein",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Jefferson M. Jones",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Michael P. Busch",
+        "author_inst": "Vitalant Research Institute"
+      },
+      {
+        "author_name": "Brian Custer",
+        "author_inst": "Vitalant Research Institute"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "obstetrics and gynecology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.04.15.22273449",
@@ -286809,14 +288207,71 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.04.12.22273804",
-    "rel_title": "Nowcasting and Forecasting COVID-19 Waves: The Recursive and Stochastic Nature of Transmission",
+    "rel_doi": "10.1101/2022.04.12.22273761",
+    "rel_title": "Multiplex RT-qPCR assay (N200) to detect and estimate prevalence of multiple SARS-CoV-2 Variants of Concern in wastewater",
     "rel_date": "2022-04-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.12.22273804",
-    "rel_abs": "We propose a parsimonious, yet effective, susceptible-exposed-infected-removed-type model that incorporates the time change in the transmission and death rates. The model is calibrated by Tikhonov-type regularization from official reports from New York City (NYC), Chicago, the State of Sao Paulo, in Brazil, and British Columbia, in Canada. To forecast, we propose different ways to extend the transmission parameter, considering its estimated values. The forecast accuracy is then evaluated using real data from the above referred places. All the techniques accurately provided forecast scenarios for periods 15 days long. One of the models effectively predicted the magnitude of the four waves of infections in NYC, including the one caused by the Omicron variant for periods of 45 days long using out-of-sample data.",
-    "rel_num_authors": 0,
-    "rel_authors": null,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.12.22273761",
+    "rel_abs": "Wastewater-based surveillance (WBS) has become an effective tool around the globe for indirect monitoring of COVID-19 in communities. Quantities of viral fragments of SARS-CoV-2 in wastewater are related to numbers of clinical cases of COVID-19 reported within the corresponding sewershed. Variants of Concern (VOCs) have been detected in wastewater by use of reverse transcription quantitative polymerase chain reaction (RT-qPCR) or sequencing. A multiplex RT-qPCR assay to detect and estimate the prevalence of multiple VOCs, including Omicron/Alpha, Beta, Gamma, and Delta, in wastewater RNA extracts was developed and validated. The probe-based multiplex assay, named \"N200\" focuses on amino acids 199-202, a region of the N gene that contains several mutations that are associated with variants of SARS- CoV-2 within a single amplicon. Each of the probes in the N200 assay are specific to the targeted mutations and worked equally well in single- and multi-plex modes. To estimate prevalence of each VOC, the abundance of the targeted mutation was compared with a non- mutated region within the same amplified region. The N200 assay was applied to monitor frequencies of VOCs in wastewater extracts from six sewersheds in Ontario, Canada collected between December 1, 2021, and January 4, 2022. Using the N200 assay, the replacement of the Delta variant along with the introduction and rapid dominance of the Omicron variant were monitored in near real-time, as they occurred nearly simultaneously at all six locations. The N200 assay is robust and efficient for wastewater surveillance can be adopted into VOC monitoring programs or replace more laborious assays currently being used to monitor SARS- CoV-2 and its VOCs.",
+    "rel_num_authors": 14,
+    "rel_authors": [
+      {
+        "author_name": "Meghan L.M. Fuzzen",
+        "author_inst": "University of Waterloo"
+      },
+      {
+        "author_name": "Nathanael BJ Harper",
+        "author_inst": "University of Waterloo"
+      },
+      {
+        "author_name": "Hadi A Dhiyebi",
+        "author_inst": "University of Waterloo"
+      },
+      {
+        "author_name": "Nivetha Srikanthan",
+        "author_inst": "University of Waterloo"
+      },
+      {
+        "author_name": "Samina Hayat",
+        "author_inst": "University of Waterloo"
+      },
+      {
+        "author_name": "Shelley W Peterson",
+        "author_inst": "National Microbiology Laboratory, Public Health Agency of Canada"
+      },
+      {
+        "author_name": "Ivy Yang",
+        "author_inst": "University of Toronto"
+      },
+      {
+        "author_name": "Jianxian X Sun",
+        "author_inst": "University of Toronto"
+      },
+      {
+        "author_name": "Elizabeth A Edwards",
+        "author_inst": "University of Toronto"
+      },
+      {
+        "author_name": "John P Giesy",
+        "author_inst": "University of Saskatchewan"
+      },
+      {
+        "author_name": "Chand S Mangat",
+        "author_inst": "National Microbiology Laboratory, Public Health Agency of Canada"
+      },
+      {
+        "author_name": "Tyson E Graber",
+        "author_inst": "Children's Hospital of Eastern Ontario Research Institute"
+      },
+      {
+        "author_name": "Robert E Delatolla",
+        "author_inst": "University of Ottawa"
+      },
+      {
+        "author_name": "Mark R Servos",
+        "author_inst": "University of Waterloo"
+      }
+    ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
@@ -288535,69 +289990,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.04.07.22273561",
-    "rel_title": "The effect of the COVID-19 lockdown on mental health care use in South Africa: an interrupted time series analysis",
+    "rel_doi": "10.1101/2022.04.07.22273593",
+    "rel_title": "Inequities in COVID-19 vaccine and booster coverage across Massachusetts ZIP codes: large gaps persist after the 2021/22 Omicron wave",
     "rel_date": "2022-04-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.07.22273561",
-    "rel_abs": "AimsIn March 2020, South Africa introduced a lockdown in response to the COVID-19 pandemic, entailing the suspension of all non-essential activities and a complete ban of tobacco and alcohol sales. We studied the effect of the lockdown on mental health care utilisation rates in private-sector care in South Africa.\n\nMethodsWe did an interrupted time series analysis using insurance claims from January 1, 2017, to June 1, 2020 of beneficiaries 18 years or older from a large private sector medical aid scheme. We calculated weekly outpatient consultation and hospital admission rates for organic mental disorders, substance use disorders, serious mental disorders, depression, anxiety, other mental disorders, any mental disorder, and alcohol withdrawal syndrome. We calculated adjusted odds ratios (OR) for the effect of the lockdown on weekly outpatient consultation and hospital admission rates and the weekly change in rates during the lockdown until June 1, 2020.\n\nResults710,367 persons were followed up for a median of 153 weeks. Hospital admission rates (OR 0.38; 95% CI 0.33-0.44) and outpatient consultation rates (OR 0.74; 95% CI 0.63-0.87) for any mental disorder decreased substantially after the lockdown and did not recover to pre-lockdown levels until June 1, 2020. Health care utilisation rates for alcohol withdrawal syndrome doubled after the introduction of the lockdown, but the statistical uncertainty around the estimates was large (OR 2.24; 95% CI 0.69-7.24).\n\nConclusionsReduced mental health care contact rates during the COVID-19 lockdown likely reflect a substantial unmet need for mental health services with potential long-term consequences for mental health patients and their families. Steps to ensure access and continuity of mental health services during future lockdowns should be considered.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.07.22273593",
+    "rel_abs": "BackgroundInequities in COVID-19 vaccine coverage may contribute to future disparities in morbidity and mortality between Massachusetts (MA) communities.\n\nMethodsWe obtained public-use data on residents vaccinated and boosted by ZIP code (and by age group: 5-19, 20-39, 40-64, 65+) from MA Department of Public Health. We constructed population denominators for postal ZIP codes by aggregating Census-tract population estimates from the 2015-2019 American Community Survey. We excluded non-residential ZIP codes and the smallest ZIP codes containing 1% of the states population. We mapped variation in ZIP-code level primary series vaccine and booster coverage and used regression models to evaluate the association of these measures with ZIP-code-level socioeconomic and demographic characteristics. Because age is strongly associated with COVID-19 severity and vaccine access/uptake, we assessed whether observed socioeconomic and racial inequities persisted after adjusting for age composition and plotted age-specific vaccine and booster coverage by deciles of ZIP-code characteristics.\n\nResultsWe analyzed data on 418 ZIP codes. We observed wide geographic variation in primary series vaccination and booster rates, with marked inequities by ZIP-code-level education, median household income, essential worker share, and racial-ethnic composition. In age-stratified analyses, primary series vaccine coverage was very high among the elderly. However, we found large inequities in vaccination rates among younger adults and children, and very large inequities in booster rates for all age groups. In multivariable regression models, each 10 percentage point increase in \"percent college educated\" was associated with a 5.0 percentage point increase in primary series vaccine coverage and a 4.9 percentage point increase in booster coverage. Although ZIP codes with higher \"percent Black/Latino/Indigenous\" and higher \"percent essential workers\" had lower vaccine coverage, these associations became strongly positive after adjusting for age and education, consistent with high demand for vaccines among Black/Latino/Indigenous and essential worker populations.\n\nConclusionOne year into MAs vaccine rollout, large disparities in COVID-19 primary series vaccine and booster coverage persist across MA ZIP codes.\n\nO_TEXTBOXKey Messages\n\nO_LIAs of March 2022, in the wake of MAs Omicron wave, there were large inequities in ZIP-code-level vaccine and booster coverage by income, education, percent Black/Latino/Indigenous, and percent essential workers.\nC_LIO_LIEducation was the strongest predictor of ZIP-code vaccine coverage in MA.\nC_LIO_LICoverage gaps in ZIP codes with many essential workers and large Black/Latino/Indigenous populations are troubling, as these groups face disproportionate risk for COVID-19 infection and severe illness. However, we found no evidence that \"hesitancy\" drives vaccination gaps. After adjusting for age and education levels, vaccine uptake was higher in ZIP codes with many Black/Latino/Indigenous residents or essential workers.\nC_LIO_LIGaps in vaccine and booster coverage among vulnerable groups may lead to excess morbidity, mortality, and economic losses during the next COVID-19 wave. These burdens will not be equitably shared and are preventable.\nC_LI\n\nC_TEXTBOX",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Anja Elisabeth Wettstein",
-        "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Switzerland and Graduate School for Health Sciences, University of Bern, Switzerland"
-      },
-      {
-        "author_name": "Mpho Tlali",
-        "author_inst": "Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa"
-      },
-      {
-        "author_name": "John A Joska",
-        "author_inst": "HIV Mental Health Research Unit, Department of Psychiatry and Mental Health, Neuroscience Institute, Cape Town, South Africa"
-      },
-      {
-        "author_name": "Morna Cornell",
-        "author_inst": "Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa"
-      },
-      {
-        "author_name": "Veronika W Skrivankova",
-        "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland"
-      },
-      {
-        "author_name": "Soraya Seedat",
-        "author_inst": "Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa"
-      },
-      {
-        "author_name": "Johannes P Mouton",
-        "author_inst": "Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa and Division of Clinical Pharmacology, Department of M"
+        "author_name": "Jacob Bor",
+        "author_inst": "Boston University"
       },
       {
-        "author_name": "Leigh L van den Heuvel",
-        "author_inst": "Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa"
+        "author_name": "Sabrina A Assoumou",
+        "author_inst": "Boston Medical Center"
       },
       {
-        "author_name": "Nicola Maxwell",
-        "author_inst": "Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa"
+        "author_name": "Kevin Lane",
+        "author_inst": "Boston University"
       },
       {
-        "author_name": "Mary-Ann Davies",
-        "author_inst": "Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa"
+        "author_name": "Yareliz Diaz",
+        "author_inst": "Boston University"
       },
       {
-        "author_name": "Gary Maartens",
-        "author_inst": "Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa"
+        "author_name": "Bisola Ojikutu",
+        "author_inst": "Boston Public Health Commission"
       },
       {
-        "author_name": "Matthias Egger",
-        "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Centre for Infectious Disease Epidemiology and Research, University of Cape "
+        "author_name": "Julia Raifman",
+        "author_inst": "Boston University"
       },
       {
-        "author_name": "Andreas D Haas",
-        "author_inst": "Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland"
+        "author_name": "Jonathan I Levy",
+        "author_inst": "Boston University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -290077,87 +291508,107 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.04.07.487520",
-    "rel_title": "Hippo Signaling Pathway Activation during SARS-CoV-2 Infection Contributes to Host Antiviral Response",
+    "rel_doi": "10.1101/2022.04.07.487528",
+    "rel_title": "Cryo-EM structures of SARS-CoV-2 Omicron BA.2 spike",
     "rel_date": "2022-04-08",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.07.487520",
-    "rel_abs": "SARS-CoV-2, responsible for the COVID-19 pandemic, causes respiratory failure and damage to multiple organ systems. The emergence of viral variants poses a risk of vaccine failures and prolongation of the pandemic. However, our understanding of the molecular basis of SARS-CoV-2 infection and subsequent COVID-19 pathophysiology is limited. In this study, we have uncovered a critical role for the evolutionarily conserved Hippo signaling pathway in COVID-19 pathogenesis. Given the complexity of COVID-19 associated cell injury and immunopathogenesis processes, we investigated Hippo pathway dynamics in SARS-CoV-2 infection by utilizing COVID-19 lung samples, and human cell models based on pluripotent stem cell-derived cardiomyocytes (PSC-CMs) and human primary lung air-liquid interface (ALI) cultures. SARS-CoV-2 infection caused activation of the Hippo signaling pathway in COVID-19 lung and in vitro cultures. Both parental and Delta variant of concern (VOC) strains induced Hippo pathway. The chemical inhibition and gene knockdown of upstream kinases MST1/2 and LATS1 resulted in significantly enhanced SARS-CoV-2 replication, indicating antiviral roles. Verteporfin a pharmacological inhibitor of the Hippo pathway downstream transactivator, YAP, significantly reduced virus replication. These results delineate a direct antiviral role for Hippo signaling in SARS-CoV-2 infection and the potential for this pathway to be pharmacologically targeted to treat COVID-19.",
-    "rel_num_authors": 17,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.07.487528",
+    "rel_abs": "The BA.2 sub-lineage of the SARS-CoV-2 Omicron variant has gained in proportion relative to BA.1. As differences in spike (S) proteins may underlie differences in their pathobiology, here we determine cryo-EM structures of a BA.2 S ectodomain and compare these to previously determined BA.1 S structures. BA.2 Receptor Binding Domain (RBD) mutations induced remodeling of the internal RBD structure resulting in its improved thermostability and tighter packing within the 3-RBD-down spike. In the S2 subunit, the fusion peptide in BA.2 was less accessible to antibodies than in BA.1. Pseudovirus neutralization and spike binding assays revealed extensive immune evasion while defining epitopes of two RBD-directed antibodies, DH1044 and DH1193, that bound the outer RBD face to neutralize both BA.1 and BA.2. Taken together, our results indicate that stabilization of the 3-RBD-down state through interprotomer RBD-RBD packing is a hallmark of the Omicron variant, and reveal differences in key functional regions in the BA.1 and BA.2 S proteins.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Gustavo Garcia Jr.",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Victoria Stalls",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Yijie Wang",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Jared Lindenberger",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Joseph Ignatius Irudayam",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Sophie Gobeil",
+        "author_inst": "Duke School of Medicine"
       },
       {
-        "author_name": "Arjit Vijey Jeyachandran",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Rory Henderson",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Sebastian Castillo Cario",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Rob Parks",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Chandani Sen",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Maggie Barr",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Shen Li",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Margaret Deyton",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Yunfeng Li",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Mitchell Martin",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Ashok Kumar",
-        "author_inst": "Wayne State University"
+        "author_name": "Katarzyna Janowska",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Karin Nielsen-Saines",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Xiao Huang",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Samuel W. French",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Aaron May",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Priya S. Shah",
-        "author_inst": "University of California, Davis"
+        "author_name": "Micah Speakman",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Kouki Morizono",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Esther Beaudoin",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Brigitte Gomperts",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Bryan Kraft",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Arjun Deb",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Xiaozhi Lu",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Arunachalam Ramaiah",
-        "author_inst": "University of California, Irvine"
+        "author_name": "Robert J Edwards",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Vaithilingaraja Arumugaswami",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Amanda Eaton",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "David Montefiori",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Wilton Williams",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Kevin Wiehe",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Barton F Haynes",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Priyamvada Acharya",
+        "author_inst": "Duke University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2022.04.08.487623",
@@ -292039,115 +293490,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.04.06.22273080",
-    "rel_title": "Serious underlying medical conditions and COVID-19 vaccine hesitancy.",
+    "rel_doi": "10.1101/2022.04.06.22273512",
+    "rel_title": "Pandemic-EBT and grab-and-go school Meals: Costs, reach, and benefits of two approaches to keep children fed during school closures due to COVID-19",
     "rel_date": "2022-04-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.06.22273080",
-    "rel_abs": "ObjectiveTo examine vaccine uptake, hesitancy and explanatory factors amongst people with serious and/or chronic health conditions, including the impact of underlying disease on attitudes to vaccination.\n\nDesignCross-sectional survey.\n\nSettingTen Australian health services.\n\nParticipants4683 patients (3560 cancer, 842 diabetes and 281 multiple sclerosis) receiving care at the health services participated in the 42-item survey, between June 30 to October 5, 2021.\n\nMain outcome measuresSociodemographic and disease-related characteristics, COVID-19 vaccine uptake, and the scores of three validated scales which measured vaccine hesitancy and vaccine-related beliefs generally and specific to the participants disease, including the Oxford COVID-19 Vaccine Hesitancy Scale, the Oxford COVID-19 Vaccine Confidence and Complacency Scale and the Disease Influenced Vaccine Acceptance Scale. Multivariable logistic regression was used to determine the associations between scale scores and vaccine uptake.\n\nResultsOf all participants, 81.5% reported having at least one COVID-19 vaccine. Unvaccinated status was associated with younger age, female sex, lower education and income, English as a second language, and residence in regional areas (all p<0.05). Unvaccinated participants were more likely to report greater vaccine hesitancy and more negative perceptions toward vaccines (all p<0.05). Disease-related vaccine concerns were associated with unvaccinated status and hesitancy, including greater complacency about COVID-19 infection, and concerns relating to vaccine efficacy and impact on their disease and/or treatment (all p<0.05).\n\nConclusionsDisease-specific concerns impact COVID-19 vaccine-related behaviours and beliefs in people with serious and/or chronic health conditions. This highlights the need to develop targeted strategies and education about COVID-19 vaccination to support medically vulnerable populations and health professionals.\n\nTrial registrationACTRN12621001467820",
-    "rel_num_authors": 24,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.06.22273512",
+    "rel_abs": "ImportanceSchool meals improve nutrition and health for millions of U.S. children. School closures due to the COVID-19 pandemic disrupted childrens access to school meals. Two policy approaches were activated to replace missed meals for children from low-income families. The Pandemic Electronic Benefit Transfer (P-EBT) program provided the cash value of missed meals directly to families on debit-like cards to use for making food purchases. The grab-and-go meals program offered prepared meals from school kitchens at community distribution points. The effectiveness of these programs at reaching those who needed them and their costs were unknown.\n\nObjectiveTo determine how many eligible children were reached by P-EBT and grab-and-go meals, how many meals or benefits were received, and how much each program cost to implement.\n\nDesignCross-sectional study, Spring 2020.\n\nSettingNational.\n\nParticipantsAll children <19 years old and children age 6-18 eligible to receive free or reduced price meals (FRPM).\n\nExposure(s)Receipt of P-EBT or grab-and-go school meals.\n\nMain Outcome(s) and Measure(s)Percentage of children reached by P-EBT and grab-and-go school meals; average benefit received per recipient; and average cost, including implementation costs and time costs to families, per meal distributed.\n\nResultsGrab-and-go school meals reached about 10.5 million children (17% of all US children), most of whom were FRPM-eligible students. Among FRPM-eligible students only, grab-and-go meals reached 27%, compared to 89% reached by P-EBT. Among those receiving benefits, the average monthly benefit was larger for grab-and-go school meals ($148) relative to P-EBT ($110). P-EBT had lower costs per meal delivered - $6.51 - compared to $8.20 for grab- and-go school meals. P-EBT had lower public sector implementation costs but higher uncompensated time costs to families (e.g., preparation time for meals) compared to grab-and-go school meals.\n\nConclusions and RelevanceBoth programs supported childrens access to food when schools were closed and in complementary ways. P-EBT is an efficient and effective policy option to support food access for eligible children when school is out.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSWhat were the operating costs, costs and benefits to families, and proportion of eligible children who received benefits of two programs aimed at replacing school meals missed when schools were closed due to COVID-19?\n\nFindingsIn this cross sectional analysis, we found that the Pandemic-Electronic Benefit Transfer program, in which state agencies sent debit cards loaded with the cash value of missed school meals directly to families, reached nearly all low income students (89%) and cost relatively little per meal provided. In comparison, grab-and-go school meals, in which school food service departments provided prepared meals for offsite consumption, reached 27% of low income children and was associated with larger per meal costs.\n\nMeaningDuring times when children cannot access school meals, state and federal agencies should support cost-efficient programs for schools to distribute prepared meals and activate programs like P-EBT to efficiently reach eligible children.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Daphne Day",
-        "author_inst": "Monash Health"
-      },
-      {
-        "author_name": "Lisa Grech",
-        "author_inst": "Monash University"
-      },
-      {
-        "author_name": "Mike Nguyen",
-        "author_inst": "Monash Health"
-      },
-      {
-        "author_name": "Nathan Bain",
-        "author_inst": "Monash Health"
-      },
-      {
-        "author_name": "Alastair Kwok",
-        "author_inst": "Monash Health"
-      },
-      {
-        "author_name": "Sam Harris",
-        "author_inst": "Bendigo Health"
-      },
-      {
-        "author_name": "Hieu Chau",
-        "author_inst": "Latrobe Regional Hospital"
-      },
-      {
-        "author_name": "Bryan Chan",
-        "author_inst": "Sunshine Coast Hospital and Health Service"
-      },
-      {
-        "author_name": "Richard Blennerhassett",
-        "author_inst": "Central Coast Haematology"
-      },
-      {
-        "author_name": "Louise Nott",
-        "author_inst": "Icon Cancer Centre Hobart"
-      },
-      {
-        "author_name": "Nada Hamad",
-        "author_inst": "St Vincent's Hospital Sydney"
-      },
-      {
-        "author_name": "Annette Tognela",
-        "author_inst": "Campbelltown Hospital"
-      },
-      {
-        "author_name": "David Hoffman",
-        "author_inst": "Dr David Hoffman"
-      },
-      {
-        "author_name": "Amelia McCartney",
-        "author_inst": "Monash Health"
-      },
-      {
-        "author_name": "Kate Webber",
-        "author_inst": "Monash Health"
-      },
-      {
-        "author_name": "Jennifer Wong",
-        "author_inst": "Monash Health"
-      },
-      {
-        "author_name": "Craig Underhill",
-        "author_inst": "Border Medical Oncology"
-      },
-      {
-        "author_name": "Brett Sillars",
-        "author_inst": "Sunshine Coast Hospital and Health Service"
+        "author_name": "Erica L Kenney",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "Antony Winkel",
-        "author_inst": "Sunshine Coast Hospital and Health Service"
+        "author_name": "Lina Pinero Walkinshaw",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Mark Savage",
-        "author_inst": "Bendigo Health"
+        "author_name": "Ye Shen",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "Bao Sheng Loe",
-        "author_inst": "Cambridge University"
+        "author_name": "Sheila E Fleischhacker",
+        "author_inst": "Georgetown University Law Center"
       },
       {
-        "author_name": "Daniel Freeman",
-        "author_inst": "University of Oxford"
+        "author_name": "Jessica Jones-Smith",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Eva Segelov",
-        "author_inst": "Monash Health"
+        "author_name": "Sara N Bleich",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "- CANVACCS, DIABVACCS, and MSVACCS investigators",
-        "author_inst": ""
+        "author_name": "James W Krieger",
+        "author_inst": "University of Washington"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "nutrition"
   },
   {
     "rel_doi": "10.1101/2022.04.04.22273058",
@@ -293761,37 +295144,49 @@
     "category": "pharmacology and therapeutics"
   },
   {
-    "rel_doi": "10.1101/2022.03.29.22273148",
-    "rel_title": "Modeling behavior change and underreporting in the early phase of COVID-19 pandemic in Metro Manila, Philippines",
+    "rel_doi": "10.1101/2022.04.03.22273370",
+    "rel_title": "Automated method to extract and purify RNA from wastewater enables more sensitive detection of SARS-CoV-2 markers in community sewersheds",
     "rel_date": "2022-04-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.29.22273148",
-    "rel_abs": "IntroductionAt the start of the pandemic, the Philippine capital Metro Manila was placed under a strict lockdown termed Enhanced Community Quarantine (ECQ). When ECQ was eased to General Community Quarantine (GCQ) after three months, healthcare systems were soon faced with a surge of COVID-19 cases, putting most facilities at high or critical risk and prompting a return to a stricter policy.\n\nMethodsWe developed a mathematical model considering behavior changes and underreporting to represent the first major epidemic wave in Metro Manila. Key parameters were fitted to the cumulative cases in the capital from March to September 2020. A bi-objective optimization problem was formulated that allows easing of restrictions at an earlier time and minimizes the necessary additional beds to ensure sufficient capacity in healthcare facilities once ECQ was lifted.\n\nResultsIf behavior was changed one to four weeks earlier before GCQ, then the cumulative number of cases can be reduced by up to 55% and the peak delayed by up to four weeks. Increasing the reporting ratio during ECQ threefold may increase the reported cases by 23% but can reduce the total cases, including the unreported, by 61% on June 2020. If GCQ began on May 28, 2020, 48 beds should have been added per day to keep the capacity only at high-risk (75% occupancy). Among the optimal solutions, the peak of cases is lowest if ECQ was lifted on May 20, 2020 and with at least 56 additional beds per day.\n\nConclusionSince infectious diseases are likely to reemerge, the formulated model can be used as a decision support tool to improve existing policies and plan effective strategies that can minimize the socioeconomic impact of strict lockdown measures and ensure adequate healthcare capacity.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.03.22273370",
+    "rel_abs": "Wastewater based epidemiology (WBE) has emerged as a strategy to identify, locate, and manage outbreaks of COVID19, and thereby possibly prevent surges in cases, which overwhelm local to global health care networks. The WBE process is based on assaying municipal wastewater for molecular markers of the SARS-CoV-2 virus. The standard process for sampling municipal wastewater is both time-consuming and requires the handling of large quantities of wastewater, which negatively affect throughput and timely reporting, and can increase safety risks. We report on a method to assay multiple sub-samples of a bulk wastewater sample. We document the effectiveness of this new approach by way of comparison of technologies for automating RNA purification from wastewater samples. We compared processes using the Perkin-Elmer Chemagic 360 to a PEG/NaCl/Qiagen protocol that is used for detection of N1 and N2 SARS-CoV-2 markers by the majority of 19 pandemic wastewater testing labs in the State of Michigan. Specifically, we found that the Chemagic 360 lowered handling time, decreased the amount of wastewater required by 10-fold, increased the amount of RNA isolated per {micro}l of final elution product by approximately five-fold, and had no deleterious effect on subsequent ddPCR analysis. Moreover, for detection of markers on the borderline of detectability, we found that use of the Chemagic 360 enabled the detection of viral markers in a significant number of samples for which the result with the PEG/NaCl/Qiagen method was below the level of detectability. This improvement in detectability of the viral markers might be particularly important for early warning to public health authorities at the beginning of an outbreak.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Victoria May P. Mendoza",
-        "author_inst": "Institute of Mathematics, University of the Philippines Diliman"
+        "author_name": "Nicholas W. West",
+        "author_inst": "Wayne State University"
       },
       {
-        "author_name": "Renier Mendoza",
-        "author_inst": "Institute of Mathematics, University of the Philippines Diliman"
+        "author_name": "Adrian A. Vasquez",
+        "author_inst": "Wayne State University"
       },
       {
-        "author_name": "Youngsuk Ko",
-        "author_inst": "Department of Mathematics, Konkuk University"
+        "author_name": "Azadeh Bahmani",
+        "author_inst": "Wayne State University"
       },
       {
-        "author_name": "Jongmin Lee",
-        "author_inst": "Department of Mathematics, Konkuk University"
+        "author_name": "Mohammed Khan",
+        "author_inst": "Wayne State University"
       },
       {
-        "author_name": "Eunok Jung",
-        "author_inst": "Department of Mathematics, Konkuk University"
+        "author_name": "James Hartrick",
+        "author_inst": "LimnoTech, 501 Avis Dr., Ann Arbor, MI 48108"
+      },
+      {
+        "author_name": "Carrie L. Turner",
+        "author_inst": "LimnoTech, 501 Avis Dr., Ann Arbor, MI 48108"
+      },
+      {
+        "author_name": "William Shuster",
+        "author_inst": "Wayne State University"
+      },
+      {
+        "author_name": "Jeffrey L. Ram",
+        "author_inst": "Wayne State University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -295783,81 +297178,57 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2022.04.02.22273333",
-    "rel_title": "High rate of BA.1, BA.1.1 and BA.2 in triple vaccinated",
+    "rel_doi": "10.1101/2022.03.31.22273111",
+    "rel_title": "Predictors of all-cause mortality among patients hospitalized with influenza, respiratory syncytial virus, or SARS-CoV-2",
     "rel_date": "2022-04-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.02.22273333",
-    "rel_abs": "BackgroundBooster vaccine doses offer protection against severe COVID-19 caused by omicron but are less effective against infection. Characteristics such as serological correlates of protection, viral abundance, and clearance of omicron infection in triple vaccinated individuals are scarce.\n\nMethodsWe conducted a 4-week twice-weekly SARS-CoV-2 qPCR screening shortly after an mRNA vaccine booster in 368 healthcare workers. Spike-specific IgG levels and neutralization titers were determined at study start. qPCR-positive participants were sampled repeatedly for two weeks and monitored for symptoms.\n\nResultIn total 81 (cumulative incidence 22%) omicron infections were detected, divided between BA.1, BA.1.1 and BA.2. Increasing post-booster antibody titers were protective against infection (p<0.05), linked to reduced viral load (p<0.01) and time to viral clearance (p<0.05). Only 10% of infected participants remained asymptomatic through the course of their infection. Viral load peaked at day 3 and live virus could be detected for up to 9 days after first PCR-positive sample. Presence of symptoms correlated to elevated viral load (p<0.0001), but despite resolution of symptoms most participants showed Ct levels <30 at day 9. No significant differences were observed for viral load and time to viral clearance between BA.1, BA.1.1 and BA.2 infected individuals.\n\nConclusionWe report a high incidence of omicron infection despite recent booster vaccination in triple vaccinated individuals. Increasing levels of vaccine-induced spike-specific WT antibodies entail increased protection against infection and reduce viral load if infected. High viral load and secretion of live virus for up to nine days may facilitate transmission in a triple vaccinated population.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273111",
+    "rel_abs": "BackgroundShared and divergent predictors of clinical severity across respiratory viruses may support clinical and community responses in the context of a novel respiratory pathogen.\n\nMethodsWe conducted a retrospective cohort study to identify predictors of 30-day all-cause mortality following hospitalization with influenza (N=45,749; 2011-09 to 2019-05), respiratory syncytial virus (RSV; N=24,345; 2011-09 to 2019-04), or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; N=8,988; 2020-03 to 2020-12; pre-vaccine) using population-based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude, and confidence intervals of risk ratios to identify shared and divergent predictors of mortality.\n\nResults3,186 (7.0%), 697 (2.9%) and 1,880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS-CoV-2, respectively. Shared predictors of increased mortality included: older age, male sex, residence in a long-term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS-CoV-2. Few comorbidities were associated with mortality among patients with SARS-CoV-2 as compared to those with influenza or RSV.\n\nConclusionsOur findings may help identify patients at greatest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local prevention and therapeutic strategies to communities with higher prevalence of risk factors.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Ulrika Marking",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Sebastian Havervall",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Nina Greilert Norin",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Oscar Bladh",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Wanda Christ",
-        "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Max Gordon",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Henry Ng",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
+        "author_name": "Mackenzie A. Hamilton",
+        "author_inst": "MAP Centre for Urban Health Solutions"
       },
       {
-        "author_name": "Kim Blom",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
+        "author_name": "Ying Liu",
+        "author_inst": "ICES"
       },
       {
-        "author_name": "Mia Phillipson",
-        "author_inst": "Department of Medical Cell Biology and SciLifeLab, Uppsala University, Uppsala, Sweden"
+        "author_name": "Andrew Calzavara",
+        "author_inst": "ICES"
       },
       {
-        "author_name": "Sara Mangsbo",
-        "author_inst": "Department of Pharmacy and SciLifeLab, Uppsala University, Uppsala, Sweden"
+        "author_name": "Maria E. Sundaram",
+        "author_inst": "Marshfield Clinic Research Institute"
       },
       {
-        "author_name": "Anna Smed-Sorensen",
-        "author_inst": "Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden."
+        "author_name": "Mohamed Djebli",
+        "author_inst": "ICES"
       },
       {
-        "author_name": "Peter Nilsson",
-        "author_inst": "Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden"
+        "author_name": "Dariya Darvin",
+        "author_inst": "University of Toronto, Department of Medicine"
       },
       {
-        "author_name": "Sophia Hober",
-        "author_inst": "Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden"
+        "author_name": "Stefan Baral",
+        "author_inst": "JHSPH"
       },
       {
-        "author_name": "Mikael Aberg",
-        "author_inst": "Department of Medical Sciences, Clinical Chemistry and SciLifeLab, Uppsala University, Uppsala, Sweden"
+        "author_name": "Rafal Kustra",
+        "author_inst": "Dalla Lana School of Public Health, University of Toronto"
       },
       {
-        "author_name": "Jonas Klingstrom",
-        "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden"
+        "author_name": "Jeffrey C. Kwong",
+        "author_inst": "ICES"
       },
       {
-        "author_name": "Charlotte Thalin",
-        "author_inst": "Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden"
+        "author_name": "Sharmistha Mishra",
+        "author_inst": "University of Toronto"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -297453,67 +298824,23 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2022.03.31.22273262",
-    "rel_title": "Emulation of epidemics via Bluetooth-based virtual safe virus spread: experimental setup, software, and data",
+    "rel_doi": "10.1101/2022.04.01.22273291",
+    "rel_title": "Metabolic alkalosis and mortality in COVID-19",
     "rel_date": "2022-04-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273262",
-    "rel_abs": "We describe an experimental setup and a currently running experiment for evaluating how physical interactions over time and between individuals affect the spread of epidemics. Our experiment involves the voluntary use of the Safe Blues Android app by participants at The University of Auckland (UoA) City Campus in New Zealand. The app spreads multiple virtual safe virus strands via Bluetooth depending on the social and physical proximity of the subjects. The evolution of the virtual epidemics is recorded as they spread through the population. The data is presented as a real-time (and historical) dashboard. A simulation model is applied to calibrate strand parameters. Participants locations are not recorded, but participants are rewarded based on the duration of participation within a geofenced area, and aggregate participation numbers serve as part of the data. Once the experiment is complete, the data will be made available as an open-source anonymized dataset.\n\nThis paper outlines the experimental setup, software, subject-recruitment practices, ethical considerations, and dataset description. The paper also highlights current experimental results in view of the lockdown that started in New Zealand at 23:59 on August 17, 2021. The experiment was initially planned in the New Zealand environment, expected to be free of COVID and lockdowns after 2020. However, a COVID Delta strain lockdown shuffled the cards and the experiment is currently extended into 2022.\n\nAuthor summaryIn this paper, we describe the Safe Blues Android app experimental setup and a currently running experiment at the University of Auckland City Campus. This experiment is designed to evaluate how physical interactions over time and between individuals affect the spread of epidemics.\n\nThe Safe Blues app spreads multiple virtual safe virus strands via Bluetooth based on the subjects unobserved social and physical proximity. The app does not record the participants locations, but participants are rewarded based on the duration of participation within a geofenced area, and aggregate participation numbers serve as part of the data. When the experiment is finished, the data will be released as an open-source anonymized dataset.\n\nThe experimental setup, software, subject recruitment practices, ethical considerations, and dataset description are all described in this paper. In addition, we present our current experimental results in view of the lockdown that started in New Zealand at 23:59 on August 17, 2021. The information we provide here may be useful to other teams planning similar experiments in the future.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.01.22273291",
+    "rel_abs": "BackgroundAs a new infectious disease affecting the world, COVID-19 has caused a huge impact on countries around the world. At present, its specific pathophysiological mechanism has not been fully clarified. We found in the analysis of the arterial blood gas data of critically ill patients that the incidence of metabolic alkalosis in such patients is high.\n\nMethodWe retrospectively analyzed the arterial blood gas analysis results of a total of 16 critically ill patients in the intensive ICU area of Xiaogan Central Hospital and 42 severe patients in the intensive isolation ward, and analyzed metabolic acidosis and respiratory acidosis. Metabolic alkalosis and respiratory alkalosis, and the relationship between metabolic alkalosis and death.\n\nResultAmong the 16 critically ill patients, the incidence of metabolic alkalosis was 100%, while the incidence of metabolic alkalosis in severe patients was 50%; the mortality rate in critically ill patients was 81.3%, and 21.4% in severe patients; The mortality of all patients with metabolic alkalosis is 95.5%,and 4.5% in without metabolic alkalosis.\n\nConclusionThe incidence of metabolic alkalosis in critically ill COVID-19 patients is high, and it is associated with high mortality.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Azam Asanjarani",
-        "author_inst": "The University of Auckland"
-      },
-      {
-        "author_name": "Aminath Shausan",
-        "author_inst": "The University of Queensland"
-      },
-      {
-        "author_name": "Keng Chew",
-        "author_inst": "The University of Queensland"
-      },
-      {
-        "author_name": "Thomas Graham",
-        "author_inst": "The University of Queensland"
-      },
-      {
-        "author_name": "Kirsty R. Short",
-        "author_inst": "The University of Queensland"
-      },
-      {
-        "author_name": "Yoni Nazarathy",
-        "author_inst": "The University of Queensland"
-      },
-      {
-        "author_name": "Shane G. Henderson",
-        "author_inst": "Cornell University"
-      },
-      {
-        "author_name": "Hermanus M. Jansen",
-        "author_inst": "Delft University of Technology"
-      },
-      {
-        "author_name": "Peter G. Taylor",
-        "author_inst": "The University of melbourne"
-      },
-      {
-        "author_name": "Aapeli Vuorinen",
-        "author_inst": "Columbia University"
-      },
-      {
-        "author_name": "Yuvraj Yadav",
-        "author_inst": "Indian Institute of Technology Delhi"
-      },
-      {
-        "author_name": "Ilze Ziedins",
-        "author_inst": "The University of Auckland"
+        "author_name": "Zhifeng Jiang",
+        "author_inst": "Xiaogan Hospital Affiliated to Wuhan University of Science and Technology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.03.31.22273242",
@@ -299427,67 +300754,315 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.03.31.22273226",
-    "rel_title": "Cross-talk between red blood cells and plasma influences blood flow and omics phenotypes in severe COVID-19",
+    "rel_doi": "10.1101/2022.03.30.22273206",
+    "rel_title": "Remdesivir for the treatment of hospitalised patients with COVID-19: final results from the DisCoVeRy randomised, controlled, open-label trial",
     "rel_date": "2022-03-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.31.22273226",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and can affect multiple organs, among which is the circulatory system. Inflammation and mortality risk markers were previously detected in COVID-19 plasma and red blood cells (RBCs) metabolic and proteomic profiles. Additionally, biophysical properties, such as deformability, were found to be changed during the infection. Based on such data, we aim to better characterize RBC functions in COVID-19. We evaluate the flow properties of RBCs in severe COVID-19 patients admitted to the intensive care unit by using in vitro microfluidic techniques and automated methods, including artificial neural networks, for an unbiased RBC analysis. We find strong flow and RBC shape impairment in COVID-19 samples and demonstrate that such changes are reversible upon suspension of COVID-19 RBCs in healthy plasma. Vice versa, healthy RBCs immediately resemble COVID-19 RBCs when suspended in COVID-19 plasma. Proteomics and metabolomics analyses allow us to detect the effect of plasma exchanges on both plasma and RBCs and demonstrate a new role of RBCs in maintaining plasma equilibria at the expense of their flow properties. Our findings provide a framework for further investigations of clinical relevance for therapies against COVID-19 and possibly other infectious diseases.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.30.22273206",
+    "rel_abs": "BackgroundThe antiviral efficacy of remdesivir is still controversial. We aimed at evaluating its clinical effectiveness in hospitalised patients with COVID-19, with indication of oxygen and/or ventilator support. Following prior publication of preliminary results, here we present the final results after completion of data monitoring.\n\nMethodsIn this European multicentre, open-label, parallel-group, randomised, controlled trial (DisCoVeRy, NCT04315948; EudraCT2020-000936-23), participants were randomly allocated to receive usual standard of care (SoC) alone or in combination with remdesivir, lopinavir/ritonavir, lopinavir/ritonavir and IFN-{beta}-1a, or hydroxychloroquine. Adult patients hospitalised with COVID-19 were eligible if they had clinical evidence of hypoxemic pneumonia, or required oxygen supplementation. Exclusion criteria included elevated liver enzyme, severe chronic kidney disease, any contra-indication to one of the studied treatments or their use in the 29 days before randomization, or use of ribavirin, as well as pregnancy or breast-feeding. Here, we report results for remdesivir + SoC versus SoC alone. Remdesivir was administered as 200 mg infusion on day 1, followed by once daily infusions of 100 mg up to 9 days, for a total duration of 10 days. It could be stopped after 5 days if the participant was discharged. Treatment assignation was performed via web-based block randomisation stratified on illness severity and administrative European region. The primary outcome was the clinical status at day 15 measured by the WHO 7-point ordinal scale, assessed in the intention-to-treat population.\n\nFindingsBetween March 22nd, 2020 and January 21st, 2021, 857 participants were randomised to one of the two arms in 5 European countries and 843 participants were included for the evaluation of remdesivir (control, n=423; remdesivir, n=420).\n\nAt day 15, the distribution of the WHO ordinal scale was as follow in the remdesivir and control groups, respectively: Not hospitalized, no limitations on activities: 62/420 (14.8%) and 72/423 (17.0%); Not hospitalized, limitation on activities: 126/420 (30%) and 135/423 (31.9%); Hospitalized, not requiring supplemental oxygen: 56/420 (13.3%) and 31/423 (7.3%); Hospitalized, requiring supplemental oxygen: 75/420 (17.9%) and 65/423 (15.4%); Hospitalized, on non-invasive ventilation or high flow oxygen devices: 16/420 (3.8%) and 16/423 (3.8%); Hospitalized, on invasive mechanical ventilation or ECMO: 64/420 (15.2%) and 80/423 (18.9%); Death: 21/420 (5%) and 24/423 (5.7%). The difference between treatment groups was not statistically significant (OR for remdesivir, 1.02, 95% CI, 0.62 to 1.70, P=0.93). There was no significant difference in the occurrence of Serious Adverse Events between treatment groups (remdesivir, n=147/410, 35.9%, versus control, n=138/423, 32.6%, p=0.29).\n\nInterpretationRemdesivir use for the treatment of hospitalised patients with COVID-19 was not associated with clinical improvement at day 15.\n\nFundingEuropean Union Commission, French Ministry of Health, DIM One Health Ile-de-France, REACTing, Fonds Erasme-COVID-ULB; Belgian Health Care Knowledge Centre (KCE), AGMT gGmbH, FEDER \"European Regional Development Fund\", Portugal Ministry of Health, Portugal Agency for Clinical Research and Biomedical Innovation. Remdesivir was provided free of charge by Gilead.",
+    "rel_num_authors": 74,
     "rel_authors": [
       {
-        "author_name": "Steffen M. Recktenwald",
-        "author_inst": "Saarland University"
+        "author_name": "Florence Ader",
+        "author_inst": "CHU Lyon"
       },
       {
-        "author_name": "Greta Simionato",
-        "author_inst": "Saarland University"
+        "author_name": "Maude Bouscambert Duchamp",
+        "author_inst": "CHU Lyon"
       },
       {
-        "author_name": "Marcelle G.M. Lopes",
-        "author_inst": "Cysmic GmbH"
+        "author_name": "Maya Hites",
+        "author_inst": "CHU Erasme"
       },
       {
-        "author_name": "Fabia Gamboni",
-        "author_inst": "University of Colorado Denver"
+        "author_name": "Nathan Peiffer Smadja",
+        "author_inst": "CHU Bichat"
       },
       {
-        "author_name": "Monika Dzieciatkowska",
-        "author_inst": "University of Colorado Denver"
+        "author_name": "Julien Poissy",
+        "author_inst": "CHU Lille"
       },
       {
-        "author_name": "Patrick Meybohm",
-        "author_inst": "University Hospital Wuerzburg"
+        "author_name": "Drifa Belhadi",
+        "author_inst": "CHU Bichat"
       },
       {
-        "author_name": "Kai Zacharowski",
-        "author_inst": "University Hospital Frankfurt"
+        "author_name": "Alpha Diallo",
+        "author_inst": "ANRS"
       },
       {
-        "author_name": "Andreas von Knethen",
-        "author_inst": "University Hospital Frankfurt"
+        "author_name": "Christelle Delmas",
+        "author_inst": "ANRS"
       },
       {
-        "author_name": "Christian Wagner",
-        "author_inst": "saarland University"
+        "author_name": "Juliette Saillard",
+        "author_inst": "Inserm"
       },
       {
-        "author_name": "Lars Kaestner",
-        "author_inst": "Saarland University"
+        "author_name": "Aline Dechanet",
+        "author_inst": "CHU Bichat"
       },
       {
-        "author_name": "Angelo D'Alessandro",
-        "author_inst": "University of Colorado Denver"
+        "author_name": "Claire Fougerou",
+        "author_inst": "CHU Rennes"
+      },
+      {
+        "author_name": "Minh Patrick Le",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "Gilles Peytavin",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "Noemie Mercier",
+        "author_inst": "ANRS"
+      },
+      {
+        "author_name": "Priyanka Velou",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "Sarah Tubiana",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "Xavier Lescure",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "Emmanuel Faure",
+        "author_inst": "CHU Lille"
+      },
+      {
+        "author_name": "Saad Nseir",
+        "author_inst": "CHU Lille"
+      },
+      {
+        "author_name": "Jean Christophe Richard",
+        "author_inst": "CHU Lyon"
+      },
+      {
+        "author_name": "Florent Wallet",
+        "author_inst": "CHU Lyon"
+      },
+      {
+        "author_name": "Francois Goehringer",
+        "author_inst": "CHU Nancy"
+      },
+      {
+        "author_name": "Benjamin Lefevre",
+        "author_inst": "CHU Nancy"
+      },
+      {
+        "author_name": "Antoine Kimmoun",
+        "author_inst": "CHU Nancy"
+      },
+      {
+        "author_name": "Francois Raffi",
+        "author_inst": "CHU Nantes"
+      },
+      {
+        "author_name": "Bejamin Gaborit",
+        "author_inst": "CHU Nantes"
+      },
+      {
+        "author_name": "Jean Reignier",
+        "author_inst": "CHU Nantes"
+      },
+      {
+        "author_name": "Jean Philippe Lanoix",
+        "author_inst": "CHU Amiens"
+      },
+      {
+        "author_name": "Claire Andrejak",
+        "author_inst": "CHU Amiens"
+      },
+      {
+        "author_name": "Yoann Zerbib",
+        "author_inst": "CHU Amiens"
       },
       {
-        "author_name": "Stephan Quint",
-        "author_inst": "Cysmic GmbH"
+        "author_name": "Firouze Bani Sadr",
+        "author_inst": "CHU Reims"
+      },
+      {
+        "author_name": "Bruno Mourvilliers",
+        "author_inst": "CHU Reims"
+      },
+      {
+        "author_name": "Francois Danion",
+        "author_inst": "CHU Strasbourg"
+      },
+      {
+        "author_name": "Yvon Ruch",
+        "author_inst": "CHU Strasbourg"
+      },
+      {
+        "author_name": "Raphael Clere Jehl",
+        "author_inst": "CHU Strasbourg"
+      },
+      {
+        "author_name": "Vincent Le Moing",
+        "author_inst": "CHU Montpellier"
+      },
+      {
+        "author_name": "Kada Klouche",
+        "author_inst": "CHU Montpellier"
+      },
+      {
+        "author_name": "Karine Lacombe",
+        "author_inst": "CHU Saint Antoine"
+      },
+      {
+        "author_name": "Guillaume Martin Blondel",
+        "author_inst": "CHU Toulouse"
+      },
+      {
+        "author_name": "Fanny Vardon Bounes",
+        "author_inst": "CHU Toulouse"
+      },
+      {
+        "author_name": "Andre Cabie",
+        "author_inst": "CHU Fort de France"
+      },
+      {
+        "author_name": "Jean Marie Turmel",
+        "author_inst": "CHU Fort de France"
+      },
+      {
+        "author_name": "Lionel Piroth",
+        "author_inst": "CHU Dijon"
+      },
+      {
+        "author_name": "Mathieu Blot",
+        "author_inst": "CHU Dijon"
+      },
+      {
+        "author_name": "Elisabeth Botelho Nevers",
+        "author_inst": "CHU Saint Etienne"
+      },
+      {
+        "author_name": "Amandine Gagneux Brunon",
+        "author_inst": "CHU Saint Etienne"
+      },
+      {
+        "author_name": "Guillaume Thiery",
+        "author_inst": "CHU St Etienne"
+      },
+      {
+        "author_name": "Francois Benezit",
+        "author_inst": "CHU Rennes"
+      },
+      {
+        "author_name": "Rostane Gaci",
+        "author_inst": "CHR Mets-Thionville"
+      },
+      {
+        "author_name": "Joy Mootien",
+        "author_inst": "CH Mulhouse"
+      },
+      {
+        "author_name": "Sebastien Gallien",
+        "author_inst": "CHU Mondor"
+      },
+      {
+        "author_name": "Denis Garot",
+        "author_inst": "CHU Tours"
+      },
+      {
+        "author_name": "Kevin Bouiller",
+        "author_inst": "CHU Besancon"
+      },
+      {
+        "author_name": "Loic Epelboin",
+        "author_inst": "CH Cayenne"
+      },
+      {
+        "author_name": "Stephane Jaureguiberry",
+        "author_inst": "CHU Bicetre"
+      },
+      {
+        "author_name": "Alexandre Gaymard",
+        "author_inst": "CHU Lyon"
+      },
+      {
+        "author_name": "Gil Verschelden",
+        "author_inst": "CHU Erasme"
+      },
+      {
+        "author_name": "Sandra Braz",
+        "author_inst": "CHU Lisboa Norte"
+      },
+      {
+        "author_name": "Joao Miguel Ferreira Ribeiro",
+        "author_inst": "CHU Lisboa Norte"
+      },
+      {
+        "author_name": "Michael Joannidis",
+        "author_inst": "CHU Innsbruck"
+      },
+      {
+        "author_name": "Therese Staub",
+        "author_inst": "CHU Luxembourg"
+      },
+      {
+        "author_name": "Antoine Altdorfer",
+        "author_inst": "CHR Citadelle"
+      },
+      {
+        "author_name": "Richard Greil",
+        "author_inst": "CHU Salzburg"
+      },
+      {
+        "author_name": "Alexander Egle",
+        "author_inst": "CHU Salzburg"
+      },
+      {
+        "author_name": "Jeremie Guedj",
+        "author_inst": "Inserm"
+      },
+      {
+        "author_name": "Marion Noret",
+        "author_inst": "CH Annecy Gennevois"
+      },
+      {
+        "author_name": "Roberto Roncon Albuquerque",
+        "author_inst": "CHU Sao Joao"
+      },
+      {
+        "author_name": "Jose Artur Paiva",
+        "author_inst": "CHU Sao Joao"
+      },
+      {
+        "author_name": "Bruno Lina",
+        "author_inst": "CHU Lyon"
+      },
+      {
+        "author_name": "Dominique Costagliola",
+        "author_inst": "Inserm"
+      },
+      {
+        "author_name": "Yazdan Yazdanpanah",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "Charles Burdet",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "France Mentre",
+        "author_inst": "CHU Bichat"
+      },
+      {
+        "author_name": "- DisCoVeRy Study Group",
+        "author_inst": "#N/A"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "hematology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.03.26.22272979",
@@ -301789,115 +303364,119 @@
     "category": "health economics"
   },
   {
-    "rel_doi": "10.1101/2022.03.29.486173",
-    "rel_title": "A mosaic-type trimeric RBD-based COVID-19 vaccine candidate induces potent neutralization against Omicron and other SARS-CoV-2 variants",
+    "rel_doi": "10.1101/2022.03.29.486253",
+    "rel_title": "Discovery of a druggable copper-signaling pathway that drives cell plasticity and inflammation",
     "rel_date": "2022-03-29",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.29.486173",
-    "rel_abs": "Large-scale populations in the world have been vaccinated with COVID-19 vaccines, however, breakthrough infections of SARS-CoV-2 are still growing rapidly due to the emergence of immune-evasive variants, especially Omicron. It is urgent to develop effective broad-spectrum vaccines to better control the pandemic of these variants. Here, we present a mosaic-type trimeric form of spike receptor-binding domain (mos-tri-RBD) as a broad-spectrum vaccine candidate, which carries the key mutations from Omicron and other circulating variants. Tests in rats showed that the designed mos-tri-RBD, whether used alone or as a booster shot, elicited potent cross-neutralizing antibodies against not only Omicron but also other immune-evasive variants. Neutralizing antibody titers induced by mos-tri-RBD were substantially higher than those elicited by homo-tri-RBD (containing homologous RBDs from prototype strain) or the inactivated vaccine BBIBP-CorV. Our study indicates that mos-tri-RBD is highly immunogenic, which may serve as a broad-spectrum vaccine candidate in combating SARS-CoV-2 variants including Omicron.",
-    "rel_num_authors": 24,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.29.486253",
+    "rel_abs": "Inflammation is a complex physiological process triggered in response to harmful stimuli. It involves specialized cells of the immune system able to clear sources of cell injury and damaged tissues to promote repair. Excessive inflammation can occur as a result of infections and is a hallmark of several diseases. The molecular basis underlying inflammatory responses are not fully understood. Here, we show that the cell surface marker CD44, which characterizes activated immune cells, acts as a metal transporter that promotes copper uptake. We identified a chemically reactive pool of copper(II) in mitochondria of inflammatory macrophages that catalyzes NAD(H) redox cycling by activating hydrogen peroxide. Maintenance of NAD+ enables metabolic and epigenetic programming towards the inflammatory state. Targeting mitochondrial copper(II) with a rationally-designed dimer of metformin triggers distinct metabolic and epigenetic states that oppose macrophage activation. This drug reduces inflammation in mouse models of bacterial and viral (SARS-CoV-2) infections, improves well-being and increases survival. Identifying mechanisms that regulate the plasticity of immune cells provides the means to develop next-generation medicine. Our work illuminates the central role of copper as a regulator of cell plasticity and unveils a new therapeutic strategy based on metabolic reprogramming and the control of epigenetic cell states.",
+    "rel_num_authors": 25,
     "rel_authors": [
       {
-        "author_name": "Jing Zhang",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Stephanie Solier",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Zi Bo Han",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Sebastian Muller",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Yu Liang",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Tatiana Caneque",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Xue Feng Zhang",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Antoine Versini",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Yu Qin Jin",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Leeroy Baron",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Li Fang Du",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Pierre Gestraud",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Shuai Shao",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Nicolas Servant",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Hui Wang",
-        "author_inst": "Beijing Institute of Biological Products Company Limited"
+        "author_name": "Laila Emam",
+        "author_inst": "Paris-Saclay"
       },
       {
-        "author_name": "Jun Wei Hou",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Arnaud Mansart",
+        "author_inst": "Paris-Saclay"
       },
       {
-        "author_name": "Ke Xu",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC)"
+        "author_name": "G. Dan Pantos",
+        "author_inst": "University of Bath"
       },
       {
-        "author_name": "Ze Hua Lei",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Vincent Gandon",
+        "author_inst": "Ecole Polytechnique"
       },
       {
-        "author_name": "Zhao Ming Liu",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Valentin Sencio",
+        "author_inst": "University of Lille"
       },
       {
-        "author_name": "Jin Zhang",
-        "author_inst": "Beijing Institute of Biological Products Company Limited"
+        "author_name": "Cyril Robin",
+        "author_inst": "University of Lille"
       },
       {
-        "author_name": "Ya Nan Hou",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Francois Trottein",
+        "author_inst": "University of Lille"
       },
       {
-        "author_name": "Ning Liu",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Anne-Laure Begue",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Fu Jie Shen",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Helene Salmon",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Jin Juan Wu",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Sylvere Durand",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Xiang Zheng",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Ting-Di Wu",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Xin Yu Li",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Nicolas Manel",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Xin Li",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Alain Puisieux",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Wei Jin Huang",
-        "author_inst": "National Institute for Food and Drug Control (NIFDC)"
+        "author_name": "Mark A. Dawson",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Gui Zhen Wu",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC)"
+        "author_name": "Sarah Watson",
+        "author_inst": "Institut Curie"
       },
       {
-        "author_name": "Ji Guo Su",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Guido Kroemer",
+        "author_inst": "Sorbonne University"
       },
       {
-        "author_name": "Qi Ming Li",
-        "author_inst": "National Vaccine and Serum Institute (NVSI)"
+        "author_name": "Djillali Annane",
+        "author_inst": "Hospital Raymond Poincare"
+      },
+      {
+        "author_name": "Raphael Rodriguez",
+        "author_inst": "Institut Curie"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "cell biology"
   },
   {
     "rel_doi": "10.1101/2022.03.29.482838",
@@ -304355,143 +305934,43 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.03.23.485509",
-    "rel_title": "Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq",
+    "rel_doi": "10.1101/2022.03.24.485734",
+    "rel_title": "SARS-CoV-2 harnesses host translational shutoff and autophagy to optimize virus yields: The role of the envelope (E) protein",
     "rel_date": "2022-03-25",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.23.485509",
-    "rel_abs": "Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-Seq for autoantigen discovery, including our previous work (Vazquez et al. 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and finally, mild and severe forms of COVID19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.",
-    "rel_num_authors": 31,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.24.485734",
+    "rel_abs": "The SARS-CoV-2 virion is composed of four structural proteins: spike (S), nucleocapsid (N), membrane (M), and envelope (E). E spans the membrane a single time and is the smallest, yet most enigmatic of the structural proteins. E is conserved among coronaviruses and has an essential role in virus-mediated pathogenesis. We found that ectopic expression of E had deleterious effects on the host cell as it activated stress responses, leading to phosphorylation of the translation initiation factor eIF2 and LC3 lipidation that resulted in host translational shutoff. During infection E is highly expressed although only a small fraction is incorporated into virions, suggesting that E activity is regulated and harnessed by the virus to its benefit. In support of this, we found that the {gamma}1 34.5 protein of herpes simplex virus 1 (HSV-1) prevented deleterious effects of E on the host cell and allowed for E protein accumulation. This observation prompted us to investigate whether other SARS-CoV-2 structural proteins regulate E. We found that the N and M proteins enabled E protein accumulation, whereas S prevented E accumulation. While {gamma}1 34.5 protein prevented deleterious effects of E on the host cells, it had a negative effect on SARS-CoV-2 replication. This negative effect of {gamma}1 34.5 was most likely associated with failure of SARS-CoV-2 to divert the translational machinery and with deregulation of autophagy pathways. Overall, our data suggest that SARS-CoV-2 causes stress responses and subjugates these pathways, including host protein synthesis (phosphorylated eIF2) and autophagy, to support optimal virus production.\n\nImportanceIn 2020, a new {beta}-coronavirus, SARS-CoV-2, entered the human population that has caused a pandemic resulting in 6 million deaths worldwide. Although closely related to SARS-CoV, the mechanisms of SARS-CoV-2 pathogenesis are not fully understood. We found that ectopic expression of the SARS-CoV-2 E protein had detrimental effects on the host cell, causing metabolic alterations including shutoff of protein synthesis and mobilization of cellular resources through autophagy activation. Co-expression of E with viral proteins known to subvert host antiviral responses such as autophagy and translational inhibition, either from SARS-CoV-2 or from heterologous viruses increased cell survival and E protein accumulation. However, such factors were found to negatively impact SARS-CoV-2 infection, as autophagy contributes to formation of viral membrane factories, and translational control offers an advantage for viral gene expression. Overall, SARS-CoV-2 has evolved mechanisms to harness host functions that are essential for virus replication.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Sara E Vazquez",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Sabrina A Mann",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Aaron Bodansky",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Andrew F Kung",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Zoe Quandt",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Elise M N Ferr\u00e9",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Nils Landegren",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Daniel Eriksson",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Paul Bastard",
-        "author_inst": "Rockefeller University"
-      },
-      {
-        "author_name": "Shen-Ying Zhang",
-        "author_inst": "Rockefeller University"
-      },
-      {
-        "author_name": "Jamin Liu",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Anthea Mitchell",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Caleigh Mandel-Brehm",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Brenda Miao",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Gavin Sowa",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Kelsey Zorn",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Alice Y Chan",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Chisato Shimizu",
-        "author_inst": "UC San Diego Health System"
-      },
-      {
-        "author_name": "Adriana Tremoulet",
-        "author_inst": "UC San Diego Health System"
-      },
-      {
-        "author_name": "Kara Lynch",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Michael R Wilson",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Olle K\u00e4mpe",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Kerry Dobbs",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Ottavia M Delmonte",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Luigi D Notarangelo",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
-      },
-      {
-        "author_name": "Jane C Burns",
-        "author_inst": "UC San Diego Health System"
+        "author_name": "Hope Waisner",
+        "author_inst": "University of Kansas Medical Center"
       },
       {
-        "author_name": "Jean-Laurent Casanova",
-        "author_inst": "Rockefeller University"
+        "author_name": "Brandon Grieshaber",
+        "author_inst": "University of Kansas Medical Center"
       },
       {
-        "author_name": "Michail S Lionakis",
-        "author_inst": "National Institute of Allergy and Infectious Diseases"
+        "author_name": "Rabina Saud",
+        "author_inst": "University of Kansas Medical Center"
       },
       {
-        "author_name": "Troy R Torgerson",
-        "author_inst": "Allen Institute for Immunology"
+        "author_name": "Wyatt Henke",
+        "author_inst": "University of Kansas Medical Center"
       },
       {
-        "author_name": "Mark S Anderson",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Edward Brice Stephens",
+        "author_inst": "University of Kansas Medical Center"
       },
       {
-        "author_name": "Joseph L DeRisi",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Maria Kalamvoki",
+        "author_inst": "University of Kansas Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.03.24.485222",
@@ -305837,43 +307316,59 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.03.24.22272835",
-    "rel_title": "Relative Effectiveness of Four Doses Compared to Three Dose of the BNT162b2 Vaccine in Israel",
+    "rel_doi": "10.1101/2022.03.24.22272892",
+    "rel_title": "The modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm) patient-reported outcome measure for Long Covid or Post-COVID syndrome",
     "rel_date": "2022-03-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.24.22272835",
-    "rel_abs": "ObjectivesThe rapid spread of the Omicron variant (B.1.1.529) alongside evidence of a relatively rapid waning of the third dose prompted Israel to administer a fourth dose of the BNT162b2 vaccine on January 2022. Thus far, sufficient real-world evidence demonstrating the effectiveness of a fourth dose against infection and severe COVID-19 are lacking. This study examined the short-term effectiveness of a fourth dose compared to three doses over the span of 10 weeks.\n\nDesignA retrospective test-negative case-control study, performing both a matched analysis and an unmatched multiple-tests analysis.\n\nSettingNationally centralized database of Maccabi Healthcare Services (MHS), an Israeli national health fund that covers 2.5 million people.\n\nParticipantsThe study population included 97,499 MHS members aged 60 or older who were eligible to receive a fourth vaccine dose and performed at least one PCR test during the study period. Of them, 27,876 received the fourth dose and 69,623 received only three doses.\n\nMain outcomes and measuresAnalyses focused on the period from January 10, 2022 (7 days after the fourth dose was first administered to eligible individuals) to March 13, 2022, an Omicron-dominant period in Israel. We evaluated two SARS-CoV-2-related outcomes: (1) breakthrough infection, defined as a positive PCR test performed 7 or more days after inoculation with the BNT162b2 vaccine; and (2) breakthrough infection resulting in a severe disease, defined as COVID-19-related hospitalization or COVID-19 associated mortality.\n\nResultsA fourth dose provided considerable additional protection against both SARS-CoV-2 infection and severe disease relative to three doses of the vaccine. However, vaccine effectiveness against infection varied over time, peaking during the third week with a VE of 64% (95% CI: 62.0%-65.9%) and declining to 29.2% (95% CI: 17.7%-39.1%) by the end of the 10-week follow-up period. Unlike VE against infection, the relative effectiveness of a fourth dose against severe COVID-19 was maintained at high level (>73%) throughout the 9-week follow-up period. Importantly, severe disease was a relatively rare event, occurring in <1% of both fourth dose and third dose only recipients.\n\nConclusionsA fourth dose of the BNT162b2 vaccine provided considerable additional protection against both SARS-CoV-2 infection and severe disease relative to three doses of the vaccine. However, effectiveness of the fourth dose against infection wanes sooner than that of the third dose.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.24.22272892",
+    "rel_abs": "BackgroundThe C19-YRS was the first validated scale reported in the literature for patient assessment and monitoring in Long Covid or Post-COVID syndrome. The 22-item scale contains four subscales measuring symptom severity, functional disability, overall health and additional symptoms.\n\nObjectivesThis study aimed to modify and refine the scale based on psychometric properties, emerging evidence on additional Long Covid symptoms, and feedback from a working group of patients and healthcare professionals.\n\nMethodsData were collected from 370 patients who completed the C19-YRS scale in a community Long COVID service. The psychometric properties of the Symptom Severity and Functional Disability subscales were assessed using a Rasch Measurement Theory framework, where all individual scale items were assessed for model fit, local dependency, response category functioning and differential item functioning (DIF) by age group and sex. Additionally, the subscales were assessed for targeting, reliability and unidimensionality. The overall health subscale is a single item, and the additional symptoms subscale is not intended to be summed, therefore neither is appropriate for Rasch analyses. Psychometric results and implications were relayed back to the working group for discussion, alongside clinical evidence of emerging and relevant symptoms not covered by the original C19-YRS.\n\nResultsRasch analysis revealed promising psychometric properties of the symptom severity and functional disability subscales, with both displaying good targeting and reliability, although some individual measurement anomalies were noted. The original 0-10 item response category structure did not operate as intended for both the subscales. Post-hoc rescoring suggested that a 4-point response category structure would be more appropriate for both the subscales, and this aligned with patient feedback. This scoring change was implemented, alongside changes in the item composition of the symptom severity and additional symptoms subscales. The functional disability item set, and the overall health single-item subscale remained unchanged.\n\nConclusionA modified version of the C19-YRS was developed based on a combination of psychometric evidence, clinical relevance of the content and feedback from the working group (comprising patients and healthcare professionals). Future studies including NIHR funded LOCOMOTION study will undertake large-scale, multi-centre validation of the modified C19-YRS.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Sivan Gazit",
-        "author_inst": "Maccabi Healthcare Services"
+        "author_name": "Manoj Sivan",
+        "author_inst": "University of Leeds"
       },
       {
-        "author_name": "Yaki Saciuk",
-        "author_inst": "Maccabi Healthcare Services"
+        "author_name": "Nick J Preston",
+        "author_inst": "University of Leeds"
       },
       {
-        "author_name": "Galit Perez",
-        "author_inst": "Maccabi health care servises"
+        "author_name": "Amy Parkin",
+        "author_inst": "Leeds Teaching Hospitals NHS Trust"
       },
       {
-        "author_name": "Asaf Peretz",
-        "author_inst": "Maccabi Healthcare Services"
+        "author_name": "Sophie Makower",
+        "author_inst": "Leeds Community Healthcare NHS Trust"
       },
       {
-        "author_name": "Virginia E. Pitzer",
-        "author_inst": "Yale School of Public Health"
+        "author_name": "Jeremy Gee",
+        "author_inst": "Airedale Hospitals NHS Trust"
       },
       {
-        "author_name": "Tal Patalon",
-        "author_inst": "Maccabi Healthcare Services"
+        "author_name": "Denise Ross",
+        "author_inst": "Leeds Teaching Hospitals NHS Trust"
+      },
+      {
+        "author_name": "Rachel Tarrant",
+        "author_inst": "Leeds Community Healthcare NHS Trust"
+      },
+      {
+        "author_name": "Jennifer Davison",
+        "author_inst": "Leeds Community Healthcare NHS Trust"
+      },
+      {
+        "author_name": "Stephen Halpin",
+        "author_inst": "University of Leeds"
+      },
+      {
+        "author_name": "Mike Horton",
+        "author_inst": "University of Leeds"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "rehabilitation medicine and physical therapy"
   },
   {
     "rel_doi": "10.1101/2022.03.24.22272883",
@@ -307819,135 +309314,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.03.23.22272804",
-    "rel_title": "Waning effectiveness of BNT162b2 and ChAdOx1 COVID-19 vaccines over six months since second dose: a cohort study using linked electronic health records",
+    "rel_doi": "10.1101/2022.03.21.22272358",
+    "rel_title": "Undiagnosed COVID-19 in households with a child with mitochondrial disease",
     "rel_date": "2022-03-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.23.22272804",
-    "rel_abs": "BackgroundThe rate at which COVID-19 vaccine effectiveness wanes over time is crucial for vaccination policies, but is incompletely understood with conflicting results from different studies.\n\nMethodsThis cohort study, using the OpenSAFELY-TPP database and approved by NHS England, included individuals without prior SARS-CoV-2 infection assigned to vaccines priority groups 2-12 defined by the UK Joint Committee on Vaccination and Immunisation. We compared individuals who had received two doses of BNT162b2 or ChAdOx1 with unvaccinated individuals during six 4-week comparison periods, separately for subgroups aged 65+ years; 16-64 years and clinically vulnerable; 40-64 years and 18-39 years. We used Cox regression, stratified by first dose eligibility and geographical region and controlled for calendar time, to estimate adjusted hazard ratios (aHRs) comparing vaccinated with unvaccinated individuals, and quantified waning vaccine effectiveness as ratios of aHRs per-4-week period. The outcomes were COVID-19 hospitalisation, COVID-19 death, positive SARS-CoV-2 test, and non-COVID-19 death.\n\nFindingsThe BNT162b2, ChAdOx1 and unvaccinated groups comprised 1,773,970, 2,961,011 and 2,433,988 individuals, respectively. Waning of vaccine effectiveness was similar across outcomes and vaccine brands: e.g. in the 65+ years subgroup ratios of aHRs versus unvaccinated for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test ranged from 1.23 (95% CI 1.15-1.32) to 1.27 (1.20-1.34) for BNT162b2 and 1.16 (0.98-1.37) to 1.20 (1.14-1.27) for ChAdOx1. Despite waning, rates of COVID-19 hospitalisation and COVID-19 death were substantially lower among vaccinated individuals compared to unvaccinated individuals up to 26 weeks after second dose, with estimated aHRs <0.20 (>80% vaccine effectiveness) for BNT162b2, and <0.26 (>74%) for ChAdOx1. By weeks 23-26, rates of SARS-CoV-2 infection in fully vaccinated individuals were similar to or higher than those in unvaccinated individuals: aHRs ranged from 0.85 (0.78-0.92) to 1.53 (1.07-2.18) for BNT162b2, and 1.21 (1.13-1.30) to 1.99 (1.94-2.05) for ChAdOx1.\n\nInterpretationThe rate at which estimated vaccine effectiveness waned was strikingly consistent for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test, and similar across subgroups defined by age and clinical vulnerability. If sustained to outcomes of infection with the Omicron variant and to booster vaccination, these findings will facilitate scheduling of booster vaccination doses.",
-    "rel_num_authors": 29,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.21.22272358",
+    "rel_abs": "BackgroundThe impact of the COVID-19 pandemic on medically fragile populations, who are at higher risk of severe illness and sequelae, has not been well characterized. Viral infection is a major cause of morbidity in children with mitochondrial disease (MtD), and the COVID-19 pandemic represents an opportunity to study this vulnerable population.\n\nMethodsA convenience sampling cross-sectional serology study was conducted (October 2020 to June 2021) in households (N = 20) containing a child with MtD (N = 22). Samples (N = 83) were collected in the home using a microsampling apparatus and shipped to investigators. Antibodies against SARS-CoV-2 nucleocapsid (IgG), spike protein (IgG, IgM, IgA), and receptor binding domain (IgG, IgM, IgA) were determined by enzyme linked immunosorbent assay.\n\nResultsWhile only 4.8% of participants were clinically diagnosed for SARS-CoV-2 infection, 75.9% of study participants were seropositive for SARS-CoV-2 antibodies. Most samples were IgM positive for spike or RBD (70%), indicating that infection was recent. This translated to all 20 families showing evidence of infection in at least one household member. For the children with MtD, 91% had antibodies against SARS-CoV-2 and had not experienced any adverse outcomes at the time of assessment. For children with recent infections (IgM+ only), serologic data suggest household members as a source.\n\nConclusionsCOVID-19 was highly prevalent and undiagnosed in households with a child with MtD through the 2020-2021 winter wave of the pandemic. In this first major wave, children with MtD tolerated SARS-CoV-2 infection well, potentially due to household adherence to CDC recommendations for risk mitigation.\n\nFundingThis study was funded by the Intramural Research Program of the National Institutes of Health (HG200381-03).\n\nClinical trial numberNCT04419870",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Elsie MF Horne",
-        "author_inst": "University of Bristol"
-      },
-      {
-        "author_name": "William J Hulme",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Ruth H Keogh",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Tom M Palmer",
-        "author_inst": "University of Bristol"
-      },
-      {
-        "author_name": "Elizabeth J Williamson",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Edward PK Parker",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Amelia Green",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Venexia Walker",
-        "author_inst": "University of Bristol"
-      },
-      {
-        "author_name": "Alex J Walker",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Helen Curtis",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Louis Fisher",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Brian MacKenna",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Richard Croker",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Lisa Hopcroft",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Robin Y Park",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Jon Massey",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Jessica Morely",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Amir Mehrkar",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Sebastian Bacon",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "David Evans",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Peter Inglesby",
-        "author_inst": "Univeristy of Oxford"
-      },
-      {
-        "author_name": "Caroline E Morton",
-        "author_inst": "Univeristy of Oxford"
+        "author_name": "Eliza M. Gordon-Lipkin",
+        "author_inst": "National Human Genome Research Institute, National Institutes of Health"
       },
       {
-        "author_name": "George Hickman",
-        "author_inst": "Univeristy of Oxford"
+        "author_name": "Christopher Marcum",
+        "author_inst": "National Institute of Allergy and Infectious Disease, National Institutes of Health"
       },
       {
-        "author_name": "Simon Davy",
-        "author_inst": "Univeristy of Oxford"
+        "author_name": "Shannon Kruk",
+        "author_inst": "National Human Genome Research Institute, National Institutes of Health"
       },
       {
-        "author_name": "Tom Ward",
-        "author_inst": "Univeristy of Oxford"
+        "author_name": "Elizabeth Thompson",
+        "author_inst": "National Human Genome Research Institute, National Institutes of Health"
       },
       {
-        "author_name": "Iain Dillingham",
-        "author_inst": "Univeristy of Oxford"
+        "author_name": "Sophie E.M. Kelly",
+        "author_inst": "National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health"
       },
       {
-        "author_name": "Ben Goldacre",
-        "author_inst": "Univeristy of Oxford"
+        "author_name": "Heather Kalish",
+        "author_inst": "National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health"
       },
       {
-        "author_name": "Miguel A Hernan",
-        "author_inst": "Harvard University"
+        "author_name": "Kaitlyn Sadtler",
+        "author_inst": "National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health"
       },
       {
-        "author_name": "Jonathan AC Sterne",
-        "author_inst": "University of Bristol"
+        "author_name": "Peter McGuire",
+        "author_inst": "NIH"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2022.03.21.22271747",
@@ -309605,31 +311016,159 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.03.21.485157",
-    "rel_title": "Stability and expression of SARS-CoV-2 spike-protein mutations",
+    "rel_doi": "10.1101/2022.03.20.485044",
+    "rel_title": "Robust and durable prophylactic protection conferred by RNA interference in preclinical models of SARS-CoV-2",
     "rel_date": "2022-03-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.21.485157",
-    "rel_abs": "Protein fold stability likely plays a role in SARS-CoV-2 S-protein evolution, together with ACE2 binding and antibody evasion. While few thermodynamic stability data are available for S-protein mutants, many systematic experimental data exist for their expression. In this paper, we explore whether such expression levels relate to the thermodynamic stability of the mutants. We studied mutation-induced SARS-CoV-2 S-protein fold stability, as computed by three very distinct methods and eight different protein structures to account for method- and structure-dependencies. For all methods and structures used (24 comparisons), computed stability changes correlate significantly (99% confidence level) with experimental yeast expression from the literature, such that higher expression is associated with relatively higher fold stability. Also significant, albeit weaker, correlations were seen for ACE2 binding. The effect of thermodynamic fold stability may be direct or a correlate of amino acid or site properties, notably the solvent exposure of the site. Correlation between computed stability and experimental expression and ACE2 binding suggests that functional properties of the SARS-CoV-2 S-protein mutant space are largely determined by a few simple features, due to underlying correlations. Our study lends promise to the development of computational tools that may ideally aid in understanding and predicting SARS-CoV-2 S-protein evolution.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.20.485044",
+    "rel_abs": "RNA interference is a natural antiviral mechanism that could be harnessed to combat SARS-CoV-2 infection by targeting and destroying the viral genome. We screened lipophilic small-interfering RNA (siRNA) conjugates targeting highly conserved regions of the SARS-CoV-2 genome and identified leads targeting outside of the spike-encoding region capable of achieving [&ge;]3-log viral reduction. Serial passaging studies demonstrated that a two-siRNA combination prevented development of resistance compared to a single-siRNA approach. A two-siRNA combination delivered intranasally protected Syrian hamsters from weight loss and lung pathology by viral infection upon prophylactic administration but not following onset of infection. Together, the data support potential utility of RNAi as a prophylactic approach to limit SARS-CoV-2 infection that may help combat emergent variants, complement existing interventions, or protect populations where vaccines are less effective. Most importantly, this strategy has implications for developing medicines that may be valuable in protecting against future coronavirus pandemics.",
+    "rel_num_authors": 35,
     "rel_authors": [
       {
-        "author_name": "Kristoffer T Baek",
-        "author_inst": "Technical University of Denmark"
+        "author_name": "Yesseinia I Anglero-Rodriguez",
+        "author_inst": "Alnylam Pharmaceuticals"
       },
       {
-        "author_name": "Rukmankesh Mehra",
-        "author_inst": "Indian Institute of Technology Bhilai"
+        "author_name": "Florian A Lempp",
+        "author_inst": "VIR Biotechnology"
       },
       {
-        "author_name": "Kasper Planeta Kepp",
-        "author_inst": "Technical University of Denmark"
+        "author_name": "James McIninch",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Mark K Schlegel",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Christopher R Brown",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Donald J Foster",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Adam B Castoreno",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Tuyen Nguyen",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Megha Subramanian",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Martin Montiel-Ruiz",
+        "author_inst": "VIR Biotechnology"
+      },
+      {
+        "author_name": "Hannah Kaiser",
+        "author_inst": "VIR Biotechnology"
+      },
+      {
+        "author_name": "Anna Sahakyan",
+        "author_inst": "VIR Biotechnology"
+      },
+      {
+        "author_name": "Roberto Spreafico",
+        "author_inst": "VIR Biotechnology"
+      },
+      {
+        "author_name": "Svetlana Shulga Morskaya",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Joseph D Barry",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Daniel Berman",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Stephanie Lefebvre",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Anne Kasper",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Timothy Racie",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Diann Weddle",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Melissa Mobley",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Arlin Rogers",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Joseph Dybowski",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Saheo Chong",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Jayprakash Nair",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Amy Simon",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Kevin Sloan",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Seungmin Hwang",
+        "author_inst": "VIR Biotechnology"
+      },
+      {
+        "author_name": "Herbert W Virgin",
+        "author_inst": "VIR Biotechnology"
+      },
+      {
+        "author_name": "Kevin Fitzgerald",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Martin A Maier",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Gregory Hinkle",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Christy Hebner",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Akin Akinc",
+        "author_inst": "Alnylam Pharmaceuticals"
+      },
+      {
+        "author_name": "Vasant Jadhav",
+        "author_inst": "Alnylam Pharmaceuticals"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "biophysics"
+    "category": "pharmacology and toxicology"
   },
   {
     "rel_doi": "10.1101/2022.03.18.22272624",
@@ -311711,47 +313250,151 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.03.16.22272527",
-    "rel_title": "Severe Acute Respiratory Coronavirus-2 Antibody and T cell response after a third vaccine dose in hemodialysis patients compared with healthy controls",
+    "rel_doi": "10.1101/2022.03.17.22272589",
+    "rel_title": "A multiplexed Cas13-based assay with point-of-care attributes for simultaneous COVID-19 diagnosis and variant surveillance",
     "rel_date": "2022-03-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.16.22272527",
-    "rel_abs": "1.Hemodialysis patients (HD patients) have a high health risk from Severe Acute Respiratory Coronavirus-2 (SARS-CoV-2) infection. In this study, we assess the impact of a third vaccine dose (3D) on antibody levels and T cell response in HD patients and compare the results to those of a healthy control group.\n\nWe conducted a prospective cohort study consisting of 60 HD patients and 65 healthy controls. All of them received two doses of the Comirnaty mRNA vaccine and a third mRNA vaccine dose (Spikevax or Comirnaty). The SARS-CoV-2 S antibody response in all participants was measured 6 months after the second vaccine dose and 6 to 8 weeks after administration of the 3D. We also assessed INF-{gamma} secretion 6-8 weeks after the 3D in 24 healthy controls, 17 HD patients with a normal and 20 HD patients with a low or no antibody response after the second dose. The groups were compared using univariate quantile regressions and multiple analyses. The adverse effects of vaccines were assessed via a questionnaire.\n\nAfter the 3D, the SARS-CoV-2-specific antibody and INF-{gamma} titers of most HD patients were comparable to those of healthy controls. A subgroup of HD patients who had shown a diminished antibody response after the first two vaccine doses developed a significantly lower antibody and INF-{gamma} response compared to responder HD patients and controls, even after the 3D. A new strategy is needed to protect this patient group from severe COVID-19 infection.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.17.22272589",
+    "rel_abs": "Point-of-care (POC) nucleic acid detection technologies are poised to aid gold-standard technologies in controlling the COVID-19 pandemic, yet shortcomings in the capability to perform critically needed complex detection--such as multiplexed detection for viral variant surveillance--may limit their widespread adoption. Herein, we developed a robust multiplexed CRISPR-based detection using LwaCas13a and PsmCas13b to simultaneously diagnose SARS-CoV-2 infection and pinpoint the causative SARS-CoV-2 variant of concern (VOC)-- including globally dominant VOCs Delta (B.1.617.2) and Omicron (B.1.1.529)--all while maintaining high levels of accuracy upon the detection of multiple SARS-CoV-2 gene targets. The platform has several attributes suitable for POC use: premixed, freeze-dried reagents for easy use and storage; convenient direct-to-eye or smartphone-based readouts; and a one-pot variant of the multiplexed detection. To reduce reliance on proprietary reagents and enable sustainable use of such a technology in low- and middle-income countries, we locally produced and formulated our own recombinase polymerase amplification reaction and demonstrated its equivalent efficiency to commercial counterparts. Our tool--CRISPR-based detection for simultaneous COVID-19 diagnosis and variant surveillance which can be locally manufactured--may enable sustainable use of CRISPR diagnostics technologies for COVID- 19 and other diseases in POC settings.",
+    "rel_num_authors": 33,
     "rel_authors": [
       {
-        "author_name": "Benedikt Simon",
-        "author_inst": "LK Mistelbach"
+        "author_name": "Maturada Patchsung",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
       },
       {
-        "author_name": "Harald Rubey",
-        "author_inst": "LK Mistelbach"
+        "author_name": "Aimorn Homchan",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand; Department of Biochemistry, Facul"
       },
       {
-        "author_name": "Martin Gromann",
-        "author_inst": "LK Mistelbach"
+        "author_name": "Kanokpol Aphicho",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
       },
       {
-        "author_name": "Astrid Knop-Voelkerer",
-        "author_inst": "LK Mistelbach"
+        "author_name": "Surased Suraritdechachai",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
       },
       {
-        "author_name": "Boris Hemedi",
-        "author_inst": "LK Mistelbach"
+        "author_name": "Thanyapat Wanitchanon",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
       },
       {
-        "author_name": "Sonja Zehetmayer",
-        "author_inst": "MedUni Wien"
+        "author_name": "Archiraya Pattama",
+        "author_inst": "Department of Microbiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand"
       },
       {
-        "author_name": "Bernhard Kirsch",
-        "author_inst": "LK Mistelbach"
+        "author_name": "Khomkrit Sappakhaw",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
+      },
+      {
+        "author_name": "Piyachat Meesawat",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
+      },
+      {
+        "author_name": "Thanakrit Wongsatit",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
+      },
+      {
+        "author_name": "Artittaya Athipanyasilp",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
+      },
+      {
+        "author_name": "Krittapas Jantarug",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
+      },
+      {
+        "author_name": "Niracha Athipanyasilp",
+        "author_inst": "Department of Microbiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Juthamas Buahom",
+        "author_inst": "Department of Microbiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Supapat Visanpattanasin",
+        "author_inst": "Department of Biochemistry and Center for Excellence in Protein and Enzyme Technology, Faculty of Science, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Nootaree Niljianskul",
+        "author_inst": "PTT Public Company Limited, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Pimchai Chaiyen",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
+      },
+      {
+        "author_name": "Ruchanok Tinikul",
+        "author_inst": "Department of Biochemistry and Center for Excellence in Protein and Enzyme Technology, Faculty of Science, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Nuanjun Wichukchinda",
+        "author_inst": "Division of Genomic Medicine and Innovation Support, Department of Medical Sciences, Ministry of Public Health, Nonthaburi, Thailand"
+      },
+      {
+        "author_name": "Surakameth Mahasirimongkol",
+        "author_inst": "Division of Genomic Medicine and Innovation Support, Department of Medical Sciences, Ministry of Public Health, Nonthaburi, Thailand"
+      },
+      {
+        "author_name": "Rujipas Sirijatuphat",
+        "author_inst": "Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Nasikarn Angkasekwinai",
+        "author_inst": "Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Michael A Crone",
+        "author_inst": "London Biofoundry, Imperial College Translation and Innovation Hub; Department of Infectious Disease; UK Dementia Research Institute Centre for Care Research an"
+      },
+      {
+        "author_name": "Paul S Freemont",
+        "author_inst": "London Biofoundry, Imperial College Translation and Innovation Hub; Department of Infectious Disease; UK Dementia Research Institute Centre for Care Research an"
+      },
+      {
+        "author_name": "Julia Joung",
+        "author_inst": "Howard Hughes Medical Institute; Broad Institute of MIT and Harvard; McGovern Institute for Brain Research at MIT; Department of Biological Engineering; Departm"
+      },
+      {
+        "author_name": "Alim Ladha",
+        "author_inst": "Howard Hughes Medical Institute; Broad Institute of MIT and Harvard; McGovern Institute for Brain Research at MIT; Department of Biological Engineering; Departm"
+      },
+      {
+        "author_name": "Omar Abudayyeh",
+        "author_inst": "McGovern Institute for Brain Research at MIT, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Jonathan Gootenberg",
+        "author_inst": "McGovern Institute for Brain Research at MIT, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Feng Zhang",
+        "author_inst": "Howard Hughes Medical Institute; Broad Institute of MIT and Harvard; McGovern Institute for Brain Research at MIT; Department of Biological Engineering; Departm"
+      },
+      {
+        "author_name": "Claire Chewapreecha",
+        "author_inst": "Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand; Wellcome Sanger Institute, Hinxton, UK"
+      },
+      {
+        "author_name": "Sittinan Chanarat",
+        "author_inst": "Department of Biochemistry and Center for Excellence in Protein and Enzyme Technology, Faculty of Science, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Navin Horthongkham",
+        "author_inst": "Department of Microbiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Danaya Pakotiprapha",
+        "author_inst": "Department of Biochemistry and Center for Excellence in Protein and Enzyme Technology, Faculty of Science, Mahidol University, Bangkok, Thailand"
+      },
+      {
+        "author_name": "Chayasith Uttamapinant",
+        "author_inst": "School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong, Thailand"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "nephrology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.03.17.22272538",
@@ -313529,83 +315172,39 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2022.03.14.22272342",
-    "rel_title": "Tongue Coating in COVID-19 Patients: A Case-Control Study",
+    "rel_doi": "10.1101/2022.03.17.22272535",
+    "rel_title": "Comparison of the 2021 COVID-19 'Roadmap' Projections against Public Health Data",
     "rel_date": "2022-03-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.14.22272342",
-    "rel_abs": "It has been suggested that COVID-19 patients have distinct tongue features, which may help to monitor the development of their condition. To determine if there was any specific tongue coating feature in COVID-19, this study investigated the difference in tongue coating between COVID-19 subjects and subjects with other acute inflammatory diseases characterized by fever. Tongue images taken with smartphones from three age-matched groups, namely, COVID group (n=92), non-COVID febrile group (n=92), and normal control group (n=92), were analyzed by two blinded raters according to a tongue coating scoring scheme, which assessed the levels of thick fur, slimy or greasy fur, discolored fur and composite index of tongue coating. Compared with control, significant increases in all coating indexes were found in the COVID group (P<0.001), as well as in the non-COVID febrile group (P<0.001). However, no difference was observed between COVID and non-COVID febrile groups for all coating indexes measured. In COVID-19 subjects, their scores of coating indexes had weak but significant correlations with certain inflammatory biomarkers, including WBC and neutrophil - lymphocyte ratio. It is concluded that COVID-19 subjects have pathological tongue coating patterns that are associated with inflammatory responses, and these coating patterns can help to indicate the direction of disease development.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.17.22272535",
+    "rel_abs": "Control and mitigation of the COVID-19 pandemic in England has relied on a combination of vaccination and non-pharmaceutical interventions (NPIs). Some of these NPIs are extremely costly (economically and socially), so it was important to relax these promptly without overwhelming already burdened health services. The eventual policy was a Roadmap of four relaxation steps throughout 2021, taking England from lock-down to the cessation of all restrictions on social interaction. In a series of six Roadmap documents generated throughout 2021, models assessed the potential risk of each relaxation step. Here we show that the model projections generated a reliable estimation of medium-term hospital admission trends, with the data points up to September 2021 generally lying within our 95% prediction intervals. The greatest uncertainties in the modelled scenarios came from vaccine efficacy estimates against novel variants, and from assumptions about human behaviour in the face of changing restrictions and risk.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Zhi Chun Wang",
-        "author_inst": "Hong Kong Baptist University"
-      },
-      {
-        "author_name": "Xi Hong Cai",
-        "author_inst": "The Third Affiliated Hospital of Guangzhou University of Chinese Medicine"
-      },
-      {
-        "author_name": "Jeremy Chan",
-        "author_inst": "Hong Kong Baptist University"
-      },
-      {
-        "author_name": "Yi Yi Chan",
-        "author_inst": "Hong Kong Baptist University"
-      },
-      {
-        "author_name": "Xiaotong Chen",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Ching Wan Cheng",
-        "author_inst": "Hong Kong Baptist University"
-      },
-      {
-        "author_name": "Donghui Huang",
-        "author_inst": "Guangdong Provincial Hospital of Traditional Chinese Medicine"
-      },
-      {
-        "author_name": "Luqi Huang",
-        "author_inst": "China Academy of Chinese Medical Sciences"
-      },
-      {
-        "author_name": "Bei-ni Lao",
-        "author_inst": "Second Clinical Medical College of Guangzhou University of Chinese Medicine: The Second Affiliated Hospital of Guangzhou University of Chinese Medicine"
-      },
-      {
-        "author_name": "Xu-sheng Liu",
-        "author_inst": "Guangdong Hospital of Traditional Chinese Medicine: Guangdong Provincial Hospital of Traditional Chinese Medicine"
-      },
-      {
-        "author_name": "Aiping Lyu",
-        "author_inst": "Hong Kong Baptist University"
-      },
-      {
-        "author_name": "Wenliang Lv",
-        "author_inst": "China Academy of Chinese Medical Sciences"
+        "author_name": "Matt J Keeling",
+        "author_inst": "University of Warwick"
       },
       {
-        "author_name": "Huixian Wang",
-        "author_inst": "Guangdong Provincial Hospital of Traditional Chinese Medicine"
+        "author_name": "Louise J Dyson",
+        "author_inst": "University of Warwick"
       },
       {
-        "author_name": "Helen Zhang",
-        "author_inst": "Hong Kong Northern District Hospital"
+        "author_name": "Michael Tildesley",
+        "author_inst": "University of Warwick"
       },
       {
-        "author_name": "Xuebin Zhang",
-        "author_inst": "Hong Kong Baptist University"
+        "author_name": "Edward M Hill",
+        "author_inst": "University of Warwick"
       },
       {
-        "author_name": "Shi Ping Zhang",
-        "author_inst": "Hong Kong Baptist University"
+        "author_name": "Sam M Moore",
+        "author_inst": "University of Warwick"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.03.14.22272314",
@@ -315259,49 +316858,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.03.14.22272368",
-    "rel_title": "Area-level social and structural inequalities determine mortality related to COVID-19 diagnosis in Ontario, Canada: a population-based explanatory modeling study of 11.8 million people",
+    "rel_doi": "10.1101/2022.03.14.22272359",
+    "rel_title": "Biomarkers Selection for Population Normalization in SARS-CoV-2 Wastewater-based Epidemiology",
     "rel_date": "2022-03-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.14.22272368",
-    "rel_abs": "ImportanceSocial determinants of health (SDOH) play an important role in COVID-19 outcomes. More research is needed to quantify this relationship and understand the underlying mechanisms.\n\nObjectivesTo examine differential patterns in COVID-19-related mortality by area-level SDOH accounting for confounders; and to compare these patterns to those for non-COVID-19 mortality, and COVID-19 case fatality (COVID-19-related death among those diagnosed).\n\nDesign, setting, and participantsPopulation-based retrospective cohort study including all community living individuals aged 20 years or older residing in Ontario, Canada, as of March 1, 2020 who were followed through to March 2, 2021.\n\nExposureSDOH variables derived from the 2016 Canada Census at the dissemination area-level including: median household income; educational attainment; proportion of essential workers, racialized groups, recent immigrants, apartment buildings, and high-density housing; and average household size.\n\nMain outcomes and measuresCOVID-19-related death was defined as death within 30 days following, or 7 days prior to a positive SARS-CoV-2 test. Cause-specific hazard models were employed to examine the associations between SDOH and COVID-19-related mortality, treating non-COVID-19 mortality as a competing risk.\n\nResultsOf 11,810,255 individuals included, 3,880 (0.03%) died related to COVID-19 and 88,107 (0.75%) died without a positive test. After accounting for demographics, baseline health, and other SDOH, the following SDOH were associated with increased hazard of COVID-19-related death (hazard ratios [95% confidence intervals]) comparing the most to least vulnerable group): lower income (1.30[1.09-1.54]), lower educational attainment (1.27[1.10-1.47]), higher proportion essential workers (1.28[1.10-1.50]), higher proportion racialized groups (1.42[1.16-1.73]), higher proportion apartment buildings (1.25[1.11-1.41]), and larger vs. medium household size (1.30[1.13-1.48]). In comparison, areas with higher proportion racialized groups were associated with a lower hazard of non-COVID-19 mortality (0.88[0.85-0.92]). With the exception of income, SDOH were not independently associated with COVID-19 case fatality.\n\nConclusions and relevanceArea-level social and structural inequalities determine COVID-19-related mortality after accounting for individual demographic and clinical factors. COVID-19 has reversed the pattern of lower non-COVID-19 mortality by racialized groups. Pandemic responses should include prioritized and community-tailored intervention strategies to address SDOH that mechanistically underpin disproportionate acquisition and transmission risks and shape barriers to the reach of, and access to prevention interventions.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSAre area-level social determinants of health factors independently associated with coronavirus disease 2019 (COVID-19)-related mortality after accounting for demographics and clinical factors?\n\nFindingsIn this population-based cohort study including 11.8 million adults residing in Ontario, Canada and 3,880 COVID-19-related death occurred between Mar 1, 2020 and Mar 2, 2021, we found that areas characterized by lower SES (including lower income, lower educational attainment, and higher proportion essential workers), greater ethnic diversity, more apartment buildings, and larger vs. medium household size were associated with increased hazard of COVID-19-related mortality compared to their counterparts, even after accounting for individual-level demographics, baseline health, and other area-level SDOH.\n\nMeaningPandemic responses should include prioritized and community-tailored intervention strategies to address SDOH that mechanistically underpin inequalities in acquisition and transmission risks, and in the reach of, and access to prevention interventions.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.14.22272359",
+    "rel_abs": "Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the COVID-19 outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater can be critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (pMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated for their utility in normalizing the SARS-CoV-2 loads through developed direct and indirect approaches. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performed candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuated population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population at any given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p<0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.\n\nHIGHLIGHT (bullet points)O_LIThe paraxanthine (PARA), the metabolite of the caffeine, is a more reliable population biomarker in SARS-CoV-2 wastewater-based epidemiology studies than the currently recommended pMMoV genetic marker.\nC_LIO_LISARS-CoV-2 load per capita could be directly normalized using the regression functions derived from correlation between paraxanthine and population without flowrate and population data.\nC_LIO_LINormalizing SARS-CoV-2 levels with the chemical marker PARA significantly improved the correlation between viral loads per capita and case numbers per capita.\nC_LIO_LIThe chemical marker PARA demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater.\nC_LI",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Linwei Wang",
-        "author_inst": "Unity Health Toronto"
+        "author_name": "Shu-Yu Hsu",
+        "author_inst": "University of Missouri"
       },
       {
-        "author_name": "Andrew Calzavara",
-        "author_inst": "ICES"
+        "author_name": "Mohamed B Bayati",
+        "author_inst": "University of Missouri Columbia"
       },
       {
-        "author_name": "Stefan Baral",
-        "author_inst": "JHSPH"
+        "author_name": "Chenhui Li",
+        "author_inst": "University of Missouri"
       },
       {
-        "author_name": "Janet Smylie",
-        "author_inst": "University of Toronto"
+        "author_name": "Hsin-Yeh Hsieh",
+        "author_inst": "University of Missouri"
       },
       {
-        "author_name": "Adrienne K Chan",
-        "author_inst": "University of Toronto"
+        "author_name": "Anthony Belenchia",
+        "author_inst": "Missouri Department of Health and Senior Services"
       },
       {
-        "author_name": "Beate Sander",
-        "author_inst": "University Health Network"
+        "author_name": "Hweiyiing Johnson",
+        "author_inst": "Missouri Department of Health and Senior Services"
       },
       {
-        "author_name": "Peter C Austin",
-        "author_inst": "ICES"
+        "author_name": "Jessica Klutts",
+        "author_inst": "Missouri Department of Natural Resources"
       },
       {
-        "author_name": "Jeff C Kwong",
-        "author_inst": "ICES"
+        "author_name": "Melissa Reynolds",
+        "author_inst": "Missouri Department of Health and Senior Services"
       },
       {
-        "author_name": "Sharmistha Mishra",
-        "author_inst": "University of Toronto"
+        "author_name": "Elizabeth Semkiw",
+        "author_inst": "Missouri Department of Health and Senior Services"
+      },
+      {
+        "author_name": "Jeff Wenzel",
+        "author_inst": "Missouri Department of Health and Senior Services"
+      },
+      {
+        "author_name": "Chris Wieberg",
+        "author_inst": "Missouri Department of Natural Resources"
+      },
+      {
+        "author_name": "Sally A Zemmer",
+        "author_inst": "Missouri Department of Natural Resources"
+      },
+      {
+        "author_name": "Trevor Foley",
+        "author_inst": "Missouri Department of Corrections"
+      },
+      {
+        "author_name": "Marc Johnson",
+        "author_inst": "University of Missouri"
+      },
+      {
+        "author_name": "Chung-Ho Lin",
+        "author_inst": "University of Missouri"
       }
     ],
     "version": "1",
@@ -317057,51 +318680,51 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.03.10.22272123",
-    "rel_title": "Polymorphism in IFNAR contributes to glucocorticoid response and outcome in ARDS and COVID-19",
+    "rel_doi": "10.1101/2022.03.10.22272237",
+    "rel_title": "Long COVID in Children and Adolescents: A Systematic Review and Meta-analyses.",
     "rel_date": "2022-03-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272123",
-    "rel_abs": "The use of glucocorticoids has given contradictory results for treating acute respiratory distress syndrome (ARDS). Here we report a novel disease association of a SNP rs9984273, which is situated in the interferon alpha/beta receptor (IFNAR2) gene in an area corresponding to a binding motif of the glucocorticoid receptor (GR). The minor allele of SNP rs9984273 associates with higher IFNAR expression, lower IFN-gamma and IL-6 levels and less severe form of coronavirus diseases (COVID-19) according to the COVID-19 Host Genetics Initiative database, and better outcome in interferon (IFN) beta treated patients with ARDS. Thus, the distribution of this SNP within clinical study arms may explain the contradictory results of multiple ARDS studies and outcomes in COVID-19 concerning type I IFN signalling and glucocorticoids.\n\nOne-Sentence SummarySingle nucleotide polymorphism in interferon receptor contributes to corticosteroid response and outcome in ARDS and COVID-19",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272237",
+    "rel_abs": "The objective of this systematic review and meta-analyses is to estimate the prevalence of long-COVID in children and adolescents and to present the full spectrum of symptoms present after acute COVID-19. We have used PubMed and Embase to identify observational studies published before February 10th, 2022 that included a minimum of 30 patients with ages ranging from 0 to 18 years that met the National Institute for Healthcare Excellence (NICE) definition of long-COVID, which consists of both ongoing (4 to 12 weeks) and post-COVID-19 ([&ge;]12 weeks) symptoms. Random-effects meta-analyses were performed using the MetaXL software to estimate the pooled prevalence with a 95% confidence interval (CI). Heterogeneity was assessed using I2 statistics. The Preferred Reporting Items for Systematic Reviewers and Meta-analysis (PRISMA) reporting guideline was followed (registration PROSPERO CRD42021275408). The literature search yielded 8,373 publications, of which 21 studies met the inclusion criteria, and a total of 80,071 children and adolescents were included. The prevalence of long-COVID was 25.24%, and the most prevalent clinical manifestations were mood symptoms (16.50%), fatigue (9.66%), and sleep disorders (8.42%). Children infected by SARS-CoV-2 had a higher risk of persistent dyspnea, anosmia/ageusia, and/or fever compared to controls. Limitations of the studies analyzed include lack of standardized definitions, recall, selection, misclassification, nonresponse and/or loss of follow-up, and a high level of heterogeneity.",
     "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Juho Jalkanen",
-        "author_inst": "Faron Pharmaceuticals"
+        "author_name": "Sandra Lopez-Leon",
+        "author_inst": "Novartis Pharmaceuticals"
       },
       {
-        "author_name": "Sofia Khan",
-        "author_inst": "University of Turku"
+        "author_name": "Talia Wegman-Ostrosky",
+        "author_inst": "Instituto Nacional de Cancerologia"
       },
       {
-        "author_name": "Kati Elima",
-        "author_inst": "University of Turku"
+        "author_name": "Norma Cipatli Ayuzo del Valle",
+        "author_inst": "Tecnologico de Monterrey, Mexico"
       },
       {
-        "author_name": "Teppo Huttunen",
-        "author_inst": "Estimates"
+        "author_name": "Carol Perelman",
+        "author_inst": "Somedicyt, UNAM"
       },
       {
-        "author_name": "Ning Wang",
-        "author_inst": "University of Turku"
+        "author_name": "Rosalinda Sepulveda",
+        "author_inst": "Harvard T.H. Chan School of Public Health Boston"
       },
       {
-        "author_name": "Maija Hollmen",
-        "author_inst": "University of Turku"
+        "author_name": "Paulina Alejandra Rebolledo",
+        "author_inst": "Rollis School of Public Health, Emory University"
       },
       {
-        "author_name": "Laura Elo",
-        "author_inst": "University of Turku"
+        "author_name": "Angelica Cuapio",
+        "author_inst": "Karolinska Institute, Stockholm, Sweden"
       },
       {
-        "author_name": "Sirpa Jalkanen",
-        "author_inst": "University of Turku"
+        "author_name": "Sonia Villapol",
+        "author_inst": "Houston Methodist Research Institute, Texas"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "respiratory medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.03.10.22272236",
@@ -318915,121 +320538,81 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2022.03.09.22272113",
-    "rel_title": "Evidence for SARS-CoV-2 Delta and Omicron co-infections and recombination",
+    "rel_doi": "10.1101/2022.03.10.22272197",
+    "rel_title": "Blood group O and post-COVID-19 syndrome",
     "rel_date": "2022-03-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.09.22272113",
-    "rel_abs": "Between November 2021 and February 2022, SARS-CoV-2 Delta and Omicron variants co-circulated in the United States, allowing for co-infections and possible recombination events. We sequenced 29,719 positive samples during this period and analyzed the presence and fraction of reads supporting mutations specific to either the Delta or Omicron variant. We identified 18 co-infections, one of which displayed evidence of a low Delta-Omicron recombinant viral population. We also identified two independent cases of infection by a Delta-Omicron recombinant virus, where 100% of the viral RNA came from one clonal recombinant. In the three cases, the 5-end of the viral genome was from the Delta genome, and the 3-end from Omicron including the majority of the spike protein gene, though the breakpoints were different. Delta-Omicron recombinant viruses were rare, and there is currently no evidence that Delta-Omicron recombinant viruses are more transmissible between hosts compared to the circulating Omicron lineages.",
-    "rel_num_authors": 26,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272197",
+    "rel_abs": "ObjectiveThe ABO blood group system modulates the inflammatory response and has been involved in COVID-19. O-group protects against SARS-CoV-2 infection, but there are no data regarding post-COVID-19 syndrome (PCS). Our aim was to assess this possible association.\n\nSubjects and methodsCase-control study in a community setting, with subjects who had experienced mild COVID-19. Cases were PCS+, controls were PCS-, and the exposure variable, O-group. Epidemiological data (age, sex, BMI, smoking, comorbidities), laboratory parameters (inflammatory markers, IgG antibodies, blood type) and clinical data were collected. Composite inflammatory indices were developed. Multivariate analyses were performed.\n\nResultsWe analyzed 121 subjects (56.2% women), mean age 45.7 {+/-} 16 years. Blood group frequencies were 43.3%, 7.7%, 5.7%, and 43.3% for A, B, AB and O, respectively. Thirty-six patients were PCS+. There were no significant differences between cases and controls. Compared to non-O, a higher prevalence of PCS (p=0.036), number of symptoms (p=0.017) and myalgia (p=0.030) were noted in O-group. Concerning inflammatory markers, PCS+ and PCS-showed no differences in A, B, and AB groups. In contrast, O-group PCS+ patients had significantly higher lymphocyte count, higher levels of fibrinogen and CRP, and higher percentages of 3 composite indices, than PCS-subjects. The O-group showed a 4-fold increased risk of PCS compared to non-O (adjusted OR=4.20 [95%CI, 1.2-14]; p=0.023).\n\nConclusionAn increased risk of PCS has shown to be associated with O-group, after controlling for confounders. In O-group subjects with PCS, slightly albeit significant, raised levels of fibrinogen, CRP, and lymphocyte count, have been demonstrated.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Alexandre Bolze",
-        "author_inst": "Helix"
+        "author_name": "Sara Diaz-Salazar",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Tracy Basler",
-        "author_inst": "Helix"
+        "author_name": "Raquel Navas",
+        "author_inst": "Camargo-Costa Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Simon White",
-        "author_inst": "Helix"
+        "author_name": "Laura Sainz-Maza",
+        "author_inst": "Camargo-Costa Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Andrew Dei Rossi",
-        "author_inst": "Helix"
+        "author_name": "Patricia Fierro",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Dana Wyman",
-        "author_inst": "Helix"
+        "author_name": "Meryam Maamar",
+        "author_inst": "Emergency Service. Osakidetza, Servicio Vasco de Salud. Bilbao. Pais Vasco. Spain."
       },
       {
-        "author_name": "Pavitra Roychoudhury",
-        "author_inst": "University of Washington"
+        "author_name": "Arancha Artime",
+        "author_inst": "El Llano - Primary Health Care Center. SESPA, Servicio de Salud del Principado de Asturias. Gijon. Asturias. Spain."
       },
       {
-        "author_name": "Alexander L. Greninger",
-        "author_inst": "University of Washington"
+        "author_name": "Hector Basterrechea",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Kathleen Hayashibara",
-        "author_inst": "Thermo Fisher Scientific"
+        "author_name": "Benedetta Petitta",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Camargo Cantabria. Spain."
       },
       {
-        "author_name": "Eric Kil",
-        "author_inst": "Helix"
+        "author_name": "Carlota Lamadrid",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Hang Dai",
-        "author_inst": "Helix"
+        "author_name": "Lucia Pedraja",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Tyler Cassens",
-        "author_inst": "Helix"
+        "author_name": "Claudia Gandara-Samperio",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Camargo. Cantabria. Spain."
       },
       {
-        "author_name": "Kevin Tsan",
-        "author_inst": "Helix"
+        "author_name": "Stefanie Pini",
+        "author_inst": "Hospital-at-Home Service. Hospital Universitario Marques de Valdecilla. Santander. Cantabria. Spain."
       },
       {
-        "author_name": "Jason Nguyen",
-        "author_inst": "Helix"
+        "author_name": "Jose M. Olmos",
+        "author_inst": "Servicio de Medicina Interna. Hospital Universitario Marques de Valdecilla. Instituto de Investigacion Valdecilla (IDIVAL). Depto de Medicina y Psiquiatria. Uni"
       },
       {
-        "author_name": "Jimmy Ramirez",
-        "author_inst": "Helix"
+        "author_name": "Carmen Ramos-Barron",
+        "author_inst": "Camargo-Costa Primary Health Care Center. Servicio Cantabro de Salud. Depto de Medicina y Psiquiatria. Universidad de Cantabria. Santander. Cantabria. Spain."
       },
       {
-        "author_name": "Scotty Carter",
-        "author_inst": "Helix"
+        "author_name": "Emilio Pariente",
+        "author_inst": "Camargo-Interior Primary Health Care Center. Servicio Cantabro de Salud. Depto de Medicina y Psiquiatria. Universidad de Cantabria. Santander. Cantabria. Spain."
       },
       {
-        "author_name": "Elizabeth T. Cirulli",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "Kelly Schiabor Barrett",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "Nicole L Washington",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "Pedro Belda-Ferre",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "Sharoni Jacobs",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "Efren Sandoval",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "David Becker",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "James T Lu",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "Magnus Isaksson",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "William Lee",
-        "author_inst": "Helix"
-      },
-      {
-        "author_name": "Shishi Luo",
-        "author_inst": "Helix"
+        "author_name": "Jose L Hernandez",
+        "author_inst": "Servicio de Medicina Interna. Hospital Universitario Marques de Valdecilla. Instituto de Investigacion Valdecilla (IDIVAL). Depto de Medicina y Psiquiatria. Uni"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -321213,31 +322796,35 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2022.03.10.483790",
-    "rel_title": "Evolutionary safety of death by mutagenesis",
+    "rel_doi": "10.1101/2022.03.10.483652",
+    "rel_title": "Open modification searching of SARS-CoV-2-human protein interaction data reveals novel viral modification sites",
     "rel_date": "2022-03-10",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.10.483790",
-    "rel_abs": "Nucleoside analogs are a major class of antiviral drugs. Some act by increasing the viral mutation rate causing \"death by mutagenesis\" of the virus. Their mutagenic capacity, however, may lead to an evolutionary safety concern. We define evolutionary safety as a probabilistic assurance that the treatment will not generate an increased number of epidemiologically concerning mutated virus progeny. We develop a mathematical framework to estimate the total mutant load produced with and without mutagenic treatment. We predict rates of appearance of virus mutants as a function of the timing of treatment and the immune competence of patients, employing various assumptions about the vulnerability of the viral genome and its potential to generate undesired phenotypes. We focus on the case study of Molnupiravir, which is an FDA-approved treatment against COVID-19. We estimate that Molnupiravir is narrowly evolutionarily safe, subject to the current estimate of parameters. Evolutionary safety can be improved by restricting treatment to individuals with a low clearance rate and by designing treatments that lead to a greater increase in mutation rate. We report a simple rule to determine the fold-increase in mutation rate required to obtain evolutionary safety which is also applicable to other pathogen-treatment combinations.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.10.483652",
+    "rel_abs": "The outbreak of the SARS-CoV-2 coronavirus, the causative agent of the COVID-19 disease, has led to an ongoing global pandemic since 2019. Mass spectrometry can be used to understand the molecular mechanisms of viral infection by SARS-CoV-2, for example, by determining virus-host protein-protein interactions (PPIs) through which SARS-CoV-2 hijacks its human hosts during infection, and to study the role of post-translational modifications (PTMs). We have reanalyzed public affinity purification mass spectrometry data using open modification searching to investigate the presence of PTMs in the context of the SARS-CoV-2 virus-host PPI network. Based on an over two-fold increase in identified spectra, our detected protein interactions show a high overlap with independent mass spectrometry-based SARS-CoV-2 studies and virus-host interactions for alternative viruses, as well as previously unknown protein interactions. Additionally, we identified several novel modification sites on SARS-CoV-2 proteins that we investigated in relation to their interactions with host proteins. A detailed analysis of relevant modifications, including phosphorylation, ubiquitination, and S-nitrosylation, provides important hypotheses about the functional role of these modifications during viral infection by SARS-CoV-2.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Gabriela Aleksandra Lobinska",
-        "author_inst": "Weizmann Institute of Science"
+        "author_name": "Charlotte Adams",
+        "author_inst": "University of Antwerp, Antwerp, Belgium"
       },
       {
-        "author_name": "Yitzhak Tzachi Pilpel",
-        "author_inst": "Weizmann Institute of Science"
+        "author_name": "Kurt Boonen",
+        "author_inst": "Flemish Institute for Technological Research (VITO), Mol, Belgium"
       },
       {
-        "author_name": "Martin Andreas Nowak",
-        "author_inst": "Harvard"
+        "author_name": "Kris Laukens",
+        "author_inst": "University of Antwerp, Antwerp, Belgium"
+      },
+      {
+        "author_name": "Wout Bittremieux",
+        "author_inst": "University of California San Diego, La Jolla, CA, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "evolutionary biology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2022.03.08.22271980",
@@ -323367,51 +324954,23 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2022.03.08.483429",
-    "rel_title": "Geneticin shows selective antiviral activity against SARS-CoV-2 by targeting programmed -1 ribosomal frameshifting",
+    "rel_doi": "10.1101/2022.03.01.22271721",
+    "rel_title": "The relative impact of vaccination momentum on COVID-19 rates of death in the USA in 2020/2021. The forgotten role of population wellness.",
     "rel_date": "2022-03-08",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.08.483429",
-    "rel_abs": "SARS-CoV-2 is currently causing an unprecedented pandemic. While vaccines are massively deployed, we still lack effective large-scale antiviral therapies. In the quest for antivirals targeting conserved structures, we focused on molecules able to bind viral RNA secondary structures. Aminoglycosides are a class of antibiotics known to interact with the ribosomal RNA of both prokaryotes and eukaryotes and have previously been shown to exert antiviral activities by interacting with viral RNA. Here we show that the aminoglycoside geneticin is endowed with antiviral activity against all tested variants of SARS-CoV-2, in different cell lines and in a respiratory tissue model at non-toxic concentrations. The mechanism of action is an early inhibition of RNA replication and protein expression related to a decrease in the efficiency of the -1 programmed ribosomal frameshift (PRF) signal of SARS-CoV-2. Using in silico modelling, we have identified a potential binding site of geneticin in the pseudoknot of frameshift RNA motif. Moreover, we have selected, through virtual screening, additional RNA binding compounds, interacting with the same site with increased potency.",
-    "rel_num_authors": 8,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.01.22271721",
+    "rel_abs": "It is widely accepted that individual underlying health conditions contribute to morbidity and mortality associated with COVID-19; and by inference population wellness will also contribute to COVID-19 outcomes. In addition, over the last two years the predominant pharmaceutical public health response to COVID-19 has been vaccination momentum (i.e. mass and rapid inoculation campaigns).\n\nThis paper aims to compare vaccination momentum throughout 2021 and measures of population wellness to estimate the relative impact of each on deaths attributed to COVID-19 across the 50 States of America, plus Washington DC, during 2020 (i.e. the pre-vaccination period) and 2021 (i.e. the vaccination period).\n\nOur analysis shows that: (a) COVID-19 rates of death in 2020 are more important, and statistically more significant, at predicting rates of death in 2021 than vaccination momentum during 2021; (b) vaccination momentum does not predict the magnitude of change in COVID-19 rates of death between 2020 and 2021; and (c) for several underlying heath and risk factors vaccination momentum is significantly less important than population wellness at predicting COVID-19 rates of death.\n\nOf particular interest are our observations that exercise and fruit consumption are 10.1 times more significant at predicting COVID-19 deaths than vaccination momentum, obesity (BMI 30+) is 9.6 times more significant at predicting COVID-19 deaths than vaccination momentum, heart attacks are 4.37 times more significant at predicting COVID-19 deaths than vaccination momentum and smoking is 3.2 times more significant at predicting COVID-19 deaths than vaccination momentum.\n\nIf medical and health regulators are to deliver a quantum decrease in COVID-19 deaths they must move beyond the overwhelming focus on COVID-19 vaccination. They must have the courage to urge governments and private organisations to mandate greater exercise, weight loss, less junk food, and better nutrition. And a concerted effort at reducing chronic adverse health conditions.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Carmine Varricchio",
-        "author_inst": "Cardiff School of Pharmacy and Pharmaceutical Sciences"
-      },
-      {
-        "author_name": "Gregory Mathez",
-        "author_inst": "University Hospital of Vaud (CHUV)"
-      },
-      {
-        "author_name": "Trestan Pillonel",
-        "author_inst": "University Hospital of Vaud (CHUV)"
-      },
-      {
-        "author_name": "Claire Bertelli",
-        "author_inst": "University Hospital of Vaud (CHUV)"
-      },
-      {
-        "author_name": "Laurent Kaiser",
-        "author_inst": "University of Geneva Hospitals"
-      },
-      {
-        "author_name": "Caroline Tapparel",
-        "author_inst": "University of Geneva"
-      },
-      {
-        "author_name": "Andrea Brancale",
-        "author_inst": "Cardiff School of Pharmacy and Pharmaceutical Sciences"
-      },
-      {
-        "author_name": "Valeria Cagno",
-        "author_inst": "University Hospital of Vaud (CHUV)"
+        "author_name": "Victor Keddis",
+        "author_inst": "University of Melbourne"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "microbiology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.02.23.22271045",
@@ -325329,69 +326888,65 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.03.04.22271890",
-    "rel_title": "Protective antibodies and T cell responses to Omicron variant three months after the booster dose of BNT162b2 vaccine",
+    "rel_doi": "10.1101/2022.03.04.22271540",
+    "rel_title": "The mutational steps of SARS-CoV-2 to become like Omicron within seven months: the story of immune escape in an immunocompromised patient.",
     "rel_date": "2022-03-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.04.22271890",
-    "rel_abs": "The high number of mutations in the Omicron variant of SARS-CoV-2 cause its immune escape when compared to the earlier variants of concern (VOC). At least three vaccine doses are required for the induction of Omicron neutralizing antibodies and further reducing the risk for hospitalization. However, most of the studies have focused on the immediate response after the booster vaccination while the duration of immune response is less known. We here studied longitudinal serum samples from the vaccinated individuals up to three months after their third dose of the BNT162b2 vaccine for their capacity to produce protective antibodies and T cell responses to Wuhan and Omicron variants. After the second dose, the antibody levels to the unmutated spike protein were significantly decreased at three months, and only 4% of the individuals were able to inhibit Omicron spike interaction compared to 47%, 38%, and 14% of individuals inhibiting wild-type, delta, and beta variants spike protein. Nine months after the second vaccination, the antibody levels were similar to the levels before the first dose and none of the sera inhibited SARS-CoV-2 wild-type or any of the three VOCs. The booster dose remarkably increased antibody levels and their ability to inhibit all variants. Three months after the booster the antibody levels and the inhibition activity were trending lower but still up and not significantly different from their peak values at two weeks after the third dose. Although responsiveness towards mutated spike peptides was lost in less than 20 % of vaccinated individuals, the wild-type spike-specific CD4+ and CD8+ memory T cells were still present at three months after the booster vaccination in the majority of studied individuals. Our data show that two doses of the BNT62b2 vaccine are not sufficient to protect against the Omicron variant, however, the spike-specific antibodies and T cell responses are strongly elicited and well maintained three months after the third vaccination dose.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.04.22271540",
+    "rel_abs": "We studied a unique case of prolonged viral shedding in an immunocompromised patient that generated a series of SARS-CoV-2 immune escape mutations over a period of seven months. During the persisting SARS-CoV-2 infection seventeen non-synonymous mutations were observed, thirteen (13/17; 76.5%) of which occurred in the genomic region coding for spike. Fifteen (15/17; 88.2%) of these mutations have already been described in the context of variants of concern and include the prominent immune escape mutations S:E484K, S:D950N, S:P681H, S:N501Y, S:del(9), N:S235F and S:H655Y. Fifty percent of all mutations acquired by the investigated strain (11/22) are found in similar form in the Omicron variant of concern. The study shows the chronology of the evolution of intra-host mutations, which can be seen as the straight mutational response of the virus to specific antibodies and should therefore be given special attention in the rating of immune escape mutations of SARS-CoV-2.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Paul Naaber",
-        "author_inst": "SYNLAB Eesti"
-      },
-      {
-        "author_name": "Liina Tserel",
-        "author_inst": "University of Tartu"
+        "author_name": "Sissy Therese Sonnleitner",
+        "author_inst": "Medical University Innsbruck"
       },
       {
-        "author_name": "Kadri Kangro",
-        "author_inst": "Icosagen Cell Factory"
+        "author_name": "Martina Prelog",
+        "author_inst": "University Hospital Wuerzburg"
       },
       {
-        "author_name": "Epp Sepp",
-        "author_inst": "University of Tartu"
+        "author_name": "Stefanie Sonnleitner",
+        "author_inst": "Dr. Gernot Walder GmbH"
       },
       {
-        "author_name": "Virge Jurjenson",
-        "author_inst": "SYNLAB Eesti"
+        "author_name": "Eva Hinterbichler",
+        "author_inst": "Dr. Gernot Walder GmbH"
       },
       {
-        "author_name": "Jaanika Karner",
-        "author_inst": "University of Tartu"
+        "author_name": "Hannah Halbfurter",
+        "author_inst": "Dr. Gernot Walder GmbH"
       },
       {
-        "author_name": "Liis Haljasmagi",
-        "author_inst": "University of Tartu"
+        "author_name": "Dominik Kopecky",
+        "author_inst": "Dr. Gernot Walder GmbH"
       },
       {
-        "author_name": "Uku Haljasorg",
-        "author_inst": "University of Tartu"
+        "author_name": "Giovanni Almanzar",
+        "author_inst": "University Hospital Wuerzburg"
       },
       {
-        "author_name": "Marilin Kuusk",
-        "author_inst": "Icosagen Cell Factory"
+        "author_name": "Stephan Koblmueller",
+        "author_inst": "University of Graz"
       },
       {
-        "author_name": "Joachim M Gerhold",
-        "author_inst": "Icosagen Cell Factory"
+        "author_name": "Christian Sturmbauer",
+        "author_inst": "University of Graz"
       },
       {
-        "author_name": "Anu Planken",
-        "author_inst": "Icosagen Cell Factory"
+        "author_name": "Leonard Feist",
+        "author_inst": "GenXPro GmbH, Frankfurt"
       },
       {
-        "author_name": "Mart Ustav",
-        "author_inst": "Icosagen Cell Factory"
+        "author_name": "Ralf Horres",
+        "author_inst": "GenXPro GmbH, Frankfurt"
       },
       {
-        "author_name": "Kai Kisand",
-        "author_inst": "University of Tartu"
+        "author_name": "Wilfried Posch",
+        "author_inst": "Medical University Innsbruck"
       },
       {
-        "author_name": "Part Peterson",
-        "author_inst": "University of Tartu"
+        "author_name": "Gernot Walder",
+        "author_inst": "Dr. Gernot Walder GmbH"
       }
     ],
     "version": "1",
@@ -327027,61 +328582,53 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2022.03.02.22271806",
-    "rel_title": "Covid-19 Exposure Assessment Tool (CEAT): Easy-to-use tool to quantify exposure based on airflow, group behavior, and infection prevalence in the community",
+    "rel_doi": "10.1101/2022.03.03.22271836",
+    "rel_title": "The relationship between BMI and COVID-19: exploring misclassification and selection bias in a two-sample Mendelian randomisation study",
     "rel_date": "2022-03-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.02.22271806",
-    "rel_abs": "The COVID-19 Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to SARS-CoV-2 for various scenarios, providing understanding of how combinations of protective measures affect exposure, dose, and risk. CEAT incorporates mechanistic, stochastic and epidemiological factors including the: 1) emission rate of virus, 2) viral aerosol degradation and removal, 3) duration of activity/exposure, 4) inhalation rates, 5) ventilation rates (indoors/outdoors), 6) volume of indoor space, 7) filtration, 8) mask use and effectiveness, 9) distance between people, 10) group size, 11) current infection rates by variant, 12) prevalence of infection and immunity in the community, 13) vaccination rates of the community, and 14) implementation of COVID-19 testing procedures. Demonstration of CEAT, from published studies of COVID-19 transmission events, shows the model accurately predicts transmission. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures. Given its accuracy and flexibility, the wide use of CEAT will have a long lasting beneficial impact in managing both the current COVID-19 pandemic as well as a variety of other scenarios.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.03.22271836",
+    "rel_abs": "ObjectiveTo use the example of the effect of body mass index (BMI) on COVID-19 susceptibility and severity to illustrate methods to explore potential selection and misclassification bias in Mendelian randomisation (MR) of COVID-19 determinants.\n\nDesignTwo-sample MR analysis.\n\nSettingSummary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) and COVID-19 Host Genetics Initiative (HGI) consortia.\n\nParticipants681,275 participants in GIANT and more than 2.5 million people from the COVID-19 HGI consortia.\n\nExposureGenetically instrumented BMI.\n\nMain outcome measuresSeven case/control definitions for SARS-CoV-2 infection and COVID-19 severity: very severe respiratory confirmed COVID-19 vs not hospitalised COVID-19 (A1) and vs population (those who were never tested, tested negative or had unknown testing status (A2)); hospitalised COVID-19 vs not hospitalised COVID-19 (B1) and vs population (B2); COVID-19 vs lab/self-reported negative (C1) and vs population (C2); and predicted COVID-19 from self-reported symptoms vs predicted or self-reported non-COVID-19 (D1).\n\nResultsWith the exception of A1 comparison, genetically higher BMI was associated with higher odds of COVID-19 in all comparison groups, with odds ratios (OR) ranging from 1.11 (95%CI: 0.94, 1.32) for D1 to 1.57 (95%CI: 1.57 (1.39, 1.78) for A2. As a method to assess selection bias, we found no strong evidence of an effect of COVID-19 on BMI in a  no-relevance analysis, in which COVID-19 was considered the exposure, although measured after BMI. We found evidence of genetic correlation between COVID-19 outcomes and potential predictors of selection determined a priori (smoking, education, and income), which could either indicate selection bias or a causal pathway to infection. Results from multivariable MR adjusting for these predictors of selection yielded similar results to the main analysis, suggesting the latter.\n\nConclusionsWe have proposed a set of analyses for exploring potential selection and misclassification bias in MR studies of risk factors for SARS-CoV-2 infection and COVID-19 and demonstrated this with an illustrative example. Although selection by socioeconomic position and arelated traits is present, MR results are not substantially affected by selection/misclassification bias in our example. We recommend the methods we demonstrate, and provide detailed analytic code for their use, are used in MR studies assessing risk factors for COVID-19, and other MR studies where such biases are likely in the available data.\n\nSummaryO_ST_ABSWhat is already known on this topicC_ST_ABS- Mendelian randomisation (MR) studies have been conducted to investigate the potential causal relationship between body mass index (BMI) and COVID-19 susceptibility and severity.\n- There are several sources of selection (e.g. when only subgroups with specific characteristics are tested or respond to study questionnaires) and misclassification (e.g. those not tested are assumed not to have COVID-19) that could bias MR studies of risk factors for COVID-19.\n- Previous MR studies have not explored how selection and misclassification bias in the underlying genome-wide association studies could bias MR results.\n\n\nWhat this study adds- Using the most recent release of the COVID-19 Host Genetics Initiative data (with data up to June 2021), we demonstrate a potential causal effect of BMI on susceptibility to detected SARS-CoV-2 infection and on severe COVID-19 disease, and that these results are unlikely to be substantially biased due to selection and misclassification.\n- This conclusion is based on no evidence of an effect of COVID-19 on BMI (a  no-relevance control study, as BMI was measured before the COVID-19 pandemic) and finding genetic correlation between predictors of selection (e.g. socioeconomic position) and COVID-19 for which multivariable MR supported a role in causing susceptibility to infection.\n- We recommend studies use the set of analyses demonstrated here in future MR studies of COVID-19 risk factors, or other examples where selection bias is likely.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Brian Schimmoller",
-        "author_inst": "Signature Science LLC"
-      },
-      {
-        "author_name": "Nidia S Trovao",
-        "author_inst": "Fogarty International Center, National Institutes of Health"
-      },
-      {
-        "author_name": "Molly Isbell",
-        "author_inst": "Signature Science LLC"
+        "author_name": "Gemma Louise Clayton",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Chirag Goel",
-        "author_inst": "Northwestern University Feinberg School of Medicine"
+        "author_name": "Ana Goncalves Soares",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Benjamin F Heck",
-        "author_inst": "Bastion Technologies, NASA Ames Research Center"
+        "author_name": "Neil Goulding",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Tenley C Archer",
-        "author_inst": "Biomea Fusion, Inc."
+        "author_name": "Maria Carolina Goncalves Borges",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Klint D Cardinal",
-        "author_inst": "Leidos, Inc., NASA Ames Research Center"
+        "author_name": "Michael Holmes",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Neil B Naik",
-        "author_inst": "Leidos, Inc., NASA Ames Research Center"
+        "author_name": "George Davey Smith",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Som Dutta",
-        "author_inst": "Mechanical & Aerospace Engineering, Utah State University"
+        "author_name": "Kate Tilling",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Ahleah Rohr Daniel",
-        "author_inst": "Space Biosciences Division, NASA Ames Research Center"
+        "author_name": "Deborah A Lawlor",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Afshin Beheshti",
-        "author_inst": "KBR, NASA Ames Research Center"
+        "author_name": "Alice R Carter",
+        "author_inst": "Medical Research Council Integrative Epidemiology Unit, University of Bristol"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -328913,65 +330460,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.02.23.22271355",
-    "rel_title": "Genomic epidemiology offers high resolution estimates of serial intervals for COVID-19",
+    "rel_doi": "10.1101/2022.02.17.22270791",
+    "rel_title": "Vaccine effectiveness and duration of protection against symptomatic and severe Covid-19 during the first year of vaccination in France",
     "rel_date": "2022-03-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.23.22271355",
-    "rel_abs": "Estimating key aspects of transmission is crucial in infectious disease control. Serial intervals - the time between symptom onset in an infector and infectee - are fundamental, and help to define rates of transmission, estimates of reproductive numbers, and vaccination levels needed to prevent transmission. However, estimating the serial interval requires knowledge of individuals contacts and exposures (who infected whom), which is typically obtained through resource-intensive contact tracing efforts. We develop an alternate framework that uses virus sequences to inform who infected whom and thereby estimate serial intervals. The advantages are many-fold: virus sequences are often routinely collected to support epidemiological investigations and to monitor viral evolution. The genomic approach offers high resolution and cluster-specific estimates of the serial interval that are comparable with those obtained from contact tracing data. Our approach does not require contact tracing data, and can be used in large populations and over a range of time periods. We apply our techniques to SARS-CoV-2 sequence data from the first two waves of COVID-19 in Victoria, Australia. We find that serial interval estimates vary between clusters, supporting the need to monitor this key parameter and use updated estimates in onward applications. Compared to an early published serial interval estimate, using cluster-specific serial intervals can cause estimates of the effective reproduction number Rt to vary by a factor of up to 2-3. We also find that serial intervals estimated in settings such as schools and meat processing/packing plants tend to be shorter than those estimated in healthcare facilities.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.17.22270791",
+    "rel_abs": "BackgroundSARS-CoV-2 continues to spread despite fast vaccine rollout, which could be attributed to waning immunity or to a reduced protection against some variants. A thorough characterization of vaccine protection and its duration in time is needed to inform vaccination policies and enhance public trust.\n\nMethodsWe matched three national databases with exhaustive information on screening, vaccination and hospitalizations in France over the year 2021. We performed a two-step analysis to estimate vaccine effectiveness against severe forms of Covid-19 in people aged 50 years or over, combining: (i) a test-negative case-control design to assess vaccine effectiveness against symptomatic infections; and (ii) a survival analysis to assess the additional protection against severe outcomes (hospitalizations and inpatient deaths) in infected individuals.\n\nResultsWe found a high vaccine effectiveness in people aged 50 years or more, reaching 82% against symptomatic infections and 94% against severe outcomes, after a full vaccination scheme.\n\nVaccine effectiveness against symptomatic infections strongly decreased over time, dropping to 53% after six months, but remained high against severe forms (90% after six months). The booster dose allowed restoring high protection levels. Vaccine protection and its evolution in time, showed little difference against the variants that circulated prior to December 2021 in France, including the Delta variant.\n\nConclusionThough vaccine immunity decreases over time, vaccination remains crucial to provide individual protection against severe diseases. This decline can be reversed by the injection of a booster dose.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jessica E Stockdale",
-        "author_inst": "Department of Mathematics, Simon Fraser University, Canada"
-      },
-      {
-        "author_name": "Kurnia Susvitasari",
-        "author_inst": "Department of Mathematics, Simon Fraser University, Canada"
-      },
-      {
-        "author_name": "Paul Tupper",
-        "author_inst": "Department of Mathematics, Simon Fraser University, Canada"
-      },
-      {
-        "author_name": "Benjamin Sobkowiak",
-        "author_inst": "Department of Mathematics, Simon Fraser University, Canada"
-      },
-      {
-        "author_name": "Nicola Mulberry",
-        "author_inst": "Department of Mathematics, Simon Fraser University, Canada"
-      },
-      {
-        "author_name": "Anders Gon\u00e7alves da Silva",
-        "author_inst": "Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for In"
-      },
-      {
-        "author_name": "Anne E Watt",
-        "author_inst": "Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for In"
-      },
-      {
-        "author_name": "Norelle Sherry",
-        "author_inst": "Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for In"
-      },
-      {
-        "author_name": "Corinna Minko",
-        "author_inst": "Victorian Department of Health, Melbourne, Victoria, Australia"
+        "author_name": "Milena Suarez Castillo",
+        "author_inst": "Insee"
       },
       {
-        "author_name": "Benjamin P Howden",
-        "author_inst": "Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for In"
+        "author_name": "Hamid Khaoua",
+        "author_inst": "Drees"
       },
       {
-        "author_name": "Courtney R Lane",
-        "author_inst": "Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for In"
-      },
-      {
-        "author_name": "Caroline Colijn",
-        "author_inst": "Department of Mathematics, Simon Fraser University, Canada"
+        "author_name": "No\u00e9mie Courtejoie",
+        "author_inst": "Drees"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -330811,67 +332322,99 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.03.02.22271385",
-    "rel_title": "Impact of Delta and Vaccination on SARS-CoV-2 transmission risk: Lessons for Emerging Breakthrough infections",
+    "rel_doi": "10.1101/2022.03.01.22271735",
+    "rel_title": "Comparison of the reactogenicity and immunogenicity of a reduced and standard booster dose of the mRNA COVID-19 vaccine in healthy adults after two doses of inactivated vaccine.",
     "rel_date": "2022-03-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.02.22271385",
-    "rel_abs": "With the continuous emergence of SARS-CoV-2 variants of concern and implementation of mass-scale interventions like vaccination, understanding factors affecting disease transmission has critical implications for control efforts. Here we used a simple adapted N95 mask sampling method to demonstrate the impact of circulating SARS-CoV-2 variants and vaccination on 92 COVID-19 patients to expel virus into the air translating to a transmission risk. Between July and September 2021, when the Delta was the dominant circulating strain in Mumbai, we noted a two-fold increase in the proportion of people expelling virus (95%), about an eighty-fold increase in median viral load and a three-fold increase in high emitter type (41%; people expelling >1000 viral copy numbers in 30 minutes) compared to initial strains of 2020. Eight percent of these patients continued to be high emitters even after eight days of symptom onset, suggesting a probable increased transmission risk for Delta strain even at this stage. There was no significant difference in expelling pattern between partial, full and un-vaccinated individuals suggesting similar transmission risk. We noted significantly more infections among vaccinated study patients and their household members than unvaccinated, probably due to increased duration from vaccination and/or increased risk behaviour upon vaccination due to lower perceived threat. This study provides biological evidence for possible continued transmission of the Delta strain even with vaccination, emphasizing the need to continue COVID-19 appropriate behaviour. The study also indicates that the mask method may be useful for screening future vaccine candidates, therapeutics or interventions for their ability to block transmission.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.01.22271735",
+    "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic has been a serious healthcare problem worldwide since December 2019. The third dose of heterologous vaccine was recently approved by World Health Organization. The present study compared the reactogenicity and immunogenicity of the reduced and standard third booster dose of the BNT162b2 and mRNA-1273 vaccine in adults who previously received the two-dose CoronaVac vaccine. Results showed that headache, joint pain, and diarrhea were more frequent in the 15 g-than the 30 g-BNT162b2 groups, whereas joint pain and chilling were more frequent in the 100 g-than the 50 g-mRNA-1273 groups. No significant differences in immunogenicity were detected. These findings demonstrate that the reduced dose of the mRNA vaccines elicited antibody responses against the SARS-CoV-2 delta and omicron variants that were comparable to the standard dose. The reduced dose could be used to increase vaccine coverage in situations of limited global vaccine supply.\n\nHighlightsO_LIThe 15 g- and 30 g-BNT162b2, and 50 g- and 100 g-mRNA-1273 booster doses were compared\nC_LIO_LIBooster vaccination with the mRNA vaccine elicits high Ig and IgG anti-RBD in CoronaVac-vaccinated adults\nC_LIO_LINo differences were observed in antibody responses after the reduced or standard booster dose of the mRNA vaccine in CoronaVac-vaccinated adults\nC_LIO_LINeutralizing antibodies against the delta and omicron variants were significantly higher after the booster dose\nC_LIO_LINeutralizing antibody titers were lower against the omicron variant than the delta variant in all vaccinated adults\nC_LI",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Kalpana Sriraman",
-        "author_inst": "The Foundation for Medical Research, Mumbai, India"
+        "author_name": "Sitthichai Kanokudom",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.;Osteoarthritis and Musculoskeleton Research U"
       },
       {
-        "author_name": "Ambreen Shaikh",
-        "author_inst": "The Foundation for Medical Research, Mumbai, India"
+        "author_name": "Suvichada Assawakosri",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.;Osteoarthritis and Musculoskeleton Research U"
       },
       {
-        "author_name": "Smriti Vaswani",
-        "author_inst": "The Foundation for Medical Research, Mumbai, India"
+        "author_name": "Nungruthai suntronwong",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
       },
       {
-        "author_name": "Tejal Mestry",
-        "author_inst": "The Foundation for Medical Research, Mumbai, India"
+        "author_name": "Jira Chansaenroj",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
       },
       {
-        "author_name": "Grishma Patel",
-        "author_inst": "The Foundation for Medical Research, Mumbai, India"
+        "author_name": "Chompoonut Auphimai",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
       },
       {
-        "author_name": "Shalini Sakthivel",
-        "author_inst": "The Foundation for Medical Research"
+        "author_name": "Pornjarim Nilyanimit",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
       },
       {
-        "author_name": "Vikas Oswal",
-        "author_inst": "Vikas Nursing Home, Mumbai, India"
+        "author_name": "Preeyaporn Vichaiwattana",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
       },
       {
-        "author_name": "Pratibha Kadam",
-        "author_inst": "The Foundation for Medical Research, Mumbai, India"
+        "author_name": "Thanunrat Thongmee",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
       },
       {
-        "author_name": "Kayzad Nilgiriwala",
-        "author_inst": "The Foundation for Medical Research, Mumbai, India"
+        "author_name": "Ritthideach Yorsaeng",
+        "author_inst": "Faculty of Medicine, Chulalongkorn University"
       },
       {
-        "author_name": "Daksha Shah",
-        "author_inst": "Municipal Corporation of Greater Mumbai, Mumbai, India"
+        "author_name": "Thaneeya Duangchinda",
+        "author_inst": "Division of Dengue Hemorrhagic Fever Research, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand.;Siriraj Center of Research Ex"
       },
       {
-        "author_name": "Mangala Gomare",
-        "author_inst": "Municipal Corporation of Greater Mumbai,Mumbai, India"
+        "author_name": "Warangkana Chantima",
+        "author_inst": "Division of Dengue Hemorrhagic Fever Research; Siriraj Center of Research Excellence in Dengue and Emerging Pathogens, Faculty of Medicine, Siriraj Hospital, Ma"
       },
       {
-        "author_name": "Nerges Mistry",
-        "author_inst": "The Foundation for Medical Research,, Mumbai, India"
+        "author_name": "Pattarakul Pakchotanon",
+        "author_inst": "Molecular Biology of Dengue and Flaviviruses Research Team, National Center for Genetic Engineering and Biotechnology, National Science and Development Agency, "
+      },
+      {
+        "author_name": "Donchida Srimuan",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
+      },
+      {
+        "author_name": "Thaksaporn Thatsanatorn",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
+      },
+      {
+        "author_name": "Sirapa Klinfueng",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
+      },
+      {
+        "author_name": "Juthathip Mongkolsapaya",
+        "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK.; Chinese Academy of Medical Science (CAMS) Oxfor"
+      },
+      {
+        "author_name": "Natthinee Sudhinaraset",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand"
+      },
+      {
+        "author_name": "Nasamon Wanlapakorn",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand."
+      },
+      {
+        "author_name": "Sittisak Honsawek",
+        "author_inst": "Department of Biochemistry, Osteoarthritis and Musculoskeleton Research Unit, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospita"
+      },
+      {
+        "author_name": "Yong Poovorawan",
+        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.;The Royal Society of Thailand (FRS(T)), Sanam"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "allergy and immunology"
   },
   {
     "rel_doi": "10.1101/2022.03.01.22271717",
@@ -332677,31 +334220,91 @@
     "category": "cell biology"
   },
   {
-    "rel_doi": "10.1101/2022.02.27.482153",
-    "rel_title": "A strategy to optimize the peptide-based inhibitors against different mutants of the spike protein of SARS-CoV-2",
+    "rel_doi": "10.1101/2022.02.25.481974",
+    "rel_title": "An immunoPET probe to SARS-CoV-2 reveals early infection of the male genital tract in rhesus macaques",
     "rel_date": "2022-02-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.27.482153",
-    "rel_abs": "SARS-CoV-2 virus has caused high-priority health concerns at a global level. Vaccines have stalled the proliferation of viruses to some extent. Yet, the emergence of newer, potentially more infectious, and dangerous mutants such as delta and omicron are among the major challenges in finding a more permanent solution for this pandemic. The effectiveness of antivirals Molnupiravir and Paxlovid, authorized for emergency use by the FDA, are yet to be assessed at larger populations. Patients with a high risk of disease progression or hospitalization have received treatment with a combination of antibodies (antibody-cocktail). Most of the mutations leading to the new lineage of SARS-CoV-2 are found in the spike protein of this virus that plays a key role in facilitating host entry. The current study has investigated how to modify a promising peptide-based inhibitor of spike protein, LCB3, against common mutations in the target protein so that it retains its efficacy against the spike protein. LCB3 being a prototype for protein-based inhibitors is an ideal testing system to learn about protein-based inhibitors. Two common mutations N501Y and K417N are considered in this work. Using a structure-based approach that considers free energy decomposition of residues, distance, and the interactions between amino acids, we propose the substitutions of amino acid residues of LCB3 inhibitors. Our binding free energy calculations suggest a possible improvement in the binding affinity of existing inhibitor LCB3 to the mutant forms of the S-protein using simple substitutions at specific positions of the inhibitor. This approach, being general, can be used in different inhibitors and other mutations and help in fighting against SARS-CoV-2.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.25.481974",
+    "rel_abs": "The systemic nature of SARS-CoV-2 infection is highly recognized, but poorly characterized. A non-invasive and unbiased method is needed to clarify whole body spatiotemporal dynamics of SARS-CoV-2 infection after transmission. We recently developed a probe based on the anti-SARS-CoV-2 spike antibody CR3022 to study SARS-CoV-2 pathogenesis in vivo. Herein, we describe its use in immunoPET to investigate SARS-CoV-2 infection of three rhesus macaques. Using PET/CT imaging of macaques at different times post-SARS-CoV-2 inoculation, we track the 64Cu-labelled CR3022-F(ab)2 probe targeting the spike protein of SARS-CoV-2 to study the dynamics of infection within the respiratory tract and uncover novel sites of infection. Using this method, we uncovered differences in lung pathology between infection with the WA1 isolate and the delta variant, which were readily corroborated through computed tomography scans. The 64Cu-CR3022-probe also demonstrated dynamic changes occurring between 1- and 2-weeks post-infection. Remarkably, a robust signal was seen in the male genital tract (MGT) of all three animals studied. Infection of the MGT was validated by immunofluorescence imaging of infected cells in the testicular and penile tissue and severe pathology was observed in the testes of one animal at 2-weeks post-infection. The results presented here underscore the utility of using immunoPET to study the dynamics of SARS-CoV-2 infection to understand its pathogenicity and discover new anatomical sites of viral replication. We provide direct evidence for SARS-CoV-2 infection of the MGT in rhesus macaques revealing the possible pathologic outcomes of viral replication at these sites.\n\nGraphic AbstractPET/CT detected SARS-CoV-2 infection of 4 different tissues in the male genital tract illuminates the cause of COVID-19 clinical sequalae of male sexual health and fertility\n\nO_FIG O_LINKSMALLFIG WIDTH=189 HEIGHT=200 SRC=\"FIGDIR/small/481974v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (74K):\norg.highwire.dtl.DTLVardef@188c53aorg.highwire.dtl.DTLVardef@4c639forg.highwire.dtl.DTLVardef@120799forg.highwire.dtl.DTLVardef@110edb1_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFigure 1.C_FLOATNO Diagram shows schematic illustration of the male genital tract of the rhesus macaque. Virus icon shows sites of SARS-CoV-2 PET signal. Text highlighting the clinical sequalae associated with each sight of infection is shown in text adjacent to each infection site.\n\nC_FIG",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Prerna Priya",
-        "author_inst": "Purnea Mahila College"
+        "author_name": "Patrick J Madden",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
       },
       {
-        "author_name": "Abdul Basit",
-        "author_inst": "School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India"
+        "author_name": "Yanique Thomas",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
       },
       {
-        "author_name": "Pradipta Bandyopadhyay",
-        "author_inst": "School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India"
+        "author_name": "Robert V Blair",
+        "author_inst": "Division of Comparative Pathology, Tulane National Primate Research Center, Covington, Louisiana, USA"
+      },
+      {
+        "author_name": "Sadia Samer",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
+      },
+      {
+        "author_name": "Mark Doyle",
+        "author_inst": "Division of Comparative Pathology, Tulane National Primate Research Center, Covington, Louisiana, USA"
+      },
+      {
+        "author_name": "Cecily C Midkiff",
+        "author_inst": "Division of Comparative Pathology, Tulane National Primate Research Center, Covington, Louisiana, USA"
+      },
+      {
+        "author_name": "Lara A. Doyle-Meyers",
+        "author_inst": "Tulane National Primate Research Center, Covington, Louisiana, USA."
+      },
+      {
+        "author_name": "Mark E Becker",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
+      },
+      {
+        "author_name": "Muhammad S Arif",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
+      },
+      {
+        "author_name": "Michael D McRaven",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
+      },
+      {
+        "author_name": "Lacy M Simons",
+        "author_inst": "Department of Medicine, Division of Infectious Diseases, Feinberg School of Medicine, Chicago, IL, USA. Center for Pathogen Genomics and Microbial Evolution, Ha"
+      },
+      {
+        "author_name": "Ann M Carias",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
+      },
+      {
+        "author_name": "Elena Martinelli",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
+      },
+      {
+        "author_name": "Ramon Lorenzo-Redondo",
+        "author_inst": "Department of Medicine, Division of Infectious Diseases, Feinberg School of Medicine, Chicago, IL, USA. Center for Pathogen Genomics and Microbial Evolution, Ha"
+      },
+      {
+        "author_name": "Judd F Hultquist",
+        "author_inst": "Department of Medicine, Division of Infectious Diseases, Feinberg School of Medicine, Chicago, IL, USA. Center for Pathogen Genomics and Microbial Evolution, Ha"
+      },
+      {
+        "author_name": "Francois J Villinger",
+        "author_inst": "New Iberia Research Center, University of Louisiana-Lafayette, New Iberia, Louisiana, USA"
+      },
+      {
+        "author_name": "Ronald S Veazey",
+        "author_inst": "Division of Comparative Pathology, Tulane National Primate Research Center, Covington, Louisiana, USA"
+      },
+      {
+        "author_name": "Thomas J Hope",
+        "author_inst": "Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "biophysics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2022.02.27.482147",
@@ -334575,63 +336178,35 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2022.02.24.481684",
-    "rel_title": "Dictionary learning for integrative, multimodal, and scalable single-cell analysis",
+    "rel_doi": "10.1101/2022.02.25.22271520",
+    "rel_title": "Late-Ensemble of Convolutional Neural Networks with Test Time Augmentation for Chest XR COVID-19 Detection",
     "rel_date": "2022-02-26",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.24.481684",
-    "rel_abs": "Mapping single-cell sequencing profiles to comprehensive reference datasets represents a powerful alternative to unsupervised analysis. Reference datasets, however, are predominantly constructed from single-cell RNA-seq data, and cannot be used to annotate datasets that do not measure gene expression. Here we introduce  bridge integration, a method to harmonize singlecell datasets across modalities by leveraging a multi-omic dataset as a molecular bridge. Each cell in the multi-omic dataset comprises an element in a  dictionary, which can be used to reconstruct unimodal datasets and transform them into a shared space. We demonstrate that our procedure can accurately harmonize transcriptomic data with independent single cell measurements of chromatin accessibility, histone modifications, DNA methylation, and protein levels. Moreover, we demonstrate how dictionary learning can be combined with sketching techniques to substantially improve computational scalability, and harmonize 8.6 million human immune cell profiles from sequencing and mass cytometry experiments. Our approach aims to broaden the utility of single-cell reference datasets and facilitate comparisons across diverse molecular modalities.\n\nAvailabilityInstallation instructions, documentations, and vignettes are available at http://www.satijalab.org/seurat",
-    "rel_num_authors": 11,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.25.22271520",
+    "rel_abs": "COVID-19, a severe acute respiratory syndrome aggressively spread among global populations in just a few months. Since then, it has had four dominant variants (Alpha, Beta, Gamma and Delta) that are far more contagious than original. Accurate and timely diagnosis of COVID-19 is critical for analysis of damage to lungs, treatment, as well as quarantine management [7]. CT, MRI or X-rays image analysis using deep learning provide an efficient and accurate diagnosis of COVID-19 that could help to counter its outbreak. With the aim to provide efficient multi-class COVID-19 detection, recently, COVID-19 Detection challenge using X-ray is organized [12]. In this paper, the late-fusion of features is extracted from pre-trained various convolutional neural networks and fine-tuned these models using the challenge dataset. The DensNet201 with Adam optimizer and EffecientNet-B3 are fine-tuned on the challenge dataset and ensembles the features to get the final prediction. Besides, we also considered the test time augmentation technique after the late-ensembling approach to further improve the performance of our proposed solution. Evaluation on Chest XR COVID-19 showed that our model achieved overall accuracy is 95.67%. We made the code is publicly available1. The proposed approach was ranked 6th in Chest XR COVID-19 detection Challenge [1].",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Yuhan Hao",
-        "author_inst": "New York Genome Center"
-      },
-      {
-        "author_name": "Tim Stuart",
-        "author_inst": "New York Genome Center"
-      },
-      {
-        "author_name": "Madeline Kowalski",
-        "author_inst": "New York Genome Center"
+        "author_name": "Abdul Qayyum",
+        "author_inst": "University of Burgundy, Dijon, France"
       },
       {
-        "author_name": "Saket Choudhary",
-        "author_inst": "New York Genome Center"
-      },
-      {
-        "author_name": "Paul Hoffman",
-        "author_inst": "New York Genome Center"
-      },
-      {
-        "author_name": "Austin Hartman",
-        "author_inst": "New York Genome Center"
-      },
-      {
-        "author_name": "Avi Srivastava",
-        "author_inst": "New York Genome Center"
-      },
-      {
-        "author_name": "Gesmira Molla",
-        "author_inst": "New York Genome Center"
-      },
-      {
-        "author_name": "Shaista Madad",
-        "author_inst": "New York Genome Center"
+        "author_name": "Imran Razzak",
+        "author_inst": "Deakin University, Geelong, Australia"
       },
       {
-        "author_name": "Carlos Fernandez-Granda",
-        "author_inst": "Center for Data Science, New York University"
+        "author_name": "Moona Mazher",
+        "author_inst": "University Rovira i Virgili, Spain"
       },
       {
-        "author_name": "Rahul Satija",
-        "author_inst": "New York Genome Center"
+        "author_name": "Domenec Puig",
+        "author_inst": "University Rovira i Virgili, Spain"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "genomics"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2022.02.23.22271303",
@@ -336409,43 +337984,23 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.02.24.22271468",
-    "rel_title": "Clinical and Virologic Factors associated with Outcomes of COVID-19 before and after Vaccination among Veterans: Retrospective Analysis from Six New England States",
-    "rel_date": "2022-02-25",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.24.22271468",
-    "rel_abs": "BackgroundA region-wide analysis of COVID-19 outcomes in New England has not been done. We aimed to characterize clinical, demographic, and vaccination status affecting COVID-19 clinical outcomes and describe viral epidemiology.\n\nMethodsClinical variables of Veterans with COVID-19 in Veterans Administration healthcare systems in six New England states from April 8, 2020, to September 2, 2021 were correlated with outcomes of 30-day mortality, non-psychiatric hospitalization, intensive care unit admission (ICU-care), and post-vaccination infection. We sequenced 754 whole viral genomes and 197 partial genomes.\n\nResultsOf 4,170 Veterans with COVID-19, 81% were White, 8% women, mean age was 60.1 {+/-}17.7 years, and 2,399 became fully vaccinated. Overall, 19% Veterans needed hospitalization, 2.8% required ICU-care, and 3.7% died. Veterans with post-vaccination COVID-19 were older, with higher rates of tobacco/drug use, CKD, and malignancy, and 0.38% died. Among the unvaccinated, ICU-care and mortality correlated with age, while hospitalization correlated with age, male sex, black race, drug use, chronic heart disease, COPD, CKD, and chronic liver disease. Age, CKD, and alcohol use correlated with hospitalization in vaccinated patients.\n\nMost New England Veterans (>97%) were infected with B.1 sub-lineages with the D614G mutation in 2020 and early 2021. B.1.617.2 lineage (71%) predominated after July 2021, including the post-vaccination infections.\n\nConclusionIn New England Veterans with mean age of 60 years, age and CKD significantly correlated with hospitalization regardless of vaccination-status. Age correlated with mortality and ICU-care among the unvaccinated. The Delta variant of SARS-CoV-2 (B.1.617.2) dominated post-vaccination infections.",
-    "rel_num_authors": 6,
+    "rel_doi": "10.1101/2022.02.21.481324",
+    "rel_title": "A single-dose of the deactivated rabies virus vectored COVID-19 vaccine, CORAVAX, is highly efficacious and alleviates lung inflammation in the hamster model.",
+    "rel_date": "2022-02-24",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.21.481324",
+    "rel_abs": "Without sufficient herd immunity through either vaccination or natural infection, the Coronavirus Disease 2019 pandemic is unlikely to be controlled. Waning immunity with the currently approved vaccines suggests the need to evaluate vaccines causing the induction of long-term responses. Here we report the immunogenicity and efficacy of our adjuvanted single-dose Rabies vectored SARS CoV-2 S1 vaccine, CORAVAX, in hamsters. CORAVAX induces high SARS CoV-2 S1 specific and virus-neutralizing antibodies (VNA) that prevent weight loss, viral loads, disease, lung inflammation, and the cytokine storm in hamsters. We also observed high Rabies VNA titers. In summary, CORAVAX is a promising dual antigen vaccine candidate for clinical evaluation against SARS CoV-2 and Rabies virus.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Megan Lee",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "Danielle Cosenino",
-        "author_inst": "VA Connecticut Healthcare System"
-      },
-      {
-        "author_name": "Tassos C Kyriakides",
-        "author_inst": "VA Connecticut Healthcare System"
-      },
-      {
-        "author_name": "Tricia Cavallaro",
-        "author_inst": "VA Connecticut Healthcare System"
-      },
-      {
-        "author_name": "Gary Stack",
-        "author_inst": "VA Connecticut Healthcare System"
-      },
-      {
-        "author_name": "Shaili Gupta",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Matthias  Johannes Schnell",
+        "author_inst": "Thomas Jefferson University - Center City Campus: Thomas Jefferson University"
       }
     ],
     "version": "1",
-    "license": "cc0",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.02.22.481436",
@@ -337995,39 +339550,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.02.23.22271403",
-    "rel_title": "Quantifying antibody dynamics of severe and non-severe patients with COVID-19",
+    "rel_doi": "10.1101/2022.02.23.22271372",
+    "rel_title": "Genomic surveillance of SARS-CoV-2 reveals emergence of Omicron BA.2 in Islamabad, Pakistan",
     "rel_date": "2022-02-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.23.22271403",
-    "rel_abs": "COVID-19 pandemic is a major public health threat with unanswered questions regarding the role of the immune system in the severity level of the disease. In this paper, based on antibody kinetic data of patients with different disease severity, topological data analysis highlights clear differences in the shape of antibody dynamics between three groups of patients, which were non-severe, severe, and one intermediate case of severity. Subsequently, different mathematical models were developed to quantify the dynamics between the different severity groups. The best model was the one with the lowest media value of Akaike Information Criterion for all groups of patients. Although it has been reported high IgG level in severe patients, our findings suggest that IgG antibodies in severe patients may be less effective than non-severe patients due to early B cell production and early activation of the seroconversion process from IgM to IgG antibody.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.23.22271372",
+    "rel_abs": "The Omicron variant of SARS-CoV-2 has rapidly replace previous variants of SARS CoV2 around the globe and is now a major variant of concern. The genomic surveillance of Omicron variant also reveals spread of its subvariant BA.2 which has differing transmissibility in comparison to its other subvariant BA.1. BA.1 and BA.2 harbors different mutational profile. One of the important change in both the subvariants is the presence of 69-70 deletion in BA.1 and absence of this deletion in BA.2. This deletion can be used as tool for the detection of omicron sub variants using real time PCR. In the current study we have used the TaqPath COVID-19 PCR kit for the detection of 69-70 deletion followed by genotyping using SNPsig(R) SARS-CoV-2 (EscapePLEX) kit (PrimerDesign, UK) that target K417N, E484K, and P681R mutations. The samples with the amplification of spike gene and K417N were termed as probable BA.2 cases. A subset of samples (n=13) were further subjected to whole genome sequencing. The results showed all the 13 samples were of BA.2. Hence, this assay can be used as a cost effective method for the detection of omicron BA.2 variant using real time PCR in resource limiting settings. Moreover, the detection of BA.2 with highly transmissible mutations in Islamabad, Pakistan may potentially increase the number of positive cases. In that scenario, there has to be stringent genomic surveillance to understand the circulating lineages in the country.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Fernanda Ordonez-Jimenez",
-        "author_inst": "UNAM"
+        "author_name": "Massab Umair",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Rodolfo Blanco-Rodriguez",
-        "author_inst": "UNAM"
+        "author_name": "Aamer Ikram",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Alexis Erich S. Almocera",
-        "author_inst": "University of the Philippines Visayas"
+        "author_name": "Zaira Rehman",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Gustavo Chinney-Herrera",
-        "author_inst": "UNAM"
+        "author_name": "Syed Adnan Haider",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Esteban Abelardo Hernandez Vargas",
-        "author_inst": "UNAM"
+        "author_name": "Muhammad Ammar",
+        "author_inst": "National Institute of Health"
+      },
+      {
+        "author_name": "Nazish Badar",
+        "author_inst": "National Institute of Health"
+      },
+      {
+        "author_name": "Qasim Ali",
+        "author_inst": "National Institute of Health"
+      },
+      {
+        "author_name": "Muhammad Suleman Rana",
+        "author_inst": "National Institute of Health"
+      },
+      {
+        "author_name": "Muhammad Salman",
+        "author_inst": "National Institute of Health"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.02.23.22271411",
@@ -339792,99 +341363,139 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2022.02.19.481107",
-    "rel_title": "Identification of a SARS-CoV-2 host metalloproteinase-dependent entry pathway differentially used by SARS-CoV-2 and variants of concern Alpha, Delta, and Omicron",
+    "rel_doi": "10.1101/2022.02.19.481089",
+    "rel_title": "Targeted Down Regulation Of Core Mitochondrial Genes During SARS-CoV-2 Infection",
     "rel_date": "2022-02-22",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.19.481107",
-    "rel_abs": "To infect cells, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) binds to angiotensin converting enzyme 2 (ACE2) via its spike glycoprotein (S), delivering its genome upon S-mediated membrane fusion. SARS-CoV-2 uses two distinct entry pathways: 1) a surface, serine protease-dependent or 2) an endosomal, cysteine protease-dependent pathway. In investigating serine protease-independent cell-cell fusion, we found that the matrix metalloproteinases (MMPs), MMP2/9, can activate SARS-CoV-2 S fusion activity, but not that of SARS-CoV-1. Importantly, metalloproteinase activation of SARS-CoV-2 S represents a third entry pathway in cells expressing high MMP levels. This route of entry required cleavage at the S1/S2 junction in viral producer cells and differential processing of variants of concern S dictated its usage. In addition, metalloproteinase inhibitors reduced replicative Alpha infection and abrogated syncytia formation. Finally, we found that the Omicron S exhibit reduced metalloproteinase-dependent fusion and viral entry. Taken together, we identified a MMP2/9-dependent mode of activation of SARS-CoV-2 S. As MMP2/9 are released during inflammation and severe COVID-19, they may play important roles in SARS-CoV-2 S-mediated cytopathic effects, tropism, and disease outcome.",
-    "rel_num_authors": 20,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.19.481089",
+    "rel_abs": "Defects in mitochondrial oxidative phosphorylation (OXPHOS) have been reported in COVID-19 patients, but the timing and organs affected vary among reports. Here, we reveal the dynamics of COVID-19 through transcription profiles in nasopharyngeal and autopsy samples from patients and infected rodent models. While mitochondrial bioenergetics is repressed in the viral nasopharyngeal portal of entry, it is up regulated in autopsy lung tissues from deceased patients. In most disease stages and organs, discrete OXPHOS functions are blocked by the virus, and this is countered by the host broadly up regulating unblocked OXPHOS functions. No such rebound is seen in autopsy heart, results in severe repression of genes across all OXPHOS modules. Hence, targeted enhancement of mitochondrial gene expression may mitigate the pathogenesis of COVID-19.\n\nOne-Sentence SummaryCovid-19 is associated with targeted inhibition of mitochondrial gene transcription.",
+    "rel_num_authors": 30,
     "rel_authors": [
       {
-        "author_name": "Mehdi Benlarbi",
-        "author_inst": "University of Ottawa"
+        "author_name": "Justin Frere",
+        "author_inst": "New York University"
       },
       {
-        "author_name": "Genevi\u00e8ve Laroche",
-        "author_inst": "University of Ottawa"
+        "author_name": "Sonja M Best",
+        "author_inst": "Rocky Mountain Laboratories NIAID, COVID-19 International Research Team"
       },
       {
-        "author_name": "Corby Fink",
-        "author_inst": "Western University"
+        "author_name": "Henry Cope",
+        "author_inst": "University of Nottingham"
       },
       {
-        "author_name": "Kathy Fu",
-        "author_inst": "University of Ottawa"
+        "author_name": "Viktorija Zaksas",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Rory P Mulloy",
-        "author_inst": "University of Ottawa"
+        "author_name": "Amanda Saravia-Butler",
+        "author_inst": "NASA Ames Research Center, Logyx LLC"
       },
       {
-        "author_name": "Alexandra Phan",
-        "author_inst": "University of Ottawa"
+        "author_name": "Cem Meydan",
+        "author_inst": "Weill Cornell Medicine, COVID-19 International Research Team"
       },
       {
-        "author_name": "Ardeshir Ariana",
-        "author_inst": "University of Ottawa"
+        "author_name": "Jonathan Foox",
+        "author_inst": "Weill Cornell Medical College"
       },
       {
-        "author_name": "Corina M Stewart",
-        "author_inst": "University of Ottawa"
+        "author_name": "Christopher Mozsary",
+        "author_inst": "Weill Cornell Medicine"
       },
       {
-        "author_name": "J\u00e9r\u00e9mie Pr\u00e9vost",
-        "author_inst": "CRCHUM / Universit\u00e9 de Montr\u00e9al"
+        "author_name": "Yared H Kidane",
+        "author_inst": "Scottish Rite for Children, COVID-19 International Research Team"
       },
       {
-        "author_name": "Guillaume Beaudoin-Bussi\u00e8res",
-        "author_inst": "CRCHUM"
+        "author_name": "Waldemar Priebe",
+        "author_inst": "University of Texas MD Anderson Cancer Center, COVID-19 International Research Team"
       },
       {
-        "author_name": "Redaet Daniel",
-        "author_inst": "University of Ottawa"
+        "author_name": "Mark Emmett",
+        "author_inst": "University of Texas Medical Branch, COVID-19 International Research Team"
       },
       {
-        "author_name": "Yuxia Bo",
-        "author_inst": "University of Ottawa"
+        "author_name": "Robert Meller",
+        "author_inst": "Morehouse School of Medicine, COVID-19 International Research Team"
       },
       {
-        "author_name": "Julien Yockell-Leli\u00e8vre",
-        "author_inst": "The Ottawa Hospital Research Institute"
+        "author_name": "Urminder Singh",
+        "author_inst": "Iowa State University, COVID-19 International Research Team."
       },
       {
-        "author_name": "William L Stanford",
-        "author_inst": "The Ottawa Hospital Research Institute"
+        "author_name": "Yaron Bram",
+        "author_inst": "Weill Cornell Medicine"
       },
       {
-        "author_name": "Patrick M Gigu\u00e8re",
-        "author_inst": "University of Ottawa"
+        "author_name": "Benjamin R. tenOever",
+        "author_inst": "New York University Langone Medical Center"
       },
       {
-        "author_name": "Samira Mubareka",
-        "author_inst": "Sunnybrook Research Institute and University of Toronto"
+        "author_name": "Mark T. Heise",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Andr\u00e9s Finzi",
-        "author_inst": "Universit\u00e9 de Montr\u00e9al"
+        "author_name": "Nathaniel J. Moorman",
+        "author_inst": "University of North Carolina"
       },
       {
-        "author_name": "Gregory A Dekaban",
-        "author_inst": "University of Western Ontario"
+        "author_name": "Emily A. Madden",
+        "author_inst": "University of North Carolina"
       },
       {
-        "author_name": "Jimmy D Dikeakos",
-        "author_inst": "University of Western Ontario"
+        "author_name": "Sharon A. Taft-Benz",
+        "author_inst": "University of North Carolina"
       },
       {
-        "author_name": "Marceline C\u00f4t\u00e9",
-        "author_inst": "University of Ottawa"
+        "author_name": "Elizabeth J. Anderson",
+        "author_inst": "University of North Carolina"
+      },
+      {
+        "author_name": "Wes A. Sanders",
+        "author_inst": "University of North Carolina"
+      },
+      {
+        "author_name": "Rebekah J. Dickmander",
+        "author_inst": "University of North Carolina"
+      },
+      {
+        "author_name": "Victoria K. Baxter",
+        "author_inst": "University of North Carolina"
+      },
+      {
+        "author_name": "Stephen Baylin",
+        "author_inst": "Johns Hopkins University, School of Medicine, COVID-19 International Research Team."
+      },
+      {
+        "author_name": "Eve Wurtele",
+        "author_inst": "Iowa State University, COVID-19 International Research Team."
+      },
+      {
+        "author_name": "Pedro Moraes-vieira",
+        "author_inst": "University of Campinas, COVID-19 International Research Team."
+      },
+      {
+        "author_name": "Christopher Mason",
+        "author_inst": "Weill Cornell Medical College, New York Genome Center, COVID-19 International Research Team."
+      },
+      {
+        "author_name": "Jonathan C Schisler",
+        "author_inst": "The University of North Carolina at Chapel Hill, COVID-19 International Research Team."
+      },
+      {
+        "author_name": "Robert  E. Schwartz",
+        "author_inst": "Weill Cornell Graduate School of Medical Sciences, COVID-19 International Research Team."
+      },
+      {
+        "author_name": "Afshin Beheshti",
+        "author_inst": "KBR, NASA Ames Research Center, Broad Institute of MIT and Harvard, Cambridge, COVID-19 International Research Team."
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2022.02.21.481247",
@@ -341826,67 +343437,67 @@
     "category": "sexual and reproductive health"
   },
   {
-    "rel_doi": "10.1101/2022.02.16.22270690",
-    "rel_title": "Narratives of the convalescent plasma donor in a Peruvian social security hospital: motivations, fears, expectations and experiences",
+    "rel_doi": "10.1101/2022.02.17.22271142",
+    "rel_title": "Performance of three rapid antigen tests against the SARS-CoV-2 Omicron variant",
     "rel_date": "2022-02-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.16.22270690",
-    "rel_abs": "ObjectivesTo know and explore from convalescent plasma donators voices the experience in the blood donation process at a Peruvian social security hospital.\n\nMethodsQualitative study with a phenomenological design. The investigation was carried out in 01 hospitals of the social security of Peru. Semi-structured interviews were carried out.\n\nResultsEleven donors of convalescent plasma were interviewed. The main motivations for donating were being able to contribute to national research and supporting patients affected by COVID-19. Fears focus on the possible risk of contagion within the hospital. Donors emphasised the attention and support of health personnel alongside the donation procedure. The main expectations and suggestions point towards greater dissemination of donation campaigns with special emphasis on safety. Likewise, an improvement in the time of the donation procedure (from enrolment to the extraction of convalescent plasma), and the implementation of friendly spaces to encourage future blood donation campaigns were highlighted.\n\nConclusionsThe experience of the convalescent plasma donors was positive. However, improvements must be made in terms of processes and infrastructure to ensure future successful blood donation campaigns.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.17.22271142",
+    "rel_abs": "Rapid antigen detection tests (RADTs) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are now in widespread use in the United States. RADTs play an important role in maintaining an open society but require periodic reassessment to ensure test performance remains intact as the virus evolves. The nucleocapsid (N) protein is the target for the majority of RADTs and the SARS-CoV-2 Omicron variant has several N protein mutations that are previously uncharacterized. We sought to assess the impact of these mutations by testing 30 Omicron variant samples across a wide range of viral loads on three widely used RADTs: the iHealth COVID-19 Antigen Rapid Test, the ACON Laboratories FlowFlex COVID-19 Antigen Home Test, and the Abbott BinaxNOW COVID-19 Antigen Card, using 30 Delta variant samples as a comparator. We found no change in the analytic sensitivity of all three RADTs for detection of Omicron versus Delta, but noted differences in performance between assays. No RADT was able to detect samples with a cycle threshold (Ct) value of [&ge;]27.5 for the envelope gene target on the Roche cobas RT-PCR assay. Epidemiologic studies are necessary to correlate these findings with their real-world performance.",
     "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Silvana M Matassini Eyzaguirre",
-        "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n - IETSI, EsSalud, Lima, Per\u00fa."
+        "author_name": "Sanjat Kanjilal",
+        "author_inst": "Harvard Medical School & Harvard Pilgrim Healthcare Institute"
       },
       {
-        "author_name": "Christian Villanueva Yapa",
-        "author_inst": "Servicio de Medicina Transfusional, Hospital Nacional Egdardo Rebagliati, EsSalud, Lima, Per\u00fa"
+        "author_name": "Sujata Chalise",
+        "author_inst": "Brigham and Women's Hospital & Harvard Medical School"
       },
       {
-        "author_name": "Ausberto Chunga Chunga",
-        "author_inst": "Servicio de Patolog\u00eda Cl\u00ednica, Hospital Nacional Egdardo Rebagliati Martins, EsSalud, Lima, Per\u00fa"
+        "author_name": "Adnan Shami Shah",
+        "author_inst": "Brigham and Women's Hospital & Harvard Medical School"
       },
       {
-        "author_name": "Arturo Sagastegui Soto",
-        "author_inst": "Servicio de Medicina Transfusional, Hospital Nacional Egdardo Rebagliati, EsSalud, Lima, Per\u00fa"
+        "author_name": "Chi-An Cheng",
+        "author_inst": "Brigham and Women's Hospital & Harvard Medical School"
       },
       {
-        "author_name": "Ibeth Melania Neyra Vera",
-        "author_inst": "Servicio de Patolog\u00eda Cl\u00ednica, Hospital Nacional Egdardo Rebagliati Martins, EsSalud, Lima, Per\u00fa"
+        "author_name": "Yasmeen Senussi",
+        "author_inst": "Brigham and Women's Hospital & Harvard Medical School"
       },
       {
-        "author_name": "Suly Soto-Ordo\u00f1ez",
-        "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n - IETSI, EsSalud, Lima, Per\u00fa."
+        "author_name": "Rockib Uddin",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Martina Guillermo Roman",
-        "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n - IETSI, EsSalud, Lima, Per\u00fa."
+        "author_name": "Vamsi Thiriveedhi",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Martin Oyanguren Miranda",
-        "author_inst": "Servicio de Cuidados Intensivos, Hospital Nacional Egdardo Rebagliati Martins, EsSalud, Lima, Peru"
+        "author_name": "Ha Eun Cho",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Percy Soto-Becerra",
-        "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n - IETSI, EsSalud, Lima, Per\u00fa."
+        "author_name": "Seamus Carroll",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Yamilee Hurtado-Roca",
-        "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n - IETSI, EsSalud, Lima, Per\u00fa."
+        "author_name": "Jacob Lemieux",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Jorge L Magui\u00f1a",
-        "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n - IETSI, EsSalud, Lima, Per\u00fa."
+        "author_name": "Sarah Turbett",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Roger Vladimir Araujo-Castillo",
-        "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n - IETSI, EsSalud, Lima, Per\u00fa."
+        "author_name": "David R. Walt",
+        "author_inst": "Brigham and Women's Hospital & Harvard Medical School"
       }
     ],
     "version": "1",
     "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "hematology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.02.16.22271042",
@@ -343820,39 +345431,31 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.02.16.22271096",
-    "rel_title": "Analytical Sensitivity of the SalivaDirect\u2122 Assay on the Liberty16 for detecting SARS-CoV-2 B.1.1.529 Omicron",
+    "rel_doi": "10.1101/2022.02.16.22271093",
+    "rel_title": "A novel SEIR-e model for disease transmission and pathogen exposure",
     "rel_date": "2022-02-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.16.22271096",
-    "rel_abs": "The newly emerged Omicron variant of SARS-CoV-2 has numerous mutations that are not found in other variants of concern (VOCs). Despite acquiring extended functions in adapting to the host-cell environment, the viral genetic variation exerts a potential negative impact on a molecular test, which in turn, compromises public health and safety. The Liberty16 has been clinically validated as a flexible and accessible device system for running the affordable SalivaDirect real time PCR detection assay for SARS-CoV-2 especially in low resource settings. Preliminary, based on in-silico sequence analysis, we found that Omicrons mutation at position 28,311 overlaps with the CDC 2019-nCoV_N1 probe binding region. In order to verify the performance of CDC 2019-nCoV-N1 primers-probe set in detecting the Omicron variant of SARS-CoV-2, plasmids containing Wuhan/WH01/2019 (wild-type) and B.1.1.529 (Omicron) sequences were serially diluted and subsequently directed for SalivaDirect RT-qPCR detection on Liberty16 using commercially procured reagents. Our findings provide analytical support for reports that the mutations in the Omicron variant have little or no impact on SalivaDirect assay in terms of amplification efficiency and detection sensitivity using either standard and the recently reported fast Liberty16 SalivaDirect thermal cycling protocols.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.16.22271093",
+    "rel_abs": "In this study, we couple compartment models for indoor air quality and disease transmission to develop a novel SEIR-e model for disease transmission and pathogen exposure. In doing so, we gain insight into the contribution of people-people and people-pathogen interactions to the spread of transmissible diseases. A general modelling framework is used to assess the risk of infection in indoor environments due to people-pathogen interactions via inhalation of viral airborne aerosols, and contact with contaminated surfaces. We couple the indoor environment model with a standard disease transmission model to investigate how both people-people and people-pathogen interactions result in disease transmission. The coupled model is referred to as the SEIR-e model. To demonstrate the applicability of the SEIR-e model and the novel insights it can provide into different exposure pathways, parameter values which describe exposure due to people-people and people-pathogen interactions are inferred using Bayesian techniques and case data relating to the 2020 outbreak of COVID-19 in Victoria (Australia).",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Yen Pei Tan",
-        "author_inst": "Ubiquitome Limited"
-      },
-      {
-        "author_name": "Mila Al-Halbouni",
-        "author_inst": "Ubiquitome Limited"
-      },
-      {
-        "author_name": "Ching-Huan Chen",
-        "author_inst": "Ubiquitome Limited"
+        "author_name": "Tamara A Tambyah",
+        "author_inst": "Defence Science and Technology Group"
       },
       {
-        "author_name": "David B. Hirst",
-        "author_inst": "Ubiquitome Limited"
+        "author_name": "Matthew J Testolin",
+        "author_inst": "Defence Science and Technology Group"
       },
       {
-        "author_name": "Paul J. Pickering",
-        "author_inst": "Ubiquitome Limited"
+        "author_name": "Alexander M Hill",
+        "author_inst": "Defence Science and Technology Group"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.02.16.22271055",
@@ -345602,41 +347205,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.02.11.22270843",
-    "rel_title": "Evaluation of test-to-return after COVID-19 diagnosis in a Massachusetts public school district",
+    "rel_doi": "10.1101/2022.02.10.22270733",
+    "rel_title": "Differential durability of humoral and T cell immunity after two and three BNT162b2 vaccinations in adults aged >80 years",
     "rel_date": "2022-02-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.11.22270843",
-    "rel_abs": "The Centers for Disease Control allows rapid antigen testing (RAT) towards the end of a 5-day isolation for COVID-19 infection to determine eligibility to leave isolation. The impact of a test-to-return (TTR) program in schools is unknown. In January 2022 a Massachusetts school district initiated a TTR program utilizing a single school-administered RAT on days 5-9 after symptom onset or positive test, whichever was first. Of 636 students with COVID-19 infection, 408 (64.2%) participated in TTR; of these, 128 (31.4%) had a positive TTR rapid antigen test. Students who were symptomatic at any time during their infection were more likely to have a positive TTR than those who were never symptomatic (43.1% vs. 17.3%); positivity rates were lower when TTR was performed later during days 6-9. TTR may identify students who carry higher viral loads after recovery from COVID-19 infection thereby extending their isolation, while facilitating earlier return of those with negative results.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.10.22270733",
+    "rel_abs": "A third mRNA-based \"booster\" vaccination is the favored strategy to maintain protection against SARS-CoV-2 infection. Yet, significant waning of specific immunity within six months after 2nd vaccination, along with higher incidence of breakthrough infections associated with the time elapsed since 2nd vaccination raises concerns regarding the durability of immunity also after 3rd vaccination. We assessed virus-specific serum antibody and T cell response in the blood after vaccination with the mRNA vaccine BNT162b2 in more than 50 individuals older than 80 years. All old adults demonstrated a strong humoral response to 3rd vaccination which was at average higher and waned slower than the response to 2nd vaccination, indicative of enhanced humoral immunity. In contrast, their respective T cell response quantitatively limited to the level obtained after 2nd vaccination, with similar waning over time and no evidence for enhanced IFNg production. Because BNT162b2-mediated protection from the Omicron variant relies more on T cells than antibodies, our findings raise concern on the durability of protection from the Omicron variant by BNT162b2 in the senior population.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Sandra B. Nelson",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Addi Josua Romero Olmedo",
+        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Philipps-University Marburg"
       },
       {
-        "author_name": "Isaac Ravi Brenner",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Axel Ronald Schulz",
+        "author_inst": "Deutsches Rheumaforschungszentrum Berlin, Leibniz Institute"
       },
       {
-        "author_name": "Elizabeth Homan",
-        "author_inst": "Arlington Public Schools"
+        "author_name": "Svenja Hochstaetter",
+        "author_inst": "Institute of Virology, Philipps-University, Marburg, Germany"
       },
       {
-        "author_name": "Sarah Bott Lee",
-        "author_inst": "Arlington Public Schools"
+        "author_name": "Dennis Das Gupta",
+        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Philipps-University Marburg"
       },
       {
-        "author_name": "Christine Bongiorno",
-        "author_inst": "Town of Arlington, Massachusetts"
+        "author_name": "Heike Hirseland",
+        "author_inst": "Deutsches Rheumaforschungszentrum Berlin, Leibniz Institute"
       },
       {
-        "author_name": "Nira Pollock",
-        "author_inst": "Boston Children's Hospital"
+        "author_name": "Daniel Staudenraus",
+        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Philipps-University Marburg"
       },
       {
-        "author_name": "Andrea L Ciaranello",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Baerbel Camara",
+        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Philipps-University Marburg"
+      },
+      {
+        "author_name": "Kirsten Volland",
+        "author_inst": "Institute of Virology, Philipps-University, Marburg"
+      },
+      {
+        "author_name": "Veronique Hefter",
+        "author_inst": "Institute of Virology, Philipps-University, Marburg"
+      },
+      {
+        "author_name": "Siddhesh Sapre",
+        "author_inst": "Institute of Virology, Philipps-University, Marburg"
+      },
+      {
+        "author_name": "Verena Kraehling",
+        "author_inst": "Institute of Virology, Philipps-University, Marburg"
+      },
+      {
+        "author_name": "Helena Mueller-Kraeuter",
+        "author_inst": "Institute of Virology, Philipps-University, Marburg"
+      },
+      {
+        "author_name": "Henrik Mei",
+        "author_inst": "Deutsches Rheumaforschungszentrum Berlin, Leibniz Institute"
+      },
+      {
+        "author_name": "Christian Keller",
+        "author_inst": "Institute of Virology, Philipps-University, Marburg"
+      },
+      {
+        "author_name": "Michael Lohoff",
+        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Philipps-University Marburg"
       }
     ],
     "version": "1",
@@ -347848,59 +349483,55 @@
     "category": "sexual and reproductive health"
   },
   {
-    "rel_doi": "10.1101/2022.02.14.22270958",
-    "rel_title": "COVID-19 mortality and excess mortality among working-age Californians, by occupational sector: March 2020 through November 2021",
+    "rel_doi": "10.1101/2022.02.11.22270859",
+    "rel_title": "Clinical and economic benefits of lenzilumab plus standard of care compared with standard of care alone for the treatment of hospitalized patients with Coronavirus Disease 19 (COVID-19) from the perspective of National Health Service England",
     "rel_date": "2022-02-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.14.22270958",
-    "rel_abs": "BackgroundDuring the first year of the pandemic, essential workers faced higher rates of SARS-CoV-2 infection and COVID-19 mortality than non-essential workers. It is unknown whether disparities in pandemic-related mortality across occupational sectors have continued to occur, amidst SARS-CoV-2 variants and vaccine availability.\n\nMethodsWe obtained data on all deaths occurring in the state of California from 2016 through 2021. We restricted our analysis to California residents who were working age (18-65 years at time of death) and died of natural causes. Occupational sector was classified into 9 essential sectors; non-essential; or not in the labor market. We calculated the number of COVID-19 deaths in total and per capita that occurred in each occupational sector. Separately, using autoregressive integrated moving average models, we estimated total, per-capita, and relative excess natural-cause mortality by week between March 1, 2020, and November 30, 2021, stratifying by occupational sector. We additionally stratified analyses of occupational risk into regions with high versus low vaccine uptake, categorizing high-uptake regions as counties where at least 50% of the population completed a vaccination series by August 1, 2021.\n\nFindingsFrom March 2020 through November 2021, essential work was associated with higher COVID-19 and excess mortality compared with non-essential work, with the highest per-capita COVID-19 mortality in agriculture (131.8 per 100,000), transportation/logistics (107.1), manufacturing (103.3), and facilities (101.1). Essential workers continued to face higher COVID-19 and excess mortality during the period of widely available vaccines (March through November 2021). Between July and November 2021, emergency workers experienced higher per-capita COVID-19 mortality (113.7) than workers from any other sector. Essential workers faced the highest COVID-19 mortality in counties with low vaccination rates, a difference that was more pronounced during the period of the Delta surge in Summer 2021.\n\nInterpretationEssential workers have continued to bear the brunt of high COVID-19 and excess mortality throughout the pandemic, particularly in the agriculture, emergency, manufacturing, facilities, and transportation/logistics sectors. This high death toll has continued during periods of vaccine availability and the delta surge. In an ongoing pandemic without widespread vaccine coverage and anticipated threats of new variants, the US must actively adopt policies to more adequately protect essential workers.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.11.22270859",
+    "rel_abs": "PurposeEstimate the clinical and economic benefits of lenzilumab plus standard of care (SOC) compared with SOC alone in the treatment of hospitalized COVID-19 patients from the National Health Service (NHS) England perspective.\n\nMethodsA cost calculator was developed to estimate the clinical benefits and costs of adding lenzilumab to SOC in newly hospitalized COVID-19 patients over 28 days. The LIVE-AIR trial results informed the clinical inputs: failure to achieve survival without ventilation (SWOV), mortality, time to recovery, intensive care unit (ICU) admission, and invasive mechanical ventilation (IMV) use. Base case costs included drug acquisition and administration for lenzilumab and remdesivir and hospital resource costs based on level of care required. Clinical and economic benefits per weekly cohort of newly hospitalized patients were also estimated.\n\nResultsIn all populations examined, specified clinical outcomes were improved with lenzilumab plus SOC over SOC treatment alone. In a base case population aged <85 years with C-reactive protein (CRP) <150 mg/L, with or without remdesivir, adding lenzilumab to SOC was estimated to result in per-patient cost savings of {pound}1,162. In a weekly cohort of 4,754 newly hospitalized patients, addition of lenzilumab to SOC could result in 599 IMV uses avoided, 352 additional lives saved, and over {pound}5.5 million in cost savings. Scenario results for per-patient cost savings included: 1) aged <85 years, CRP <150 mg/L, and receiving remdesivir ({pound}3,127); 2) Black patients with CRP <150 mg/L ({pound}9,977); and 3) Black patients from the full population ({pound}2,369). Conversely, in the full mITT population, results estimated additional cost of {pound}4,005 per patient.\n\nConclusionFindings support clinical benefits for SWOV, mortality, time to recovery, time in ICU, time on IMV, and ventilator use, and an economic benefit from the NHS England perspective when adding lenzilumab to SOC for hospitalized COVID-19 patients.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Yea-Hung Chen",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Alicia R Riley",
-        "author_inst": "University of California, Santa Cruz"
+        "author_name": "Adrian Kilcoyne",
+        "author_inst": "Humanigen Inc"
       },
       {
-        "author_name": "Kate A Duchowny",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Edward Jordan",
+        "author_inst": "Humanigen Inc."
       },
       {
-        "author_name": "Helene E Aschmann",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Kimberly Thomas",
+        "author_inst": "EVERSANA"
       },
       {
-        "author_name": "Ruijia Chen",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Alicia N. Pepper",
+        "author_inst": "EVERSANA"
       },
       {
-        "author_name": "Mathew V Kiang",
-        "author_inst": "Stanford University"
+        "author_name": "Allen Zhou",
+        "author_inst": "EVERSANA"
       },
       {
-        "author_name": "Alyssa Mooney",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Dale Chappell",
+        "author_inst": "Humanigen Inc."
       },
       {
-        "author_name": "Andrew C Stokes",
-        "author_inst": "Boston University"
+        "author_name": "Miyuru Amarapala",
+        "author_inst": "Humanigen Inc."
       },
       {
-        "author_name": "M Maria Glymour",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Rachel-Karson Theriault",
+        "author_inst": "EVERSANA"
       },
       {
-        "author_name": "Kirsten Bibbins-Domingo",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Melissa Thompson",
+        "author_inst": "EVERSANA"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "category": "health economics"
   },
   {
     "rel_doi": "10.1101/2022.02.11.22270504",
@@ -349774,43 +351405,83 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2022.02.10.22270744",
-    "rel_title": "Coronavirus Disease 2019 (COVID-19) Vaccine Boosting in Persons Already Protected by Natural or Vaccine-Induced Immunity",
+    "rel_doi": "10.1101/2022.02.11.22270667",
+    "rel_title": "Correlation between post-vaccination titres of combined IgG, IgA, and IgM anti-Spike antibodies and protection against breakthrough SARS-CoV-2 infection: a population-based longitudinal study (COVIDENCE UK)",
     "rel_date": "2022-02-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.10.22270744",
-    "rel_abs": "BackgroundThe purpose of this study was to evaluate whether boosting healthcare personnel, already reasonably protected by prior infection or vaccination, with a vaccine developed for an earlier variant of COVID-19 protects against the Omicron variant.\n\nMethodsEmployees of Cleveland Clinic who were previously infected with or vaccinated against COVID-19, and were working in Ohio the day the Omicron variant was declared a variant of concern, were included. The cumulative incidence of COVID-19 was examined over two months during an Omicron variant surge. Protection provided by boosting (analyzed as a time-dependent covariate) was evaluated using Cox proportional hazards regression. Analyses were adjusted for time since proximate overt immunologic challenge (POIC) as a time-dependent covariate.\n\nResultsAmong 39 766 employees, 8037 (20%) previously infected and the remaining previously vaccinated, COVID-19 occurred in 6230 (16%) during the study. Risk of COVID-19 increased with time since POIC. In multivariable analysis, boosting was independently associated with lower risk of COVID-19 among those with vaccine-induced immunity (HR, .43; 95% CI, .41-.46) as well as those with natural immunity (HR, .66; 95% CI, .58-.76). Among those with natural immunity, receiving 2 compared to 1 dose of vaccine was associated with higher risk of COVID-19 (HR, 1.54; 95% CI, 1.21-1.97).\n\nConclusionsAdministering a COVID-19 vaccine not designed for the Omicron variant, 6 months or more after prior infection or vaccination, protects against Omicron variant infection in both previously infected and previously vaccinated individuals. There is no evidence of an advantage to administering more than 1 dose of vaccine to previously infected persons.\n\nSummaryAmong 39 766 Cleveland Clinic employees already protected by prior infection or vaccination, vaccine boosting after 6 months was associated with significantly lower risk of COVID-19. After COVID-19 infection, there was no advantage to more than one dose of vaccine.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.11.22270667",
+    "rel_abs": "In this population-based cohort of 7530 adults, combined IgG/A/M anti-Spike titres measured after SARS-CoV-2 vaccination were predictive of protection against breakthrough SARS-CoV-2 infection. Discrimination was significantly improved by adjustment for factors influencing risk of SARS-CoV-2 exposure including household overcrowding, public transport use, and visits to indoor public places.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Nabin K Shrestha",
-        "author_inst": "Cleveland Clinic"
+        "author_name": "Giulia Vivaldi",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
       },
       {
-        "author_name": "Priyanka Shrestha",
-        "author_inst": "Stanford University"
+        "author_name": "David A Jolliffe",
+        "author_inst": "Blizard Institute and the Wolfson Institute of Population Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London"
       },
       {
-        "author_name": "Patrick C Burke",
-        "author_inst": "Cleveland Clinic"
+        "author_name": "Sian Faustini",
+        "author_inst": "Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK"
       },
       {
-        "author_name": "Amy S Nowacki",
-        "author_inst": "Cleveland Clinic"
+        "author_name": "Hayley Holt",
+        "author_inst": "Blizard Institute and the Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London"
       },
       {
-        "author_name": "Paul Terpeluk",
-        "author_inst": "Cleveland Clinic"
+        "author_name": "Natalia Perdek",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
       },
       {
-        "author_name": "Steven M Gordon",
-        "author_inst": "Cleveland Clinic"
+        "author_name": "Mohammad Talaei",
+        "author_inst": "Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Florence Tydeman",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Emma S Chambers",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Weigang Cai",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Wenhao Li",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Joseph M Gibbons",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Corinna Pade",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "\u00c1ine McKnight",
+        "author_inst": "Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Seif O Shaheen",
+        "author_inst": "Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK"
+      },
+      {
+        "author_name": "Alex G Richter",
+        "author_inst": "Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK"
+      },
+      {
+        "author_name": "Adrian R Martineau",
+        "author_inst": "Blizard Institute and the Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.02.11.22270876",
@@ -351547,63 +353218,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.02.09.22270747",
-    "rel_title": "Immune responses after twofold SARS-CoV-2 immunisation in elderly residents and Health Care Workers in nursing homes and homes with assisted living support - Proposal for a correlate of protection",
+    "rel_doi": "10.1101/2022.02.10.22270783",
+    "rel_title": "Implementation and economic effects of local non-pharmaceutical interventions",
     "rel_date": "2022-02-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.09.22270747",
-    "rel_abs": "In the present study, we were interested in the decline over time of anti SARS-CoV-2 antibodies and SARS-CoV-2 specific T-cell responses after two doses of mRNA vaccines in total and by age group and comorbidity. The second goal was to suggest an immunological correlate for protection on an individual basis and to describe the probability of protection over time after second vaccination.\n\nWe analysed blood samples from 228 residents (median age 83.8 years) and from 273 Health Care Workers (HCW; median age 49.7 years) of five nursing homes and one home for the elderly with assisted living support. Participants had received two vaccinations. The blood samples were analysed for SARS-CoV-2 specific antibody and T-cell responses. We compared outcomes in the HCW and residents in the respective institutions. No breakthrough infections occurred during the study period. The initial immune responses in the younger participants were about 30 % higher than in the older ones. Over time, all parameters dropped continuously in all groups within the maximum observation period of 232 days. Comorbidities such as coronary heart disease or diabetes mellitus reduced the initial immune responses, regardless of age. In contrast to an almost linear decline in antibody levels, we observed that the interferon-gamma response remained at a constant level between about day 120 and 180, only to decline further thereafter.\n\nBased on our data, we propose on an individual level a correlate of protection: Persons who have a neutralizing capacity of 75 % (which would correspond to approx. 200 BAU/ml) and an interferon-gamma response above 200 mIU/ml should be considered to be protected resp. sufficiently immunized.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.10.22270783",
+    "rel_abs": "In this paper, we analyze economic costs and consequences of local non-pharmaceutical interventions (NPIs) aimed at containing the COVID-19 pandemic. Using comprehensive data on municipal and regional policies in Norway, we implement a difference-in-differences framework identifying impacts of local NPIs from discontinuous differential shifts in outcomes following the implementation of new policies. In treated municipalities, local NPIs lead to persistent reductions in mobility, persistent increases in unemployment, and transient reductions in consumer spending. Analyses of spatial spillovers show that the implementation of local NPIs increases retail mobility in non-treated neighboring municipalities. Overall, our findings suggest that local NPIs have economic consequences for local economies and induce residents to shift their consumption of goods and services to neighboring municipalities.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Julia Schiffner",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
-      },
-      {
-        "author_name": "Nora Eisemann",
-        "author_inst": "Institute of Social Medicine and Epidemiology, University of Luebeck, Germany"
-      },
-      {
-        "author_name": "Hannah Baltus",
-        "author_inst": "Institute of Social Medicine and Epidemiology, University of Luebeck, Germany"
-      },
-      {
-        "author_name": "Sina Jensen",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
-      },
-      {
-        "author_name": "Katharina Wunderlich",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
-      },
-      {
-        "author_name": "Stefan Schuesseler",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
-      },
-      {
-        "author_name": "Charlotte Eicker",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
-      },
-      {
-        "author_name": "Bianca Teegen",
-        "author_inst": "Klinisch-Immunologisches Labor Stoecker, Luebeck, Germany"
-      },
-      {
-        "author_name": "Doreen Boniakowsky",
-        "author_inst": "Vorwerker Diakonie gemeinnuetzige GmbH, Luebeck, Germany"
-      },
-      {
-        "author_name": "Werner Solbach",
-        "author_inst": "Center for Infection and Inflammation Research, University of Luebeck, Luebeck, Germany, German Center for Infection Research (DZIF), Luebeck, Germany"
+        "author_name": "Anna Aasen Godoy",
+        "author_inst": "The Norwegian Institute of Public Health"
       },
       {
-        "author_name": "Alexander Mischnik",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
+        "author_name": "Maja Weemes Grotting",
+        "author_inst": "The Norwegian Institute of Public Health"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "health economics"
   },
   {
     "rel_doi": "10.1101/2022.02.09.22269744",
@@ -353449,73 +355084,61 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.02.07.479477",
-    "rel_title": "The mechanisms of catalysis and ligand binding for the SARS-CoV-2 NSP3 macrodomain from neutron and X-ray diffraction at room temperature",
+    "rel_doi": "10.1101/2022.02.07.479471",
+    "rel_title": "The mechanism of RNA capping by SARS-CoV-2",
     "rel_date": "2022-02-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.07.479477",
-    "rel_abs": "The NSP3 macrodomain of SARS CoV 2 (Mac1) removes ADP-ribosylation post-translational modifications, playing a key role in the immune evasion capabilities of the virus responsible for the COVID-19 pandemic. Here, we determined neutron and X-ray crystal structures of the SARS-CoV-2 NSP3 macrodomain using multiple crystal forms, temperatures, and pHs, across the apo and ADP-ribose-bound states. We characterize extensive solvation in the Mac1 active site, and visualize how water networks reorganize upon binding of ADP-ribose and non-native ligands, inspiring strategies for displacing waters to increase potency of Mac1 inhibitors. Determining the precise orientations of active site water molecules and the protonation states of key catalytic site residues by neutron crystallography suggests a catalytic mechanism for coronavirus macrodomains distinct from the substrate-assisted mechanism proposed for human MacroD2. These data provoke a re-evaluation of macrodomain catalytic mechanisms and will guide the optimization of Mac1 inhibitors.",
-    "rel_num_authors": 15,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.07.479471",
+    "rel_abs": "The SARS-CoV-2 RNA genome contains a 5-cap that facilitates translation of viral proteins, protection from exonucleases and evasion of the host immune response1-4. How this cap is made is not completely understood. Here, we reconstitute the SARS-CoV-2 7MeGpppA2-O-Me-RNA cap using virally encoded non-structural proteins (nsps). We show that the kinase-like NiRAN domain5 of nsp12 transfers RNA to the amino terminus of nsp9, forming a covalent RNA-protein intermediate (a process termed RNAylation). Subsequently, the NiRAN domain transfers RNA to GDP, forming the cap core structure GpppA-RNA. The nsp146 and nsp167 methyltransferases then add methyl groups to form functional cap structures. Structural analyses of the replication-transcription complex bound to nsp9 identified key interactions that mediate the capping reaction. Furthermore, we demonstrate in a reverse genetics system8 that the N-terminus of nsp9 and the kinase-like active site residues in the NiRAN domain are required for successful SARS-CoV-2 replication. Collectively, our results reveal an unconventional mechanism by which SARS-CoV-2 caps its RNA genome, thus exposing a new target in the development of antivirals to treat COVID-19.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Galen J Correy",
-        "author_inst": "Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Daniel W Kneller",
-        "author_inst": "Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA"
-      },
-      {
-        "author_name": "Gwyndalyn Phillips",
-        "author_inst": "Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA"
-      },
-      {
-        "author_name": "Swati Pant",
-        "author_inst": "Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA"
+        "author_name": "Gina J Park",
+        "author_inst": "UT Southwestern"
       },
       {
-        "author_name": "Silvia Russi",
-        "author_inst": "Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA"
+        "author_name": "Adam Osinski",
+        "author_inst": "UT Southwestern Medical Center"
       },
       {
-        "author_name": "Aina E Cohen",
-        "author_inst": "Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA"
+        "author_name": "Genaro Hernandez",
+        "author_inst": "UT Southwestern"
       },
       {
-        "author_name": "George Meigs",
-        "author_inst": "Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA"
+        "author_name": "Jennifer Eitson",
+        "author_inst": "UT Southwestern"
       },
       {
-        "author_name": "James M Holton",
-        "author_inst": "Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA"
+        "author_name": "Abir Majumdar",
+        "author_inst": "UT Southwestern"
       },
       {
-        "author_name": "Stefan Gahbauer",
-        "author_inst": "Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA"
+        "author_name": "Marco Tonelli",
+        "author_inst": "UW-Madison"
       },
       {
-        "author_name": "Michael C Thompson",
-        "author_inst": "Department of Chemistry and Chemical Biology, University of California Merced, CA 95343, USA"
+        "author_name": "Katherine Henzler-Wildman",
+        "author_inst": "University of Wisconsin - Madison"
       },
       {
-        "author_name": "Alan Ashworth",
-        "author_inst": "Helen Diller Family Comprehensive Cancer, University of California San Francisco, CA 94158, USA"
+        "author_name": "Krzysztof Pawlowski",
+        "author_inst": "UT Southwestern"
       },
       {
-        "author_name": "Leighton Coates",
-        "author_inst": "Second Target Station, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA"
+        "author_name": "Zhe Chen",
+        "author_inst": "UT Southwestern"
       },
       {
-        "author_name": "Andrey Kovalevsky",
-        "author_inst": "Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA"
+        "author_name": "Yang Li",
+        "author_inst": "University of Texas Southwestern Medical Center at Dallas"
       },
       {
-        "author_name": "Flora Meilleur",
-        "author_inst": "Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA"
+        "author_name": "John Schoggins",
+        "author_inst": "University of Texas Southwestern Medical Center"
       },
       {
-        "author_name": "James S Fraser",
-        "author_inst": "Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA"
+        "author_name": "Vincent S. Tagliabracci",
+        "author_inst": "HHMI/UT Southwestern Medical Center"
       }
     ],
     "version": "1",
@@ -355539,29 +357162,41 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2022.02.07.22270555",
-    "rel_title": "Clinical outcomes in hospitalized vaccine-breakthrough COVID-19 cases compared with contemporary unvaccinated hospitalized adults",
+    "rel_doi": "10.1101/2022.02.07.22270613",
+    "rel_title": "Time to reinfection and vaccine breakthrough SARS-CoV-2 infections: a retrospective cohort study",
     "rel_date": "2022-02-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270555",
-    "rel_abs": "SummaryThe inactivated SARS-CoV-2 vaccine (CoronaVac(R)) has been the principal vaccine used in Chiles pre-booster immunization campaign. We compared major outcomes in 260 hospitalized vaccinated vs 507 unvaccinated adults with COVID-19 (mid-2021). The vaccinated group was much older, required less critical care, had lower hospital mortality (adjusted by age), and had shorter hospitalization than the unvaccinated. Benefits were most pronounced in those older than 59 years\n\nObjectiveTo compare major outcomes in fully vaccinated and unvaccinated adult persons hospitalized for COVID-19 in a general private hospital in Santiago, Chile during mid2021.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270613",
+    "rel_abs": "BackgroundIt is important to understand how BNT162b2, mRNA-1273, and JNJ-78436735 COVID-19 vaccines, as well as prior infection, protect against breakthrough cases and reinfections. Real world evidence on acquired immunity from vaccines, and from SARS-CoV-2 infection, can help public health decision-makers understand disease dynamics and viral escape to inform resource allocation for curbing the spread of pandemic.\n\nMethodsThis retrospective cohort study presents demographic information, survival functions, and probability distributions for 2,627,914 patients who received recommended doses of COVID-19 vaccines, and 63,691 patients who had a prior COVID-19 infection. In addition, patients receiving different vaccines were matched by age, sex, ethnic group, state of residency, and the quarter of the year in 2021 the COVID-19 vaccine was completed, to support survival analysis on pairwise matched cohorts.\n\nFindingsEach of the three vaccines and infection-induced immunity all showed a high probability of survival against breakthrough or reinfection cases (mRNA-1273: 0.997, BNT162b2: 0.997, JNJ-78436735: 0.992, previous infection: 0.965 at 180 days). The incidence rate of reinfection among those unvaccinated and previously infected was higher than that of breakthrough among the vaccinated population (reinfection: 0.9%; breakthrough:0.4%). In addition, 280 vaccinated patients died (0.01% all-cause mortality) within 21 days of the last vaccine dose, and 5898 (3.1 %) died within 21 days of a positive COVID-19 test.\n\nConclusionsDespite a gradual decline in vaccine-induced and infection-induced immunity, both acquired immunities were highly effective in preventing breakthrough and reinfection. In addition, for unvaccinated patients with COVID-19, those who did not die within 90 days of their initial infection (9565 deaths, 5.0% all-cause mortality rate), had a comparable asymptotic pattern of breakthrough infection as those who acquired immunity from a vaccine. Overall, the risks associated with COVID-19 infection are far greater than the marginal advantages of immunity acquired by prior infection.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Marcelo J Wolff Sr.",
-        "author_inst": "Clinica Santa Maria; U. of Chile School of Medicine;"
+        "author_name": "Sevda Molani",
+        "author_inst": "Institute For Systems Biology"
+      },
+      {
+        "author_name": "Andrew M Baumgartner",
+        "author_inst": "Institute for Systems Biology"
+      },
+      {
+        "author_name": "Yeon Mi Hwang",
+        "author_inst": "Institute for Systems Biology"
       },
       {
-        "author_name": "Margarita Gilabert",
-        "author_inst": "Clinica Santa Maria, Santiago, Chile"
+        "author_name": "Venkata R Duvvuri",
+        "author_inst": "Institute for Systems Biology"
       },
       {
-        "author_name": "Rodrigo Hernandez",
-        "author_inst": "Clinica Santa maria, Santiago, Chile"
+        "author_name": "Jason Goldman",
+        "author_inst": "Swedish Medical Center"
+      },
+      {
+        "author_name": "Jennifer J Hadlock",
+        "author_inst": "Institute for System Biology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -357529,65 +359164,161 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.02.06.479332",
-    "rel_title": "A potent SARS-CoV-2 neutralizing antibody recognizing a conserved epitope with broad mutant variant and SARS-CoV activity.",
+    "rel_doi": "10.1101/2022.02.06.479285",
+    "rel_title": "Vaccine Protection Against the SARS-CoV-2 Omicron Variant in Macaques",
     "rel_date": "2022-02-07",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.06.479332",
-    "rel_abs": "COVID-19 is the deadliest respiratory virus pandemic since 1918 and the latest of several coronavirus epidemics and pandemics in recent years. Despite the unprecedented response by both the government and private sectors to develop vaccines and therapies, the evolution of SARS-CoV-2 variants resistant to these interventions reveals a crucial need for therapeutics that maintain their efficacy against current and future mutant variants. Here we describe a SARS-CoV-2 neutralizing antibody, ABP-310, with potent activity against all variants tested including the Omicron variant. ABP-310 also displays potent neutralizing activity against SARS-CoV, highlighting the conserved nature of the ABP-310 epitope. By targeting a conserved epitope, we believe that ABP-310 has therapeutic promise not only against the current SARS-CoV-2 variants but would be expected to maintain efficacy against future variants and possibly even novel coronaviruses.",
-    "rel_num_authors": 12,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.06.479285",
+    "rel_abs": "BackgroundThe rapid spread of the SARS-CoV-2 Omicron (B.1.1.529) variant, including in highly vaccinated populations, has raised important questions about the efficacy of current vaccines. Immune correlates of vaccine protection against Omicron are not known.\n\nMethods30 cynomolgus macaques were immunized with homologous and heterologous prime-boost regimens with the mRNA-based BNT162b2 vaccine and the adenovirus vector-based Ad26.COV2.S vaccine. Following vaccination, animals were challenged with the SARS-CoV-2 Omicron variant by the intranasal and intratracheal routes.\n\nResultsOmicron neutralizing antibodies were observed following the boost immunization and were higher in animals that received BNT162b2, whereas Omicron CD8+ T cell responses were higher in animals that received Ad26.COV2.S. Following Omicron challenge, sham controls showed more prolonged virus in nasal swabs than in bronchoalveolar lavage. Vaccinated macaques demonstrated rapid control of virus in bronchoalveolar lavage, and most vaccinated animals also controlled virus in nasal swabs, showing that current vaccines provide substantial protection against Omicron in this model. However, vaccinated animals that had moderate levels of Omicron neutralizing antibodies but negligible Omicron CD8+ T cell responses failed to control virus in the upper respiratory tract. Virologic control correlated with both antibody and T cell responses.\n\nConclusionsBNT162b2 and Ad26.COV2.S provided robust protection against high-dose challenge with the SARS-CoV-2 Omicron variant in macaques. Protection against this highly mutated SARS-CoV-2 variant correlated with both humoral and cellular immune responses.",
+    "rel_num_authors": 36,
     "rel_authors": [
       {
-        "author_name": "Adam J Pelzek",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Abishek Chandrashekar",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Jingyou Yu",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Katherine McMahan",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Catherine Jacob-Dolan",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Jinyan Liu",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Xuan He",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "David Hope",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Tochi Anioke",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Julia Barrett",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Benjamin Chung",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Nicole Hachmann",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Michelle Lifton",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Jessica Miller",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Olivia Powers",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Michaela Sciacca",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Daniel Sellers",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Mazuba Siamatu",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Nehalee Surve",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Haley VanWyk",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Huahua Wan",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Cindy Wu",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Laurent Pessaint",
+        "author_inst": "Bioqual Inc"
+      },
+      {
+        "author_name": "Daniel Valentin",
+        "author_inst": "Bioqual"
+      },
+      {
+        "author_name": "Alex Van Ry",
+        "author_inst": "Bioqual"
+      },
+      {
+        "author_name": "Jeanne Muench",
+        "author_inst": "Bioqual"
       },
       {
-        "author_name": "Sanam Ebtehaj",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Mona Boursiquot",
+        "author_inst": "Bioqual"
       },
       {
-        "author_name": "James Lulo",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Anthony Cook",
+        "author_inst": "Bioqual"
       },
       {
-        "author_name": "Lucy Zhang",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Jason Velasco",
+        "author_inst": "Bioqual"
       },
       {
-        "author_name": "Olivia Balduf",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Elyse Teow",
+        "author_inst": "Bioqual"
       },
       {
-        "author_name": "Lindsay Dolan",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Adrianus Boon",
+        "author_inst": "Washington University in St Louis"
       },
       {
-        "author_name": "Chaohua Zhang",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Mehul Suthar",
+        "author_inst": "Emory University"
       },
       {
-        "author_name": "Shengqin Wan",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Neharika Jain",
+        "author_inst": "Tufts"
       },
       {
-        "author_name": "Gang An",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Amanda J. Martinot",
+        "author_inst": "Tufts University Cummings School of Veterinary Medicine"
       },
       {
-        "author_name": "Awo Kankam",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Mark  G. Lewis",
+        "author_inst": "Bioqual Inc"
       },
       {
-        "author_name": "Eugene Chan",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Hanne Andersen",
+        "author_inst": "Bioqual Inc"
       },
       {
-        "author_name": "Shaun P Murphy",
-        "author_inst": "Abpro Corporation"
+        "author_name": "Dan H. Barouch",
+        "author_inst": "Beth Israel Deaconess Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "new results",
     "category": "microbiology"
   },
@@ -360011,87 +361742,39 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.02.04.22270433",
-    "rel_title": "The usefulness of D-dimer as a predictive marker for mortality in patients with COVID-19 hospitalized during the first wave in Italy.",
+    "rel_doi": "10.1101/2022.02.05.22270499",
+    "rel_title": "Comparative study of immunogenicity and safety of Gam-COVID-Vac and Sinopharm BBIBP-CorV vaccines in Belarus",
     "rel_date": "2022-02-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.04.22270433",
-    "rel_abs": "BackgroundThe coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources.\n\nAimsThe primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality.\n\nMethodsThis was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrells C-index and model calibration was assessed using a calibration plot.\n\nResultsOut of 1049 patients, 501 patients had evaluable data. Of these 501 patients, 96 died. The cumulative incidence of in-hospital mortality within 30 days was 20% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot.\n\nConclusionThe predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.05.22270499",
+    "rel_abs": "IntroductionLack of comparative studies on efficiency of a broad range of COVID19 vaccines leads to lower levels of adoption and subsequent lower total immunity in several regions, including Republic of Belarus. This clinical study captures and transparently demonstrates varying immunogenic responses to Sputnik V and Sinopharm vaccines.\n\nAim of this study wasto compare the immunogenicity and reactogenicity of Sputnik V (Gam-COVID-Vac), RF and Sinopharm (BBIBP-CorV), PRC vaccines in vaccinated individuals.\n\nMaterials and MethodsA total of 60 adults participated the study. The immune response after vaccination was assessed using enzyme immunoassay. IgG levels measured in all participants at three time points: before the vaccination, 42 days after the first vaccine dose, and 6 months after the first vaccine dose. The results of the SARS-CoV-2 antibody test is quantified according to the WHO First International Standard (NIBSC code:20/136) and expressed in international units (BAU/ml).\n\nResultsThe study participants were divided into two groups, where 30 people (50%) were vaccinated with Sputnik V (Gam-COVID-Vac), and 30 people were vaccinated with Sinopharm (BBIBP-CorV), with no gender differences in the groups. The IgG levels at 42 days after the first vaccine dose were: Sputnik V (Gam-COVID-Vac)(42 days): Me=650.4 (642.2-669.4); Sinopharm (BBIBP-CorV)(42 days): Me=376.5 (290.9-526.4); p<0,001). The IgG levels at 6 months after the first vaccine dose were: Sputnik V (Gam-COVID-Vac)(6 months) Me=608.7 (574.6-647.1); Sinopharm (BBIBP-CorV)(6 months): Me=106.3 (78.21-332.4); p<0,001). Reactions after vaccination appeared in 27 vaccinated individuals (45%).\n\nConclusionThe study showed that Sputnik V (Gam-COVID-Vac) vaccine was more immunogenic than Sinopharm (BBIBP-CorV) vaccine. IgG levels in vaccinated individuals who previously recovered from SARS-CoV-2 infection (\"hybrid immunity\") were higher than in SARS-CoV-2 naive individuals. Reactions after vaccines administration were mild to moderate.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Shermarke Hassan",
-        "author_inst": "University of Milan"
-      },
-      {
-        "author_name": "Barbara Ferrari",
-        "author_inst": "Policlinico di Milano: Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico"
-      },
-      {
-        "author_name": "Raffaella Rossio",
-        "author_inst": "Policlinico di Milano: Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico"
-      },
-      {
-        "author_name": "Vincenzo la Mura",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
-      },
-      {
-        "author_name": "Andrea Artoni",
-        "author_inst": "Policlinico di Milano: Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico"
-      },
-      {
-        "author_name": "Roberta Gualtierotti",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
-      },
-      {
-        "author_name": "Ida Martinelli",
-        "author_inst": "Policlinico di Milano: Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico"
-      },
-      {
-        "author_name": "Alessandro Nobili",
-        "author_inst": "Mario Negri Institute for Pharmacological Research Branch of Milan: Istituto di Ricerche Farmacologiche Mario Negri"
-      },
-      {
-        "author_name": "Alessandra Bandera",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
-      },
-      {
-        "author_name": "Andrea Gori",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
-      },
-      {
-        "author_name": "Francesco Blasi",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
-      },
-      {
-        "author_name": "Valter Monzani",
-        "author_inst": "Policlinico di Milano: Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico"
-      },
-      {
-        "author_name": "Giorgio Costantino",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
+        "author_name": "Igor Stoma",
+        "author_inst": "Gomel state medical university"
       },
       {
-        "author_name": "Sergio Harari",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
+        "author_name": "Katsiaryna Korsak",
+        "author_inst": "Gomel state medical university"
       },
       {
-        "author_name": "Frits  Richard Rosendaal",
-        "author_inst": "Leiden Universitair Medisch Centrum: Leids Universitair Medisch Centrum"
+        "author_name": "Evgenii Voropaev",
+        "author_inst": "Gomel state medical university"
       },
       {
-        "author_name": "Flora Peyvandi",
-        "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano"
+        "author_name": "Olga Osipkina",
+        "author_inst": "Gomel state medical university"
       },
       {
-        "author_name": "the COVID-19 Network working group",
-        "author_inst": ""
+        "author_name": "Aleksey Kovalev",
+        "author_inst": "Gomel state medical university"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.02.04.22270143",
@@ -362145,51 +363828,59 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2022.02.03.22270401",
-    "rel_title": "RISK STRATIFICATION OF PATIENTS WITH COVID-19 DISEASE THROUGH THE USE OF CLINICAL SCORES IN AN EMERGENCY DEPARTMENT. A review of the literature",
+    "rel_doi": "10.1101/2022.02.03.22270417",
+    "rel_title": "Fatality assessment and variant risk monitoring for COVID-19 using three new hospital occupancy related metrics",
     "rel_date": "2022-02-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.03.22270401",
-    "rel_abs": "DISCLAIMER STATEMENTThe authors have withdrawn the manuscript because there are some errors in the Area Under the Curve values regarding to intensive care unit admission and mortality for some scores analyzed. The article must be revised in its conclusions in order to affirm that NEWS and NEWS2 are the best clinical scores to be used in Emergency to evaluate patients with Covid-19 disease.\n\nTherefore, the authors do not wish this work to be cited as reference for one project. If you have any questions, please contact the corresponding author.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.03.22270417",
+    "rel_abs": "BackgroundThough case fatality rate (CFR) is widely used to reflect COVID-19 fatality risk, its use is limited by large temporal and spatial variation. Hospital mortality rate (HMR) is also used to assess the severity of COVID-19, but HMR data is not directly available except 35 states of USA. Alternative metrics are needed for COVID-19 severity and fatality assessment.\n\nMethodsNew metrics and their applications in fatality measurements and risk monitoring are proposed here. We also introduce a new mathematical model to estimate average hospital length of stay for death (Ldead) and discharges (Ldis). Multiple data sources were used for our analysis.\n\nFindingsWe propose three new metrics, hospital occupancy mortality rate (HOMR), ratio of total deaths to hospital occupancy (TDHOR) and ratio of hospital occupancy to cases (HOCR), for dynamic assessment of COVID-19 fatality risk. Estimated Ldead and Ldis for 501,079 COVID-19 hospitalizations in US 34 states between Aug 7, 2020 and Mar 1, 2021 were 14.0 and 18.2 days, respectively. We found that TDHOR values of 27 countries are less spatially and temporally variable and more capable of detecting changes in COVID-19 fatality risk. The dramatic changes in COVID-19 CFR observed in 27 countries during early stages of the pandemic were mostly caused by undiagnosed cases. Compared to the first week of November, 2021, the week mean HOCRs (mimics hospitalization-to-case ratio) for Omicron variant decreased 34.08% and 65.16% in the United Kingdom and USA respectively as of Jan 16, 2022.\n\nInterpretationThese new and reliable measurements for COVID-19 that could be expanded as a general index to other fatal infectious diseases for disease fatality risk and variant-associated risk monitoring.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, medRxiv, and bioRxiv for peer-reviewed articles, preprints, and research reports on risk and health care evaluation for COVID-19 using the search terms \"hospital occupancy mortality rate\", \"ratio of total deaths to hospital occupancy\", \"ratio of hospital occupancy to case\" up to Jan 20, 2022. No similar concepts or studies were found. No similar mathematical models based on \"hospital occupancy mortality rate\" for the estimation of hospital length of stay for deaths and discharges have been identified to date.\n\nAdded value of the studyOur new metrics, HOMR and TDHOR, mimic HMR for COVID-19 fatality risk assessment but utilize readily available data for many US states and countries around the world. HOCR mimics hospitalization-to-case ratio for COVID-19. We also provide evidence that explains why COVID-19 CFR has such dramatic changes at the beginning of a COVID-19 outbreak. We have additionally provided new metrics for COVID-19 fatality risk dynamic monitoring including Omicron variant and showed that these metrics provided additional information.\n\nImplications of all the available evidenceThe results of this study, including average hospital length of stay for deaths and discharges for over 500,000 COVID-19 hospitalizations in the US, can aid county, state, and national leaders in making informed public health decisions related to the ongoing COVID-19 pandemic. This is the first study to provide quantitative evidence to address why CFR has a such a large variation at the beginning of the COVID-19 pandemic in most countries and will hopefully encourage more countries to release hospital occupancy data, which we show is both useful and easy information to collect. The new metrics introduced by our study are effective indicators for monitoring COVID-19 fatality risk, as well as potentially fatal COVID-19 variants, and could also be expanded to other fatal infectious diseases.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Simone Zanella",
-        "author_inst": "APSS Trento"
+        "author_name": "Ping-Wu Zhang",
+        "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine; Baltimore, MD, 21231, USA"
       },
       {
-        "author_name": "Francesco Zanella",
-        "author_inst": "APSS Trento"
+        "author_name": "Steven H Zhang",
+        "author_inst": "Department of Computer Science, University of Maryland at College park, undergraduate student (present affiliation)"
       },
       {
-        "author_name": "Alena Mancosu",
-        "author_inst": "University of Verona"
+        "author_name": "Wei-Feng Li",
+        "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine; Baltimore, MD, 21231, USA"
       },
       {
-        "author_name": "Anna Brugnolli",
-        "author_inst": "Nursing School of Trento, University of Verona"
+        "author_name": "Casey J Keuthan",
+        "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine; Baltimore, MD, 21231, USA"
       },
       {
-        "author_name": "Alessandro Carrara",
-        "author_inst": "APSS Trento"
+        "author_name": "Shuaizhang Li",
+        "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine; Baltimore, MD, 21231, USA"
       },
       {
-        "author_name": "Anita Bevilacqua",
-        "author_inst": "Nursing School of Trento, University of Verona"
+        "author_name": "Felipe Takaesu",
+        "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine; Baltimore, MD, 21231, USA"
       },
       {
-        "author_name": "Elisa Marinelli",
-        "author_inst": "Nursing School of Trento, University of Verona"
+        "author_name": "Cynthia A Berlinicke",
+        "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine; Baltimore, MD, 21231, USA"
       },
       {
-        "author_name": "Nicola Ricci",
-        "author_inst": "APSS Trento"
+        "author_name": "Jun Wan",
+        "author_inst": "Department of Medical and Molecular Genetics, Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 4620"
+      },
+      {
+        "author_name": "Jing Sun",
+        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, MD, 21113, USA"
+      },
+      {
+        "author_name": "Donald J Zack",
+        "author_inst": "Wilmer Eye Institute, Johns Hopkins University School of Medicine; Baltimore, MD, 21231, USA"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "emergency medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.02.02.22270353",
@@ -363879,197 +365570,21 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2022.02.03.22270391",
-    "rel_title": "Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a prospective, multicentre study",
+    "rel_doi": "10.1101/2022.02.03.22270396",
+    "rel_title": "COVID-19 Vaccination is Associated with Decreasing Cases, Hospitalizations, and Deaths Across Age Groups and Variants over 9 months in Switzerland",
     "rel_date": "2022-02-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.03.22270391",
-    "rel_abs": "ObjectivesTo describe physical behaviours following hospital admission for COVID-19 including associations with acute illness severity and ongoing symptoms.\n\nMethods1077 patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and type 2 diabetes were comparators.\n\nResultsValid accelerometer data from 253 women and 462 men were included. Women engaged in a mean{+/-}SD of 14.9{+/-}14.7 minutes/day of moderate-to-vigorous physical activity (MVPA), with 725.6{+/-}104.9 minutes/day spent inactive and 7.22{+/-}1.08 hours/day asleep. The values for men were 21.0{+/-}22.3 and 755.5{+/-}102.8 minutes/day and 6.94{+/-}1.14 hours/day, respectively. Over 60% of women and men did not have any days containing a 30-minute bout of MVPA. Variability in sleep timing was approximately 2 hours in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer sleep duration, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes.\n\nConclusionsPhysical activity and regulating sleep patterns are potential treatable traits for COVID-19 recovery programmes.",
-    "rel_num_authors": 45,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.03.22270396",
+    "rel_abs": "Recent studies assessing COVID-19 vaccine efficacy at the population level found counterintuitive results, such as positive associations between vaccination and infections or deaths. These ecological studies have limitations, including too short observation periods, focusing on infections, and not controlling for age groups and dominant variants. The current study addresses these limitations by investigating the relations between vaccination and COVID-19 cases, hospitalizations, and deaths over a longer period (9[1/2] months) while also considering age groups (from 10 to 80+ years old) and variants (Alpha and Delta), utilizing data from Switzerland. Results suggest that vaccination is negatively related to cases overall and in all cantons of Switzerland, and that vaccination is negatively related to hospitalizations and deaths from 50 years old. Furthermore, vaccination is a significant predictor of cases, hospitalizations, and deaths while holding the effects of age and dominant variant constant.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Tatiana Plekhanova",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Alex V Rowlands",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Rachael A Evans",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Charlotte L Edwardson",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Nicolette C Bishop",
-        "author_inst": "School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK"
-      },
-      {
-        "author_name": "Charlotte E Bolton",
-        "author_inst": "University of Nottingham, Nottingham, UK"
-      },
-      {
-        "author_name": "James D Chalmers",
-        "author_inst": "University of Dundee, Ninewells Hospital and Medical School, Dundee, UK"
-      },
-      {
-        "author_name": "Melanie J Davies",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Enya Daynes",
-        "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Annemarie B Docherty",
-        "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK"
-      },
-      {
-        "author_name": "Omer Elneima",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Neil J Greening",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Sharlene A Greenwood",
-        "author_inst": "King's College Hospital, Department of Physiotherapy and Renal Medicine, London, UK"
-      },
-      {
-        "author_name": "Andrew P Hall",
-        "author_inst": "University Hospitals of Leicester NHS Trust, Leicester, UK"
-      },
-      {
-        "author_name": "Victoria C Harris",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Ewen M Harrison",
-        "author_inst": "Centre for Medical Informatics, The Usher Institute, University of Edinburgh, Edinburgh, UK"
-      },
-      {
-        "author_name": "Joseph Henson",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Ling-Pei Ho",
-        "author_inst": "MRC Human Immunology Unit, University of Oxford, Oxford, UK"
-      },
-      {
-        "author_name": "Alex Horsley",
-        "author_inst": "Division of Infection, Immunity & Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK"
-      },
-      {
-        "author_name": "Linzy Houchen-Wolloff",
-        "author_inst": "Centre for Exercise and Rehabilitation Science, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Kamlesh Khunti",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Olivia C Leavy",
-        "author_inst": "Department of Health Sciences, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Nazir I Lone",
-        "author_inst": "Usher Institute, University of Edinburgh, Edinburgh, UK"
-      },
-      {
-        "author_name": "Michael Marks",
-        "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK"
-      },
-      {
-        "author_name": "Ben Maylor",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Hamish J C McAuley",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Claire M Nolan",
-        "author_inst": "Harefield Respiratory Research Group, Royal Brompton and Harefield Clinical Group, Guys and St. Thomas NHS Foundation Trust, London, UK"
-      },
-      {
-        "author_name": "Krisnah Poinasamy",
-        "author_inst": "Asthma UK and British Lung Foundation, London, UK"
-      },
-      {
-        "author_name": "Jennifer K Quint",
-        "author_inst": "NHLI, Imperial College London, London, UK"
-      },
-      {
-        "author_name": "Betty Raman",
-        "author_inst": "Radcliffe Department of Medicine, University of Oxford, Oxford, UK"
-      },
-      {
-        "author_name": "Matthew Richardson",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Jack A Sargeant",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Ruth M Saunders",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Marco Sereno",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Aarti Shikotra",
-        "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Amisha Singapuri",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Michael Steiner",
-        "author_inst": "Department of Respiratory Sciences, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "David J Stensel",
-        "author_inst": "NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Louise V Wain",
-        "author_inst": "Department of Health Sciences, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Julie Whitney",
-        "author_inst": "School of Life Course & Population Sciences, Kings College London, London, UK"
-      },
-      {
-        "author_name": "Dan G Wootton",
-        "author_inst": "Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK"
-      },
-      {
-        "author_name": "Christopher E Brightling",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "William D-C Man",
-        "author_inst": "Royal Brompton and Harefield Clinical Group, Guys and St. Thomas NHS Foundation Trust, London, UK"
-      },
-      {
-        "author_name": "Sally J Singh",
-        "author_inst": "The Institute for Lung Health, NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK"
-      },
-      {
-        "author_name": "Tom Yates",
-        "author_inst": "Diabetes Research Centre, University of Leicester, Leicester, UK"
+        "author_name": "Jean-Luc Jucker",
+        "author_inst": "Currently none"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -365893,29 +367408,57 @@
     "category": "cell biology"
   },
   {
-    "rel_doi": "10.1101/2022.02.01.478632",
-    "rel_title": "Design and development of potent h-ACE2 derived peptide mimetics in SARS-CoV-2 Omicron variant therapeutics",
+    "rel_doi": "10.1101/2022.02.01.478697",
+    "rel_title": "Patterns of Volatility Across the Spike Protein Accurately Predict the Emergence of Mutations within SARS-CoV-2 Lineages",
     "rel_date": "2022-02-02",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.01.478632",
-    "rel_abs": "The pandemic of COVID-19 has become the global health challenge due to the emergence of new variants. The Receptor binding domain (RBD) of spike protein that makes direct interaction with ACE-2 has shown unique mutated residues in most of the variants of concern (VOC). Recently WHO declared the Omicron (B.1.1.529) as VOC considering it as a highly mutated variant which includes a total of 60 mutations out of which 15 mutations occurred in RBD region of SARS-CoV-2. Inhibition of Protein-protein (Omicron RBD-h-ACE2) interaction was already proved to inhibit the viral infection. In this study, by using molecular dynamic simulations efforts are made to explore the atomistic details of Omicron RBD-h-ACE2 interaction. Based on MD simulations, h-ACE2 motif is found to be interacting with omicron RBD domain. Interaction analysis had provided key residues interacting with Omicron-RBD that helped to extract h-ACE2 peptide. Here, rational design of the peptides that have resemblance with h-ACE2 is done and the peptide library is subjected for inhibition studies against Omicron-RBD. The current study helped to identify the significant peptides that can inhibit Omicron-RBD. Altogether the performed studies will provide an opportunity to develop potential therapeutic peptidomimetics effective against Omicron variant of SARS-CoV-2.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.01.478697",
+    "rel_abs": "Mutations in the spike glycoprotein of SARS-CoV-2 allow the virus to probe the sequence space in search of higher-fitness states. New sublineages of SARS-CoV-2 variants-of-concern (VOCs) continuously emerge with such mutations. Interestingly, the sites of mutation in these sublineages vary between the VOCs. Whether such differences reflect the random nature of mutation appearance or distinct evolutionary spaces of spike in the VOCs is unclear. Here we show that each position of spike has a lineage-specific likelihood for mutations to appear and dominate descendent sublineages. This likelihood can be accurately estimated from the lineage-specific mutational profile of spike at a protein-wide level. The mutability environment of each position, including adjacent sites on the protein structure and neighboring sites on the network of comutability, accurately forecast changes in descendent sublineages. Mapping of imminent changes within the VOCs can contribute to the design of immunogens and therapeutics that address future forms of SARS-CoV-2.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Stanly M L Paul",
-        "author_inst": "University of Szeged"
+        "author_name": "Roberth Anthony Rojas Chavez",
+        "author_inst": "The University of Iowa"
+      },
+      {
+        "author_name": "Mohammad Fili",
+        "author_inst": "Iowa State University"
       },
       {
-        "author_name": "Swathi Nadendla",
-        "author_inst": "National Institute of Pharmaceutical Education and Research (NIPER) S.A.S. Nagar"
+        "author_name": "Changze Han",
+        "author_inst": "The University of Iowa"
+      },
+      {
+        "author_name": "Syed A. Rahman",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Isaiah Guzman L Bicar",
+        "author_inst": "The University of Iowa"
+      },
+      {
+        "author_name": "Sullivan Gregory",
+        "author_inst": "The University of Iowa"
       },
       {
-        "author_name": "Elizabeth M Sobhia",
-        "author_inst": "National Institute of Pharmaceutical Education and Research (NIPER) S.A.S. Nagar"
+        "author_name": "Guiping Hu",
+        "author_inst": "Rochester Institute of Technology"
+      },
+      {
+        "author_name": "Jishnu Das",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Grant D. Brown",
+        "author_inst": "The University of Iowa"
+      },
+      {
+        "author_name": "Hillel Haim",
+        "author_inst": "The University of Iowa"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
     "category": "bioinformatics"
   },
@@ -367687,95 +369230,143 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.01.29.22270074",
-    "rel_title": "Partnering with Athletes to Assess Risk of COVID-Related Myocarditis",
+    "rel_doi": "10.1101/2022.02.01.22270170",
+    "rel_title": "Detection of prevalent SARS-CoV-2 variant lineages in wastewater and clinical sequences from cities in Quebec, Canada",
     "rel_date": "2022-02-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.29.22270074",
-    "rel_abs": "BackgroundMyocarditis in athletes is a feared complication of SARS-CoV-2, yet guidelines for screening with cardiac magnetic resonance imaging are lacking. Further, stakeholder involvement in the research is rare.\n\nHypothesisWe sought to determine the rates of cardiac magnetic resonance imaging evidence of SARS-CoV-2 related myocarditis in student athletes. We hypothesized that rates of myocarditis were lower than initially reported and that including athletes on the research team would enhance participant satisfaction and scientific integrity.\n\nMethodsAccordingly, when members of a hockey team were infected with SARS-CoV-2, we invited them and their team physicians to be part of the design of a study assessing the incidence of myocarditis. We performed cardiac magnetic resonance imaging on participating hockey players infected with SARS-CoV-2 and compared them to a healthy lacrosse cohort. Participants were given an optional survey to complete at the end of the study to assess their satisfaction with it.\n\nResultsFour hockey players and two team physicians joined the study team; eight hockey players and four lacrosse players participated in the study. Zero athletes met imaging criteria for myocarditis; delayed enhancement was observed in seven cases and three controls. Athletes supported sharing the findings with the participants. No athletes reported feeling uncomfortable participating, knowing other athletes participated on the research team.\n\nConclusionRates of SARS-CoV-2 myocarditis in young athletes appears to be lower than initially reported. Partnered research is important, especially in populations with more to lose, such as collegiate athletes; future studies should include stakeholders in the study design and execution.\n\nKey pointsCardiac MRI findings of myocarditis after COVID infection in young athletes is rare. Subjects of research studies appreciate involvement in the development of the study, and this also builds trust with the research team.",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.01.22270170",
+    "rel_abs": "Wastewater-based epidemiology has emerged as a promising tool to monitor pathogens in a population, particularly when clinical diagnostic capacities become overwhelmed. During the ongoing COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), several jurisdictions have tracked viral concentrations in wastewater to inform public health authorities. While some studies have also sequenced SARS-CoV-2 genomes from wastewater, there have been relatively few direct comparisons between viral genetic diversity in wastewater and matched clinical samples from the same region and time period. Here we report sequencing and inference of SARS-CoV-2 mutations and variant lineages (including variants of concern) in 936 wastewater samples and thousands of matched clinical sequences collected between March 2020 and July 2021 in the cities of Montreal, Quebec City, and Laval, representing almost half the population of the Canadian province of Quebec. We benchmarked our sequencing and variant-calling methods on known viral genome sequences to establish thresholds for inferring variants in wastewater with confidence. We found that variant frequency estimates in wastewater and clinical samples are correlated over time in each city, with similar dates of first detection. Across all variant lineages, wastewater detection is more concordant with targeted outbreak sequencing than with semi-random clinical swab sampling. Most variants were first observed in clinical and outbreak data due to higher sequencing rate. However, wastewater sequencing is highly efficient, detecting more variants for a given sampling effort. This shows the potential for wastewater sequencing to provide useful public health data, especially at places or times when sufficient clinical sampling is infrequent or infeasible.",
+    "rel_num_authors": 31,
     "rel_authors": [
       {
-        "author_name": "Bradley William Kay",
-        "author_inst": "Yale New Haven Hospital"
+        "author_name": "Arnaud N'Guessan",
+        "author_inst": "Universite de Montreal"
       },
       {
-        "author_name": "Attila Feher",
-        "author_inst": "Yale New Haven Hospital"
+        "author_name": "Alexandra Tsitouras",
+        "author_inst": "McGill University"
       },
       {
-        "author_name": "Samuel Reinhardt",
-        "author_inst": "Yale New Haven Hospital"
+        "author_name": "Fernando Sanchez-Quete",
+        "author_inst": "McGill University"
       },
       {
-        "author_name": "Jason Cuomo",
-        "author_inst": "Yale New Haven Hospital"
+        "author_name": "Eyerusalem Goitom",
+        "author_inst": "Polytechnique Montreal"
       },
       {
-        "author_name": "Stephanie Arlis-Mayor",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Sarah Julia Reiling",
+        "author_inst": "McGill Genome Centre"
       },
       {
-        "author_name": "Matthew Lynch",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Jose Hector Galvez",
+        "author_inst": "Canadian Centre for Computational Genomics"
       },
       {
-        "author_name": "Kyle Johnson",
-        "author_inst": "Yale University"
+        "author_name": "Thanh Luan Nguyen",
+        "author_inst": "Polytechnique Montreal"
       },
       {
-        "author_name": "Phil Kemp",
-        "author_inst": "Yale University"
+        "author_name": "Ha Thanh Loan Nguyen",
+        "author_inst": "Polytechnique Montreal"
       },
       {
-        "author_name": "Henry Wagner",
-        "author_inst": "Yale University"
+        "author_name": "Flavia Visentin",
+        "author_inst": "Polytechnique Montreal"
       },
       {
-        "author_name": "Tyler Welsh",
-        "author_inst": "Yale University"
+        "author_name": "Mounia Hachad",
+        "author_inst": "Polytechnique Montreal"
       },
       {
-        "author_name": "Jerome Lamy",
-        "author_inst": "Yale New Haven Hospital"
+        "author_name": "Kateryna Krylova",
+        "author_inst": "Polytechnique Montreal"
       },
       {
-        "author_name": "Dana Peters",
-        "author_inst": "Yale New Haven Hospital"
+        "author_name": "Sara Matthews",
+        "author_inst": "Polytechnique Montreal"
       },
       {
-        "author_name": "Hamid Mojibian",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Susanne A Kraemer",
+        "author_inst": "McGill University"
       },
       {
-        "author_name": "Lawrence Young",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Paul Stretenowich",
+        "author_inst": "Canadian Centre for Computational Genomics"
       },
       {
-        "author_name": "Rachel Lampert",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Mathieu Bourgey",
+        "author_inst": "Canadian Centre for Computational Genomics"
       },
       {
-        "author_name": "Robert McNamara",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Haig Djambazian",
+        "author_inst": "McGill Genome Centre"
       },
       {
-        "author_name": "Lauren Baldassarre",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Shu-Huang Chen",
+        "author_inst": "McGill University"
       },
       {
-        "author_name": "Edward J Miller",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Anne-Marie Roy",
+        "author_inst": "McGill University"
       },
       {
-        "author_name": "Erica S Spatz",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Brent Brookes",
+        "author_inst": "McGill University"
+      },
+      {
+        "author_name": "Sally Lee",
+        "author_inst": "McGill University"
+      },
+      {
+        "author_name": "Marie-Michelle Simon",
+        "author_inst": "McGill University"
+      },
+      {
+        "author_name": "Thomas Maere",
+        "author_inst": "Universite Laval"
+      },
+      {
+        "author_name": "Peter Vanrolleghem",
+        "author_inst": "Universite Laval"
+      },
+      {
+        "author_name": "Marc-Andre Labelle",
+        "author_inst": "Centre des technologies de l'eau"
+      },
+      {
+        "author_name": "Sandrine Moreira",
+        "author_inst": "Laboratoire de Sante Publique du Quebec, Institut National de Sante Publique"
+      },
+      {
+        "author_name": "Ines Levade",
+        "author_inst": "Laboratoire de Sante Publique du Quebec, Institut National de Sante Publique"
+      },
+      {
+        "author_name": "Guillaume Bourque",
+        "author_inst": "Canadian Centre for Computational Genomics, McGill University"
+      },
+      {
+        "author_name": "Jiannis Ragoussis",
+        "author_inst": "McGill Genome Centre"
+      },
+      {
+        "author_name": "Sarah Dorner",
+        "author_inst": "Polytechnique Montreal"
+      },
+      {
+        "author_name": "Dominic Frigon",
+        "author_inst": "McGill University"
+      },
+      {
+        "author_name": "B. Jesse Shapiro",
+        "author_inst": "McGill University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "cardiovascular medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.01.31.22270226",
@@ -369301,47 +370892,215 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2022.01.30.22269980",
-    "rel_title": "Quantitative risk assessment of COVID-19 and serious illness among spectators at mass gathering events with vaccine-testing package implementation",
+    "rel_doi": "10.1101/2022.01.29.22270094",
+    "rel_title": "Polygenic predisposition to venous thromboembolism is associated with increased COVID-19 positive testing rates",
     "rel_date": "2022-01-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.30.22269980",
-    "rel_abs": "While mass gathering events have resumed in conjunction with vaccine-testing (VT) packages, their effects on reducing COVID-19 risk remain unclear. Here, we used an environmental exposure model to analyze the effects of vaccinations and proof of negative test results on reducing infection risk and serious illness among spectators at mass gathering events. We then analyzed the difference in risk with and without VT and regular seat zoning. Risk of infection and serious illness were quantified using a model incorporating parameters such as vaccination coverage, vaccine prevention effectiveness, and sensitivity of polymerase chain reaction (PCR) or qualitative antigen tests. When vaccine prevention effectiveness was 50% (corresponding to 4 months for the delta variant and 1-2 months for the omicron variant after the second vaccine dose), the risk of infection and serious illness among vaccinated spectators were 0.32-0.40 and 0.13-0.16 times of those who tested negative, respectively. In contrast, the risks of infection and serious illness among vaccinated spectators without measures such as mask wearing were 4.0 and 1.6 times higher than those among unvaccinated spectators with such measures, respectively. The risk of infection with an 80% vaccination coverage and a vaccine prevention effectiveness of 20% (corresponding to 5-6 months for the delta variant or 3-4 months for the omicron variant after the second vaccine dose) was comparable to that of a 20% vaccine coverage and a vaccine prevention effectiveness of 80% (corresponding to 1-3 months for delta variant after the second vaccine dose). Regarding zoning, there was little difference in risk with a vaccination coverage of [&ge;]80%. Adherence to individual measures after vaccination and maintenance of high vaccine effectiveness among spectators at stadiums are important for reducing risk of infection and serious illness. Furthermore, seat zoning did not affect overall infection risk reduction.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.29.22270094",
+    "rel_abs": "Genetic predisposition to venous thrombosis may impact COVID-19 infection and its sequelae. Participants in the ongoing prospective cohort study, Million Veteran Program (MVP), who were tested for COVID-19, with European ancestry, were evaluated for associations with polygenic venous thromboembolic risk, Factor V Leiden mutation (FVL) (rs6025) and prothrombin gene 3 -UTR mutation (F2 G20210A)(rs1799963), and their interactions. Logistic regression models assessed genetic associations with VTE diagnosis, COVID-19 (positive) testing rates and outcome severity (modified WHO criteria), and post-test conditions, adjusting for outpatient anticoagulation medication usage, age, sex, and genetic principal components. 108,437 out of 464,961 European American MVP participants were tested for COVID-19 with 9786 (9%) positive. PRS(VTE), FVL, F2 G20210A were not significantly associated with the propensity of being tested for COVID-19. PRS(VTE) was significantly associated with a positive COVID-19 test in F5 wild type (WT) individuals (OR 1.05; 95% CI [1.02-1.07]), but not in FVL carriers (0.97, [0.91-1.94]). There was no association with severe outcome for FVL, F2 G20210A or PRS(VTE). Outpatient anticoagulation usage in the two years prior to testing was associated with worse clinical outcomes. PRS(VTE) was associated with prevalent VTE diagnosis among both FVL carriers or F5 wild type individuals as well as incident VTE in the two years prior to testing. Increased genetic propensity for VTE in the MVP was associated with increased COVID-19 positive testing rates, suggesting a role of coagulation in the initial steps of COVID-19 infection.\n\nKey PointsO_LIIncreased genetic predisposition to venous thrombosis is associated with increased COVID-19 positive testing rates.\nC_LIO_LIPRS for VTE further risk stratifies factor V Leiden carriers regarding their VTE risk.\nC_LI",
+    "rel_num_authors": 49,
     "rel_authors": [
       {
-        "author_name": "Michio Murakami",
-        "author_inst": "Osaka University; National Institute of Advanced Industrial Science and Technology"
+        "author_name": "Jessica Minnier",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Tsukasa Fujita",
-        "author_inst": "National Institute of Advanced Industrial Science and Technology"
+        "author_name": "Jennifer E Huffman",
+        "author_inst": "VA Boston Healthcare System"
       },
       {
-        "author_name": "Yuichi Iwasaki",
-        "author_inst": "National Institute of Advanced Industrial Science and Technology"
+        "author_name": "Lina Gao",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Masaki Onishi",
-        "author_inst": "National Institute of Advanced Industrial Science and Technology"
+        "author_name": "Jacob Joseph",
+        "author_inst": "VA Boston Healthcare System"
       },
       {
-        "author_name": "Wataru Naito",
-        "author_inst": "National Institute of Advanced Industrial Science and Technology"
+        "author_name": "Emily S Wan",
+        "author_inst": "VA Boston Healthcare System"
       },
       {
-        "author_name": "Seiya Imoto",
-        "author_inst": "The University of Tokyo"
+        "author_name": "Wen-Chih Wu",
+        "author_inst": "Providence VA Healthcare System"
       },
       {
-        "author_name": "Tetsuo Yasutaka",
-        "author_inst": "National Institute of Advanced Industrial Science and Technology"
+        "author_name": "Ayako Suzuki",
+        "author_inst": "Durham VA Medical Center"
+      },
+      {
+        "author_name": "Gita A Pathak",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Renato Polimanti",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Mehrdad Arjomandi",
+        "author_inst": "San Francisco VA Healthcare System; University of California San Francisco"
+      },
+      {
+        "author_name": "Kyong-Mi Chang",
+        "author_inst": "Corporal Michael J Crescenz VA Medical Center"
+      },
+      {
+        "author_name": "Helene Garcon",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "Anurag Verma",
+        "author_inst": "Corporal Michael J Crescenz VA Medical Center"
+      },
+      {
+        "author_name": "Yuk-Lam Ho",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "James B Meigs",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Kelly Cho",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "Robert A Bonomo",
+        "author_inst": "Louis Stokes Cleveland VA"
+      },
+      {
+        "author_name": "Bryan R Gorman",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "Saiju Pyarajan",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "Elise Gatsby",
+        "author_inst": "VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System"
+      },
+      {
+        "author_name": "Nallakkandi Rajeevan",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Kristine E Lynch",
+        "author_inst": "VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System"
+      },
+      {
+        "author_name": "Julie A Lynch",
+        "author_inst": "VA Salt Lake City Health Care System"
+      },
+      {
+        "author_name": "Seyedeh Maryam Zekavat",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Pradeep Natarajan",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Cecelia J Madison",
+        "author_inst": "Portland VA Medical Center"
+      },
+      {
+        "author_name": "Jin J Zhou",
+        "author_inst": "University of California, Los Angeles"
+      },
+      {
+        "author_name": "Darshana N Jhala",
+        "author_inst": "Corporal Michael J Crescenz VA Medical Center"
+      },
+      {
+        "author_name": "Curtis J Donskey",
+        "author_inst": "Louis Stokes Cleveland VA and Case Western Reserve University"
+      },
+      {
+        "author_name": "John E McGeary",
+        "author_inst": "Providence VA Medical Center"
+      },
+      {
+        "author_name": "Peter D Reaven",
+        "author_inst": "Phoenix VA Healthcare System"
+      },
+      {
+        "author_name": "Yan V Sun",
+        "author_inst": "Emory University School of Public Health"
+      },
+      {
+        "author_name": "Mat Freiberg",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Joel Gelernter",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Jeffrey M Petersen",
+        "author_inst": "Corporal Michael J Crescenz VA Medical Center"
+      },
+      {
+        "author_name": "Adriana Hung",
+        "author_inst": "Tennesse Valley Healthcare System"
+      },
+      {
+        "author_name": "Rose DL Huang",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "Ravi K Madduri",
+        "author_inst": "Argonne National Laboratory"
+      },
+      {
+        "author_name": "Sharvari Dalal",
+        "author_inst": "Corporal Michael J Crescenz VA Medical Center"
+      },
+      {
+        "author_name": "Quinn S Wells",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Katherine P Liao",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "Peter W.F. Wilson",
+        "author_inst": "Atlanta VA Health Care System"
+      },
+      {
+        "author_name": "Philip S Tsao",
+        "author_inst": "VA Palo Alto Health Care System"
+      },
+      {
+        "author_name": "Christopher J O'Donnell",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "John M Gaziano",
+        "author_inst": "VA Boston Healthcare System"
+      },
+      {
+        "author_name": "- VA Million Veteran Program",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Richard L Hauger",
+        "author_inst": "VA San Diego Healthcare System"
+      },
+      {
+        "author_name": "Sudha K. Iyengar",
+        "author_inst": "Case Western Reserve University"
+      },
+      {
+        "author_name": "Shiuh-Wen Luoh",
+        "author_inst": "VA Portland Health Care System"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "hematology"
   },
   {
     "rel_doi": "10.1101/2022.01.30.22269998",
@@ -371131,111 +372890,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.01.27.22269949",
-    "rel_title": "Tracking the progressive spread of the SARS-CoV-2 Omicron variant in Italy, December 2021 - January 2022",
+    "rel_doi": "10.1101/2022.01.28.22270022",
+    "rel_title": "Continuing inequalities in COVID-19 mortality in England and Wales, and the changing importance of regional, over local, deprivation",
     "rel_date": "2022-01-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.27.22269949",
-    "rel_abs": "The SARS-CoV-2 variant of concern Omicron was first detected in Italy in November 2021. Data from three genomic surveys conducted in Italy between December 2021 and January 2022 suggest that Omicron became dominant in less than one month (prevalence on January 3: 78.6%-83.8%) with a doubling time of 2.7-3.1 days. The mean net reproduction number rose from about 1.15 in absence of Omicron to a peak of 1.83 for symptomatic cases and 1.33 for hospitalized cases, while it remained stable for critical cases.",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.28.22270022",
+    "rel_abs": "BackgroundObservational studies have highlighted that where individuals live is far more important for risk of dying with COVID-19, than for dying of other causes. Deprivation is commonly proposed as explaining such differences. During the period of localised restrictions in late 2020, areas with higher restrictions tended to be more deprived. We explore how this impacted the relationship between deprivation and mortality and see whether local or regional deprivation matters more for inequalities in COVID-19 mortality.\n\nMethodsWe use publicly available population data on deaths due to COVID-19 and all-cause mortality between March 2020 and April 2021 to investigate the scale of spatial inequalities. We use a multiscale approach to simultaneously consider three spatial scales through which processes driving inequalities may act. We go on to explore whether deprivation explains such inequalities.\n\nResultsAdjusting for population age structure and number of care homes, we find highest regional inequality in October 2020, with a COVID-19 mortality rate ratio of 5.86 (95% CI 3.31 to 19.00) for the median between-region comparison. We find spatial context is most important, and spatial inequalities higher, during periods of low mortality. Almost all unexplained spatial inequality in October 2020 is removed by adjusting for deprivation. During October 2020, one standard deviation increase in regional deprivation was associated with 2.45 times higher local mortality (95% CI, 1.75 to 3.48).\n\nConclusionsSpatial inequalities are greatest in periods of lowest overall mortality, implying that as mortality declines it does not do so equally. During the prolonged period of low restrictions and low mortality in summer 2020, spatial inequalities strongly increased. Contrary to previous months, we show that the strong spatial patterning during autumn 2020 is almost entirely explained by deprivation. As overall mortality declines, policymakers must be proactive in detecting areas where this is not happening, or risk worsening already strong health inequalities.\n\nKey messages- Spatial inequalities in local mortality are highest in periods of lower overall mortality.\n- Spatial inequality in COVID-19 mortality peaked in October 2020, before decreasing strongly in November and over the winter period.\n- Deprivation explains almost all inequality during October when inequality was at its highest.\n- Regional deprivation was far more strongly associated with local mortality than local deprivation during September to November 2020.\n- This is consistent with an overdispersed distribution of secondary infections governed by transmission heterogeneity structured by deprivation.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Paola Stefanelli",
-        "author_inst": "Istituto Superiore di Sanita"
-      },
-      {
-        "author_name": "Filippo Trentini",
-        "author_inst": "Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy"
-      },
-      {
-        "author_name": "Daniele Petrone",
-        "author_inst": "Istituto Superiore di Sanita"
-      },
-      {
-        "author_name": "Alessia Mammone",
-        "author_inst": "Ministero della Salute"
-      },
-      {
-        "author_name": "Luigina Ambrosio",
-        "author_inst": "Istituto Superiore di Sanita"
-      },
-      {
-        "author_name": "Mattia Manica",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Giorgio Guzzetta",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Valeria D Andrea",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Valentina Marziano",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Agnese Zardini",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Carla Molina Grane",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Marco Ajelli",
-        "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA"
-      },
-      {
-        "author_name": "Angela Di Martino",
-        "author_inst": "Istituto Superiore di Sanita"
-      },
-      {
-        "author_name": "Flavia Riccardo",
-        "author_inst": "Istituto Superiore di Sanita"
-      },
-      {
-        "author_name": "Antonino Bella",
-        "author_inst": "Istituto Superiore di Sanita"
-      },
-      {
-        "author_name": "Monica Sane Schepisi",
-        "author_inst": "Ministero della Salute"
-      },
-      {
-        "author_name": "Francesco Maraglino",
-        "author_inst": "Ministero della Salute"
-      },
-      {
-        "author_name": "Piero Poletti",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Anna Teresa Palamara",
-        "author_inst": "Istituto Superiore di Sanita"
+        "author_name": "Gareth J Griffith",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Silvio Brusaferro",
-        "author_inst": "Istituto Superiore di Sanita"
+        "author_name": "Gwilym Owen",
+        "author_inst": "University of Liverpool"
       },
       {
-        "author_name": "Giovanni Rezza",
-        "author_inst": "Ministero della Salute"
+        "author_name": "David Manley",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Patrizio Pezzotti",
-        "author_inst": "Istituto Superiore di Sanita"
+        "author_name": "Laura D Howe",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Stefano Merler",
-        "author_inst": "Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy"
+        "author_name": "George Davey Smith",
+        "author_inst": "University of Bristol"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.01.27.22269982",
@@ -373005,31 +374692,147 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2022.01.26.22269874",
-    "rel_title": "General practitioner wellbeing during the COVID-19 pandemic: a qualitative interview study",
+    "rel_doi": "10.1101/2022.01.26.22269856",
+    "rel_title": "Antibody and T cell responses to SARS-CoV-2 mRNA vaccines during maintenance therapy for immune-mediated inflammatory diseases",
     "rel_date": "2022-01-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.26.22269874",
-    "rel_abs": "BackgroundWorkload pressures and poor job satisfaction have been reported by UK general practitioners (GPs) for some time. The COVID-19 pandemic presented new challenges, with growing international evidence of its negative impact on GPs mental health and wellbeing. While there has been wide commentary on this topic, UK research evidence is lacking. Developing greater understanding of these lived experiences and subgroup differences is important as doctor wellbeing may affect the sustainability of health care systems and quality of patient care.\n\nObjectivesTo explore the lived experience of UK GPs during COVID-19, and the pandemics impact on their psychological wellbeing.\n\nDesign and SettingIn-depth qualitative interviews, conducted remotely by telephone or video call, with NHS GPs.\n\nParticipantsGPs were sampled purposively across three career stages (early career, established and late career or retired GPs) with variation in other key demographics. A comprehensive recruitment strategy used multiple channels. Data were analysed thematically using Framework Analysis.\n\nResultsWe interviewed 40 GPs; most described generally negative sentiment and many displayed signs of psychological distress and burnout. Causes of stress and anxiety related to personal risk, workload, practice changes, public perceptions and leadership, teamworking and wider collaboration and personal challenges. GPs described facilitators of their wellbeing, including sources of support and plans to reduce clinical hours or change career path.\n\nConclusionsA range of factors detrimentally affected the wellbeing of GPs during the pandemic and we highlight the potential impact of this on workforce retention and quality of care. As the pandemic progresses and general practice faces continued challenges, urgent policy measures are now needed.\n\nStrengths and limitations of this studyO_LIWhile there is growing international evidence base demonstrating the impact of the COVID-19 pandemic on GPs wellbeing and much UK media coverage, this qualitative interview study provides much-needed research evidence of UK GPs lived experiences and wellbeing during COVID-19.\nC_LIO_LI40 GPs were sampled purposively to include GPs with different demographic and practice characteristics.\nC_LIO_LIWhile there are no easy solutions to the problems highlighted, this research provides increased contextualised understanding of how these experiences may impact future workforce retention and the sustainability of health systems longer-term.\nC_LIO_LISub-group differences by gender and age are reported; highlighting a potential need for further research and support targeted at specific groups.\nC_LIO_LIFindings are necessarily limited to the time of data collection (Spring/Summer 2021); further tensions in general practice have since arisen, particularly regarding negative and misleading media portrayal.\nC_LI",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.26.22269856",
+    "rel_abs": "BackgroundLimited information is available on the impact of immunosuppressants on COVID-19 vaccination in patients with immune-mediated inflammatory diseases (IMID).\n\nMethodsThis observational cohort study examined the immunogenicity of SARS-CoV-2 mRNA vaccines in adult patients with inflammatory bowel disease, rheumatoid arthritis, ankylosing spondylitis, or psoriatic disease, with or without maintenance immunosuppressive therapies. Antibody and T cell responses to SARS-COV-2, including neutralization against SARS-CoV-2 variants were determined before and after 1 and 2 vaccine doses.\n\nResultsWe prospectively followed 150 subjects, 26 healthy controls, 9 IMID patients on no treatment, 44 on anti-TNF, 16 on anti-TNF with methotrexate/azathioprine (MTX/AZA), 10 on anti-IL-23, 28 on anti-IL-12/23, 9 on anti-IL-17, and 8 on MTX/AZA. Antibody and T cell responses to SARS-CoV-2 were detected in all participants, increasing from dose 1 to dose 2 and declining 3 months later, with greater attrition in IMID patients compared to healthy controls. Antibody levels and neutralization efficacy against variants of concern were substantially lower in anti-TNF treated patients than in healthy controls and were undetectable against Omicron by 3 months after dose 2.\n\nConclusionsOur findings support the need for a third dose of mRNA vaccine and for continued monitoring of immunity in these patient groups.\n\nFundingFunded by a donation from Juan and Stefania Speck and by Canadian Institutes of Health (CIHR) /COVID-Immunity Task Force (CITF) grants VR-1 172711 and VS1-175545 (T.H.W. and A.C.G); CIHR FDN-143250 (T.H.W.), GA2-177716 (V.C., A.C.G., T.W.), GA1-177703 (A.C.G.) and the CIHR rapid response network to SARS-CoV-2 variants, CoVaRR-Net (to A.C.G.).",
+    "rel_num_authors": 32,
     "rel_authors": [
       {
-        "author_name": "Laura A Jefferson",
-        "author_inst": "University of York"
+        "author_name": "Roya M Dayam",
+        "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada"
       },
       {
-        "author_name": "Claire Heathcote",
-        "author_inst": "University of York"
+        "author_name": "Jaclyn C Law",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
       },
       {
-        "author_name": "Karen Bloor",
-        "author_inst": "University of York"
+        "author_name": "Rogier L Goetgebuer",
+        "author_inst": "Zane Cohen Centre for Digestive Diseases, Division of Gastroenterology, Mount Sinai Hospital, Sinai Health System, University of Toronto, Toronto, Ontario, Cana"
+      },
+      {
+        "author_name": "Gary YC Chao",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "Kento T Abe",
+        "author_inst": "Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health "
+      },
+      {
+        "author_name": "Mitchell Sutton",
+        "author_inst": "Schroeder Arthritis Institute, Krembil Research Institute, University Health Network; Division of Rheumatology, Department of Medicine, University of Toronto, T"
+      },
+      {
+        "author_name": "Naomi Finkelstein",
+        "author_inst": "Schroeder Arthritis Institute, Krembil Research Institute, University Health Network; Division of Rheumatology, Department of Medicine, University of Toronto, T"
+      },
+      {
+        "author_name": "Joanne M Stempak",
+        "author_inst": "Zane Cohen Centre for Digestive Diseases, Division of Gastroenterology, Mount Sinai Hospital, Sinai Health System, University of Toronto, Toronto, Ontario, Cana"
+      },
+      {
+        "author_name": "Daniel Pereira",
+        "author_inst": "Schroeder Arthritis Institute, Krembil Research Institute, University Health Network; Division of Rheumatology, Department of Medicine, University of Toronto, T"
+      },
+      {
+        "author_name": "David Croituru",
+        "author_inst": "Division of Dermatology, Department of Medicine, University of Toronto, Toronto, Canada"
+      },
+      {
+        "author_name": "Lily Acheampong",
+        "author_inst": "Division of Dermatology, Department of Medicine, Womens College Hospital, Toronto, Canada"
+      },
+      {
+        "author_name": "Saima Rizwan",
+        "author_inst": "Zane Cohen Centre for Digestive Diseases, Division of Gastroenterology, Mount Sinai Hospital, Sinai Health System, University of Toronto, Toronto, Ontario, Cana"
+      },
+      {
+        "author_name": "Klaudia Rymaszewski",
+        "author_inst": "Zane Cohen Centre for Digestive Diseases, Division of Gastroenterology, Mount Sinai Hospital, Sinai Health System, University of Toronto, Toronto, Ontario, Cana"
+      },
+      {
+        "author_name": "Raquel Milgrom",
+        "author_inst": "Zane Cohen Centre for Digestive Diseases, Division of Gastroenterology, Mount Sinai Hospital, Sinai Health System, University of Toronto, Toronto, Ontario, Cana"
+      },
+      {
+        "author_name": "Darshini Ganatra",
+        "author_inst": "Schroeder Arthritis Institute, Krembil Research Institute, University Health Network; Division of Rheumatology, Department of Medicine, University of Toronto, T"
+      },
+      {
+        "author_name": "Nathalia Vieira Batista",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "Melanie Girard",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "Irene Lau",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "Ryan Law",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "Michelle W Cheung",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "Bhavisha Rathod",
+        "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "Julia Kitaygorodsky",
+        "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada,Department of Molecular Genetics, University of To"
+      },
+      {
+        "author_name": "Reuben Samson",
+        "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada, Department of Molecular Genetics, University of T"
+      },
+      {
+        "author_name": "Queenie Hu",
+        "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada"
+      },
+      {
+        "author_name": "W Rod Hardy",
+        "author_inst": "Sinai Health System"
+      },
+      {
+        "author_name": "Nigil Haroon",
+        "author_inst": "Schroeder Arthritis Institute, Krembil Research Institute, University Health Network; Division of Rheumatology, Department of Medicine, University of Toronto, T"
+      },
+      {
+        "author_name": "Robert D Inman",
+        "author_inst": "Schroeder Arthritis Institute, Krembil Research Institute, University Health Network; Division of Rheumatology, Department of Medicine, University of Toronto, T"
+      },
+      {
+        "author_name": "Vincent Piguet",
+        "author_inst": "Division of Dermatology, Department of Medicine, University of Toronto, Toronto, Canada;   Division of Dermatology, Department of Medicine, Womens College Hospi"
+      },
+      {
+        "author_name": "Vinod Chandran",
+        "author_inst": "Schroeder Arthritis Institute, Krembil Research Institute, University Health Network; Division of Rheumatology, Department of Medicine, University of Toronto, T"
+      },
+      {
+        "author_name": "Mark S Silverberg",
+        "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada,Zane Cohen Centre for Digestive Diseases, Division"
+      },
+      {
+        "author_name": "Anne-Claude Gingras",
+        "author_inst": "Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital; Sinai Health System, Department of Molecular Genetics, University of Toronto, Toronto, Ontario, "
+      },
+      {
+        "author_name": "Tania H Watts",
+        "author_inst": "Department of Immunology, University of Toronto, Toronto, Ontario, Canada"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.01.26.22269824",
@@ -375051,107 +376854,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.01.18.22269420",
-    "rel_title": "Immune response to third SARS-CoV-2 vaccination in seronegative kidney transplant recipients: possible improvement by mycophenolate mofetil reduction",
+    "rel_doi": "10.1101/2022.01.20.21267627",
+    "rel_title": "\"It affects every aspect of your life\": A qualitative study of the impact of delaying surgery during COVID-19",
     "rel_date": "2022-01-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.18.22269420",
-    "rel_abs": "BackgroundModification of vaccination strategies is needed to improve the immune response to SARS-CoV-2 vaccination in kidney transplant recipients (KTRs).\n\nMethodsThis multicenter observational study aimed to determine antibody kinetics among 60 seropositive KTRs and analyzed the effects of the third vaccination against SARS-CoV-2 in 174 previously seronegative KTRs. We investigated whether mycophenolate mofetil (MMF) dose reduction by 25-50% prior the third vaccination influences vaccination success.\n\nResults18 of 60 (30%) seropositive KTRs became seronegative in the serological assay within six months. Loss of antibodies was predicted by low initial antibody levels ([&le;]206.8 BAU/ml), older age, and impaired graft function. A third vaccination in previously seronegative KTRs induced seroconversion in 56 of 174 (32.1%) KTRs with median antibody levels 119 (76-353) BAU/ml and median neutralizing capacity titer of 1:10 (0- 1:40). Multivariate logistic regression revealed that initial antibody levels (OR 1.39, 95% CI 1.09-1.76), graft function (OR 0.05, 95% CI 0.01-0.39), time after transplantation (OR 1.04, 95% CI 1.02-1.07) and MMF trough levels (OR 0.43, 95% CI 0.21-0.88) correlated with seroconversion, p<0.05. After controlling for these confounders, the effect of MMF dose reduction was calculated using propensity score matching. KTRs in the MMF reduction group had significantly lower MMF serum concentrations prior to the third vaccination and were more likely to develop antibody levels [&ge;]35.2 BAU/ml than their matched KTRs (p=0.02).\n\nConclusionsTemporary reduction in MMF dose might be a promising approach to improve the immune response in KTRs.",
-    "rel_num_authors": 22,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.20.21267627",
+    "rel_abs": "BackgroundThe COVID-19 pandemic has overwhelmed healthcare systems, leading many jurisdictions to reduce surgical services to create capacity (beds and staff) to care for the surge of patients with COVID-19. These decisions were made in haste, and little is known about the impact on patients whose surgery was delayed. This study explores the impact of delaying non-urgent surgeries on patients, from their perspective.\n\nMethodsUsing an interpretative description approach, we conducted interviews with adult patients and their caregivers who had their surgery delayed or cancelled during the COVID-19 pandemic in Alberta, Canada. Trained interviewers conducted semi-structured interviews. Interviews were iteratively analyzed by two independent reviewers using an inductive approach to thematic content analysis to understand key elements of the patient experience.\n\nResultsWe conducted 16 interviews with participants ranging from 27 to 75 years of age with a variety of surgical procedures delayed. We identified four interconnected themes: individual-level impacts (physical health, mental health, family and friends, work, quality of life), system-level factors (healthcare resources, communication, perceived accountability/responsibility), unique issues related to COVID-19, and uncertainty.\n\nInterpretationThe patient-reported impact of having a surgery delayed during the COVID-19 pandemic was diffuse and consequential. While the decision to delay non-urgent surgeries was made to manage the strain on healthcare systems, our study illustrates the consequences of these decisions. We advocate for the development and adoption of strategies to mitigate the burden of distress that waiting for surgery during and after COVID-19 has on patients and their family/caregivers.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Marta Kantauskaite",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Lias Mueller",
-        "author_inst": "University Hospital Duesseldorf"
-      },
-      {
-        "author_name": "Jonas Hillebrandt",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Joshua Leon Lamberti",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Svenja Fischer",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Thilo Kolb",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Katrin Ivens",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Michael Koch",
-        "author_inst": "Nephrocare Mettmann"
-      },
-      {
-        "author_name": "Marcel Andree",
-        "author_inst": "University Hospital Duesseldorf"
-      },
-      {
-        "author_name": "Nadine Luebke",
-        "author_inst": "University Hospital Duesseldorf"
-      },
-      {
-        "author_name": "Michael Schmitz",
-        "author_inst": "Klinikum Solingen"
-      },
-      {
-        "author_name": "Tom Luedde",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Hans Martin Orth",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Torsten Feldt",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
-      },
-      {
-        "author_name": "Heiner Schaal",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
+        "author_name": "Khara M Sauro",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Ortwin Adams",
-        "author_inst": "University Hospital Duesseldorf"
+        "author_name": "Christine Smith",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Claudia Schmidt",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
+        "author_name": "Jaling Kersen",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Margarethe Kittel",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
+        "author_name": "Emma Schalm",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Eva Koenigshausen",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
+        "author_name": "Natalia Jaworska",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Lars Christian Rump",
-        "author_inst": "Heinrich-Heine University-Duesseldorf"
+        "author_name": "Pamela Roach",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Joerg Timm",
-        "author_inst": "University hospital Duesseldorf"
+        "author_name": "Sanjay Beesoon",
+        "author_inst": "Alberta Health Services"
       },
       {
-        "author_name": "Johannes Stegbauer",
-        "author_inst": "Heinrich-Heine-University Duesseldorf"
+        "author_name": "Mary Brindle",
+        "author_inst": "University of Calgary"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "nephrology"
+    "category": "surgery"
   },
   {
     "rel_doi": "10.1101/2022.01.26.22269659",
@@ -377349,71 +379096,31 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.01.23.22269669",
-    "rel_title": "Effects of 12 weeks of Multi-nutrient supplementation on the Immune and Musculoskeletal systems of Older Adults in Aged-Care (The Pomerium Study): Protocol for a Randomised Controlled Trial",
+    "rel_doi": "10.1101/2022.01.23.22269626",
+    "rel_title": "Death review caused by Covid 19 in Bangladesh",
     "rel_date": "2022-01-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.23.22269669",
-    "rel_abs": "IntroductionImmunosenescence leads to increased morbidity and mortality associated with viral infections and weaker vaccine responses. This has been well documented for seasonal influenza and the current pandemic with Sars-Cov2, which disproportionately impact older adults, particularly those in residential aged care facilities. Inadequate nutrient intake associated with impaired immunity, respiratory and muscle function are likely to augment the effects of immunosenescence. In this study, we test whether the effects of inadequate nutrition can be reversed by multi-nutrient supplementation, consequently enhancing vaccine responses, reducing the risk of viral infections, and improving respiratory and muscle function.\n\nMethods and analysisThe Pomerium Study is a 12-week, single-blinded, randomised, placebo-controlled trial testing the effects of two daily servings of an oral multi-nutrient supplement (330 kcal, 20g protein, 1.2g CaHMB, 449mg calcium, 520IU vitamin D3, and 25 vitamins and minerals) on the immune system and muscle and respiratory function of older adults in aged-care in Melbourne, Australia. 160 older adults ([&ge;]75 years old) will be recruited from aged-care facilities and randomised to treatment (multi-nutrient supplement) or control (usual care). Primary outcome is the change in T-cell subsets CD8+ and CD28null counts at 4 and 12 weeks post-intervention. Secondary outcomes measured at baseline and after 12 weeks post-intervention are multiple markers of immunosenescence, body composition (bioimpedance), handgrip strength (dynamometer), physical function (short physical performance battery), respiratory function (spirometry), and quality of life (EQ-5D-3L). Incidence and complications of COVID-19 and/or viral infections (i.e., hospitalisation, complications, or death) will be recorded throughout the trial.\n\nDiscussionIf the Pomerium Study demonstrates efficacy and safety of a multi-nutrient supplement on immune, muscle and respiratory function, it may be suitable as a strategy to reduce the adverse outcomes from seasonal influenza and viral infections such as COVID-19 in older adults in aged-care.\n\nFunding, Ethics, Registration and DisseminationThe study is funded by the Australian Medical Research Future Fund. It is approved by Melbourne Health Human Research Ethics Committee (Ref No. HREC/73985/MH-2021, ERM Ref No. RMH73985, Melbourne Health Site Ref No. 2021.115), and registered at ANZCTR (12621000420842). Results will be published in peer-reviewed journals and made available to aged-care stakeholders, including providers, residents, and government bodies.\n\nArticle Summary Strengths and LimitationsO_LIThis is the first study performing a comprehensive immune, respiratory and functional assessment in aged care residents after receiving a multi-nutrient solution that is commercially available.\nC_LIO_LIOur design and tested intervention assure that the results of the study will be rapidly translated into practice.\nC_LIO_LIThe main limitation is that any biological effect observed cannot be attributed to one component of the multi-nutrient supplement.\nC_LIO_LIAnother limitation is that the potential effect of group differences in energy intake on outcomes can only be monitored by assessing regular dietary intake and weight changes during the study period.\nC_LI",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.23.22269626",
+    "rel_abs": "IntroductionCOVID-19 pandemic had taken away lots of human life prematurely worldwide and death laid its icy hands also on Bangladesh. So, objectives of this study were to explore the monthly distributions, age, sex, co-morbidities, localities and duration of hospital stay among the COVID death cases.\n\nMethodsIn this observational study six months hospital death files were collected and explored for monthly distributions, age, sex, co-morbidities, localities and hospital stay. RT-PCR positive confirmed 113 COVID deaths were enrolled and suspected COVID deaths were excluded. Ethical clearance from the hospital authority was taken before hand. Data was compiled and analyzed by SPSS-20.\n\nResultsThere was a low frequency of death in May-2021 and October-2021(7.1% and 2.7% respectively) but more during June -2021 to September 2021 (12.4%, 16.8%, 42.5% and 18.6% respectively). Female deaths were little more than male deaths(53.1% vs 46.9%). Age more than 51 years were the most vulnerable where 26(23%) deaths were at age group 51-60 years, 39(34.5%) deaths were at 61-70 years and 22(19.4%) deaths were more than 71 years. Mean age of death was found 60.66 years and mean duration of hospital stay was found 9.45 days. Maximum duration of hospital stay was 45 days for one patient. Co-morbidities of death cases revealed 52(46.00%) patients had DM and HTN both, 17(15.0%) patients had HTN, 16(14.1%) had DM, 3(2.6%) had BA and COPD, 4(3.5%) had CKD, 2(1.7%) had cancer, 3(2.6%) had CVD, 19(16.8%) had IHD and 16(14.1%) patients had no co-morbidities. Locality of the death cases revealed 44(38.9%) came from rural areas and 69(61.1%) came from urban areas.\n\nConclusionHigher age group and multiple co-morbidities specially DM, HTN and IHD were related with COVID deaths mostly found in our study.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Ahmed Al Saedi",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Ben Kirk",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Sandra Iuliano",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Jesse Zanker",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Sara Vogrin",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Lata Jayaram",
-        "author_inst": "Western Health"
-      },
-      {
-        "author_name": "Shane Thomas",
-        "author_inst": "Australian Institute for Musculoskeletal Science (AIMSS)"
-      },
-      {
-        "author_name": "Christine Golding",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Diana Navarro-Perez",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Petra Marusic",
-        "author_inst": "Australian Institute for Musculoskeletal Science (AIMSS)"
-      },
-      {
-        "author_name": "Sean Leng",
-        "author_inst": "Johns Hopkins University"
+        "author_name": "Rajat Sanker Roy Biswas",
+        "author_inst": "CMOSHMC"
       },
       {
-        "author_name": "Ralph Nanan",
-        "author_inst": "University of Sydney"
+        "author_name": "Jishu Deb Nath",
+        "author_inst": "CMOSHMC"
       },
       {
-        "author_name": "Gustavo Duque",
-        "author_inst": "The University of Melbourne"
+        "author_name": "Fatema Emrose Nisha",
+        "author_inst": "CMOSHMC"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "geriatric medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.01.23.22269497",
@@ -378939,47 +380646,59 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.01.25.22269735",
-    "rel_title": "Acquired neutralizing breadth against SARS-CoV-2 variants including Omicron after three doses of mRNA COVID-19 vaccination and the vaccine efficacy",
+    "rel_doi": "10.1101/2022.01.24.22269781",
+    "rel_title": "Effects of vaccination against COVID-19 on the emotional health of Peruvian older adults",
     "rel_date": "2022-01-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.25.22269735",
-    "rel_abs": "To investigate the induction of neutralizing antibodies against Omicron after two and three vaccine doses in recipients of different ages. Physicians at Kobe University Hospital who had received the second dose of the BNT162b2 mRNA vaccine. At 2 months after the second vaccinations, the positive rate of neutralizing antibody against Omicron was 28%, and the titer was significantly lower than those against other variants, 11.8-fold and 3.6-fold lower than those against D614G and Delta, respectively. Unlike Delta, that positive rates of neutralizing antibody against Omicron were low in all age groups, and there was no significant difference in titers among age groups. Seven months after the 2nd dose, the positive rate of neutralizing antibody against Omicron decreased to 6%, but after the booster,3rd vaccination, it increased to 100%, and the titer was much higher than those at 2 and 7 months post-vaccination, 32-fold and 39-fold respectively. The booster vaccination effect was also observed in the younger at 41-fold, middle-aged at 43-fold, and older at 27-fold groups compared to the 7-month titers. Surprisingly, higher-than-predicted titers of the neutralizing antibodies against Omicron were induced after the booster vaccination regardless of recipient age, while this effect was not observed after two doses, indicating the induction of antibodies against common epitopes by the booster vaccination. Three doses can be confidently recommended to suppress the pandemic.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.24.22269781",
+    "rel_abs": "BackgroundCOVID-19 vaccination may reduce anxiety and depression. However, the pandemic significantly impacted the elderly from low-middle-income countries. Therefore, we aimed to estimate the effect of vaccination against COVID-19 on the emotional health of older adults.\n\nMethodsWe selected a nationally stratified sample of non-hospitalized adults aged 60 to 79 years who intended to receive the COVID-19 vaccine or had already received it during recruitment. We assess the fear, anxiety, and worry about COVID-19, general anxiety, and depression at baseline and after a month. We estimated the adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) for each altered emotional health outcomes in those who had one and two doses, compared with those who were not vaccinated using multilevel logistic regression with mixed effects.\n\nResultsWe recruited 861 older adults. Loss to follow-up was 20.8%. At baseline, 43.9% had only one dose of the vaccine, and 49.1% had two doses. In the analysis during follow-up, those who had two doses had less fear (ORa: 0.19; CI95%: 0.07 to 0.51) and anxiety to COVID-19 (ORa: 0.45; CI95%: 0.22 to 0.89), compared to non-vaccinated. We observed no effects in those with only one dose.\n\nLimitationsInability to obtain the planned sample size for primary analysis. There is a selection bias during recruitment and a measurement bias because of self-reported vaccination.\n\nConclusionsCOVID-19 vaccination with two doses in elders improves the perception of COVID-19 infection consequences. This information could be integrated into the vaccination campaign as its beneficial effect.\n\nHighlightsO_LIUp to 90% of elders in a Peruvian sample had at least one dose of COVID-19 vaccine\nC_LIO_LITwo doses of COVID-19 vaccine reduced the levels of fear and anxiety for COVID-19\nC_LIO_LIOnly one dose of vaccine didnt had effect in any emotional mental outcome\nC_LI",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Koichi Furukawa",
-        "author_inst": "Kobe Unibersity"
+        "author_name": "Christoper A. Alarcon-Ruiz",
+        "author_inst": "Direccion de Investigacion en Salud, Instituto de Evaluacion de Tecnologias en Salud e Investigacion, IETSI, EsSalud, Lima, Peru"
       },
       {
-        "author_name": "Lidya Handayani Tjan",
-        "author_inst": "Kobe University"
+        "author_name": "Zoila Romero-Albino",
+        "author_inst": "Gerencia de la Persona Adulta Mayor y Prestaciones Sociales, EsSalud, Lima, Peru"
       },
       {
-        "author_name": "Yukiya Kurahashi",
-        "author_inst": "Kobe University"
+        "author_name": "Percy Soto-Becerra Sr.",
+        "author_inst": "Direccion de Investigacion en Salud, Instituto de Evaluacion de Tecnologias en Salud e Investigacion, IETSI, EsSalud, Lima, Peru"
       },
       {
-        "author_name": "Silvia Sutandhio",
-        "author_inst": "Kobe University"
+        "author_name": "Jeff Huarcaya-Victoria",
+        "author_inst": "Departamento de Psiquiatria, Unidad Funcional de Psiquiatria de Enlace, Hospital Nacional Guillermo Almenara Irigoyen, EsSalud, Lima, Peru"
       },
       {
-        "author_name": "Mitsuhiro Nishimura",
-        "author_inst": "Kobe University"
+        "author_name": "Fernando M. Runzer-Colmenares",
+        "author_inst": "Facultad de Ciencias de la Salud, Universidad Cientifica del Sur, Lima, Peru"
       },
       {
-        "author_name": "Jun Arii",
-        "author_inst": "Kobe University"
+        "author_name": "Elisa Romani-Huacani",
+        "author_inst": "Asociacion benefica PRISMA, Lima Peru"
       },
       {
-        "author_name": "Yasuko Mori",
-        "author_inst": "Kobe University Graduate School of Medicine"
+        "author_name": "David Villarreal-Zegarra",
+        "author_inst": "Instituto Peruano de Orientacion Psicologica, Lima, Peru"
+      },
+      {
+        "author_name": "Jorge L. Maguina",
+        "author_inst": "Direccion de Investigacion en Salud, Instituto de Evaluacion de Tecnologias en Salud e Investigacion, IETSI, EsSalud, Lima, Peru"
+      },
+      {
+        "author_name": "Moises Apolaya-Segura",
+        "author_inst": "Direccion de Investigacion en Salud, Instituto de Evaluacion de Tecnologias en Salud e Investigacion, IETSI, EsSalud, Lima, Peru"
+      },
+      {
+        "author_name": "Sofia Cuba-Fuentes",
+        "author_inst": "Gerencia de la Persona Adulta Mayor y Prestaciones Sociales, EsSalud, Lima, Peru"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2022.01.24.22269542",
@@ -380569,63 +382288,167 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.01.23.22269716",
-    "rel_title": "Evidence on the role of journal editors in the COVID19 infodemic: metascientific study analyzing COVID19 publication rates and patterns",
+    "rel_doi": "10.1101/2022.01.24.22269734",
+    "rel_title": "SARS-CoV-2 viremia precedes an IL6 response in severe COVID-19 patients: results of a longitudinal prospective cohort",
     "rel_date": "2022-01-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.23.22269716",
-    "rel_abs": "ObjectiveInfodemic, a neologism characterizing an excess of fast-tracked low quality publications, has been employed to depict the scientific research response to the COVID19 crisis. The concept relies on the presumed exponential growth of research output. This study aimed to test the COVID19 infodemic claim by assessing publication rates and patterns of COVID19-related research and a control, a year prior.\n\nDesignA Reproduction Number of Publications (Rp) was conceived. It was conceptualized as a division of a week incidence of publications by the average of publications of the previous week. The publication growth rates of preprint and MEDLINE-indexed peer-reviewed literature on COVID19 were compared using the correspondent Influenza output, a year prior, as control. Rp for COVID19 and Influenza papers and preprints were generated and compared and then analyzed in light of the respective growth patterns of their papers and preprints.\n\nMain outcomesOutput growth rates and Reproduction Number of Publications (Rp).\n\nResultsCOVID19 peer-reviewed papers showed a fourteen fold increase compared to Influenza papers. COVID19 papers and preprints displayed an exponential growth curve until the 20th week. COVID19 papers displayed Rp=3.17{+/-}0.72, while the control group presented Rp=0.97{+/-}0.12. Their preprints exhibited Rp=2.18{+/-}0.54 and Rp=0.97{+/-}0.27 respectively, with no evidence of exponential growth in the control group, as its Rp remained approximately one.\n\nConclusionsCOVID19 publications displayed an epidemic pattern. As the growth patterns of COVID19 peer-reviewed articles and preprints were similar, and the majority of the COVID19 output came from indexed journals, not only authors but also editors appear to had played a significant part on the infodemic.\n\nReview protocolhttps://osf.io/q3zkw/?view_only=ff540dc4630b4c6e9a2639d732047324\n\nEthical aspectsNo ethical clarence was required as all analyzed data were publicly available.\n\nO_TEXTBOXSUMMARY BOX\n\n1. What is already known about this subject?\n\nMuch has been commented on 2020s excess of publications on COVID19. Independent studies found evidence of increased volume and speed of publication, decreased methodological quality, and qualitative variations in peer review of COVID19 papers, when compared to the scholarly output from before the pandemic. This phenomenon has been branded an infodemic, a neologism implying an epidemic of low-quality information on COVID19 when high quality scientific reports to inform health policies would have been needed the most.\n\n2. What are the new findings?\n\nNo study pushed the infodemic metaphor forward to analyze not only volume of publication but also publication rates comparing them to a control group as to clearly pinpoint an exponential phase of contagion in the infodemic (as it would take place in a real epidemic) through a mathematical analysis of the growth patterns and rates of those publications. In this paper, we were able to demonstrate that there has been an infodemic indeed and that the editor population was as susceptible to the infodemic bug as the author population because the exponential phase was shaped not only by authors but mainly by editors from PubMed-indexed journals.\n\n3.How might it impact clinical practice in the foreseeable future?\n\nThese results and conclusions are consequential to subsequent studies on rigor and depth of post publication peer review and on editorial practices within the life and health sciences research community.\n\nC_TEXTBOX",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.24.22269734",
+    "rel_abs": "BackgroundInterleukin 6 (IL6) levels and SARS-CoV-2 viremia have been correlated with COVID-19 severity. The association over time between them has not been assessed in a prospective cohort. Our aim was to evaluate the relationship between SARS-CoV-2 viremia and time evolution of IL6 levels in a COVID-19 prospective cohort.\n\nMethodsSecondary analysis from a prospective cohort including COVID-19 hospitalized patients from Hospital Universitario La Princesa between November 2020 and January 2021. Serial plasma samples were collected from admission until discharge. Viral load was quantified by Real-Time Polymerase Chain Reaction and IL6 levels with an enzyme immunoassay. To represent the evolution over time of both variables we used the graphic command twoway of Stata.\n\nResultsA total of 57 patients were recruited, with median age of 63 years (IQR [53-81]), 61.4% male and 68.4% caucasian. The peak of viremia appeared shortly after symptom onset in patients with persistent viremia (more than 1 sample with >1.3 log10 copies/ml) and also in those with at least one IL6>30 pg/ml, followed by a progressive increase in IL6 around 10 days later. Persistent viremia in the first week of hospitalization was associated with higher levels of IL6. Both IL6 and SARS-CoV-2 viral load were higher in males, with a quicker increase with age.\n\nConclusionsIn those patients with worse outcomes, an early peak of SARS-CoV-2 viral load precedes an increase in IL6 levels. Monitoring SARS-CoV-2 viral load during the first week after symptom onset may be helpful to predict disease severity in COVID-19 patients.",
+    "rel_num_authors": 37,
     "rel_authors": [
       {
-        "author_name": "Gabriel Grisi",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Emilia Roy-Vallejo",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Laura Cardenoso",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Joao de Deus Barreto Segundo",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Ana Triguero-Martinez",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Camila Veronica Freire",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Marta Chicot Llano",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Nelly D. Zurita Cruz",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Denise Matias",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Elena Avalos Perez-Urria",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Mariana Cruz",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Ana Barrios",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Larrie Rabelo Laporte",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Julia Hernando Santos",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Daniel Medina",
-        "author_inst": "Universidade Federal do Reconcavo da Bahia"
+        "author_name": "Javier Ortiz",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Thiago Masashi Taniguchi",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Sebastian C. Rodriguez-Garcia",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Leticia Requiao",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Marianela Ciudad Sanudo",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Bruno Goes",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Celeste Marcos",
+        "author_inst": "Hospital Universitario de La Princesa"
       },
       {
-        "author_name": "Luis Claudio Lemos Correia",
-        "author_inst": "Escola Bahiana de Medicina e Saude Publica"
+        "author_name": "Elena Garcia Castillo",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Leticia Fontan Garcia-Rodrigo",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Begona Gonzalez",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Rosa Mendez",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Isabel Iturrate",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Ancor Sanz-Garcia",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Almudena Villa",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Ana Sanchez Azofra",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Begona Quicios",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "David Arribas",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Jesus Alvarez-Rodriguez",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Pablo Patino",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Marina Trigueros",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Miren Uriarte",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Alexandra Martin Ramirez",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Cristina Arevalo",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Jose Maria Galvan-Roman",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Rosario Garcia-Vicuna",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Julio Ancochea",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Cecilia Munoz-Calleja",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Elena Fernandez-Ruiz",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Rafael de la Camara",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Carmen Suarez Fernandez",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Isidoro Gonzalez-Alvaro",
+        "author_inst": "Hospital Universitario de La Princesa"
+      },
+      {
+        "author_name": "Diego A. Rodriguez Serrano",
+        "author_inst": "Hospital Universitario de La Princesa"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2022.01.24.477479",
@@ -382579,143 +384402,39 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.01.17.475291",
-    "rel_title": "Comprehensive Evaluation of ACE2-Fc Combination with Neutralization Antibody on Broad Protection against SARS-CoV-2 and Its Variants",
+    "rel_doi": "10.1101/2022.01.20.477105",
+    "rel_title": "In Silico Analysis Of The Effects Of Omicron Spike Amino Acid Changes On The Interactions With Human ACE2 Receptor And Structurally Characterized Complexes With Human Antibodies",
     "rel_date": "2022-01-22",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.17.475291",
-    "rel_abs": "Emerging SARS-CoV-2 variants are threatening the efficacy of antibody therapies. Combination treatments including ACE2-Fc have been developed to overcome the evasion of neutralizing antibodies (NAbs) in individual cases. Here we conducted a comprehensive evaluation of this strategy by combining ACE2-Fc with NAbs of diverse epitopes on the RBD. NAb+ACE2-Fc combinations efficiently neutralized HIV-based pseudovirus carrying the spike protein of the Delta or Omicron variants, achieving a balance between efficacy and breadth. In an antibody escape assay using replication-competent VSV-SARS-CoV-2-S, all the combinations had no escape after fifteen passages. By comparison, all the NAbs without combo with ACE2-Fc had escaped within six passages. Further, the VSV-S variants escaped from NAbs were neutralized by ACE2-Fc, revealing the mechanism of NAb+ACE2-Fc combinations survived after fifteen passages. We finally examined ACE2-Fc neutralization against pseudovirus variants that were resistant to the therapeutic antibodies currently in clinic. Our results suggest ACE2-Fc is a universal combination partner to combat SARS-CoV-2 variants including Delta and Omicron.",
-    "rel_num_authors": 31,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.20.477105",
+    "rel_abs": "The new SARS-CoV-2 variant Omicron is characterised, among others, by more than 30 amino acid changes (including 4 deletions and 1 insertion) occurring on the spike glycoprotein.\n\nWe report a comprehensive analysis of the effects of the Omicron spike amino acid changes in the interaction with human ACE2 receptor or with human antibodies, obtained by analysing the publicly available resolved 3D structures. Our analysis predicts that amino acid changes occurring on amino acids interacting with the ACE2 receptor may increase Omicron transmissibility. The interactions of Omicron spike with human antibodies can be both negatively and positively affected by amino acid changes, with a predicted total loss of interactions only in few complexes. We believe that such an approach can be used to better understand SARS-CoV-2 transmissibility, detectability, and epidemiology, especially when extended to other than spike proteins.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Haoneng Tang",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Yong Ke",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Hang Ma",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Lei Han",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China; Jecho Institu"
-      },
-      {
-        "author_name": "Lei Wang",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Huifang Zong",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Yunsheng Yuan",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Zhenyu Wang",
-        "author_inst": "Jecho Biopharmaceuticals Co., Ltd. Tianjin 300467, China"
-      },
-      {
-        "author_name": "Yang He",
-        "author_inst": "Jecho Biopharmaceuticals Co., Ltd. Tianjin 300467, China"
-      },
-      {
-        "author_name": "Yunsong Chang",
-        "author_inst": "Jecho Biopharmaceuticals Co., Ltd. Tianjin 300467, China"
+        "author_name": "Deborah Giordano",
+        "author_inst": "National Research Council, Institute of Food Science"
       },
       {
-        "author_name": "Shusheng Wang",
-        "author_inst": "Jecho Laboratories, Inc. Frederick, MD 21704, USA"
+        "author_name": "Bernardina Scafuri",
+        "author_inst": "Department of Chemistry and Biology \"A. Zambelli\", University of Salerno"
       },
       {
-        "author_name": "Junjun Liu",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
+        "author_name": "Carmen Biancaniello",
+        "author_inst": "Department of Electrical Engineering and Information Technology, University of Naples \"Federico II\""
       },
       {
-        "author_name": "Yali Yue",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Wenbo Xu",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, China CDC, Beijing 102206, China"
+        "author_name": "Mauro Petrillo",
+        "author_inst": "Seidor Italy srl"
       },
       {
-        "author_name": "Xiaoju Zhang",
-        "author_inst": "Zhengzhou University Peoples Hospital; Henan Provincial Peoples Hospital, Department of Respiratory and Critical Care Medicine, Zhengzhou 450003, Henan, China"
-      },
-      {
-        "author_name": "Ziqi Wang",
-        "author_inst": "Zhengzhou University Peoples Hospital; Henan Provincial Peoples Hospital, Department of Respiratory and Critical Care Medicine, Zhengzhou 450003, Henan, China"
-      },
-      {
-        "author_name": "Li Yang",
-        "author_inst": "Zhengzhou University Peoples Hospital; Henan Provincial Peoples Hospital, Department of Respiratory and Critical Care Medicine, Zhengzhou 450003, Henan, China"
-      },
-      {
-        "author_name": "Hua Chen",
-        "author_inst": "Jecho Laboratories, Inc. Frederick, MD 21704, USA"
-      },
-      {
-        "author_name": "Yanlin Bian",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Baohong Zhang",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Yunji Liao",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Haiyang Yin",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Yi Chen",
-        "author_inst": "Zhengzhou University Peoples Hospital; Henan Provincial Peoples Hospital, Clinical Research Service Center, Zhengzhou 450003, Henan, China"
-      },
-      {
-        "author_name": "En Zhang",
-        "author_inst": "School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; Shanghai Municipal Veterinary Key Laboratory, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Xiaoxiao Zhang",
-        "author_inst": "School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; Shanghai Municipal Veterinary Key Laboratory, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Hua Jiang",
-        "author_inst": "Jecho Biopharmaceuticals Co., Ltd. Tianjin 300467, China; Jecho Laboratories, Inc. Frederick, MD 21704, USA"
-      },
-      {
-        "author_name": "Yueqing Xie",
-        "author_inst": "Jecho Laboratories, Inc. Frederick, MD 21704, USA"
-      },
-      {
-        "author_name": "John Gilly",
-        "author_inst": "Jecho Biopharmaceuticals Co., Ltd. Tianjin 300467, China; Jecho Laboratories, Inc. Frederick, MD 21704, USA"
-      },
-      {
-        "author_name": "Mingyuan Wu",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Tao Sun",
-        "author_inst": "School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; Shanghai Municipal Veterinary Key Laboratory, Shanghai 200240, China"
-      },
-      {
-        "author_name": "Jianwei Zhu",
-        "author_inst": "Engineering Research Center of Cell and Therapeutic Antibody, Ministry of Education, China; Shanghai Jiao Tong University, Shanghai 200240, China; Jecho Biophar"
+        "author_name": "Angelo Facchiano",
+        "author_inst": "National Research Council, Institute of Food Science"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "new results",
-    "category": "cell biology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2022.01.20.477107",
@@ -384437,57 +386156,45 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2022.01.20.22269321",
-    "rel_title": "Extreme \u03b3' fibrinogen levels in COVID-19 patients",
+    "rel_doi": "10.1101/2022.01.20.22269618",
+    "rel_title": "Molecular diagnosis of SARS-CoV-2: a validation of saliva samples",
     "rel_date": "2022-01-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.20.22269321",
-    "rel_abs": "BackgroundCOVID-19 progression can be accompanied by a \"cytokine storm\" that leads to secondary sequelae such as thrombosis and acute respiratory distress syndrome. Several inflammatory cytokines have been associated with COVID-19 progression, but have far too much daily intra-individual variability to be useful in tracking the course of the disease. In contrast, we have shown that the inflammatory biomarker {gamma} fibrinogen ({gamma} Fbg) has a 6-fold lower coefficient of variability compared to other inflammatory markers such as hs-CRP. Objectives: The aims of the study were to measure {gamma} Fbg in serial blood samples from COVID-19 patients at a tertiary care medical center in order to investigate its association with clinical measures of disease progression.\n\nMethodsCOVID-19 patients at a tertiary care medical center were retrospectively enrolled between 3/16/2020 and 8/1/2020. {gamma} Fbg was measured using a commercial ELISA. Results: Our results showed that nine out of the seventeen patients with COVID-19 had extremely high levels of {gamma} Fbg. {gamma} Fbg levels were significantly associated with the need for ECMO and with mortality.\n\nConclusionsWe found that COVID-19 patients can develop extraordinarily high levels of {gamma} Fbg. The previous highest {gamma} Fbg level that we are aware of was 80.3 mg/dL found in a study of 10,601 participants in the ARIC study. These results have several important clinical implications. {gamma} Fbg contains a high affinity binding site for thrombin that binds to anion-binding exosite II on thrombin and protects it from inactivation by heparin. High levels of {gamma} Fbg therefore provide a reservoir of heparin-resistant clot-bound thrombin when the {gamma} Fbg is clotted. These findings have potential implications regarding prophylactic anticoagulation of COVID-19 patients and suggest that heparin prophylaxis may be less effective than using other anticoagulants, particularly direct thrombin inhibitors.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.20.22269618",
+    "rel_abs": "Nasopharyngeal swabs are the most used in sample collecting for covid-19 tests in SARS-CoV-2 molecular diagnosis. However, this sampling method presents some disadvantages, since, in addition to being dependent on imported materials, it is invasive, causes discomfort in patients, and, presents the risk of contamination for the medical collection team. This study aimed at validating saliva samples to obtain viral RNA to be used in the molecular diagnostic test for SARS-CoV-2 using the RT-qPCR technique. Results presented 93,44% concordance in in comparison to nasopharyngeal swabs sampling. Therefore, saliva samples used in SARS-CoV-2 RT-qPCR detection tests presented consistent results.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "David Henry Farrell",
-        "author_inst": "Oregon Health & Science University"
+        "author_name": "Natalia V R da Silva",
+        "author_inst": "Laboratory of Molecular Diagnosis, Federal University of Vicosa, campus Rio Paranaiba."
       },
       {
-        "author_name": "Matthew Hudkins",
-        "author_inst": "OHSU"
+        "author_name": "Samyra S N Pereira",
+        "author_inst": "Laboratory of Molecular Diagnosis, Federal University of Vicosa, campus Rio Paranaiba"
       },
       {
-        "author_name": "Heather Hamilton",
-        "author_inst": "OHSU"
+        "author_name": "Karine F Kavalco",
+        "author_inst": "Laboratory of Molecular Diagnosis, Federal University of Vicosa, campus Rio Paranaiba"
       },
       {
-        "author_name": "Samantha J Underwood",
-        "author_inst": "OHSU"
+        "author_name": "Fabiano B Menegidio",
+        "author_inst": "University of Mogi das Cruzes"
       },
       {
-        "author_name": "Elizabeth N Dewey",
-        "author_inst": "OHSU"
+        "author_name": "Luanda Medeiros-Santana",
+        "author_inst": "Laboratory of Molecular Diagnosis, Federal University of Vicosa, campus Rio Paranaiba"
       },
       {
-        "author_name": "Diana E Kazmierczak",
-        "author_inst": "OHSU"
-      },
-      {
-        "author_name": "Steven C Kazmierczak",
-        "author_inst": "OHSU"
-      },
-      {
-        "author_name": "William B Messer",
-        "author_inst": "OHSU"
-      },
-      {
-        "author_name": "Akram Khan",
-        "author_inst": "OHSU"
+        "author_name": "Liliane E Visotto",
+        "author_inst": "Laboratory of Molecular Diagnosis, Federal University of Vicosa, campus Rio Paranaiba"
       },
       {
-        "author_name": "Martin A Schreiber",
-        "author_inst": "OHSU"
+        "author_name": "Rubens Pasa",
+        "author_inst": "Laboratory of Molecular Diagnosis, Federal University of Vicosa, campus Rio Paranaiba"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -386427,67 +388134,83 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2022.01.17.476644",
-    "rel_title": "Nirmatrelvir, an orally active Mpro inhibitor, is a potent inhibitor of SARS-CoV-2 Variants of Concern",
+    "rel_doi": "10.1101/2022.01.17.22269283",
+    "rel_title": "ELF5 is a respiratory epithelial cell-specific risk gene for severe COVID-19",
     "rel_date": "2022-01-19",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.17.476644",
-    "rel_abs": "New variants of SARS-CoV-2 with potential for enhanced transmission, replication, and immune evasion capabilities continue to emerge causing reduced vaccine efficacy and/or treatment failure. As of January 2021, the WHO has defined five  variants of concern (VOC): B.1.1.7 (Alpha, ), B.1.351 (Beta, {beta}), P.1 (Gamma, {gamma}), B.1.617.2 (Delta, {delta}), and B.1.1.529 (Omicron, o). To provide a therapeutic option for the treatment of COVID-19 and variants, Nirmatrelvir, the antiviral component of PAXLOVID, an oral outpatient treatment recently authorized for conditional or emergency use treatment of COVID-19, was developed to inhibit SARS-CoV-2 replication. Nirmatrelvir (PF-07321332) is a specific inhibitor of coronavirus main protease (Mpro, also referred to as 3CLpro), with potent antiviral activity against several human coronaviruses, including SARS-CoV-2, SARS-CoV, and MERS (Owen et al, Science 2021. doi: 10.1126/science.abl4784). Here, we evaluated PF-07321332 against the five SARS-CoV-2 VOC (, {beta}, {gamma}, {delta},, o) and two Variants of Interest or VOI, C.37 ({lambda}) and B.1.621 (), using qRT-PCR in VeroE6 cells lacking the P-glycoprotein (Pgp) multidrug transporter gene (VeroE6 P-gp knockout cells). Nirmatrelvir potently inhibited USA-WA1/2020 strain, and , {beta}, {gamma}, {lambda}, {delta}, , and o variants in VeroE6 P-gp knockout cells with mean EC50 values 38.0 nM, 41.0 nM, 127.2 nM, 24.9 nM, 21.2 nM, 15.9 nM, 25.7 nM and 16.2 nM, respectively. Sequence analysis of the Mpro encoded by the variants showed ~100% identity of active site amino acid sequences, reflecting the essential role of Mpro during viral replication leading to ability of Nirmatrelvir to exhibit potent activity across all the variants.",
-    "rel_num_authors": 12,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269283",
+    "rel_abs": "Despite two years of intense global research activity, host genetic factors that predispose to a poorer prognosis and severe course of COVID-19 infection remain poorly understood. Here, we identified eight candidate protein mediators of COVID-19 outcomes by establishing a shared genetic architecture at protein-coding loci using large-scale human genetic studies. The transcription factor ELF5 (ELF5) showed robust and directionally consistent associations across different outcome definitions, including a >4-fold higher risk (odds ratio: 4.85; 95%-CI: 2.65-8.89; p-value<3.1x10-7) for severe COVID-19 per 1 s.d. higher genetically predicted plasma ELF5. We show that ELF5 is specifically expressed in epithelial cells of the respiratory system, such as secretory and alveolar type 2 cells, using single-cell RNA sequencing and immunohistochemistry. These cells are also likely targets of SARS-CoV-2 by colocalisation with key host factors, including ACE2 and TMPRSS2. We also observed a 25% reduced risk of severe COVID-19 per 1 s.d. higher genetically predicted plasma G-CSF, a finding corroborated by a clinical trial of recombinant human G-CSF in COVID-19 patients with lymphopenia reporting a lower number of patients developing critical illness and death. In summary, large-scale human genetic studies together with gene expression at single-cell resolution highlight ELF5 as a novel risk gene for COVID-19 prognosis, supporting a role of epithelial cells of the respiratory system in the adverse host response to SARS-CoV-2.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Devendra K. Rai",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA"
+        "author_name": "Maik Pietzner",
+        "author_inst": "Computational Medicine, Berlin Institute of Health (BIH) at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"
       },
       {
-        "author_name": "Irina Yurgelonis",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA"
+        "author_name": "Robert Lorenz Chua",
+        "author_inst": "Center for Digital Health, Berlin Institute of Health (BIH) at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"
       },
       {
-        "author_name": "Patricia McMonagle",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA"
+        "author_name": "Eleanor Wheeler",
+        "author_inst": "MRC Epidemiology Unit, University of Cambridge, Cambridge, UK"
       },
       {
-        "author_name": "Hussin A. Rothan",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA."
+        "author_name": "Katharina Jechow",
+        "author_inst": "Center for Digital Health, Berlin Institute of Health (BIH) at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"
       },
       {
-        "author_name": "Li Hao",
-        "author_inst": "Pfizer Worldwide Researhc, Development & Medical, Pearl River, NY 10965, USA."
+        "author_name": "Helena Radbruch",
+        "author_inst": "Department of Neuropathology, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin und Humboldt-Universit\u00e4t zu Berlin, Berlin, Ger"
       },
       {
-        "author_name": "Alexey Gribenko",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA."
+        "author_name": "Saskia Trump",
+        "author_inst": "Molecular Epidemiology Unit, Charit\u00e9 - Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin, Humboldt-Universit\u00e4t zu Berlin and Berlin Insti"
       },
       {
-        "author_name": "Elizabeth Titova",
-        "author_inst": "Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, NJ 07110, USA"
+        "author_name": "Bettina Heidecker",
+        "author_inst": "Department of Cardiology, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin und Humboldt-Universit\u00e4t zu Berlin, Berlin, Germany"
       },
       {
-        "author_name": "Barry Kreiswirth",
-        "author_inst": "Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, NJ 07110, USA"
+        "author_name": "Frank Heppner",
+        "author_inst": "Department of Neuropathology, Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin und Humboldt-Universit\u00e4t zu Berlin, Berlin, Ger"
       },
       {
-        "author_name": "Kris M. White",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA,  and Global Health Emerging Pathogens Institute, Icahn School of Med"
+        "author_name": "Roland Eils",
+        "author_inst": "Center for Digital Health, Berlin Institute of Health (BIH) at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"
       },
       {
-        "author_name": "Yuao Zhu",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA"
+        "author_name": "Marcus Mall",
+        "author_inst": "Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Charit\u00e9-Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t B"
       },
       {
-        "author_name": "Annaliesa S. Anderson",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA"
+        "author_name": "Leif Erik Sander",
+        "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charit\u00e9 - Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin, Humboldt-Univers"
+      },
+      {
+        "author_name": "Irina Lehmann",
+        "author_inst": "Molecular Epidemiology Unit, Charit\u00e9 - Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin, Humboldt-Universit\u00e4t zu Berlin and Berlin Insti"
+      },
+      {
+        "author_name": "S\u00f6ren Lukassen",
+        "author_inst": "Center for Digital Health, Berlin Institute of Health (BIH) at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"
+      },
+      {
+        "author_name": "Nicholas J. Wareham",
+        "author_inst": "MRC Epidemiology Unit, University of Cambridge, Cambridge, UK"
+      },
+      {
+        "author_name": "Christian Conrad",
+        "author_inst": "Center for Digital Health, Berlin Institute of Health (BIH) at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"
       },
       {
-        "author_name": "Rhonda D. Cardin",
-        "author_inst": "Pfizer Worldwide Research, Development & Medical, Pearl River, NY 10965, USA"
+        "author_name": "Claudia Langenberg",
+        "author_inst": "Computational Medicine, Berlin Institute of Health (BIH) at Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "genetic and genomic medicine"
   },
   {
     "rel_doi": "10.1101/2022.01.19.22269529",
@@ -388328,79 +390051,43 @@
     "category": "scientific communication and education"
   },
   {
-    "rel_doi": "10.1101/2022.01.14.22269074",
-    "rel_title": "Evaluation of an emergency safe supply drug and managed alcohol program in COVID-19 isolation hotel shelters for people experiencing homelessness",
+    "rel_doi": "10.1101/2022.01.16.22269377",
+    "rel_title": "The Impact of State Paid Sick Leave Policies on Longitudinal Weekday Workplace Mobility During the COVID-19 Pandemic",
     "rel_date": "2022-01-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.14.22269074",
-    "rel_abs": "BackgroundDuring a COVID-19 outbreak in the congregate shelter system in Halifax, Nova Scotia, Canada, a multidisciplinary health care team provided an emergency \"safe supply\" of pharmaceutical-grade medications and beverage-grade alcohol to facilitate isolation in COVID-19 hotel shelters for residents who are dependent on these substances. We aimed to evaluate (a) substances and dosages provided, and (b) effectiveness and safety of the program.\n\nMethodsWe retrospectively reviewed medical records of all COVID-19 isolation hotel shelter residents during May 2021. We extracted data on medication and alcohol dosages provided each day. The primary outcome was residents prematurely leaving isolation against public health orders. Adverse events included (a) overdose; (b) intoxication; and (c) diversion, selling, or sharing of medications or alcohol.\n\nResultsOver 25 days, 77 isolation hotel residents were assessed (mean age 42 {+/-} 14 years; 24% women). Sixty-two (81%) residents were provided medications, alcohol, or cigarettes. Seventeen residents (22%) received opioid agonist treatment medications (methadone, buprenorphine, or slow-release oral morphine) and 27 (35%) received hydromorphone tablets. Thirty-one (40%) residents received stimulant tablets with methylphenidate (27; 35%), dextroamphetamine (8; 10%), or lisdexamfetamine (2; 3%). Six residents (8%) received benzodiazepines. Forty-two (55%) residents received alcohol, including 41 (53%) with strong beer, three (3%) with wine, and one (1%) with hard liquor. Over 14 days in isolation, mean daily dosages increased of hydromorphone (45 {+/-} 32 to 57 {+/-} 42mg), methylphenidate (51 {+/-} 28 to 77 {+/-} 37mg), dextroamphetamine (33 {+/-} 16 to 46 {+/-} 13mg), and alcohol (12.3 {+/-} 7.6 to 13.0 {+/-} 6.9 standard drinks). Six residents (8%) left isolation prematurely, but four of those residents returned. Over 1,059 person-days in isolation, there were zero overdoses. Documented concerns regarding intoxication occurred six times (0.005 events/person-day) and medication diversion or sharing three times (0.003 events/person-day).\n\nConclusionsAn emergency safe supply and managed alcohol program, paired with housing, was associated with low rates of adverse events and high rates of successful completion of the 14-day isolation period in COVID-19 isolation hotel shelters. This supports the effectiveness and safety of emergency safe supply prescribing and managed alcohol in this setting.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.16.22269377",
+    "rel_abs": "ObjectivesTo evaluate whether the Families First Coronavirus Response Act (FFCRA) modified the association between pre-existing state paid sick leave (PSL) and weekday workplace mobility between February 15 and July 7, 2020.\n\nMethodsThe 50 US states and Washington, D.C. were divided into exposure groups based on the presence or absence of pre-existing state PSL policies. Derived from Google COVID-19 Community Mobility Reports, the outcome was measured as the daily percent change in weekday workplace mobility. Mixed-effects, interrupted time series regression was performed to evaluate weekday workplace mobility after the implementation of the FFCRA on April 1st, 2020.\n\nResultsStates with pre-existing PSL policies exhibited a greater drop in mobility following the passage of the FFCRA ({beta}=-8.86,95%CI:-11.6,-6.10,P< 001). This remained significant after adjusting for state-level health, economic, and sociodemographic indicators ({beta}=-3.13,95%CI:-5.92,-0.34,P=.039).\n\nConclusionsPre-existing PSL policies contributed to a significant decline in weekday workplace mobility after the FFCRA, which may have influenced local health outcomes.\n\nPolicy implicationsThe presence of pre-existing state policies may differentially influence the impact of federal legislation enacted during emergencies.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Thomas D Brothers",
-        "author_inst": "Dalhousie University; University College London"
-      },
-      {
-        "author_name": "Malcolm Leaman",
-        "author_inst": "North End Community Health Centre"
-      },
-      {
-        "author_name": "Matthew Bonn",
-        "author_inst": "Canadian Association of People who Use Drugs (CAPUD)"
-      },
-      {
-        "author_name": "Dan Lewer",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Jacqueline Atkinson",
-        "author_inst": "Mobile Outreach Street Health (MOSH), North End Community Health Centre"
-      },
-      {
-        "author_name": "John Fraser",
-        "author_inst": "North End Community Health Centre"
-      },
-      {
-        "author_name": "Amy Gillis",
-        "author_inst": "Dalhousie University"
-      },
-      {
-        "author_name": "Michael Gniewek",
-        "author_inst": "Dalhousie University; Direction 180"
-      },
-      {
-        "author_name": "Leisha Hawker",
-        "author_inst": "North End Community Health Centre; Dalhousie University"
-      },
-      {
-        "author_name": "Heather Hayman",
-        "author_inst": "Mobile Outreach Street Health (MOSH), North End Community Health Centre"
+        "author_name": "Catherine C. Pollack",
+        "author_inst": "Geisel School of Medicine at Dartmouth"
       },
       {
-        "author_name": "Peter Jorna",
-        "author_inst": "Nova Pharmacy"
+        "author_name": "Akshay Deverakonda",
+        "author_inst": "COVID-19 Dispersed Volunteer Research Network"
       },
       {
-        "author_name": "David Martell",
-        "author_inst": "Dalhousie University; Direction 180"
+        "author_name": "Fahim Hassan",
+        "author_inst": "University of Alberta"
       },
       {
-        "author_name": "Tiffany O'Donnell",
-        "author_inst": "Mobile Outreach Street Health (MOSH), North End Community Health Centre; Dalhousie University"
+        "author_name": "Syed Haque",
+        "author_inst": "Northeastern University"
       },
       {
-        "author_name": "Helen Rivers-Bowerman",
-        "author_inst": "Mobile Outreach Street Health (MOSH), North End Community Health Centre"
+        "author_name": "Angel N. Desai",
+        "author_inst": "University of California - Davis"
       },
       {
-        "author_name": "Leah Genge",
-        "author_inst": "Mobile Outreach Street Health (MOSH), North End Community Health Centre; Dalhousie University; Direction 180"
+        "author_name": "Maimuna Majumder",
+        "author_inst": "Boston Children's Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "addiction medicine"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2022.01.17.22269201",
@@ -390046,31 +391733,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2022.01.11.22269069",
-    "rel_title": "Hydroxychloroquine/Chloroquine in COVID-19 With Focus on Hospitalized Patients - A Systematic Review",
+    "rel_doi": "10.1101/2022.01.13.476204",
+    "rel_title": "Covariance predicts conserved protein residue interactions important to the emergence and continued evolution of SARS-CoV-2 as a human pathogen",
     "rel_date": "2022-01-14",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.11.22269069",
-    "rel_abs": "BackgroundIn the beginning of the COVID-19 pandemic, many hospitalized patients received empiric hydroxychloroquine/chloroquine (HC/CQ). Although some retrospective-observational trials suggested potential benefit, all subsequent randomized clinical trials (RCTs) failed to show benefit and use generally ceased. Herein, we summarize key studies that clinicians advising patients on HC/CQs efficacy:safety calculus in hospitalized COVID-19 patients would want to know about in a practical one-stop-shopping source.\n\nMethodsPubmed and Google were searched on November 4, 2021. Search words included: COVID-19, hydroxychloroquine, chloroquine, in vitro, animal studies, clinical trials, and meta-analyses. Studies were assessed for import and included if considered impactful for benefit:risk assessment.\n\nResultsThese searches led to inclusion of 12 in vitro and animal reports; 12 retrospective-observational trials, 19 interventional clinical trials (17 RCTs, 1 single-arm, 1 controlled but unblinded), and 51 meta-analyses in hospitalized patients.\n\nInconsistent efficacy was seen in vitro and in animal studies for coronaviruses and nil in SARS-CoV-2 animal models specifically. Most retrospective-observational studies in hospitalized COVID-19 patients found no efficacy; QT prolongation and increased adverse events and mortality were reported in some. All RCTs and almost all meta-analyses provided robust data showing no benefit in overall populations and subgroups, yet concerning safety issues in many.\n\nConclusionsHC/CQ have inconsistent anti-coronavirus efficacy in vitro and in animal models, and no convincing efficacy yet substantial safety issues in the overwhelming majority of retrospective-observational trials, RCTs, and meta-analyses in hospitalized COVID-19 patients. HC/CQ should not be prescribed for hospitalized COVID-19 patients outside of clinical trials.\n\nKey Summary PointsPreclinical hydroxychloroquine/chloroquine in vitro studies found inconsistent activity against coronaviruses including SARS-CoV-2.\n\nPreclinical hydroxychloroquine/chloroquine animals studies found inconsistent efficacy for coronaviruses in general and none for SARS-CoV-2.\n\nThe overhwelming majority of RCTs and retrospective-observational trials found no benefit for hydroxychloroquine/chloroquine in hospitalized COVID-19 patients, and many found concerning safety signals.\n\nThe majority of RCTs and retrospective-observational trials found no benefit for hydroxychloroquine/chloroquine in COVID-19 outpatients or for pre- or post-exposure prophylaxis, and some found concerning safety signals.\n\nThe overwhelming majority of meta-analyses found no benefit for hydroxychloroquine/chloroquine in COVID-19 inpatients, outpatients, or for prophylaxis, and many found concerning safety signals.",
-    "rel_num_authors": 3,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.13.476204",
+    "rel_abs": "SARS-CoV-2 is one of three recognized coronaviruses (CoVs) that have caused epidemics or pandemics in the 21st century and that likely emerged from animal reservoirs. Differences in nucleotide and protein sequence composition within related {beta}-coronaviruses are often used to better understand CoV evolution, host adaptation, and their emergence as human pathogens. Here we report the comprehensive analysis of amino acid residue changes that have occurred in lineage B {beta}-coronaviruses that show covariance with each other. This analysis revealed patterns of covariance within conserved viral proteins that potentially define conserved interactions within and between core proteins encoded by SARS-CoV-2 related {beta}-coranaviruses. We identified not only individual pairs but also networks of amino acid residues that exhibited statistically high frequencies of covariance with each other using an independent pair model followed by a tandem model approach. Using 149 different CoV genomes that vary in their relatedness, we identified networks of unique combinations of alleles that can be incrementally traced genome by genome within different phylogenic lineages. Remarkably, covariant residues and their respective regions most abundantly represented are implicated in the emergence of SARS-CoV-2 are also enriched in dominant SARS-CoV-2 variants.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Daniel Freilich",
-        "author_inst": "Bassett Medical Center"
-      },
-      {
-        "author_name": "Jennifer Victory",
-        "author_inst": "Bassett Research Institute"
+        "author_name": "William P Robins",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Anne Gadomski",
-        "author_inst": "Bassett Research Institute"
+        "author_name": "John J Mekalanos",
+        "author_inst": "Harvard Medical School"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.01.13.476223",
@@ -392192,55 +393875,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.01.12.22269048",
-    "rel_title": "A unique dexamethasone-dependent gene expression profile in the lungs of COVID-19 patients",
+    "rel_doi": "10.1101/2022.01.13.22269236",
+    "rel_title": "Estimating the relative proportions of SARS-CoV-2 strains from wastewater samples",
     "rel_date": "2022-01-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.12.22269048",
-    "rel_abs": "Local immunopathogenesis of COVID-19 acute respiratory distress syndrome (CARDS) and the effects of systemic dexamethasone (DXM) treatment on pulmonary immunity in COVID-19 remain insufficiently understood. To provide further insight into insight into immune regulatory mechanisms in the lungs of CARDS (with and without DXM treatment) and critically ill non-COVID-19 patients (without DXM treatment), transcriptomic RNA-seq analysis of bronchoalveolar lavage fluid (BALF) was performed in these patients. Functional analysis was performed using gene ontology and a blood transcription module, and gene expression of select pro-inflammatory cytokines, interferon-stimulated genes (ISGs) and auto-IFN antibodies were assessed. We found 550 and 2173 differentially expressed genes in patients with non-DXM-CARDS and DXM-CARDS, respectively. DXM-CARDS was characterized by upregulation of genes related to pulmonary innate and adaptive immunity, notably B-cell and complement pathway activation, antigen presentation, phagocytosis and FC-gamma receptor signalling. Pro-inflammatory genes were not differentially expressed in CARDS vs. non-COVID-19, nor did they differ according to DXM. Most ISGs were specifically upregulated in CARDS, particularly in non-DXM-CARDS. Auto-IFN autoantibodies were detectable in BALF of some CARDS patients. In conclusion, DXM treatment was not associated with regulation of pro-inflammatory pathways in CARDS but with regulation of other specific local innate and adaptive immune responses.\n\nsummaryThis study identifies differentially expressed genes in bronchoalveolar fluid of COVID-19 acute respiratory distress patients with a distinct RNA expression profile of those treated with dexamethasone. These results challenge the concept of a COVID-19 specific cytokine storm.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.13.22269236",
+    "rel_abs": "Wastewater surveillance has become essential for monitoring the spread of SARS-CoV-2. The quantification of SARS-CoV-2 RNA in wastewater correlates with the Covid-19 caseload in a community. However, estimating the proportions of different SARS-CoV-2 strains has remained technically difficult. We present a method for estimating the relative proportions of SARS-CoV-2 strains from wastewater samples. The method uses an initial step to remove unlikely strains, imputation of missing nucleotides using the global SARS-CoV-2 phylogeny, and an Expectation-Maximization (EM) algorithm for obtaining maximum likelihood estimates of the proportions of different strains in a sample. Using simulations with a reference database of >3 million SARS-CoV-2 genomes, we show that the estimated proportions accurately reflect the true proportions given sufficiently high sequencing depth and that the phylogenetic imputation is highly accurate and substantially improves the reference database.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Ulrik Fahnoe",
-        "author_inst": "Copenhagen University Hospital - Amager and Hvidovre; Copenhagen University"
-      },
-      {
-        "author_name": "Andreas Ronit",
-        "author_inst": "Copenhagen University Hospital - Amager and Hvidovre"
-      },
-      {
-        "author_name": "Ronan M.G. Berg",
-        "author_inst": "Copenhagen University Hospital - Rigshospitalet; Copenhagen University"
-      },
-      {
-        "author_name": "Sofie E.G. Joergensen",
-        "author_inst": "Aarhus University Hospital; Aarhus University"
-      },
-      {
-        "author_name": "Trine H. Mogensen",
-        "author_inst": "Aarhus University Hospital; Aarhus University"
-      },
-      {
-        "author_name": "Alexander P. Underwood",
-        "author_inst": "Copenhagen University Hospital - Amager and Hvidovre"
+        "author_name": "Lenore Pipes",
+        "author_inst": "University of California, Berkeley"
       },
       {
-        "author_name": "Troels K.H. Scheel",
-        "author_inst": "The Rockefeller University; University of Copenahagen"
+        "author_name": "Zihao Chen",
+        "author_inst": "Peking University"
       },
       {
-        "author_name": "Jens Bukh",
-        "author_inst": "Copenhagen University Hospital - Amager and Hvidovre; Copenhagen University"
+        "author_name": "Svetlana Afanaseva",
+        "author_inst": "University of California-Berkeley"
       },
       {
-        "author_name": "Ronni R. Plovsing",
-        "author_inst": "Copenhagen University Hospital - Amager and Hvidovre; Copenhagen University"
+        "author_name": "Rasmus Nielsen",
+        "author_inst": "University of California, Berkeley"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.01.12.22269157",
@@ -394258,135 +395921,71 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.01.11.475947",
-    "rel_title": "SARS-CoV-2 drives NLRP3 inflammasome activation in human microglia through spike-ACE2 receptor interaction",
+    "rel_doi": "10.1101/2022.01.11.475327",
+    "rel_title": "Systemic infection of SARS-CoV-2 in free ranging Leopard (Panthera pardus fusca) in India",
     "rel_date": "2022-01-12",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.11.475947",
-    "rel_abs": "Coronavirus disease-2019 (COVID-19) is primarily a respiratory disease, however, an increasing number of reports indicate that SARS-CoV-2 infection can also cause severe neurological manifestations, including precipitating cases of probable Parkinsons disease. As microglial NLRP3 inflammasome activation is a major driver of neurodegeneration, here we interrogated whether SARS-CoV-2 can promote microglial NLRP3 inflammasome activation utilising a model of human monocyte-derived microglia. We identified that SARS-CoV-2 isolates can bind and enter microglia, triggering inflammasome activation in the absence of viral replication. Mechanistically, microglial NLRP3 could be both primed and activated with SARS-CoV-2 spike glycoprotein in a NF-{kappa}B and ACE2-dependent manner. Notably, virus- and spike protein-mediated inflammasome activation in microglia was significantly enhanced in the presence of -synuclein fibrils, which was entirely ablated by NLRP3-inhibition. These results support a possible mechanism of microglia activation by SARS-CoV-2, which could explain the increased vulnerability to developing neurological symptoms akin to Parkinsons disease in certain COVID-19 infected individuals, and a potential therapeutic avenue for intervention.\n\nSIGNIFICANCE STATEMENTSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) principally affects the lungs, however there is evidence that the virus can also reach the brain and lead to chronic neurological symptoms. In this study, we examined the interaction SARS-CoV-2 with brain immune cells, by using an ex-vivo model of human monocyte-derived microglia. We identified robust activation of the innate immune sensor complex, NLRP3 inflammasome, in cells exposed to SARS-CoV-2. This was dependent on spike protein-ACE2 receptor interaction and was potentiated in the presence of -synuclein. We therefore identify a possible mechanism for SARS-CoV-2 and increased vulnerability to developing neurological dysfunction. These findings support a potential therapeutic avenue for treatment of SARS-CoV-2 driven neurological manifestations, through use of NLRP3 inflammasome or ACE2 inhibitors.",
-    "rel_num_authors": 29,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.11.475327",
+    "rel_abs": "We report patho-morphological and virological characterization of SARS-CoV-2 in naturally infected, free ranging Indian Leopard (Panthera pardus fusca). Whole genome sequence analysis confirmed infection of Delta variant of SARS-CoV-2, possibly spill over from humans, but the case was detected when infection level had dropped significantly in human population. This report underlines the need for intensive screening of wild animals for keeping track of the virus evolution and development of carrier status of SARS-CoV-2 among wildlife species.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Eduardo A Albornoz",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
-      },
-      {
-        "author_name": "Alberto A Amarilla",
-        "author_inst": "School of Chemistry and molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Naphak Modhiran",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Sandra Parker",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
-      },
-      {
-        "author_name": "Xaria X Li",
-        "author_inst": "School of biomedical sciences, University of Queensland"
-      },
-      {
-        "author_name": "Danushka K Wijesundara",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Adriana Pliego Zamora",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
+        "author_name": "Sonalika Mahajan",
+        "author_inst": "ICAR Indian Veterinary Research Institute"
       },
       {
-        "author_name": "Christopher LD McMillan",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
+        "author_name": "Karikalan Mathesh",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar"
       },
       {
-        "author_name": "Benjamin Liang",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Nias Y.G Peng",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Julian D.J Sng",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Fatema Tuj Saima",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
-      },
-      {
-        "author_name": "Devina Paramitha",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
+        "author_name": "Vishal Chander",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar Bareilly UP"
       },
       {
-        "author_name": "Rhys Parry",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
+        "author_name": "Abhijit M Pawde",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar Bareilly UP"
       },
       {
-        "author_name": "Michael S Avumegah",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
+        "author_name": "G Saikumar",
+        "author_inst": "ICAR Indian Veterinary Research Institute Izatnagar"
       },
       {
-        "author_name": "Ariel Isaacs",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
+        "author_name": "M Semmaran",
+        "author_inst": "Divisional Director, Social forestry, Bijnor, Uttar Pradesh 246701"
       },
       {
-        "author_name": "Martin Lo",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
+        "author_name": "P Sree lakshmi",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar Bareilly Uttar Pradesh"
       },
       {
-        "author_name": "Zaray Miranda-Chacon",
-        "author_inst": "Institute of Medicine, Faculty of Medicine, Universidad Austral de Chile"
+        "author_name": "Megha Sharma",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar Bareilly Uttar Pradesh"
       },
       {
-        "author_name": "Daniella Bradshaw",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
+        "author_name": "Sukdeb nandi",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar Bareilly Uttar Pradesh"
       },
       {
-        "author_name": "Constanza Salinas-Rebolledo",
-        "author_inst": "Institute of Medicine, Faculty of Medicine, Universidad Austral de Chile"
+        "author_name": "Karam Pal Singh",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar Bareilly Uttar Pradesh"
       },
       {
-        "author_name": "Niwanthi W Rajapakse",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
+        "author_name": "Vivek Kumar Gupta",
+        "author_inst": "ICAR-Indian Veterinary Research Institute Izatnagar Bareilly Uttar Pradesh"
       },
       {
-        "author_name": "Trent Munro",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
+        "author_name": "R. K. Singh",
+        "author_inst": "Division of Virology, Indian Veterinary Research Institute"
       },
       {
-        "author_name": "Alejandro Rojas-Fernandez",
-        "author_inst": "Institute of Medicine, Faculty of Medicine, Universidad Austral de Chile"
-      },
-      {
-        "author_name": "Paul R Young",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Katryn J Stacey",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Alexander A Khromykh",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Keith J Chappell",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Daniel Watterson",
-        "author_inst": "School of Chemistry and Molecular Biosciences, University of Queensland"
-      },
-      {
-        "author_name": "Trent M Woodruff",
-        "author_inst": "School of Biomedical Sciences, Faculty of Medicine, University of Queensland"
+        "author_name": "Gaurav Sharma",
+        "author_inst": "ICAR-Indian Veterinary Research Institute"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "neuroscience"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2022.01.11.475922",
@@ -396060,91 +397659,107 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.01.07.22268883",
-    "rel_title": "Safety and immunogenicity of the BBIBP-CorV vaccine in adolescents aged 12-17 years in Thai population, prospective cohort study.",
+    "rel_doi": "10.1101/2022.01.08.22268953",
+    "rel_title": "Anti-PEG antibodies boosted in humans by SARS-CoV-2 lipid nanoparticle mRNA vaccine",
     "rel_date": "2022-01-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.07.22268883",
-    "rel_abs": "IntroductionCOVID-19 pandemic affects all populations worldwide, including adolescents. Adolescents can develop a severe form of COVID-19, especially with comorbidity underlying. The prior studies of the mRNA COVID-19 vaccine showed excellent effectiveness in adolescents. Therefore, this study aimed to evaluate the safety and effectiveness of the BBIBP-CorV vaccine with the immunobridging approach in Thai adolescents.\n\nMethodsThis single-center, prospective cohort study compared the immunogenicity after 2 doses of the BBIBO-CorV vaccine with 21 days interval of participants aged 12-17 years with 18-30 years at Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand. The key eligible criteria were healthy or had stable pre-existing comorbidity participants, aged 12-17 years. The primary endpoint was the anti-receptor binding domain antibody concentration at 4 weeks after dose 2 of the vaccine. In addition, safety profiles were solicited adverse events within 7 days after each dose of vaccine and any adverse events through 1 month after dose 2 of the vaccine.\n\nResultsFour weeks after the second vaccination, the GMC of anti-RBD antibody in the adolescent cohort was 102.9 BAU/mL (95%CI; 91.0-116.4) and 36.9 BAU/mL (95%CI; 30.9-44.0) in the adult cohort. The GMR of the adolescent cohort was 2.79 (95%CI; 2.25-3.46, p-value; <0.0001) compared with the adult cohort which met non-inferiority criteria. The reactogenicity was slightly less reported in the adolescent cohort compared with the adult cohort. No serious adverse events were reported in both cohorts.\n\nConclusionVaccination with the BBIBP-CorV vaccine in the adolescent participants was safe and effective.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.08.22268953",
+    "rel_abs": "Humans commonly have low level antibodies to poly(ethylene) glycol (PEG) due to environmental exposure. Lipid nanoparticle (LNP) mRNA vaccines for SARS-CoV-2 contain small amounts of PEG but it is not known whether PEG antibodies are enhanced by vaccination and what their impact is on particle-immune cell interactions in human blood. We studied plasma from 130 adults receiving either the BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) mRNA vaccines, or no SARS-CoV-2 vaccine for PEG-specific antibodies. Anti-PEG IgG was commonly detected prior to vaccination and was significantly boosted a mean of 13.1-fold (range 1.0 to 70.9) following mRNA-1273 vaccination and a mean of 1.78-fold (range 0.68 to 16.6) following BNT162b2 vaccination. Anti-PEG IgM increased 68.5-fold (range 0.9 to 377.1) and 2.64-fold (0.76 to 12.84) following mRNA-1273 and BNT162b2 vaccination, respectively. The rise in PEG-specific antibodies following mRNA-1273 vaccination was associated with a significant increase in the association of clinically relevant PEGylated LNPs with blood phagocytes ex vivo. PEG antibodies did not impact the SARS-CoV-2 specific neutralizing antibody response to vaccination. However, the elevated levels of vaccine-induced anti-PEG antibodies correlated with increased systemic reactogenicity following two doses of vaccination. We conclude that PEG-specific antibodies can be boosted by LNP mRNA-vaccination and that the rise in PEG-specific antibodies is associated with systemic reactogenicity and an increase of PEG particle-leukocyte association in human blood. The longer-term clinical impact of the increase in PEG-specific antibodies induced by lipid nanoparticle mRNA-vaccines should be monitored.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Kriangkrai Tawinprai",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Yi Ju",
+        "author_inst": "RMIT University"
       },
       {
-        "author_name": "Taweegrit Siripongboonsitti",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Wen Shi Lee",
+        "author_inst": "The Peter Doherty Institute for Infection and Immunity, University of Melbourne"
       },
       {
-        "author_name": "Thachanun Porntharukchareon",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Emily H. Pilkington",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Preeda Vanichsetakul",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Hannah G. Kelly",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Saraiorn Thonginnetra",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Shiyao Li",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Krongkwan Niemsorn",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Kevin J. Selva",
+        "author_inst": "The Peter Doherty Institute for Infection and Immunity"
       },
       {
-        "author_name": "Pathariya Promsena",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Kathleen M. Wragg",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Manunya Tandhansakul",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Kanta Subbarao",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Naruporn Kasemlawan",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Thi H.O. Nguyen",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Natthanan Ruangkijpaisal",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Louise C. Rowntree",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Narin Banomyong",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Lilith F. Allen",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Nanthida Phattraprayoon",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Katherine Bond",
+        "author_inst": "Royal Melbourne Hospital"
       },
       {
-        "author_name": "Teerapat Ungtrakul",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Deborah A. Williamson",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Kasiruck Wittayasak",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Nghia P. Truong",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Nawarat Thonwirak",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Magdalena Plebanski",
+        "author_inst": "RMIT University"
       },
       {
-        "author_name": "Kamonwan Soonklang",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Katherine Kedzierska",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne"
       },
       {
-        "author_name": "Gaidganok Sornsamdang",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Siddhartha Mahanty",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne"
       },
       {
-        "author_name": "Nithi Mahanonda",
-        "author_inst": "Chulabhorn Royal Academy"
+        "author_name": "Amy W. Chung",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Frank Caruso",
+        "author_inst": "The University of Melbourne"
+      },
+      {
+        "author_name": "Adam K. Wheatley",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Jennifer A Juno",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Stephen J. Kent",
+        "author_inst": "University of Melbourne"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "allergy and immunology"
   },
   {
     "rel_doi": "10.1101/2022.01.08.22268901",
@@ -397801,113 +399416,61 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.01.07.475248",
-    "rel_title": "Fusogenicity and neutralization sensitivity of the SARS-CoV-2 Delta sublineage AY.4.2",
+    "rel_doi": "10.1101/2022.01.10.475620",
+    "rel_title": "Strong SARS-CoV-2 N-specific CD8+ T immunity induced by engineered extracellular vesicles associates with protection from lethal infection in mice.",
     "rel_date": "2022-01-10",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.07.475248",
-    "rel_abs": "SARS-CoV-2 lineages are continuously evolving. As of December 2021, the AY.4.2 Delta sub-lineage represented 20 % of sequenced strains in UK and has been detected in dozens of countries. It has since then been supplanted by the Omicron variant. AY.4.2 displays three additional mutations (T95I, Y145H and A222V) in the N-terminal domain (NTD) of the spike when compared to the original Delta variant (B.1.617.2) and remains poorly characterized. Here, we analyzed the fusogenicity of the AY.4.2 spike and the sensitivity of an authentic AY.4.2 isolate to neutralizing antibodies. The AY.4.2 spike exhibited similar fusogenicity and binding to ACE2 than Delta. The sensitivity of infectious AY.4.2 to a panel of monoclonal neutralizing antibodies was similar to Delta, except for the anti-RBD Imdevimab, which showed incomplete neutralization. Sensitivity of AY.4.2 to sera from individuals having received two or three doses of Pfizer or two doses of AstraZeneca vaccines was reduced by 1.7 to 2.1 fold, when compared to Delta. Our results suggest that mutations in the NTD remotely impair the efficacy of anti-RBD antibodies. The temporary spread of AY.4.2 was not associated with major changes in spike function but rather to a partially reduced neutralization sensitivity.",
-    "rel_num_authors": 24,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.10.475620",
+    "rel_abs": "SARS-CoV-2-specific CD8+ T cell immunity is expected to counteract viral variants in both efficient and durable ways. We recently described a way to induce a potent SARS-CoV-2 CD8+ T immune response through the generation of engineered extracellular vesicles (EVs) emerging from muscle cells. This method relies on intramuscular injection of DNA vectors expressing different SARS-CoV-2 antigens fused at their N-terminus with Nefmut protein, i.e., a very efficient EV-anchoring protein. However, quality, tissue distribution, and efficacy of these SARS-CoV-2-specific CD8+ T cells remained uninvestigated. To fill the gaps, antigen-specific CD8+ T lymphocytes induced by the immunization through the Nefmut-based method were characterized in terms of their polyfunctionality and localization at lung airways, i.e., the primary targets of SARS-CoV-2 infection. We found that injection of vectors expressing Nefmut/S1 and Nefmut/N generated polyfunctional CD8+ T lymphocytes in both spleens and bronchoalveolar lavage fluids (BALFs). When immunized mice were infected with 4.4 lethal doses 50% of SARS-CoV-2, all S1-immunized mice succumbed, whereas those developing the highest percentages of N-specific CD8+ T lymphocytes resisted the lethal challenge. We also provide evidence that the N-specific immunization coupled with the development of antigen-specific CD8+ T-resident memory cells in lungs, supporting the idea that the Nefmut- based immunization can confer a long-lasting, lung-specific immune memory. In view of the limitations of current anti-SARS-CoV-2 vaccines in terms of antibody waning and efficiency against variants, our CD8+ T cell-based platform could be considered for a new combination prophylactic strategy.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Nell Saunders",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Delphine Planas",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "William Henry Bolland",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Christophe Rodriguez",
-        "author_inst": "AP-HP"
-      },
-      {
-        "author_name": "Slim Fourati",
-        "author_inst": "AP-HP"
-      },
-      {
-        "author_name": "Julian Buchrieser",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Cyril Planchais",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Matthieu Prot",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Isabelle Staropoli",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Florence Guivel-Benhassine",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Francoise Porrot",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "David Veyer",
-        "author_inst": "AP-HP"
-      },
-      {
-        "author_name": "Helene Pere",
-        "author_inst": "AP-HP"
-      },
-      {
-        "author_name": "Nicolas Robillard",
-        "author_inst": "AP-HP"
+        "author_name": "Flavia Ferrantelli",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Madelina Saliba",
-        "author_inst": "AP-HP"
+        "author_name": "Chiara Chiozzini",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Artem Baidaliuk",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Francesco Manfredi",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Aymeric Seve",
-        "author_inst": "CHR Orleans"
+        "author_name": "Patrizia Leone",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Laurent Hocqueloux",
-        "author_inst": "CHR Orleans"
+        "author_name": "Massimo Spada",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Thierry Prazuck",
-        "author_inst": "CHR Orleans"
+        "author_name": "Antonio DiVirgilio",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Hugo Mouquet",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Andrea Giovannelli",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Etienne Simon-Loriere",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Massimo Sanchez",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Timothee Bruel",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Andrea Cara",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Jean-Michel Pawlotsky",
-        "author_inst": "AP-HP"
+        "author_name": "Zuleika Michelini",
+        "author_inst": "Istituto Superiore di Sanita"
       },
       {
-        "author_name": "Olivier Schwartz",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Maurizio Federico",
+        "author_inst": "Istituto Superiore di Sanita"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
     "category": "microbiology"
   },
@@ -399847,31 +401410,155 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2022.01.06.475246",
-    "rel_title": "Climate Surveys of Biomedical PhD Students and Training Faculty Members in the Time of Covid",
-    "rel_date": "2022-01-07",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.06.475246",
-    "rel_abs": "In July 2020, four months into the disruption of normal life caused by the Covid-19 pandemic, we assessed the institutional climate within the School of Medicine. Voluntary surveys were completed by 135 graduate students in 11 PhD-granting programs and by 83 members of the graduate training faculty. Several themes emerged. PhD students work hard, but the number of hours spent on research-related activities has declined during the pandemic. The students are worried about the pandemics impact on their research productivity, consequent delays in their graduation, and diminished future job prospects. Many late stage PhD students feel they do not have adequate time or resources to plan for their future careers. Symptoms of anxiety and/or depression are prevalent in 51% of the students, based on answers to standardized questions. Most students report they have strong mentoring relationships with their faculty advisors and like their programs, but they identify to a lesser extent with the medical school as a whole. Faculty think highly of their graduate students and are also worried about the pandemics impact upon productivity and the welfare of students. Students are interested in access to an Ombuds office, which is currently being organized by the medical school. Moving forward, the school needs to address issues of bias, faculty diversity, support for mentor training, professional development, and the imposter syndrome. We must also work to create a climate in which many more graduate students feel that they are valued members of the academic medicine community.",
-    "rel_num_authors": 3,
+    "rel_doi": "10.1101/2022.01.05.21268323",
+    "rel_title": "Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey",
+    "rel_date": "2022-01-06",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.05.21268323",
+    "rel_abs": "The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non- SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly in the current phase of the pandemic with routine RT-PCR testing now ended in the community.",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Deepti Ramadoss",
-        "author_inst": "University of Pittsburgh"
+        "author_name": "Katrina A Lythgoe",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Meghan Campbell McCord",
-        "author_inst": "University of Pittsburgh"
+        "author_name": "Tanya Golubchik",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Johm P Horn",
-        "author_inst": "University of Pittsburgh"
+        "author_name": "Matthew Hall",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Thomas House",
+        "author_inst": "University of Manchester"
+      },
+      {
+        "author_name": "Roberto Cahuantzi",
+        "author_inst": "University of Manchester"
+      },
+      {
+        "author_name": "George MacIntyre-Cockett",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Helen Fryer",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Laura Thomson",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Anel Nurtay",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Mahan Ghafari",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "David Buck",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Angie Green",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Amy Trebes",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Paolo Piazza",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Lorne J Lonie",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ruth Studley",
+        "author_inst": "Office for National Statistics"
+      },
+      {
+        "author_name": "Emma Rourke",
+        "author_inst": "Office for National Statistics"
+      },
+      {
+        "author_name": "Darren Smith",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Matthew Bashton",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Andrew Nelson",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Matthew Crown",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Clare McCann",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Gregory R Young",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Rui Andre Nunes de Santos",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Zack Richards",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "Adnan Tariq",
+        "author_inst": "Northumbria University"
+      },
+      {
+        "author_name": "- Wellcome Sanger Institute COVID-19 Surveillance Team",
+        "author_inst": "Wellcome Sanger Institute"
+      },
+      {
+        "author_name": "- COVID-19 Infection Survey Group",
+        "author_inst": "Office for National Statistics"
+      },
+      {
+        "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Christophe Fraser",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ian Diamond",
+        "author_inst": "Office for National Statistics"
+      },
+      {
+        "author_name": "Jeff Barrett",
+        "author_inst": "Wellcome Sanger Institute"
+      },
+      {
+        "author_name": "Ann Sarah Walker",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "David Bonsall",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "scientific communication and education"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.01.06.22268711",
@@ -401540,71 +403227,99 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2022.01.03.22268704",
-    "rel_title": "Immune responses to inactivated and vector-based vaccines in individuals previously infected with SARS-CoV-2",
+    "rel_doi": "10.1101/2022.01.03.22268681",
+    "rel_title": "Reported Cases of Multisystem Inflammatory Syndrome in Children Aged 12 to 20 Years in the United States Who Received COVID-19 Vaccine, December 2020 through August 2021",
     "rel_date": "2022-01-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.03.22268704",
-    "rel_abs": "Immunity wanes in individuals previously infected with SARS-CoV-2, and vaccinating those individuals may help reduce reinfection. Herein, reactogenicity and immunogenicity following vaccination with inactivated (CoronaVac) and vector-based (ChAdOx1-S, AZD1222) vaccines were examined in previously infected individuals. Immune response was also compared between short and long intervals between first date of detection and vaccination. Adverse events were mild but were higher with AZD1222 than with CoronaVac. Baseline IgG-specific antibodies and neutralizing activity were significantly higher with shorter than longer intervals. With a single-dose vaccine, IgG and IgA-specific binding antibodies, neutralizing activity, and total interferon-gamma response peaked at 14 days. Immune response was significantly higher in recovered individuals than in infection-naive individuals. Antibody response was greater with longer than shorter intervals. AZD1222 induced higher antibody and T cell responses than those of CoronaVac. Thus, to achieve immunity, individuals with prior SARS-CoV-2 exposure may require only a single dose of AZD1222 or two doses of CoronaVac to achieve the immune response. These findings supported vaccine strategies in previously infected individuals.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.03.22268681",
+    "rel_abs": "BackgroundMultisystem inflammatory syndrome in children (MIS-C) is a hyperinflammatory condition associated with antecedent SARS-CoV-2 infection. In the United States, reporting of MIS-C after vaccination is required under COVID-19 vaccine emergency use authorizations. This case series describes persons aged 12-20 years with MIS-C following COVID-19 vaccination reported to passive surveillance systems or through clinician outreach to CDC.\n\nMethodsWe investigated potential cases of MIS-C after COVID-19 vaccination reported to CDCs health department-based national MIS-C surveillance, the Vaccine Adverse Event Reporting System (VAERS, co-administered by CDC and the U.S. FDA), and CDCs Clinical Immunization Safety Assessment Project (CISA) from December 14, 2020, to August 31, 2021. We describe cases meeting the CDC MIS-C case definition. Any positive SARS-CoV-2 serology test satisfied the case criteria although anti-nucleocapsid antibody indicates SARS-CoV-2 infection, while anti-spike protein antibody indicates either infection or COVID-19 vaccination.\n\nFindingsWe identified 21 persons with MIS-C after COVID-19 vaccination. Of these 21 persons, median age was 16 years (range, 12-20 years); 13 (62%) were male. All were hospitalized; 12 (57%) had intensive care unit admission, and all were discharged home. Fifteen (71%) of the 21 had laboratory evidence of past or recent SARS-CoV-2 infection, and six (29%) did not. Through August 2021, 21,335,331 persons aged 12-20 years had received [&ge;]1 dose of COVID-19 vaccine, making the overall reporting rate for MIS-C following vaccination 1{middle dot}0 case per million persons receiving [&ge;]1 vaccine dose in this age group. The reporting rate for those without evidence of SARS-CoV-2 infection was 0{middle dot}3 cases per million vaccinated persons.\n\nInterpretationIn our case series, we describe a small number of persons with MIS-C who had received [&ge;]1 COVID-19 vaccine dose before illness onset. Continued reporting of potential cases and surveillance for MIS-C illnesses after COVID-19 vaccination is warranted.\n\nFundingThis work was supported by the Centers for Disease Control and Prevention Clinical Immunization Safety Assessment (CISA] Project contracts 200-2012-50430-0005 to Vanderbilt University Medical Center and 200-2012-53661 to Cincinnati Childrens Hospital Medical Center.\n\nResearch in context panelO_ST_ABSEvidence before this studyC_ST_ABSMultisystem inflammatory syndrome in children (MIS-C), also known as paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS), is an uncommon, but serious, complication described after SARS-CoV-2 infection that is characterized by a generalized hyperinflammatory response. A review of the literature using PubMed identified reports of six persons aged 12-20 years who developed MIS-C following COVID-19 vaccination. Search terms used to identify these reports were: \"multisystem inflammatory syndrome in children\", \"MIS-C\", \"MISC\", \"multisystem inflammatory syndrome in adults\", \"MIS-A\", \"MISA\", \"paediatric inflammatory multisystem syndrome\", and \"PIMS-TS\" each with any COVID-19 vaccine type. There were no exclusion criteria (i.e., all ages and languages).\n\nAdded value of this studyWe conducted integrated surveillance for MIS-C after COVID-19 vaccination using two passive surveillance systems, CDCs MIS-C national surveillance and the Vaccine Adverse Event Reporting System (VAERS), and clinician or health department outreach to CDC, including through Clinical Immunization Safety Assessment (CISA) Project consultations. We investigated reports of potential MIS-C occurring from December 14, 2020, to August 31, 2021, in persons aged 12-20 years any time after receipt of COVID-19 vaccine to identify those that met the CDC MIS-C case definition. Any positive serology test was accepted as meeting the CDC MIS-C case definition, although anti- nucleocapsid antibody is indicative of SARS-CoV-2 infection, while anti-spike protein antibody may be induced either by SARS-CoV-2 infection or by COVID-19 vaccination. We investigated 47 reports and identified 21 persons with MIS-C after receipt of COVID-19 vaccine. Of the 21 persons with MIS-C, median age was 16 years (range 12-20 years), and 13 (62%) were male. Fifteen (71%) had laboratory evidence of past or recent SARS-CoV-2 infection (positive SARS-CoV-2 nucleic acid amplification test [NAAT], viral antigen, or serology test before or during MIS-C illness evaluation), and 5 (33%) of those 15 had illness onset after their second vaccine dose. Six (29%) of 21 persons had no laboratory evidence of past or recent SARS-CoV-2 infection, and five of those six (83%) had onset of MIS-C after the second vaccine dose.\n\nImplications of all the available evidenceDuring the first nine months of the COVID-19 vaccination program in the United States, >21 million persons aged 12 to 20 years received [&ge;]1 dose of COVID-19 vaccine as of August 31, 2021. This case series describes MIS-C in 21 persons following vaccine receipt during this time period; the majority of persons reported also had evidence of SARS-CoV-2 infection. The surveillance has limitations, but our findings suggest that MIS-C as identified in this report following COVID-19 vaccination is rare. In evaluating persons with a clinical presentation consistent with MIS-C after COVID-19 vaccination it is important to consider alternative diagnoses, and anti-nucleocapsid antibody testing may be helpful. Continued surveillance for MIS-C illness after COVID-19 vaccination is warranted, especially as pediatric COVID-19 vaccination expands. Providers are encouraged to report potential MIS-C cases after COVID-19 vaccination to VAERS.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Nungruthai Suntronwong",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Anna R. Yousaf",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Ritthideach Yorsaeng",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Margaret Cortese",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Chompoonut Auphimai",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Allan W. Taylor",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Thanunrat Thongmee",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Karen R. Broder",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Preeyaporn Vichaiwattana",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Matthew E. Oster",
+        "author_inst": "Emory University School of Medicine"
       },
       {
-        "author_name": "Sitthichai Kanokudom",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Joshua M. Wong",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Suvichada Assawakosri",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Alice Y. Guh",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Pornjarim Nilyanimit",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "David W. McCormick",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Donchida Srimuan",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Satoshi Kamidani",
+        "author_inst": "Emory University School of Medicine"
       },
       {
-        "author_name": "Thaksaporn Thatsanatorn",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Elizabeth Schlaudecker",
+        "author_inst": "Cincinnati Childrens Hospital Medical Center"
       },
       {
-        "author_name": "Natthinee Sudhinaraset",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Kathryn Edwards",
+        "author_inst": "Vanderbilt University Medical Center"
       },
       {
-        "author_name": "Nasamon Wanlapakorn",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "C. Buddy Creech",
+        "author_inst": "Vanderbilt University Medical Center"
       },
       {
-        "author_name": "Yong Poovorawan",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Mary A. Staat",
+        "author_inst": "Cincinnati Childrens Hospital Medical Center"
+      },
+      {
+        "author_name": "Ermias D. Belay",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Paige Marquez",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "John R. Su",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Mark B. Salzman",
+        "author_inst": "Kaiser Permanente West Los Angeles Medical Center"
+      },
+      {
+        "author_name": "Deborah Thompson",
+        "author_inst": "Food and Drug Administration"
+      },
+      {
+        "author_name": "Angela P. Campbell",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "- MIS-C Investigation Authorship Group",
+        "author_inst": ""
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2022.01.01.21268576",
@@ -403270,23 +404985,107 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2022.01.05.22268637",
-    "rel_title": "Personal Resilience, Social Support, and Organizational Support Impact Burnout among Nurses During COVID-19",
+    "rel_doi": "10.1101/2022.01.05.22268646",
+    "rel_title": "SARS-CoV-2 Genetic diversity and lineage dynamics of in Egypt",
     "rel_date": "2022-01-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.05.22268637",
-    "rel_abs": "BackgroundNurses have been under heavy workloads since the outbreak of COVID-19 and are at a high risk of infection, leading to a high level of psychosocial risk. This can adversely affect nurses both psychologically and physically. Burnout is caused by prolonged stress during work. In the nursing profession, burnout is common, potentially affecting the well-being of nurses and their productivity. The identification of factors that may contribute to maintaining mental health and reducing burnout among frontline nurses during a pandemic is essential.\n\nPurposeThe purpose of this study was to explore how personal resilience, social support, and organizational support impact burnout among frontline staff nurses.\n\nMethodsThis study involved 129 registered nurses from a COVID-19 designated hospital using four standardized scales.\n\nResultsThe mean age of the respondents was 29.46 years (standard deviation = 4.89). The mean number of years respondents worked in this organization was 5.60 years and the nursing profession was 4.16 years. Most of the respondents were female and held a bachelors degree in nursing. Multiple regression analysis was performed to predict burnout. Burnout was statistically significantly predicted by the multiple regression model (R2 = .420, F (3, 125) = 10.941, p < .0001; adjusted R2 = .406). Personal resilience, social support, and organizational support added statistically significantly to the prediction of burnout (p < .05).\n\nConclusionFindings from multiple regression analysis showed that nurses with low resilience and those who perceived inadequate social and organizational support had a higher risk of reporting more burnout. As a result of a bivariate analysis, there was no significant correlation between nurse variables and burnout level, except for age, which was negatively correlated with burnout level. Accordingly, young nurses tend to experience burnout, and nurse directors and managers must address this problem.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.05.22268646",
+    "rel_abs": "COVID-19 was first diagnosed in Egypt on 14 February 2020. By the end of November 2021, over 333,840 cases and 18,832 deaths had been reported. As part of national genomic surveillance, 1,027 SARS-CoV-2 near whole-genomes had been generated and published by the end of May 2021. Here we describe the genomic epidemiology of SARS-CoV-2 in Egypt over this period using a subset of 976 high-quality Egyptian genomes analysed together with a representative set of global sequences within a phylogenetic framework. We show that a single lineage, C.36, introduced early in the pandemic was responsible for most cases in Egypt. Furthermore, we show that to remain dominant in the face of mounting immunity from previous infection and vaccination, this lineage evolved into various sub-lineages acquiring several mutations known to confer adaptive advantage and pathogenic properties. These results highlight the value of continuous genomic surveillance in regions where VOCs are not predominant and enforcement of public health measures to prevent expansion of existing lineages.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Hanan Daghash",
-        "author_inst": "Al-Ghad International Colleges for Health Sciences"
+        "author_name": "Wael Hamed Roshdy",
+        "author_inst": "Central Public Health Laboratory, Ministry of Health and Population, Cairo, Egypt."
+      },
+      {
+        "author_name": "Mohamed K Khalifa",
+        "author_inst": "Omicsense, Cairo, Egypt."
+      },
+      {
+        "author_name": "James Emmanuel San",
+        "author_inst": "Kwazulu Natal Research and Innovation Sequencing Platform"
+      },
+      {
+        "author_name": "Houriiyah Tegally",
+        "author_inst": "Kwazulu Natal research and Innovation Sequencing Platform (KRISP)"
+      },
+      {
+        "author_name": "Eduan Wilkinson",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa"
+      },
+      {
+        "author_name": "Shymaa Showky",
+        "author_inst": "Central Public Health Laboratory, Ministry of Health and Population, Cairo, Egypt"
+      },
+      {
+        "author_name": "Darren P Martin",
+        "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa."
+      },
+      {
+        "author_name": "Monika Moir",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa"
+      },
+      {
+        "author_name": "Amel Naguib",
+        "author_inst": "Central Public Health Laboratory, Ministry of Health and Population, Cairo, Egypt."
+      },
+      {
+        "author_name": "Nancy Elguindy",
+        "author_inst": "Central Public Health Laboratory, Ministry of Health and Population, Cairo, Egypt."
+      },
+      {
+        "author_name": "Mokhtar R Gomaa",
+        "author_inst": "Centre of Scientific Excellence for Influenza Viruses, National Research Centre, 12622  Dokki, Giza, Egypt."
+      },
+      {
+        "author_name": "Manal Fahim",
+        "author_inst": "Department of Surveillance and Epidemiology, Ministry of Health and Population, Cairo, Egypt."
+      },
+      {
+        "author_name": "Hanaa Abu Elsood",
+        "author_inst": "Public Health Initiative, Cairo, Egypt."
+      },
+      {
+        "author_name": "Amira A Mohsen",
+        "author_inst": "World Health Organization, Egypt Country Office, Cairo, Egypt."
+      },
+      {
+        "author_name": "Ramy Galal",
+        "author_inst": "World Health Organization, Egypt Country Office, Cairo, Egypt."
+      },
+      {
+        "author_name": "Mohamed Hassany",
+        "author_inst": "World Health Organization, Egypt Country Office, Cairo, Egypt."
+      },
+      {
+        "author_name": "Richard J Lessells",
+        "author_inst": "Kwazulu Natal research and Innovation Sequencing Platform (KRISP)"
+      },
+      {
+        "author_name": "Ahmed A Al Karmalawy",
+        "author_inst": "Department of Pharmaceutical Medicinal Chemistry, Faculty of Pharmacy, Horus University-Egypt, New Damietta 34518, Egypt."
+      },
+      {
+        "author_name": "Rabeh EL Shesheny",
+        "author_inst": "Omicsense, Cairo, Egypt."
+      },
+      {
+        "author_name": "Ahmed M Kandeil",
+        "author_inst": "Department of Pharmaceutical Medicinal Chemistry, Faculty of Pharmacy, Horus University-Egypt, New Damietta 34518, Egypt."
+      },
+      {
+        "author_name": "Mohamed A Ali",
+        "author_inst": "Public Health Initiative, Cairo, Egypt."
+      },
+      {
+        "author_name": "Tulio de Oliveira",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "nursing"
+    "category": "genetic and genomic medicine"
   },
   {
     "rel_doi": "10.1101/2022.01.04.22268773",
@@ -405308,39 +407107,31 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2022.01.02.22268629",
-    "rel_title": "Cognitive predictors of vaccine hesitancy and COVID-19 mitigation behaviors in a population representative sample",
+    "rel_doi": "10.1101/2021.12.30.21268571",
+    "rel_title": "Estimation the state of the Covid-19 epidemic curve in Mayotte",
     "rel_date": "2022-01-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.02.22268629",
-    "rel_abs": "With the continued threat of COVID-19, predictors of vaccination hesitancy and mitigation behaviors are critical to identify. Prior studies have found that cognitive factors are associated with some COVID-19 mitigation behaviors, but few studies employ representative samples and to our knowledge no prior studies have examined cognitive predictors of vaccine hesitancy. The purpose of the present study, conducted among a large national sample of Canadian adults, was to examine associations between cognitive variables (executive function, delay discounting, and temporal orientation) and COVID-19 mitigation behaviors (vaccination, mask wearing, social distancing, and hand hygiene). Findings revealed that individuals with few executive function deficits, limited delay discounting and who adopted a generally future-orientation mindset were more likely to be double-vaccinated and to report performing COVID-19 mitigation behaviors with high consistency. The most reliable findings were for delay discounting and future orientation, with executive function deficits predicting mask wearing and hand hygiene behaviors but not distancing and vaccination. These findings identify candidate mediators and moderators for health communication messages targeting COVID-19 mitigation behaviors and vaccine hesitancy.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.30.21268571",
+    "rel_abs": "We study in this work some statistical methods to estimate the parameters resulting from the use of an age-structured contact mathematical epidemic model in order to analyze the evolution of the epidemic curve of Covid-19 in the French overseas department Mayotte from march 13, 2020 to february 26,2021. Using several statistic methods based on time dependent method, maximum likelihood, mixture method, we fit the probability distribution which underlines the serial interval distribution and we give an adapted version of the generation time distribution from Package R0. The best-fit model of the serial interval was given by a mixture of Weibull distribution. Furthermore this estimation allows to obtain the evolution of the time varying effective reproduction number and hence the temporal transmission rates. Finally based on others known estimates parameters we incorporate the estimated parameters in the model in order to give an approximation of the epidemic curve in Mayotte under the conditions of the model. We also discuss the limit of our study and the conclusion concerned a probable impact of non pharmacological interventions of the Covid-19 in Mayotte such us the re-infection cases and the introduction of the variants which probably affect the estimates.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Anna Hudson",
-        "author_inst": "University of Waterloo"
-      },
-      {
-        "author_name": "Peter A Hall",
-        "author_inst": "University of Waterloo"
+        "author_name": "Solym Mawaki MANOU-ABI",
+        "author_inst": "Institut Montpellierain Alexander Grothendieck"
       },
       {
-        "author_name": "Sara Hitchman",
-        "author_inst": "University of Zurich"
+        "author_name": "Yousri SLAOUI",
+        "author_inst": "LMA"
       },
       {
-        "author_name": "Gang Meng",
-        "author_inst": "University of Waterloo"
-      },
-      {
-        "author_name": "Geoffrey T Fong",
-        "author_inst": "University of Waterloo"
+        "author_name": "Julien BALICCHI",
+        "author_inst": "Agence Regionale de Sante de Mayotte"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2022.01.02.22268622",
@@ -407194,127 +408985,71 @@
     "category": "pathology"
   },
   {
-    "rel_doi": "10.1101/2021.12.29.21268529",
-    "rel_title": "Humoral immune responses against SARS-CoV-2 variants including omicron in solid organ transplant recipients after three doses of a COVID-19 mRNA vaccine",
+    "rel_doi": "10.1101/2021.12.30.21268565",
+    "rel_title": "Effectiveness of COVID-19 vaccines against Omicron or Delta infection",
     "rel_date": "2022-01-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.29.21268529",
-    "rel_abs": "BackgroundSolid organ transplant recipients (SOTR), who typically receive post-transplant immunosuppression, show increased COVID-19-related mortality. It is unclear whether an additional dose of COVID-19 vaccines in SOTR can overcome the reduced immune responsiveness against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants.\n\nMethodsWe performed a prospective cohort study of 53 SOTR receiving SARS-CoV-2 vaccination into a prospective cohort study performing detailed immunoprofiling of humoral immune responses against SARS-CoV-2 and its variants.\n\nResultsPrior to the additional vaccine dose, 60.3% of SOTR showed no measurable neutralization and only 18.9% demonstrated neutralizing activity of >90% following two vaccine doses. More intensive immunosuppression, antimetabolites in particular, negatively impacted antiviral immunity. While absolute IgG levels were lower in SOTR than controls, antibody titers against microbial recall antigens were in fact higher. In contrast, SOTR showed reduced vaccine-induced IgG/IgA antibody titers against SARS-CoV-2 and its delta variants. Vaccinated SOTR showed a markedly fewer linear B cell epitopes, indicating reduced B cell diversity. Importantly, a third vaccine dose led to an increase in anti-SARS-CoV-2 antibody titers and neutralizing activity across alpha, beta and delta variants. However, we observed a significant decrease in anti-spike antibody titers with the omicron variant.\n\nConclusionsOnly a small subgroup of SOTR generated functionally relevant antibodies after completing the initial vaccine series based on dysfunctional priming of immune responses against novel antigens. An additional dose of the vaccine results in dramatically improved antibody responses against all SARS-CoV-2 variants except omicron.",
-    "rel_num_authors": 27,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.30.21268565",
+    "rel_abs": "BackgroundThe incidence of SARS-CoV-2 infection, including among those who have received 2 doses of COVID-19 vaccines, increased substantially following the emergence of Omicron in Ontario, Canada.\n\nMethodsApplying the test-negative study design to linked provincial databases, we estimated vaccine effectiveness (VE) against symptomatic infection and severe outcomes (hospitalization or death) caused by Omicron or Delta between December 6 and 26, 2021. We used multivariable logistic regression to estimate the effectiveness of 2 or 3 COVID-19 vaccine doses by time since the latest dose, compared to unvaccinated individuals.\n\nResultsWe included 16,087 Omicron-positive cases, 4,261 Delta-positive cases, and 114,087 test-negative controls. VE against symptomatic Delta infection declined from 89% (95%CI, 86-92%) 7-59 days after a second dose to 80% (95%CI, 74-84%) after [&ge;]240 days, but increased to 97% (95%CI, 96-98%) [&ge;]7 days after a third dose. VE against symptomatic Omicron infection was only 36% (95%CI, 24-45%) 7-59 days after a second dose and provided no protection after [&ge;]180 days, but increased to 61% (95%CI, 56-65%) [&ge;]7 days after a third dose. VE against severe outcomes was very high following a third dose for both Delta and Omicron (99% [95%CI, 98-99%] and 95% [95%CI, 87-98%], respectively).\n\nConclusionsIn contrast to high levels of protection against both symptomatic infection and severe outcomes caused by Delta, our results suggest that 2 doses of COVID-19 vaccines only offer modest and short-term protection against symptomatic Omicron infection. A third dose improves protection against symptomatic infection and provides excellent protection against severe outcomes for both variants.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Kapil K. Saharia",
-        "author_inst": "Institute of Human Virology, University of Maryland School of Medicine"
-      },
-      {
-        "author_name": "Jennifer S. Husson",
-        "author_inst": "Institute of Human Virology, University of Maryland School of Medicine"
-      },
-      {
-        "author_name": "Silke V. Niederhaus",
-        "author_inst": "Department of Surgery, University of Maryland School of Medicine"
-      },
-      {
-        "author_name": "Thierry Iraguha",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
-      },
-      {
-        "author_name": "Stephanie V. Avila",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
-      },
-      {
-        "author_name": "Youngchae J. Yoo",
-        "author_inst": "Institute of Human Virology, University of Maryland School of Medicine"
-      },
-      {
-        "author_name": "Nancy M. Hardy",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
-      },
-      {
-        "author_name": "Xiaoxuan Fan",
-        "author_inst": "University of Maryland Greenebaum Comprehensive Cancer Center"
-      },
-      {
-        "author_name": "Destiny Omili",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
-      },
-      {
-        "author_name": "Alice Crane",
-        "author_inst": "Department of Surgery, University of Maryland School of Medicine"
-      },
-      {
-        "author_name": "Amber Carrier",
-        "author_inst": "Department of Surgery, University of Maryland School of Medicine"
-      },
-      {
-        "author_name": "Wen Y. Xie",
-        "author_inst": "Department of Surgery, University of Florida College of Medicine"
-      },
-      {
-        "author_name": "Erica Vander Mause",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
-      },
-      {
-        "author_name": "Kim Hankey",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
-      },
-      {
-        "author_name": "Sheri Bauman",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
+        "author_name": "Sarah A Buchan",
+        "author_inst": "Public Health Ontario"
       },
       {
-        "author_name": "Patricia Lesho",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
+        "author_name": "Hannah Chung",
+        "author_inst": "ICES"
       },
       {
-        "author_name": "Heather D. Mannuel",
-        "author_inst": "University of Maryland Greenebaum Comprehensive Cancer Center"
+        "author_name": "Kevin A Brown",
+        "author_inst": "Public Health Ontario"
       },
       {
-        "author_name": "Ashish Ahuja",
-        "author_inst": "Department of Medicine, University of Maryland Medical Center"
+        "author_name": "Peter C Austin",
+        "author_inst": "ICES"
       },
       {
-        "author_name": "Minu Mathew",
-        "author_inst": "Divison of Infectious Diseases, University of Maryland School of Medicine"
+        "author_name": "Deshayne B Fell",
+        "author_inst": "University of Ottawa"
       },
       {
-        "author_name": "James Avruch",
-        "author_inst": "Department of Surgery, University of Maryland School of Medicine"
+        "author_name": "Jonathan Gubbay",
+        "author_inst": "Public Health Ontario"
       },
       {
-        "author_name": "John Baddley",
-        "author_inst": "Institute of Human Virology, University of Maryland School of Medicine"
+        "author_name": "Sharifa Nasreen",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Olga Goloubeva",
-        "author_inst": "Department of Epidemiology and Public Health, University of Maryland Greenebaum Comprehensive Cancer Center"
+        "author_name": "Kevin L Schwartz",
+        "author_inst": "Public Health Ontario"
       },
       {
-        "author_name": "Kirti Shetty",
-        "author_inst": "Division of Hepatology/Liver Transplantation, University of Maryland School of Medicine,"
+        "author_name": "Maria E Sundaram",
+        "author_inst": "Marshfield Clinic Research Institute"
       },
       {
-        "author_name": "Saurabh Dahiya",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
+        "author_name": "Mina Tadrous",
+        "author_inst": "Womens College Hospital"
       },
       {
-        "author_name": "Aaron P. Rapoport",
-        "author_inst": "Transplant and Cellular Therapy Program, Department of Medicine, University of Maryland"
+        "author_name": "Kumanan Wilson",
+        "author_inst": "University of Ottawa"
       },
       {
-        "author_name": "Tim Luetkens",
-        "author_inst": "Department of Microbiology and Immunology, University of Maryland"
+        "author_name": "Sarah E Wilson",
+        "author_inst": "Public Health Ontario"
       },
       {
-        "author_name": "Djordje Atanackovic",
-        "author_inst": "University of Maryland Greenebaum Comprehensive Cancer Center"
+        "author_name": "Jeff Kwong",
+        "author_inst": "ICES"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "transplantation"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.12.31.21268580",
@@ -409484,51 +411219,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.12.24.474110",
-    "rel_title": "Reduced infectivity but increased immune escape of the new SARS-CoV-2 variant of concern Omicron",
+    "rel_doi": "10.1101/2021.12.30.21268537",
+    "rel_title": "The rich-to-poor vaccine donation game: When will self-interested countries donate their surplus vaccines during pandemics?",
     "rel_date": "2021-12-30",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.24.474110",
-    "rel_abs": "A new detected SARS-CoV-2 variant Omicron (B.1.1.529) had reported from more than 80 countries. In the past few weeks, a new wave of infection driven by Omicron is in progress. Omicron Spike (S) protein pseudotyped virus was used to determine the effect of S mutations on its capacity of infectivity and immune evasion. Our results showed the lower entry efficiency and less cleavage ability of Omicron than D614G variant. Pseudotype-based neutralizing assay was performed to analyze neutralizing antibodies elicited by previously infection or the RBD-based protein subunit vaccine ZF2001 against the Omicron variant. Sera sampled at around one month after symptom onset from 12 convalescents who were previously infected by SARS-CoV-2 original strain shows a more than 20-fold decrease of neutralizing activity against Omicron variant, when compared to D614G variant. Among 12 individuals vaccinated by RBD subunit vaccine, 58.3% (7/12) sera sampled at 15-60 days after 3rd-dose vaccination did not neutralize Omicron. Geometric mean titers (GMTs, 50% inhibitory dose [ID50]) of these sera against Omicron were 9.4-fold lower than against D614G. These results suggested a higher risk of Omicron breakthrough infections and reduced efficiency of the protective immunity elicited by existing vaccines. There are important implications about the modification and optimization of the current epidemic prevention and control including vaccine strategies and therapeutic antibodies against Omicron variant.",
-    "rel_num_authors": 8,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.30.21268537",
+    "rel_abs": "When will self-interested vaccine-rich countries voluntarily donate their surplus vaccines to vaccine-poor countries during a pandemic? We develop a game-theoretic approach to address this question. We identify vaccine-rich countries optimal surplus donation strategies, and then examine whether these strategies are stable (Nash equilibrium or self-enforcing international agreement). We identify parameter ranges in which full or partial surplus stock donations are optimal for the donor countries. Within a more restrictive parameter region, these optimal strategies are also stable. This implies that, under certain conditions (notably a total amount of surplus vaccines that is sufficiently large), simple coordination can lead to significant donations by strictly self-interested vaccine-rich countries. On the other hand, if the total amount that the countries can donate is small, we expect no contribution from self-interested countries. The results of this analysis provide guidance to policy makers in identifying the circumstances in which coordination efforts are likely to be effective.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Jie Hu",
-        "author_inst": "Chongqing Medical University"
-      },
-      {
-        "author_name": "Pai Peng",
-        "author_inst": "Chongqing Medical University"
-      },
-      {
-        "author_name": "Kang Wu",
-        "author_inst": "Chongqing Medical University"
-      },
-      {
-        "author_name": "Quan-xin Long",
-        "author_inst": "Chongqing Medical University"
-      },
-      {
-        "author_name": "Juan Chen",
-        "author_inst": "Chongqing Medical University"
+        "author_name": "Adam Lampert",
+        "author_inst": "The Hebrew University"
       },
       {
-        "author_name": "Kai Wang",
-        "author_inst": "Chongqing Medical University"
+        "author_name": "Raanan Sulitzeanu-Kenan",
+        "author_inst": "The Hebrew University"
       },
       {
-        "author_name": "Ni Tang",
-        "author_inst": "Chongqing Medical University"
+        "author_name": "Pieter Vanhuysse",
+        "author_inst": "University of Southern Denmark"
       },
       {
-        "author_name": "Ailong Huang",
-        "author_inst": "Chongqing Medical University"
+        "author_name": "Markus Tepe",
+        "author_inst": "University of Oldenburg"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "microbiology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2021.12.30.21268307",
@@ -411494,117 +413213,109 @@
     "category": "hematology"
   },
   {
-    "rel_doi": "10.1101/2021.12.27.21268459",
-    "rel_title": "Immunogenicity of heterologous BNT162b2 booster in fully vaccinated individuals with CoronaVac against SARS-CoV-2 variants Delta and Omicron: the Dominican Republic Experience",
+    "rel_doi": "10.1101/2021.12.27.21268416",
+    "rel_title": "Divergent SARS CoV-2 Omicron-specific T- and B-cell responses in COVID-19 vaccine recipients",
     "rel_date": "2021-12-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.27.21268459",
-    "rel_abs": "The recent emergence of the SARS-CoV-2 Omicron variant is raising concerns because of its increased transmissibility and by its numerous spike mutations with potential to evade neutralizing antibodies elicited by COVID-19 vaccines. The Dominican Republic was among the first countries in recommending the administration of a third dose COVID-19 vaccine to address potential waning immunity and reduced effectiveness against variants. Here, we evaluated the effects of a heterologous BNT162b2 mRNA vaccine booster on the humoral immunity of participants that had received a two-dose regimen of CoronaVac, an inactivated vaccine used globally. We found that heterologous CoronaVac prime followed by BNT162b2 booster regimen induces elevated virus-specific antibody levels and potent neutralization activity against the ancestral virus and Delta variant, resembling the titers obtained after two doses of mRNA vaccines. While neutralization of Omicron was undetectable in participants that had received a two-dose regimen of CoronaVac vaccine, BNT162b2 booster resulted in a 1.4-fold increase in neutralization activity against Omicron, compared to two-dose mRNA vaccine. Despite this increase, neutralizing antibody titers were reduced by 6.3-fold and 2.7-fold for Omicron compared to ancestral and Delta variant, respectively. Surprisingly, previous SARS-CoV-2 infection did not affect the neutralizing titers for Omicron in participants that received the heterologous regimen. Our findings have immediate implications for multiples countries that previously used a two-dose regimen of CoronaVac and reinforce the notion that the Omicron variant is associated with immune escape from vaccines or infection-induced immunity, highlighting the global need for vaccine boosters to combat the impact of emerging variants.",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.27.21268416",
+    "rel_abs": "The severe acute respiratory distress syndrome coronavirus-2 (SARS-CoV-2) Omicron variant (B.1.1.529) is spreading rapidly, even in vaccinated individuals, raising concerns about immune escape. Here, we studied neutralizing antibodies and T-cell responses to SARS-CoV-2 D614G (wildtype, WT), and the B.1.351 (Beta), B.1.617.2 (Delta), and B.1.1.529 (Omicron) variants of concern (VOC) in a cohort of 60 health care workers (HCW) after immunization with ChAdOx-1 S, Ad26.COV2.S, mRNA-1273 or BNT162b2. High binding antibody levels against WT SARS-CoV-2 spike (S) were detected 28 days after vaccination with both mRNA vaccines (mRNA-1273 or BNT162b2), which significantly decreased after 6 months. In contrast, antibody levels were lower after Ad26.COV2.S vaccination but did not wane. Neutralization assays with authentic virus showed consistent cross-neutralization of the Beta and Delta variants in study participants, but Omicron-specific responses were significantly lower or absent (up to a 34-fold decrease compared to D614G). Notably, BNT162b2 booster vaccination after either two mRNA-1273 immunizations or Ad26.COV.2 priming partially restored neutralization of the Omicron variant, but responses were still up to-17-fold decreased compared to D614G. CD4+ T-cell responses were detected up to 6 months after all vaccination regimens; S-specific T-cell responses were highest after mRNA-1273 vaccination. No significant differences were detected between D614G- and variant-specific T-cell responses, including Omicron, indicating minimal escape at the T-cell level. This study shows that vaccinated individuals retain T-cell immunity to the SARS-CoV-2 Omicron variant, potentially balancing the lack of neutralizing antibodies in preventing or limiting severe COVID-19. Booster vaccinations may be needed to further restore Omicron cross-neutralization by antibodies.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Eddy Perez-Then",
-        "author_inst": "Ministry of Health, Santo Domingo, Dominican Republic."
-      },
-      {
-        "author_name": "Carolina Lucas",
-        "author_inst": "Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA."
-      },
-      {
-        "author_name": "Valter Silva Monteiro",
-        "author_inst": "Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA."
+        "author_name": "Corine H. GeurtsvanKessel",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Marija Miric",
-        "author_inst": "Two Oceans in Health, Santo Domingo, Dominican Republic."
+        "author_name": "Daryl Geers",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Vivian Brache",
-        "author_inst": "Departamento de Investigaciones Biomedicas, Clinica Evangelina Rodriguez, PROFAMILIA. Santo Domingo, Dominican Republic."
+        "author_name": "Katharina S. Schmitz",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Leila Cochon",
-        "author_inst": "Departamento de Investigaciones Biomedicas, Clinica Evangelina Rodriguez, PROFAMILIA. Santo Domingo, Dominican Republic."
+        "author_name": "Anna Z. Mykytyn",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Chantal B.F. Vogels",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA."
+        "author_name": "Mart M. Lamers",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Elena De la Cruz",
-        "author_inst": "Departamento de Investigaciones Biomedicas, Clinica Evangelina Rodriguez, PROFAMILIA. Santo Domingo, Dominican Republic."
+        "author_name": "Susanne Bogers",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Aidelis Jorge",
-        "author_inst": "Departamento de Investigaciones Biomedicas, Clinica Evangelina Rodriguez, PROFAMILIA. Santo Domingo, Dominican Republic."
+        "author_name": "Lennert Gommers",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Margarita De los Santos",
-        "author_inst": "Departamento de Investigaciones Biomedicas, Clinica Evangelina Rodriguez, PROFAMILIA. Santo Domingo, Dominican Republic."
+        "author_name": "Roos S.G. Sablerolles",
+        "author_inst": "Department of Hospital Pharmacy, Erasmus MC, Rotterdam, Netherlands"
       },
       {
-        "author_name": "Patricia Leon",
-        "author_inst": "Laboratorio de Referencia, Dominican Republic."
+        "author_name": "Nella N. Nieuwkoop",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Mallery I. Breban",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA."
+        "author_name": "Laurine C. Rijsbergen",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Kendall Billig",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA."
+        "author_name": "Laura L.A. van Dijk",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Inci Yildirim",
-        "author_inst": "Department of Pediatric, Section of Infectious Diseases and Global Health; Yale University School of Medicine, New Haven, CT, USA."
+        "author_name": "Janet de Wilde",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Claire Pearson",
-        "author_inst": "Connecticut State Department of Public Health, Rocky Hill, USA"
+        "author_name": "Kimberly Alblas",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Randy Downing",
-        "author_inst": "Connecticut State Department of Public Health, Rocky Hill, USA"
+        "author_name": "Tim I. Breugem",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Emily Gagnon",
-        "author_inst": "Connecticut State Department of Public Health, Rocky Hill, USA"
+        "author_name": "Bart J.A. Rijnders",
+        "author_inst": "Department of Medical Microbiology and Infectious Diseases, Erasmus MC, Rotterdam, The Netherlands"
       },
       {
-        "author_name": "Anthony Muyombwe",
-        "author_inst": "Connecticut State Department of Public Health, Rocky Hill, USA"
+        "author_name": "Herbert de Jager",
+        "author_inst": "Department of Occupational Health Services, Erasmus MC, Rotterdam, Netherlands"
       },
       {
-        "author_name": "Jafar Razeq",
-        "author_inst": "Connecticut State Department of Public Health, Rocky Hill, USA"
+        "author_name": "Daniela Weiskopf",
+        "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA 92037, USA"
       },
       {
-        "author_name": "Melissa Campbell",
-        "author_inst": "Department of Pediatric, Section of Infectious Diseases and Global Health; Yale University School of Medicine, New Haven, CT, USA."
+        "author_name": "P. Hugo M. van der Kuy",
+        "author_inst": "Department of Hospital Pharmacy, Erasmus MC, Rotterdam, Netherlands"
       },
       {
-        "author_name": "Albert Ko",
-        "author_inst": "Yale University School of Public Health"
+        "author_name": "Alessandro Sette",
+        "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA 92037, USA"
       },
       {
-        "author_name": "Saad B. Omer",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA."
+        "author_name": "Marion P.G. Koopmans",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Nathan D Grubaugh",
-        "author_inst": "Yale School of Public Health"
+        "author_name": "Alba Grifoni",
+        "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA 92037, USA"
       },
       {
-        "author_name": "Sten H. Vermund",
-        "author_inst": "Yale School of Public Health, New Haven, CT, USA."
+        "author_name": "Bart L. Haagmans",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       },
       {
-        "author_name": "Akiko Iwasaki",
-        "author_inst": "Yale University School of Medicine"
+        "author_name": "Rory D. de Vries",
+        "author_inst": "Department of Viroscience, Erasmus MC, Rotterdam, the Netherlands"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -413628,73 +415339,73 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.12.27.474218",
-    "rel_title": "Vaccine-breakthrough infection by the SARS-CoV-2 Omicron variant elicits broadly cross-reactive immune responses",
+    "rel_doi": "10.1101/2021.12.26.472655",
+    "rel_title": "Evaluation of maternal-infant dyad inflammatory cytokines in pregnancies affected by maternal SARS-CoV-2 infection in early and late gestation.",
     "rel_date": "2021-12-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.27.474218",
-    "rel_abs": "Highly transmissible SARS-CoV-2 Omicron variant has posted a new crisis for COVID-19 pandemic control. Within a month, Omicron is dominating over Delta variant in several countries probably due to immune evasion. It remains unclear whether vaccine-induced memory responses can be recalled by Omicron infection. Here, we investigated host immune responses in the first vaccine-breakthrough case of Omicron infection in Hong Kong. We found that the breakthrough infection rapidly recruited potent cross-reactive broad neutralizing antibodies (bNAbs) against current VOCs, including Alpha, Beta, Gamma, Delta and Omicron, from unmeasurable IC50 values to mean 1:2929 at around 9-12 days, which were higher than the mean peak IC50 values of BioNTech-vaccinees. Cross-reactive spike- and nucleocapsid-specific CD4 and CD8 T cell responses were detected. Similar results were also obtained in the second vaccine-breakthrough case of Omicron infection. Our preliminary findings may have timely implications to booster vaccine optimization and preventive strategies of pandemic control.",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.26.472655",
+    "rel_abs": "ObjectiveSARS-CoV-2 infection induces significant inflammatory cytokine production in adults, but infant cytokine signatures in pregnancies affected by maternal SARS-CoV-2 are less well characterized. We aimed to evaluate cytokine profiles of mothers and their infants following COVID-19 in pregnancy.\n\nStudy DesignSerum samples at delivery from 31 mother-infant dyads with maternal SARS-CoV-2 infection in pregnancy (COVID) were examined in comparison to 29 control dyads (Control). Samples were evaluated using a 13-plex cytokine assay.\n\nResultsIn comparison with controls, interleukin (IL)-6 and interferon gamma-induced protein 10 (IP-10) were higher in COVID maternal and infant samples (p<0.05) and IL-8 uniquely elevated in COVID infant samples (p<0.05). Significant elevations in IL-6, IP-10 and IL-8 were found among both early (1st/2nd Trimester) and late (3rd Trimester) maternal SARS-CoV-2 infections.\n\nConclusionsMaternal SARS-CoV-2 infections throughout gestation are associated with increased maternal and infant inflammatory cytokines at birth with potential to impact long-term infant health.",
     "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Runhong Zhou",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Elizabeth Taglauer",
+        "author_inst": "Department of Pediatrics, Boston Medical Center"
       },
       {
-        "author_name": "Kelvin Kai-Wang To",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Yashoda Dhole",
+        "author_inst": "Boston University School of Medicine"
       },
       {
-        "author_name": "Qiaoli Peng",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Jeffery Boateng",
+        "author_inst": "Department of Pediatrics, Boston Medical Center"
       },
       {
-        "author_name": "Jacky Man-Chun Chan",
-        "author_inst": "Princess Margaret Hospital"
+        "author_name": "Jennifer E Snyder-Cappione",
+        "author_inst": "Department of Microbiology, Boston University School of Medicine"
       },
       {
-        "author_name": "Haode Huang",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Samantha E Parker",
+        "author_inst": "Boston University School of Public Health"
       },
       {
-        "author_name": "Dawei Yang",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Katherine Clarke",
+        "author_inst": "Department of Microbiology, Boston University School of Medicine"
       },
       {
-        "author_name": "Bosco Hoi-Shiu Lam",
-        "author_inst": "Princess Margaret Hospital"
+        "author_name": "Lillian Juttukonda",
+        "author_inst": "Department of Pediatrics, Boston Medical Center"
       },
       {
-        "author_name": "Vivien Wai-Man Chuang",
-        "author_inst": "Quality & Safety Division, Hospital Authority"
+        "author_name": "Jean Devera",
+        "author_inst": "Boston University School of Medicine"
       },
       {
-        "author_name": "Jian-Piao Cai",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Jessica Hunnewell",
+        "author_inst": "Boston University School of Public Health"
       },
       {
-        "author_name": "Na Liu",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Elizabeth Barnett",
+        "author_inst": "Department of Pediatrics, Boston Medical Center"
       },
       {
-        "author_name": "Ka-Kit Au",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Hongpeng Jia",
+        "author_inst": "Johns Hopkins University School of Medicine"
       },
       {
-        "author_name": "Owen Tak-Yin Tsang",
-        "author_inst": "Princess Margaret Hospital"
+        "author_name": "Christina Yarrington",
+        "author_inst": "Department of Obstetrics and Gynecology, Boston Medical Center"
       },
       {
-        "author_name": "Kwok-Yung Yuen",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Vishakha Sabharwal",
+        "author_inst": "Department of Pediatrics, Boston Medical Center"
       },
       {
-        "author_name": "Zhiwei Chen",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Elisha Wachman",
+        "author_inst": "Department of Pediatrics, Boston Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
     "category": "immunology"
   },
@@ -415814,83 +417525,487 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2021.12.26.473325",
-    "rel_title": "Comparative analysis of single cell lung atlas of bat, cat, tiger and pangolin",
+    "rel_doi": "10.1101/2021.12.21.21268143",
+    "rel_title": "Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission",
     "rel_date": "2021-12-27",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.26.473325",
-    "rel_abs": "Horseshoe bats (Rhinolophus sinicus) might help maintain coronaviruses severely affecting human health, such as SARS-CoV and SARS-CoV-2. It has long been suggested that bats may be more tolerant of viral infection than other mammals due to their unique immune system, but the exact mechanism remains to be fully explored. During the COVID-19 pandemic, multiple animal species were diseased by SARS-CoV-2 infection, especially in the respiratory system. Herein, single-cell transcriptomic data of the lungs of a horseshoe bat, a cat, a tiger, and a pangolin were generated. The receptor distribution of twenty-eight respiratory viruses belonging to fourteen viral families were characterized for the four species. Comparison on the immune-related transcripts further revealed limited cytokine activations in bats, which might explain the reason why bats experienced only mild diseases or even no symptoms upon virus infection. Our findings might increase our understanding of the immune background of horseshoe bats and their insensitivity to virus infections.",
-    "rel_num_authors": 16,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.21.21268143",
+    "rel_abs": "As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.",
+    "rel_num_authors": 117,
     "rel_authors": [
       {
-        "author_name": "Xiran Wang",
-        "author_inst": "National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, South China Agricultural University, Guangzhou, China; Guangdong L"
+        "author_name": "Smruthi Karthikeyan",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Zhihua Ou",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen 518083, China."
+        "author_name": "Joshua I Levy",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
       },
       {
-        "author_name": "Peiwen Ding",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China"
+        "author_name": "Peter De Hoff",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Chengcheng Sun",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; School of Basic Medicine, Qing"
+        "author_name": "Greg Humphrey",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Daxi Wang",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen 518083, China."
+        "author_name": "Amanda Birmingham",
+        "author_inst": "Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Jiacheng Zhu",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China"
+        "author_name": "Kristen Jepsen",
+        "author_inst": "Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Wendi Wu",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; School of Basic Medicine, Qing"
+        "author_name": "Sawyer Farmer",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Yanan Wei",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; School of Basic Medicine, Qing"
+        "author_name": "Helena M. Tubb",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Xiangning Ding",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China"
+        "author_name": "Tommy Valles",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Lihua Luo",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China"
+        "author_name": "Caitlin E Tribelhorn",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Meiling Li",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China"
+        "author_name": "Rebecca Tsai",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Wensheng Zhang",
-        "author_inst": "School of Basic Medical Sciences, Binzhou Medical University, No. 346, Guanhai Road, Laishan District, Yantai City, Shandong, China"
+        "author_name": "Stefan Aigner",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Xin Jin",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China"
+        "author_name": "Shashank Sathe",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Jian Sun",
-        "author_inst": "National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, South China Agricultural University, Guangzhou, China; Guangdong L"
+        "author_name": "Niema Moshiri",
+        "author_inst": "Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Huan Liu",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China"
+        "author_name": "Benjamin Henson",
+        "author_inst": "Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA"
       },
       {
-        "author_name": "Dongsheng Chen",
-        "author_inst": "BGI-Shenzhen, Shenzhen 518083, China"
+        "author_name": "Abbas Hakim",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Nathan A Baer",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Tom Barber",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Pedro Belda-Ferre",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Marisol Chacon",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Willi Cheung",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Evelyn S Crescini",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Emily R Eisner",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Alma L Lastrella",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Elijah S Lawrence",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Clarisse A Marotz",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Toan T Ngo",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Tyler Ostrander",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Ashley Plascencia",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Rodolfo A Salido",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Phoebe Seaver",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Elizabeth W Smoot",
+        "author_inst": "Expedited COVID Identification Environment (EXCITE) Laboratory, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Daniel McDonald",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Robert M Neuhard",
+        "author_inst": "Operational Strategic Initiatives, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Angela L Scioscia",
+        "author_inst": "Student Health and Well-Being, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Alysson M. Satterlund",
+        "author_inst": "Student Affairs, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Elizabeth H Simmons",
+        "author_inst": "Academic Affairs, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Dismas B. Abelman",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "David Brenner",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Judith Carbone Bruner",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Anne Buckley",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Michael Ellison",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Jeffrey Gattas",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Steven L Gonias",
+        "author_inst": "Department of Pathology, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Matt Hale",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Faith Kirkham Hawkins",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Lydia Ikeda",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Hemlata Jhaveri",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Ted Johnson",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Vince Kellen",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Brendan Kremer",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Gary C. Matthews",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Ronald McLawhon",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Pierre Ouillet",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Daniel Park",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Allorah Pradenas",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Sharon Reed",
+        "author_inst": "Department of Pathology and Medicine, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Lindsay Riggs",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Alison M. Sanders",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Bradley Sollenberger",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Angela Song",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Benjamin White",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Terri Winbush",
+        "author_inst": "Return to Learn, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Christine M Aceves",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Catelyn Anderson",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Karthik Gangavarapu",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Emory Hufbauer",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Ezra Kurzban",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Justin Lee",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Nathaniel L Matteson",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Edyth Parker",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Sarah A Perkins",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Karthik S Ramesh",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Refugio Robles-Sikisaka",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Madison A Schwab",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Emily Spencer",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Shirlee Wohl",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Laura Nicholson",
+        "author_inst": "Scripps Health"
+      },
+      {
+        "author_name": "Ian H Mchardy",
+        "author_inst": "Scripps Health"
+      },
+      {
+        "author_name": "David P Dimmock",
+        "author_inst": "Rady Children's Institute for Genomic Medicine, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Charlotte A Hobbs",
+        "author_inst": "Rady Children's Institute for Genomic Medicine, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Omid Bakhtar",
+        "author_inst": "Sharp Healthcare, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Aaron Harding",
+        "author_inst": "Sharp Healthcare, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Art Mendoza",
+        "author_inst": "Sharp Healthcare, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Alexandre Bolze",
+        "author_inst": "Helix, San Mateo, CA, USA"
+      },
+      {
+        "author_name": "David Becker",
+        "author_inst": "Helix, San Mateo, CA, USA"
+      },
+      {
+        "author_name": "Elizabeth T Cirulli",
+        "author_inst": "Helix, San Mateo, CA, USA"
+      },
+      {
+        "author_name": "Magnus Isaksson",
+        "author_inst": "Helix, San Mateo, CA, USA"
+      },
+      {
+        "author_name": "Kelly M Schiabor Barrett",
+        "author_inst": "Helix, San Mateo, CA, USA"
+      },
+      {
+        "author_name": "Nicole L Washington",
+        "author_inst": "Helix, San Mateo, CA, USA"
+      },
+      {
+        "author_name": "John D Malone",
+        "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Ashleigh Murphy Schafer",
+        "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Nikos Gurfield",
+        "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Sarah Stous",
+        "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Rebecca Fielding-Miller",
+        "author_inst": "Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA; Division of Infectious Disease and Globa"
+      },
+      {
+        "author_name": "Tommi Gaines",
+        "author_inst": "Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Richard Garfein",
+        "author_inst": "Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Cheryl A. M. Anderson",
+        "author_inst": "Herbert Wertheim School of Public Health and Human Longevity Science , Division of Hypertension and Nephrology, University of California San Diego, La Jolla, CA"
+      },
+      {
+        "author_name": "Natasha K. Martin",
+        "author_inst": "Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Robert T Schooley",
+        "author_inst": "Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Brett Austin",
+        "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Duncan R. MacCannell",
+        "author_inst": "Office of Advanced Molecular Detection, Centers for Disease Control and Prevention, Atlanta, GA, USA"
+      },
+      {
+        "author_name": "Stephen F Kingsmore",
+        "author_inst": "Rady Children's Institute for Genomic Medicine, San Diego, CA, USA"
+      },
+      {
+        "author_name": "William Lee",
+        "author_inst": "Helix, San Mateo, CA, USA"
+      },
+      {
+        "author_name": "Seema Shah",
+        "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Eric McDonald",
+        "author_inst": "County of San Diego Health and Human Services Agency, San Diego, CA, USA"
+      },
+      {
+        "author_name": "Alexander T. Yu",
+        "author_inst": "COVID-19 Detection, Investigation, Surveillance, Clinical, and Outbreak Response, California Department of Public Health, Richmond, CA, USA"
+      },
+      {
+        "author_name": "Mark Zeller",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Kathleen M Fisch",
+        "author_inst": "Center for Computational Biology and Bioinformatics, Department of Obstetrics, Gynecology, and Reproductive Science"
+      },
+      {
+        "author_name": "Christopher A. Longhurst",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA; Department of Biomedical Informatics, University of California, San Diego, La J"
+      },
+      {
+        "author_name": "Patty Maysent",
+        "author_inst": "Office of the UC San Diego Health CEO, University of California, San Diego"
+      },
+      {
+        "author_name": "David Pride",
+        "author_inst": "Departments of Pathology and Medicine, University of California, San Diego, La Jolla, CA"
+      },
+      {
+        "author_name": "Pradeep K. Khosla",
+        "author_inst": "Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Louise C Laurent",
+        "author_inst": "Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA, Department of Obstetrics, Gynecology, and Reproductive Sciences, "
+      },
+      {
+        "author_name": "Gene W Yeo",
+        "author_inst": "Sanford Consortium of Regenerative Medicine, University of California San Diego, La Jolla, CA, Department of Cellular and Molecular Medicine, University of Cali"
+      },
+      {
+        "author_name": "Kristian G Andersen",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA, Scripps Research Translational Institute, La Jolla, CA, USA"
+      },
+      {
+        "author_name": "Rob Knight",
+        "author_inst": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA; Department of Bioengineering, University of California San Diego, La Jolla, CA,"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc_by_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.12.22.21268232",
@@ -417744,95 +419859,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.12.23.21267374",
-    "rel_title": "Immunogenicity and Safety Following a Homologous Booster Dose of a SARS-CoV-2 recombinant spike protein vaccine (NVX-CoV2373): A Phase 2 Randomized Placebo-Controlled Trial",
+    "rel_doi": "10.1101/2021.12.23.21268332",
+    "rel_title": "Extending upon: What effect might border screening have on preventing importation of COVID-19 compared with other infections? - Considering the additional effect of post-arrival isolation",
     "rel_date": "2021-12-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.23.21267374",
-    "rel_abs": "BackgroundEmerging SARS-CoV-2 variants and evidence of waning vaccine efficacy present significant obstacles toward controlling the COVID-19 pandemic. Booster doses of SARS-CoV-2 vaccines may address these concerns by both amplifying and broadening the immune responses seen with initial vaccination regimens.\n\nMethodsIn a phase 2 study, a single booster dose of a SARS-CoV-2 recombinant spike protein vaccine with Matrix-M adjuvant (NVX-CoV2373) was administered to healthy adult participants 18 to 84 years of age approximately 6 months following their primary two-dose vaccination series. Safety and immunogenicity parameters were assessed, including assays for IgG, MN50, and hACE2 receptor binding inhibition against the ancestral SARS-CoV-2 strain and select variants (B.1.351 [Beta], B.1.1.7 [Alpha], B.1.617.2 [Delta], and B.1.1.529 [Omicron]). This trial is registered with ClinicalTrials.gov, NCT04368988.\n\nFindingsAn incremental increase in the incidence of solicited local and systemic reactogenicity events was observed with subsequent vaccinations. Following the booster, incidence rates of local and systemic reactions were 82.5% (13.4% [&ge;] Grade 3) and 76.5% (15.3% [&ge;] Grade 3), respectively, compared to 70.0% (5.2% [&ge;] Grade 3) and 52.8% (5.6% [&ge;] Grade 3), respectively, following the primary vaccination series. Events were primarily mild or moderate in severity and transient in nature, with a median duration of 1.0 to 2.5 days. Immune responses seen 14 days following the primary vaccination series were compared with those observed 28 days following the booster (Day 35 and Day 217, respectively). For the ancestral SARS-CoV-2 strain, serum IgG geometric mean titers (GMTs) increased [~]4.7-fold from 43,905 ELISA units (EU) at day 35 to 204,367 EU at Day 217. Neutralization (MN50) assay GMTs showed a similar increase of [~]4.1-fold from 1,470 at day 35 to 6,023 at Day 217. A functional hACE2 receptor binding inhibition assay analyzing activity against ancestral and variant strains of SARS-CoV-2 at Day 189 vs Day 217 found 54.4-fold (Ancestral), 21.9-fold (Alpha), 24.5-fold (Beta), 24.4-fold (Delta), and 20.1-fold (Omicron) increases in titers. An anti-rS IgG activity assay comparing the same time points across the same SARS-CoV-2 strains found titers improved 61.2-fold, 85.9-fold, 65.0-fold, 92.5-fold, and 73.5-fold, respectively.\n\nInterpretationAdministration of a booster dose of NVX-CoV2373 approximately 6 months following the primary vaccination series resulted in an incremental increase in reactogenicity along with enhanced immune responses. For both the prototype strain and all variants evaluated, immune responses following the booster were notably higher than those associated with high levels of efficacy in phase 3 studies of the vaccine.\n\nFundingNovavax(R) and the Coalition for Epidemic Preparedness Innovations (CEPI(R)).",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.23.21268332",
+    "rel_abs": "We recently described a simple model through which we assessed what effect subjecting travellers to a single on-arrival test might have on reducing risk of importing disease cases during simulated outbreaks of COVID-19, Influenza, SARS, and Ebola. We build upon this work to allow for the additional requirement that inbound travellers also undergo a period of self-isolation upon arrival, where upon completion the traveller is again tested for signs of infection prior to admission across the border. Prior results indicated that a single on-arrival test has the potential to detect 9% of travellers infected with COVID-19, compared to 35%, 10% and 3% for travellers infected with influenza, SARS, and Ebola respectively. Our extended model shows that testing administered after a 2-day isolation period may be able to detect up to 41%, 97%, 44% and 15% of COVID-19, Influenza, SARS, and Ebola infected travellers respectively. Longer self-isolation periods increase detection rates further, with an 8-day self-isolation period suggesting detection rates of up to 94%, 100%, 98% and 62% for travellers infected with COVID-19, Influenza, SARS, and Ebola respectively. These results therefore suggest that testing arrivals after an enforced period of self-isolation may present a reasonable method of protecting against case importation during international outbreaks.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Raburn Mallory",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Neil Formica",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Susan Pfeiffer",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Bethanie Wilkinson",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Alex Marcheschi",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Gary Albert",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Heather McFall",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Michelle Robinson",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Joyce Plested",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "MingZhu Zhu",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Shane Cloney-Clark",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Bin Zhou",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Gordon Chau",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Andreana Robertson",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Sonia Maciejewski",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Gale Smith",
-        "author_inst": "Novavax"
-      },
-      {
-        "author_name": "Nita Patel",
-        "author_inst": "Novavax"
+        "author_name": "Declan Bays",
+        "author_inst": "United Kingdom Health Security Agency"
       },
       {
-        "author_name": "Gregory M Glenn",
-        "author_inst": "Novavax"
+        "author_name": "Emma Bennett",
+        "author_inst": "United Kingdom Health Security Agency"
       },
       {
-        "author_name": "Filip Dubovsky",
-        "author_inst": "Novavax"
+        "author_name": "Thomas James Ronald Finnie",
+        "author_inst": "United Kingdom Health Security Agency"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.12.22.21268253",
@@ -419558,77 +421609,41 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.12.22.21268265",
-    "rel_title": "Infrared spectroscopy enables rapid, robust, portable COVID-19 saliva screening based on pathophysiological response to SARS-CoV-2",
+    "rel_doi": "10.1101/2021.12.23.21267893",
+    "rel_title": "Echinacea as a Potential Force against Coronavirus Infections? A Mini-Review of Randomized Controlled Trials in Adults and Children",
     "rel_date": "2021-12-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268265",
-    "rel_abs": "Fourier-transform infrared (FTIR) spectroscopy provides a (bio)chemical snapshot of the sample, and was recently proposed for COVID-19 saliva screening in proof-of-concept cohort studies. As a step towards translation of this technology, we conducted controlled validation experiments in multiple biological systems. SARS-CoV-2 or UV-inactivated SARS-CoV-2 were used to infect Vero E6 cells in vitro, and K18-hACE2 mice in vivo. Potentially infectious culture supernatant or mouse oral lavage samples were treated with ethanol or Trizol to 75% (v/v) for attenuated total reflectance (ATR)-FTIR spectroscopy, or RT-PCR, respectively. The control condition, UV-inactivated SARS-CoV-2 elicited strong biochemical changes in culture supernatant/oral lavage despite lack of replication determined by RT-PCR or cell culture infectious dose 50%. Crucially, we show that active SARS-CoV-2 infection induced additional FTIR signals over the UV-inactivated SARS-CoV-2 infection, which correspond to innate immune response, aggregated proteins, and RNA. For human patient cohort prediction, we achieved high sensitivity of 93.48% on leave-on-out cross validation (n=104 participants) for predicting COVID-19 positivity using a partial least squares discriminant analysis model, in agreement with recent studies. However, COVID-19 patients negative on follow-up (RT-PCR on day of saliva sampling) were poorly predicted in this model. Importantly, COVID-19 vaccination did not lead to mis-classification of COVID-19 negatives. Meta-analysis revealed SARS-CoV-2 induced increase in Amide II band in all arms of this study and recent studies, indicative of altered {beta}-sheet structures in secreted proteins. In conclusion, ATR-FTIR is a robust, simple, portable method for COVID-19 saliva screening based on detection of pathophysiological responses to SARS-CoV-2.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.23.21267893",
+    "rel_abs": "Echinacea purpurea was shown to broadly inhibit coronaviruses and SARS-CoV-2 in vitro. This review discusses the available clinical evidence from randomized, blinded and controlled human studies. Two RCTs with results on enveloped viruses, respectively coronavirus infections during prevention treatment were detected. Incidence and/or viral loads were measured by RT-PCR and symptom severity was recorded. Jawad et al. (2012) collected nasopharyngeal swabs from adults (N=755) over 4 months of continuous prevention. Overall, 24 and 47 enveloped virus infections occurred, including 21 and 33 coronavirus detections [229E; HKU1; OC43] with Echinaforce(R) extract [2400mg daily] and placebo, respectively (p=0.0114). Ogal et al. (2021) administered the same extract [1200mg] or control for 4 months to children (4 - 12 years) (N=203). Echinacea reduced the incidence of enveloped virus infections from 47 to 29 (p=0.0038) whereas 11 and 13 coronavirus detections [229E, OC43, NL63] were counted (p>0.05). Respiratory symptoms during coronavirus infections were significantly lower with area-under-curve AUC=75.8 (+/-50.24) versus 27.1 (+/-21.27) score points (p=0.0036). Importantly, viral loads in nasal secretions were significantly reduced by 98.5%, with Ct-values 31.1 [95% CI 26.3; 35.9] versus 25.0 [95% CI 20.5; 29.5] (p = 0.0479). Results from clinical studies confirm the antiviral activity found for Echinacea in vitro, embracing enveloped respiratory pathogens and therefore coronaviruses as well. Substantiating results from a new completed study seems to extrapolate these effects to the prevention of SARS-CoV-2 infection. As hypothesized, the testified broad antiviral activity of Echinacea extract appears to be inclusive for SARS-CoV-2.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Seth Kazmer",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "Gunter Hartel",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "Harley Robinson",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "Renee  S Richards",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "Kexin Yan",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "Sebastiaan  J. Van Hal",
-        "author_inst": "NSW Health Pathology: New South Wales Health Pathology"
-      },
-      {
-        "author_name": "Raymond Chan",
-        "author_inst": "NSW Health Pathology: New South Wales Health Pathology"
+        "author_name": "Simon Nicolussi",
+        "author_inst": "iC-Cure scientific"
       },
       {
-        "author_name": "Andrew Hind",
-        "author_inst": "Agilent Technologies Australia"
+        "author_name": "Karin Ardjomand-Woelkart",
+        "author_inst": "Institute of Pharmaceutical Sciences, Department of Pharmacognosy, University Graz, Austria"
       },
       {
-        "author_name": "David Bradley",
-        "author_inst": "Agilent Technologies Australia"
+        "author_name": "Rainer Stange",
+        "author_inst": "Institute of Social Medicine, Epidemiology and Health Economics, Charite-Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Un"
       },
       {
-        "author_name": "Fabian Zieschang",
-        "author_inst": "Agilent Technologies Australia"
+        "author_name": "Giuseppe Gancitano",
+        "author_inst": "1st \"Tuscania\" Paratrooper Regiment Carabinieri, Italian Ministry of Defence, Livorno, Italy"
       },
       {
-        "author_name": "Daniel  J Rawle",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "Thuy  T Le",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "David  W Reid",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
-      },
-      {
-        "author_name": "Andreas Suhrbier",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
+        "author_name": "Peter Klein",
+        "author_inst": "d.s.h. statistical services GmbH, Rohrbach Germany"
       },
       {
-        "author_name": "Michelle  M Hill",
-        "author_inst": "QIMR Berghofer Medical Research Institute"
+        "author_name": "Mercedes Ogal",
+        "author_inst": "Pediatric clinic, Brunnen, Switzerland"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -421591,41 +423606,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.12.22.21268021",
-    "rel_title": "Omicron outbreak at a private gathering in the Faroe Islands, infecting 21 of 33 triple-vaccinated healthcare workers",
+    "rel_doi": "10.1101/2021.12.22.21268274",
+    "rel_title": "SARS-CoV-2 Antigen Tests Predict Infectivity Based on Viral Culture: Comparison of Antigen, PCR Viral Load, and Viral Culture Testing on a Large Sample Cohort",
     "rel_date": "2021-12-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268021",
-    "rel_abs": "There are concerns that the SARS-CoV-2 Omicron variant evades immune responses due to unusually high numbers of mutations on the spike protein. Here we report a super-spreading event of Omicron infections amongst triple-vaccinated healthcare workers, infecting 21 of 33 attending a private gathering in the Faroe Islands.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268274",
+    "rel_abs": "The relationship of SARS-CoV-2 antigen testing results, viral load, and viral culture detection remains to be fully defined. Presumptively, viral culture can provide a surrogate measure for infectivity of sampled individuals, and thereby inform how and where to most appropriately deploy available diagnostic testing modalities. We therefore determined the relationship of antigen testing results from three lateral flow and one microfluidics assay to viral culture performed in parallel in 181 nasopharyngeal swab samples positive for SARS-CoV-2. Sample viral loads, determined by RT-qPCR, were distributed across the range of viral load values observed in our testing population. We found that antigen tests were predictive of viral culture positivity, with the LumiraDx method showing enhanced sensitivity (90%; 95% confidence interval (95% CI) 83-94%) compared with the BD Veritor (74%, 95% CI 65-81%), CareStart (74%, 95% CI 65-81%) and Oscar Corona (74%, 95% CI 65-82%) lateral flow antigen tests. Antigen and viral culture positivity were also highly correlated with sample viral load, with areas under the receiver-operator characteristic curves (ROCs) of 0.94-0.97 and 0.92, respectively. In particular, a viral load threshold of 100,000 copies/mL was 95% sensitive (95% CI, 90-98%) and 72% specific (95% CI, 60-81%) for predicting viral culture positivity. Taken together, the detection of SARS-CoV-2 antigen identified highly infectious individuals, some of whom may harbor 10,000-fold more virus in their samples than those with any detectable infectious virus. As such, our data support use of antigen testing in defining infectivity status at the time of sampling.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Gunnhild Helmsdal",
-        "author_inst": "General Practitioner Service, Vestmanna, Faroe Islands"
+        "author_name": "James E Kirby",
+        "author_inst": "Beth Israel Deaconess Medical Center"
       },
       {
-        "author_name": "Olga Kristina Hansen",
-        "author_inst": "Office of the Chief Medical Officer, Torshavn, Faroe Islands"
+        "author_name": "Stefan Riedel",
+        "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School"
       },
       {
-        "author_name": "Lars Fodgaard Moller",
-        "author_inst": "Office of the Chief Medical Officer, Torshavn, Faroe Islands"
+        "author_name": "Sanjucta Dutta",
+        "author_inst": "Beth Israel Deaconess Medical Center"
       },
       {
-        "author_name": "Debes Hammershaimb Christiansen",
-        "author_inst": "Faroese Food and Veterinary Authority, Torshavn, Faroe Islands"
+        "author_name": "Ramy Arnaout",
+        "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School"
       },
       {
-        "author_name": "Maria Skaalum Petersen",
-        "author_inst": "The Faroese Hospital System, Torshavn, Faroe Islands"
+        "author_name": "Annie Cheng",
+        "author_inst": "Beth Israel Deaconess Medical Center"
       },
       {
-        "author_name": "Marnar Fridheim Kristiansen",
-        "author_inst": "University of the Faroe Islands, Torshavn, Faroe Islands"
+        "author_name": "Sarah Ditelberg",
+        "author_inst": "Beth Israel Deaconess Medical Center"
+      },
+      {
+        "author_name": "Donald J Hamel",
+        "author_inst": "Harvard School of Public Health"
+      },
+      {
+        "author_name": "Charlotte A. Chang",
+        "author_inst": "Harvard T.H.Chan School of Public Health"
+      },
+      {
+        "author_name": "Phyllis J. Kanki",
+        "author_inst": "Harvard T. H. Chan School of Public Health"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -423653,235 +425680,35 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.12.17.473248",
-    "rel_title": "SARS-CoV-2 Omicron spike mediated immune escape, infectivity and cell-cell fusion",
+    "rel_doi": "10.1101/2021.12.17.473140",
+    "rel_title": "Human genetic variants associated with COVID-19 severity are enriched in immune and epithelium regulatory networks",
     "rel_date": "2021-12-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.17.473248",
-    "rel_abs": "The SARS-CoV-2 Omicron BA.1 variant emerged in late 2021 and is characterised by multiple spike mutations across all spike domains. Here we show that Omicron BA.1 has higher affinity for ACE2 compared to Delta, and confers very significant evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralising antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralisation. Importantly, antiviral drugs remdesevir and molnupiravir retain efficacy against Omicron BA.1. We found that in human nasal epithelial 3D cultures replication was similar for both Omicron and Delta. However, in lower airway organoids, Calu-3 lung cells and gut adenocarcinoma cell lines live Omicron virus demonstrated significantly lower replication in comparison to Delta. We noted that despite presence of mutations predicted to favour spike S1/S2 cleavage, the spike protein is less efficiently cleaved in live Omicron virions compared to Delta virions. We mapped the replication differences between the variants to entry efficiency using spike pseudotyped virus (PV) entry assays. The defect for Omicron PV in specific cell types correlated with higher cellular RNA expression of TMPRSS2, and accordingly knock down of TMPRSS2 impacted Delta entry to a greater extent as compared to Omicron. Furthermore, drug inhibitors targeting specific entry pathways demonstrated that the Omicron spike inefficiently utilises the cellular protease TMPRSS2 that mediates cell entry via plasma membrane fusion. Instead, we demonstrate that Omicron spike has greater dependency on cell entry via the endocytic pathway requiring the activity of endosomal cathepsins to cleave spike. Consistent with suboptimal S1/S2 cleavage and inability to utilise TMPRSS2, syncytium formation by the Omicron spike was dramatically impaired compared to the Delta spike. Overall, Omicron appears to have gained significant evasion from neutralising antibodies whilst maintaining sensitivity to antiviral drugs targeting the polymerase. Omicron has shifted cellular tropism away from TMPRSS2 expressing cells that are enriched in cells found in the lower respiratory and GI tracts, with implications for altered pathogenesis.",
-    "rel_num_authors": 54,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.17.473140",
+    "rel_abs": "Human genetic variants can influence the severity of symptoms being infected with SARS-COV-2. Several genome-wide association studies have identified human genomic risk SNPs associated with COVID-19 severity. However, the causal tissues or cell types of COVID-19 severity are uncertain and candidate genes associated with these human risk SNPs were investigated in genomic proximity instead of their functional cellular contexts. Here, we compiled regulatory networks of 77 human contexts and revealed those risk SNPs enriched cellular contexts and associated transcript factors, regulatory elements, and target genes. Twenty-one human contexts were identified and grouped into two categories: immune cells and epithelium cells. We further aggregated the regulatory networks of immune cells, epithelium cells, and immune-epithelium crosstalk and investigated their association with risk SNPs regulation. Two genomic clusters, chemokine receptors cluster and OAS cluster, showed the strongest association with COVID-19 severity and different regulations in immune and epithelium contexts. Our findings were supported by analysis on both microarray and whole genome sequencing based GWAS summary statistics.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Bo Meng",
-        "author_inst": "University of Cambridge"
+        "author_name": "Zhanying Feng",
+        "author_inst": "Academy of Mathematics and System Science"
       },
       {
-        "author_name": "Isabella Ferreira",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Adam Abdullahi",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Niluka Goonawardane",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Akatsuki Saito",
-        "author_inst": "University of Miyazaki"
-      },
-      {
-        "author_name": "Izumi Kimura",
-        "author_inst": "The University of Tokyo"
-      },
-      {
-        "author_name": "Daichi Yamasoba",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Steven A Kemp",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Guido Papa",
-        "author_inst": "LMB Cambridge"
-      },
-      {
-        "author_name": "Saman Fatihi",
-        "author_inst": "CSIR Institute of Genomics and Integrative Biology, Delhi, India"
-      },
-      {
-        "author_name": "Surabhi Rathore",
-        "author_inst": "CSIR Institute of Genomics and Integrative Biology, Delhi, India"
-      },
-      {
-        "author_name": "Pehuen Perera Gerba",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Terumasa Ikeda",
-        "author_inst": "Kumamoto Univ"
-      },
-      {
-        "author_name": "Mako Toyoda",
-        "author_inst": "Kumamoto University, Kumamoto"
-      },
-      {
-        "author_name": "Toong Seng Tan",
-        "author_inst": "Kuramochi Clinic Interpark"
-      },
-      {
-        "author_name": "Jin Kuramochi",
-        "author_inst": "Kuramochi Clinic Interpark"
-      },
-      {
-        "author_name": "Shigeki Mitsunaga",
-        "author_inst": "National Institute of Genetics, Mishima, Shizuoka"
-      },
-      {
-        "author_name": "Takamasa Ueno",
-        "author_inst": "Kumamoto University, Kumamoto"
-      },
-      {
-        "author_name": "Oscar Charles",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Dami Collier",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "- CITIID-NIHR BioResource COVID-19 Collaboration",
-        "author_inst": "-"
-      },
-      {
-        "author_name": "- The Genotype to Phenotype Japan (G2P-Japan) Consortium",
-        "author_inst": "-"
-      },
-      {
-        "author_name": "- Ecuador-COVID19 Consortium",
-        "author_inst": "-"
-      },
-      {
-        "author_name": "John Bradley",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Jinwook Choi",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Kenneth Smith",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Elo Madissoon",
-        "author_inst": "Wellcome Sanger Institute"
-      },
-      {
-        "author_name": "Kerstin Meyer",
-        "author_inst": "Wellcome Sanger Institute"
-      },
-      {
-        "author_name": "Petra Mlcochova",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Rainer Doffinger",
-        "author_inst": "Cambridge University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Sarah A Teichmann",
-        "author_inst": "Cambridge University"
-      },
-      {
-        "author_name": "Leo James",
-        "author_inst": "MRC LMB"
-      },
-      {
-        "author_name": "Joo Hyeon Lee",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Teresa Brevini",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Matteo Pizzuto",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Myra Hosmillo",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Donna Mallery",
-        "author_inst": "MRC LMB Cambridge"
-      },
-      {
-        "author_name": "Samantha Zepeda",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Alexandra Walls",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Anshu Joshi",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "John Bowen",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "John Briggs",
-        "author_inst": "University of Heidelberg"
-      },
-      {
-        "author_name": "Alex Sigal",
-        "author_inst": "Africa Health Research Institute, Durban, South Africa"
-      },
-      {
-        "author_name": "Laurelle Jackson",
-        "author_inst": "Africa Health Research Institute, Durban, South Africa"
-      },
-      {
-        "author_name": "Sandile Cele",
-        "author_inst": "Africa Health Research Institute, Durban, South Africa"
-      },
-      {
-        "author_name": "Anna De Marco",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Fotios Sampaziotis",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Davide Corti",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "David Veesler",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Nicholas Matheson",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Ian Goodfellow",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Lipi Thukral",
-        "author_inst": "CSIR Institute of Genomics and Integrative Biology, Delhi, India"
+        "author_name": "Xianwen Ren",
+        "author_inst": "Peking University"
       },
       {
-        "author_name": "Kei Sato",
-        "author_inst": "The University of Tokyo"
+        "author_name": "Zhana Duren",
+        "author_inst": "Clemson University"
       },
       {
-        "author_name": "Ravindra K Gupta",
-        "author_inst": "University of Cambridge"
+        "author_name": "Yong Wang",
+        "author_inst": "Academy of mathematics and systems science, Chinese Academy of Sciences."
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "genetics"
   },
   {
     "rel_doi": "10.1101/2021.12.19.473380",
@@ -426098,89 +427925,49 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.12.20.21268134",
-    "rel_title": "Activity of convalescent and vaccine serum against a B.1.1.529 variant SARS-CoV-2 isolate",
+    "rel_doi": "10.1101/2021.12.20.21268124",
+    "rel_title": "SARS-CoV-2 vaccine effectiveness and breakthrough infections in maintenance dialysis patients",
     "rel_date": "2021-12-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.20.21268134",
-    "rel_abs": "The B.1.1.529 (Omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified in November of 2021 in South Africa and Botswana as well as in a sample of a traveler from South Africa in Hong Kong.1,2 Since then, B.1.1.529 has been detected in many countries globally. This variant seems to be more infectious than B.1.617.2 (Delta), has already caused super spreader events3 and has outcompeted Delta within weeks in several countries and metropolitan areas. B.1.1.529 hosts an unprecedented number of mutations in its spike gene and early reports have provided evidence for extensive immune escape and reduced vaccine effectiveness.2,4-6 Here, we investigated the neutralizing and binding activity of sera from convalescent, mRNA double vaccinated, mRNA boosted as well as convalescent double vaccinated and convalescent boosted individuals against wild type, B.1.351 and B.1.1.529 SARS-CoV-2 isolates. Neutralizing activity of sera from convalescent and double vaccinated participants was undetectable to very low against B.1.1.529 while neutralizing activity of sera from individuals who had been exposed to spike three or four times was maintained, albeit at strongly reduced levels. Binding to the B.1.1.529 receptor binding domain (RBD) and N-terminal domain (NTD) was reduced in convalescent not vaccinated but was mostly retained in vaccinated individuals.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.20.21268124",
+    "rel_abs": "BackgroundSARS-CoV-2 vaccine effectiveness during the Delta period and immunogenicity threshold associated with protection against COVID-19 related hospitalization or death in the dialysis population is unknown.\n\nMethodsA retrospective, observational study assessed SARS-CoV-2 vaccine effectiveness and immunogenicity threshold in all adult maintenance dialysis patients without COVID-19 history treated between February 1 and October 2, 2021. All COVID-19 infections, composite of hospitalization or death following COVID-19 and available SARS-CoV-2 anti-spike immunoglobulin (Ig) G values were extracted from electronic medical record. COVID-19 cases per 10,000 days at risk and vaccine effectiveness during pre-Delta and Delta periods were determined.\n\nResultsOf 15,718 patients receiving dialysis during the study period, 11,191 (71%) were fully vaccinated, 733 (5%) were partially vaccinated and 3,794 (24%) were unvaccinated. 967 COVID-19 were cases identified: 511 (53%) occurred in unvaccinated patients and 579 (60%) occurred during the Delta period. COVID-19 related hospitalization or death was less likely among vaccinated versus unvaccinated patients for all vaccines (adjusted HR 0.19 [0.12, 0.30]) and for BNT162b2/Pfizer, mRNA-1273/Moderna, and Ad26.COV2.S/Janssen (adjusted HR=0.25 [0.16, 0.40], 0.14 [0.08, 0.22], and 0.34 [0.17, 0.68] respectively). Among those with anti-spike IgG levels, those with IgG level [&ge;] 7 had significantly lower risk of a COVID-19 diagnosis (HR=0.25 [0.15, 0.42]) and none experienced a COVID-related hospitalization or death.\n\nConclusionsAmong maintenance dialysis patients, SARS-CoV-2 vaccination was associated with a lower risk of COVID-19 diagnosis and associated hospitalization or death. Among vaccinated patients, low anti-spike IgG level is associated with worse COVID-19 related outcomes.\n\nSignificance StatementSARS-CoV-2 vaccine effectiveness and association between antibody levels and clinical outcomes in maintenance dialysis patients is not known. Between February 1 and October 2, 2021, vaccine effectiveness was 85% against COVID-19 infection and 81% against composite of COVID-related hospitalization or death. COVID-19 case rates and severe outcomes were higher during the Delta dominant period (June 27-October 2, 2021). Increasing time (weeks) since full vaccination status was associated with increased risk for COVID-19 related hospitalization or death. Anti-spike IgG level [&ge;] 7 had lower risk of a COVID-19 diagnosis and no COVID-related hospitalization or death. Our findings supports utilization of SARS-CoV-2 vaccination and suggests that monitoring SARS-CoV-2 antibody levels and administering additional vaccine doses to maintain adequate immunity will be beneficial.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Juan Manuel Carreno",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Hala Alshammary",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Johnstone Tcheou",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Gagandeep Singh",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Ariel Raskin",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Hisaaki Kawabata",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Levy Sominsky",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Jordan Clark",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Daniel C. Adelsberg",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Dominika Bielak",
-        "author_inst": "ISMMS"
-      },
-      {
-        "author_name": "Ana Silvia Gonzalez-Reiche",
-        "author_inst": "ISMMS"
+        "author_name": "Harold J Manley",
+        "author_inst": "Dialysis Clinic Inc"
       },
       {
-        "author_name": "PSP/PARIS Study Group",
-        "author_inst": "ISMMS"
+        "author_name": "Gideon Aweh",
+        "author_inst": "dialysis clinic, inc"
       },
       {
-        "author_name": "Komal Srivastava",
-        "author_inst": "ISMMS"
+        "author_name": "Caroline M Hsu",
+        "author_inst": "Tufts Medical Center"
       },
       {
-        "author_name": "Emilia M Sordillo",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Daniel E Weiner",
+        "author_inst": "Tufts Medical Center"
       },
       {
-        "author_name": "Goran Bajic",
-        "author_inst": "ISMMS"
+        "author_name": "Dana Miskulin",
+        "author_inst": "Tufts Medical Center"
       },
       {
-        "author_name": "Harm van Bakel",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Antonia M Harford",
+        "author_inst": "Dialysis Clinic, Inc"
       },
       {
-        "author_name": "Viviana Simon",
-        "author_inst": "Icahn School of Medicine"
+        "author_name": "Doug Johnson",
+        "author_inst": "Dialysis Clinic, Inc."
       },
       {
-        "author_name": "Florian Krammer",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Eduardo K Lacson Jr.",
+        "author_inst": "Dialysis Clinic, Inc."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -427952,99 +429739,411 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.12.21.21267983",
-    "rel_title": "GB0139, an inhaled small molecule inhibitor of galectin-3, in COVID-19 pneumonitis: a randomised, controlled, open-label, phase 2a experimental medicine trial of the safety, pharmacokinetics, and potential therapeutic value",
+    "rel_doi": "10.1101/2021.12.19.21268028",
+    "rel_title": "Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa",
     "rel_date": "2021-12-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.21.21267983",
-    "rel_abs": "RationaleHigh galectin-3 levels predict poor outcomes in patients with COVID-19. Galectin-3 activates monocytes and macrophages which are directly implicated in COVID-19 immunopathology and the cytokine storm. GB0139 is a potent thiodigalactoside galectin-3 inhibitor and may reduce the severe effects of the disease. We report safety and pharmacokinetics and pharmacodynamics of the inhaled galectin-3 inhibitor, GB0139, and assess clinical outcomes and key systemic inflammatory biomarkers in hospitalised patients with COVID-19 (ClinicalTrials.gov/EudraCT identifier: NCT04473053/2020-002230-32).\n\nMethodsAdults with COVID-19 requiring oxygen, and with pneumonitis on x-ray, were randomised to receive standard of care (SOC; including dexamethasone; n=21) or SOC plus 10 mg GB0139 twice daily for 48 hours, then once daily for [&le;]14 days (n=20).\n\nResultsPatients aged 27-87 years were enrolled from July 2020; the final patient completed the 90-day follow-up in April 2021. GB0139+SOC was well tolerated with no treatment-related serious adverse events reported. Incidences of adverse events were similar between treatment arms (40 with GB0139+SOC vs 35 with SOC). Plasma GB0139 was measurable in all patients after inhaled exposure, with moderate interpatient variability, and demonstrated target engagement with decreased circulating galectin (overall treatment effect post-hoc over days 2-7: p=0{middle dot}0099 vs SOC). Rate of decline in fraction of inspired oxygen (%) requirement was significantly greater in the GB0139+SOC arm with a posterior mean difference of -1{middle dot}51 (95% highest posterior density: -2{middle dot}90, -0{middle dot}189) versus SOC. Plasma levels of biomarkers associated with inflammation, coagulopathy, major organ function and fibrosis showed a downward trend versus SOC.\n\nConclusionsGB0139+SOC was well tolerated and achieved clinically relevant plasma concentrations and target engagement. This, and the reduction in markers associated with inflammatory, coagulation, fibrosis, and reduction in inspired oxygen (%) over SOC alone, indicates the therapeutic potential for inhaled GB0139 in hospitalised patients with COVID-19.",
-    "rel_num_authors": 20,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.19.21268028",
+    "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.",
+    "rel_num_authors": 98,
     "rel_authors": [
       {
-        "author_name": "Erin Gaughan",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Raquel Viana",
+        "author_inst": "Lancet Laboratories, Johannesburg, South Africa"
       },
       {
-        "author_name": "Tariq Sethi",
-        "author_inst": "Galecto Inc."
+        "author_name": "Sikhulile Moyo",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana Harvard T.H. Chan School of Public health, Boston, Ma"
       },
       {
-        "author_name": "Tom Quinn",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Daniel Gyamfi Amoako",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
       },
       {
-        "author_name": "Nikhil Hirani",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Houriiyah Tegally",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa Centre"
+      },
+      {
+        "author_name": "Cathrine Scheepers",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Richard J Lessells",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa Centre"
       },
       {
-        "author_name": "Andrew Mills",
-        "author_inst": "Exploristics"
+        "author_name": "Jennifer Giandhari",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
       },
       {
-        "author_name": "Annya M. Bruce",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Nicole Wolter",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
       },
       {
-        "author_name": "Alison MacKinnon",
-        "author_inst": "Galecto Inc."
+        "author_name": "Josie Everatt",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
       },
       {
-        "author_name": "Vassilios Aslanis",
-        "author_inst": "Galecto Inc."
+        "author_name": "Andrew Rambaut",
+        "author_inst": "Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK"
       },
       {
-        "author_name": "Feng Li",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Christian Althaus",
+        "author_inst": "University of Bern"
       },
       {
-        "author_name": "Richard O'Connor",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Eduan Wilkinson",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University; Stellenbosch, South Africa"
       },
       {
-        "author_name": "Richard A. Parker",
-        "author_inst": "Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh"
+        "author_name": "Adriano Mendes",
+        "author_inst": "Zoonotic arbo and Resiratory virus program, Department Medical Virology, University of Pretoria, Pretoria, South Africa"
       },
       {
-        "author_name": "John Norrie",
-        "author_inst": "Edinburgh Clinical Trials Unit, Usher Institute, University of Edinburgh"
+        "author_name": "Amy Strydom",
+        "author_inst": "Zoonotic arbo and Resiratory virus program, Department Medical Virology, University of Pretoria, Pretoria, South Africa"
       },
       {
-        "author_name": "James Dear",
-        "author_inst": "Centre for Cardiovascular Science, University of Edinburgh"
+        "author_name": "Michaela Davids",
+        "author_inst": "Zoonotic arbo and Resiratory virus program, Department Medical Virology, University of Pretoria, Pretoria, South Africa"
       },
       {
-        "author_name": "Ahsan R. Akram",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Simnikiwe Mayaphi",
+        "author_inst": "Department Medical Virology University of Pretoria, Pretoria, South Africa National Health Laboratory Services, Thswane Academic Devision, Pretoria, South Afric"
       },
       {
-        "author_name": "Oliver Koch",
-        "author_inst": "Infectious Diseases Department, NHS Lothian"
+        "author_name": "Simani Gaseitsiwe",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana Department of Immunology and Infectious Diseases, Har"
+      },
+      {
+        "author_name": "Wonderful T Choga",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Dorcas Maruapula",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana"
       },
       {
-        "author_name": "Jie Wang-Jairaj",
-        "author_inst": "Galecto Inc."
+        "author_name": "Boitumelo Zuze",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana"
       },
       {
-        "author_name": "Robert J. Slack",
-        "author_inst": "Galecto Inc."
+        "author_name": "Botshelo Radibe",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana"
       },
       {
-        "author_name": "Lise Gravelle",
-        "author_inst": "Galecto Inc."
+        "author_name": "Legodile Koopile",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Botswana Harvard HIV Reference Laboratory, Gaborone, Botswana"
       },
       {
-        "author_name": "Bertil Lindmark",
-        "author_inst": "Galecto Inc."
+        "author_name": "Roger Shapiro",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Gaborone, Botswana Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Bos"
       },
       {
-        "author_name": "Kevin Dhaliwal",
-        "author_inst": "Centre for Inflammation Research, Edinburgh BioQuarter, University of Edinburgh"
+        "author_name": "Shahin Lockman",
+        "author_inst": "Botswana Harvard AIDS Institite Partnership, Gaborone, Botswana Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Bos"
+      },
+      {
+        "author_name": "Mpaphi B. Mbulawa",
+        "author_inst": "National Health Laboratory, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Thongbotho Mphoyakgosi",
+        "author_inst": "National Health Laboratory, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Pamela Smith-Lawrence",
+        "author_inst": "Health Services, Ministry of Health and Wellness, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Mosepele Mosepele",
+        "author_inst": "Department of Medicine, Faculty of Medicine, University of Botswana, Gaborone, Botswana Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana Botswana Pr"
+      },
+      {
+        "author_name": "Mogomotsi Matshaba",
+        "author_inst": "Botswana-Baylor Children's Clinical Centre of E cellence Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana Botswana Presidential COVID-19 Taskforce"
+      },
+      {
+        "author_name": "Kereng Masupu",
+        "author_inst": "Botswana Presidential COVID-19 Taskforce, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Mohammed Chand",
+        "author_inst": "Diagnofirm Medical Laboratories, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Charity Joseph",
+        "author_inst": "Diagnofirm Medical Laboratories, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Lesego Kuate-Lere",
+        "author_inst": "Ministry of Health and Wellness, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Onalethatha Lesetedi-Mafoko",
+        "author_inst": "Ministry of Health and Wellness, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Kgomotso Moruisi",
+        "author_inst": "Ministry of Health and Wellness, Gaborone, Botswana"
+      },
+      {
+        "author_name": "Lesley Scott",
+        "author_inst": "University of the Witwatersrand"
+      },
+      {
+        "author_name": "Wendy Stevens",
+        "author_inst": "University of the Witwatersrand"
+      },
+      {
+        "author_name": "Constantinos Kurt Wibmer",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Anele Mnguni",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Arshad Ismail",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Boitshoko Mahlangu",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Darren P. Martin",
+        "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa; Wellcome Centre for Infectious Diseases Research in Af"
+      },
+      {
+        "author_name": "Verity Hill",
+        "author_inst": "Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK"
+      },
+      {
+        "author_name": "Rachel Colquhoun",
+        "author_inst": "Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK"
+      },
+      {
+        "author_name": "Modisa S. Motswaledi",
+        "author_inst": "Department of Medical Laboratory Sciences, School of Allied Health Professions, Faculty of Health Sciences, University of Botswana,Gaborone, Botswana"
+      },
+      {
+        "author_name": "James Emmanuel San",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Noxolo Ntuli",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Gerald Motsatsi",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Sureshnee Pillay",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Thabo Mohale",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Upasana Ramphal",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Yeshnee Naidoo",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Naume Tebeila",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa Department of Veterinary Tropic"
+      },
+      {
+        "author_name": "Marta Giovanetti",
+        "author_inst": "FioCruz Foundation"
+      },
+      {
+        "author_name": "Koleka Mlisana",
+        "author_inst": "National Health Laboratory Service (NHLS), Johannesburg, South Africa Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Carolyn Williamson",
+        "author_inst": "Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa; National Health Laboratory Service (NHLS),South Africa"
+      },
+      {
+        "author_name": "Nei-yuan Hsiao",
+        "author_inst": "Division of Medical Virology, Faculty of Health Sciences, University of Cape Town and National Health Laboratory Service, Cape Town, South Africa National Healt"
+      },
+      {
+        "author_name": "Nokukhanya Msomi",
+        "author_inst": "National Health Laboratory Service (NHLS), Johannesburg, South Africa Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Kamela Mahlakwane",
+        "author_inst": "National Health Laboratory Service (NHLS), Johannesburg, South Africa Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Susan Engelbrecht",
+        "author_inst": "Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, South Africa;"
+      },
+      {
+        "author_name": "Tongai Maponga",
+        "author_inst": "Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, South Africa;"
+      },
+      {
+        "author_name": "Wolfgang Preiser",
+        "author_inst": "Division of Medical Virology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town, South Africa; National Health Laboratory S"
+      },
+      {
+        "author_name": "Zinhle Makatini",
+        "author_inst": "National Health Laboratory Service (NHLS), Johannesburg, South Africa National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Oluwakemi Laguda-Akingba",
+        "author_inst": "National Health Laboratory Service (NHLS), Johannesburg, South Africa Faculty of Health Sciences, Walter Sisulu University, Eastern Cape, South Africa"
+      },
+      {
+        "author_name": "Lavanya Singh",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Ugochukwu J. Anyaneji",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Monika Moir",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University; Stellenbosch, South Africa"
+      },
+      {
+        "author_name": "Stephanie van Wyk",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University; Stellenbosch, South Africa"
+      },
+      {
+        "author_name": "Derek Tshiabuila",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University; Stellenbosch, South Africa"
+      },
+      {
+        "author_name": "Yajna Ramphal",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University; Stellenbosch, South Africa"
+      },
+      {
+        "author_name": "Arisha Maharaj",
+        "author_inst": "Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University; Stellenbosch, South Africa"
+      },
+      {
+        "author_name": "Sergei Pond",
+        "author_inst": "Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Pennsylvania, USA"
+      },
+      {
+        "author_name": "Alexander G Lucaci",
+        "author_inst": "Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Pennsylvania, USA"
+      },
+      {
+        "author_name": "Steven Weaver",
+        "author_inst": "Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, Pennsylvania, USA"
+      },
+      {
+        "author_name": "Maciej F Boni",
+        "author_inst": "Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA"
+      },
+      {
+        "author_name": "Koen Deforche",
+        "author_inst": "Emweb bv, Herent, Belgium"
+      },
+      {
+        "author_name": "Kathleen Subramoney",
+        "author_inst": "National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Diana Hardie",
+        "author_inst": "Division of Medical Virology, Faculty of Health Sciences, University of Cape Town and National Health Laboratory Service, Cape Town, South Africa"
+      },
+      {
+        "author_name": "Gert Marais",
+        "author_inst": "Division of Medical Virology, Faculty of Health Sciences, University of Cape Town and National Health Laboratory Service, Cape Town, South Africa"
+      },
+      {
+        "author_name": "Deelan Doolabh",
+        "author_inst": "Division of Medical Virology, Faculty of Health Sciences, University of Cape Town,  Cape Town, South Africa"
+      },
+      {
+        "author_name": "Rageema Joseph",
+        "author_inst": "Division of Medical Virology, Faculty of Health Sciences, University of Cape Town,  Cape Town, South Africa"
+      },
+      {
+        "author_name": "Nokuzola Mbhele",
+        "author_inst": "Division of Medical Virology, Faculty of Health Sciences, University of Cape Town,  Cape Town, South Africa"
+      },
+      {
+        "author_name": "Luicer Olubayo",
+        "author_inst": "Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa)  Division of Computational Biology, Faculty of Health Sciences, Unversity of Cape Town"
+      },
+      {
+        "author_name": "Arash Iranzadeh",
+        "author_inst": "Division of Computational Biology, Faculty of Health Sciences, Unversity of Cape Town"
+      },
+      {
+        "author_name": "Alexander E Zarebski",
+        "author_inst": "Department of Zoology, University of Oxford, Mansfield Road, Oxford, Oxford OX1 3SZ, UK"
+      },
+      {
+        "author_name": "Joseph Tsui",
+        "author_inst": "Department of Zoology, University of Oxford, Mansfield Road, Oxford, Oxford OX1 3SZ, UK"
+      },
+      {
+        "author_name": "Moritz UG Kraemer",
+        "author_inst": "Department of Zoology, University of Oxford, Mansfield Road, Oxford, Oxford OX1 3SZ, UK"
+      },
+      {
+        "author_name": "Oliver G Pybus",
+        "author_inst": "Department of Zoology, University of Oxford, Mansfield Road, Oxford, Oxford OX1 3SZ, UK"
+      },
+      {
+        "author_name": "Dominique Goedhals",
+        "author_inst": "PathCare Vermaak, Pretoria, South Africa Division of Virology, University of the Free State, Bloemfontein, South Africa"
+      },
+      {
+        "author_name": "Phillip Armand Bester",
+        "author_inst": "Division of Virology, National Health Laboratory Service, Bloemfontein, South Africa Division of Virology, University of the Free State, Bloemfontein, South Afr"
+      },
+      {
+        "author_name": "Martin M Nyaga",
+        "author_inst": "Next Generation Sequencing Unit, University of the Free State, Bloemfontein, South Africa Division of Virology, University of the Free State, Bloemfontein, Sout"
+      },
+      {
+        "author_name": "Peter N Mwangi",
+        "author_inst": "Next Generation Sequencing Unit, University of the Free State, Bloemfontein, South Africa Division of Virology, University of the Free State, Bloemfontein, Sout"
+      },
+      {
+        "author_name": "Allison Glass",
+        "author_inst": "Lancet Laboratories, Johannesburg, South Africa; School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Florette Treurnicht",
+        "author_inst": "National Health Laboratory Service (NHLS), Johannesburg, South Africa"
+      },
+      {
+        "author_name": "Marietjie Venter",
+        "author_inst": "Zoonotic arbo and Respiratory virus research programme, Department Medical Virology, University of Pretoria;"
+      },
+      {
+        "author_name": "Jinal N. Bhiman",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa Faculty of Health Sciences, Uni"
+      },
+      {
+        "author_name": "Anne von Gottberg",
+        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa Faculty of Health Sciences, Uni"
+      },
+      {
+        "author_name": "Tulio de Oliveira",
+        "author_inst": "University of KwaZulu-Natal"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "respiratory medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.12.20.21267966",
@@ -429794,35 +431893,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.12.18.21267819",
-    "rel_title": "Knowledge, Attitude and Practices towards COVID 19 pandemic among homeless street young adults in Lusaka, Zambia: A Mixed Methods Approach",
+    "rel_doi": "10.1101/2021.12.18.21268026",
+    "rel_title": "Measurement of the extent of Anxiety and Depression that has occurred in college students due to the COVID 19 pandemic: An Survey based cross-sectional study.",
     "rel_date": "2021-12-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.18.21267819",
-    "rel_abs": "ObjectiveTo determine the knowledge, attitude and practices towards COVID-19 among homeless street young adults in Lusaka district, Zambia.\n\nMethodsA total of 89 young street adults aged between 16-35 years were sampled. A concurrent mixed methods approach was used, Structured questionnaires and focused group discussion, to achieve the objectives. STATA 13 was used to produce Descriptive statistics while thematic analysis was used to analyze the qualitative data.\n\nResultsMajority of the survey participants were male 67(78%), 55(62%) were single while 53(59%) had attained a Primary School Education. The majority of the participants received the COVID-19 information through the radio (61%). Only 44 (49%)% had adequate knowledge on Covid-19 of whom 70 (78.6%) had a positive attitude towards COVID-19. However, the 65(73%) had a low risk perception of contracting the disease. Further, 66 (74.2%) had a positive attitude towards the effectiveness of precautionary behaviors and measures. The finding also revealed that only 3(3.3%) had good practice towards the Covid-19 preventative measures overall with (SD:0).\n\nConclusionKnowledge and attitudes towards COVID-19 were quite high among homeless street adults. However, their good practices were alarmingly low. Specific strategies for them being a vulnerable group are required.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.18.21268026",
+    "rel_abs": "OVERVIEWThe ongoing Pandemic because of the Coronavirus disease 2019 (COVID-19) has caused all the educational institutes including colleges to be closed for a very long time. As a result the students are compelled to remain in their homes for this time. Prolonged stay at home along with excess use of social media and other modes to \"kill\" the time are quite famous to cause certain health issues in a person, specially the teenagers and adolescents. Mental wellbegin, being a dimension of health as per WHO should not be ignored at all specially in these situations.\n\nMETHOD OF STUDYAn Online Questionnaire is prepared based of the ZUNG Self Rating Anxiety and Self Rating Depression Scale (Pre-validated Scales). The Form is circulated digitally among the people and then we have collected the data in excel. Based on the result we have prepared our statistical chart.\n\nRESULTQuite a significant number of candidates were suffering due to the pandemic situation. 17.091% were suffering from mild to moderate anxiety, 1.785% had marked to severe anxiety levels(Constituting approximately 18.9% of the total). On the other hand, 8.673% of the students had mild depression, while 1 candidate (0.255%) had moderate depression and 1 (0.255%) had severe depression, (Constituting approximately 9.20% of the total). We found that candidates in the age group of 23-24 years had the maximum prevalence of depression, it was followed by candidates with age between 21-22 years. We found that the candidates with age between 23 to 24 years were having highest prevalence of significant anxiety levels which is closely followed by candidates having age which lies between 22 years to 23 years.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Kahilu Samuyachi",
-        "author_inst": "Keeping Girls in School Project-Ministry of Education, Lusaka, Zambia"
-      },
-      {
-        "author_name": "Mowa Zambwe",
-        "author_inst": "Workers Compensation Fund Control Board"
+        "author_name": "Shubham Goswami",
+        "author_inst": "Bankura Sammilani Medical College and Hospital"
       },
       {
-        "author_name": "Mutale Sampa",
-        "author_inst": "University of Zambia"
+        "author_name": "Soujanya Chakraborty",
+        "author_inst": "Bankura Sammilani Medical College and Hospital"
       },
       {
-        "author_name": "Peter J. Chipimo",
-        "author_inst": "Zambia National Public Health Institute"
+        "author_name": "Aritra Chakraborty",
+        "author_inst": "Bankura Sammilani Medical College and Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2021.12.17.21267987",
@@ -431740,63 +433835,91 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2021.12.17.21267968",
-    "rel_title": "Patients' and carers' experiences of, and engagement with remote home monitoring services for COVID-19 patients: a rapid mixed-methods study",
+    "rel_doi": "10.1101/2021.12.16.21267932",
+    "rel_title": "A Single Dose of COVID-19 mRNA Vaccine Induces Airway Immunity in COVID-19 Convalescent Patients",
     "rel_date": "2021-12-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.17.21267968",
-    "rel_abs": "IntroductionRemote home monitoring models were implemented during the COVID-19 pandemic to shorten hospital length of stay, reduce unnecessary hospital admission, readmission and infection, and appropriately escalate care. Within these models, patients are asked to take and record readings and escalate care if advised. There is limited evidence on how patients and carers experience these services. This study aimed to evaluate patient experiences of, and engagement with, remote home monitoring models for COVID-19.\n\nMethodsA rapid mixed-methods study in England. We conducted a cross-sectional survey and interviews with patients and carers. Interview findings were summarised using rapid assessment procedures sheets and grouping data into themes (using thematic analysis). Survey data were analysed using descriptive statistics.\n\nResultsWe received 1069 surveys (18% response rate) and conducted interviews with patients (n=59) and carers (n=3).  Care relied on support from staff members, and family/friends. Patients and carers reported positive experiences and felt that the service and human contact reassured them and was easy to engage with. Yet, some patients and carers identified problems with engagement. Engagement was influenced by: patient factors such as health and knowledge, support from family/friends and staff, availability and ease-of-use of informational and material resources (e.g. equipment), and service factors.\n\nConclusionRemote home monitoring models place responsibility on patients to self-manage symptoms in partnership with staff; yet many patients required support and preferred human contact (especially for identifying problems). Caring burden and experiences of those living alone, and barriers to engagement should be considered when designing and implementing remote home monitoring services.\n\nPatient or public contributionFor this evaluation, members of the study team met with service user and public members of the BRACE PPI group and Health and Care Panel and patient representatives from RSET in a series of workshops. These workshops informed study design, data collection tools, data interpretation and to discuss study dissemination for Phase 2. For example, patient facing documents, such as the consent form, topic guides, patient survey and patient information sheet were reviewed by this group. Additionally, PPI members helped to pilot patient surveys and interview guides with the research team. We also asked some members of the public to pilot the patient survey. Members of the PPI group were given the opportunity to comment on the manuscript. One PPI member commented on the manuscript and the manuscript was amended accordingly.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267932",
+    "rel_abs": "BackgroundMucosal antibodies can prevent virus entry and replication in mucosal epithelial cells and hence virus shedding. Preclinical and clinical studies have shown that a parenteral booster injection of a vaccine against a mucosal pathogen promotes stronger mucosal immune responses following prior infection compared to two injections of a parenteral vaccine. We investigated whether this was also the case for a COVID-19 mRNA vaccine.\n\nMethodsTwenty-three COVID-19 convalescent patients and 20 SARS-CoV-2-naive subjects were vaccinated with respectively one and two doses of the Pfizer-BioNTech COVID-19 RNA vaccine. Nasal Epithelial Lining Fluid (NELF) and plasma were collected before and after vaccination and assessed for Immunoglobulin (Ig)G and IgA to Spike and for their ability to inhibit the binding of Spike to its ACE-2 receptor. Blood was analyzed one week after vaccination for the number of Spike-specific Antibody Secreting Cells (ASCs) with a mucosal tropism.\n\nResultsIn COVID-19 convalescent patients, a single dose of vaccine amplified pre-existing Spike-specific IgG and IgA antibody responses in both NELF and blood against both vaccine homologous and variant strains, including delta. These responses were associated with Spike-specific IgG and IgA ASCs with a mucosal tropism in blood. Nasal IgA and IgG antibody responses were lower in magnitude in SARS-CoV-2-naive subjects after two vaccine doses\n\nConclusionThis study showed that a parenteral booster injection of a COVID-19 RNA vaccine promoted stronger mucosal immune responses in COVID-19 convalescent patients compared to SARS-CoV-2 naive subjects who had received a first vaccine dose.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Holly Walton",
-        "author_inst": "University College London"
+        "author_name": "Charles Hugo MARQUETTE",
+        "author_inst": "Universite Cote d'azur"
       },
       {
-        "author_name": "Cecilia Vindrola-Padros",
-        "author_inst": "University College London"
+        "author_name": "Emanuela MARTINUZZI",
+        "author_inst": "Universite Cote d'Azur, CNRS, Institut de Pharmacologie Moleculaire et Cellulaire, Valbonne, France"
       },
       {
-        "author_name": "Nadia Crellin",
-        "author_inst": "Nuffield Trust"
+        "author_name": "Jonathan BENZAQUEN",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice, Department of Pulmonary Medicine, CNRS, INSERM, Institute of Research on Cancer and Aging, Nic"
       },
       {
-        "author_name": "Manbinder S Sidhu",
-        "author_inst": "University of Birmingham"
+        "author_name": "Olivier GUERIN",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice. Pole rehabilitation autonomie viellissement, Nice, France"
       },
       {
-        "author_name": "Lauren Herlitz",
-        "author_inst": "University College London"
+        "author_name": "Sylvie LEROY",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice, Department of Pulmonary Medicine, CNRS, Institut de Pharmacologie Moleculaire et Cellulaire, N"
       },
       {
-        "author_name": "Ian Litchfield",
-        "author_inst": "University of Birmingham"
+        "author_name": "Thomas SIMON",
+        "author_inst": "Universite Cote d'Azur, CNRS, Institut de Pharmacologie Moleculaire et Cellulaire, Valbonne, France"
       },
       {
-        "author_name": "Jo Ellins",
-        "author_inst": "University of Birmingham"
+        "author_name": "Marius ILIE",
+        "author_inst": "Universite Cote d'Azur, CNRS, INSERM, Institute of Research on Cancer and Aging, Centre Hospitalier Universitaire de Nice, Laboratory of Clinical and Experiment"
       },
       {
-        "author_name": "Pei Li Ng",
-        "author_inst": "University College London"
+        "author_name": "Veronique HOFMAN",
+        "author_inst": "Universite Cote d'Azur, CNRS, INSERM, Institute of Research on Cancer and Aging, Centre Hospitalier Universitaire de Nice, Laboratory of Clinical and Experiment"
       },
       {
-        "author_name": "Efthalia Massou",
-        "author_inst": "University of Cambridge"
+        "author_name": "Maryline ALLEGRA",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice, Laboratory of Clinical and Experimental Pathology, Biobank (BB-0033-00025), FHU OncoAge, Centr"
       },
       {
-        "author_name": "Sonila M Tomini",
-        "author_inst": "University College London"
+        "author_name": "Virginie TANGA",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice, Laboratory of Clinical and Experimental Pathology, Biobank (BB-0033-00025), FHU OncoAge, Centr"
       },
       {
-        "author_name": "Naomi J Fulop",
-        "author_inst": "University College London"
+        "author_name": "Emeline MICHEL",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice. Pole rehabilitation autonomie viellissement, Nice, France"
+      },
+      {
+        "author_name": "Jacques BOUTROS",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice, Department of Pulmonary Medicine, FHU OncoAge, Nice, France"
+      },
+      {
+        "author_name": "Charlotte MANIEL",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice, Department of Pulmonary Medicine, FHU OncoAge, Nice, France"
+      },
+      {
+        "author_name": "Antoine SICARD",
+        "author_inst": "Universite Cote d'Azur, Centre Hospitalier Universitaire de Nice, Clinical Research Unit, Nice, France"
+      },
+      {
+        "author_name": "Nicolas GLAICHENHAUS",
+        "author_inst": "Universite Cote d'Azur, CNRS, Institut de Pharmacologie Moleculaire et Cellulaire, Valbonne, France"
+      },
+      {
+        "author_name": "Cecil CZERKINSKY",
+        "author_inst": "Universite Cote d'Azur, CNRS, Institut de Pharmacologie Moleculaire et Cellulaire, Valbonne, France"
+      },
+      {
+        "author_name": "Philippe BLANCOU",
+        "author_inst": "Universite Cote d'Azur, CNRS, Institut de Pharmacologie Moleculaire et Cellulaire, Valbonne, France"
+      },
+      {
+        "author_name": "Paul HOFMAN",
+        "author_inst": "Universite Cote d'Azur, CNRS, INSERM, Institute of Research on Cancer and Aging, Centre Hospitalier Universitaire de Nice, Laboratory of Clinical and Experiment"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health systems and quality improvement"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.12.17.21267925",
@@ -433390,111 +435513,75 @@
     "category": "geriatric medicine"
   },
   {
-    "rel_doi": "10.1101/2021.12.16.21267902",
-    "rel_title": "Waning of mRNA-1273 vaccine effectiveness against SARS-CoV-2 infection in Qatar",
+    "rel_doi": "10.1101/2021.12.16.21267703",
+    "rel_title": "Evaluation of SARS-CoV-2 Antibody Point of Care Devices in the Laboratory and Clinical Setting",
     "rel_date": "2021-12-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267902",
-    "rel_abs": "BACKGROUNDIn early 2021, Qatar launched a mass immunization campaign with Modernas mRNA-1273 COVID-19 vaccine. We assessed persistence of real-world mRNA-1273 effectiveness against SARS-CoV-2 infection and against COVID-19 hospitalization and death.\n\nMETHODSEffectiveness was estimated using test-negative, case-control study design, between January 1 and December 5, 2021. Effectiveness was estimated against documented infection (a PCR-positive swab, regardless symptoms), and against any severe (acute-care hospitalization), critical (ICU hospitalization), or fatal COVID-19.\n\nRESULTSBy December 5, 2021, 2,962 breakthrough infections had been recorded among those who received two mRNA-1273 doses. Of these infections, 19 progressed to severe COVID-19 and 4 to critical, but none to fatal disease. mRNA-1273 effectiveness against infection was negligible for the first two weeks after the first dose, increased to 65.5% (95% CI: 62.7-68.0%) 14 or more days after the first dose, and reached its peak at about 90% in the first three months after the second dose. Effectiveness declined gradually starting from the fourth month after the second dose and was below 50% by the 7th month after the second dose. Effectiveness against severe, critical, or fatal COVID-19 reached its peak at essentially 100% right after the second dose, and there was no evidence for declining effectiveness over time. Effectiveness against symptomatic versus asymptomatic infection demonstrated the same pattern of waning, but effectiveness against symptomatic infection was consistently higher than that against asymptomatic infection and waned more slowly.\n\nCONCLUSIONSmRNA-1273-induced protection against infection appears to wane month by month after the second dose. Meanwhile, protection against hospitalization and death appears robust with no evidence for waning for several months after the second dose.",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267703",
+    "rel_abs": "SARS-CoV-2 Antibody tests have been marketed to diagnose previous SARS-CoV-2 infection and as a test of immune status. There is a lack of evidence on the performance and clinical utility of these tests. We aimed to carry out an evaluation of 14 point of care (POC) SARS-CoV-2 antibody tests.\n\nSerum from participants with previous RT-PCR (Real-Time Polymerase chain reaction) confirmed SARS-CoV-2 infection and pre-pandemic controls were used to determine specificity and sensitivity of each POC device. Changes in sensitivity with increasing time from infection were determined on a cohort of participants. Corresponding neutralising antibody status was measured to establish whether the detection of antibodies by the POC device correlated with immune status. Paired capillary and serum samples were collected to ascertain whether POC devices performed comparably on capillary samples.\n\nSensitivity and specificity varied between the POC devices and in general did not meet the manufacturers reported performance characteristics signifying the importance of independent evaluation of these tests. The sensitivity peaked at >20 days following symptoms onset however sensitivity of 3 POC devices evaluated at extended time points showed that sensitivity declined with time and this was particularly marked at >140 days post infection onset. This is relevant if the tests are to be used for sero-prevelence studies. Neutralising antibody data showed positive antibody results on POC devices did not necessarily confer high neutralising antibody titres and these POC devices cannot be used to determine immune status to the SARS-CoV-2 virus. Comparison of paired serum and capillary results showed that there was a decline in sensitivity using capillary blood. This has implications in the utility of the test as they are designed to be used on capillary blood by the general population.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Laith J Abu-Raddad",
-        "author_inst": "Weill Cornell Medicine-Qatar"
-      },
-      {
-        "author_name": "Hiam Chemaitelly",
-        "author_inst": "Weill Cornell Medicine-Qatar"
-      },
-      {
-        "author_name": "Houssein H. Ayoub",
-        "author_inst": "Qatar University"
-      },
-      {
-        "author_name": "HADI M. YASSINE",
-        "author_inst": "Qatar University"
-      },
-      {
-        "author_name": "Fatiha Benslimane",
-        "author_inst": "Qatar University"
-      },
-      {
-        "author_name": "Heba A. Al Khatib",
-        "author_inst": "Qatar University"
-      },
-      {
-        "author_name": "Patrick Tang",
-        "author_inst": "Sidra Medicine"
-      },
-      {
-        "author_name": "Mohammad Rubayet Hasan",
-        "author_inst": "Sidra Medicine"
-      },
-      {
-        "author_name": "Peter Coyle",
-        "author_inst": "Hamad Medical Corporation"
-      },
-      {
-        "author_name": "Zaina Al Kanaani",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Kirsty McCance",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Einas Al Kuwari",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Helen Wise",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Andrew Jeremijenko",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Jennifer Simpson",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Anvar Hassan Kaleeckal",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Becky Bachelor",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Ali Nizar Latif",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Harriet Hale",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Riyazuddin Mohammad Shaik",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Linday McDonald",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Hanan F. Abdul Rahim",
-        "author_inst": "Qatar University"
+        "author_name": "Azul Zorzoli",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Gheyath Nasrallah",
-        "author_inst": "Qatar University"
+        "author_name": "Elizabeth Furrie",
+        "author_inst": "NHS Tayside"
       },
       {
-        "author_name": "Mohamed Ghaith Al Kuwari",
-        "author_inst": "Primary Health Care Corporation"
+        "author_name": "Charu Chopra",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Adeel A Butt",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Frauke Muecksch",
+        "author_inst": "Rocherfeller University"
       },
       {
-        "author_name": "Hamad Eid Al Romaihi",
-        "author_inst": "Ministry of Public Health"
+        "author_name": "Theodora Hatziioannou",
+        "author_inst": "Rockerfeller University"
       },
       {
-        "author_name": "Mohamed H. Al-Thani",
-        "author_inst": "Ministry of Public Health"
+        "author_name": "Paul Bieniasz",
+        "author_inst": "Rockerfeller University"
       },
       {
-        "author_name": "Abdullatif Al Khal",
-        "author_inst": "Hamad Medical Corporation"
+        "author_name": "Kate Templeton",
+        "author_inst": "NHS Lothian"
       },
       {
-        "author_name": "Roberto Bertollini",
-        "author_inst": "Ministry of Public Health"
+        "author_name": "Sara Jenks",
+        "author_inst": "NHS Lothian"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pathology"
   },
   {
     "rel_doi": "10.1101/2021.12.16.21267785",
@@ -435559,215 +437646,71 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.12.13.21267368",
-    "rel_title": "Acute COVID-19 severity and 16-month mental morbidity trajectories in patient populations of six nations",
+    "rel_doi": "10.1101/2021.12.14.21267418",
+    "rel_title": "COVID-19 vaccination and Guillain-Barre syndrome: analyses using the National Immunoglobulin Database",
     "rel_date": "2021-12-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267368",
-    "rel_abs": "BACKGROUNDThe aim of this multinational study was to assess the development of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis.\n\nMETHODSParticipants consisted of 247 249 individuals from seven cohorts across six countries (Denmark, Estonia, Iceland, Norway, Scotland, and Sweden) recruited from April 2020 through August 2021. We used multivariable Poisson regression to contrast symptom-prevalence of depression, anxiety, COVID-19 related distress, and poor sleep quality among individuals with and without a diagnosis of COVID-19 at entry to respective cohorts by time (0-16 months) from diagnosis. We also applied generalised estimating equations (GEE) analysis to test differences in repeated measures of mental health symptoms before and after COVID-19 diagnosis among individuals ever diagnosed with COVID-19 over time.\n\nFINDINGSA total of 9979 individuals (4%) were diagnosed with COVID-19 during the study period and presented overall with a higher symptom burden of depression (prevalence ratio [PR] 1{middle dot}18, 95% confidence interval [95% CI] 1{middle dot}03-1{middle dot}36) and poorer sleep quality (1{middle dot}13, 1{middle dot}03-1{middle dot}24) but not with higher levels of symptoms of anxiety or COVID-19 related distress compared with individuals without a COVID-19 diagnosis. While the prevalence of depression and COVID-19 related distress attenuated with time, the trajectories varied significantly by COVID-19 acute infection severity. Individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risks of depression and anxiety (PR 0{middle dot}83, 95% CI 0{middle dot}75-0{middle dot}91 and 0{middle dot}77, 0{middle dot}63-0{middle dot}94, respectively), while patients bedridden for more than 7 days were persistently at higher risks of symptoms of depression and anxiety (PR 1{middle dot}61, 95% CI 1{middle dot}27-2{middle dot}05 and 1{middle dot}43, 1{middle dot}26-1{middle dot}63, respectively) throughout the 16-month study period.\n\nCONCLUSIONAcute infection severity is a key determinant of long-term mental morbidity among COVID-19 patients.",
-    "rel_num_authors": 49,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267418",
+    "rel_abs": "Vaccination against viruses has rarely been associated with Guillain-Barre syndrome (GBS). An association with the COVID-19 vaccine is unknown. We performed a population-based study of National Health Service data in England and a multicentre surveillance study from UK hospitals, to investigate the relationship between COVID-19 vaccination and GBS.\n\nFirstly, case dates of GBS identified retrospectively in the National Immunoglobulin Database from 8 December 2021 to 8 July 2021 were linked to receipt dates of a COVID-19 vaccines using data from the National Immunisation Management System in England. For the linked dataset, GBS cases temporally associated with vaccination within a 6-week risk window of any COVID-19 vaccine were identified. Secondly, we prospectively collected incident UK-wide (four nations) GBS cases from 1 January 2021 to 7 November 2021 in a separate UK multicentre surveillance database. For this multicentre UK-wide surveillance dataset, we explored phenotypes of reported GBS cases to identify features of COVID-19 vaccine-associated GBS.\n\n996 GBS cases were recorded in the National Immunoglobulin Database from January to October 2021. A spike of GBS cases above the 2016-2020 average occurred in March-April 2021. 198 GBS cases occurred within 6 weeks of the first-dose COVID-19 vaccination in England (0.618 cases per 100,000 vaccinations, 176 ChAdOx1 nCoV-19 (AstraZeneca), 21 tozinameran (Pfizer), 1 mRNA-1273 (Moderna)). The 6-week excess of GBS (compared to the baseline rate of GBS cases 6-12 weeks after vaccination) occurs with a peak at 24 days post-vaccination; first-doses of ChAdOx1 nCoV-19 accounted for the excess. No excess was seen for second-dose vaccination. The absolute number of excess GBS cases from January-July 2021 was between 98-140 cases for first-dose ChAdOx1 nCoV-19 vaccination. First-dose tozinameran and second-dose of any vaccination showed no excess GBS risk. Detailed clinical data from 121 GBS patients were reported in the separate multicentre surveillance dataset during this timeframe. No phenotypic or demographic differences identified between vaccine-associated and non-vaccinated GBS cases occurring in the same timeframe.\n\nAnalysis of the linked NID/NIMS dataset suggests that first-dose ChAdOx1 nCoV-19 vaccination is associated with an excess GBS risk of 0.576 (95%CI 0.481-0.691) cases per 100,000 doses. However, examination of a multicentre surveillance dataset suggests that no specific clinical features, including facial weakness, are associated with vaccination-related GBS compared to non-vaccinated cases. The pathogenic cause of the ChAdOx1 nCoV-19 specific first dose link warrants further study.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Ingibjorg Magnusdottir",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Aniko Lovik",
-        "author_inst": "Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Anna Bara Unnarsdottir",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Daniel L. McCartney",
-        "author_inst": "Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK"
-      },
-      {
-        "author_name": "Helga Ask",
-        "author_inst": "Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway"
-      },
-      {
-        "author_name": "Kadri Koiv",
-        "author_inst": "Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia"
-      },
-      {
-        "author_name": "Lea Arregui Nordahl Christoffersen",
-        "author_inst": "Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Sverre Urnes Johnson",
-        "author_inst": "Department of Psychology, University of Oslo, Oslo, Norway"
-      },
-      {
-        "author_name": "Andrew M McIntosh",
-        "author_inst": "Division of Psychiatry, University of Edinburgh, Edinburgh, UK"
-      },
-      {
-        "author_name": "Anna K. Kahler",
-        "author_inst": "Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Archie Campbell",
-        "author_inst": "Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK"
-      },
-      {
-        "author_name": "Arna Hauksdottir",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Chloe Fawns-Ritchie",
-        "author_inst": "Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK"
-      },
-      {
-        "author_name": "Christian Erikstrup",
-        "author_inst": "Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark"
-      },
-      {
-        "author_name": "Dorte Helenius",
-        "author_inst": "Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Drew Altschul",
-        "author_inst": "Department of Psychology, University of Edinburgh, Edinburgh, UK"
-      },
-      {
-        "author_name": "Edda Bjork Thordardottir",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Elias Eythorsson",
-        "author_inst": "Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Emma M. Frans",
-        "author_inst": "Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Gunnar Tomasson",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Harpa Lind Jonsdottir",
-        "author_inst": "Faculty of Psychology, University of Iceland School of Health Sciences, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Harpa Runarsdottir",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Henrik Hjalgrim",
-        "author_inst": "Danish Cancer Society Research Center, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Hronn Hardardottir",
-        "author_inst": "Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland"
-      },
-      {
-        "author_name": "Juan Gonzalez-Hijon",
-        "author_inst": "Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Karina Banasik",
-        "author_inst": "Translational Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Khoa Manh Dinh",
-        "author_inst": "Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark"
-      },
-      {
-        "author_name": "Li Lu",
-        "author_inst": "Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway"
-      },
-      {
-        "author_name": "Lili Milani",
-        "author_inst": "Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia"
-      },
-      {
-        "author_name": "Lill Trogstad",
-        "author_inst": "Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway"
-      },
-      {
-        "author_name": "Maria Didriksen",
-        "author_inst": "Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark"
-      },
-      {
-        "author_name": "Omid V. Ebrahimi",
-        "author_inst": "Department of Psychology, University of Oslo, Oslo, Norway"
-      },
-      {
-        "author_name": "Patrick F. Sullivan",
-        "author_inst": "Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill, North Carolina, USA"
-      },
-      {
-        "author_name": "Per Minor Magnus",
-        "author_inst": "Centre of Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway"
-      },
-      {
-        "author_name": "Qing Shen",
-        "author_inst": "Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden"
-      },
-      {
-        "author_name": "Ragnar Nesvag",
-        "author_inst": "Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway."
-      },
-      {
-        "author_name": "Reedik Magi",
-        "author_inst": "Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia"
+        "author_name": "Ryan Yann Shern Keh",
+        "author_inst": "National Hospital for Neurology and Neurosurgery"
       },
       {
-        "author_name": "Runolfur Palsson",
-        "author_inst": "Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland"
+        "author_name": "Sophie Scanlon",
+        "author_inst": "Medicines and Healthcare products Regulatory Agency, UK"
       },
       {
-        "author_name": "Sisse Rye Ostrowski",
-        "author_inst": "Department of Clinical Immunology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark"
+        "author_name": "Preeti Datta-Nemdharry",
+        "author_inst": "Medicines and Healthcare products Regulatory Agency, UK"
       },
       {
-        "author_name": "Thomas Werge",
-        "author_inst": "Institute of Biological Psychiatry, Mental Health Services Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark"
+        "author_name": "Katherine Donegan",
+        "author_inst": "Medicines and Healthcare products Regulatory Agency, UK"
       },
       {
-        "author_name": "Asle Hoffart",
-        "author_inst": "Department of Psychology, University of Oslo, Oslo, Norway"
+        "author_name": "Sally Cavanagh",
+        "author_inst": "NHS England & Improvement (NHSEI), National Health Service, UK"
       },
       {
-        "author_name": "David J. Porteous",
-        "author_inst": "Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, UK"
+        "author_name": "Mark Foster",
+        "author_inst": "Medical Data Solutions and Services (MDSAS) Ltd, data platform provider for the National Immunoglobulin Database"
       },
       {
-        "author_name": "Fang Fang",
-        "author_inst": "Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden"
+        "author_name": "David Skelland",
+        "author_inst": "NHS Arden and Greater East Midlands (GEM) Commissioning Support Unit (CSU), UK"
       },
       {
-        "author_name": "Johanna Jakobsdottir",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
+        "author_name": "James Palmer",
+        "author_inst": "NHS England & Improvement (NHSEI), National Health Service, UK"
       },
       {
-        "author_name": "Kelli Lehto",
-        "author_inst": "Estonian Genome Centre, Institute of Genomics, University of Tartu, Estonia"
+        "author_name": "Pedro Machado",
+        "author_inst": "MRC Centre for Neuromuscular Diseases, National Hospital of Neurology and Neurosurgery, Queen Square, University College London Hospitals NHS Foundation Trust, "
       },
       {
-        "author_name": "Ole A. Andreassen",
-        "author_inst": "NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway"
+        "author_name": "Stephen Keddie",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Ole B.V. Pedersen",
-        "author_inst": "Department of Clinical Immunology, Zealand University Hospital, Denmark"
+        "author_name": "Aisling Carr",
+        "author_inst": "MRC Centre for Neuromuscular Diseases, National Hospital of Neurology and Neurosurgery, Queen Square, University College London Hospitals NHS Foundation Trust, "
       },
       {
-        "author_name": "Thor Aspelund",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
+        "author_name": "Michael Lunn",
+        "author_inst": "MRC Centre for Neuromuscular Diseases, National Hospital of Neurology and Neurosurgery, Queen Square, University College London Hospitals NHS Foundation Trust, "
       },
       {
-        "author_name": "Unnur Anna Valdimarsdottir",
-        "author_inst": "Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland"
+        "author_name": "- BPNS/ABN COVID-19 Vaccine GBS Study Group",
+        "author_inst": ""
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "neurology"
   },
   {
     "rel_doi": "10.1101/2021.12.14.21267773",
@@ -437805,33 +439748,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.12.10.21267574",
-    "rel_title": "Safety and immunogenicity of a heterologous booster of protein subunit vaccine MVC-COV1901 after two doses of adenoviral vector vaccine AZD1222",
+    "rel_doi": "10.1101/2021.12.10.21267582",
+    "rel_title": "Echinacea purpurea for the Long-term Prevention of Viral Respiratory Tract Infections during COVID-19 Pandemic: A Randomized, Open, Controlled, Exploratory Clinical Study",
     "rel_date": "2021-12-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.10.21267574",
-    "rel_abs": "We report the interim safety and immunogenicity results in participants administrated with a booster dose of protein subunit vaccine MVC-COV1901 at 12 or 24 weeks after two doses of AZD1222 (ChAdOx1 nCoV-19). In subjects fully vaccinated with two doses of AZD1222, waning antibody immunity was apparent within six months of the second dose of AZD1222. At one month after the MVC-COV1901 booster dose, anti-SARS-CoV-2 spike IgG antibody titers and neutralizing antibody titers were 14- and 8.6-fold increased, respectively, when compared to the titer levels on the day of the booster dose. We also observed 5.2- and 5.6-fold increases in neutralizing titer levels against wildtype and Omicron variant pseudovirus after the booster dose, respectively. These interim results support the use of MVC-COV1901 as a heterologous booster for individuals vaccinated with AZD1222.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.10.21267582",
+    "rel_abs": "IntroductionSARS-CoV-2 vaccination is effective in preventing severe COVID-19, but efficacy in reducing viral load and transmission wanes over time. In addition, the emergence of novel SARS-CoV-2 variants increases the threat of uncontrolled dissemination and additional antiviral therapies are urgently needed for effective containment. In previous in vitro studies Echinacea purpurea demonstrated strong antiviral activity against enveloped viruses, including SARS-CoV-2. In this study, we examined the potential of Echinacea purpurea in preventing and treating respiratory tract infections (RTIs) and in particular, SARS-CoV-2 infections.\n\nMethods120 healthy volunteers (m,f, 18 - 75 years) were randomly assigned to Echinacea prevention or control group without any intervention. After a run-in week, participants went through 3 prevention cycles of 2, 2 and 1 months with daily 2400mg Echinacea purpurea extract (Echinaforce(R), EF). The prevention cycles were interrupted by breaks of 1 week. Acute respiratory symptoms were treated with 4000 mg EF for up to 10 days, and their severity assessed via a diary. Naso/oropharyngeal swabs and venous blood samples were routinely collected every month and during acute illnesses for detection and identification of respiratory viruses, including SARS-CoV-2 via RT-qPCR and serology.\n\nResultsSummarized over all phases of prevention, 21 and 29 samples tested positive for any virus in the EF and control group, of which 5 and 14 samples tested SARS-CoV-2 positive (RR=0.37, Chi-square test, p=0.03). Overall, 10 and 14 symptomatic episodes occurred, of which 5 and 8 were COVID-19 (RR=0.70, Chi-square test, p>0.05). EF treatment when applied during acute episodes significantly reduced the overall virus load by at least 2.12 log10 or approx. 99% (t-test, p<0.05), the time to virus clearance by 8.0 days for all viruses (Wilcoxon test, p=0.02) and by 4.8 days for SARS-CoV-2 (p>0.05) in comparison to control. Finally, EF treatment significantly reduced fever days (1 day vs 11 days, Chi-square test, p=0.003) but not the overall symptom severity. There were fewer COVID-19 related hospitalizations in the EF treatment group (N=0 vs N=2).\n\nDiscussion/ConclusionEF exhibited antiviral effects and reduced the risk of viral RTIs, including SARS-CoV-2. By substantially reducing virus loads in infected subjects, EF offers a supportive addition to existing mandated treatments like vaccinations. Future confirmatory studies are warranted.\n\nClinical Trials registration NrNCT05002179",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Shu-Hsing Cheng",
-        "author_inst": "Taoyuan General Hospital"
+        "author_name": "Emil Kolev",
+        "author_inst": "Clinical Research Center DCC Convex Ltd"
       },
       {
-        "author_name": "Yi-Chun Lin",
-        "author_inst": "Taoyuan General Hospital"
+        "author_name": "Lilyana Mircheva",
+        "author_inst": "Convex ltd"
       },
       {
-        "author_name": "Cheng-Pin Chen",
-        "author_inst": "Taoyuan General Hospital"
+        "author_name": "Michael Edwards",
+        "author_inst": "National Heart Lung Institute, Imperial College London St Marys Campus"
       },
       {
-        "author_name": "Chien-Yu Cheng",
-        "author_inst": "Taoyuan General Hospital"
+        "author_name": "Sebastian L Johnston",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Krassimir Kalinov",
+        "author_inst": "Medistat Ltd. Statistical Services"
+      },
+      {
+        "author_name": "Rainer Stange",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Immanuel Hospital Berlin"
+      },
+      {
+        "author_name": "Giuseppe Gancitano",
+        "author_inst": "1st  \"Tuscania\" Paratrooper Regiment Carabinieri, Italian Ministry of Defence"
+      },
+      {
+        "author_name": "Wim Vanden Berghe",
+        "author_inst": "Laboratory of Protein Chemistry, Proteomics and Epigenetic Signaling (PPES)  and Integrated Personalized and Precision Oncology Network (IPPON),  Department of "
+      },
+      {
+        "author_name": "Samo Kreft",
+        "author_inst": "Faculty of Pharmacy, University of Ljubljana"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -439887,139 +441850,43 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.12.11.472236",
-    "rel_title": "Isolation and comparative analysis of antibodies that broadly neutralize sarbecoviruses",
+    "rel_doi": "10.1101/2021.12.13.21267761",
+    "rel_title": "SARS-CoV-2 Omicron variant escapes neutralization by vaccinated and convalescent sera and therapeutic monoclonal antibodies",
     "rel_date": "2021-12-14",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.11.472236",
-    "rel_abs": "The devastation caused by SARS-CoV-2 has made clear the importance of pandemic preparedness. To address future zoonotic outbreaks due to related viruses in the sarbecovirus subgenus, we identified a human monoclonal antibody, 10-40, that neutralized or bound all sarbecoviruses tested in vitro and protected against SARS-CoV-2 and SARS-CoV in vivo. Comparative studies with other receptor-binding domain (RBD)-directed antibodies showed 10-40 to have the greatest breadth against sarbecoviruses and thus its promise as an agent for pandemic preparedness. Moreover, structural analyses on 10-40 and similar antibodies not only defined an epitope cluster in the inner face of the RBD that is well conserved among sarbecoviruses, but also uncovered a new antibody class with a common CDRH3 motif. Our analyses also suggested that elicitation of this class of antibodies may not be overly difficult, an observation that bodes well for the development of a pan-sarbecovirus vaccine.\n\nOne sentence summaryA monoclonal antibody that neutralizes or binds all sarbecoviruses tested and represents a reproducible antibody class.",
-    "rel_num_authors": 30,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267761",
+    "rel_abs": "The novel SARS-CoV-2 variant, Omicron (B.1.1.529) contains about 30 mutations in the spike protein and the numerous mutations raise the concern of escape from vaccine, convalescent sera and therapeutic drugs. Here we analyze the alteration of their neutralizing titer with Omicron pseudovirus. Sera of 3 months after double BNT162b2 vaccination exhibite [~]27-fold lower neutralization titers against Omicron than D614G mutation. Neutralization titer is also reduced in convalescent sera from Alpha and Delta patients. However, some Delta patients have relatively preserved neutralization activity up to the level of 3-month double BNT162b2 vaccination. Omicron escapes from the cocktail of imdevimab and casirivimab, whereas sotrovimab that targets the conserved region to prevent viral escape is effective to Omicron similarly to the original SARS-CoV-2. The ACE2 decoy is another modality that neutralize the virus independently of mutational escape and Omicron is also sensitive to the engineered ACE2.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Lihong Liu",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Sho Iketani",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Yicheng Guo",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Ryan Casner",
-        "author_inst": "Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA"
-      },
-      {
-        "author_name": "Eswar Reddem",
-        "author_inst": "Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA"
-      },
-      {
-        "author_name": "Manoj S. Nair",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Jian Yu",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Jasper Chan",
-        "author_inst": "State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University"
-      },
-      {
-        "author_name": "Maple Wang",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Gabriele Cerutti",
-        "author_inst": "Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA"
-      },
-      {
-        "author_name": "Zhiteng Li",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Candace Castagna",
-        "author_inst": "Institute of Comparative Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA"
-      },
-      {
-        "author_name": "Laura Corredor",
-        "author_inst": "Institute of Comparative Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA"
-      },
-      {
-        "author_name": "Hin Chu",
-        "author_inst": "State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University"
-      },
-      {
-        "author_name": "Shuofeng Yuan",
-        "author_inst": "State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University"
-      },
-      {
-        "author_name": "Vincent Poon",
-        "author_inst": "State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University"
-      },
-      {
-        "author_name": "Chris Chan",
-        "author_inst": "State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University"
-      },
-      {
-        "author_name": "Zhiwei Chen",
-        "author_inst": "State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University"
-      },
-      {
-        "author_name": "Yang Luo",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Marcus Cunningham",
-        "author_inst": "Hackensack Meridian Health Center for Discovery and Innovation, Nutley, NJ 07110, USA"
-      },
-      {
-        "author_name": "Alejandro Chavez",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA"
-      },
-      {
-        "author_name": "Michael Yin",
-        "author_inst": "Division of Infectious Diseases, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA"
-      },
-      {
-        "author_name": "David Perlin",
-        "author_inst": "Hackensack Meridian Health Center for Discovery and Innovation, Nutley, NJ 07110, USA"
-      },
-      {
-        "author_name": "Moriya Tsuji",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
-      },
-      {
-        "author_name": "Kwok-Yung Yuen",
-        "author_inst": "State Key Laboratory of Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University"
+        "author_name": "Nariko Ikemura",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Peter Kwong",
-        "author_inst": "Vaccine Research Center, National Institutes of Health, Bethesda, MD 20892, USA"
+        "author_name": "Atsushi Hoshino",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Zizhang Sheng",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
+        "author_name": "Yusuke Higuchi",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Yaoxing Huang",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
+        "author_name": "Shunta Taminishi",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "Lawrence Shapiro",
-        "author_inst": "Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA"
+        "author_name": "Tohru Inaba",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       },
       {
-        "author_name": "David D. Ho",
-        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032"
+        "author_name": "Satoaki Matoba",
+        "author_inst": "Kyoto Prefectural University of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_by_nc",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.12.13.21267748",
@@ -441597,79 +443464,47 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.12.12.472286",
-    "rel_title": "The Omicron variant is highly resistant against antibody-mediated neutralization - implications for control of the COVID-19 pandemic",
-    "rel_date": "2021-12-13",
+    "rel_doi": "10.1101/2021.12.09.471735",
+    "rel_title": "The T cell receptor repertoire reflects the dynamics of the immune response to vaccination",
+    "rel_date": "2021-12-12",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.12.472286",
-    "rel_abs": "The rapid spread of the SARS-CoV-2 Omicron variant suggests that the virus might become globally dominant. Further, the high number of mutations in the viral spike-protein raised concerns that the virus might evade antibodies induced by infection or vaccination. Here, we report that the Omicron spike was resistant against most therapeutic antibodies but remained susceptible to inhibition by Sotrovimab. Similarly, the Omicron spike evaded neutralization by antibodies from convalescent or BNT162b2-vaccinated individuals with 10- to 44-fold higher efficiency than the spike of the Delta variant. Neutralization of the Omicron spike by antibodies induced upon heterologous ChAdOx1/BNT162b2-vaccination or vaccination with three doses of BNT162b2 was more efficient, but the Omicron spike still evaded neutralization more efficiently than the Delta spike. These findings indicate that most therapeutic antibodies will be ineffective against the Omicron variant and that double immunization with BNT162b2 might not adequately protect against severe disease induced by this variant.",
-    "rel_num_authors": 15,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.09.471735",
+    "rel_abs": "Early, high-resolution metrics are needed to ascertain the immune response to vaccinations. The T cell receptor (TCR), a heterodimer of one  and one {beta} chain, is a promising target, with the complete TCR repertoire reflecting the T cells present in an individual. To this end, we developed Tseek, an unbiased and accurate method for profiling the TCR repertoire by sequencing the TCR  and {beta} chains and developing a suite of tools for repertoire analysis. An added advantage is the ability to non-invasively analyze T cells in peripheral blood mononuclear cells (PBMCs). Tseek and the analytical suite were used to explore the T cell response to both the COVID-19 mRNA vaccine (n=9) and the seasonal inactivated Influenza vaccine (n=5) at several time points. Neutralizing antibody titers were also measured in the covid vaccine samples. The COVID-19 vaccine elicited a broad T cell response involving multiple expanded clones, whereas the Influenza vaccine elicited a narrower response involving fewer clones. Many distinct T cell clones responded at each time point, over a month, providing temporal details lacking in the antibody measurements, especially before the antibodies are detectable. In individuals recovered from a SARS-CoV-2 infection, the first vaccine dose elicited a robust T cell response, while the second dose elicited a comparatively weaker response, indicating a saturation of the response. The physical symptoms experienced by the recipients immediately following the vaccinations were not indicative of the TCR/antibody responses. The TCR responses broadly presaged the antibody responses. We also found that the TCR repertoire acts as an individual fingerprint: donors of blood samples taken years apart could be identified solely based upon their TCR repertoire, hinting at other surprising uses the TCR repertoire may have. These results demonstrate the promise of TCR repertoire sequencing as an early and sensitive measure of the adaptive immune response to vaccination, which can help improve immunogen selection and optimize vaccine dosage and spacing between doses.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Markus Hoffmann",
-        "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut f\u00fcr Primatenforschung"
+        "author_name": "Kevin Mohammed",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, NY 10029"
       },
       {
-        "author_name": "Nadine Kr\u00fcger",
-        "author_inst": "Deutsches Primatenzentrum - Leibniz Institut f\u00fcr Primatenforschung"
-      },
-      {
-        "author_name": "Sebastian Schulz",
-        "author_inst": "Friedrich-Alexander-Universit\u00e4 Erlangen-N\u00fcrnberg"
-      },
-      {
-        "author_name": "Anne Cossmann",
-        "author_inst": "Medizinische Hochschule Hannover"
-      },
-      {
-        "author_name": "Cheila Rocha",
-        "author_inst": "Deutsches Primatenzentrum - Leibniz Institut f\u00fc Primatenforschung"
-      },
-      {
-        "author_name": "Amy Kempf",
-        "author_inst": "Deutsches Primatenzentrum - Leibniz Institut f\u00fcr Primatenforschung"
+        "author_name": "Austin Meadows",
+        "author_inst": "Girihlet Inc., 355 30th St., Oakland, CA 94609"
       },
       {
-        "author_name": "Inga Nehlmeier",
-        "author_inst": "Deutsches Primatenzentrum - Leibniz Institut f\u00fcr Primatenforschung"
-      },
-      {
-        "author_name": "Luise Graichen",
-        "author_inst": "Deutsches Primatenzentrum - Leibniz Institut f\u00fcr Primatenforschung"
-      },
-      {
-        "author_name": "Anna-Sophie Moldenhauer",
-        "author_inst": "Deutsches Primatenzentrum - Leibniz Institut f\u00fcr Primatenforschung"
-      },
-      {
-        "author_name": "Martin Sebastian Winkler",
-        "author_inst": "Universit\u00e4tsmedizin G\u00f6ttingen"
-      },
-      {
-        "author_name": "Martin Lier",
-        "author_inst": "Universit\u00e4tsmedizin G\u00f6ttingen"
+        "author_name": "Sandra Hatem",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, NY 10029"
       },
       {
-        "author_name": "Alexandra Dopfer-Jablonka",
-        "author_inst": "Medizinische Hochschule Hannover"
+        "author_name": "Saboor Hekmaty",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Hans-Martin J\u00e4ck",
-        "author_inst": "Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg"
+        "author_name": "Viviana Simon",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, NY 10029"
       },
       {
-        "author_name": "Georg Behrens",
-        "author_inst": "Medizinische Hochschule Hannover"
+        "author_name": "Anitha D Jayaprakash",
+        "author_inst": "Girihlet Inc., 355 30th St, Oakland, CA 94609"
       },
       {
-        "author_name": "Stefan P\u00f6hlmann",
-        "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut f\u00fcr Primatenforschung"
+        "author_name": "Ravi Sachidanandam",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "microbiology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.12.10.21267590",
@@ -443875,59 +445710,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.12.10.21267338",
-    "rel_title": "Mental health indicators in Sweden over a 12-month period during the COVID-19 pandemic",
+    "rel_doi": "10.1101/2021.12.09.21267349",
+    "rel_title": "Down-regulation of SARS-CoV-2 neutralizing antibodies in vaccinated smokers",
     "rel_date": "2021-12-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.10.21267338",
-    "rel_abs": "BackgroundThe ongoing COVID-19 pandemic has had an unprecedented impact on the lives of people globally and is expected to have profound effects on mental health. Yet, self-reported large-scale online surveys on mental health are still relatively uncommon. Here we aim to describe the mental health burden experienced in Sweden using baseline data of the Omtanke2020 Study.\n\nMethodSelf-reported baseline data collected over a 12-month period (June 9, 2020-June 8, 2021) from the longitudinal online survey of the Omtanke2020 Study including 27,950 adults in Sweden. Participants were volunteers or actively recruited through existing cohorts and after providing informed consent responded to monthly online questionnaires on socio-demographics, mental and physical health, COVID-19 infection, and impact. Poisson regression was fitted to assess the relative risk of high mental health burden (depression, anxiety, and COVID-19 specific PTSD).\n\nResultThe overall proportion of persons with high level of symptoms was 15.6%, 9.5% and 24.5% for depression, anxiety, and COVID-19 specific PTSD, respectively. Overall, 43.4% of the participants had significant, clinically relevant symptoms for at least one mental health outcome and 7.3% had significant symptoms for all three outcomes. We also observed differences in the prevalence of these symptoms across strata of sex, age, recruitment type, COVID-19 status, region, and seasonality.\n\nConclusionWhile the proportion of persons with high mental health burden remains higher than in pre-pandemic publications, our estimates are lower than previously reported levels of depression, anxiety, and PTSD during the pandemic in Sweden and elsewhere.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267349",
+    "rel_abs": "Vaccination is an effective approach to help control coronavirus disease 2019 (COVID-19). However, since the vaccines produce a heterogenous immune response, the risk of breakthrough infection is increased in vaccinated individuals who generate low levels of neutralizing antibodies (NAbs). It is therefore paramount in the fight against COVID-19 to identify individuals who have a higher risk of breakthrough infection despite being vaccinated. Here we addressed the effect of cigarette smoking on the production of neutralizing antibodies (NAbs) following COVID-19 vaccination since smoking profoundly suppresses the adaptive immune response to pathogen infection and the association between vaccination and smoking remains unclear. The SARS-CoV-2 Spike antibodies and NAbs (days 0, 14, 42, and 90) were measured in 164 participants received two vaccine doses of an inactivated vaccine (Sinovac-CoronaVac) longitudinally. Anti-Spike antibodies was elevated 14 and 42 days after COVID-19 vaccination compared to baseline (i.e., \"Day 0\"). Notably, RBD antibodies showed significantly higher expression in the nonsmoking group (n=153) than the smoking (n=11) group on day 42 (p<0.0001, Students t-test). NAbs continually increased after the first and second vaccine dose, peaking on day 42. NAbs titers then significantly decreased until day 90. Compared to nonsmokers, the NAb levels in smokers remained low throughout the period of testing. The median NAb titers in the smoking group was 1.40-, 1.32-, or 3.00-fold lower than that of nonsmoking group on day 14, 42, or 90, respectively. Altogether, our results indicate that smoking is a specific risk factor for COVID-19 breakthrough infection following vaccination.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Anik\u00f3 Lovik",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Juan Gonz\u00e1lez-Hij\u00f3n",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Anna K. K\u00e4hler",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Unnur A. Valdimarsd\u00f3ttir",
-        "author_inst": "University of Iceland, Karolinska Institutet"
+        "author_name": "Jiahui Zhang",
+        "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom"
       },
       {
-        "author_name": "Emma M. Frans",
-        "author_inst": "Karolinska Institutet"
+        "author_name": "Fei Teng",
+        "author_inst": "Emergency Medicine Clinical Research Center, Beijing Chao-Yang Hospital, Capital Medical University, & Beijing Key Laboratory of Cardiopulmonary Cerebral Resusc"
       },
       {
-        "author_name": "Nancy L. Pedersen",
-        "author_inst": "Karolinska Institutet"
+        "author_name": "Xiaomei Zhang",
+        "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom"
       },
       {
-        "author_name": "Per Hall",
-        "author_inst": "Karolinska Institutet"
+        "author_name": "Hongye Wang",
+        "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom"
       },
       {
-        "author_name": "Kamila Czene",
-        "author_inst": "Karolinska Institutet"
+        "author_name": "Te Liang",
+        "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom"
       },
       {
-        "author_name": "Patrick F. Sullivan",
-        "author_inst": "University of North Carolina, Karolinska Institutet"
+        "author_name": "Shu-Bin Guo",
+        "author_inst": "Emergency Medicine Clinical Research Center, Beijing Chao-Yang Hospital, Capital Medical University, & Beijing Key Laboratory of Cardiopulmonary Cerebral Resusc"
       },
       {
-        "author_name": "Fang Fang",
-        "author_inst": "Karolinska Institutet"
+        "author_name": "xiaobo yu",
+        "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.12.09.21267545",
@@ -445693,87 +447516,123 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.12.07.471590",
-    "rel_title": "A novel bacterial protease inhibitor adjuvant in RBD-based COVID-19 vaccine formulations increases neutralizing antibodies, specific germinal center B cells and confers protection against SARS-CoV-2 infection.",
+    "rel_doi": "10.1101/2021.12.08.471814",
+    "rel_title": "Nanotrap Particles Improve Nanopore Sequencing of SARS-CoV-2 and Other Respiratory Viruses",
     "rel_date": "2021-12-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.07.471590",
-    "rel_abs": "In this work we evaluated recombinant receptor binding domain (RBD) based vaccine formulation prototypes with potential for further clinical development. We assessed different formulations containing RBD plus Alum, AddaS03, AddaVax or the combination of Alum and U-Omp19: a novel Brucella spp. protease inhibitor vaccine adjuvant. Results show that the vaccine formulation composed of U-Omp19 and Alum as adjuvants have a better performance: it significantly increased mucosal and systemic neutralizing antibodies in comparison to antigen plus Alum, AddaVax or AddaS03. Antibodies induced with the formulation containing U-Omp19 not only increased their neutralization capacity against the wild-type virus but also cross neutralized alpha, lambda and gamma variants with similar potency. Also, addition of U-Omp19 to vaccine formulation increased the frequency of RBD-specific geminal center B cells and plasmablasts. Additionally, U-Omp19+Alum formulation induced RBD-specific Th1 and CD8+ T cell responses in spleens and lungs. Finally, this vaccine formulation conferred protection against an intranasal SARS-CoV-2 challenge of K18-hACE2 mice.",
-    "rel_num_authors": 17,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.08.471814",
+    "rel_abs": "Presented here is a magnetic hydrogel particle enabled workflow for capturing and concentrating SARS-CoV-2 from diagnostic remnant swab samples that significantly improves sequencing results using the Oxford Nanopore Technologies MinION sequencing platform. Our approach utilizes a novel affinity-based magnetic hydrogel particle, circumventing low input sample volumes and allowing for both rapid manual and automated high throughput workflows that are compatible with nanopore sequencing. This approach enhances standard RNA extraction protocols, providing up to 40x improvements in viral mapped reads, and improves sequencing coverage by 20-80% from lower titer diagnostic remnant samples. Furthermore, we demonstrate that this approach works for contrived influenza virus and respiratory syncytial virus samples, suggesting that it can be used to identify and improve sequencing results of multiple viruses in VTM samples. These methods can be performed manually or on a KingFisher Apex system.",
+    "rel_num_authors": 26,
     "rel_authors": [
       {
-        "author_name": "Lorena M Coria",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Patrick Daniel Andersen",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Lucas M Saposnik",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Stephanie Barksdale",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Celeste Pueblas Castro",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Robert Alex Barclay",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Eliana F Castro",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Natalie Smith",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Laura A Bruno",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Justin Fernandes",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "William B Stone",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Daniel Goldfarb",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Paula S Perez",
-        "author_inst": "Instituto de Investigaciones Biomedicas en Retrovirus y SIDA (INBIRS, Universidad de Buenos Aires - CONICET)"
+        "author_name": "Robbie Barbero",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "M. Laura Darriba",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Tara Jones-Roe",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Lucia B Chemes",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Katherine Besse",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Julieta Alcain",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Ross Dunlap",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Ignacio Mazzitelli",
-        "author_inst": "Instituto de Investigaciones Biomedicas en Retrovirus y SIDA (INBIRS, Universidad de Buenos Aires - CONICET)"
+        "author_name": "Ross Kelly",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Augusto Varese",
-        "author_inst": "Instituto de Investigaciones Biomedicas en Retrovirus y SIDA (INBIRS, Universidad de Buenos Aires - CONICET)"
+        "author_name": "Shida Miao",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Melisa Salvatori",
-        "author_inst": "Instituto de Investigaciones Biomedicas en Retrovirus y SIDA (INBIRS, Universidad de Buenos Aires - CONICET)"
+        "author_name": "Chamodya Ruhunusiri",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Albert J Auguste",
-        "author_inst": "Virginia Polytechnic Institute and State University"
+        "author_name": "Amy Munns",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Diego E Alvarez",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Sayed Mosavi",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Karina A Pasquevich",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Denton Munns",
+        "author_inst": "Ceres Nanosciences"
       },
       {
-        "author_name": "Juliana Cassataro",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas Dr. Rodolfo A. Ugalde, Universidad Nacional de San Martin, Consejo Nacional de Investigaciones Cientificas y Tecnic"
+        "author_name": "Laura Sanson",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Sahoo Saswata",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Olivia Swahn",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Killian Hull",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "David White",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Kevin Kolb",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Fatemeh Noroozi",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Joshna Seelam",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Anurag Patnaik",
+        "author_inst": "Ceres Nanosciences"
+      },
+      {
+        "author_name": "Ben Lepene",
+        "author_inst": "Ceres Nanosciences"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.12.08.21267496",
@@ -447207,39 +449066,35 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.12.06.471215",
-    "rel_title": "The influence of new SARS-CoV-2 variant Omicron (B.1.1.529) on vaccine efficacy, its correlation to Delta Variants: a computational approach",
+    "rel_doi": "10.1101/2021.12.07.21267442",
+    "rel_title": "Dynamic analysis and evaluation of asymptomatic infection in the spread of COVID-19",
     "rel_date": "2021-12-08",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.06.471215",
-    "rel_abs": "The newly discovered COVID variant B.1.1.529 in Botswana has more than 30 mutations in spike and many other in non-spike proteins, far more than any other SARS-CoV-2 variant accepted as a variant of concern by the WHO and officially named Omicron, and has sparked concern among scientists and the general public. Our findings provide insights into structural modification caused by the mutations in the Omicrons receptor-binding domain and look into the effects on interaction with the hosts neutralising antibodies CR3022, B38, CB6, P2B-2F6, and REGN, as well as ACE2R using an in silico approach. We have employed secondary structure prediction, structural superimposition, protein disorderness, molecular docking, and MD simulation to investigate host-pathogen interactions, immune evasion, and transmissibility caused by mutations in the RBD region of the spike protein of the Omicron variant and compared it to the Delta variants (AY.1, AY.2, & AY.3) and wild type. Computational analysis revealed that the Omicron variant has a higher binding affinity for the human ACE2 receptor than the wild and Delta (AY.1 and AY.2 strains), but lower than the Delta AY.3 strain. MD simulation and docking analysis suggest that the omicron and Delta AY.3 were found to have relatively unstable and compact RBD structures and hampered interactions with antibodies more than wild and Delta (AY.1 and AY.2), which may lead to relatively more pathogenicity and antibody escape. In addition, we observed lower binding affinity of Omicron for human monoclonal antibodies (CR3022, B38, CB6, and P2B2F6) when compared to wild and Delta (AY.1 & AY.2). However, the binding affinity of Omicron RBD variants for CR3022, B38, and P2B2F6 antibodies is lower as compared to Delta AY.3, which might promote immune evasion and reinfection and needs further experimental investigation.",
-    "rel_num_authors": 5,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.07.21267442",
+    "rel_abs": "COVID-19 has spread worldwide for nearly two years. Many countries have experienced repeated epidemics, that is, after the epidemic has been controlled for a period of time, the number of new cases per day is low, and the outbreak will occur again a few months later. In order to study the relationship between this low level of infection and the number of asymptomatic infections, and to evaluate the role of asymptomatic infections in the development of the epidemic, we have established an improved infectious disease dynamics model that can be used to evaluate the spread of the COVID-19 epidemic, and fitted the epidemic data in the three flat periods in England. According to the obtained parameters, according to the calculation of the model, the proportion of asymptomatic infections in these three flat periods are 41%, 53% and 58% respectively. After the first flat period, the number of daily newly confirmed cases predicted by the model began to increase around July 1, 2020. After more than four months of epidemic spread, it reached a peak on November 12, which is consistent with the actual case situation. Unanimous. After the second flat period, the model predicts that the number of new confirmed cases per day will increase from about May 7, 2021, and after about 73 days of epidemic development, it will reach a peak on July 20, showing the overall trend of the epidemic. In the above, the predicted results of the model are consistent with the actual cases. After the third flat period, the number of daily newly diagnosed cases predicted by the model began to increase around December 1, 2021, and reached a peak in December, and the number of cases will drop to a very low level after May 2022. According to our research results, due to the large number of asymptomatic infections, the spread of the epidemic is not easy to stop completely in a short time. However, when the epidemic enters a period of flat time, nucleic acid testing is performed, and asymptomatic infections are isolated at home for 14 days (the recovery period of symptomatic infection is about 10 days) may be an option that can be considered to interrupt the transmission of the case.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Prashant Ranjan",
-        "author_inst": "Banaras Hindu University"
-      },
-      {
-        "author_name": "Neha",
-        "author_inst": "Banaras Hindu University"
+        "author_name": "Chuan qing XU",
+        "author_inst": "Beijing University of Civil Engineering and Architecture"
       },
       {
-        "author_name": "Chandra Devi",
-        "author_inst": "Banaras Hindu University"
+        "author_name": "Zonghao Zhang",
+        "author_inst": "Beijing University of Civil Engineering and Architecture"
       },
       {
-        "author_name": "Kaviyapriya Arulmozhi Devar",
-        "author_inst": "Banaras Hindu University"
+        "author_name": "Xiaotong Huang",
+        "author_inst": "Beijing University of Civil Engineering and Arcihtecture"
       },
       {
-        "author_name": "Parimal Das",
-        "author_inst": "Banaras Hindu University"
+        "author_name": "Jingan Cui",
+        "author_inst": "Beijing University of Civil Engineering and Architecture"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "bioinformatics"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.12.02.21266468",
@@ -449253,31 +451108,55 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2021.12.05.471290",
-    "rel_title": "Constructing a multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and co-infecting microbes",
+    "rel_doi": "10.1101/2021.12.05.471277",
+    "rel_title": "A zebrafish model of COVID-19-associated cytokine storm syndrome reveals differential proinflammatory activities of Spike proteins of SARS-CoV-2 variants of concern.",
     "rel_date": "2021-12-07",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.05.471290",
-    "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused millions of deaths worldwide. Many efforts have focused on unraveling the mechanism of the viral infection to develop effective strategies for treatment and prevention. Previous studies have provided some clarity on the protein-protein interaction linkages occurring during the life cycle of viral infection; however, we lack a complete understanding of the full interactome, comprising human miRNAs and protein-coding genes and co-infecting microbes. To comprehensively determine this, we developed a statistical modeling method using latent Dirichlet allocation (called MLCrosstalk, for multiple-layer crosstalk) to fuse many types of data to construct the full interactome of SARS-CoV-2. Specifically, MLCrosstalk is able to integrate samples with multiple layers of information (e.g., miRNA and microbes), enforce a consistent topic distribution on all data types, and infer individual-level linkages (i.e., differing between patients). We also implement a secondary refinement with network propagation to allow our microbe-gene linkages to address larger network structures (e.g., pathways). Using MLCrosstalk, we generated a list of genes and microbes linked to SARS-CoV-2. Interestingly, we found that two of the identified microbes, Rothia mucilaginosa and Prevotella melaninogenica, show distinct patterns representing synergistic and antagonistic relationships with the virus, respectively. We also identified several SARS-COV-2-associated pathways, including the VEGFA-VEGFR2 and immune response pathways, which may provide potential targets for drug design.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.05.471277",
+    "rel_abs": "The sudden and unexpected appearance of the COVID-19 pandemic turned the whole world upside down in a very short time. One of the main challenges faced has been to understand COVID-19 patient heterogeneity, as a minority develop life-threatening hyperinflammation, the so-called cytokine storm syndrome (CSS). Using the unique advantages of the zebrafish model we report here the proinflammatory role of Spike (S) proteins from different SARS-CoV-2 variants of concern after injection into the hindbrain ventricle, a cavity filled with cerebrospinal fluid to which immune cells can be easily recruited and that mimics the alveolar environment of the human lung. We found that wild type/Wuhan variant S1 (S1WT) protein promoted neutrophil and macrophage recruitment, local and systemic hyperinflammation, emergency myelopoiesis, and hemorrhages. In addition, S1{gamma} protein was more proinflammatory and S1{delta} was less proinflammatory than S1WT and, strikingly, S1{beta} promoted delayed and long-lasting inflammation. Pharmacological inhibition of the canonical inflammasome robustly alleviated S1 protein-induced inflammation and emergency myelopoiesis. In contrast, genetic inhibition of angiotensin-converting enzyme 2 strengthened the proinflammatory activity of S1, and the administration of angiopoietin (1-7) fully rescued S1-induced hyperinflammation and hemorrhages. These results shed light into the mechanisms orchestrating the COVID-19-associated CSS and the host immune response to different SARS-CoV-2 S protein variants.\n\nHighlightsO_LIS proteins of SARS-CoV-2 promote hyperinflammation, neutrophilia, monocytosis and hemorrhages in zebrafish.\nC_LIO_LIS protein effects in zebrafish are mediated via the canonical inflammasome and the Ace2/Angiopoietin (1-7) axis.\nC_LIO_LIDelta S1 is less proinflammatory than wild type S1 and fails to induce emergency myelopoiesis in zebrafish.\nC_LIO_LINaive and primed human white blood cells are unable to respond to S proteins.\nC_LI",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Shaoke Lou",
-        "author_inst": "Yale University"
+        "author_name": "Sylwia D Tyrkalska",
+        "author_inst": "Universidad de Murcia"
       },
       {
-        "author_name": "Tianxiao Li",
-        "author_inst": "Yale University"
+        "author_name": "Alicia Martinez-Lopez",
+        "author_inst": "Universidad de Murcia"
       },
       {
-        "author_name": "Mark Gerstein",
-        "author_inst": "Yale university"
+        "author_name": "Ana B Arroyo",
+        "author_inst": "Universidad de Murcia"
+      },
+      {
+        "author_name": "Francisco J Martinez-Morcillo",
+        "author_inst": "Universidad de Murcia"
+      },
+      {
+        "author_name": "Sergio Candel",
+        "author_inst": "Universidad de Murcia"
+      },
+      {
+        "author_name": "Pablo Mesa-del-Castillo",
+        "author_inst": "Hospital Clinico Universitario Virgen de la Arrixaca"
+      },
+      {
+        "author_name": "Diana Garcia-Moreno",
+        "author_inst": "Universidad de Murcia"
+      },
+      {
+        "author_name": "Maria L. Cayuela",
+        "author_inst": "University Hospital \"Virgen de la Arrixaca\""
+      },
+      {
+        "author_name": "Victoriano Mulero",
+        "author_inst": "Universidad de Murcia"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.12.06.471377",
@@ -450927,21 +452806,177 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.12.06.21267289",
-    "rel_title": "Testing the Validity of the Modified Vaccine Attitude Question Battery across 22 Languages with a Large-scale International Survey Dataset",
+    "rel_doi": "10.1101/2021.12.06.21267101",
+    "rel_title": "SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia",
     "rel_date": "2021-12-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.06.21267289",
-    "rel_abs": "In this study, we tested the validity of the modified version of the Vaccine Attitude Question Battery (VAQB) across 22 different languages. Validity test was conducted with a large-scale international survey dataset, COVIDiSTRESSII Global Survey, collected from 20,601 participants from 62 countries. We employed exploratory and confirmatory factor analysis, measurement invariance test, and measurement alignment for internal validity test. Moreover, we examined correlation between the VAQB score, vaccination intent, compliance with preventive measures, and trust in public health-related agents. The results reported that the modified VAQB, which included five items, showed good validity across 22 languages with measurement alignment. Furthermore, the VAQB score showed negative association with vaccination intent, compliance, and trust as expected. The findings from this study provide additional evidence supporting the validity of the modified VAQB in 22 languages for future large-scale international research on COVID-19 and vaccination.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.06.21267101",
+    "rel_abs": "Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work has demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces such as Halloween candy, and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions, and to test whether our past observations linking SARS-CoV-2 abundance to Rothia spp. in hospitals also hold in a residential setting, we performed detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences to assess the bacterial community at each location and to the Cq value of the contemporaneous clinical test. Our results show that the highest SARS-CoV-2 load in this setting is on touched surfaces such as light switches and faucets, but detectable signal is present in many non-touched surfaces that may be more relevant in settings such as schools where mask wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association.\n\nImportanceSurface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g. touching a light switch) or indirectly (e.g. by droplets or aerosols settling). We found highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g. in schools, where students do not touch the light switches and also wear masks so they have no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.",
+    "rel_num_authors": 40,
     "rel_authors": [
       {
-        "author_name": "Hyemin Han",
-        "author_inst": "University of Alabama"
+        "author_name": "Victor J. Cant\u00fa",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Rodolfo A. Salido",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Shi Huang",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Gibraan Rahman",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Rebecca Tsai",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Holly D. Valentine",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Celestine G Magallanes",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Stefan Aigner",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Nathan A. Baer",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Tom Barber",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Pedro Belda-Ferre",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Maryan Betty",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "MacKenzie Bryant",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Mart\u00edn Casas Maya",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Anelizze Castro-Mart\u00ednez",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Marisol Chac\u00f3n",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Willi Cheung",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Evelyn S. Crescini",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Peter De Hoff",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Emily Eisner",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Sawyer Farmer",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Abbas Hakim",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Laura Kohn",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Alma L. Lastrella",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Elijah S. Lawrence",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Sydney C Morgan",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Toan T. Ngo",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Alhakam Nouri",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "R. Tyler Ostrander",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Ashley Plascencia",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Christopher A. Ruiz",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Shashank Sathe",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Phoebe Seaver",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Tara Schwartz",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Elizabeth W. Smoot",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Thomas Valles",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Gene W. Yeo",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Louise Laurent",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Rebecca Fielding-Miller",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Rob Knight",
+        "author_inst": "University of California, San Diego"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -452873,79 +454908,43 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2021.12.03.21267281",
-    "rel_title": "Safety and immunogenicity of the third booster dose with inactivated, viral vector, and mRNA COVID-19 vaccines in fully immunized healthy adults with inactivated vaccine",
+    "rel_doi": "10.1101/2021.12.04.21267294",
+    "rel_title": "Characteristics of Patients Referred to a Cardiovascular Disease Clinic for Post-Acute Sequelae of SARS-CoV-2 Infection",
     "rel_date": "2021-12-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.03.21267281",
-    "rel_abs": "The coronavirus disease-2019 (COVID-19) pandemic has become a severe healthcare problem worldwide since the first outbreak in late December 2019. Currently, the COVID-19 vaccine has been used in many countries, but it is still unable to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection despite patients receiving full vaccination doses. Therefore, we aimed to appraise the booster effect of the different platforms of vaccines, including inactivated vaccine (BBIBP), viral vector vaccine (AZD122), and mRNA vaccine (BNT162b2) in healthy adults who received the full dose of inactivated vaccine (CoronaVac). The booster dose was safe with no serious adverse events. Moreover, the immunogenicity indicated that the booster dose with viral vector and mRNA vaccine achieved a significant proportion of Ig anti-receptor binding domain (RBD), IgG anti-RBD, and IgA anti-S1 booster response. In contrast, inactivated vaccine achieved a lower booster response than others. Consequently, the neutralization activity of vaccinated serum had a high inhibition of over 90% against SARS-CoV-2 wild-type and their variants (B.1.1.7-alpha, B.1.351-beta, and B.1.617.2-delta). In addition, IgG anti-nucleocapsid was observed only among the group that received the BBIBP booster. Our study found a significant increase in levels of interferon gamma-secreting T-cell response after the additional viral vector or mRNA booster vaccination. This study showed that administration with either viral vector (AZD1222) or mRNA (BNT162b2) boosters in individuals with a history of two doses of inactivated vaccine (CoronaVac) obtained great immunogenicity with acceptable adverse events.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.04.21267294",
+    "rel_abs": "There is limited literature on the cardiovascular manifestations of post-acute sequelae of SARS-CoV-2 infection (PASC). We aimed to describe the characteristics, diagnostic evaluations, and cardiac diagnoses in patients referred to a cardiovascular disease clinic designed for patients with PASC from May 2020 to September 2021. Of 126 patients, average age was 46 years (range 19-81 years), 43 (34%) were male. Patients presented on average five months after COVID-19 diagnosis. 30 (24%) patients were hospitalized for acute COVID-19. Severity of acute COVID-19 was mild in 37%, moderate in 41%, severe in 11%, and critical in 9%. Patients were also followed for PASC by pulmonology (53%), neurology (33%), otolaryngology (11%), and rheumatology (7%). Forty-three patients (34%) did not have significant comorbidities. The most common symptoms were dyspnea (52%), chest pain/pressure (48%), palpitations (44%), and fatigue (42%), commonly associated with exertion or exercise intolerance. The following cardiovascular diagnoses were identified: nonischemic cardiomyopathy (5%); new ischemia (3%); coronary vasospasm (2%); new atrial fibrillation (2%), new supraventricular tachycardia (2%); myocardial involvement (15%) by cardiac MRI, characterized by late gadolinium enhancement (LGE; 60%) or inflammation (48%). The remaining 97 patients (77%) exhibited common symptoms of fatigue, dyspnea on exertion, tachycardia, or chest pain, which we termed \"cardiovascular PASC syndrome.\" Three of these people met criteria for postural orthostatic tachycardia syndrome. Lower severity of acute COVID-19 was a significant predictor of cardiovascular PASC syndrome. In this cohort of patients referred to cardiology for PASC, 23% had a new diagnosis, but most displayed a pattern of symptoms associated with exercise intolerance.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Sitthichai Kanokudom",
-        "author_inst": "Center of Excellence in Clinical Virology, Department of Biochemistry, Osteoarthritis and Musculoskeleton Research Unit, Faculty of Medicine, Chulalongkorn Univ"
-      },
-      {
-        "author_name": "Suvichada Assawakosri",
-        "author_inst": "Center of Excellence in Clinical Virology, Department of Biochemistry, Osteoarthritis and Musculoskeleton Research Unit, Faculty of Medicine, Chulalongkorn Univ"
-      },
-      {
-        "author_name": "Nungruthai Suntronwong",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
-      },
-      {
-        "author_name": "Chompoonut Auphimai",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
-      },
-      {
-        "author_name": "Pornjarim Nilyanimit",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
-      },
-      {
-        "author_name": "Preeyaporn Vichaiwattana",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
-      },
-      {
-        "author_name": "Thanunrat Thongmee",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
-      },
-      {
-        "author_name": "Ritthideach Yorsaeng",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
-      },
-      {
-        "author_name": "Donchida Srimuan",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
-      },
-      {
-        "author_name": "Thaksaporn Thatsanatorn",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Stephen Y Wang",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Sirapa Klinfueng",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Philip Adejumo",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Natthinee Sudhinaraset",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Claudia See",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Nasamon Wanlapakorn",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand"
+        "author_name": "Oyere K Onuma",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Sittisak Honsawek",
-        "author_inst": "Department of Biochemistry, Osteoarthritis and Musculoskeleton Research Unit, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospita"
+        "author_name": "Edward J Miller",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Yong Poovorawan",
-        "author_inst": "Center of Excellence in Clinical Virology, Faculty of Medicine, Chulalongkorn University, Thailand and FRS(T), the Royal Society of Thailand"
+        "author_name": "Erica S Spatz",
+        "author_inst": "Yale School of Medicine"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "cardiovascular medicine"
   },
   {
     "rel_doi": "10.1101/2021.12.03.21267258",
@@ -454631,51 +456630,107 @@
     "category": "pediatrics"
   },
   {
-    "rel_doi": "10.1101/2021.12.03.21266538",
-    "rel_title": "Introduction and community transmission of SARS-CoV-2 lineage A.2.5 in Florida with novel spike INDELS",
-    "rel_date": "2021-12-05",
+    "rel_doi": "10.1101/2021.12.03.21267155",
+    "rel_title": "High viral loads: what drives fatal cases of COVID-19 in vaccinees? an autopsy study",
+    "rel_date": "2021-12-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.03.21266538",
-    "rel_abs": "SARS-CoV-2 (SC2) variants of concern (VOC) continue to emerge and spread globally, threatening the use of monoclonal antibody therapies and vaccine effectiveness. Several mutations in the SC2 spike glycoprotein have been associated with reduction in antibody neutralization. Genomic surveillance of SC2 variants has been imperative to inform the public health response regarding the use of clinical therapies in specific jurisdictions based on the proportion of particular variants (e.g., Gamma (P.1)) in a region. Florida Department of Health Bureau of Public Health Laboratories (BPHL) performs tiled-amplicon whole genome sequencing for baseline and targeted surveillance of SC2 isolates in Florida from clinical specimens collected from county health departments and hospitals throughout the state. Here, we describe the introduction of SC2 lineage A.2.5 in Florida, which contains S:L452R (a substitution of therapeutic concern) and two novel Spike INDELS, the deletion of 141-143 and ins215AGY, with unknown implications on immune response. The A.2.5 lineage was first detected in Florida among an outbreak at a healthcare facility in January 2021, and subsequent A.2.5 isolates were detected across all geographical regions throughout the state. A time-scaled maximum clade credibility phylogeny determined there were at least eight separate introductions of A.2.5 in the state. The time of introduction of a monophyletic Florida clade was established to be December 2020. The Spike INDELS were determined to reside in the N-terminal domain, a region associated with antibody neutralization. As community transmission of SARS-CoV-2 in Florida continues, genomic surveillance of circulating variants in Florida and the detection of emerging variants are critical for informing public health response to COVID-19.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.03.21267155",
+    "rel_abs": "BackgroundThe rate of SARS-CoV-2 breakthrough infections in vaccinees is becoming an increasingly serious issue.\n\nObjectiveTo determine the causes of death, histological organ alteration, and viral spread in relation to demographic, clinical-pathological, viral variants, and vaccine types.\n\nDesignComprehensive retrospective observational cohort study. Setting: Consecutive cases from four German academic medical centers.\n\nPatientsDeceased with proven SARS-CoV-2 infection after vaccination who died between January and November 2021. Collections of 29 vaccinees which were analyzed and compared to 141 nonvaccinated control cases.\n\nResultsAutopsies were performed on 16 partially and 13 fully vaccinated individuals. Most patients were elderly and suffered from several relevant comorbidities. Real-time RT-PCR (RT-qPCR) identified a significantly increased rate of generalized viral dissemination within the organism in vaccinated cases versus nonvaccinated cases (45% vs. 16%, respectively; P = 0.008). Vaccinated cases also showed high viral loads, reaching Ct values below 10, especially in the upper airways and lungs. This was accompanied by high rates of pulmonal bacterial or mycotic superinfections and the occurrence of immunocompromising factors such as malignancies, immunosuppressive drug intake, or decreased immunoglobulin levels. All these findings were particularly accentuated in partially vaccinated patients compared to fully vaccinated individuals. A fatal course after vaccination occurred in only 14% of all COVID-19 deceased in Augsburg.\n\nLimitationsRestricted number of cases\n\nConclusionsFatal cases of COVID-19 in vaccinees were rare and often associated with severe comorbidities or other immunosuppressive conditions. Interestingly, we observed striking virus dissemination in our case study, which may indicate a decreased ability to eliminate the virus in patients with an impaired immune system. However, the potential role of antibody-dependent enhancement must also be ruled out in future studies.\n\nFunding sourceThis work was supported by the German Registry of COVID-19 Autopsies (www.DeRegCOVID.ukaachen.de) and funded by the Federal Ministry of Health (ZMVI1-2520COR201), the Federal Ministry of Education and Research within the framework of the network of university medicine (DEFEAT PANDEMICs, 01KX2021), and the German Federal Ministry of Food and Agriculture through the Federal Office for Agriculture and Food (project ZooSeq, grant number 2819114019).",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Sarah E Schmedes",
-        "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health"
+        "author_name": "Klaus Hirschbuehl",
+        "author_inst": "Hematology and Oncology, Medical Faculty, University of Augsburg, Augsburg, Germany"
       },
       {
-        "author_name": "Taj Azarian",
-        "author_inst": "Burnett School of Biomedical Sciences, University of Central Florida"
+        "author_name": "Tina Schaller",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany"
       },
       {
-        "author_name": "Eleonora Cella",
-        "author_inst": "Burnett School of Biomedical Sciences, University of Central Florida"
+        "author_name": "Bruno Maerkl",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany"
       },
       {
-        "author_name": "Jessy Motes",
-        "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health"
+        "author_name": "Rainer Claus",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany and Hematology and Oncology, Medical Faculty, University"
       },
       {
-        "author_name": "Omer Tekin",
-        "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health"
+        "author_name": "Eva Sipos",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany"
       },
       {
-        "author_name": "James Weiss",
-        "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health"
+        "author_name": "Lukas Rentschler",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany"
       },
       {
-        "author_name": "Nancimae Miller",
-        "author_inst": "Pathology Consultants of South Broward, Memorial Healthcare System"
+        "author_name": "Andrea Maccagno",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany"
       },
       {
-        "author_name": "Jason Blanton",
-        "author_inst": "Bureau of Public Health Laboratories, Florida Department of Health"
+        "author_name": "Bianca Grosser",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany"
+      },
+      {
+        "author_name": "Elisabeth Kling",
+        "author_inst": "Microbiology, Medical Faculty, University of Augsburg, Augsburg, Germany"
+      },
+      {
+        "author_name": "Michael Neidig",
+        "author_inst": "IV. Medical Clinic, University Hospital Augsburg, Augsburg, Germany"
+      },
+      {
+        "author_name": "Thomas Kroencke",
+        "author_inst": "Diagnostic and Interventional Radiology, Medical Faculty, University of Augsburg, Augsburg, Germany"
+      },
+      {
+        "author_name": "Oliver Spring",
+        "author_inst": "Anesthesiology and Operative Intensive Care Medicine, Medical Faculty, University of Augsburg, Augsburg, Germany"
+      },
+      {
+        "author_name": "Georg Braun",
+        "author_inst": "Gastroenterology, Medical Faculty, University of Augsburg, Augsburg, Germany"
+      },
+      {
+        "author_name": "Hans Boesmueller",
+        "author_inst": "Institute for Pathology and Neuropathology, University Hospital of Thuebingen, Thuebingen, Germany"
+      },
+      {
+        "author_name": "Maximilian Seidl",
+        "author_inst": "Institute of Pathology, University of Duesseldorf, Duesseldorf, Germany"
+      },
+      {
+        "author_name": "Irene Esposito",
+        "author_inst": "Institute of Pathology, University of Duesseldorf, Duesseldorf, Germany"
+      },
+      {
+        "author_name": "Jessica Pablik",
+        "author_inst": "Department of Pathology, Technische Universitaet Dresden, Dresden, Germany"
+      },
+      {
+        "author_name": "Julia Hilsenbeck",
+        "author_inst": "Department of Pathology, Technische Universitaet Dresden, Dresden, Germany"
+      },
+      {
+        "author_name": "Peter Boor",
+        "author_inst": "Insitute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+      },
+      {
+        "author_name": "Martin Beer",
+        "author_inst": "Institute of Diagnostic Virology, Friedrich-Loeffler-Institute, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany"
+      },
+      {
+        "author_name": "Sebastian Dintner",
+        "author_inst": "General Pathology and Molecular Diagnostics, Medical Faculty, University of Augsburg, Augsburg, Germany"
+      },
+      {
+        "author_name": "Claudia Wylezich",
+        "author_inst": "Institute of Diagnostic Virology, Friedrich-Loeffler-Institute, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.12.03.21267146",
@@ -456373,25 +458428,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.12.02.21267185",
-    "rel_title": "Tajima D test accurately forecasts Omicron / COVID-19 outbreak",
+    "rel_doi": "10.1101/2021.11.30.21267071",
+    "rel_title": "Increased risk of psychiatric sequelae of COVID-19 is highest early in the clinical course",
     "rel_date": "2021-12-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.02.21267185",
-    "rel_abs": "On 26 November 2021, the World Health Organization designated the SARS-CoV-2 variant B.1.1.529, Omicron, a variant of concern. However, the phylogenetic and evolutionary dynamics of this variant remain unclear. An analysis of the 131 Omicron variant sequences from November 9 to November 28, 2021 reveals that variants have diverged into at least 6 major subgroups. 86.3% of the cases have an insertion at amino acid 214 (INS214EPE) of the spike protein. Neutrality analysis of DH (-2.814, p<0.001) and Zengs E (0.0583, p=1.0) tests suggested that directional selection was the major driving force of Omicron variant evolution. The synonymous (Dsyn) and nonsynonymous (Dnonsyn) polymorphisms of the Omicron variant spike gene were estimated with Tajimas D statistic to eliminate homogenous effects. Both D ratio (Dnonsyn/Dsyn, 1.57) and {Delta}D (Dsyn-Dnonsyn, 0.63) indicate that purifying selection operates at present. The low nucleotide diversity (0.00008) and Tajima D value (-2.709, p<0.001) also confirms that Omicron variants had already spread in human population for more than the 6 weeks than has been reported. These results, along with our previous analysis of Delta and Lambda variants, also supports the validity of the Tajimas D test score, with a threshold value as -2.50, as an accurate predictor of new COVID-19 outbreaks.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.30.21267071",
+    "rel_abs": "BackgroundCOVID-19 has been shown to increase the risk of adverse mental health consequences. A recent electronic health record (EHR)-based observational study showed an almost two-fold increased risk of new-onset mental illness in the first 90 days following a diagnosis of acute COVID-19.\n\nMethodsWe used the National COVID Cohort Collaborative, a harmonized EHR repository with 2,965,506 COVID-19 positive patients, and compared cohorts of COVID-19 patients with comparable controls. Patients were propensity score-matched to control for confounding factors. We estimated the hazard ratio (COVID-19:control) for new-onset of mental illness for the first year following diagnosis. We additionally estimated the change in risk for new-onset mental illness between the periods of 21-120 and 121-365 days following infection.\n\nFindingsWe find a significant increase in incidence of new-onset mental disorders in the period of 21-120 days following COVID-19 (3.8%, 3.6-4.0) compared to patients with respiratory tract infections (3%, 2.8-3.2). We further show that the risk for new-onset mental illness decreases over the first year following COVID-19 diagnosis compared to other respiratory tract infections and demonstrate a reduced (non-significant) hazard ratio over the period of 121-365 days following diagnosis. Similar findings are seen for new-onset anxiety disorders but not for mood disorders.\n\nInterpretationPatients who have recovered from COVID-19 are at an increased risk for developing new-onset mental illness, especially anxiety disorders. This risk is most prominent in the first 120 days following infection.\n\nFundingNational Center for Advancing Translational Sciences (NCATS).",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Ting-Yu Yeh",
-        "author_inst": "Institute of Marine and Environmental Technology"
+        "author_name": "Ben Coleman",
+        "author_inst": "The Jackson Laboratory, Genomic Medicine, Farmington 6032, CT, USA"
       },
       {
-        "author_name": "Gregory P. Contreras",
-        "author_inst": "Auxergen Inc."
+        "author_name": "Elena Casiraghi",
+        "author_inst": "AnacletoLab, Dipartimento di Informatica, Universita degli Studi di Milano, Italy"
+      },
+      {
+        "author_name": "Hannah Blau",
+        "author_inst": "The Jackson Laboratory, Genomic Medicine, Farmington 6032, CT, USA"
+      },
+      {
+        "author_name": "Lauren Chan",
+        "author_inst": "College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA"
+      },
+      {
+        "author_name": "Melissa A Haendel",
+        "author_inst": "University of Colorado Anschutz Medical Campus, Center for Health AI, Aurora 80045, CO, USA"
+      },
+      {
+        "author_name": "Bryan Laraway",
+        "author_inst": "University of Colorado Anschutz Medical Campus, Center for Health AI, Aurora 80045, CO, USA"
+      },
+      {
+        "author_name": "Tiffany J Callahan",
+        "author_inst": "University of Colorado Anschutz Medical Campus, Center for Health AI, Aurora 80045, CO, USA"
+      },
+      {
+        "author_name": "Rachel R Deer",
+        "author_inst": "University of Texas Medical Branch, Galveston, TX, 77550 USA"
+      },
+      {
+        "author_name": "Ken Wilkins",
+        "author_inst": "Biostatistics Program, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland"
+      },
+      {
+        "author_name": "Justin Reese",
+        "author_inst": "Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Peter N Robinson",
+        "author_inst": "The Jackson Laboratory, Genomic Medicine, Farmington 6032, CT, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -458055,81 +460146,113 @@
     "category": "health systems and quality improvement"
   },
   {
-    "rel_doi": "10.1101/2021.11.29.21267041",
-    "rel_title": "COVID-19 Variant Detection with a High-Fidelity CRISPR-Cas12 Enzyme",
+    "rel_doi": "10.1101/2021.11.29.21267042",
+    "rel_title": "Favipiravir for the Treatment of Coronavirus Disease 2019; a propensity score-matched cohort study",
     "rel_date": "2021-11-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21267041",
-    "rel_abs": "Laboratory tests for the accurate and rapid identification of SARS-CoV-2 variants can potentially guide the treatment of COVID-19 patients and inform infection control and public health surveillance efforts. Here we present the development and validation of a rapid COVID-19 variant DETECTR(R) assay incorporating loop-mediated isothermal amplification (LAMP) followed by CRISPR-Cas12 based identification of single nucleotide polymorphism (SNP) mutations in the SARS-CoV-2 spike (S) gene. This assay targets the L452R, E484K/Q/A, and N501Y mutations that are associated with nearly all circulating viral lineages and identifies the two circulating variants of concern, Delta and Omicron. In a comparison of three different Cas12 enzymes, only the newly identified enzyme CasDx1 was able to accurately identify all targeted SNP mutations. An analysis pipeline for CRISPR-based SNP identification from 139 clinical samples yielded an overall SNP concordance of 98% and agreement with SARS-CoV-2 lineage classification of 138/139 compared to viral whole-genome sequencing. We also showed that detection of the single E484A mutation was necessary and sufficient to accurately identify Omicron from other major circulating variants in patient samples. These findings demonstrate the utility of CRISPR-based DETECTR(R) as a faster and simpler diagnostic than sequencing for SARS-CoV-2 variant identification in clinical and public health laboratories.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21267042",
+    "rel_abs": "BackgroundWe investigated clinical outcomes of favipiravir in patients with COVID-19 pneumonia.\n\nMethodsPatients who between 23 May 2020 and 18 July 2020 received [&ge;]24 hours of favipiravir were assigned to the favipiravir group, while those who did not formed the non-favipiravir group. The primary outcome was 28-day clinical improvement, defined as two-category improvement from baseline on an 8-point ordinal scale. Propensity scores (PS) for favipiravir therapy were used for 1:1 matching. Cox regression was used to examine associations with the primary endpoint.\n\nResultsThe unmatched cohort included 1,493 patients, of which 51.7% were in the favipiravir group, and 48.3% were not receiving supplemental oxygen at baseline. Favipiravir was started within a median of 5 days from symptoms onset. Significant baseline differences between the two unmatched groups existed, but not between the PS-matched groups (N = 774). After PS-matching, there were no significant differences between the two groups in the proportion with 28-day clinical improvement (93.3% versus 92.8%, P 0.780), or 28-day all-cause mortality (2.1% versus 3.1%, P 0.360). Favipiravir was associated with more viral clearance by day 28 (79.8% versus 64.1%, P <0.001). In the adjusted Cox proportional hazards model, favipiravir therapy was not associated 28-day clinical improvement (adjusted hazard ratio 0.978, 95% confidence interval 0.862 -1.109, P 0.726). Adverse events were common in both groups, but the 93.9% were Grades 1-3.\n\nConclusionFavipiravir therapy for COVID-19 pneumonia is well tolerated but is not associated with an increased likelihood of clinical improvement or reduced all-cause mortality by 28 days.",
+    "rel_num_authors": 25,
     "rel_authors": [
       {
-        "author_name": "Clare L Fasching",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Rand A ALATTAR",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Venice Servellita",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Shiema ABDALLA",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Bridget McKay",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Tasneem AK ABDALLAH",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Vaishnavi Nagesh",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Rashid KAZMAN",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "James P Broughton",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Aseelah QADMOUR",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Noah Brazer",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Tawheeda BH IBRAHIM",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Baolin Wang",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Bassem ALHARIRI",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Alicia Sotomayor-Gonzalez",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Shahd SHAAR",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Kevin Reyes",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Abeer BAJWA",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Jessica Streithorst",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Abeir BH ALIMAM",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Rabia QAZI",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Rachel N Deraney",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Fatma BEN ABID",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Emma Stanfield",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Joanne DAGHFAL",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Carley G Hendriks",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Ali M ELDEEB",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Steve Miller",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Kinda SHUKRI",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Jesus Ching",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Ahmed ELSAYED",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Janice S Chen",
-        "author_inst": "Mammoth Biosciences"
+        "author_name": "Fatima RUSTOM",
+        "author_inst": "Hamad Medical Corporation"
       },
       {
-        "author_name": "Charles Y Chiu",
-        "author_inst": "University of California San Francisco"
+        "author_name": "Musaed ALSAMAWI",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Alaaeldin ABDELMAJID",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Miguel AP BASULTO",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Armando AR COBIAN",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Mohamed ABUKHATTAB",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Muna A ALMASLAMANI",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Abdullatif ALKHAL",
+        "author_inst": "Hamad Medical Corporation"
+      },
+      {
+        "author_name": "Ali S OMRANI",
+        "author_inst": "Hamad Medical Corporation"
       }
     ],
     "version": "1",
@@ -459901,47 +462024,51 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.11.25.21266875",
-    "rel_title": "COVID-19 trends and severity among symptomatic children aged 0 to 17 years in ten EU countries, 3 August 2020 to 3 October 2021",
+    "rel_doi": "10.1101/2021.11.29.21266976",
+    "rel_title": "Impact of the COVID-19 pandemic on the malaria burden in northern Ghana: Analysis of routine surveillance data",
     "rel_date": "2021-11-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.25.21266875",
-    "rel_abs": "To guide evidence-based prevention of COVID-19 in children, we estimated risks of severe outcomes in 820,404 symptomatic paediatric cases reported by 10 EU Member States between August 2020 and October 2021. Case and hospitalisation rates rose as overall transmission increased but severe outcomes were rare: 9,611 (1.2%) were hospitalised, 640 (0.08%) required intensive care and 84 (0.01%) died. Despite increased individual risk (aOR; 95% CI for hospitalisation: 7.3; 3.3 - 16.2, ICU: 8.7; 6.2 - 12.3) in cases with comorbidities such as cancer, diabetes, cardiac or lung disease, most (83.7%) hospitalised children had no reported comorbidity.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21266976",
+    "rel_abs": "IntroductionThe COVID-19 pandemic and its collateral damage severely impact health systems globally and risk to worsen the malaria situation in endemic countries. Malaria is a leading cause of morbidity and mortality in Ghana. This study aims to analyze routine surveillance data to assess possible effects on the malaria burden in the first year of the COVID-19 pandemic in the Northern Region of Ghana.\n\nMethodsMonthly routine data from the District Health Information Management System II (DHIMS2) of the Northern Region of Ghana were analyzed. Overall outpatient department visits and malaria incidence rates from the years 2015 to 2019 were compared to the corresponding data of the year 2020.\n\nResultsCompared to the corresponding periods of the years 2015 to 2019, overall visits and malaria incidence in pediatric and adult outpatient departments in northern Ghana decreased in March and April 2020, when major movement and social restrictions were implemented in response to the pandemic. Incidence slightly rebounded afterwards in 2020 but stayed below the average of the previous years. Data from inpatient departments showed a similar but more pronounced trend when compared to outpatient departments. In pregnant women, however, malaria incidence in outpatient departments increased after the first COVID-19 wave.\n\nDiscussionThe findings from this study show that the COVID-19 pandemic affects the malaria burden in health facilities of Ghana, with declines in in- and outpatient rates. Pregnant women may experience reduced access to intermittent preventive malaria treatment and insecticide treated nets, resulting in subsequent higher malaria morbidity. Further data from other African countries, particularly on community-based studies, are needed to fully determine the impact of the pandemic on the malaria situation.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Nick Bundle",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC)"
+        "author_name": "Anna-Katharina Heuschen",
+        "author_inst": "Institute of Global Health, Medical School, Ruprecht-Karls-University Heidelberg, Germany"
       },
       {
-        "author_name": "Nishi Dave",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC)"
+        "author_name": "Alhassan Abdul-Mumin",
+        "author_inst": "University for Development Studies, School of Medicine, Department of Pediatrics and Child Health, Tamale, Ghana"
       },
       {
-        "author_name": "Anastasia Pharris",
-        "author_inst": "European Centre for Disease Prevention and Control"
+        "author_name": "Martin Nyaaba Adokiya",
+        "author_inst": "University for Development Studies, School of Public Health, Department of Epidemiology, Biostatistics and Disease Control, Tamale, Ghana"
       },
       {
-        "author_name": "Gianfranco Spiteri",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC)"
+        "author_name": "Guangyu Lu",
+        "author_inst": "School of Public Health, Medical School, Yangzhou University, China"
       },
       {
-        "author_name": "Charlotte Deogan",
-        "author_inst": "European Centre for Disease Prevention and Control (ECDC)"
+        "author_name": "Albrecht Jahn",
+        "author_inst": "Institute of Global Health, Medical School, Ruprecht-Karls-University Heidelberg, Germany"
       },
       {
-        "author_name": "Jonathan E. Suk",
-        "author_inst": "European Centre for Disease Prevention and Control"
+        "author_name": "Oliver Razum",
+        "author_inst": "Department of Epidemiology and International Public Health, School of Public Health, Bielefeld University, Germany"
       },
       {
-        "author_name": "- Study group members",
-        "author_inst": ""
+        "author_name": "Volker Winkler",
+        "author_inst": "Institute of Global Health, Medical School, Ruprecht-Karls-University Heidelberg, Germany"
+      },
+      {
+        "author_name": "Olaf Mueller",
+        "author_inst": "Institute of Global Health, Medical School, Ruprecht-Karls-University Heidelberg, Germany"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.11.23.469709",
@@ -461719,121 +463846,37 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2021.11.24.21266812",
-    "rel_title": "SARS-CoV-2 Convalescent Sera Binding and Neutralizing Antibody Concentrations Compared with COVID-19 Vaccine Efficacy Estimates Against Symptomatic Infection",
+    "rel_doi": "10.1101/2021.11.21.21266633",
+    "rel_title": "SARS-CoV-2 vaccination predicts COVID-19 progression and outcomes in hospitalized patients",
     "rel_date": "2021-11-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.24.21266812",
-    "rel_abs": "Previous vaccine efficacy (VE) studies have estimated neutralizing and binding antibody concentrations that correlate with protection from symptomatic infection; how these estimates compare to those generated in response to SARS-CoV-2 infection is unclear. Here, we assessed quantitative neutralizing and binding antibody concentrations using standardized SARS-CoV-2 assays on 3,067 serum specimens collected during July 27, 2020-August 27, 2020 from COVID-19 unvaccinated persons with detectable anti-SARS-CoV-2 antibodies using qualitative antibody assays. Quantitative neutralizing and binding antibody concentrations were strongly positively correlated (r=0.76, p<0.0001) and were noted to be several fold lower in the unvaccinated study population as compared to published data on concentrations noted 28 days post-vaccination. In this convenience sample, [~]88% of neutralizing and [~]63-86% of binding antibody concentrations met or exceeded concentrations associated with 70% COVID-19 VE against symptomatic infection from published VE studies; [~]30% of neutralizing and 1-14% of binding antibody concentrations met or exceeded concentrations associated with 90% COVID-19 VE. These data support observations of infection-induced immunity and current recommendations for vaccination post infection to maximize protection against symptomatic COVID-19.",
-    "rel_num_authors": 26,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.21.21266633",
+    "rel_abs": "BackgroundSARS-CoV-2 vaccination might impact on clinical progression of cases with breakthrough COVID-19 disease.\n\nObjectiveto evaluate the impact of SARS-CoV-2 vaccination on disease progression in COVID-19 hospitalized patient\n\nMethods and FindingsTwo-hundred eighty-four consecutive COVID-19 hospitalized patients, including 50 vaccinated cases entered the study. Compared to unvaccinated cases, vaccinated patients were older, exhibited more comorbidities and did not differ for COVID-19 severity at admission. During hospitalisation, unvaccinated patients showed worse disease progression, including higher need of oxygen and higher risk of death compared to vaccinated patients (OR 3.3; 1.05-10.7 95% CI in the whole cohort and OR 54.8; 3.5-852 in the ventilated cases).\n\nDiscussionThese findings argue for an important reduction in severity among vaccine breakthrough infection compared to unvaccinated cases in COVID-19 disease.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Amy J. Schuh",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Panayampalli S. Satheshkumar",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Stephanie Dietz",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Lara Bull-Otterson",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Myrna Charles",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Chris Edens",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Jefferson M. Jones",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Kristina L. Bajema",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Kristie E.N. Clarke",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "L. Clifford McDonald",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Sadhna Patel",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Kendra Cuffe",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Natalie J. Thornburg",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Jarad Schiffer",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Kelly Chun",
-        "author_inst": "Labcorp"
-      },
-      {
-        "author_name": "Monique Bastidas",
-        "author_inst": "Labcorp"
-      },
-      {
-        "author_name": "Manory Fernando",
-        "author_inst": "Labcorp"
-      },
-      {
-        "author_name": "Christos J. Petropoulos",
-        "author_inst": "Labcorp"
-      },
-      {
-        "author_name": "Terri Wrin",
-        "author_inst": "Labcorp"
-      },
-      {
-        "author_name": "Suqin Cai",
-        "author_inst": "Labcorp"
-      },
-      {
-        "author_name": "Dot Adcock",
-        "author_inst": "Labcorp"
+        "author_name": "alessandro padovani",
+        "author_inst": "University of Brescia and ASST Spedalicivili of Brescia"
       },
       {
-        "author_name": "Deborah Sesok-Pizzini",
-        "author_inst": "Labcorp"
+        "author_name": "Viviana Cristillo",
+        "author_inst": "University of Brescia and ASST Spedali Civili of Brescia"
       },
       {
-        "author_name": "Stanley Letovsky",
-        "author_inst": "Labcorp"
+        "author_name": "daniela tomasoni",
+        "author_inst": "University of Brescia and ASST Spedali CIvili of Brescia"
       },
       {
-        "author_name": "Alicia M. Fry",
-        "author_inst": "United States Centers for Disease Control and Prevention"
+        "author_name": "stefano gipponi",
+        "author_inst": "University of Brescia and ASST Spedali CIvili of Brescia"
       },
       {
-        "author_name": "Aron J. Hall",
-        "author_inst": "United States Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Adi V. Gundlapalli",
-        "author_inst": "United States Centers for Disease Control and Prevention"
+        "author_name": "Andrea Pilotto",
+        "author_inst": "University of Brescia and ASST Spedali CIvili of Brescia"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -463717,69 +465760,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.11.22.21266692",
-    "rel_title": "Serological responses to COVID-19 booster vaccine in England",
+    "rel_doi": "10.1101/2021.11.22.21266713",
+    "rel_title": "In Vitro Nasal Tissue Model for the Validation of Nasopharyngeal and Mid-turbinate Swabs for SARS-CoV-2 Testing",
     "rel_date": "2021-11-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.22.21266692",
-    "rel_abs": "IntroductionThere are limited data on immune responses after COVID-19 vaccine boosters in individuals receiving primary immunisation with BNT162b2 (Pfizer-BioNTech) or AZD1222 (AstraZeneca).\n\nMethodsA prospective, cohort study to assess SARS-CoV-2 antibody responses before and after booster vaccination with BNT162b2 in adults receiving either (i) two BNT162b2 doses <30 days apart (BNT162b2-control), (ii) two BNT162b2 doses [&ge;]30 days apart (BNT162b2-extended) or (iii) two AZD1222 doses [&ge;]30 days apart (AZD1222-extended) in London, England. SARS-CoV-2 spike protein antibody geometric mean titres (GMTs) before and 2-4 weeks after booster were compared.\n\nResultsOf 750 participants, 626 provided serum samples for up to 38 weeks after their second vaccine dose. Antibody GMTs peaked at 2-4 weeks after the second dose, before declining by 68% at 36-38 weeks after dose 2 for BNT162b2-control participants, 85% at 24-29 weeks for BNT162b2-extended participants and 78% at 24-29 weeks for AZD1222-extended participants. Antibody GMTs was highest in BNT162b2-extended participants (942 [95%CI, 797-1113]) than AZD1222-extended (183 [124-268]) participants at 24-29 weeks or BNT162b2-control participants at 36-38 weeks (208; 95%CI, 150-289). At 2-4 weeks after booster, GMTs were significantly higher than after primary vaccination in all three groups: 18,104 (95%CI, 13,911-23,560; n=47) in BNT162b2-control (76.3-fold), 13,980 (11,902-16,421; n=118) in BNT162b2-extended (15.9-fold) and 10,799 (8,510-13,704; n=43) in AZD1222-extended (57.2-fold) participants. BNT162b2-control participants (median:262 days) had a longer interval between primary and booster doses than BNT162b2-extended or AZD1222-extended (both median:186 days) participants.\n\nConclusionsWe observed rapid serological responses to boosting with BNT162b2, irrespective of vaccine type or schedule used for primary immunisation, with higher post-booster responses with longer interval between primary immunisation and boosting. Boosters will not only provide additional protection for those at highest risk of severe COVID-19 but also prevent infection and, therefore, interrupt transmission, thereby reducing infections rates in the population. Ongoing surveillance will be important for monitoring the duration of protection after the booster.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.22.21266713",
+    "rel_abs": "Large-scale population testing is a key tool to mitigate the spread of respiratory pathogens, as in the current COVID-19 pandemic, where swabs are used to collect samples in the upper airways (e.g. nasopharyngeal and mid-turbinate nasal cavities) for diagnostics. However, the high volume of supplies required to achieve large-scale population testing has posed unprecedented challenges for swab manufacturing and distribution, resulting in a global shortage that has heavily impacted testing capacity world-wide and prompted the development of new swabs suitable for large-scale production. Newly designed swabs require rigorous pre-clinical and clinical validation studies that are costly and time consuming (i.e. months to years long); reducing the risks associated with swab validation is therefore paramount for their rapid deployment. To address these shortages, we developed a 3D-printed tissue model that mimics the nasopharyngeal and mid-turbinate nasal cavities, and we validated its use as a new tool to rapidly test swab performance. In addition to the nasal architecture, the tissue model mimics the soft nasal tissue with a silk-based sponge lining, and the physiological nasal fluid with asymptomatic and symptomatic viscosities of synthetic mucus. We performed several assays comparing standard flocked and injection-molded swabs. We quantified the swab pick-up and release, and determined the effect of viral load and mucus viscosity on swab efficacy by spiking the synthetic mucus with heat-inactivated SARS-CoV-2 virus. By molecular assays, we found that injected molded swabs performed similarly or superiorly in comparison to standard flocked swabs and we underscored a viscosity-dependent difference in cycle threshold values between the asymptomatic and symptomatic mucus for both swabs. To conclude, we developed an in vitro nasal tissue model, that corroborated previous swab performance data from clinical studies, with the potential of providing researchers with a clinically relevant, reproducible, safe, and cost-effective validation tool for the rapid development of newly designed swabs.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Georgina Ireland",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Heather Whitaker",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Shamez N Ladhani",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Frances Baawuah",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Vani Subbarao",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Devon R Hartigan",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Ezra Linley",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Miryam Adelfio",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Lenesha Warrener",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Molly E Shutt",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Michelle O'Brien",
-        "author_inst": "Brondesbury Medical Centre, Kilburn, London, United Kingdom"
+        "author_name": "Stephanie M Jones",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Corrine Whillock",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Shreya Patel",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Paul Moss",
-        "author_inst": "University of Birmingham"
+        "author_name": "Joshua T Marchand",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Mary E Ramsay",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Pamela D McGuinness",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Gayatri Amirthalingam",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Bryan O Buchholz",
+        "author_inst": "University of Massachusetts Lowell"
       },
       {
-        "author_name": "Kevin E Brown",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Chiara Elia Ghezzi",
+        "author_inst": "University of Massachusetts Lowell"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -465447,65 +467474,33 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2021.11.24.21266401",
-    "rel_title": "Effectiveness of BNT162b2 and ChAdOx1 against SARS-CoV-2 household transmission - a prospective cohort study in England",
+    "rel_doi": "10.1101/2021.11.22.21266599",
+    "rel_title": "Modeling on Wastewater Treatment Process in Saudi Arabia: a perspective of Covid-19",
     "rel_date": "2021-11-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.24.21266401",
-    "rel_abs": "BackgroundThe ability of SARS-CoV-2 vaccines to protect against infection and onward transmission determines whether immunisation can control global circulation. We estimated effectiveness of BNT162b2 and ChAdOx1 vaccines against acquisition and transmission of the Alpha and Delta variants in a prospective household study in England.\n\nMethodsAdult index cases in the community and their household contacts took oral-nasal swabs on days 1, 3 and 7 after enrolment. Swabs were tested by RT-qPCR with genomic sequencing conducted on a subset. We used Bayesian logistic regression to infer vaccine effectiveness against acquisition and transmission, adjusted for age, vaccination history and variant.\n\nFindingsBetween 2 February 2021 and 10 September 2021 213 index cases and 312 contacts were followed up. After excluding households lacking genomic proximity (N=2) or with unlikely serial intervals (N=16), 195 households with 278 contacts remained of whom 113 (41%) became PCR positive. Delta lineages had 1.64 times the risk (95% Credible Interval: 1.15 - 2.44) of transmission than Alpha; contacts older than 18 years were 1.19 times (1.04 - 1.52) more likely to acquire infection than children. Effectiveness of two doses of BNT162b2 against transmission of Delta was 31% (-3%, 61%) and 42% (14%, 69%) for ChAdOx1, similar to their effectiveness for Alpha. Protection against infection with Alpha was higher than for Delta, 71% (12%,95%) vs 24% (-2%, 64%) respectively for BNT162b2 and 26% (-39%, 73%) vs 14% (-5%, 46%) respectively for ChAdOx1.\n\nInterpretationBNT162b2 and ChAdOx1 reduce transmission of the Delta variant from breakthrough infections in the household setting though their protection against infection is low.\n\nFundingThis study was funded by the UK Health Security Agency (formerly Public Health England) as part of the COVID-19 response.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.22.21266599",
+    "rel_abs": "The novel coronavirus disease (COVID-19) pandemic has had devastating effects on healthcare systems and the global economy. Moreover, coronavirus has been found in human feces, sewage, and in wastewater treatment plants. In this paper, we highlight the transmission behavior, occurrence, and persistence of the virus in sewage and wastewater treatment plants. Our approach follows the process of identifying a coronavirus hotspot through existing wastewater plants in major cities of Saudi Arabia. The mathematical distributions, including the log-normal distribution, Gaussian model, and susceptible exposed infected recovery (SEIR) model, are adopted to predict the coronavirus load in wastewater plants. We highlight not only the potential virus removal techniques from wastewater treatment plants, but also methods of tracing SARS-CoV-2 in humans through wastewater treatment plants.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Samuel Clifford",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Pauline Waight",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Jada Hackman",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Stephane Hue",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Charlotte M Gower",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Freja CM Kirsebom",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Catriona Skarnes",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Louise Letley",
-        "author_inst": "UK Health Security Agency"
-      },
-      {
-        "author_name": "Jamie Lopez Bernal",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Abdullah A Ahmadini",
+        "author_inst": "Jazan University"
       },
       {
-        "author_name": "Nick Andrews",
-        "author_inst": "UK Health Security Agency"
+        "author_name": "Ahmed Msmali Hussein",
+        "author_inst": "Jazan University"
       },
       {
-        "author_name": "Stefan Flasche",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Zico Meetei Mutum",
+        "author_inst": "Jazan University"
       },
       {
-        "author_name": "Elizabeth Miller",
-        "author_inst": "London School of Hygiene and Tropical Medicine, UK Health Security Agency"
+        "author_name": "Yaspal Raghav Singh",
+        "author_inst": "Jazan University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -467293,71 +469288,55 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.11.19.21266580",
-    "rel_title": "COVID-19 cases and hospitalizations averted by case investigation and contact tracing in the United States",
+    "rel_doi": "10.1101/2021.11.19.21266581",
+    "rel_title": "Baseline hypocapnia is associated with intubation in COVID-19 diagnosed patients",
     "rel_date": "2021-11-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.19.21266580",
-    "rel_abs": "ImportanceEvidence of the impact of COVID-19 Case Investigation and Contact Tracing (CICT) programs is lacking. Policymakers need this evidence to assess its value.\n\nObjectiveEstimate COVID-19 cases and hospitalizations averted nationwide by US states CICT programs.\n\nDesignWe combined data from US CICT programs (e.g., proportion of cases interviewed, contacts notified or monitored, and days to case and contact notification) with incidence data to model CICT impacts over 60 days period (November 25, 2020 to January 23, 2021) during the height of the pandemic. We estimated a range of impacts by varying assumed compliance with isolation and quarantine recommendations.\n\nSettingUS States and Territories\n\nParticipantsFifty-nine state and territorial health departments that received federal funding supporting COVID-19 pandemic response activities were eligible for inclusion. Of these, 22 states and 1 territory reported all measures necessary for the analysis. These 23 jurisdictions covered 42.5% of the US population (140 million persons), spanned all 4 census regions, and reported data that reflected all 59 federally funded CICT programs.\n\nInterventionPublic health case investigation and contact tracing\n\nMain Outcomes and MeasuresCases and hospitalizations averted; percent of cases averted among cases not prevented by vaccination and other non-pharmaceutical interventions (other NPIs).\n\nResultsWe estimated 1.11 million cases and 27,231 hospitalizations were averted by CICT programs under a scenario where 80% of interviewed cases and monitored contacts, and 30% of notified contacts fully complied with isolation and quarantine guidance, eliminating their contributions to future transmission. As many as 1.36 million cases and 33,527 hospitalizations could have been prevented if all interviewed cases and monitored contacts had entered into and fully complied with isolation and quarantine guidelines upon being interviewed or notified. Across all scenarios and jurisdictions, CICT averted a median of 21.2% (range: 1.3% - 65.8%) of the cases not prevented by vaccination and other NPIs.\n\nConclusions and RelevanceCICT programs likely had a substantial role in curtailing the pandemic in most jurisdictions during the winter 2020-2021 peak. Differences in impact across jurisdictions indicate an opportunity to further improve CICT effectiveness. These estimates demonstrate the potential benefits from sustaining and improving these programs.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSWhat were the health impacts of COVID-19 case investigation and contact tracing programs (CICT) in the US?\n\nFindingsBy combining CICT program data from 22 states and 1 territory with mathematical modeling, we estimate CICT averted between 1.11 to 1.36 million cases and 27,231 to 33,527 hospitalizations over 60 days during the height of the pandemic (winter 2020-21). The upper estimate assumes all interviewed cases and monitored contacts complied with isolation and quarantine guidelines, while the lower estimate assumes fractions of interviewed cases and monitored or notified contacts did so.\n\nMeaningCICT programs likely played a critical role in curtailing the pandemic.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.19.21266581",
+    "rel_abs": "IntroductionHypocapnia may be one of the several factors predefining the need for intubation of patients needing hospitalization for COVID-19 pneumonia.\n\nMethodsA retrospective evaluation of patient files hospitalized for COVID-19 pneumonia from October 2020 until January 2021. Univariate and multivariate regression was used, as well as a multinomial regression to account for multiple endpoints (discharge, intubation, death).\n\nResultsHypocapnia was strongly associated with intubation (OR: 0.86, 95% CI: 0.76, 0.97). Additionally, last pCO2 (OR: 1.08, 95% CI: 1.01, 1.16), baseline FiO2 (OR: 1.05, 95% CI: 1.03, 1.07) as well as last FiO2 (OR: 1.21, 95% CI: 1.11, 1.46), total severity score on admission (OR: 1.18, 95% CI: 1.03, 1.37) and last pO2 (OR: 0.89, 95% CI: 0.85, 0.92) were found to have a significant impact on intubation. Incorporation of deceased patients withheld the negative association with pCO2 levels (OR: 0.88, 95% CI: 0.78, 0.98).\n\nConclusionThe dissociation between respiratory failure and a clinically comfortable patient is partly due to decreased carbon dioxide levels and clinicians should bare it in mind when handling patients with COVID-19 pneumonia. Hypocapnia seems to be a determinant factor of intubation in patients with COVID-19 pneumonia in this study.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Gabriel Rainisch",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Seonghye Jeon",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Danielle Pappas",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Kimberly Spencer",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Leah S Fischer",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Athanasios Gounidis Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Bishwa Adhikari",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Alexandros Evangeliou Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Melanie Taylor",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Christina Kloura Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Bradford Greening Jr.",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Evangelia Magganari Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Patrick Moonan",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Christiana Parisi Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "John Oeltmann",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Michail Kourtidis Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Emily B Kahn",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Martha Apostolopoulou Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Michael Washington",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Georgios Kotronis Dr",
+        "author_inst": "Department of Internal Medicine, Agios Pavlos General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Martin I Meltzer",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Fani Apostolidou Kiouti MD",
+        "author_inst": "Laboratory of Hygiene, Social & Preventive Medicine and Medical Statistics, Medical Faculty, Aristotle University of Thessaloniki"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "respiratory medicine"
   },
   {
     "rel_doi": "10.1101/2021.11.18.21266489",
@@ -469015,79 +470994,87 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.11.17.21266488",
-    "rel_title": "Enoxaparin for thromboprophylaxis in hospitalized COVID-19 patients: comparison of 40 mg o.d. vs 40 mg b.i.d. The X-COVID19 Randomized Clinical Trial",
-    "rel_date": "2021-11-21",
+    "rel_doi": "10.1101/2021.11.17.21266367",
+    "rel_title": "A prospective study of asymptomatic SARS-CoV-2 infection among individuals involved in academic research under limited operations during the COVID-19 pandemic",
+    "rel_date": "2021-11-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266488",
-    "rel_abs": "It is uncertain whether higher doses of anticoagulants than recommended for thromboprophylaxis are necessary in COVID-19 patients hospitalized in general wards. This is a multicentre, open-label, randomized trial performed in 9 Italian centres, comparing 40 mg b.i.d. vs 40 mg o.d. enoxaparin in COVID-19 patients, between April 30, 2020 and April 25, 2021. Primary efficacy outcome was in-hospital incidence of venous thromboembolism (VTE): asymptomatic or symptomatic proximal deep vein thrombosis (DVT) diagnosed by serial compression ultrasonography (CUS), and/or symptomatic pulmonary embolism (PE) diagnosed by computed tomography angiography (CTA). Secondary endpoints included each individual component of the primary efficacy outcome and a composite of death, VTE, mechanical ventilation, stroke, myocardial infarction, admission to ICU. Safety outcomes included major bleeding. The study was interrupted prematurely due to slow recruitment. We included 183 (96%) of the 189 enrolled patients in the primary analysis (91 in b.i.d., 92 in o.d.). Primary efficacy outcome occurred in 6 patients (6{middle dot}5%, 0 DVT, 6 PE) in the o.d. group and 0 in the b.id. group (ARR 6{middle dot}5, 95% CI, 1{middle dot}5-11{middle dot}6). Absence of concomitant DVT and imaging characteristics suggest that most pulmonary artery occlusions were actually caused by local thrombi rather than PE. Statistically non-significant differences in secondary and safety endpoints were observed, with two major bleeding events in each arm. In conclusion, no DVT developed in COVID-19 patients hospitalized in general wards, independently of enoxaparin dosing used for thromboprophylaxis. Pulmonary artery occlusions developed only in the o.d. group. Our trial is underpowered and with few events.\n\nREGISTRATIONClinicalTrials.gov Identifier: NCT04366960\n\nEthics Commettee approvation number75/2020",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266367",
+    "rel_abs": "BackgroundEarly in the pandemic, transmission risk from asymptomatic infection was unclear making it imperative to monitor infection in workplace settings. Further, data on SARS-CoV-2 seroprevalence within university populations has been limited.\n\nMethodsWe performed a longitudinal study of University research employees on campus July-December 2020. We conducted questionnaires on COVID-19 risk factors, RT-PCR testing, and SARS-CoV-2 serology using an in-house spike RBD assay, laboratory-based Spike NTD assay, and standard nucleocapsid platform assay. We estimated prevalence and cumulative incidence of seroconversion with 95% confidence intervals using the inverse of the Kaplan-Meier estimator.\n\nResults910 individuals were included in this analysis. At baseline, 6.2% (95% CI 4.29-8.19) were seropositive using the spike RBD assay; four (0.4%) were seropositive using the nucleocapsid assay, and 44 (4.8%) using the Spike NTD assay. Cumulative incidence was 3.61% (95% CI: 2.04-5.16). Six asymptomatic individuals had positive RT-PCR results.\n\nConclusionsPrevalence and incidence of SARS-CoV-2 infections was low; however differences in target antigens of serological tests provided different estimates. Future research on appropriate methods of serological testing in unvaccinated and vaccinated populations is needed. Frequent RT-PCR testing of asymptomatic individuals is required to detect acute infections, and repeated serosurveys are beneficial for monitoring subclinical infection.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Nuccia Morici",
-        "author_inst": "ASST GRANDE OSPEDALE METROPOLITANO NIGUARDA"
+        "author_name": "Audrey Pettifor",
+        "author_inst": "Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Gian Marco Podda",
-        "author_inst": "University of Milan; Medicina 2, ASST Santi Paolo e Carlo, Milan, Italy"
+        "author_name": "Bethany L DiPrete",
+        "author_inst": "Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599;  Injury Prevention Rese"
       },
       {
-        "author_name": "Simone Birocchi",
-        "author_inst": "Medicina 2, ASST Santi Paolo e Carlo, Milan, Italy"
+        "author_name": "Bonnie E Shook-Sa",
+        "author_inst": "Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Luca Bonacchini",
-        "author_inst": "ASST Grande Ospedale Metropolitano Niguarda"
+        "author_name": "Lakshmanane Premkumar",
+        "author_inst": "Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Marco Merli",
-        "author_inst": "ASST Grande Ospedale Metropolitano Niguarda"
+        "author_name": "Kriste Kuczynski",
+        "author_inst": "Department of Social Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Michele Trezzi",
-        "author_inst": "Struttura Operativa Complessa (SOC) Malattie Infettive II, AUSL Toscana Centro, Ospedale San Jacopo, Pistoia, Italy"
+        "author_name": "Dirk Dittmer",
+        "author_inst": "Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Gianluca Massaini",
-        "author_inst": "Struttura Operativa Semplice (SOS) Chirurgia vascolare, AUSL Toscana Centro, Ospedale San Jacopo, Pistoia, Italy"
+        "author_name": "Allison Aiello",
+        "author_inst": "Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Marco Agostinis",
-        "author_inst": "Emergency Department, Ospedale San Carlo Borromeo, ASST Santi Paolo e Carlo, Milano, Italy"
+        "author_name": "Shannon Wallet",
+        "author_inst": "Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599; Division of Oral and Craniofa"
       },
       {
-        "author_name": "Giulia Carioti",
-        "author_inst": "Emergency Department, Ospedale San Carlo Borromeo, ASST Santi Paolo e Carlo, Milano, Italy"
+        "author_name": "Robert Maile",
+        "author_inst": "Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599; Department of Surgery, School"
       },
       {
-        "author_name": "Francesco Saverio Serino",
-        "author_inst": "ASL 4 Veneto, Covid Hospital, Jesolo, Italy"
+        "author_name": "Joyce Tan",
+        "author_inst": "Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Gianluca Gazzaniga",
-        "author_inst": "Postgraduate School of Clinical Pharmacology and Toxicology, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy"
+        "author_name": "Ramesh Jadi",
+        "author_inst": "Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Daniela Barberis",
-        "author_inst": "ASST Grande Ospedale Metropolitano Niguarda"
+        "author_name": "Linda Pluta",
+        "author_inst": "Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Laura Antolini",
-        "author_inst": "Center of Bioinformatics, Biostatistics and Bioimaging, School of Medicine and Surgery, University of Milano Bicocca, Monza, Italy"
+        "author_name": "Aravinda M de Silva",
+        "author_inst": "Department of Microbiology and Immunology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       },
       {
-        "author_name": "Maria Grazia Valsecchi",
-        "author_inst": "Center of Bioinformatics, Biostatistics and Bioimaging, School of Medicine and Surgery, University of Milano Bicocca, Monza, Italy"
+        "author_name": "David J Weber",
+        "author_inst": "Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599; Division of Infectious "
       },
       {
-        "author_name": "Marco Cattaneo",
-        "author_inst": "University of Milan; Medicina 2, ASST Santi Paolo e Carlo, Milan, Italy"
+        "author_name": "Min Kim",
+        "author_inst": "Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
+      },
+      {
+        "author_name": "Arlene C Se\u00f1a",
+        "author_inst": "Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
+      },
+      {
+        "author_name": "Corbin D Jones",
+        "author_inst": "Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.11.16.21266265",
@@ -470589,59 +472576,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.11.14.21266334",
-    "rel_title": "Attenuation of antibody titres during 3-6 months after the second dose of the BNT162b2 vaccine depends on sex, with age and smoking as risk factors for lower antibody titres at 6 months",
+    "rel_doi": "10.1101/2021.11.16.21266414",
+    "rel_title": "Unraveling the spatiotemporal spread of COVID-19 in Brazil through spatial network connectivity",
     "rel_date": "2021-11-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.14.21266334",
-    "rel_abs": "ObjectiveWe aimed to determine antibody titres at 6 months and their rate of change during 3-6 months after the second dose of the BNT162b2 coronavirus disease 2019 (COVID-19) mRNA vaccine (Pfizer/BioNTech) and to explore clinical variables associated with titres in Japan.\n\nMethodsWe enrolled 365 healthcare workers (250 women, 115 men) whose 3-month antibody titres were analyzed in our previous study and whose blood samples were collected 183 {+/-} 15 days after the second dose. Participant characteristics collected previously were used. The relationships of these factors with antibody titres at 6 months and rates of change in antibody titres during 3-6 months were analyzed.\n\nResultsMedian age was 44 years. Median antibody titre at 6 months was 539 U/mL. Older participants had significantly lower antibody titres (20s, 752 U/mL; 60s-70s, 365 U/mL). In age-adjusted analysis, smoking was the only factor associated with lower antibody titres. Median rate of change in antibody titres during 3-6 months was -29.4%. The only factor significantly associated with the rate of change in Ab titres was not age or smoking, but sex (women, -31.6%; men, -25.1%).\n\nConclusionThe most important factors associated with lower antibody titres at 6 months were age and smoking, as at 3 months, probably reflecting their effect on peak antibody titres. However, antibody titres significantly attenuated during 3-6 months in women alone, which reduced the sex difference in antibody titres seen during the first 3 months. Antibody titres may be affected by different factors at different time points.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.16.21266414",
+    "rel_abs": "BackgroundDescribing and understanding the process of diffusion can allow local managers better plan emergence scenarios. Thus, the main aim of this study was to describe and unveil the spatiotemporal patterns of diffusion of the COVID-19 in Brazil from February 2020 until April 2021.\n\nMethodsThis is a retrospective purely observational ecologic study including all notified cases and deaths. We used satellite-derived night light imagery and spatiotemporal Empirical Orthogonal Function analysis to quantify the spatial network structure of lighted development and the spatiotemporal transmission of the pathogen through the network.\n\nResultsThe more populous state capitals within the largest network components presented higher frequency of deaths and earlier onset compared to the increasing numbers of smaller, less populous municipalities trending toward lower frequency of deaths and later onset. By week 48 2020, the full network was almost completely affected. Cases and deaths showed a distinct second wave of wider geographic expansion beginning in early November 2020.\n\nConclusionsThe spatiotemporal diffusion in Brazil was characterized by an intertwined process of overseas relocation, hierarchical network transmission and contagious effects. A rapid response as the immediate control of all ports, airports and borders combined with mandatory quarantine are critical to retard disease diffusion.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Yushi Nomura",
-        "author_inst": "National Hospital Organization Utsunomiya National Hospital"
-      },
-      {
-        "author_name": "Michiru Sawahata",
-        "author_inst": "Jichi Medical University"
-      },
-      {
-        "author_name": "Yosikazu Nakamura",
-        "author_inst": "Jichi Medical University"
-      },
-      {
-        "author_name": "Ryousuke Koike",
-        "author_inst": "National Hospital Organization Utsunomiya National Hospital"
-      },
-      {
-        "author_name": "Otohiro Katsube",
-        "author_inst": "National Hospital Organization Utsunomiya National Hospital"
-      },
-      {
-        "author_name": "Koichi Hagiwara",
-        "author_inst": "Jichi Medical University"
-      },
-      {
-        "author_name": "Seiji Niho",
-        "author_inst": "Dokkyo Medical University"
-      },
-      {
-        "author_name": "Norihiro Masuda",
-        "author_inst": "National Hospital Organization Utsunomiya National Hospital"
-      },
-      {
-        "author_name": "Takaaki Tanaka",
-        "author_inst": "National Hospital Organization Utsunomiya National Hospital"
+        "author_name": "Ligia V Barrozo",
+        "author_inst": "Universidade de Sao Paulo"
       },
       {
-        "author_name": "Kumiya Sugiyama",
-        "author_inst": "National Hospital Organization Utsunomiya National Hospital"
+        "author_name": "Christopher Small",
+        "author_inst": "Columbia University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.11.16.21266350",
@@ -472331,47 +474286,79 @@
     "category": "nephrology"
   },
   {
-    "rel_doi": "10.1101/2021.11.15.21265526",
-    "rel_title": "COVID-19 in the Republic of Belarus: pandemic features and the interim safety and efficacy assessment of the Gam-COVID-Vac vaccine",
+    "rel_doi": "10.1101/2021.11.16.21266391",
+    "rel_title": "From online data collection to identification of disease mechanisms: The IL-1beta, IL-6 and TNF-alpha; cytokine triad is associated with post-acute sequelae of COVID-19 in a digital research cohort",
     "rel_date": "2021-11-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.15.21265526",
-    "rel_abs": "ObjectiveTo study the COVID-19 pandemic features among the population of the Republic of Belarus from February 2020 to September 2021 and assess the safety (tolerance) and epidemiological efficacy of the Gam-COVID-Vac vaccine (Sputnik V).\n\nMaterials and methodsA retrospective analysis of COVID-19 cases in the Republic of Belarus from the beginning of registration (February 28, 2020) to September 12, 2021 was performed. To assess the COVID-19 case detection dynamics, official registration data available on the website of the Ministry of Health of the Republic of Belarus were used.\n\nVaccine safety (tolerance) and efficacy were assessed in an observational study. Safety (tolerance) was assessed by presence/absence of adverse reactions: general and local ones.\n\nThe efficacy rate (E) and the epidemiological efficacy index (K) was calculated according to the formula: E(%)=100*(b-a)/b, K=b/a.\n\nResultsOur data show that The COVID-19 pandemic in the Republic of Belarus is characterized by successive development stages: the first is the absence of COVID-19 cases in the country; the second is the registration of individual infection cases that came from abroad followed by local pathogen spread among the countrys population; the third is a local spread of COVID-19 among individuals who had contact with infected people; the fourth is the detection of cases where patients had no history of exposure to COVID-19 patients.\n\nAs of calendar week 26, 2021 Delta variant of SARS-CoV-2 has become the prevalent in the country.\n\nFollow-up results in January-August 2021 showed that the Sputnik V vaccine was well tolerated, with 80,832 adverse reactions reported (2.99% (95% CI 2.9-3.0) of the total number of vaccine doses administered). In terms of severity, adverse reactions were mild (91.4% (95% CI 91.2-91.6)) and moderate (8.6% (95% CI 8.6-8.8)). The epidemiological efficacy rate was 96.3%, the epidemiological efficacy index was 26.7. Thus, the results obtained testify to high prophylactic efficacy of the Sputnik V vaccine.\n\nConclusionsThe COVID-19 pandemic in the Republic of Belarus is characterized by successive development stages: from no cases in early 2020 to detected cases where most individuals had no history of contact with COVID-19 patients; periods of rising and falling incidence. The Sputnik V vaccine has demonstrated a high safety profile and epidemiological efficacy throughout mass vaccination in the Republic of Belarus.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.16.21266391",
+    "rel_abs": "Post-acute sequelae of COVID-19 (PASC) emerge as a global problem with unknown molecular drivers. In a digital epidemiology approach, we rapidly recruited 8,077 individuals out of 129,733 households in Halle (Saale) to the cohort study for digital health research in Germany (DigiHero). These responded to a basic questionnaire followed by a PASC-focused survey and blood sampling in case of prior positive SARS-CoV-2 testing in their household. The presented analysis is based on the first 318 DigiHero participants, the majority thereof after mild infections. PASC were reported in 67.8% of cases, consisted predominantly in fatigue, dyspnea and concentration deficit, persisted in 60% over the follow-up period of on average eight months and their resolution was unaffected by post-infection vaccination. PASC was not associated with post-COVID-19 autoantibodies, but with elevated levels of IL-1{beta}, IL-6 and TNF-. Blood profiling and single-cell data from validation cohorts with early infection suggested the induction of these cytokines in COVID-19 lung pro-inflammatory macrophages creating a self-sustaining feedback loop. Our data indicate a long-lasting cytokine triad -potentially underlying PASC symptoms - to be driven by macrophage primed during infection. We demonstrate how the combination of digital epidemiology with selective biobanking can rapidly generate hints towards disease mechanisms.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Ala M Dashkevich",
-        "author_inst": "Republican Centre of Hygiene, Epidemiology and Public Health"
+        "author_name": "Christoph Schultheiss",
+        "author_inst": "Martin-Luther-University Halle-Wittenberg, Internal Medicine IV"
       },
       {
-        "author_name": "Veronika S Vysotskaya",
-        "author_inst": "Republican Centre of Hygiene, Epidemiology and Public Health"
+        "author_name": "Edith Willscher",
+        "author_inst": "Martin-Luther-University Halle-Wittenberg, Internal Medicine IV"
       },
       {
-        "author_name": "Iryna N Hlinskaya",
-        "author_inst": "Republican Centre of Hygiene, Epidemiology and Public Health"
+        "author_name": "Lisa Paschold",
+        "author_inst": "Martin-Luther-University Halle-Wittenberg, Internal Medicine IV"
       },
       {
-        "author_name": "Anzhela L Skuranovich",
-        "author_inst": "Republican Centre of Hygiene, Epidemiology and Public Health"
+        "author_name": "Cornelia Gottschick",
+        "author_inst": "Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther Univer"
       },
       {
-        "author_name": "Aliaksandr A Tarasenka",
-        "author_inst": "Ministry of Health of the Republic of Belarus"
+        "author_name": "Bianca Klee",
+        "author_inst": "Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther Univer"
       },
       {
-        "author_name": "Inna A Karaban",
-        "author_inst": "Ministry of Health of the Republic of Belarus"
+        "author_name": "Svenja-Sibylla Henkes",
+        "author_inst": "Martin-Luther-University Halle-Wittenberg, Internal Medicine IV"
       },
       {
-        "author_name": "Natalia D Kolomiets",
-        "author_inst": "Belarusian Medical Academy of Postgraduate Education"
+        "author_name": "Lidia Bosurgi",
+        "author_inst": "Department of Medicine, University Medical Center Hamburg-Eppendorf"
+      },
+      {
+        "author_name": "Jochen Dutzmann",
+        "author_inst": "Mid-German Heart Center, Department of Cardiology and Intensive Care Medicine, University Hospital, Martin-Luther-University Halle-Wittenberg"
+      },
+      {
+        "author_name": "Daniel Sedding",
+        "author_inst": "Mid-German Heart Center, Department of Cardiology and Intensive Care Medicine, University Hospital, Martin-Luther-University Halle-Wittenberg"
+      },
+      {
+        "author_name": "Thomas Frese",
+        "author_inst": "Institute of General Practice and Family Medicine, Martin-Luther-University Halle-Wittenberg"
+      },
+      {
+        "author_name": "Matthias Girndt",
+        "author_inst": "Department of Internal Medicine II, Martin-Luther-University Halle-Wittenberg"
+      },
+      {
+        "author_name": "Jessica I. Hoell",
+        "author_inst": "Pediatric Hematology and Oncology, Martin-Luther-University Halle-Wittenberg"
+      },
+      {
+        "author_name": "Michael Gekle",
+        "author_inst": "Julius Bernstein-Institute of Physiology, Faculty of Medicine, Martin-Luther-University Halle-Wittenberg"
+      },
+      {
+        "author_name": "Rafael Mikolajczyk",
+        "author_inst": "Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin-Luther Univer"
+      },
+      {
+        "author_name": "Mascha Binder",
+        "author_inst": "Martin-Luther-University Halle-Wittenberg, Internal Medicine IV"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.11.14.21266214",
@@ -474501,51 +476488,111 @@
     "category": "cardiovascular medicine"
   },
   {
-    "rel_doi": "10.1101/2021.11.12.21266292",
-    "rel_title": "Covid-19 Pandemic and its Effect on Residents' Mental Well-Being",
+    "rel_doi": "10.1101/2021.11.10.21266063",
+    "rel_title": "Case Series of Thrombosis with Thrombocytopenia Syndrome following COVID-19 vaccination--United States, December 2020-August 2021",
     "rel_date": "2021-11-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.12.21266292",
-    "rel_abs": "Concerns about COVID-19s long-term consequences on the mental health of frontline health professionals are mounting as the entire world strives anew to contain it. The primary objective of this research is to describe the impact of working during the COVID-19 pandemic on junior doctors mental health and to investigate the effect of the COVID-19 pandemic on junior doctors training and professional performance. A cross-sectional online survey using the Google Forms platform was conducted from May 1st to May 30th, 2021, in 311 healthcare workers who were currently enrolled in a residency program at the Kuwait Institutional of Medical Specialization (KIMS). Socio-demographic details of each health worker were collected and the scores related to depression, anxiety, and stress were measured using the previously validated depression anxiety stress scale-21 (DASS-21). Higher stress scores were seen in those who were devoid of the option to work with COVID-19 patients (adjusted {beta} 5.1 (95%CI:1.2-9);p=0.01), who reported that working during the pandemic affected their study schedule (adjusted {beta} 4.8 (95%CI:1.6-8.1);p= 0.004), and who lost off service training time (adjusted {beta} 2.7 (95%CI:0.13-5.2); p=0.034). Further, the anxiety scores were significantly higher in females. The impact of the ongoing pandemic on residents mental health is grave, necessitating psychological treatment and support. The study discovered various factors linked to depression, anxiety, and stress. As a result, these aspects must be regarded to protect the residents mental health.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.10.21266063",
+    "rel_abs": "BackgroundThrombosis with thrombocytopenia syndrome (TTS) is a potentially life-threatening condition associated with adenoviral-vectored COVID-19 vaccination. TTS presents similarly to autoimmune heparin-induced thrombocytopenia. Twelve cases of cerebral venous sinus thrombosis following Janssen/Johnson & Johnson (Ad26.COV2.S) COVID-19 vaccination have been described.\n\nObjectiveDescribe surveillance data and reporting rates of TTS cases following COVID-19 vaccination.\n\nDesignCase series.\n\nSettingUnited States\n\nPatientsCase-patients reported to the Vaccine Adverse Event Reporting System (VAERS) receiving COVID-19 vaccine from December 14, 2020 through August 31, 2021, with thrombocytopenia and thrombosis (excluding isolated ischemic stroke or myocardial infarction). If thrombosis was only in an extremity vein or pulmonary embolism, a positive enzyme-linked immunosorbent assay for anti-platelet factor 4 antibody was required.\n\nMeasurementsReporting rates (cases/million vaccine doses) and descriptive epidemiology.\n\nResults52 TTS cases were confirmed following Ad26.COV2.S (n=50) or mRNA-based COVID-19 (n=2) vaccination. TTS reporting rates were 3.55 per million (Ad26.COV2.S) and 0.0057 per million (mRNA-based COVID-19 vaccines). Median age of patients with TTS following Ad26.COV2.S vaccination was 43.5 years (range: 18-70); 70% were female. Both TTS cases following mRNA-based COVID-19 vaccination occurred in males aged >50 years. All cases following Ad26.COV2.S vaccination involved hospitalization including 32 (64%) with intensive care unit admission. Outcomes of hospitalizations following Ad26.COV2.S vaccination included death (12%), discharge to post-acute care (16%), and discharge home (72%).\n\nLimitationsUnder-reporting and incomplete case follow-up.\n\nConclusionTTS is a rare but serious adverse event associated with Ad26.COV2.S vaccination. The different demographic characteristics of the two cases reported after mRNA-based COVID-19 vaccines and the much lower reporting rate suggest that these cases represent a background rate.\n\nFunding SourceCDC",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Anwar Yazdani",
-        "author_inst": "Anesthesia and ICU Department, AlSabah Hospital, Kuwait"
+        "author_name": "Isaac See",
+        "author_inst": "CDC"
+      },
+      {
+        "author_name": "Allison Lale",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Paige Marquez",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Hend Esmaeili",
-        "author_inst": "Department of Anesthesia and Critical Care, Farwaniya Hospital, Kuwait"
+        "author_name": "Michael B Streiff",
+        "author_inst": "The Johns Hopkins University"
       },
       {
-        "author_name": "Abdulla K AlSaleh",
-        "author_inst": "Anesthesia and ICU Department, Amiri Hospital, Kuwait"
+        "author_name": "Allison P Wheeler",
+        "author_inst": "Vanderbilt University Medical Center"
       },
       {
-        "author_name": "Ahmed Sultan",
-        "author_inst": "Anesthesia and ICU Department, Amiri Hospital, Kuwait"
+        "author_name": "Naomi K Tepper",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Esam Alamad",
-        "author_inst": "Anesthesia and ICU Department, Al Adan Hospital, Kuwait"
+        "author_name": "Emily Jane Woo",
+        "author_inst": "Food and Drug Administration"
       },
       {
-        "author_name": "Ali Bandar",
-        "author_inst": "Department of Anesthesia and critical care, Jaber Hospital, Kuwait"
+        "author_name": "Karen R Broder",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Hanouf Rawdhan",
-        "author_inst": "Department of Anesthesia  Kuwait Cancer Control Center"
+        "author_name": "Kathryn M Edwards",
+        "author_inst": "Vanderbilt University Medical Center"
       },
       {
-        "author_name": "Mariam Ayed",
-        "author_inst": "Ministry of Health"
+        "author_name": "Ruth Gallego",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Andrew I Geller",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Kelly A Jackson",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Shashi Sharma",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Kawsar R Talaat",
+        "author_inst": "The Johns Hopkins University"
+      },
+      {
+        "author_name": "Emmanuel B Walter",
+        "author_inst": "Duke University School of Medicine"
+      },
+      {
+        "author_name": "Imo J Akpan",
+        "author_inst": "Columbia University Irving Medical Center"
+      },
+      {
+        "author_name": "Thomas L Ortel",
+        "author_inst": "Duke University School of Medicine"
+      },
+      {
+        "author_name": "Shannon Walker",
+        "author_inst": "Vanderbilt University Medicine Center"
+      },
+      {
+        "author_name": "Jennifer C Yui",
+        "author_inst": "The Johns Hopkins University"
+      },
+      {
+        "author_name": "Tom T Shimabukuro",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Adamma Mba-Jonas",
+        "author_inst": "Food and Drug Administration"
+      },
+      {
+        "author_name": "John R Su",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "David K Shay",
+        "author_inst": "Centers for Disease Control and Prevention"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.11.12.21266183",
@@ -476315,57 +478362,45 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.11.11.21266216",
-    "rel_title": "Effectiveness of non-pharmaceutical measures (NPIs) on COVID-19 in Europe: A systematic literature review",
+    "rel_doi": "10.1101/2021.11.10.21266124",
+    "rel_title": "Differences in COVID-19 vaccination coverage by occupation in England: a national linked data study",
     "rel_date": "2021-11-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.11.21266216",
-    "rel_abs": "BackgroundThe study objective was to conduct a systematic review to assess the effectiveness of non-pharmaceutical interventions (NPIs) to reduce the transmission of SARS-CoV-2 in Europe during the first wave of the pandemic.\n\nMethodsWe searched OVID Medline, EMBASE, and the Cochrane and Campbell Databases for Systematic Reviews published up to April 15th 2021. Focusing on community (meso-level) and society (macro-level) level NPIs, we included all study designs, while a geographic restriction was limited to the EU, UK and European Economic Area (EEA) countries. Using the PICO framework, two reviewers independently extracted data and assessed quality using appropriate quality appraisal tools. A qualitative synthesis was performed, with NPIs grouped initially by a) Physical Distancing measures, b) Case detection and management measures, and c) hygiene measures and subsequently by country.\n\nResultsOf 17,692 studies initially assessed, 45 met all inclusion criteria. Most studies (n=30) had a modelling study design, while 13 were observational, one quasi-experimental and one experimental. Evidence from across the European continent, presented by country, indicates that the implementations of physical distancing measures (i.e., lockdowns/quarantines), preferably earlier in the pandemic, reduce the number of cases and hospitalisation across settings and for which the timing and duration are essential parameters. Case detection and management measures were also identified as effective measures at certain levels of testing and incidence, while hygiene and safety measures complemented the implementation of physical distancing measures.\n\nConclusionsThis literature review represents a comprehensive assessment of the effectiveness of NPIs in Europe up to April 2021. Despite heterogeneity across studies, NPIs, as assessed within the context of this systematic review at the macro and meso level, are effective in reducing SARS-CoV-2 transmission rates and COVID-19 hospitalisation rates and deaths in the European Region and may be applied as response strategies to reduce the burden of COVID-19 in forthcoming waves.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.10.21266124",
+    "rel_abs": "BackgroundMonitoring differences in COVID-19 vaccination uptake in different groups is crucial to help inform the policy response to the pandemic. A key gap is the absence of data on uptake by occupation.\n\nMethodsUsing nationwide population-level data, we calculated the proportion of people who had received two doses of a COVID-19 vaccine (assessed on 31 August 2021) by detailed occupational categories in adults aged 40-64 and estimated adjusted odds ratios to examine whether these differences were driven by occupation or other factors, such as education. We also examined whether vaccination rates differed by ability to work from home.\n\nResultsOur study population included 14,298,147 adults 40-64. Vaccination rates differed markedly by occupation, being higher in administrative and secretarial occupations (90.8%); professional occupations (90.7%); and managers, directors and senior officials (90.6%); and lowest (83.1%) in people working in elementary occupations. We found substantial differences in vaccination rates looking at finer occupational groups even after adjusting for confounding factors, such as education. Vaccination rates were higher in occupations which can be done from home and lower in those which cannot. Many occupations with low vaccination rates also involved contact with the public or with vulnerable people\n\nConclusionsIncreasing vaccination coverage in occupations with low vaccination rates is crucial to help protecting the public and control infection, especially in occupations that cannot be done from home and involve contacts with the public. Policies such as  work from home if you can may only have limited future impact on hospitalisations and deaths\n\nWhat is already known on this subject?Whilst several studies highlight differences in vaccination coverage by ethnicity, religion, socio-demographic factors and certain underlying health conditions, there is very little evidence on how vaccination coverage varies by occupation, in the UK and elsewhere. The few study looking at occupational differences in vaccine hesitancy focus on healthcare workers or only examined broad occupational groups. There is currently no large-scale study on occupational differences in COVID-19 vaccination coverage in the UK.\n\nWhat this study adds?Using population-level linked data combining the 2011 Census, primary care records, mortality and vaccination data, we found that the vaccination rates of adults aged 40 to 64 years in England differed markedly by occupation. Vaccination rates were high in administrative and secretarial occupations, professional occupations and managers, directors and senior officials and low in people working in elementary occupations. Adjusting for other factors likely to be linked to occupation and vaccination, such as education, did not substantially alter the results. Vaccination rates were also associated with the ability to work from home, with the vaccination rate being higher in occupations which can be done performed from home. Policies aiming to increase vaccination rates in occupations that cannot be done from home and involve contacts with the public should be priorities",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Constantine Vardavas",
-        "author_inst": "University of Crete"
-      },
-      {
-        "author_name": "Katerina Nikitara",
-        "author_inst": "University of Crete"
-      },
-      {
-        "author_name": "Katerina Aslanoglou",
-        "author_inst": "University of Crete"
-      },
-      {
-        "author_name": "Michele Hilton Boon",
-        "author_inst": "WISE Centre for Economic Justice, Glasgow Caledonian University"
+        "author_name": "Vahe Nafilyan",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Revati Phalkey",
-        "author_inst": "Climate Change and Health Group, Public Health England, United Kingdom"
+        "author_name": "Ted Dolby",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Jo Leonardi-Bee",
-        "author_inst": "Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, UK"
+        "author_name": "Katie Finning",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Gkikas Magiorkinis",
-        "author_inst": "National and Kapodistrian University of Athens"
+        "author_name": "Jasper Morgan",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Paraskevi Katsaounou",
-        "author_inst": "Department of Respiratory Medicine, National and Kapodistrian University of Athens, Athens, Greece"
+        "author_name": "Rhiannon Edge",
+        "author_inst": "Lancaster University"
       },
       {
-        "author_name": "Anastasia Pharris",
-        "author_inst": "European Centre for Disease Prevention and Control"
+        "author_name": "Myer Glickman",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Ettore Severi",
-        "author_inst": "European Centre for Disease Prevention and Control"
+        "author_name": "Neil Pearce",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Jonathan E. Suk",
-        "author_inst": "European Centre for Disease Prevention and Control"
+        "author_name": "Martie Van Tongeren",
+        "author_inst": "University of Manchester"
       }
     ],
     "version": "1",
@@ -478249,71 +480284,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.11.09.21266145",
-    "rel_title": "Viral kinetic modeling and clinical trial simulation predicts disruption of respiratory disease trials by non-pharmaceutical COVID-19 interventions",
+    "rel_doi": "10.1101/2021.11.09.467827",
+    "rel_title": "A novel histone deacetylase inhibitor-based approach to eliminate microglia and retain astrocyte properties in glial cell culture.",
     "rel_date": "2021-11-10",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.09.21266145",
-    "rel_abs": "Clinical research in infectious respiratory diseases has been profoundly affected by non-pharmaceutical interventions (NPIs) against COVID-19. On top of trial delays or even discontinuation which have been observed in all disease areas, NPIs altered transmission pattern of many seasonal respiratory viruses which followed regular patterns for decades before the pandemic. Clinical trial design based on pre-pandemic historical data therefore needs to be put in question. In this article, we show how knowledge-based mathematical modeling can be used to address this issue. We set up an epidemiological model of respiratory tract infection (RTI) sensitive to a time dependent between-host transmission rate and coupled this model to a mechanistic description of viral RTI episodes in an individual patient. By reducing the transmission rate when the lockdown was introduced in the United Kingdom in March 2020, we were able to reproduce the perturbed 2020 RTI disease burden data. Using this setup, we simulated several NPIs scenarios of various strength (none, mild, medium, strong) and conducted placebo-controlled in silico clinical trials in pediatric patients with recurrent RTIs (RRTI) quantifying annual RTI rate distributions. In interventional arms, virtual patients aged 1-5 years received the bacterial lysate OM-85 (approved in several countries for the prevention of pediatric RRTIs) through a pro-type I immunomodulation mechanism of action described by a physiologically based pharmacokinetics and pharmacodynamics approach (PBPK/PD). Our predictions showed that sample size estimates based on the ratio of RTI rates (or the post-hoc power of fixed sample size trials) are not majorly impacted under NPIs which are less severe (none, mild and medium NPIs) than a strict lockdown (strong NPI). However, NPIs show a stronger impact on metrics more relevant for assessing the clinical relevance of the effect such as absolute benefit. This dichotomy shows the risk that successful trials (even with their primary endpoints being met) still get challenged in risk benefit assessment during the review of market authorization. Furthermore, we found that a mild NPI scenario already affected the time to recruit significantly when sticking to eligibility criteria complying with historical data. In summary, our model predictions can help rationalize and forecast post-COVID-19 trial feasibility. They advocate for gauging absolute and relative benefit metrics as well as clinical relevance for assessing efficacy hypotheses in trial design and they question eligibility criteria misaligned with the actual disease burden.",
-    "rel_num_authors": 13,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.09.467827",
+    "rel_abs": "The close association between astrocytes and microglia causes great difficulties to distinguish their individual roles in innate immune responses in central nervous system. Current chemical-based methods to eliminate microglia in glial cell culture introduce various molecular and functional alterations to astrocytes. Here, we describe a novel two-step approach to achieve a complete elimination of microglia without affecting the biological properties of co-cultured astrocytes by temporal treatment of histone deacetylase inhibitor trichostatin A (TSA). We verify TSA as a potent inducer for microglial-specific cell death, which also causes comprehensive gene expression changes in astrocytes. However, withdrawal of TSA not only ensures no microglia repopulation, but also restores all the gene expression changes in terms of astrocyte functions, including neurotrophic factors, glutamate and potassium transporters, and reactive astrocyte subtypes. By contrast, withdrawal of PLX5622, the commonly used colony-stimulating factor 1 receptor inhibitor neither prevents microglia repopulation nor restores the gene expression changes mentioned above. Using this method, we are able to discriminate differential roles of microglia and astrocytes in the induced expression of antiviral and pro-inflammatory cytokines upon various pathological stimuli including the spike protein of SARS-CoV-2. This simple and efficient method can be customized for the understanding of microglia-astrocyte interaction and the development of epigenetic therapies that target over-activated microglia in neuroinflammation-related diseases.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Simon Ars\u00e8ne",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Claire Couty",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Igor Faddeenkov",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Natacha Go",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Sol\u00e8ne Granjeon-Noriot",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Daniel \u0160m\u00edt",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Riad Kahoul",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Ben Illigens",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Jean-Pierre Boissel",
-        "author_inst": "Novadiscovery"
-      },
-      {
-        "author_name": "Aude Chevalier",
-        "author_inst": "OM Pharma"
+        "author_name": "Xi-Biao He",
+        "author_inst": "Shanghai University of Medicine & Health Sciences"
       },
       {
-        "author_name": "Lorenz Lehr",
-        "author_inst": "OM Pharma"
+        "author_name": "Yi Wu",
+        "author_inst": "Speech Therapy Department, The Second Rehabilitation Hospital of Shanghai, Shanghai, China"
       },
       {
-        "author_name": "Christian Pasquali",
-        "author_inst": "OM Pharma"
+        "author_name": "Haozhi Huang",
+        "author_inst": "Department of Orthopaedic Surgery, Shanghai Tenth Peoples Hospital Affiliated to Tongji University, Shanghai, China"
       },
       {
-        "author_name": "Alexander Kulesza",
-        "author_inst": "Novadiscovery"
+        "author_name": "Fang Guo",
+        "author_inst": "Shanghai University of Medicine & Health Sciences, Shanghai, China."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc",
+    "type": "new results",
+    "category": "neuroscience"
   },
   {
     "rel_doi": "10.1101/2021.11.09.467693",
@@ -479874,33 +481873,53 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.11.09.21266122",
-    "rel_title": "The effects of the first national lockdown in England on geographical inequalities in the evolution of COVID-19 case rates: An ecological study",
+    "rel_doi": "10.1101/2021.11.08.21266055",
+    "rel_title": "Immunity to COVID-19 in India through vaccination and natural infection",
     "rel_date": "2021-11-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.09.21266122",
-    "rel_abs": "BackgroundSocio-economic inequalities in COVID-19 case rates have been noted worldwide. Previous studieshave compared case rates over set phases. There has been no analysis of how inequalities in cases changed overtime and were shaped by national mitigation strategies (e.g. lock downs). This paper provides the first analysis of the evolution of area-level inequalities in COVID-19 cases by deprivation levels in the first wave of the pandemic (January to July 2020) in England - with a focus on the effects of the first national lockdown (March - July 2020).\n\nMethodsWeekly case rates per Middle Super Output Area (MSOA, n=4412) in England from 2020-03-15 to 2020-07-04 were obtained, and characteristics of local epidemics were calculated, e.g. the highest case rate per area. Simple linear and logistic regression analyses were employed to assess the association of these metrics with index of multiple deprivation (IMD). Local authority-level (n=309) cases were used similarly in a sensitivity analysis, as these data were available daily and extended further back in time. The impact of lockdown was assessed by comparing the cumulative case rate in the most deprived 20% of MSOAs to the least deprived 20%, for the periods before the lockdown, and by the end of lockdown.\n\nFindingsLess deprived areas began recording COVID-19 cases earlier than more deprived areas and were more likely to have peaked by March 2020. More deprived areas case rates grew faster and peaked higher than less deprived areas. During the first national lockdown in the UK, the relative excess in case rates in the most deprived areas increased to 130% of that of the least deprived ones.\n\nInterpretationThe pattern of disease spread in England confirm the hypothesis that initial cases of a novel infectious disease are likely to occur in more affluent communities, but more deprived areas will overtake them once national mitigation strategies begin, and bear the brunt of the total case load. The strict first national lockdown served to increase case rate inequalities in England.\n\nFundingThis work was supported by a grant from The Health Foundation (Ref: 2211473), who took no part in the design, analysis or writing of this study.\n\nResearch in Context\n\nEvidence before this studyThe magnitude and distribution of deprivation-related inequalities in COVID-19 cases have been reported for England and many other countries, however, none have yet investigated the initial evolution of these inequalities, nor the effects of the first national lockdown.\n\nAdded value of this studyWe leverage the benefits of two separate datasets of COVID-19 case counts to investigate the initiation and evolution in inequalities in disease burden by deprivation. We found that cases were first recorded in less deprived areas before rising faster in more deprived areas. The first national lockdown led to an increase in these geographical inequalities.\n\nImplications of all the available evidenceNational lockdowns are an important tool in the armoury of pandemic control, but their timing and duration must be carefully decided and be locally specific. Because case rate inequalities were already present before lockdown in England, movement restrictions served to further increase them.\n\nSummary Box\n\nSection 1: What is already known on this subjectGeographical inequalities in COVID-19 case rates have been noted worldwide, and in England. However, how these inequalities were affected by policy responses - such as national lockdowns - has yet to be investigated.\n\nSection 2: What this study addsWe examined geographical inequalities in COVID-19 case rates by deprivation during the first English lock down (March - July, 2020). We find that cases were first reported in the less deprived areas of England, but this pattern quickly reversed and large excesses of cases occurred in the most deprived areas during the first national lockdown. Case rates in more deprived areas also rose more sharply, peaked higher, and then dropped faster than in less deprived areas. Inequality in cumulative case rates grew over the lockdown, increasing inequalities in disease burden.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.08.21266055",
+    "rel_abs": "In India, Corona Virus-2 Disease-2019 (COVID-19) continues to this day, although with subdued intensity, following two major waves of viral infection. Despite ongoing vaccination drives to curb the spread of COVID-19, the potential of the administered vaccines to render immune protection to the general population, and how this compares with the immune potential of natural infection remain unclear. In this study we examined correlates of immune protection (humoral and cell mediated) induced by the two vaccines Covishield and Covaxin, in individuals living in and around Kolkata, India. Additionally, we compared the vaccination induced immune response profile with that of natural infection, evaluating thereby if individuals infected during the first wave retained virus specific immunity. Our results indicate that while Covaxin generates better cell-mediated immunity toward the Delta variant of SARS-CoV-2 than Covishield, Covishield is more effective than Covaxin in inducing humoral immunity. Both Covishield and Covaxin, however, are more effective toward the wild type virus than the Delta variant. Moreover, the overall immune response resulting from natural infection in and around Kolkata is not only to a certain degree better than that generated by vaccination, especially in the case of the Delta variant, but cell mediated immunity to SARS-CoV-2 also lasts for at least ten months after the viral infection.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Claire E Welsh",
-        "author_inst": "Newcastle University"
+        "author_name": "Tresa Rani Sarraf",
+        "author_inst": "CSIR-IICB"
       },
       {
-        "author_name": "Viviana Albani",
-        "author_inst": "Newcastle University"
+        "author_name": "Shreyasi Maity",
+        "author_inst": "CSIR-IICB"
       },
       {
-        "author_name": "Fiona E Matthews",
-        "author_inst": "Newcastle University"
+        "author_name": "Arjun Ghosh",
+        "author_inst": "Biobharati Life Science"
       },
       {
-        "author_name": "Clare Bambra",
-        "author_inst": "Newcastle University"
+        "author_name": "Suchandan Bhattacharjee",
+        "author_inst": "Biobharati Life Science"
+      },
+      {
+        "author_name": "Arijit Pani",
+        "author_inst": "Biobharati Life Science"
+      },
+      {
+        "author_name": "Kaushik Saha",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Dhrubajyoti Chattopadhyay",
+        "author_inst": "Sister Nivedita University, Kolkata"
+      },
+      {
+        "author_name": "Gourisankar Ghosh",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Malini Sen",
+        "author_inst": "CSIR-Indian Institute of Chemical Biology, Kolkata"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -481756,97 +483775,41 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2021.11.03.21265533",
-    "rel_title": "Effect of the Neutralizing SARS-CoV-2 Antibody Sotrovimab in Preventing Progression of COVID-19: A Randomized Clinical Trial",
+    "rel_doi": "10.1101/2021.11.05.21265763",
+    "rel_title": "Surveillance of COVID-19 in a Vaccinated Population: A Rapid Literature Review",
     "rel_date": "2021-11-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.03.21265533",
-    "rel_abs": "ImportanceOlder patients and those with underlying comorbidities infected with SARS-CoV-2 may be at increased risk of hospitalization and death from COVID-19. Sotrovimab is a neutralizing antibody designed for treatment of high-risk patients to prevent COVID-19 progression.\n\nObjectiveTo evaluate the efficacy and safety of sotrovimab in preventing progression of mild to moderate COVID-19 to severe disease.\n\nDesignRandomized, double-blind, multicenter, placebo-controlled, phase 3 study.\n\nSetting57 centers in 5 countries.\n\nParticipantsNonhospitalized patients with symptomatic, mild to moderate COVID-19 and at least 1 risk factor for disease progression.\n\nInterventionPatients were randomized (1:1) to an intravenous infusion of sotrovimab 500 mg or placebo.\n\nMain Outcomes and MeasuresThe primary efficacy outcome was the proportion of patients with COVID-19 progression, defined as all-cause hospitalization longer than 24 hours for acute illness management or death through day 29. Key secondary outcomes included the proportion of patients with COVID-19 progression, defined as emergency room visit, hospitalization of any duration, or death, and proportion of patients developing severe/critical respiratory COVID-19 requiring supplemental oxygen.\n\nResultsAmong 1057 patients randomized (sotrovimab, 528; placebo, 529), all-cause hospitalization longer than 24 hours or death was significantly reduced with sotrovimab (6/528 [1%]) vs placebo (30/529 [6%]) by 79% (95% CI, 50% to 91%; P<.001). Secondary outcome results further demonstrated the effect of sotrovimab in reducing emergency room visits, hospitalization of any duration, or death, which was reduced by 66% (95% CI, 37% to 81%; P<.001), and severe/critical respiratory COVID-19, which was reduced by 74% (95% CI, 41% to 88%; P=.002). No patients receiving sotrovimab required high-flow oxygen, oxygen via nonrebreather mask, or mechanical ventilation compared with 14 patients receiving placebo. The proportion of patients reporting adverse events was similar between treatment groups; sotrovimab was well tolerated, and no safety concerns were identified.\n\nConclusions and RelevanceAmong nonhospitalized patients with mild to moderate COVID-19, a single 500-mg intravenous dose of sotrovimab prevented progression of COVID-19, with a reduction in hospitalization and need for supplemental oxygen. Sotrovimab is a well-tolerated, effective treatment option for patients at high risk for severe morbidity and mortality from COVID-19.\n\nTrial RegistrationClinicalTrials.gov Identifier: NCT04545060",
-    "rel_num_authors": 20,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265763",
+    "rel_abs": "ObjectivesWith the availability of COVID-19 vaccines, public health focus is shifting to post-vaccination surveillance to identify breakthrough infections in vaccinated populations. Therefore, the objectives of these reviews are to identify scientific evidence and international guidance on surveillance and testing approaches to monitor the presence of the virus in a vaccinated population.\n\nMethodWe searched Ovid MEDLINE(R), including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Embase, EBM Reviews - Cochrane Central Register of Controlled Trials, and EBM Reviews - Cochrane Database of Systematic Reviews. We also searched the Web of Science Core Collection. A grey literature search was also conducted. This search was limited to studies conducted since December 2020 and current to June 13th, 2021. There were no language limitations. COVID-19 surveillance studies that were published after December 2020 but did not specify whether they tested a vaccinated population were also considered for inclusion.\n\nFor the international guidance review, a grey literature search was conducted, including a thorough search of Google, websites of international government organizations (e.g., Center for Disease Control and Prevention [CDC], World Health Organization [WHO]), and McMaster Health Forum (CoVID-END). This search was primarily examining surveillance guidance published since December 2020 (to capture guidance specific to vaccinations) and any relevant pre-December 2020 guidance.\n\nResultsThirty-three studies were included for data synthesis of scientific evidence on surveillance of COVID-19. All the studies were published between April and June 2021. Twenty-one studies were from peer-reviewed journals. Five approaches to monitoring post-vaccination COVID-19 cases and emerging variants of concern were identified, including screening with reverse transcriptase polymerase chain reaction (RT-PCR) and/or a rapid antigen test, genomic surveillance, wastewater surveillance, metagenomics, and testing of air filters on public buses. For population surveillance, the following considerations and limitations were observed: variability in person-to-person testing frequency; lower sensitivity of antigen tests; timing of infections relative to PCR testing can result in missed infections; large studies may fail to identify local variations; and loss of interest in testing by participants in long follow-up studies.\n\nThrough comprehensive grey literature searching, 68 international guidance documents were captured for full-text review. A total of 26 documents met the inclusion criteria and were included in our synthesis. Seven overarching surveillance methods emerged in the literature. PCR-testing was the most recommended surveillance method, followed by genomic screening, serosurveillance, wastewater surveillance, antigen testing, health record screening, and syndromic surveillance.\n\nConclusionEvidence for post-vaccination COVID-19 surveillance was derived from studies in partially or fully vaccinated populations. Population PCR screening, supplemented by rapid antigen tests, was the most frequently used surveillance method and also the most commonly recommended across jurisdictions. Most recent guidance on COVID-19 surveillance is not specific to vaccinated individuals, or it is in effect but has not yet been updated to reflect that. Therefore, more evidence-informed guidance on testing and surveillance approaches in a vaccinated population that incorporates all testing modalities is required.\n\nEXECUTIVE SUMMARYO_ST_ABSObjectivesC_ST_ABSWith the availability of COVID-19 vaccines, public health focus is shifting to post-vaccination surveillance to identify breakthrough infections in vaccinated populations. Therefore, the objectives of these reviews are to: 1) identify scientific evidence on surveillance and testing approaches to monitor the presence of the virus in a vaccinated population and determine how these influence testing strategies; 2) identify international guidance on testing and surveillance for COVID-19 and its variants of concern in a vaccinated population; and 3) identify emerging technologies for surveillance.\n\nDesignA rapid review was conducted to identify scientific evidence on COVID-19 surveillance and testing approaches, and a targeted literature review was conducted on international guidance.\n\nMethodWe searched Ovid MEDLINE(R), including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Embase, EBM Reviews - Cochrane Central Register of Controlled Trials, and EBM Reviews - Cochrane Database of Systematic Reviews. We also searched the Web of Science Core Collection. We performed all searches on June 13, 2021. A grey literature search was also conducted, including: MedRxiv, Google, McMaster Health Forum (COVID-END), and websites of international government organizations (e.g., Center for Disease Control and Prevention [CDC], World Health Organization [WHO]). This search was limited to studies conducted since December 2020 and current to June 13th, 2021. There were no language limitations. COVID-19 surveillance studies that were published after December 2020 but did not specify whether they tested a vaccinated population were also considered for inclusion.\n\nFor the international guidance review, a grey literature search was conducted, including a thorough search of Google, websites of international government organizations (e.g., Center for Disease Control and Prevention [CDC], World Health Organization [WHO]), and McMaster Health Forum (CoVID-END). This search was primarily examining surveillance guidance published since December 2020 (to capture guidance specific to vaccinations) and any relevant pre-December 2020 guidance. Although the primary focus was on surveillance guidance in a vaccinated population, guidance that was published after December 2020 but was not vaccine-specific was also considered for inclusion; it was assumed that this guidance was still in effect and was not yet updated. There were no language limitations. A patient partner was engaged during the co-production of a plain language summary for both the rapid review of primary literature and the review of international guidance.\n\nResultsThirty-three studies were included for data synthesis of scientific evidence on surveillance of COVID-19. All the studies were published between April and June 2021. Twenty-one studies were from peer-reviewed journals. Five approaches to monitoring post-vaccination COVID-19 cases and emerging variants of concern were identified including, screening with reverse transcriptase polymerase chain reaction (RT-PCR) and/or a rapid antigen test, genomic surveillance, wastewater surveillance, metagenomics, and testing of air filters on public buses. Population surveillance with RT-PCR testing and/or rapid antigen testing was utilized in 22 studies, mostly in healthcare settings, but also in long-term care facilities (LTCFs) and in the community. The frequency of testing varied depending on whether there was an outbreak.\n\nFor population surveillance, the following considerations and limitations were observed: studies with discretionary access to testing have highly variable person-to-person testing frequency; antigen tests have lower sensitivity, therefore some positive cases may be missed; timing of infections relative to PCR testing as well as the sensitivity of the tests can result in missed infections; large sample sizes from multicentre studies increase generalizability, but fail to identify local variations from individual centres; with electronic database surveillance, it is difficult to confirm whether patients with a breakthrough infection and a previous positive SARS-CoV-2 test result had a true reinfection or had prolonged shedding from the previous infection; and participants lose interest in studies with long follow-up, with decrease in testing rates over time.\n\nSix wastewater surveillance and three genomic surveillance studies were identified in this review. A number of benefits such as, good correlation with clinical data, ability to predict major outbreaks, and rapid turnaround time were observed with wastewater surveillance. However, challenges such as, inconsistencies in variant representation depending on where the samples were taken within the community, differences in the capacity of wastewater to predict case numbers based on the size of the wastewater treatment plants, and cost, were noted. Emerging technologies like viral detection in public transport filters, novel sampling, and assay platforms were also identified.\n\nThrough comprehensive grey literature searching, 68 international guidance documents were captured for full-text review. A total of 26 documents met the inclusion criteria and were included in our synthesis. Most were not specific to vaccinated populations but reported on a surveillance method of COVID-19 and were therefore included in the review; it was assumed that they were still in effect but have not yet been updated. Eleven countries/regions were represented, including Australia, Brazil, France, Germany, India, New Zealand, Spain, United Kingdom, United States, Europe, and International. All of the guidance documents included surveillance methods appropriate for community settings. Other settings of interest were healthcare settings, including hospitals and primary care centres, long-term care facilities, points of entry for travel, schools, and other sentinel sites (e.g., prisons and closed settings). Seven overarching surveillance methods emerged in the literature. PCR-testing was the most recommended surveillance method, followed by genomic screening, serosurveillance, wastewater surveillance, antigen testing, health record screening, and syndromic surveillance.\n\nOnly one document (published by Public Health England) was identified that provided guidance on surveillance specific to vaccinated populations. The document outlined a plan to surveil and monitor COVID-19 in vaccinated populations through a series of targeted longitudinal studies, routine surveillance, enhanced surveillance, use of electronic health records, surveillance of vaccine failure (including follow-up with viral whole genome sequencing), and sero-surveillance (including blood donor samples, routine blood tests, and residual sera).\n\nConclusionEvidence for post-vaccination COVID-19 surveillance was derived from studies in partially or fully vaccinated populations. Population PCR screening, supplemented by rapid antigen tests, was the most frequently used surveillance method and also the most commonly recommended across jurisdictions. The selection of testing method and the frequency of testing was determined by the intensity of the disease and the scale of testing. Other common testing methods included wastewater surveillance and genomic surveillance. A few novel technologies are emerging, however, many of these are yet to be utilized in the real-world setting. There is limited evidence-based guidance on surveillance in a vaccinated population. Most recent guidance on COVID-19 surveillance is not specific to vaccinated individuals, or it is in effect but has not yet been updated to reflect that. Therefore, more evidence-informed guidance on testing and surveillance approaches in a vaccinated population that incorporates all testing modalities is required.\n\nProtocol/Topic RegistrationPROSPERO-CRD42021261215.\n\nKey DefinitionsAntigen: a foreign protein which induces an immune response in the body, especially the production of antibodies\n\nFully vaccinated: refers to individuals who have received complete dosage of a given vaccine\n\nPartially vaccinated: refers to individuals who have received an incomplete dosage of a given vaccine\n\nSero-surveillance: estimation of antibody levels against infectious diseases\n\nSurveillance: ongoing systematic collection, analysis, and interpretation of health data that are essential to the planning, implementation, and evaluation of public health practice\n\nVariants of Concern: a variant for which there is evidence of an increase in transmissibility and/or more severe disease\n\nVariants: virus with a permanent change in its genetic sequence",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Anil Gupta",
-        "author_inst": "Albion Finch Medical, William Osler Health Centre"
-      },
-      {
-        "author_name": "Yaneicy Gonzalez-Rojas",
-        "author_inst": "Optimus U, Corp."
-      },
-      {
-        "author_name": "Erick Juarez",
-        "author_inst": "Florida International Medical Research"
-      },
-      {
-        "author_name": "Manuel Crespo",
-        "author_inst": "Alvaro Cunqueiro Hospital, IIS Galicia Sur"
-      },
-      {
-        "author_name": "Jaynier Moya",
-        "author_inst": "Pines Care Research Center"
-      },
-      {
-        "author_name": "Diego Falci",
-        "author_inst": "Hospital de Clinicas de Porto Alegre"
-      },
-      {
-        "author_name": "Elias Sarkis",
-        "author_inst": "Sarkis Clinical Trials"
-      },
-      {
-        "author_name": "Joel Solis",
-        "author_inst": "Centex Studies"
-      },
-      {
-        "author_name": "Hanzhe Zheng",
-        "author_inst": "Vir Biotechnology, Inc"
-      },
-      {
-        "author_name": "Nicola Scott",
-        "author_inst": "GlaxoSmithKline"
-      },
-      {
-        "author_name": "Andrea L. Cathcart",
-        "author_inst": "Vir Biotechnology, Inc"
-      },
-      {
-        "author_name": "Sergio Parra",
-        "author_inst": "Vir Biotechnology, Inc"
-      },
-      {
-        "author_name": "Jennifer E. Sager",
-        "author_inst": "Vir Biotechnology, Inc"
-      },
-      {
-        "author_name": "Daren J Austin",
-        "author_inst": "GlaxoSmithKline"
-      },
-      {
-        "author_name": "Amanda Peppercorn",
-        "author_inst": "GlaxoSmithKline"
+        "author_name": "Oluwaseun Egunsola",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Elizabeth Alexander",
-        "author_inst": "Vir Biotechnology, Inc"
+        "author_name": "Brenlea Farkas",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Wendy W. Yeh",
-        "author_inst": "Vir Biotechnology, Inc"
+        "author_name": "Jordyn Flanagan",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Cynthia Brinson",
-        "author_inst": "Central Texas Clinical Research"
+        "author_name": "Charleen Salmon",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Melissa Aldinger",
-        "author_inst": "Vir Biotechnology, Inc."
+        "author_name": "Liza Mastikhina",
+        "author_inst": "University of Calgary"
       },
       {
-        "author_name": "Adrienne E Shapiro",
-        "author_inst": "University of Washington"
+        "author_name": "Fiona Clement",
+        "author_inst": "University of Calgary"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -483630,31 +485593,43 @@
     "category": "synthetic biology"
   },
   {
-    "rel_doi": "10.1101/2021.11.04.21265937",
-    "rel_title": "Estimation of the basic reproduction number of COVID-19 from the incubation period distribution",
+    "rel_doi": "10.1101/2021.11.04.21265910",
+    "rel_title": "SARS-CoV-2 Aerosol Transmission Indoors: A Closer Look at Viral Load, Infectivity, the Effectiveness of Preventive Measures and a Simple Approach for Practical Recommendations",
     "rel_date": "2021-11-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.04.21265937",
-    "rel_abs": "BackgroundThe estimates of future course of spreading of the SARS-CoV-2 virus are frequently based on Markovian models in which the transitions between the compartments are exponentially distributed. Specifically, the basic reproduction number R0 is also determined from formulae where it is related to the parameters of such models. The observations show that the start of infectivity of an individual appears nearly at the same time as the onset of symptoms, while the distribution of the incubation period is not an exponential.\n\nMethodsWe propose a method for estimation of R0 for COVID-19 based on the empirical incubation period distribution and assumed very short infectivity period that lasts only few days around the onset of symptoms. It is tested on daily new cases in six major countries in Europe, in the first wave of epidemic in spring, 2020.\n\nResultsThe calculations show that even if the infectivity starts two days before the onset of symptoms and stops immediately when they appear, the value of R0 is larger than that from the classical, Markovian approach. For more realistic cases, when only individuals with mild symptoms spread the virus for few days after onset of symptoms, the respective values are even larger.\n\nConclusionsThe calculations of R0 and other characteristics of spreading of COVID-19 based on the classical, Markovian approaches should be taken very cautiously. Instead, non-Markovian models with general distribution functions of transition between compartments should be considered as more appropriate.\n\nKey messagesO_LIAlthough formulae for estimate of the basic reproduction number R0, by using general-form functions of infectivity are known since the earliest works in epidemiology, majority of studies are based on exponential distribution function.\nC_LIO_LIWe introduce a new methodology of calculating R0 with an infectivity function obtained by combining empirical incubation period distribution with infectivity window function that is localized around the onset of symptoms.\nC_LIO_LIEstimates of R0 for the first wave of COVID - 19 in the spring 2020, by the proposed methodology are larger than those from the classical SIR model.\nC_LIO_LIWhen possible, the estimates of R0 should be based on empirical distributions of the infectivity functions, while the values obtained with the conventional epidemic spreading models should be taken with caution.\nC_LI",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.04.21265910",
+    "rel_abs": "Currently, airborne transmission is seen as the most important transmission path for SARS-CoV-2. In this investigation, a classic dose-response model is used on the one hand to find out retrospectively the probable viral load of the infectious source patient at the time of transmission in 25 documented outbreaks. We showed that an infection due to airborne transmission at a distance from the infectious person was probably only possible in the 25 outbreaks examined, with attack rates of 4-100%, if the viral load had been higher than 1E+08 viral copies/ml. This demonstrates that the viral load estimated from the swab might overestimate a persons infectivity via aerosol, because a person is generally considered infectious, independent of the transmission way, when the viral load from the swab is 1E+06 viral copies/ml.\n\nOn the other hand, a possible approach is presented to predict the probable situational Attack Rate (PARs) of a group of persons in a room through aerosol particles emitted by an infectious source patient. Four main categories of influence on the risk of infection are formed: First the emitted viruses, depending on the viral load and the amount of respiratory particles, and necessary number of reproducible viruses for infection, second the room-specific data and duration of stay of the group of people, third the activity of the exposed persons, and fourth the effect of personal protection (e.g. wearing masks from infectious and/or susceptible person).\n\nFurthermore, a simplified method is presented to calculate either the maximum possible number of persons in a room, so that probably a maximum of one person becomes infected when an infectious person is in the room, or the PARs,simple for a given number of persons, ventilation rate and time of occupancy. We additionally show, taking into account organizational preventive measures, which person-related virus-free supply air flow rates are necessary to keep the number of newly infected persons to less than 1. The simple approach makes it easy to derive preventive organizational and ventilation measures. Our results show that the volume flow rate or a person-related flow rate is a much more effective parameter to evaluate ventilation for infection prevention than the air change rate. We suggest to monitor the CO2 concentration as an easy to implement and valid measurement system for indoor spaces.\n\nFinally, we show that of the three measures, besides of wearing masks and increasing ventilation, testing contributes the most to the joint protective effect. This corresponds to the classic approach to implement protection concepts: preventing the source from entering the room and emitting viruses at all. In summary, a layered approach of different measures is recommended to mutually compensate for possible failures of any one measure (e.g. incorrect execution of tests, incorrect fit of masks or irregular window opening), to increase the degree of protection and thus reduce the risk of transmission of SARS-CoV-2.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Lasko Basnarkov",
-        "author_inst": "SS Cyril and Methodius University in Skopje, Macedonia"
+        "author_name": "Martin Kriegel",
+        "author_inst": "Technical University of Berlin, Hermann-Rietschel-Institut"
       },
       {
-        "author_name": "Igor Tomovski",
-        "author_inst": "Macedonian Academy of Sciences and Arts"
+        "author_name": "Anne Hartmann",
+        "author_inst": "Technical University of Berlin, Hermann-Rietschel-Institut"
+      },
+      {
+        "author_name": "Udo Buchholz",
+        "author_inst": "Robert-Koch-Institute, Department for Infectious Disease Epidemiology"
       },
       {
-        "author_name": "Florin Avram",
-        "author_inst": "Universite de Pau, France"
+        "author_name": "Janna Seifried",
+        "author_inst": "Robert-Koch-Institute, Department for Infectious Disease Epidemiology"
+      },
+      {
+        "author_name": "Sigrid Baumgarte",
+        "author_inst": "Local health authority Hamburg-Nord"
+      },
+      {
+        "author_name": "Petra Gastmeier",
+        "author_inst": "Charite-University Medicine Berlin, Institute for Hygiene and Environmental Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.11.04.21265916",
@@ -485496,47 +487471,55 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.11.02.466951",
-    "rel_title": "Drug targeting Nsp1-ribosomal complex shows antiviral activity against SARS-CoV-2",
+    "rel_doi": "10.1101/2021.11.03.21265876",
+    "rel_title": "Investigating the relationship between interventions, contact patterns, and SARS-CoV-2 transmissibility",
     "rel_date": "2021-11-03",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.02.466951",
-    "rel_abs": "The SARS-Cov-2 non-structural protein 1 (Nsp1) contains an N-terminal domain and C-terminal helices connected by a short linker region. The C-terminal helices of Nsp1 (Nsp1-C-ter) from SARS-Cov-2 bind in the mRNA entry channel of the 40S ribosomal subunit and block the entry of mRNAs thereby shutting down host protein synthesis. Nsp1 suppresses the host immune function and is vital for viral replication. Hence, Nsp1 appears to be an attractive target for therapeutics. In this study, we have in silico screened Food and Drug Administration (FDA)-approved drugs against Nsp1-C-ter and find that montelukast sodium hydrate binds to Nsp1-C-ter with a binding affinity (KD) of 10.8{+/-}0.2 M in vitro and forms a stable complex with it in simulation runs with a binding energy of -76.71{+/-}8.95 kJ/mol. The drug also rescues the inhibitory effect of Nsp1 in host protein synthesis as demonstrated by the expression of firefly luciferase reporter gene in cells. Importantly, montelukast sodium hydrate demonstrates antiviral activity against SARS-CoV-2 with reduced viral replication in HEK cells expressing ACE2 and Vero-E6 cells. We therefore propose montelukast sodium hydrate may help in combatting SARS-CoV-2 infection.",
-    "rel_num_authors": 7,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.03.21265876",
+    "rel_abs": "BackgroundAfter a rapid upsurge of COVID-19 cases in Italy during the fall of 2020, the government introduced a three-tiered restriction system aimed at increasing physical distancing. The Ministry of Health, after periodic epidemiological risk assessments, assigned a tier to each of the 21 Italian regions and autonomous provinces (AP). It is still unclear to what extent these different measures altered mixing patterns and how quickly the population adapted their social interactions to continuous changes in restrictions.\n\nMethods and findingsWe conducted a survey between July 2020 and March 2021 to monitor changes in social contact patterns among individuals in the metropolitan city of Milan, Italy, which was hardly hit by the second wave of COVID-19 pandemic. The number of contacts during periods characterized by different levels of restrictions was analyzed through negative binomial regression models and age-specific contact matrices were estimated under the different tiers. Relying on the empirically estimated mixing patterns, we quantified relative changes in SARS-CoV-2 transmission potential associated with the different tiers.\n\nAs tighter restrictions were implemented during the fall of 2020, a progressive reduction in the mean number of contacts recorded by study participants was observed: from 16.4% under mild restrictions (yellow tier), to 45.6% under strong restrictions (red tier). Higher restrictions levels were also found to increase the relative contribution of contacts occurring within the household. The SARS-CoV-2 reproduction number was estimated to decrease by 18.7% (95%CI: 4.6-30.8), 33.4% (95%CI: 22.7-43.2), and 50.2% (95%CI: 40.9-57.7) under the yellow, orange, and red tiers, respectively.\n\nConclusionsOur results give an important quantification of the expected contribution of different restriction levels in shaping social contacts and decreasing the transmission potential of SARS-CoV-2. These estimates can find an operational use in anticipating the effect that the implementation of these tiered restriction can have on SARS-CoV-2 reproduction number under an evolving epidemiological situation.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Tanweer Hussain",
-        "author_inst": "Indian Institute of Science"
+        "author_name": "Filippo Trentini",
+        "author_inst": "Dondena Centre, Bocconi University"
       },
       {
-        "author_name": "Mohammad Afsar",
-        "author_inst": "Indian Institute of Science"
+        "author_name": "Adriana Manna",
+        "author_inst": "Department of Network and Data Science, Central European University, Wien, Austria"
       },
       {
-        "author_name": "Rohan Narayan",
-        "author_inst": "Indian Institute of Science"
+        "author_name": "Nicoletta Balbo",
+        "author_inst": "Department of Social and Political Sciences, Bocconi University, Milan, Italy"
       },
       {
-        "author_name": "Md Noor Akhtar",
-        "author_inst": "Indian Institute of Science"
+        "author_name": "Valentina Marziano",
+        "author_inst": "Fondazione Bruno Kessler"
       },
       {
-        "author_name": "Huma Rahil",
-        "author_inst": "Indian Institute of Science"
+        "author_name": "Giorgio Guzzetta",
+        "author_inst": "Fondazione Bruno Kessler"
       },
       {
-        "author_name": "Sandeep Eswarappa",
-        "author_inst": "Indian Institute of Science Bangalore"
+        "author_name": "Stefano Merler",
+        "author_inst": "Fondazione Bruno Kessler"
       },
       {
-        "author_name": "Shashank Tripathi",
-        "author_inst": "Indian Institute of Science"
+        "author_name": "Marco Ajelli",
+        "author_inst": "Department of Epidemiology and Biostatistics, Indiana University School of Public Health"
+      },
+      {
+        "author_name": "Piero Poletti",
+        "author_inst": "Bruno Kessler Foundation"
+      },
+      {
+        "author_name": "Alessia Melegaro",
+        "author_inst": "Bocconi University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "new results",
-    "category": "biophysics"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.11.03.21265861",
@@ -487866,27 +489849,47 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.11.01.21265653",
-    "rel_title": "Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives",
+    "rel_doi": "10.1101/2021.11.01.21265729",
+    "rel_title": "Quantifying the effects of non-pharmaceutical and pharmaceutical interventions against COVID-19 epidemic in the Republic of Korea: Mathematical model-based approach considering age groups and the Delta variant",
     "rel_date": "2021-11-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.01.21265653",
-    "rel_abs": "Since the outbreak of COVID-19, an astronomical number of publications on the pandemic dynamics appeared in the literature, of which many use the susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) models, or their variants, to simulate and study the spread of the coronavirus. SIR and SEIR are continuous-time models which are a class of initial value problems (IVPs) of ordinary differential equations (ODEs). Discrete-time models such as regression and machine learning have also been applied to analyze COVID-19 pandemic data (e.g. predicting infection cases), but most of these methods use simplified models involving a small number of input variables pre-selected based on a priori knowledge, or use very complicated models (e.g. deep learning), purely focusing on certain prediction purposes and paying little attention to the model interpretability. There have been relatively fewer studies focusing on the investigations of the inherent time-lagged or time-delayed relationships e.g. between the reproduction number (R number), infection cases, and deaths, analyzing the pandemic spread from a systems thinking and dynamic perspective. The present study, for the first time, proposes using systems engineering and system identification approach to build transparent, interpretable, parsimonious and simulatable (TIPS) dynamic machine learning models, establishing links between the R number, the infection cases and deaths caused by COVID-19. The TIPS models are developed based on the well-known NARMAX (Nonlinear AutoRegressive Moving Average with eXogenous inputs) model, which can help better understand the COVID-19 pandemic dynamics. A case study on the UK COVID-19 data is carried out, and new findings are detailed. The proposed method and the associated new findings are useful for better understanding the spread dynamics of the COVID-19 pandemic.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.01.21265729",
+    "rel_abs": "BackgroundEarly vaccination efforts and non-pharmaceutical interventions were insufficient to prevent a surge of coronavirus disease 2019 (COVID-19) cases triggered by the Delta variant. This study aims to understand how vaccination and variants contribute to the spread of COVID-19 so that appropriate measures are implemented.\n\nMethodsA compartment model that includes age, vaccination, and infection with the Delta or non-Delta variants was developed. We estimated the transmission rates using maximum likelihood estimation and phase-dependent reduction effect of non-pharmaceutical interventions (NPIs) according to government policies from 26 February to 8 October 2021. We extended our model simulation until 31 December considering the initiation of eased NPIs. Furthermore, we also performed simulations to examine the effect of NPIs, arrival timing of Delta variant, and speed of vaccine administration.\n\nResultsThe estimated transmission rate matrices show distinct pattern, with the transmission rates of younger age groups (0 39 years) much larger than non-Delta. Social distancing (SD) level 2 and SD4 in Korea were associated with transmission reduction factors of 0.64 to 0.69 and 0.70 to 0.78, respectively. The easing of NPIs to a level comparable to SD2 should be initiated not earlier than 16 October to keep the number of severe cases below the capacity of Koreas healthcare system. Simulation results also showed that a surge prompted by the spread of the Delta variant can be prevented if the number of people vaccinated daily was larger.\n\nConclusionsSimulations showed that the timing of easing and intensity of NPIs, vaccination speed, and screening measures are key factors in preventing another epidemic wave.\n\n2 Key MessagesO_LIMaximum likelihood estimation can be utilized to determine the transmission rates of the Delta and non-Delta variants.\nC_LIO_LIThe phase-dependent NPIs implemented by the Korean government were effectively quantified in the modelling study.\nC_LIO_LIEven with fast vaccination, resurgence of cases is still possible if NPIs are eased too early or screening measures are relaxed.\nC_LIO_LIThe model can be used as a guide for policy makers on deciding appropriate SD level that considers not only disease control, but also the socio-economic impact of maintaining strict measures.\nC_LI",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Hua-Liang Wei",
-        "author_inst": "The University Of Sheffield"
+        "author_name": "Youngsuk Ko",
+        "author_inst": "Konkuk University"
       },
       {
-        "author_name": "Stephen A Billings",
-        "author_inst": "The University of Sheffield"
+        "author_name": "Victoria May P Mendoza",
+        "author_inst": "Konkuk University"
+      },
+      {
+        "author_name": "Yubin Seo",
+        "author_inst": "Hallym University College of Medicine"
+      },
+      {
+        "author_name": "Jacob Lee",
+        "author_inst": "Hallym University College of Medicine"
+      },
+      {
+        "author_name": "Yeonju Kim",
+        "author_inst": "Korea Disease Control and Prevention Agency"
+      },
+      {
+        "author_name": "Donghyok Kwon",
+        "author_inst": "Korea Disease Control and Prevention Agency"
+      },
+      {
+        "author_name": "Eunok Jung",
+        "author_inst": "Konkuk University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.10.31.21265627",
@@ -489520,61 +491523,53 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2021.10.28.21265499",
-    "rel_title": "Time of day of vaccination affects SARS-CoV-2 antibody responses in an observational study of healthcare workers",
+    "rel_doi": "10.1101/2021.10.28.21265544",
+    "rel_title": "In vitro characterisation and clinical evaluation of the diagnostic accuracy of a new antigen test for SARS-CoV-2 detection.",
     "rel_date": "2021-10-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.28.21265499",
-    "rel_abs": "The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global crisis with unprecedented challenges for public health. Vaccinations against SARS-CoV-2 have slowed the incidence of new infections and reduced disease severity. As the time-of-day of vaccination has been reported to influence host immune responses to multiple pathogens, we quantified the influence of SARS-CoV-2 vaccination time, vaccine type, age, sex, and days post-vaccination on anti-Spike antibody responses in healthcare workers. The magnitude of the anti-Spike antibody response associated with the time-of-day of vaccination, vaccine type, participant age, sex, and days post vaccination. These results may be relevant for optimizing SARS-CoV-2 vaccine efficacy.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.28.21265544",
+    "rel_abs": "Background and aimsQuick, user-friendly and sensitive diagnostic tools are the key to controlling the spread of the SARS-CoV-2 pandemic in the new epidemiologic landscape. The aim of this work is to characterise a new Covid-19 antigen test that uses an innovative chromatographic Affimer(R)-based technology designed for the qualitative detection of SARS-CoV-2 antigen. As rapid technology to detect Covid-19, the test was extensively characterised in vitro. Once the analytical parameters of performance were set, the test system was challenged in a test field study. The aim of this study was to evaluate its diagnostic accuracy, as compared by the gold standard RT-PCR and other existing lateral flow tests.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Wei Wang",
-        "author_inst": "Division of Sleep and Circadian Disorders, Brigham and Womens Hospital; Division of Sleep Medicine, Harvard Medical School, US."
-      },
-      {
-        "author_name": "Peter Balfe",
-        "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford, UK"
-      },
-      {
-        "author_name": "David W Eyre",
-        "author_inst": "University of Oxford"
+        "author_name": "J.J. Montoya",
+        "author_inst": "Departamento de Radiologia, Rehabilitacion y Fisioterapia. Facultad de Medicina, Universidad Complutense de Madrid."
       },
       {
-        "author_name": "Sheila F Lumley",
-        "author_inst": "University of Oxford"
+        "author_name": "J.M. Rubio",
+        "author_inst": "Centro Nacional de Microbiologia, Instituto de Salud Carlos III, Ctra. de Pozuelo, 28, 28222 Majadahonda, Madrid."
       },
       {
-        "author_name": "Denise O'Donnell",
-        "author_inst": "Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK"
+        "author_name": "Y. Ouahid",
+        "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens (Avda. Industria no 4, Edificio 1) en colabo"
       },
       {
-        "author_name": "Fiona Warren",
-        "author_inst": "Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK"
+        "author_name": "A. Lopez-Lopez",
+        "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens (Avda. Industria no 4, Edificio 1) en colabo"
       },
       {
-        "author_name": "Derrick W Crook",
-        "author_inst": "NIHR Oxford Biomedical Research Centre"
+        "author_name": "A. Madejon",
+        "author_inst": "Centro de Investigacion Biomedica en Red, C/ Sinesio Delgado 10, 28029-MADRID, Hospital La Paz, Madrid, Spain."
       },
       {
-        "author_name": "Katie Jeffery",
-        "author_inst": "Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, and\tRadcliffe Department of Medic"
+        "author_name": "A.I. Gil-Garcia",
+        "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens (Avda. Industria no 4, Edificio 1) en colabo"
       },
       {
-        "author_name": "Philippa C Matthews",
-        "author_inst": "Nuffield Department of Medicine, and 4.\tDepartment of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hos"
+        "author_name": "R.J. Hannam",
+        "author_inst": "Avacta Life Sciences, Unit 20, Thorp Arch Estate, Wetherby, LS23 7FA, UK."
       },
       {
-        "author_name": "Elizabeth B Klerman",
-        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+        "author_name": "H.R.E. Butler",
+        "author_inst": "Avacta Life Sciences, Unit 20, Thorp Arch Estate, Wetherby, LS23 7FA, UK."
       },
       {
-        "author_name": "Jane McKeating",
-        "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford UK"
+        "author_name": "P. Castan",
+        "author_inst": "Unidad de Desarrollo de Herramientas Moleculares para Diagnostico e Investigacion Clinica (UDHM-DC), MiRNAX Biosens (Avda. Industria no 4, Edificio 1) en colabo"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -491394,85 +493389,33 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.10.27.21265574",
-    "rel_title": "Boosting of Cross-Reactive Antibodies to Endemic Coronaviruses by SARS-CoV-2 Infection but not Vaccination with Stabilized Spike",
+    "rel_doi": "10.1101/2021.10.27.21265591",
+    "rel_title": "How many lives do COVID vaccines save? Evidence from Israel.",
     "rel_date": "2021-10-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.27.21265574",
-    "rel_abs": "Pre-existing antibodies to endemic coronaviruses (CoV) that cross-react with SARS-CoV-2 have the potential to influence the antibody response to COVID-19 vaccination and infection for better or worse. In this observational study of mucosal and systemic humoral immunity in acutely infected, convalescent, and vaccinated subjects, we tested for cross reactivity against endemic CoV spike (S) protein at subdomain resolution. Elevated responses, particularly to the {beta}-CoV OC43, were observed in all natural infection cohorts tested and were correlated with the response to SARS-CoV-2. The kinetics of this response and isotypes involved suggest that infection boosts preexisting antibody lineages raised against prior endemic CoV exposure that cross react. While further research is needed to discern whether this recalled response is desirable or detrimental, the boosted antibodies principally targeted the better conserved S2 subdomain of the viral spike and were not associated with neutralization activity. In contrast, vaccination with a stabilized spike mRNA vaccine did not robustly boost cross-reactive antibodies, suggesting differing antigenicity and immunogenicity. In sum, this study provides evidence that antibodies targeting endemic CoV are robustly boosted in response to SARS-CoV-2 infection but not to vaccination with stabilized S, and that depending on conformation or other factors, the S2 subdomain of the spike protein triggers a rapidly recalled, IgG-dominated response that lacks neutralization activity.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC=\"FIGDIR/small/21265574v1_figA1.gif\" ALT=\"Figure 1\">\nView larger version (22K):\norg.highwire.dtl.DTLVardef@168d38aorg.highwire.dtl.DTLVardef@1183afcorg.highwire.dtl.DTLVardef@1c88b77org.highwire.dtl.DTLVardef@13c6e0a_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOGraphical AbstractC_FLOATNO Antibody responses to SARS-CoV-2 and endemic CoV spike proteins were measured in diverse cohorts. While antibodies to SARS-CoV-2 were induced across all isotypes, only IgA and IgG responses to endemic CoV were robustly boosted, and only among naturally-infected but not vaccinated individuals. These recalled, cross-reactive responses to endemic CoV primarily recognized the better conserved S2 domain and were non-neutralizing. While other antiviral activities of broadly cross-reactive S2-specifc antibodies are not known, the differing antigenicity of natural infection and vaccination with stabilized pre-fusion spike has potential implications for the breadth and level of protection afforded by each.\n\nC_FIG",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.27.21265591",
+    "rel_abs": "BackgroundIn December 2020, Israel began a mass vaccination program with the rapid rollout of the Pfizer-BioNTech COVID-19 BNT162b2 vaccine for adults in Israel. The campaign vaccinated fewer people than necessary for herd immunity. However, at the same time, government stringency measures in terms of closing public life were decreased. Real-world observational data were used to examine the effect of mass vaccination on Covid-19 mortality.\n\nMethodsThe study period to examine the effect of vaccination on mortality was chosen to capture when at least 90% of the population over age 70 were vaccinated for less than seven months. Projected deaths as expected from vaccine efficacy and actual mortality data were compared for the study population with examination of potential confounding effects of government stringency. Average government stringency (Oxford Stringency Index) was calculated in the study period and the preceding period of the pandemic. Potential confounding effects of an age shift in the distribution of deaths were examined by analyzing the distributions of deaths and cases before and after the study period.\n\nResultsConfirmed deaths from COVID-19 in the population over 70 after mass vaccination were recorded as 370, versus 408 expected from applying person-days of vaccine efficacy, and 5,120 estimated without vaccinations.\n\nConclusionsVaccines against COVID-19 saved more lives than expected by simply applying individual vaccine efficacy to the vaccinated population in Israel, despite a loosening of government stringency.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Andrew R Crowley",
-        "author_inst": "Dartmouth College"
-      },
-      {
-        "author_name": "Harini Natarajan",
-        "author_inst": "Dartmouth College"
-      },
-      {
-        "author_name": "Andrew P Hederman",
-        "author_inst": "Dartmouth College"
-      },
-      {
-        "author_name": "Carly A Bobak",
-        "author_inst": "Dartmouth College"
-      },
-      {
-        "author_name": "Joshua A Weiner",
-        "author_inst": "Dartmouth College"
-      },
-      {
-        "author_name": "Wendy F. Wieland-Alter",
-        "author_inst": "Dartmouth Hitchcock Medical Center"
-      },
-      {
-        "author_name": "Jiwon Lee",
-        "author_inst": "Dartmouth College"
-      },
-      {
-        "author_name": "Evan M Bloch",
-        "author_inst": "Johns Hopkins Medicine"
-      },
-      {
-        "author_name": "Aaron AR Tobian",
-        "author_inst": "Johns Hopkins Hospital"
-      },
-      {
-        "author_name": "Andrew Redd",
-        "author_inst": "Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Joel N. Blankson",
-        "author_inst": "Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Dana Wolf",
-        "author_inst": "Hadassah University Medical Center"
-      },
-      {
-        "author_name": "Tessa Goetghebuer",
-        "author_inst": "CHU St. Pierre"
-      },
-      {
-        "author_name": "Arnaud Marchant",
-        "author_inst": "Universite libre de Bruxelles"
+        "author_name": "Ronen Arbel",
+        "author_inst": "Maximizing Health Outcomes Research Lab, Sapir College, Sderot, Israel"
       },
       {
-        "author_name": "Ruth I Connor",
-        "author_inst": "Dartmouth Hitchcock Medical Center"
+        "author_name": "Candace Makeda Moore",
+        "author_inst": "Maximizing Health Outcomes Research Lab, Sapir College, Sderot, Israel"
       },
       {
-        "author_name": "Peter F Wright",
-        "author_inst": "Dartmouth Hitchcock Medical Center"
+        "author_name": "Ruslan Sergienko",
+        "author_inst": "Department of Health Policy and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel"
       },
       {
-        "author_name": "Margaret E Ackerman",
-        "author_inst": "Dartmouth College"
+        "author_name": "Joseph Pliskin",
+        "author_inst": "Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, MA, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -493224,95 +495167,47 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.10.25.465714",
-    "rel_title": "Nanobodies recognizing conserved hidden clefts of all SARS-CoV-2 spike variants",
+    "rel_doi": "10.1101/2021.10.22.21265188",
+    "rel_title": "Response to the coronavirus disease 2019 (COVID-19) pandemic at private retail pharmacies in Kenya: a mixed methods study",
     "rel_date": "2021-10-26",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.25.465714",
-    "rel_abs": "We are in the midst of the historic coronavirus infectious disease 2019 (COVID-19) pandemic caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2). Although countless efforts to control the pandemic have been attempted--most successfully, vaccination1-3--imbalances in accessibility to vaccines, medicines, and diagnostics among countries, regions, and populations have been problematic. Camelid variable regions of heavy chain-only antibodies (VHHs or nanobodies)4 have unique modalities: they are smaller, more stable, easier to customize, and, importantly, less expensive to produce than conventional antibodies5, 6. We present the sequences of nine alpaca nanobodies that detect the spike proteins of four SARS-CoV-2 variants of concern (VOCs)--namely, the alpha, beta, gamma, and delta variants. We show that they can quantify or detect spike variants via ELISA and lateral flow, kinetic, flow cytometric, microscopy, and Western blotting assays7. The panel of nanobodies broadly neutralized viral infection by pseudotyped SARS-CoV-2 VOCs. Structural analyses showed that a P86 clone targeted epitopes that were conserved yet unclassified on the receptor-binding domain (RBD) and located inside the N-terminal domain (NTD). Human antibodies have hardly accessed both regions; consequently, the clone buries hidden crevasses of SARS-CoV-2 spike proteins undetected by conventional antibodies and maintains activity against spike proteins carrying escape mutations.",
-    "rel_num_authors": 19,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.22.21265188",
+    "rel_abs": "BackgroundPrivate retail pharmacies in developing countries present a unique channel for COVID-19 prevention. We assessed the response to the COVID-19 pandemic by pharmacies in Kenya, aiming to identify strategies for maximising their contribution to the national response.\n\nMethodsWe conducted a prospective mixed-methods study, consisting of a questionnaire survey (n=195), a simulated client survey (n=103), and in-depth interviews (n=18). Data collection started approximately seven months after the pandemic reached Kenya. Quantitative data were summarized using measures of central tendency and multivariable modelling done using logistic regression. Qualitative analysis followed a thematic approach.\n\nResultsThe initial weeks of the pandemic were characterized by fear and panic among service providers and a surge in client flow. Subsequently, 61% of pharmacies experienced a dip in demand to below pre-pandemic levels and 31% reported challenges with unavailability, high price, and poor-quality of products. Almost all pharmacies were actively providing preventive materials and therapies; educating clients on prevention measures; counselling anxious clients; and handling and referring suspect cases. Fifty-nine pharmacies (55% [95% CI 45-65%]) reported ever receiving a client asking for COVID-19 testing and a similar proportion supported pharmacy-based testing. For treatment, most pharmacies (71%) recommended alternative therapies and nutritional supplements such as vitamin C; only 27% recommended conventional therapies such as antibiotics. While 48% had at least one staff member trained on COVID-19, a general feeling of disconnection from the national program prevailed.\n\nConclusionsPrivate pharmacies in Kenya were actively contributing to the COVID-19 response, but more deliberate engagement, support and linkages are required. Notably, there is an urgent need to develop guidelines for pharmacy-based COVID-19 testing, a service that is clearly needed and which could greatly increase test coverage. Roll-out of this and other pharmacy-based COVID-19 programs should be accompanied with implementation research in order to inform current and future pandemic responses.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Ryota Maeda",
-        "author_inst": "Kyoto University & COGNANO Inc."
-      },
-      {
-        "author_name": "Junso Fujita",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Yoshinobu Konishi",
-        "author_inst": "Kyoto University"
-      },
-      {
-        "author_name": "Yasuhiro Kazuma",
-        "author_inst": "Kyoto University"
-      },
-      {
-        "author_name": "Hiroyuki Yamazaki",
-        "author_inst": "COGNANO Inc."
-      },
-      {
-        "author_name": "Itsuki Anzai",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Keishi Yamaguchi",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Kazuki Kasai",
-        "author_inst": "Kyoto University & COGNANO Inc."
-      },
-      {
-        "author_name": "Kayoko Nagata",
-        "author_inst": "Kyoto University"
-      },
-      {
-        "author_name": "Yutaro Yamaoka",
-        "author_inst": "Yokohama City University"
-      },
-      {
-        "author_name": "Kei Miyakawa",
-        "author_inst": "Yokohama City University"
-      },
-      {
-        "author_name": "Akihide Ryo",
-        "author_inst": "Yokohama City University"
+        "author_name": "Peter Mwangi Mugo",
+        "author_inst": "KEMRI Wellcome Trust Research Programme"
       },
       {
-        "author_name": "Kotaro Shirakawa",
-        "author_inst": "Kyoto University"
+        "author_name": "Audrey Nyawira Mumbi",
+        "author_inst": "KEMRI Wellcome trust Research Programme"
       },
       {
-        "author_name": "Fumiaki Makino",
-        "author_inst": "Osaka University & JEOL Ltd."
+        "author_name": "Daniella Munene",
+        "author_inst": "Pharmaceutical Society of Kenya"
       },
       {
-        "author_name": "Yoshiharu Matsuura",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Tsuyoshi Inoue",
-        "author_inst": "Osaka University"
+        "author_name": "Jacinta Nzinga",
+        "author_inst": "KEMRI Wellcome Trust Research Programme"
       },
       {
-        "author_name": "Akihiro Imura",
-        "author_inst": "COGNANO Inc."
+        "author_name": "Sassy Molyneux",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Keiichi Namba",
-        "author_inst": "Osaka University & JEOL YOKOGUSHI Research Alliance Laboratories & RIKEN Center for Biosystems Dynamics Research and SPring-8 Center"
+        "author_name": "Edwine Barasa",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme"
       },
       {
-        "author_name": "Akifumi Takaori-Kondo",
-        "author_inst": "Kyoto University"
+        "author_name": "- Pharmaceutical Society of Kenya (PSK) COVID-19 Response Taskforce (CRT)",
+        "author_inst": ""
       }
     ],
     "version": "1",
     "license": "cc_by",
-    "type": "new results",
-    "category": "molecular biology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "health systems and quality improvement"
   },
   {
     "rel_doi": "10.1101/2021.10.19.21265195",
@@ -495198,187 +497093,91 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.10.18.21264530",
-    "rel_title": "Integrated Genomic Surveillance reveals extensive onward transmission of travel-imported SARS-CoV-2 infections in the community",
-    "rel_date": "2021-10-26",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.18.21264530",
-    "rel_abs": "Integration of genomic surveillance with contact tracing provides a powerful tool for the reconstruction of person-to-person pathogen transmission chains. We report two large clusters of SARS-CoV-2 cases (\"Delta\" clade, 110 cases combined) detected in July 2021 by Integrated Genomic Surveillance in Dusseldorf. Structured interviews and deep contact tracing demonstrated an association to a single SARS-CoV-2 infected return traveller (Cluster 1) and to return travel from Catalonia and other European countries (Cluster 2), highlighting the importance of containing travel-imported SARS-CoV-2 infections.",
-    "rel_num_authors": 42,
+    "rel_doi": "10.1101/2021.10.24.465626",
+    "rel_title": "SARS-CoV-2 infects human adipose tissue and elicits an inflammatory response consistent with severe COVID-19",
+    "rel_date": "2021-10-25",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.24.465626",
+    "rel_abs": "The COVID-19 pandemic, caused by the viral pathogen SARS-CoV-2, has taken the lives of millions of individuals around the world. Obesity is associated with adverse COVID-19 outcomes, but the underlying mechanism is unknown. In this report, we demonstrate that human adipose tissue from multiple depots is permissive to SARS-CoV-2 infection and that infection elicits an inflammatory response, including the secretion of known inflammatory mediators of severe COVID-19. We identify two cellular targets of SARS-CoV-2 infection in adipose tissue: mature adipocytes and adipose tissue macrophages. Adipose tissue macrophage infection is largely restricted to a highly inflammatory subpopulation of macrophages, present at baseline, that is further activated in response to SARS-CoV-2 infection. Preadipocytes, while not infected, adopt a proinflammatory phenotype. We further demonstrate that SARS-CoV-2 RNA is detectable in adipocytes in COVID-19 autopsy cases and is associated with an inflammatory infiltrate. Collectively, our findings indicate that adipose tissue supports SARS-CoV-2 infection and pathogenic inflammation and may explain the link between obesity and severe COVID-19.\n\nOne sentence summaryOur work provides the first in vivo evidence of SARS-CoV-2 infection in human adipose tissue and describes the associated inflammation.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Torsten Houwaart",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Samir Belhaj",
-        "author_inst": "D\u00fcsseldorf Health Authority (Gesundheitsamt D\u00fcsseldorf), D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Emran Tawalbeh",
-        "author_inst": "D\u00fcsseldorf Health Authority (Gesundheitsamt D\u00fcsseldorf), D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Dirk Nagels",
-        "author_inst": "D\u00fcsseldorf Health Authority (Gesundheitsamt D\u00fcsseldorf), D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Patrick Finzer",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany; Zotz | Klimas, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Lisa Stiller",
-        "author_inst": "Medizinische Laboratorien D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Jacqueline Blum",
-        "author_inst": "Medizinische Laboratorien D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Christian Lange",
-        "author_inst": "Medizinische Laboratorien D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Yara Fr\u00f6hlich",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Assia Benmoumene",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Dounia Asskali",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Hussein Haidar",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Janina von Dahlen",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Carla Adelmann",
-        "author_inst": "Solingen Health Authority (Gesundheitsamt Solingen)"
-      },
-      {
-        "author_name": "Britta Schroer",
-        "author_inst": "Solingen Health Authority (Gesundheitsamt Solingen)"
-      },
-      {
-        "author_name": "Ute Osmers",
-        "author_inst": "MVZ SYNLAB Leverkusen GmbH"
-      },
-      {
-        "author_name": "Christiane Grice",
-        "author_inst": "MVZ SYNLAB Leverkusen GmbH"
-      },
-      {
-        "author_name": "Phillipp P. Kirfel",
-        "author_inst": "MVZ SYNLAB Leverkusen GmbH"
-      },
-      {
-        "author_name": "Hassan Jomaa",
-        "author_inst": "MVZ SYNLAB Leverkusen GmbH"
-      },
-      {
-        "author_name": "Moritz Pigulla",
-        "author_inst": "D\u00fcsseldorf Health Authority (Gesundheitsamt D\u00fcsseldorf), D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Pascal Kreuzer",
-        "author_inst": "D\u00fcsseldorf Health Authority (Gesundheitsamt D\u00fcsseldorf), D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Alona Tyshaieva",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Jonas Weber",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Daniel Strelow",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
-      },
-      {
-        "author_name": "Jessica Nicolai",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Giovanny J Mart\u00ednez-Col\u00f3n",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Tobias Wienemann",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Kalani Ratnasiri",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Malte Kohns Vasconcelos",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Heping Chen",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Lisanna H\u00fclse",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Sizun Jiang",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Katrin Hoffmann",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Elizabeth Zanley",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Nadine L\u00fcbke",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Arjun Rustagi",
+        "author_inst": "Stanford University School of Medicine"
       },
       {
-        "author_name": "Sandra Hauka",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Renu Verma",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Marcel Andree",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Han Chen",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Claus J\u00fcrgen Scholz",
-        "author_inst": "Labor Dr. Wisplinghoff, Cologne, Germany"
+        "author_name": "Jason R Andrews",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Nathalie Jazmati",
-        "author_inst": "Labor Dr. Wisplinghoff, Cologne, Germany"
+        "author_name": "Kirsten Mertz",
+        "author_inst": "Cantonal Hospital Baselland"
       },
       {
-        "author_name": "Klaus G\u00f6bels",
-        "author_inst": "D\u00fcsseldorf Health Authority (Gesundheitsamt D\u00fcsseldorf), D\u00fcsseldorf, Germany"
+        "author_name": "Alexandar Tzankov",
+        "author_inst": "University Hospital of Basel"
       },
       {
-        "author_name": "Rainer Zotz",
-        "author_inst": "Zotz | Klimas, D\u00fcsseldorf, Germany; Labor Dr. Wisplinghoff, Cologne, Germany"
+        "author_name": "Dan Azagury",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Klaus Pfeffer",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Jack Boyd",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "J\u00f6rg Timm",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Garry P Nolan",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Lutz Ehlkes",
-        "author_inst": "D\u00fcsseldorf Health Authority (Gesundheitsamt D\u00fcsseldorf), D\u00fcsseldorf, Germany"
+        "author_name": "Christian M. Sch\u00fcrch",
+        "author_inst": "University Hospital and Comprehensive Cancer Center T\u00fcbingen"
       },
       {
-        "author_name": "Andreas Walker",
-        "author_inst": "Institute of Virology, University Hospital D\u00fcsseldorf, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Matthias S Matter",
+        "author_inst": "University Hospital of Basel"
       },
       {
-        "author_name": "Alexander T. Dilthey",
-        "author_inst": "Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University D\u00fcsseldorf, D\u00fcsseldorf, Germany"
+        "author_name": "Catherine A Blish",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "- German COVID-19 OMICS Initiative (DeCOI)",
-        "author_inst": ""
+        "author_name": "Tracey L McLaughlin",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.10.21.21265272",
@@ -497272,143 +499071,211 @@
     "category": "pharmacology and toxicology"
   },
   {
-    "rel_doi": "10.1101/2021.10.22.465476",
-    "rel_title": "The humanized nanobody RBD-1-2G tolerates the spike N501Y mutation to neutralize SARS-CoV-2",
+    "rel_doi": "10.1101/2021.10.23.465542",
+    "rel_title": "Protection from SARS-CoV-2 Delta one year after mRNA-1273 vaccination in nonhuman primates is coincident with an anamnestic antibody response in the lower airway",
     "rel_date": "2021-10-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.22.465476",
-    "rel_abs": "Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants.",
-    "rel_num_authors": 31,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.23.465542",
+    "rel_abs": "mRNA-1273 vaccine efficacy against SARS-CoV-2 Delta wanes over time; however, there are limited data on the impact of durability of immune responses on protection. We immunized rhesus macaques at weeks 0 and 4 and assessed immune responses over one year in blood, upper and lower airways. Serum neutralizing titers to Delta were 280 and 34 reciprocal ID50 at weeks 6 (peak) and 48 (challenge), respectively. Antibody binding titers also decreased in bronchoalveolar lavage (BAL). Four days after challenge, virus was unculturable in BAL and subgenomic RNA declined [~]3-log10 compared to control animals. In nasal swabs, sgRNA declined 1-log10 and virus remained culturable. Anamnestic antibody responses (590-fold increase) but not T cell responses were detected in BAL by day 4 post-challenge. mRNA-1273-mediated protection in the lungs is durable but delayed and potentially dependent on anamnestic antibody responses. Rapid and sustained protection in upper and lower airways may eventually require a boost.",
+    "rel_num_authors": 48,
     "rel_authors": [
       {
-        "author_name": "Ying Fu",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Matthew Gagne",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Juliana da Fonseca Rezende e Mello",
-        "author_inst": "National Institute of Environmental Health Sciences"
+        "author_name": "Kizzmekia S. Corbett",
+        "author_inst": "Vaccine Research Center, NIAID, NIH, Bethesda, Maryland, 20892, United States of America  Department of Microbiology and Immunology, Harvard T.H. Chan School of"
       },
       {
-        "author_name": "Bryan D Fleming",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Barbara J. Flynn",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Alex Renn",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Kathryn E. Foulds",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Catherine Z. Chen",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Danielle A. Wagner",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Xin Hu",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Shayne F. Andrew",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Miao Xu",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "John-Paul M. Todd",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Kirill Gorshkov",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Christopher Cole Honeycutt",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Quinlin Hanson",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Lauren McCormick",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Wei Zheng",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Saule T. Nurmukhambetova",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Emily M Lee",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Meredith E. Davis-Gardner",
+        "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St"
       },
       {
-        "author_name": "Lalith Perera",
-        "author_inst": "National Institute of Environmental Health Sciences"
+        "author_name": "Laurent Pessaint",
+        "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America"
       },
       {
-        "author_name": "Robert Petrovich",
-        "author_inst": "National Institute of Environmental Health Sciences"
+        "author_name": "Kevin W. Bock",
+        "author_inst": "Infectious Disease Pathogenesis Section, Comparative Medicine Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rock"
       },
       {
-        "author_name": "Manisha Pradhan",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Bianca M. Nagata",
+        "author_inst": "Infectious Disease Pathogenesis Section, Comparative Medicine Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rock"
       },
       {
-        "author_name": "Richard T Eastman",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Mahnaz Minai",
+        "author_inst": "Infectious Disease Pathogenesis Section, Comparative Medicine Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rock"
       },
       {
-        "author_name": "Zina Itkin",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Anne P. Werner",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Thomas Stanley",
-        "author_inst": "National Institute of Environmental Health Services"
+        "author_name": "Juan I. Moliva",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Allen Hsu",
-        "author_inst": "National Institute of Environmental Health Sciences"
+        "author_name": "Courtney Tucker",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Venkata Dandey",
-        "author_inst": "National Institute of Environmental Health Sciences"
+        "author_name": "Cynthia G. Lorang",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "William Gillette",
-        "author_inst": "Frederick National Laboratory for Cancer Research"
+        "author_name": "Bingchun Zhao",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Troy Taylor",
-        "author_inst": "Frederick National Laboratory for Cancer Research"
+        "author_name": "Elizabeth McCarthy",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Nitya Ramakrishnan",
-        "author_inst": "Frederick National Laboratory for Cancer Research"
+        "author_name": "Anthony Cook",
+        "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America"
       },
       {
-        "author_name": "Shelley Perkins",
-        "author_inst": "Frederick National Laboratory for Cancer Research"
+        "author_name": "Alan Dodson",
+        "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America"
       },
       {
-        "author_name": "Dominic Esposito",
-        "author_inst": "Frederick National Laboratory for Cancer Research"
+        "author_name": "Prakriti Mudvari",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Eunkeu Oh",
-        "author_inst": "Naval Research Laboratory"
+        "author_name": "Jesmine Roberts-Torres",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Kimihiro Susumu",
-        "author_inst": "Jacobs Corporation"
+        "author_name": "Farida Laboune",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Mason Wolak",
-        "author_inst": "Naval Research Laboratory"
+        "author_name": "Lingshu Wang",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Marc Ferrer",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Adrienne Goode",
+        "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America"
       },
       {
-        "author_name": "Matthew D. Hall",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Swagata Kar",
+        "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America"
       },
       {
-        "author_name": "Mario J Borgnia",
-        "author_inst": "National Institute of Environmental Health Sciences"
+        "author_name": "Seyhan Boyoglu-Barnum",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       },
       {
-        "author_name": "Anton Simeonov",
-        "author_inst": "National Center for Advancing Translational Sciences"
+        "author_name": "Eun Sung Yang",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Wei Shi",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Aur\u00e9lie Ploquin",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Nicole Doria-Rose",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Andrea Carfi",
+        "author_inst": "Moderna Inc., Cambridge, MA, 02139, United States of America"
+      },
+      {
+        "author_name": "John R. Mascola",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Eli A. Boritz",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Darin K. Edwards",
+        "author_inst": "Moderna Inc., Cambridge, MA, 02139, United States of America"
+      },
+      {
+        "author_name": "Hanne Andersen",
+        "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America"
+      },
+      {
+        "author_name": "Mark G. Lewis",
+        "author_inst": "Bioqual, Inc., Rockville, Maryland, 20850, United States of America"
+      },
+      {
+        "author_name": "Mehul S. Suthar",
+        "author_inst": "Department of Pediatrics, Emory Vaccine Center, Yerkes National Primate Research Center, Emory University School of Medicine, Atlanta, Georgia, 30322, United St"
+      },
+      {
+        "author_name": "Barney S. Graham",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Mario Roederer",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Ian N. Moore",
+        "author_inst": "Infectious Disease Pathogenesis Section, Comparative Medicine Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rock"
+      },
+      {
+        "author_name": "Martha C. Nason",
+        "author_inst": "Biostatistics Research Branch, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Ma"
+      },
+      {
+        "author_name": "Nancy J. Sullivan",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Daniel C. Douek",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
+      },
+      {
+        "author_name": "Robert A. Seder",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, 20892, United States of Ameri"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "synthetic biology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.10.23.465567",
@@ -499153,37 +501020,145 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2021.10.20.21265149",
-    "rel_title": "Differences in COVID-19 Risk by Race and County-Level Social Determinants of Health Among Veterans",
+    "rel_doi": "10.1101/2021.10.21.21265133",
+    "rel_title": "Post COVID-19 in children, adolescents, and adults: results of a matched cohort study including more than 150,000 individuals with COVID-19",
     "rel_date": "2021-10-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.20.21265149",
-    "rel_abs": "COVID-19 disparities by area-level social determinants of health (SDH) may be impacting U.S. Veterans. This retrospective analysis utilized COVID-19 data from the U.S. Department of Veterans Affairs (VA)s EHR and geographically linked county-level data from 18 area-based socioeconomic measures. The risk of testing positive with Veterans county-level SDHs adjusting for demographics, comorbidities, and facility characteristics was calculated using generalized linear models. We found an exposure-response relationship whereby individual COVID-19 infection risk increased with each increasing quartile of adverse county-level SDH such as the percentage of residents in a county without a college degree, eligible for Medicaid, and living in crowded housing.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.21.21265133",
+    "rel_abs": "BackgroundLong-term health sequelae of the coronavirus disease 2019 (COVID-19) are a major public health concern. However, evidence on post-acute COVID-19 syndrome (post COVID-19) is still limited, particularly for children and adolescents. Utilizing comprehensive healthcare data on more than 45 percent of the German population from January 2019 through December 2020, we investigated post COVID-19 in children/adolescents and adults.\n\nMethodsFrom a total of 38 million individuals, we identified all patients with laboratory confirmed diagnosis of COVID-19 through June 30, 2020. A control cohort was assigned using 1:5 exact matching on age, sex, and propensity score matching on prevalent medical conditions. COVID-19 and control cohorts were followed for incident morbidity outcomes documented at least three months after the date of COVID-19 diagnosis, which was used as the index date for both groups. Overall, 96 pre-defined outcomes were aggregated into 13 diagnosis/symptom complexes and three domains (physical health, mental health, physical/mental overlap domain). We used Poisson regression to estimate incidence rate ratios (IRRs) with 95%-confidence intervals (95%-CI).\n\nResultsThe study population included 157,134 individuals (11,950 children/adolescents and 145,184 adults) with confirmed COVID-19. COVID-19 and control cohort were well-balanced regarding covariates. For all health outcomes combined, incidence rates (IRs) in the COVID-19 cohort were significantly higher than those in the control cohort in both children/adolescents (IRR=1.30, 95%-CI=[1.25-1.35], IR COVID-19=436.91, IR Control=335.98) and adults (IRR=1.33, 95%-CI=[1.31-1.34], IR COVID-19=615.82, IR Control=464.15). The relative magnitude of increased documented morbidity was similar for the physical, mental, and physical/mental overlap domain. In the COVID-19 cohort, incidence rates were significantly higher in all 13 diagnosis/symptom complexes in adults and in ten diagnosis/symptom complexes in children/adolescents. IRR estimates were similar for the age groups 0-11 and 12-17. Incidence rates in children/adolescents were consistently lower than those in adults. Among the specific outcomes with the highest IRR and an incidence rate of at least 1/100 person-years in the COVID-19 cohort in children and adolescents were malaise/fatigue/exhaustion (IRR=2.28, 95%-CI=[1.71-3.06], IR COVID-19=12.58, IR Control=5.51), cough (IRR=1.74, 95%-CI=[1.48-2.04], IR COVID-19=36.56, IR Control=21.06), and throat/chest pain (IRR=1.72, 95%-CI=[1.39-2.12], IR COVID-19=20.01, IR Control=11.66). In adults, these included dysgeusia (IRR=6.69, 95%-CI=[5.88-7.60], IR COVID-19=12.42, IR Control=1.86), fever (IRR=3.33, 95%-CI=[3.01-3.68], IR COVID-19=11.53, IR Control=3.46), and dyspnea (IRR=2.88, 95%-CI=[2.74-3.02], IR COVID-19=43.91, IR Control=15.27).\n\nConclusionsThis large, matched cohort study indicates substantial new-onset post COVID-19 morbidity in pediatric and adult populations based on routine health care documentation. Further investigation is required to assess the persistence and long-term health impact of post COVID-19 conditions, especially in children and adolescents.",
+    "rel_num_authors": 32,
     "rel_authors": [
       {
-        "author_name": "Hoda S. Abdel Magid",
-        "author_inst": "Stanford University; Veterans Affairs Palo Alto Healthcare System"
+        "author_name": "Martin Roessler",
+        "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden,  Dresden, Germany"
       },
       {
-        "author_name": "Jacqueline M Ferguson",
-        "author_inst": "Stanford University; Veterans Affairs Palo Alto Healthcare System"
+        "author_name": "Falko Tesch",
+        "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden,  Dresden, Germany"
       },
       {
-        "author_name": "Raymond V Cleve",
-        "author_inst": "Stanford University; Veterans Affairs Palo Alto Healthcare System"
+        "author_name": "Manuel Batram",
+        "author_inst": "Vandage GmbH, Bielefeld, Germany and Faculty for Business Administration and Economics, Bielefeld University, Bielefeld, Germany"
       },
       {
-        "author_name": "Amanda Purnell",
-        "author_inst": "Veterans Affairs Central Office"
+        "author_name": "Josephine Jacob",
+        "author_inst": "InGef - Institute for Applied Health Research Berlin, Berlin, Germany"
       },
       {
-        "author_name": "Thomas F Osborne",
-        "author_inst": "Stanford University; Veterans Affairs Palo Alto Healthcare System"
+        "author_name": "Friedrich Loser",
+        "author_inst": "Techniker Krankenkasse, Hamburg, Germany"
+      },
+      {
+        "author_name": "Oliver Weidinger",
+        "author_inst": "AOK Bayern - Die Gesundheitskasse, Regensburg, Germany"
+      },
+      {
+        "author_name": "Danny Wende",
+        "author_inst": "BARMER Institut f\u00fcr Gesundheitssystemforschung (bifg), Berlin, Germany"
+      },
+      {
+        "author_name": "Annika Vivirito",
+        "author_inst": "InGef - Institute for Applied Health Research Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Nicole Toepfner",
+        "author_inst": "Department of Pediatrics, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden,  Dresden, Germany"
+      },
+      {
+        "author_name": "Martin Seifert",
+        "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden,  Dresden, Germany"
+      },
+      {
+        "author_name": "Oliver Nagel",
+        "author_inst": "InGef - Institute for Applied Health Research Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Christina K\u00f6nig",
+        "author_inst": "Techniker Krankenkasse, Hamburg, Germany"
+      },
+      {
+        "author_name": "Roland Jucknewitz",
+        "author_inst": "AOK Bayern - Die Gesundheitskasse, Regensburg, Germany"
+      },
+      {
+        "author_name": "Jakob Peter Armann",
+        "author_inst": "Department of Pediatrics, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden,  Dresden, Germany"
+      },
+      {
+        "author_name": "Reinhard Berner",
+        "author_inst": "Department of Pediatrics, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden,  Dresden, Germany"
+      },
+      {
+        "author_name": "Marina Treskova-Schwarzbach",
+        "author_inst": "Robert Koch-Institut, Berlin, Germany"
+      },
+      {
+        "author_name": "Dagmar Hertle",
+        "author_inst": "BARMER Institut f\u00fcr Gesundheitssystemforschung (bifg), Berlin, Germany"
+      },
+      {
+        "author_name": "Stefan Scholz",
+        "author_inst": "Robert Koch-Institut, Berlin, Germany"
+      },
+      {
+        "author_name": "Stefan Stern",
+        "author_inst": "AOK Bayern - Die Gesundheitskasse, Regensburg, Germany"
+      },
+      {
+        "author_name": "Pedro Ballesteros",
+        "author_inst": "BARMER Institut f\u00fcr Gesundheitssystemforschung (bifg), Berlin, Germany"
+      },
+      {
+        "author_name": "Stefan Ba\u00dfler",
+        "author_inst": "AOK PLUS, Dresden, Germany"
+      },
+      {
+        "author_name": "Barbara Bertele",
+        "author_inst": "Techniker Krankenkasse, Hamburg, Germany"
+      },
+      {
+        "author_name": "Uwe Repschl\u00e4ger",
+        "author_inst": "BARMER Institut f\u00fcr Gesundheitssystemforschung (bifg), Berlin, Germany"
+      },
+      {
+        "author_name": "Nico Richter",
+        "author_inst": "DAK-Gesundheit, Hamburg, Germany"
+      },
+      {
+        "author_name": "Cordula Riederer",
+        "author_inst": "DAK-Gesundheit, Hamburg, Germany"
+      },
+      {
+        "author_name": "Franziska Sobik",
+        "author_inst": "DAK-Gesundheit, Hamburg, Germany"
+      },
+      {
+        "author_name": "Anja Schramm",
+        "author_inst": "AOK Bayern - Die Gesundheitskasse, Regensburg, Germany"
+      },
+      {
+        "author_name": "Claudia Schulte",
+        "author_inst": "BARMER Institut f\u00fcr Gesundheitssystemforschung (bifg), Berlin, Germany"
+      },
+      {
+        "author_name": "Lothar Wieler",
+        "author_inst": "Robert Koch-Institut, Berlin, Germany"
+      },
+      {
+        "author_name": "Jochen Walker",
+        "author_inst": "InGef - Institute for Applied Health Research Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Christa Scheidt-Nave",
+        "author_inst": "Robert Koch-Institut, Berlin, Germany"
+      },
+      {
+        "author_name": "Jochen Schmitt",
+        "author_inst": "Center for Evidence-Based Healthcare (ZEGV), University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, TU Dresden,  Dresden, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -501191,45 +503166,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.10.18.21265057",
-    "rel_title": "Impact of routine asymptomatic screening on COVID-19 incidence in a highly vaccinated university population",
+    "rel_doi": "10.1101/2021.10.15.21265037",
+    "rel_title": "Extreme COVID-19 waves reveal hyperexponential growth and finite-time singularity",
     "rel_date": "2021-10-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.18.21265057",
-    "rel_abs": "BackgroundWith the return of in-person classes, an understanding of COVID-19 transmission in vaccinated university campuses is essential. Given the context of high anticipated vaccination rates and other measures, there are outstanding questions of the potential impact of campus-based asymptomatic screening.\n\nMethodsWe estimated the expected number of cases and hospitalizations in one semester using rates derived for British Columbia (BC), Canada up to September 15th, 2021 and age-standardizing to a University population. To estimate the expected number of secondary cases averted due to routine tests of unvaccinated individuals in a BC post-secondary institution, we used a probabilistic model based on the incidence, vaccination effectiveness, vaccination coverage and R0. We examined multiple scenarios of vaccine coverage, screening frequency, and pre-vaccination R0.\n\nResultsFor one 12 week semester, the expected number of cases is 67 per 50,000 for 80% vaccination coverage and 37 per 50,000 for 95% vaccination coverage. Screening of the unvaccinated population averts an expected 6-16 cases per 50,000 at 80% decreasing to 1-2 averted cases per 50,000 at 95% vaccination coverage for weekly to daily screening. Further scenarios can be explored using a web-based application.\n\nInterpretationRoutine screening of unvaccinated individuals may be of limited benefit if vaccination coverage is 80% or greater within a university setting.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.15.21265037",
+    "rel_abs": "Coronavirus disease 2019 (COVID-19) has rapidly spread throughout our planet, bringing human lives to a standstill. Understanding the early transmission dynamics helps plan intervention strategies such as lockdowns that mitigate further spread, minimizing the adverse impact on humanity and the economy1-3. Exponential growth of infections was thought to be the defining feature of an epidemic in its initial growth phase4-7; any variation from an exponential growth was described by adjusting the parameters of the exponential model7,8. Here, we show that, contrary to common belief, early stages of extreme COVID-19 waves display an unbounded growth and finite-time singularity accompanying a hyperexponential power-law. The faster than exponential growth phase is hazardous and would entail stricter regulations. Such a power-law description allows us to characterize COVID-19 waves with single power-law exponents, better than piece-wise exponentials. Furthermore, we identify the presence of log-periodic patterns decorating the power-law growth. These log-periodic oscillations may enable better prediction of the finite-time singularity. We anticipate that our findings of hyperexponential growth and log-periodicity will help model the COVID-19 transmission more accurately.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Rebeca Cardim Falcao",
-        "author_inst": "BC Centre for Disease Control"
-      },
-      {
-        "author_name": "Michael Otterstatter",
-        "author_inst": "BC Centre for Disease Control"
-      },
-      {
-        "author_name": "May A. Ahmed",
-        "author_inst": "BC Centre for Disease Control"
-      },
-      {
-        "author_name": "Michelle Spencer",
-        "author_inst": "BC Centre for Disease Control"
-      },
-      {
-        "author_name": "Sarafa Iyaniwura",
-        "author_inst": "BC Centre for Disease Control"
-      },
-      {
-        "author_name": "Naveed Z. Janjua",
-        "author_inst": "BC Centre for Disease Control"
+        "author_name": "Induja Pavithran",
+        "author_inst": "Indian Institue of technology Madras"
       },
       {
-        "author_name": "Geoff McKee",
-        "author_inst": "BC Centre for Disease Control"
-      },
-      {
-        "author_name": "Michael A. Irvine",
-        "author_inst": "BC Centre for Disease Control"
+        "author_name": "R. I. Sujith",
+        "author_inst": "Indian Institue of technology Madras"
       }
     ],
     "version": "1",
@@ -503020,65 +504971,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.10.13.21264919",
-    "rel_title": "Agile design and development of a high throughput cobas(R) SARS-CoV-2 RT-PCR diagnostic test",
+    "rel_doi": "10.1101/2021.10.14.21265010",
+    "rel_title": "How frequent are acute reactions to COVID-19 vaccination and who is at risk?",
     "rel_date": "2021-10-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.13.21264919",
-    "rel_abs": "Diagnostic testing is essential for management of the COVID-19 pandemic. An agile assay design methodology, optimized for the cobas(R) 6800/8800 system, was used to develop a dual-target, qualitative SARS-CoV-2 RT-PCR test using commercially available reagents and existing sample processing and thermocycling profiles. The limit of detection was 0.004 to 0.007 TCID50/mL for USA-WA1/2020. Assay sensitivity was confirmed for SARS-CoV-2 variants Alpha, Beta, Gamma, Delta and Kappa. The coefficients of variation of the cycle threshold number (Ct) were between 1.1 and 2.2%. There was no difference in Ct using nasopharyngeal compared to oropharyngeal swabs in universal transport medium (UTM). A small increase in Ct was observed with specimens collected in cobas(R) PCR medium compared to UTM. In silico analysis indicated that the dual-target test is capable of detecting all >1,800,000 SARS-CoV-2 sequences in the GISAID database. Our agile assay design approach facilitated rapid development and deployment of this SARS-CoV-2 RT-PCR test.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21265010",
+    "rel_abs": "IntroductionOur objective was to describe and compare self-reported side effects of COVID-19 vaccines in the USA.\n\nMethodsA web-based registry enrolled volunteers who received a COVID-19 vaccine between March 19 -July 15, 2021. We collected self-reported short-term side effects, medical consultation, hospitalization, and quality of life impact following completed vaccination regimens (Pfizer, Moderna, J&J).\n\nResultsWe recruited 6,966 volunteers who completed their full course of vaccination (median age 48 years, IQR 35.0-62.0; 83.6% female): Pfizer 3,486; Moderna 2,857; J&J 623. Few (3.1%) sought medical care for post-vaccination side effects. Hospitalization (n=17; 0.3%) and severe allergic reactions (n=39; 0.6%) also were rare. Those with autoimmune disease or lung disease were approximately twice as likely to seek medical care (adjusted odds ratio (aOR) 2.01 [95% CI: 1.39;2.92] and 1.70 [95% CI: 1.12;2.58] respectively). 92.4% of participants reported [&ge;]1 side effect (median 3), with injection site reactions (78.9%), fatigue (70.3%), headache (49.0%) reported most frequently. More side effects were reported after the second dose of two-dose vaccines (medians: 1 vs. 2 for Pfizer and 1 vs. 3 for Moderna for first and second doses respectively) versus 3 for J&Js single-dose vaccine. For the employed, the median number of workdays missed was one. Diabetics and those vaccinated against influenza were substantially less likely to report [&ge;]3 symptoms (aOR 0.68, 95% CI 0.56,0.82 and aOR 0.82, 95% CI 0.73,0.93, respectively.)\n\nDiscussionThe total side effect burden was, not unexpectedly, greater with two-dose regimens but all three vaccines appear relatively safe. Very few subjects reported side effects serious enough to warrant medical care or reported post-vaccination hospitalization. While these findings do not address possible long-term effects, they do inform on their short-term safety and tolerability and will hopefully provide some reassurance and positively inform the benefit-risk and pharmacoeconomic assessment for all three vaccines.\n\nClinicaltrials.gov NCT04368065",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Chitra Manohar",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
-      },
-      {
-        "author_name": "Jingtao Sun",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
-      },
-      {
-        "author_name": "Peter Schlag",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
-      },
-      {
-        "author_name": "Chris Santini",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
-      },
-      {
-        "author_name": "Marcel Fontecha",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
-      },
-      {
-        "author_name": "Pirmin Lotscher",
-        "author_inst": "Roche Diagnostics International AG, Rotkreuz, Switzerland"
+        "author_name": "Nancy A Dreyer",
+        "author_inst": "IQVIA"
       },
       {
-        "author_name": "Carolin Bier",
-        "author_inst": "Roche Diagnostics International AG, Rotkreuz, Switzerland"
+        "author_name": "Matthew W Reynolds",
+        "author_inst": "IQVIA"
       },
       {
-        "author_name": "Kristina Goepfert",
-        "author_inst": "Roche Diagnostics International AG, Rotkreuz, Switzerland"
+        "author_name": "Lisa M Albert",
+        "author_inst": "IQVIA"
       },
       {
-        "author_name": "Dana Duncan",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
+        "author_name": "Emma Brinkley",
+        "author_inst": "IQVIA"
       },
       {
-        "author_name": "Gene Spier",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
+        "author_name": "Tom Kwon",
+        "author_inst": "IQVIA"
       },
       {
-        "author_name": "Daniel Jarem",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
+        "author_name": "Christina D Mack",
+        "author_inst": "IQVIA"
       },
       {
-        "author_name": "Dmitriy Kosarikov",
-        "author_inst": "Roche Molecular Systems, Inc., Pleasanton, United States"
+        "author_name": "Stephen Toovey",
+        "author_inst": "Pegasus Research"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -504610,29 +506541,49 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.10.17.21265101",
-    "rel_title": "Time-varying effectiveness of the mRNA-1273, BNT162b2 and Ad26.COV2.S vaccines against SARS-CoV-2 infections and COVID-19 hospitalizations and deaths: an analysis based on observational data from Puerto Rico",
+    "rel_doi": "10.1101/2021.10.18.21265046",
+    "rel_title": "Comparative assessment of methods for short-term forecasts of COVID-19 admissions in England at the local level",
     "rel_date": "2021-10-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.17.21265101",
-    "rel_abs": "BackgroundAs of October 1, 2021 2,217,547 individuals were fully vaccinated against COVID-19 in Puerto Rico. Since the vaccination process commenced on December 15, 2020 111,052 laboratory-confirmed SARS-CoV-2 infections have been reported. These data permitted us to quantify the benefits of the immunization campaign and to compare effectiveness of the mRNA-1273 (Moderna), BNT162b2 (Pfizer), and Ad26.COV2.S (J&J) vaccines.\n\nMethodsDepartment of Health databases holding vaccination status, SARS-CoV-2 test results, and COVID-19 hospitalizations and deaths were integrated. We fit a statistical model that adjusted for time-varying incidence rates and age to estimate vaccine effectiveness and hospitalization and death relative risks. Code and data are provided here: https://github.com/rafalab/vax-eff-pr.\n\nResultsAt the peak of their protection, mRNA-1273, BNT162b2, and Ad26.COV2.S had an effectiveness of 90% (88%-91%), 87% (85%-89%), and 58% (51%-65%), respectively. After four months, effectiveness waned to about 70%, 60%, and 30%. We found no evidence that effectiveness was different after the Delta variant became dominant. For those infected, the vaccines provided further protection against hospitalization and deaths across all age groups. All vaccines had a lower effectiveness for those over 85 years, with a larger decrease for the Ad26.COV2.S vaccine. Overall, thousands of hospitalizations and deaths were avoided thanks to the vaccines.\n\nConclusionsThe mRNA-1273 and BNT162b2 vaccines were highly effective across all age groups. They were still effective after four months although the protection waned. The Ad26.COV2.S vaccine was effective but to a lesser degree, especially for older age groups.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.18.21265046",
+    "rel_abs": "BackgroundForecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.\n\nMethodsWe made weekly forecasts of daily COVID-19 hospital admissions for National Health Service (NHS) Trusts in England between August 2020 and April 2021 using three disease-agnostic forecasting models: a mean ensemble of autoregressive time series models, a linear regression model with 7-day-lagged local cases as a predictor, and a scaled convolution of local cases and a delay distribution. We compared their point and probabilistic accuracy to a mean-ensemble of them all, and to a simple baseline model of no change from the last day of admissions. We measured predictive performance using the Weighted Interval Score (WIS) and considered how this changed in different scenarios (the length of the predictive horizon, the date on which the forecast was made, and by location), as well as how much admissions forecasts improved when future cases were known.\n\nResultsAll models outperformed the baseline in the majority of scenarios. Forecasting accuracy varied by forecast date and location, depending on the trajectory of the outbreak, and all individual models had instances where they were the top- or bottom-ranked model. Forecasts produced by the mean-ensemble were both the most accurate and most consistently accurate forecasts amongst all the models considered. Forecasting accuracy was improved when using future observed, rather than forecast, cases, especially at longer forecast horizons.\n\nConclusionsAssuming no change in current admissions is rarely better than including at least a trend. Using confirmed COVID-19 cases as a predictor can improve admissions forecasts in some scenarios, but this is variable and depends on the ability to make consistently good case forecasts. However, ensemble forecasts can make forecasts that make consistently more accurate forecasts across time and locations. Given minimal requirements on data and computation, our admissions forecasting ensemble could be used to anticipate healthcare needs in future epidemic or pandemic settings.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Monica M. Robles-Fontan",
-        "author_inst": "Departamento de Salud de Puerto Rico"
+        "author_name": "Sophie Meakin",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
       },
       {
-        "author_name": "Elvis G. Nieves",
-        "author_inst": "Departamento de Salud de Puerto Rico"
+        "author_name": "Sam Abbott",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
       },
       {
-        "author_name": "Iris Cardona-Gerena",
-        "author_inst": "Departamento de Salud de Puerto Rico"
+        "author_name": "Nikos I Bosse",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
       },
       {
-        "author_name": "Rafael A Irizarry",
-        "author_inst": "Dana-Farber Cancer Institute"
+        "author_name": "James D Munday",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "Hugo Gruson",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "Joel Hellewell",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "Katharine Sherratt",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "- CMMID COVID-19 Working Group",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Sebastian Funk",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
       }
     ],
     "version": "1",
@@ -506611,87 +508562,47 @@
     "category": "pediatrics"
   },
   {
-    "rel_doi": "10.1101/2021.10.11.21264709",
-    "rel_title": "Quantitative chest CT combined with plasma cytokines predict outcomes in COVID-19 patients",
+    "rel_doi": "10.1101/2021.10.12.21264890",
+    "rel_title": "Breastfeeding infants receive neutralizing antibodies and cytokines from mothers immunized with a COVID-19 mRNA vaccine",
     "rel_date": "2021-10-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.11.21264709",
-    "rel_abs": "Despite extraordinary international efforts to dampen the spread and understand the mechanisms behind SARS-CoV-2 infections, accessible predictive biomarkers directly applicable in the clinic are yet to be discovered. Recent studies have revealed that diverse types of assays bear limited predictive power for COVID-19 outcomes. Here, we harness the predictive power of chest CT in combination with plasma cytokines using a machine learning approach for predicting death during hospitalization and maximum severity degree in COVID-19 patients. Patients (n=152) from the Mount Sinai Health System in New York with plasma cytokine assessment and a chest CT within 5 days from admission were included. Demographics, clinical, and laboratory variables, including plasma cytokines (IL-6, IL-8, and TNF-) were collected from the electronic medical record. We found that chest CT combined with plasma cytokines were good predictors of death (AUC 0.78) and maximum severity (AUC 0.82), whereas CT quantitative was better at predicting severity (AUC 0.81 vs 0.70) while cytokine measurements better predicted death (AUC 0.70 vs 0.66). Finally, we provide a simple scoring system using plasma IL-6, IL-8, TNF-, GGO to aerated lung ratio and age as novel metrics that may be used to monitor patients upon hospitalization and help physicians make critical decisions and considerations for patients at high risk of death for COVID-19.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.12.21264890",
+    "rel_abs": "ObjectiveTo evaluate the immune response to COVID-19 mRNA-based vaccines present in breastmilk and the transfer of the immune response to the breastfeeding child.\n\nMethodsA prospective cohort study enrolled 30 lactating women who received an mRNA-based COVID-19 vaccine between January and April 2021. Women provided serial milk samples, which included milk expressed before vaccination, milk expressed across 2-3 weeks after the first dose, and milk expressed across 3 weeks after the second dose. Women also were asked to provide their blood, spotted on cards (dried blood spots; DBS) 19 days after the first dose and 21 days after the second dose. Stool samples from the breastfed infants were collected 21 days after mothers received their second dose. Pre-pandemic samples of milk, DBS cards, and infant stool from prior studies were also utilized. Milk and infant stool samples were tested by ELISA for receptor-binding domain (RBD)-specific IgA and IgG. Milk samples were tested for the presence of neutralizing antibodies against the spike and four variants of concern (VOCs): D614G, B.1.1.7 (alpha), B.1.351 (beta), and P.1 (gamma). Milk samples were also tested by electrochemiluminescence assay for levels of 10 cytokines.\n\nResultsMilk from COVID-19-immunized women neutralized the spike and four VOCs and this response is primarily IgG-driven. The immune response in milk also included significantly elevated levels of interferon-{gamma} (IFN-{gamma}). The immune response to maternal vaccination was reflected in breastfed babies; anti-RBD IgG and anti-RBD IgA was detected in 33% and 30% of infant stool samples, respectively. Levels of anti-RBD antibodies in infant stool correlated with maternal vaccine side-effects.\n\nConclusionHumoral and cellular immune responses to mRNA-based COVID-19 vaccination are present in the breastmilk of most women. The milk anti-RBD antibodies can neutralize SARS-CoV-2 spike and VOCs. Importantly, we describe for the first time the transfer of anti-RBD antibodies to breastfed infants, with the potential to confer passive immunity against SARS-CoV-2.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Guillermo Carbonell",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Diane Marie Del Valle",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Edgar E Gonzalez-Kozlova",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Brett Marinelli",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Emma Klein",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Maria El Homsi",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Daniel Stocker",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Michael Chung",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Adam Bernheim",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Nicole Simons",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Jiani Xiang",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Vignesh Narayanaswamy",
+        "author_inst": "University of Massachusetts Amherst"
       },
       {
-        "author_name": "Sharon Nirenberg",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Brian Pentecost",
+        "author_inst": "University of Massachusetts Amherst"
       },
       {
-        "author_name": "Patricia Kovatch",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Corina N Schoen",
+        "author_inst": "Baystate Medical Center"
       },
       {
-        "author_name": "Sara Lewis",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Dominique Alfandari",
+        "author_inst": "University of Massachusetts Amherst"
       },
       {
-        "author_name": "Miriam Merad",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Sallie S Schneider",
+        "author_inst": "Baystate Medical Center"
       },
       {
-        "author_name": "Sacha Gnjatic",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Ryan Baker",
+        "author_inst": "University of Massachusetts Amherst"
       },
       {
-        "author_name": "Bachir Taouli",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Kathleen F Arcaro",
+        "author_inst": "University of Massachusetts Amherst"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "radiology and imaging"
+    "category": "obstetrics and gynecology"
   },
   {
     "rel_doi": "10.1101/2021.10.11.21264831",
@@ -508473,89 +510384,61 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.10.13.21264975",
-    "rel_title": "Disparities in SARS-CoV-2 exposure: evidence from a citywide seroprevalence study in Holyoke, Massachusetts, USA",
+    "rel_doi": "10.1101/2021.10.13.21264901",
+    "rel_title": "Soluble angiotensin-converting enzyme 2 as a prognostic biomarker for disease progression in patients infected with SARS-CoV-2",
     "rel_date": "2021-10-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.13.21264975",
-    "rel_abs": "BackgroundSeroprevalence studies are important tools to estimate the prevalence of prior or recent SARS-CoV-2 infections, identifying hotspots and high-risk groups and informing public health responses to the COVID-19 pandemic. We conducted a city-level seroprevalence study in Holyoke, Massachusetts, USA to estimate the seroprevalence of SARS-CoV-2 antibodies and risk factors for seropositivity.\n\nMethodsWe invited inhabitants of 2,000 randomly sampled addresses between November 5 and December 31, 2020. Participants completed questionnaires measuring sociodemographic and health characteristics, and COVID-19 exposure history, and provided dried blood spots for measurement of SARS-CoV-2 IgG and IgM antibodies. We calculate total and subgroup seroprevalence estimates based on presence of IgG antibodies using a Bayesian procedure that incorporates uncertainty in antibody test sensitivity and specificity. We account for clustering by household and weighting based on demographic characteristics to ensure estimates represented the citys population.\n\nFindingsWe enrolled 280 households including 472 individuals. 328 underwent antibody testing. The citywide seroprevalence estimate of SARS-CoV-2 IgG was 13.1% (95%CI 6.9-22.3) compared to 9.8% based on publicly reported case counts. Seroprevalence was 16.1% (95%CI 6.2-31.8) among individuals identifying as Hispanic compared to 9.4% (95%CI 4.6-16.4) among those identifying as non-Hispanic white. Seroprevalence was higher among Spanish speaking households (21.9%; 95% CI 8.3-43.9) compared to English speaking households (10.2%; 95% CI 5.2-18.0) and among individuals living in high vulnerability areas (14.4%; 95% CI 7.1-25.5) compared to low vulnerability areas (8.2%; 95% CI 3.1-16.9).\n\nInterpretationThe measured SARS-CoV-2 seroprevalence of IgG antibodies in Holyoke was only 13.1% during the second surge of SARS-CoV-2 in this region, far from accepted thresholds for \"herd immunity.\" Already vulnerable communities were at highest risk of prior infection. Implementation of local serosurveys in tandem with proactive public health interventions that address disparities in SARS-CoV-2 exposure are crucial to ensure at-risk communities have appropriate educational materials and access to vaccines, testing, and timely treatment.\n\nFundingThe Sullivan Family Foundation, Harvard Data Science Institute Bias2 program, the US Centers for Disease Control and Prevention.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.13.21264901",
+    "rel_abs": "BackgroundThere is a need for better prediction of disease severity in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Soluble angiotensin-converting enzyme 2 (sACE2) arises from shedding of membrane ACE2 (mACE2) that is known to be a receptor for the spike protein of SARS-CoV-2; however, its value as a biomarker for disease severity is unknown. This study evaluated the predictive value of sACE2 in the context of other known biomarkers of inflammation and tissue damage (C-reactive protein [CRP], growth/differentiation factor-15 [GDF-15], interleukin-6 [IL-6], and soluble fms-like tyrosine kinase-1 [sFlt-1]) in patients with and without SARS-CoV-2 with different clinical outcomes.\n\nMethodsFor univariate analyses, median differences between biomarker levels were calculated for the following patient groups classified according to clinical outcome: reverse transcription polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 positive (Groups 1-4); RT-PCR-confirmed SARS-CoV-2 negative following previous SARS-CoV-2 infection (Groups 5 and 6); and RT-PCR-confirmed SARS-CoV-2 negative controls (Group 7).\n\nResultsMedian levels of CRP, GDF-15, IL-6, and sFlt-1 were significantly higher in patients with SARS-CoV-2 who were admitted to hospital compared with patients who were discharged (all p<0.001), whereas levels of sACE2 were significantly lower (p<0.001). Receiver operating characteristic curve analysis of sACE2 provided cut-offs for the prediction of hospital admission of [&le;]0.05 ng/mL (positive predictive value: 89.1%) and [&ge;]0.42 ng/mL (negative predictive value: 84.0%).\n\nConclusionThese findings support further investigation of sACE2, either as a single biomarker or as part of a panel, to predict hospitalisation risk and disease severity in patients infected with SARS-CoV-2.\n\nHIGHLIGHTSNoelia Diaz Troyano: Noy-Lee-ah Dee-az Tro-yah-no\n\nBetter prediction of disease severity in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is needed. We measured soluble angiotensin-converting enzyme 2 (soluble ACE2) and other biomarkers of inflammation and tissue damage in patients recruited from Vall dHebron University Hospital, with and without SARS-CoV-2 and with different clinical outcomes. Levels of soluble ACE2 were significantly lower in patients with SARS-CoV-2 who had the most severe clinical outcome in all comparisons. These findings support a protective role for soluble ACE2 in SARS-CoV-2 infection and warrant further investigation of soluble ACE2 as a biomarker for disease severity in patients with SARS-CoV-2.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Wilfredo Rafael Matias",
-        "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA; Division of Infectious Diseases, Brigham and Womens Hospital, Boston, MA; Center fo"
-      },
-      {
-        "author_name": "Isabel R Fulcher",
-        "author_inst": "Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA; Harvard Data Science Initiative, Cambridge, MA"
-      },
-      {
-        "author_name": "Sara M Sauer",
-        "author_inst": "Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA"
+        "author_name": "Noelia Diaz Troyano",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Cody P Nolan",
-        "author_inst": "Department of Medicine, Brigham and Womens Hospital, Boston, MA"
-      },
-      {
-        "author_name": "Yodeline Guillaume",
-        "author_inst": "Center for Global Health, Massachusetts General Hospital, Boston, MA"
+        "author_name": "Pablo Gabriel Medina",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Jack Zhu",
-        "author_inst": "Center for Global Health, Massachusetts General Hospital, Boston, MA"
-      },
-      {
-        "author_name": "Francisco J Molano",
-        "author_inst": "Center for Global Health, Massachusetts General Hospital, Boston, MA"
-      },
-      {
-        "author_name": "Elizabeth Uceta",
-        "author_inst": "Center for Global Health, Massachusetts General Hospital, Boston, MA"
+        "author_name": "Stephen Weber",
+        "author_inst": "Roche Diagnostics GmbH"
       },
       {
-        "author_name": "Shannon Collins",
-        "author_inst": "Center for Global Health, Massachusetts General Hospital, Boston, MA"
+        "author_name": "Martin Klammer",
+        "author_inst": "Roche Diagnostics GmbH"
       },
       {
-        "author_name": "Damien M Slater",
-        "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA"
+        "author_name": "Raquel Barquin-DelPino",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Vanessa M Sanchez",
-        "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA"
+        "author_name": "Laura Castillo-Ribelles",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Serina Moheed",
-        "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA"
+        "author_name": "Angels Esteban",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Jason B Harris",
-        "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA; Department of Pediatrics, Harvard Medical School, Boston, MA"
+        "author_name": "Manuel Hern\u00e1ndez-Gonz\u00e1lez",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Richelle C Charles",
-        "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA; Department of Medicine, Harvard Medical School, Boston, MA"
+        "author_name": "Roser Ferrer-Costa",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Ryan M Paxton",
-        "author_inst": "Holyoke Board of Health, Holyoke, MA"
-      },
-      {
-        "author_name": "Sean F Gonsalves",
-        "author_inst": "Holyoke Board of Health, Holyoke, MA"
-      },
-      {
-        "author_name": "Molly F Franke",
-        "author_inst": "Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA"
+        "author_name": "Tomas Pumarola",
+        "author_inst": "Vall d'Hebron University Hospital"
       },
       {
-        "author_name": "Louise C Ivers",
-        "author_inst": "Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA; Center for Global Health, Massachusetts General Hospital, Boston, MA; Department of"
+        "author_name": "Francisco Rodriguez Frias",
+        "author_inst": "Vall d'Hebron University Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -510283,23 +512166,31 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2021.10.09.21264794",
-    "rel_title": "Covid-19 Epidemic Prediction in France: the Multimodal Case.",
+    "rel_doi": "10.1101/2021.10.11.463917",
+    "rel_title": "Secondary structure of subgenomic RNA M of SARS-CoV-2",
     "rel_date": "2021-10-12",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.09.21264794",
-    "rel_abs": "In two previous papers we have proposed models to estimate the Covid-19 epidemic when the number of daily positive cases has a bell shaped form that we call a mode. We have observed that each Covid variant produces this type of epidemic shape at a different moment, resulting in a multimodal epidemic shape. We will show in this document that each mode can still be estimated with models described in the two previous papers provides we replace the cumulated number of positive cases y by the cumulated number of positive cases reduced by a parameter P to be estimated. Therefore denoting z the logarithm of y -P, z follows approximately the differential equation [z] = b -azr where a, b, r have also to be estimated from the observed data. We will show the obtained predictions on the four French modes April, November 2020, May and September 2021. The comparison between the prediction obtained before the containment decisions made by the French government and the observed data afterwards suggests the inefficiency of the epidemic lockdowns.",
-    "rel_num_authors": 1,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.11.463917",
+    "rel_abs": "SARS-CoV-2 belongs the Coronavirinae family. As other coronaviruses, SARS-CoV-2 is enveloped and possesses positive-sense, single-stranded RNA genome of [~] 30 kb. Genome RNA is used as the template for replication and transcription. During these processes, positive-sense genomic RNA (gRNA) and subgenomic RNAs (sgRNAs) are created. Several studies showed importance of genomic RNA secondary structure in SARS-CoV-2 replication. However, the structure of sgRNAs have remained largely unsolved so far. In this study, we performed probing of sgRNA M of SARS-CoV-2 in vitro. This is the first experimentally informed secondary structure model of sgRNA M, which presents features likely to be important in sgRNA M function. The knowledge about sgRNA M provides insights to better understand virus biology and could be used for designing new therapeutics.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jean-Pierre Quadrat",
-        "author_inst": "Retired from INRIA"
+        "author_name": "Marta Soszynska-Jozwiak",
+        "author_inst": "Institute of Bioorganic Chemistry, Polish Academy of Sciences"
+      },
+      {
+        "author_name": "Ryszard Kierzek",
+        "author_inst": "Institute of Bioorganic Chemistry, Polish Academy of Sciences"
+      },
+      {
+        "author_name": "Elzbieta Kierzek",
+        "author_inst": "Institute of Bioorganic Chemistry, Polish Academy of Sciences"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "type": "new results",
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2021.10.09.463779",
@@ -512204,71 +514095,31 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.10.07.21264419",
-    "rel_title": "Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy",
+    "rel_doi": "10.1101/2021.10.08.21264749",
+    "rel_title": "Longitudinal changes in home confinement and mental health implications: A 17-month follow-up study in England during the COVID-19 pandemic",
     "rel_date": "2021-10-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.07.21264419",
-    "rel_abs": "With a dataset of testing and case counts from over 1,400 institutions of higher education (IHEs) in the United States, we analyze the number of infections and deaths from SARS-CoV-2 in the counties surrounding these IHEs during the Fall 2020 semester (August to December, 2020). We used a matching procedure designed to create groups of counties that are aligned along age, race, income, population, and urban/rural categories--socio-demographic variables that have been shown to be correlated with COVID-19 outcomes. We find that counties with IHEs that remained primarily online experienced fewer cases and deaths during the Fall 2020 semester; whereas before and after the semester, these two groups had almost identical COVID-19 incidence. Additionally, we see fewer deaths in counties with IHEs that reported conducting any on-campus testing compared to those that reported none. We complement the statistical analysis with a case study of IHEs in Massachusetts--a rich data state in our dataset--which further highlights the importance of IHE-affiliated testing for the broader community. The results in this work suggest that campus testing can itself be thought of as a mitigation policy and that allocating additional resources to IHEs to support efforts to regularly test students and staff would be beneficial to mitigating the spread of COVID-19 in the general population.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.08.21264749",
+    "rel_abs": "BackgroundThe COVID-19 pandemic has brought about significant behavioural changes, one of which is increased time spent at home. Although official lockdowns were typically short-term and allowed people to leave their homes for exercise and essential activities, some individuals did not leave their home for prolonged periods due to a range of factors including clinical vulnerability. This study aimed to explore longitudinal patterns of such  home confinement across different stages of the COVID-19 pandemic in the UK, and its associated predictors and mental health outcomes.\n\nMethodsData were from the UCL COVID -19 Social Study. The analytical sample consisted of 25,390 adults in England who were followed up for 17 months from March 2020 to July 2021. Data were analysed using growth mixture models.\n\nResultsOur analyses identified three classes of growth trajectories, including one class showing a high level of persistent home confinement (24.8%), one changing class with clear alignment with national containment policy/advice (32.0%), and one class with a persistently low level of confinement (43.1%). A range of factors were found to be associated the class membership of home confinement trajectories, such as age, gender, income, employment status, social relationships and health. The class with a high level of confinement had the highest number of depressive and anxiety symptoms at the end of the follow-up independent of potential confounders.\n\nConclusionsThere was substantial heterogeneity in longitudinal patterns of home confinement during the COVID-19 pandemic. However, a striking proportion of our sample maintained a high level of home confinement over the course of 17 months, even during periods when containment measures were eased or removed and when infection rates were low. They also had the worst mental health outcomes. This group warrants special attention in addressing the mental health impact of the COVID-19 pandemic.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Brennan Klein",
-        "author_inst": "Northeastern University Network Science Institute"
-      },
-      {
-        "author_name": "Nicholas Generous",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Matteo Chinazzi",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Zarana Bhadricha",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Rishab Gunashekar",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Preeti Kori",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Bodian Li",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Stefan McCabe",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Jon Green",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "David Lazer",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Christopher R. Marsicano",
-        "author_inst": "Davidson College"
+        "author_name": "Feifei Bu",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Samuel V. Scarpino",
-        "author_inst": "The Rockefeller Foundation Pandemic Prevention Institute"
+        "author_name": "Andrew Steptoe",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Alessandro Vespignani",
-        "author_inst": "Northeastern University"
+        "author_name": "Daisy Fancourt",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.10.07.463592",
@@ -514150,33 +516001,25 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.10.04.21264540",
-    "rel_title": "Detailed reconstruction of the Iranian COVID-19 epidemic reveals high attack rates of SARS-CoV-2 in several provinces",
+    "rel_doi": "10.1101/2021.10.06.21264645",
+    "rel_title": "A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal",
     "rel_date": "2021-10-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.04.21264540",
-    "rel_abs": "Detailed reconstruction of the SARS-CoV-2 transmission dynamics and assessment of its burden in several parts of the world has still remained largely unknown due to the scarcity of epidemiological analyses and limited testing capacities of different countries to identify cases and deaths attributable to COVID-19 [1-4]. Understanding the true burden of the Iranian COVID-19 epidemic is subject to similar challenges with limited clinical and epidemiological studies at the subnational level [5-9]. To address this, we develop a new quantitative framework that enables us to fully reconstruct the transmission dynamics across the country and assess the level of under-reporting in infections and deaths using province-level, age-stratified all-cause mortality data. We show that excess mortality aligns with seroprevalence estimates in each province and subsequently estimate that as of 2021-10-22, only 48% (95% confidence interval: 43-55%) of COVID-19 deaths in Iran have been reported. We find that in the most affected provinces such as East Azerbaijan, Qazvin, and Qom approximately 0.4% of the population have died of COVID-19 so far. We also find significant heterogeneity in the estimated attack rates across the country with 11 provinces reaching close to or higher than 100% attack rates. Despite a relatively young age structure in Iran, our analysis reveals that the infection fatality rate in most provinces is comparable to high-income countries with a larger percentage of older adults, suggesting that limited access to medical services, coupled with undercounting of COVID-19-related deaths, can have a significant impact on accurate estimation of COVID-19 fatalities. Our estimation of high attack rates in provinces with largely unmitigated epidemics whereby, on average, between 10% to 25% individuals have been infected with COVID-19 at least twice over the course of 20 months also suggests that, despite several waves of infection, herd immunity through natural infection has not been achieved in the population.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.06.21264645",
+    "rel_abs": "Montreal is the epicentre of the COVID-19 pandemic in Canada with highest number of deaths. The cumulative numbers of cases and deaths in the 33 areas of Montreal are modelled through bivariate hierarchical Bayesian models using Poisson distributions. The Poisson means are decomposed in the log scale as the sums of fixed effects and latent effects. The areal median age, the educational level, and the number of beds in long-term care homes are included in the fixed effects. To explore the correlation between cases and deaths inside and across areas, three bivariate models are considered for the latent effects, namely an independent one, a conditional autoregressive model, and one that allows for both spatially structured and unstructured sources of variability. As the inclusion of spatial effects change some of the fixed effects, we extend the Spatial+ approach to a Bayesian areal set up to investigate the presence of spatial confounding.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Mahan Ghafari",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Oliver J Watson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Ariel Karlinsky",
-        "author_inst": "Hebrew University of Jerusalem"
+        "author_name": "Victoire Michal",
+        "author_inst": "McGill University"
       },
       {
-        "author_name": "Luca Ferretti",
-        "author_inst": "Nuffield Department of Medicine"
+        "author_name": "Leo Vanciu",
+        "author_inst": "Marianapolis College"
       },
       {
-        "author_name": "Aris Katzourakis",
-        "author_inst": "University of Oxford"
+        "author_name": "Alexandra M. Schmidt",
+        "author_inst": "McGill University"
       }
     ],
     "version": "1",
@@ -516316,51 +518159,75 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.10.05.21264548",
-    "rel_title": "Feasibility and acceptability of daily testing at school as an alternative to self-isolation following close contact with a confirmed case of COVID-19: A qualitative analysis",
-    "rel_date": "2021-10-07",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.05.21264548",
-    "rel_abs": "BackgroundDaily testing using a rapid Lateral Flow Device (LFD) has been suggested as an alternative to self-isolation. A randomised trial comparing daily contact testing (DCT) in schools with self-isolation found that SARS-CoV-2 transmission within school was comparable and low in both groups. However, if this approach is to be adopted widely, it is critical that we understand the perspective of those who will be delivering and receiving DCT. The aim of this qualitative process study embedded in the randomised controlled trial (RCT) was to improve understanding of a range of behavioural factors that could influence implementation.\n\nMethodsInterviews were conducted with 63 participants, including staff, students, and parents of students who had been identified as being in close contact with someone with COVID-19. The topic guide explored perceptions of daily testing, understanding of positive and negative test results, and adherence to guidance. Data were analysed using an inductive thematic approach.\n\nResultsResults were organised under three main headings: (1) factors influencing daily testing (2) interpretation of test results (3) behaviour during testing period. Participants recognized that daily testing may allow students to remain in school, which was viewed as necessary for both education and social needs. Whilst some felt safer as a result of daily testing, others raised concerns about safety. Participants did not always understand how to interpret and respond to test results, and although participants reported high levels of adherence to the guidance, improved communications were desired.\n\nConclusionDaily testing may be a feasible and acceptable alternative to self-isolation among close contacts of people who test positive. However, improved communications are needed to ensure that all students and parents have a good understanding of the rationale for testing, what test results mean, how test results should be acted on, and how likely students are to test positive following close contact. Support is needed for students and parents of students who have to self-isolate and for those who have concerns about the safety of daily testing.",
-    "rel_num_authors": 8,
+    "rel_doi": "10.1101/2021.10.05.463205",
+    "rel_title": "SARS-CoV-2 causes human BBB injury and neuroinflammation indirectly in a linked organ chip platform",
+    "rel_date": "2021-10-06",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.05.463205",
+    "rel_abs": "COVID-19 is a multi-system disease affecting many organs outside of the lungs, and patients generally develop varying degrees of neurological symptoms. Whereas, the pathogenesis underlying these neurological manifestations remains elusive. Although in vitro models and animal models are widely used in studies of SARS-CoV-2 infection, human organ models that can reflect the pathological alterations in a multi-organ context are still lacking. In this study, we propose a new strategy to probe the effects of SARS-CoV-2 on human brains in a linked alveolus-BBB organ chip platform. The new multi-organ platform allows to recapitulate the essential features of human alveolar-capillary barrier and blood-brain barrier in a microfluidic condition by co-culturing the organ-specific cells. The results reveal direct SARS-CoV-2 exposure has no obvious effects on BBB chip alone. While, infusion of endothelial medium from infected alveolus chips can cause BBB dysfunction and neuroinflammation on the linked chip platform, including brain endothelium disruption, glial cell activation and inflammatory cytokines release. These new findings suggest that SARS-CoV-2 could induce neuropathological alterations, which might not result from direct viral infection through hematogenous route, but rather likely from systemic inflammation following lung infection. This work provides a new strategy to study the virus-host interaction and neuropathology at an organ-organ context, which is not easily obtained by other in vitro models. This will facilitate to understand the neurological pathogenesis in SARS-CoV-2 and accelerate the development of new therapeutics.\n\nSUMMARYO_LIA linked human alveolus-BBB chip platform is established to explore the influences of SARS-CoV-2 on human brains in an organ-organ context.\nC_LIO_LISARS-CoV-2 infection could induce BBB injury and neuroinflammation.\nC_LIO_LIThe neuropathological changes are caused by SARS-CoV-2 indirectly, which might be mediated by systemic inflammation following lung infection, but probably not by direct viral neuroinvasion.\nC_LI",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Sarah Denford",
-        "author_inst": "University of Bristol"
+        "author_name": "Peng Wang",
+        "author_inst": "Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China"
       },
       {
-        "author_name": "Lauren Towler",
-        "author_inst": "University of Southampton"
+        "author_name": "Lin Jin",
+        "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences, , Kunming Institute of Zoology, Chinese Academy of Sciences, Kunmin"
       },
       {
-        "author_name": "Behiye Ali",
-        "author_inst": "University of Bristol"
+        "author_name": "Min Zhang",
+        "author_inst": "Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China"
       },
       {
-        "author_name": "Georgia Treneman-Evans",
-        "author_inst": "University of Bristol"
+        "author_name": "Yunsong Wu",
+        "author_inst": "Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China"
       },
       {
-        "author_name": "Rachael Bloomer",
-        "author_inst": "University of Bristol"
+        "author_name": "Zilei Duan",
+        "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences, , Kunming Institute of Zoology, Chinese Academy of Sciences, Kunmin"
       },
       {
-        "author_name": "Tim E Peto",
-        "author_inst": "oxford university"
+        "author_name": "Wenwen Chen",
+        "author_inst": "Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China"
       },
       {
-        "author_name": "Bernadette C Young",
-        "author_inst": "University of Oxford"
+        "author_name": "Chaoming Wang",
+        "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences, , Kunming Institute of Zoology, Chinese Academy of Sciences, Kunmin"
       },
       {
-        "author_name": "Lucy Yardley",
-        "author_inst": "University of Bristol"
+        "author_name": "Zhiyi Liao",
+        "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences, , Kunming Institute of Zoology, Chinese Academy of Sciences, Kunmin"
+      },
+      {
+        "author_name": "Jianbao Han",
+        "author_inst": "Kunming National High-level Bio-safety Research Center for Non-human Primates, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy "
+      },
+      {
+        "author_name": "Yingqi Guo",
+        "author_inst": "Core Technology Facility of Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, Yunnan, China"
+      },
+      {
+        "author_name": "Yaqiong Guo",
+        "author_inst": "Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China"
+      },
+      {
+        "author_name": "Yaqing Wang",
+        "author_inst": "Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China"
+      },
+      {
+        "author_name": "Ren Lai",
+        "author_inst": "Kunming Institute of Zoology, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Jianhua Qin",
+        "author_inst": "Dalian Insititute of Chemistry Physics, Chinese Academy of Sciences"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "bioengineering"
   },
   {
     "rel_doi": "10.1101/2021.10.05.463008",
@@ -518690,115 +520557,31 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.10.02.21264210",
-    "rel_title": "SARS-CoV-2 multi-variant graphene biosensor based on engineered dimeric ACE2 receptor",
+    "rel_doi": "10.1101/2021.10.01.452232",
+    "rel_title": "Characterization and Structural Prediction of ORF10, ORF7b, ORF7a, ORF6, Membrane Glycoprotein, and Envelope Protein in SARS-CoV-2 Bangladeshi Variant through Bioinformatics Approach",
     "rel_date": "2021-10-04",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.02.21264210",
-    "rel_abs": "Fast, reliable and point-of-care systems to detect the SARS-CoV-2 infection are crucial to contain viral spreading and to adopt timely clinical treatments. Many of the rapid detection tests currently in use are based on antibodies that bind viral proteins1. However, newly appearing virus variants accumulate mutations in their RNA sequence and produce proteins, such as Spike, that may show reduced binding affinity to these diagnostic antibodies, resulting in less reliable tests and in the need for continuous update of the sensing systems2. Here we propose a graphene field-effect transistor (gFET) biosensor which exploits the key interaction between the Spike protein and the human ACE2 receptor. This interaction is one of the determinants of host infections and indeed recently evolved Spike variants were shown to increase affinity for ACE2 receptor3. Through extensive computational analyses we show that a chimeric ACE2-Fc construct mimics the ACE2 dimer, normally present on host cells membranes, better than its soluble truncated form. We demonstrate that ACE2-Fc functionalized gFET is effective for in vitro detection of Spike and outperforms the same chip functionalized with either a diagnostic antibody or the soluble ACE2. Our sensor is implemented in a portable, wireless, point-of-care device and successfully detected both alpha and gamma virus variants in patients clinical samples. As incomplete immunization, due to vaccine roll-out, may offer new selective grounds for antibody-escaping virus variants4, our biosensor opens to a class of highly sensitive, rapid and variant-robust SARS-CoV-2 detection systems.",
-    "rel_num_authors": 24,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.01.452232",
+    "rel_abs": "The acute respiratory disease induced by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has become a global epidemic in just less than a year by the first half of 2020. The subsequent efficient human-to-human transmission of this virus eventually affected millions of people worldwide. The most devastating thing is that the infection rate is continuously uprising and resulting in significant mortality especially among the older age population and those with health co-morbidities. This enveloped, positive-sense RNA virus is chiefly responsible for the infection of the upper respiratory system. The virulence of the SARS-CoV-2 is mostly regulated by its proteins like entry to the host cell through fusion mechanism, fusion of infected cells with neighboring uninfected cells to spread the virus, inhibition of host gene expression, cellular differentiation, apoptosis, mitochondrial biogenesis, etc. But very little is known about the protein structures and functionalities. Therefore, the main purpose of this study is to learn more about these proteins through bioinformatics approaches. In this study, ORF10, ORF7b, ORF7a, ORF6, membrane glycoprotein, and envelope protein have been selected from a Bangladeshi Corona-virus strain G039392 and a number of bioinformatics tools (MEGA-X-V10.1.7, PONDR(R), ProtScale, ProtParam, SCRIBER, NetSurfP v2.0, IntFOLD, UCSF Chimera, and PyMol) and strategies were implemented for multiple sequence alignment and phylogeny analysis with 9 different variants, predicting hydropathicity, amino acid compositions, protein-binding propensity, protein disorders, 2D and 3D protein modeling. Selected proteins were characterized as highly flexible, structurally and electrostatically extremely stable, ordered, biologically active, hydrophobic, and closely related to the proteins of different variants. This detailed information regarding the characterization and structure of proteins of SARS-CoV-2 Bangladeshi variant was performed for the first time ever to unveil the deep mechanism behind the virulence features and also, this robust appraisal paves the future way for molecular docking, vaccine development targeting these characterized proteins.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Mattia D'Agostino",
-        "author_inst": "Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Eleonora Pavoni",
-        "author_inst": "Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Alice Romagnoli",
-        "author_inst": "Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy. New York-Marche Structural Biology Ce"
+        "author_name": "Pinky Debnath",
+        "author_inst": "Research Assistant, Chemical Biotechnology Department, Technical University of Munich , Schuigasse 22, D 94315 Straubing , Germany"
       },
       {
-        "author_name": "Chiara Ardiccioni",
-        "author_inst": "Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy. New York-Marche Structural Biology Ce"
+        "author_name": "Umama Khan",
+        "author_inst": "Research Assistant, Biotechnology and Genetic Engineering Discipline, Khulna University, Khulna 9208, Bangladesh."
       },
       {
-        "author_name": "Stefano Motta",
-        "author_inst": "Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy."
-      },
-      {
-        "author_name": "Paolo Crippa",
-        "author_inst": "Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Giorgio Biagetti",
-        "author_inst": "Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Valentina Notarstefano",
-        "author_inst": "Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Simone Barocci",
-        "author_inst": "Department of Clinical Pathology, ASUR Marche AV1, Urbino, PU, Italy."
-      },
-      {
-        "author_name": "Brianna K Costabile",
-        "author_inst": "Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, 10032, USA."
-      },
-      {
-        "author_name": "Gabriele Colasurdo",
-        "author_inst": "OMME GEARS, Falconara M.am, Zona Ind. CIAF, 60015, Ancona, Italy."
-      },
-      {
-        "author_name": "Sara Caucci",
-        "author_inst": "Virology Unit, Department of Biomedical Sciences and Public Health, Polytechnic University of Marche, Torrette, 60126 Ancona, Italy."
-      },
-      {
-        "author_name": "Davide Mencarelli",
-        "author_inst": "Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Claudio Turchetti",
-        "author_inst": "Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Marco Farina",
-        "author_inst": "Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Luca Pierantoni",
-        "author_inst": "Department of Information Engineering, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Anna La Teana",
-        "author_inst": "Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy. New York-Marche Structural Biology Ce"
-      },
-      {
-        "author_name": "Richard Al Hadi",
-        "author_inst": "Alcatera Inc, Los Angeles, CA 90024, USA."
-      },
-      {
-        "author_name": "Mauro Chinappi",
-        "author_inst": "Department of Industrial Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy."
-      },
-      {
-        "author_name": "Emiliano Trucchi",
-        "author_inst": "Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy."
-      },
-      {
-        "author_name": "Filippo Mancia",
-        "author_inst": "Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, 10032, USA."
-      },
-      {
-        "author_name": "Blasco Morozzo della Rocca",
-        "author_inst": "Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica 1, 00133 Rome, Italy."
-      },
-      {
-        "author_name": "Ilda D'Annessa",
-        "author_inst": "Institute of Chemical Science and Technologies, SCITEC-CNR, Via Mario Bianco 9, 20131, Milan, Italy."
-      },
-      {
-        "author_name": "Daniele Di Marino",
-        "author_inst": "Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, 60131, Ancona, Italy. New York-Marche Structural Biology Ce"
+        "author_name": "Md. Salauddin Khan",
+        "author_inst": "Assistant Professor, Statistics Discipline, Khulna University, Khulna 9208, Bangladesh"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.10.01.462821",
@@ -520360,71 +522143,127 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.10.01.21264412",
-    "rel_title": "Initial SARS-CoV-2 viral load is associated with disease severity: a retrospective cohort study",
+    "rel_doi": "10.1101/2021.10.01.21264428",
+    "rel_title": "Risk factors for infection, predictors of severe disease and antibody response to COVID-19 in patients with rheumatic diseases in Portugal - a multicentre, nationwide study",
     "rel_date": "2021-10-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.01.21264412",
-    "rel_abs": "BackgroundWe aimed to assess the association between initial SARS-CoV-2 viral load and the subsequent hospital and intensive care unit (ICU) admission and overall survival.\n\nMethodsAll persons with a positive SARS-CoV-2 RT-PCR result from a combined nasopharyngeal (NP) and oropharyngeal (OP) swab (first samples from unique persons only) that was collected between March 17, 2020, and March 31, 2021, in Public Health testing facilities in the region Kennemerland, province of North Holland, the Netherlands were included. Data on hospital (and ICU) admission were collected from the two large teaching hospitals in the region Kennemerland.\n\nResultsIn total, 20,207 SARS-CoV-2 positive persons were included in this study, of whom 310 (1.5%) were hospitalized in a regional hospital within 30 days of their positive SARS-CoV-2 RT-PCR test. When persons were categorized in three SARS-CoV-2 viral load groups, the high viral load group (Cp < 25) was associated with an increased risk of hospitalization as compared to the low viral load group (Cp > 30) (ORadjusted [95%CI]: 1.57 [1.11-2.26], p-value=0.012), adjusted for age and sex. The same association was seen for ICU admission (ORadjusted [95%CI]: 7.06 [2.15-43.57], p-value=0.007). For a subset of 243 of the 310 hospitalized patients, the association of initial SARS-CoV-2 Cp-value with in-hospital mortality was analyzed. The initial SARS-CoV-2 Cp-value of the 17 patients who deceased in the hospital was significantly lower (indicating a higher viral load) compared to the 226 survivors: median Cp-value [IQR]: 22.7 [3.4] vs. 25.0 [5.2], OR[95%CI]: 0.81 [0.68-0.94], p-value = 0.010.\n\nConclusionsOur data show that higher initial SARS-CoV-2 viral load is associated with an increased risk of hospital admission, ICU admission, and in-hospital mortality. We believe that our findings emphasize the added value of reporting SARS-CoV-2 viral load based on Cp-values to identify persons who are at the highest risk of adverse outcomes such as hospital or ICU admission and who therefore may benefit from more intensive monitoring.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.01.21264428",
+    "rel_abs": "In order to identify risk factors for SARS-CoV-2 infection as well as for severe/critical COVID-19 in rheumatic and musculoskeletal diseases (RMDs) patients, we conducted a multicentre observational nationwide study of adult patients prospectively-followed in the Rheumatic Diseases Portuguese Register - Reuma.pt - during the first 6 months of the pandemic. We further evaluated the development of IgG antibodies against the receptor-binding domain (RBD) of SARS-CoV-2 in patients with RMDs. We used multivariate logistic regression to compare patients with COVID-19 (COVID-19+) with those who did not develop the disease (COVID-19-) and patients with mild/moderate disease with those exhibiting severe/critical COVID-19. COVID-19+ patients were asked to collect a blood sample for IgG testing [&ge;] 3 months after infection and results were compared with age-, sex- and sampling date-matched controls. Overall, 179 cases of COVID-19 were registered in Reuma.pt in the period of interest (median age 55 (IQR 20); 76.5% females) in a total of 6404 registered appointments. We found that patients treated with TNF inhibitors had reduced odds of infection (OR=0.16, 95%CI 0.10-0.26, p<0.001), severe disease (OR 0.11, 95%CI 0.01-0.84, p=0.010) and seroconversion rates (OR 0.13, 95%CI 0.02-0.91, p=0.040). Tocilizumab was also associated with a reduced risk of COVID-19 (OR 0.15, 95%CI 0.05-0.41, p<0.001). Older age, major comorbidities (diabetes, hypertension, obesity, cardiovascular disease, chronic pulmonary and kidney disease) and rituximab were associated with an increased risk of infection and worse prognosis, in line with previous reports. Importantly, most patients with inflammatory RMDs (86.2%) were able to develop a robust antibody response after SARS-CoV-2 infection, which was linked with disease severity.",
+    "rel_num_authors": 27,
     "rel_authors": [
       {
-        "author_name": "Dennis Souverein",
-        "author_inst": "Regional Public Health Laboratory Kennemerland"
+        "author_name": "Ana Rita Cruz-Machado",
+        "author_inst": "Rheumatology Department, Hospital de Santa Maria, Centro Hospitalar Universitario Lisboa Norte, Lisbon Academic Medical Center and European Reference Network on"
       },
       {
-        "author_name": "Karlijn van Stralen",
-        "author_inst": "Spaarne Gasthuis"
+        "author_name": "Sofia C. Barreira",
+        "author_inst": "Rheumatology Department, Hospital de Santa Maria, Centro Hospitalar Universitario Lisboa Norte, Lisbon Academic Medical Center and European Reference Network on"
       },
       {
-        "author_name": "Steven van Lelyveld",
-        "author_inst": "Spaarne Gasthuis"
+        "author_name": "Matilde Bandeira",
+        "author_inst": "Rheumatology Department, Hospital de Santa Maria, Centro Hospitalar Universitario Lisboa Norte, Lisbon Academic Medical Center and European Reference Network on"
       },
       {
-        "author_name": "Claudia van Gemeren",
-        "author_inst": "Spaarne Gasthuis"
+        "author_name": "Marc Veldhoen",
+        "author_inst": "Instituto de Medicina Molecular Joao Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal."
       },
       {
-        "author_name": "Milly Haverkort",
-        "author_inst": "Public Health Service Kennemerland"
+        "author_name": "Andreia Gomes",
+        "author_inst": "Instituto de Medicina Molecular Joao Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal."
       },
       {
-        "author_name": "Dominic Snijders",
-        "author_inst": "Spaarne Gasthuis"
+        "author_name": "Marta Serrano",
+        "author_inst": "Instituto de Medicina Molecular Joao Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal."
       },
       {
-        "author_name": "Robin Soetekouw",
-        "author_inst": "Spaarne Gasthuis"
+        "author_name": "Catarina Duarte",
+        "author_inst": "Rheumatology Department, Hospital de Santa Maria, Centro Hospitalar Universitario Lisboa Norte, Lisbon Academic Medical Center and European Reference Network on"
       },
       {
-        "author_name": "Erik Kapteijns",
-        "author_inst": "Rode Kruis Ziekenhuis"
+        "author_name": "Maria Rato",
+        "author_inst": "Rheumatology Department, Centro Hospitalar Universitario de Sao Joao EPE, Porto, Portugal."
       },
       {
-        "author_name": "Evelien de Jong",
-        "author_inst": "Rode Kruis Ziekenhuis"
+        "author_name": "Bruno Miguel Fernandes",
+        "author_inst": "Rheumatology Department, Centro Hospitalar Universitario de Sao Joao EPE, Porto, Portugal."
       },
       {
-        "author_name": "Gonneke Hermanides",
-        "author_inst": "Rode Kruis Ziekenhuis"
+        "author_name": "Salom\u00e9 Garcia",
+        "author_inst": "Rheumatology Department, Centro Hospitalar Universitario de Sao Joao EPE, Porto, Portugal."
       },
       {
-        "author_name": "Sem Aronson",
-        "author_inst": "Spaarne Gasthuis"
+        "author_name": "Filipe Pinheiro",
+        "author_inst": "Rheumatology Department, Centro Hospitalar Universitario de Sao Joao EPE, Porto, Portugal."
       },
       {
-        "author_name": "Alex Wagemakers",
-        "author_inst": "Regional Public Health Laboratory Kennemerland"
+        "author_name": "Miguel Bernardes",
+        "author_inst": "Rheumatology Department, Centro Hospitalar Universitario de Sao Joao EPE, Porto, Portugal."
       },
       {
-        "author_name": "Sjoerd Euser",
-        "author_inst": "Regional Public Health Laboratory Kennemerland"
+        "author_name": "Nathalie Madeira",
+        "author_inst": "Rheumatology Department, Instituto Portugues de Reumatologia, Lisbon, Portugal."
+      },
+      {
+        "author_name": "Cl\u00e1udia Miguel",
+        "author_inst": "Rheumatology Department, Instituto Portugues de Reumatologia, Lisbon, Portugal."
+      },
+      {
+        "author_name": "Rita Torres",
+        "author_inst": "Rheumatology Department, Hospital de Egas Moniz, Centro Hospitalar Lisboa Ocidental, Lisbon, Portugal."
+      },
+      {
+        "author_name": "Ana Bento Silva",
+        "author_inst": "Rheumatology Department, Hospital de Egas Moniz, Centro Hospitalar Lisboa Ocidental, Lisbon, Portugal."
+      },
+      {
+        "author_name": "Jorge Pestana",
+        "author_inst": "Rheumatology Department, Hospital Garcia de Orta, Almada, Portugal."
+      },
+      {
+        "author_name": "Diogo Almeida",
+        "author_inst": "Rheumatology Department, Hospital de Braga, Braga, Portugal."
+      },
+      {
+        "author_name": "Carolina Mazeda",
+        "author_inst": "Rheumatology Department, Centro Hospitalar do Baixo Vouga and Ibimed, Institute for Biomedicine, University of Aveiro, Aveiro, Portugal."
+      },
+      {
+        "author_name": "Filipe Cunha Santos",
+        "author_inst": "Rheumatology Department, Local Health Unit of Guarda, Guarda, Portugal."
+      },
+      {
+        "author_name": "Patr\u00edcia Pinto",
+        "author_inst": "Rheumatology Department, Centro Hospitalar de Vila Nova de Gaia/Espinho, Gaia, Portugal."
+      },
+      {
+        "author_name": "Marlene Sousa",
+        "author_inst": "Rheumatology Department, Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal."
+      },
+      {
+        "author_name": "Hugo Parente",
+        "author_inst": "Rheumatology Department, Unidade Local de Saude do Alto Minho, Ponte de Lima, Portugal."
+      },
+      {
+        "author_name": "Gra\u00e7a Sequeira",
+        "author_inst": "Rheumatology Department, Centro Hospitalar Universitario do Algarve, Faro, Portugal."
+      },
+      {
+        "author_name": "Maria Jos\u00e9 Santos",
+        "author_inst": "Rheumatology Department, Hospital Garcia de Orta, Almada, Portugal."
+      },
+      {
+        "author_name": "Jo\u00e3o Eurico Fonseca",
+        "author_inst": "Rheumatology Department, Hospital de Santa Maria, Centro Hospitalar Universitario Lisboa Norte, Lisbon Academic Medical Center and European Reference Network on"
+      },
+      {
+        "author_name": "Vasco C. Rom\u00e3o",
+        "author_inst": "Rheumatology Department, Hospital de Santa Maria, Centro Hospitalar Universitario Lisboa Norte, Lisbon Academic Medical Center and European Reference Network on"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "rheumatology"
   },
   {
     "rel_doi": "10.1101/2021.09.29.21263145",
@@ -522026,55 +523865,75 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.10.01.21264382",
-    "rel_title": "COVID-19 Pandemic Response in a Migrant Farmworker Community: Excess Mortality, Testing Access and Contact Tracing in Immokalee, Florida",
+    "rel_doi": "10.1101/2021.10.01.462460",
+    "rel_title": "ZBP1 induces inflammatory signaling via RIPK3 and promotes SARS-CoV-2-induced cytokine expression",
     "rel_date": "2021-10-01",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.01.21264382",
-    "rel_abs": "IntroductionWe aim to estimate the impact of COVID-19 in Immokalee, FL and assess community experiences with workplace conditions, access to testing, sources of information, and contact tracing to inform and strengthen local public health sector efforts in reaching and providing high-quality care to the community.\n\nMethodsWe conducted a descriptive analysis of data on COVID-19 deaths for Collier County from May-August 2020. We surveyed a cross-sectional, randomized representative sample of 318 adults living in Immokalee from March-November 2020 to assess socio-demographics, sources of information, ability to follow guidelines, and experiences with local programs. Results were compared across language groups.\n\nResultsAverage excess mortality in Collier County was 108%. The majority surveyed in Immokalee had socio-demographic factors associated with higher COVID risk. Non-English speakers had higher workplace risk due to less ability to work from home. Haitian Creole speakers were less likely to be tested, though all participants were willing to get symptomatic testing and quarantine. Those participants who tested positive or had COVID-19 exposures had low engagement with the contact tracing program, and Spanish-speakers reported lower quality of contact tracing than English speakers.\n\nConclusionsThe community of Immokalee, FL is a vulnerable population that suffered disproportionate deaths from COVID-19. This study reveals language inequities in COVID testing and contact tracing should be targeted in future pandemic response in Immokalee and other migrant farmworker communities.",
-    "rel_num_authors": 9,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.01.462460",
+    "rel_abs": "COVID-19 caused by the SARS-CoV-2 virus remains a threat to global health. The disease severity is mediated by cell death and inflammation, which regulate both the antiviral and the pathological innate immune responses. ZBP1, an interferon-induced cytosolic nucleic acid sensor, facilitates antiviral responses via RIPK3. Although ZBP1-mediated cell death is widely described, whether and how it promotes inflammatory signaling is unclear. Here, we report a ZBP1-induced inflammatory signaling pathway that depends on ubiquitination and RIPK3s scaffolding ability independently of cell death. In human cells, ZBP1 associates with RIPK1 and RIPK3 as well as ubiquitin ligases cIAP1 and LUBAC. RIPK1 and ZBP1 are ubiquitinated to promote TAK1- and IKK-mediated inflammatory signaling. Additionally, RIPK1 recruits the p43/41-caspase-8-p43-FLIP heterodimer to suppress RIPK3 kinase activity, which otherwise promotes inflammatory signaling in a kinase activity-dependent manner. Lastly, we show that ZBP1 contributes to SARS-CoV-2-induced cytokine production. Taken together, we describe a ZBP1-RIPK1-RIPK3-mediated inflammatory signaling pathway relayed by the scaffolding role of RIPKs and regulated by caspase-8. Our results suggest the ZBP1 pathway contributes to inflammation in response to SARS-CoV-2 infection.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Neha Limaye",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Ruoshi Peng",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Brennan Ninesling",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Xuan Wang-Kan",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Frantzso Marcelin",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Manja Idorn",
+        "author_inst": "Aarhus University"
       },
       {
-        "author_name": "Cody Nolan",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Felix Y Zhou",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Walter Sobba",
-        "author_inst": "NYU Grossman School of Medicine"
+        "author_name": "Susana L Orozco",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Matthew Hing",
-        "author_inst": "David Geffen School of Medicine at UCLA"
+        "author_name": "Julia McCarthy",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Emily Ptaszek",
-        "author_inst": "Healthcare Network of Southwest Florida"
+        "author_name": "Carol S Leung",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Fernet Leandre",
-        "author_inst": "Partners in Health"
+        "author_name": "Xin Lu",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Daniel Palazuelos",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Katrin Bagola",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Jan Rehwinkel",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Andrew Oberst",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "Jonathan Maelfait",
+        "author_inst": "VIB-Ugent IRC"
+      },
+      {
+        "author_name": "Soren R. Paludan",
+        "author_inst": "Aarhus University"
+      },
+      {
+        "author_name": "Mads Gyrd-Hansen",
+        "author_inst": "University of Copenhagen"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "license": "cc_by",
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.09.30.462687",
@@ -524268,27 +526127,23 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.09.27.21264174",
-    "rel_title": "Counter-intuitive COVID-19 Trajectories - Explanations, Early Warning Indicator and Mitigation Strategies",
+    "rel_doi": "10.1101/2021.09.29.21264261",
+    "rel_title": "World Science against COVID-19: Gender and Geographical Distribution of Research.",
     "rel_date": "2021-09-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264174",
-    "rel_abs": "The COVID-19 trajectories worldwide have shown several surprising features which are outside the purview of classical epidemiological models. These include (a) almost constant and low daily case rates over extended periods of time, (b) sudden waves emerging from the above solution despite no or minimal change in the level of non-pharmaceutical interventions (NPI), and (c) reduction or flattening of case counts even after relaxation of NPI. To explain these phenomena, we add contact tracing to our recently developed cluster seeding and transmission (CST) model, which is predicated on heterogeneous rather than homogeneous mixing of people in society. With this addition, we find no fewer than four effects which make prediction of epidemic trajectories uncertain. These are (a) cryptogenic instability, where a small increase in population-averaged contact rate causes a large increase in cases, (b) critical mass effect, where a wave can manifest after weeks of quiescence with no change in parameter values, (c) knife-edge effect, where a small change in parameter across a critical value can cause a huge change in the response of the system, and (d) hysteresis effect, where the timing and not just the strength of a particular NPI determines the subsequent evolution of the epidemic. Despite these effects however, it is a robust conclusion that a good contact tracing program can effectively substitute for much more invasive measures. We further find that the contact tracing capacity ratio - a metric of the stress to which the tracers are subject - can act as a reliable early warning indicator of an imminent epidemic wave. Extensive simulations demonstrate that whenever there is a drop in capacity ratio during a period of low daily infections, there is a very high probability of the case counts rising significantly in the immediate future.\n\nAuthor summaryClose to two years into the pandemic, the trajectories of COVID-19 in different places and at different times have shown wild variations and confounded modeling and forecasting efforts. Our new mathematical model can help to explain these variations. Some solutions of our model are non-standard but realistic. For example, we find an epidemic curve where daily cases remain on a plateau for a long time before suddenly exploding into a wave, despite interventions remaining constant throughout. We also find solutions showing that a specific intervention, for example capacity reduction at public gatherings, is very effective if implemented early on in a wave but useless if implemented a little later. Our proposed early warning indicator can be a game-changer for epidemic forecasting and model-based intervention strategies. Current forecasting algorithms have the weakest performance at the inflection points where there is an abrupt change in trend in the daily infection rates. The early warning indicator can give us advance notice of an approaching inflection point, and enable the authorities to take preventive measures before a wave actually arrives. Our results indicate that close communication between contact tracing personnel and public health authorities can achieve synergistic mitigation of the pandemic.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.29.21264261",
+    "rel_abs": "In just a year and a half, an enormous volume of scientific research has been generated throughout the world to study a virus/disease that turned into a pandemic. All the articles on COVID-19 or SARS-CoV-2 included in the SCI-EXPANDED database (Web of Science), signed by more than a third of a million of authorships, were analyzed. Gender could be identified in 92% of the authorships. Women represent 40% of all authors, a similar proportion as first authors, but just 30% as last/senior authors. The pattern of collaboration shows an interesting finding: when a woman signs as a first or last/senior author, the article byline approximates gender parity\n\nAccording to the corresponding address, the USA shares 22.8% of all world articles, followed by China (14.4%), Italy (7.8%), the UK (5.8%), India (4.2%), Spain (3.8%), Germany (3.6%), France (2.9%), Turkey (2.5%), and Canada (2.4%).\n\nDespite their short lives, the papers received an average of 11 citations. The high impact of papers from China is striking (25.1 citations; the UK, 12.4 citations; the USA, 11.3 citations), presumably because the disease emerged in China, and the first publications (very cited) came from there.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "B Shayak",
-        "author_inst": "Cornell University"
-      },
-      {
-        "author_name": "Mohit Manoj Sharma",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "JULIO GONZALEZ-ALVAREZ Sr.",
+        "author_inst": "UNIVERSITY JAUME I"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.09.27.21264211",
@@ -526414,27 +528269,23 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.09.27.21264044",
-    "rel_title": "Sub-Saharan African Countries' COVID-19 Research: An analysis of the External and Internal Contributions, Collaboration Patterns and Funding Sources",
+    "rel_doi": "10.1101/2021.09.27.21264130",
+    "rel_title": "Effectiveness of the mRNA BNT162b2 vaccine against SARS-CoV-2 severe infections in the Israeli over 60 population: a temporal analysis done by using the national surveillance data.",
     "rel_date": "2021-09-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264044",
-    "rel_abs": "This study aims at providing some evidence-based insight into Sub-Saharan Africas first eighteen months of COVID-19 research by evaluating its research contributions, patterns of collaboration, and funding sources. Eighteen months (2020 January 1-2021 June 30) COVID-19 publication data of 46 Sub-Saharan African countries was collected from Scopus for analysis. Country of affiliation of the authors and funding agencies data was analyzed to understand country contributions, collaboration pattern and funding sources. USA (23.08%) and the UK (19.63%), the top two external contributors, collaborated with Sub-Saharan African countries about three times more than other countries. Collaborative papers between Sub-Saharan African countries - without contributions from outside the region-made up less than five percent of the sample, whereas over 50% of the papers were written in collaboration with researchers from outside the region. Organizations that are in USA and the UK funded 45% of all the COVID-19 research from Sub-Saharan Africa. 53.44% of all the funding from Sub-Saharan African countries came from South African organizations. This study provides evidence that pan-African COVID-19 research collaboration is low, perhaps due to poor funding and lack of institutional support within Sub-Saharan Africa. This mirrors the collaborative features of science in Sub-Saharan Africa before the COVID-19 pandemic. The high volume of international collaboration during the pandemic is a good development. There is also a strong need to forge more robust pan-African research collaboration networks, through funding from Africas national and regional government organizations, with the specific objective of meeting local COVID-19 and other healthcare needs.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.27.21264130",
+    "rel_abs": "Last August, when the delta variant became the dominant infection strain, Israel, one of the countries with the highest levels of vaccination in the world, faced a scary pandemic wave. The frighteningly increasing number of infections was seen as the perfect storm to test the effectiveness of the mRNA BNT162b2 vaccine. The new surge forced the government to use a booster shot to protect the most vulnerable age groups. Starting from the August national surveillance data, we analysed the temporal effectiveness of vaccination against severe infections in the Israeli over 60 population. The study shows that the two-dose vaccine still works in preventing people from getting seriously sick but not with the same effectiveness observed in the first months of 2021. However, the observed temporal increase of the vaccine effectiveness in Israel, during August, suggests a correlation with the increase of the population protected by the booster shot.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Toluwase Victor Asubiaro",
-        "author_inst": "University of Western Ontario"
-      },
-      {
-        "author_name": "Hafsah Shaik",
-        "author_inst": "Independent Researcher"
+        "author_name": "Stefano De Leo",
+        "author_inst": "State University of Campinas"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.09.21.21263825",
@@ -527968,35 +529819,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.09.25.21264082",
-    "rel_title": "Contact surveys reveal heterogeneities in age-group contributions to SARS-CoV-2 dynamics in the United States",
+    "rel_doi": "10.1101/2021.09.26.21264145",
+    "rel_title": "Racial and ethnic inequalities in COVID-19 mortality within carceral settings: An analysis of Texas prisons and jails",
     "rel_date": "2021-09-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.25.21264082",
-    "rel_abs": "SARS-CoV-2 is spread primarily through person-to-person contacts. Quantifying population contact rates is important for understanding the impact of physical distancing policies and for modeling COVID-19, but contact patterns have changed substantially over time due to shifting policies and behaviors. There are surprisingly few empirical estimates of age-structured contact rates in the United States both before and throughout the COVID-19 pandemic that capture these changes. Here, we use data from six waves of the Berkeley Interpersonal Contact Survey (BICS), which collected detailed contact data between March 22, 2020 and February 15, 2021 across six metropolitan designated market areas (DMA) in the United States. Contact rates were low across all six DMAs at the start of the pandemic. We find steady increases in the mean and median number of contacts across these localities over time, as well as a greater proportion of respondents reporting a high number of contacts. We also find that young adults between ages 18 and 34 reported more contacts on average compared to other age groups. The 65 and older age group consistently reported low levels of contact throughout the study period. To understand the impact of these changing contact patterns, we simulate COVID-19 dynamics in each DMA using an age-structured mechanistic model. We compare results from models that use BICS contact rate estimates versus commonly used alternative contact rate sources. We find that simulations parameterized with BICS estimates give insight into time-varying changes in relative incidence by age group that are not captured in the absence of these frequently updated estimates. We also find that simulation results based on BICS estimates closely match observed data on the age distribution of cases, and changes in these distributions over time. Together these findings highlight the role of different age groups in driving and sustaining SARS-CoV-2 transmission in the U.S. We also show the utility of repeated contact surveys in revealing heterogeneities in the epidemiology of COVID-19 across localities in the United States.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.26.21264145",
+    "rel_abs": "Several analyses have highlighted racial and ethnic disparities related to COVID-19 health outcomes across the United States. Less focus has been placed on more localized contexts, such as carceral settings, where racial and ethnic inequities in COVID-19 health outcomes also exist, but the proximal drivers of inequality are different. In this study, we analyzed mortality rates among incarcerated people in the Texas Department of Criminal Justice (TDCJ) to assess racial and ethnic differences in COVID-19 mortality. We obtained monthly demographic and mortality information of the TDCJ population from April 1, 2019 to March 31, 2021 from TDCJ monthly reports and open record requests filed by the Texas Justice Initiative. We estimated the risk of COVID-19 mortality for the Hispanic and Black population relative to the White population using a Bayesian regression framework, adjusting for sex and age. In the first 12 months of the pandemic, Hispanic and Black all-cause mortality rates were higher than that of the White population, reversing the pattern observed the 12 months prior. Adjusted risk of COVID-19 mortality relative to the White population was 1.96 (CI 1.32-2.93) for the Hispanic population and 1.66 (CI 1.10-2.52) for the Black population. We find that COVID-19 mortality has disproportionately impacted Hispanic and Black individuals within the TDCJ population. As the proximal mechanisms which drive these inequalities are likely different than those which lead to racial inequalities in the non-incarcerated populations, future studies should look to assess and address the specific drivers of COVID-19 related disparities in carceral settings.",
     "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Taylor Chin",
-        "author_inst": "Harvard T.H. Chan School of Public Health"
+        "author_name": "Neal Marquez",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Dennis M. Feehan",
-        "author_inst": "UC Berkeley"
+        "author_name": "Destiny Moreno",
+        "author_inst": "University of Texas at Austin"
       },
       {
-        "author_name": "Caroline O. Buckee",
-        "author_inst": "Harvard School of Public Health"
+        "author_name": "Amanda Klonsky",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Ayesha S. Mahmud",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Sharon Dolovich",
+        "author_inst": "University of California Los Angeles"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.09.25.21264120",
@@ -530102,33 +531953,93 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.09.23.21264014",
-    "rel_title": "Neutralizing efficacy of vaccines against the SARS-CoV-2 Mu variant",
+    "rel_doi": "10.1101/2021.09.21.21263902",
+    "rel_title": "Quantification and prognostic significance of interferon-\u03b3 secreting SARS-CoV-2 responsive T cells in hospitalised patients with acute COVID-19",
     "rel_date": "2021-09-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21264014",
-    "rel_abs": "The rise of mutant strains of SARS-CoV-2 poses an additional problem to the existing pandemic of COVID-19. There are rising concerns about the Mu variant which can escape humoral immunity acquired from infections from previous strains or vaccines. We examined the neutralizing efficacy of the BNT162b2 mRNA vaccine against the Mu variant and report that the vaccine has 76% neutralizing effectiveness against the Mu compared to 96% with the original strain. We also show that Mu, similar to the Delta variant, causes cell-to-cell fusion which can be an additional factor for the variant to escape vaccine-mediated humoral immunity. Despite the rise in vaccine escape strains, the vaccine still possesses adequate ability to neutralize majority of the mutants.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.21.21263902",
+    "rel_abs": "Little is known about T-cell responses during acute coronavirus disease-2019 (COVID-19). We measured T-cell interferon gamma (IFN-{gamma}) responses to spike 1 (S1), spike 2 (S2), nucleocapsid (N) and membrane (M) SARS-CoV-2 antigens using the T-SPOT(R) Discovery SARS-CoV-2 assay, a proven EliSPOT technology, in 114 hospitalised adult COVID-19 patients and assessed their association with clinical disease phenotype. T-SPOT(R) Discovery SARS-CoV-2 responses were detectable within 2 days of a positive PCR and did not correlate with vaccination status or symptom duration. Higher responses to S1 protein associated with a higher symptom burden, and serum IL-6 levels. Despite treatment with dexamethasone this subgroup was also at greater risk of requiring continuous positive airway pressure (CPAP) in the days following sampling. Higher T-cell responses measured using T-SPOT(R) Discovery SARS-CoV-2 associate with progressive disease in acute COVID-19 disease and may have utility as a prognostic biomarker that should be evaluated in larger cohorts.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Kei Miyakawa",
-        "author_inst": "Yokohama City University School of Medicine"
+        "author_name": "Daniel Pan",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Sundararaj Stanleyraj Jeremiah",
-        "author_inst": "Yokohama City University School of Medicine"
+        "author_name": "Jee Whang Kim",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Hideaki Kato",
-        "author_inst": "Yokohama City University Hospital"
+        "author_name": "Joshua Nazareth",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Akihide Ryo",
-        "author_inst": "Yokohama City University School of Medicine"
+        "author_name": "Sara Assadi",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Adam Bellass",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Jack Leach",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "James G Brosnan",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Adam Ahmed",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Fleur Starcevic",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Shirley Sze",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Christopher A Martin",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Caroline M Williams",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Michael R Barer",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Amandip Sahota",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Prashanth Patel",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Andrea Tattersall",
+        "author_inst": "Oxford Immunotec"
+      },
+      {
+        "author_name": "Andrea Cooper",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Manish Pareek",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Pranabashis Haldar",
+        "author_inst": "University of Leicester"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -531760,63 +533671,55 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.09.23.461605",
-    "rel_title": "Apixaban, an orally available anticoagulant, inhibits SARS-CoV-2 replication by targeting its major protease in a non-competitive way",
+    "rel_doi": "10.1101/2021.09.23.21262822",
+    "rel_title": "Plasma S-Adenosylmethionine is Associated with Lung Injury in COVID-19",
     "rel_date": "2021-09-24",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.23.461605",
-    "rel_abs": "Anticoagulants are associated with clinical benefit against the 2019 coronavirus disease (COVID-19), preventing COVID-19 associated coagulopathy. Blood coagulation factor Xa (FXa) and SARS-CoV-2 major protease (Mpro) share over 80% homology at the three-dimensional protein level. Thus, it is worth interrogating whether there is crosstalk between inhibitors and substrates between these enzymes. Here, we found that the clinically-approved FXa inhibitor apixaban targets SARS-CoV-2 Mpro with a 21-fold higher potency than boceprevir (GC376). Apixaban displayed a non-competitive mechanism of inhibition towards Mpro, since it targets the enzyme/substrate complex and the allosteric site onto the viral protease. Enzymatic assays were further validated in infected Calu-3 cells, which reveal that apixaban decreases the production of infectious viral particles in a dose-dependent manner, with an inhibitory potency in the micromolar range. Our results are in line with the proposed early use of anticoagulants, including FXa inhibitors, to improve clinical outcome of COVID-19 patients. In this context, apixaban may display a dual mechanism of action by targeting FXa to prevent coagulopathy and, at some level, SARS-CoV-2 Mpro.",
-    "rel_num_authors": 11,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21262822",
+    "rel_abs": "ObjectiveS-Adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are indicators of global transmethylation and may play an important role as markers of severity of COVID-19.\n\nMethodsThe levels of plasma SAM and SAH were determined in patients admitted with COVID-19 (n = 56, mean age = 61). Lung injury was identified by computed tomography (CT) in accordance with the CT0-4 classification.\n\nResultsSAM was found to be a potential marker of lung damage risk in COVID-19 patients (SAM > 80 nM; CT3,4 vs. CT 0-2: relative ratio (RR) was 3.0; p = 0.0029). SAM/SAH > 6.0 was also found to be a marker of lung injury (CT2-4 vs. CT0,1: RR = 3.47, p = 0.0004). Interleukin-6 (IL-6) levels were associated with SAM ({rho} = 0.44, p = 0.01) and SAH ({rho} = 0.534, p = 0.001) levels.\n\nConclusionsHigh SAM levels and high methylation index are associated with the risk of lung injury in COVID-19 patients. The association of SAM and SAH with IL-6 indicates an important role of transmethylation in the development of cytokine imbalance in COVID-19 cases.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Otavio Augusto Chaves",
-        "author_inst": "Oswaldo Cruz Foundation"
-      },
-      {
-        "author_name": "Carolina Q. Sacramento",
-        "author_inst": "FIOCRUZ"
+        "author_name": "Evgeny Kryukov",
+        "author_inst": "Burdenko Main Military Clinical Hospital"
       },
       {
-        "author_name": "Natalia Fintelman-Rodrigues",
-        "author_inst": "FIOCRUZ"
-      },
-      {
-        "author_name": "Jairo Ramos Temerozo",
-        "author_inst": "Oswaldo Cruz Institute"
+        "author_name": "Alexander Ivanov",
+        "author_inst": "Institute of General Pathology and Pathophysiology"
       },
       {
-        "author_name": "Filipe Pereira-Dutra",
-        "author_inst": "Oswaldo Cruz Foundation"
+        "author_name": "Vladimir Karpov",
+        "author_inst": "Burdenko Main Military Clinical Hospital"
       },
       {
-        "author_name": "Daniella M. Mizurini",
-        "author_inst": "UFRJ"
+        "author_name": "Valery Alexandrin",
+        "author_inst": "Institute of General Pathology and Pathophysiology"
       },
       {
-        "author_name": "Robson Q. Monteiro",
-        "author_inst": "UFRJ"
+        "author_name": "Alexander Dygai",
+        "author_inst": "Institute of General Pathology and Pathophysiology"
       },
       {
-        "author_name": "Leonardo Vazquez",
-        "author_inst": "Fiocruz"
+        "author_name": "Maria Kruglova",
+        "author_inst": "Sechenov First Moscow State Medical University"
       },
       {
-        "author_name": "Patricia T. Bozza",
-        "author_inst": "Lab Imunofarmacologia, Instituto Oswaldo Cruz, FIOCRUZ"
+        "author_name": "Gennady Kostiuchenko",
+        "author_inst": "Regional Clinical Hospital"
       },
       {
-        "author_name": "Hugo Caire Castro-Faria-Neto",
-        "author_inst": "Fiocruz"
+        "author_name": "Sergei Kazakov",
+        "author_inst": "Burdenko Main Military Clinical Hospital"
       },
       {
-        "author_name": "Thiago Moreno L. Souza",
-        "author_inst": "Oswaldo Cruz Foundation"
+        "author_name": "Aslan Kubatiev",
+        "author_inst": "Institute of General Pathology and Pathophysiology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "respiratory medicine"
   },
   {
     "rel_doi": "10.1101/2021.09.21.21262927",
@@ -533478,39 +535381,107 @@
     "category": "cardiovascular medicine"
   },
   {
-    "rel_doi": "10.1101/2021.09.18.21263773",
-    "rel_title": "COVID-19 Acceleration and Vaccine Status in France - August 2021",
+    "rel_doi": "10.1101/2021.09.19.21262487",
+    "rel_title": "Genomic analysis of SARS-CoV-2 breakthrough infections from Varanasi, India",
     "rel_date": "2021-09-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.18.21263773",
-    "rel_abs": "ObjectivesThis note provides an assessment of COVID-19 acceleration among groups with different vaccine status in France.\n\nMethodsWe assess viral acceleration using a novel indicator introduced in Baunez et al. (2021). The acceleration index relates the percentage change of tests that have been performed on a given day to the percentage change in the associated positive cases that same day. We compare viral acceleration among vaccinated and unvaccinated individuals in France over the period May 31st - August 29, 2021.\n\nResultsOnce the state of the epidemic within each groups is accounted for, it turns out that viral acceleration has since mid-July converged to similar levels among vaccinated and unvaccinated individuals in France, even though viral speed is larger for the latter group compared to the former.\n\nConclusionOur results call for an increasing testing effort for both vaccinated and unvaccinated individuals, in view of the fact that viral circulation is currently accelerating at similar levels for both groups in France.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.19.21262487",
+    "rel_abs": "Studies worldwide have shown that the available vaccines are highly effective against SARS-CoV-2. However, there are growing laboratory reports that the newer variants of concerns (VOCs e.g. Alpha, Beta, Delta etc) may evade vaccine induced defense. In addition to that, there are few ground reports on health workers having breakthrough infections. In order to understand VOC driven breakthrough infection we investigated 14 individuals who tested positive for SARS-CoV-2 after being administered a single or double dose of Covishield (ChAdOx1, Serum Institute of India) from the city of Varanasi, which is located in the Indian state of Uttar Pradesh. Genomic analysis revealed that 78.6% (11/14) of the patients were infected with the B.1.617.2 (Delta) variant. Notably, the frequency (37%) of this variant in the region was significantly lower (p<0.01), suggesting that the vaccinated people were asymmetrically infected with the Delta variant. Most of the patients tested displayed mild symptoms, indicating that even a single dose of the vaccine can help in reducing the severity of the disease. However, more comprehensive epidemiological studies are required to understand the effectiveness of vaccines against the newer VOCs.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Christelle Baunez",
-        "author_inst": "Institut Neurosciences Timone"
+        "author_name": "Lamuk Zaveri",
+        "author_inst": "CSIR - Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Mickael Degoulet",
-        "author_inst": "Institut Neurosciences Timone"
+        "author_name": "Royana Singh",
+        "author_inst": "Banaras Hindu University"
       },
       {
-        "author_name": "Stephane Luchini",
-        "author_inst": "Aix-Marseille School of Economics"
+        "author_name": "Priyoneel Basu",
+        "author_inst": "Banaras Hindu University"
       },
       {
-        "author_name": "Patrick Pintus",
-        "author_inst": "Aix-Marseille University and CNRS"
+        "author_name": "Sofia Banu",
+        "author_inst": "CSIR - Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Miriam Teschl",
-        "author_inst": "Aix-Marseille School of Economics"
+        "author_name": "Payel Mukherjee",
+        "author_inst": "CSIR - Centre for Cellular and Molecular Biology"
+      },
+      {
+        "author_name": "Shani Vishwakarma",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Chetan Sahni",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Manpreet Kaur",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Nitish Kumar Singh",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Abhay Kumar Yadav",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Ajay Kumar Yadav",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Ashish Ashish",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Shivani Mishra",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Shivam Tiwari",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Surendra Pratap Mishra",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Amareshwar Vodapalli",
+        "author_inst": "CSIR - Centre for Cellular and Molecular Biology"
+      },
+      {
+        "author_name": "Himasri Bollu",
+        "author_inst": "CSIR - Centre for Cellular and Molecular Biology"
+      },
+      {
+        "author_name": "Debashruti Das",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Prajjval Pratap Singh",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Gyaneshwer Chaubey",
+        "author_inst": "Banaras Hindu University"
+      },
+      {
+        "author_name": "Divya Tej Sowpati",
+        "author_inst": "CSIR - Centre for Cellular and Molecular Biology"
+      },
+      {
+        "author_name": "Karthik Bharadwaj Tallapaka",
+        "author_inst": "CSIR - Centre for Cellular and Molecular Biology"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.09.18.21263782",
@@ -535376,45 +537347,89 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.09.16.21263576",
-    "rel_title": "Impact of prior SARS-CoV-2 infection on post-vaccination SARS-CoV-2 spike IgG antibodies in a longitudinal cohort of healthcare workers",
+    "rel_doi": "10.1101/2021.09.20.21263875",
+    "rel_title": "Comparative single-dose mRNA and ChAdOx1 vaccine effectiveness against SARS-CoV-2, including early variants of concern: a test-negative design, British Columbia, Canada",
     "rel_date": "2021-09-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.16.21263576",
-    "rel_abs": "Waning serum antibodies against SARS-CoV-2 have sparked discussions about long-term immunity and need for vaccine boosters. We examined SARS-CoV-2 spike IgG antibodies in a longitudinal cohort, comparing antibody decay in individuals who received an mRNA SARS-CoV-2 vaccine, with and without prior SARS-CoV-2 infection. We completed a longitudinal cohort of healthcare workers (HWs) between June 2020 and September 2021. HWs were included if they had a serum sample collected after SARS-CoV-2 infection and/or a serum sample collected [&ge;] 14 days after second dose of an mRNA SARS-CoV-2 vaccine. Linear regression models adjusting for vaccine type, age, and sex were used to compare post-vaccination antibody levels between 1) HWs with and without prior SARS-CoV-2 infection and 2) HWs with prior SARS-CoV-2 infection [&le;] 90 days and > 90 days prior to first vaccine. Serum was collected from 98 HWs after SARS-CoV-2 infection and before vaccine, and 1960 HWs [&ge;] 14 days following second vaccine dose. Serum spike antibody levels were higher after vaccination than after natural infection. Compared to SARS-CoV-2 naive individuals, those with prior infection maintained higher post-vaccination mean spike IgG values at 1, 3, and 6 months, after adjusting for age, sex, and vaccine type. Individuals with PCR-confirmed infection > 90 days before vaccination had higher post-vaccination antibody levels than individuals infected [&le;] 90 days before vaccination. Individuals with three exposures to spike protein maintain the highest antibody levels particularly when first and second exposures were greater than 90 days apart. A booster dose provides a third exposure and may similarly induce a more durable antibody response.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.20.21263875",
+    "rel_abs": "IntroductionIn randomized controlled trials, single-dose efficacy against SARS-CoV-2 illness exceeded 90% for mRNA vaccines (BNT162b2 and mRNA-1273), and 75% for ChAdOx1. In British Columbia (BC), Canada second doses were deferred up to 16 weeks and ChAdOx1 was only initially recommended for adults 55 years of age and older. We compared single-dose vaccine effectiveness (VE) during the spring 2021 wave in BC when Alpha and Gamma variants of concern (VOC) predominated.\n\nMethodsVE was estimated against infection and hospitalization by test-negative design: cases were RT-PCR test-positive for SARS-CoV-2 and controls were test-negative. Adults 50-69 years old with specimen collection between April 4 and May 22 (weeks 14-20) were included. Variant-specific VE was estimated between weeks 17-20 when genetic characterization of all case viruses was performed, primarily through whole genome sequencing.\n\nResultsVE analyses included 7,116 (10%) cases and 60,958 controls. Three-quarters of vaccinated participants received mRNA vaccine (60% BNT162b2, 15% mRNA-1273) and 25% received ChAdOx1. Half of genetically characterized viruses were Alpha, with 38% Gamma, 4% Delta and 8% non-VOCs. Single-dose VE against any infection was 75% (95%CI: 72-78) for BNT162b2, 82% (95%CI: 76-87) for mRNA-1273 and 61% (95%CI: 54-66) for ChAdOx1. VE against hospitalization was 83% (95%CI: 76-89), 85% (95%CI: 63-94) and 96% (95%CI: 86-99), respectively. VE against Alpha vs. Gamma infections did not differ among mRNA (78%;95%CI: 73-82 and 80%;95%CI: 74-85) or ChAdOx1 (66%;95%CI: 57-74 and 60%;95%CI: 48-69) recipients.\n\nConclusionsA single dose of mRNA vaccine reduced the SARS-CoV-2 infection risk by at least 75%, including infections due to early VOC. Although effectiveness of a single dose of ChAdOx1 was lower at 60% against infection, just one dose of any vaccine reduced the hospitalization risk by more than 80%. In the context of constrained vaccine supplies, these findings have implications for global vaccine deployment to reduce the overall burden of infections and hospitalizations due to SARS-CoV-2.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Diana Zhong",
-        "author_inst": "Johns Hopkins University School of Medicine"
+        "author_name": "Danuta M Skowronski",
+        "author_inst": "BC Centre for Disease Control"
       },
       {
-        "author_name": "Shaoming Xiao",
-        "author_inst": "Johns Hopkins University School of Medicine"
+        "author_name": "Solmaz Setayeshgar",
+        "author_inst": "BC Centre for Disease Control"
       },
       {
-        "author_name": "Amanda K Debes",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Macy Zou",
+        "author_inst": "BC Centre for Disease Control"
       },
       {
-        "author_name": "Emily R Egbert",
-        "author_inst": "Johns Hopkins University School of Medicine"
+        "author_name": "Natalie Prystajecky",
+        "author_inst": "BC Centre for Disease Control"
       },
       {
-        "author_name": "Patrizio Caturegli",
-        "author_inst": "Johns Hopkins University School of Medicine"
+        "author_name": "John R Tyson",
+        "author_inst": "BC Centre for Disease Control"
       },
       {
-        "author_name": "Elizabeth Colantuoni",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Hind Sbihi",
+        "author_inst": "BC Centre for Disease Control"
       },
       {
-        "author_name": "Aaron M Milstone",
-        "author_inst": "Johns Hopkins University School of Medicine"
+        "author_name": "Chris D Fjell",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "Eleni Galanis",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "Monika Naus",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "David M Patrick",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "Shiraz El Adam",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "May Ahmed",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "Shinhye Kim",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "Bonnie Henry",
+        "author_inst": "Office of the Provincial Health Officer, Ministry of Health"
+      },
+      {
+        "author_name": "Linda Hoang",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "Manish Sadarangani",
+        "author_inst": "Vaccine Evaluation Center, BC Children's Hospital Research Institute"
+      },
+      {
+        "author_name": "Agathat N Jassem",
+        "author_inst": "BC Centre for Disease Control"
+      },
+      {
+        "author_name": "Mel Krajden",
+        "author_inst": "BC Centre for Disease Control"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -536795,47 +538810,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.09.17.21263723",
-    "rel_title": "Optimized Post-Vaccination Strategies and Preventative Measures for SARS-CoV-2",
+    "rel_doi": "10.1101/2021.09.16.21263714",
+    "rel_title": "The Relationship of Vaccine Uptake and COVID-19 Infections among Nursing Home Staff and Residents in Missouri",
     "rel_date": "2021-09-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.17.21263723",
-    "rel_abs": "IntroductionSince March of 2020, over 210 million SARS-CoV-2 cases have been reported and roughly five billion doses of a SARS-CoV-2 vaccine have been delivered. The rise of the more infectious delta variant has recently indicated the value of reinstating previously relaxed non-pharmacological and test-driven preventative measures. These efforts have been met with resistance, due, in part, to a lack of site-specific quantitative evidence which can justify their value. As vaccination rates continue to increase, a gap in knowledge exists regarding appropriate thresholds for escalation and de-escalation of COVID-19 preventative measures.\n\nMethodsWe conducted a series of simulation experiments, trialing the spread of SARS-CoV-2 virus in a hypothesized working environment that is subject to COVID-19 infections from the surrounding community. We established cohorts of individuals who would, in simulation, work together for a set period of time. With these cohorts, we tested the rates of workplace and community acquired infections based on applied isolation strategies, community infection rates (CIR), scales of testing, non-pharmaceutical interventions, variant predominances and testing strategies, vaccination coverages, and vaccination efficacies of the members included. Permuting through each combination of these variables, we estimated expected case counts for 33,462 unique workplace scenarios.\n\nResultsWhen the CIR is 5 new confirmed cases per 100,000 or fewer, and at 50% of the workforce is vaccinated with a 95% efficacious vaccine, then testing daily with an antigen-based or PCR based test in only unvaccinated workers will result in less than one infection through 4,800 person weeks. When the community infection rate per 100,000 persons is less than or equal to 60, and the vaccination coverage of the workforce is 100% with 95% vaccine efficacy then no masking or routine testing + isolation strategies are needed to prevent workplace acquired infections regardless of variant predominance. Identifying and isolating workers with antigen-based SARS-CoV-2 testing methods results in the same or fewer workplace acquired infections than testing with polymerase chain reaction (PCR) methods.\n\nConclusionsSpecific scenarios exist in which preventative measures taken to prevent SARS-CoV-2 spread, including masking, and testing plus isolation strategies can safely be relaxed. Further, efficacious testing with quarantine strategies exist for implementation in only unvaccinated cohorts in a workplace. Due to shorter turnaround time, antigen-based testing with lower sensitivity is more effective than PCR testing with higher sensitivities in comparable testing strategies. The general reference interactive heatmap we provide can be used for site specific, immediate, parameter-based case count predictions to inform appropriate institutional policy making.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.16.21263714",
+    "rel_abs": "Nursing homes (NH) continue to struggle with COVID-19 morbidity and mortality with older adult residents at greater risk of infection due to proximity to other residents, advanced aging-related chronic illnesses, and contact with staff. While many states have prioritized COVID-19 vaccinations among older adults, vaccinations among NH staff vary. The purpose of this study was to quantify the relationship between nursing home staff vaccination uptake and COVID-19 infections among residents. A zero-inflated Poisson regression model was constructed to predict the weekly number of COVID-19 cases among Missouri nursing home residents using data from the Centers for Medicaid and Medicare Services. A total of 1,124 COVID-19 infections were reported among 504 NH residents between January 1, 2021 and August 22, 2021. After adjusting for number of total residents, resident vaccine rate, staff quality rating, and respective county COVID-19 rate, for every percent increase in nursing home staff vaccine rate the risk of COVID-19 infections significantly decreased by 13% (IRR 0.87, 95% CI 0.81, 0.93). This study identified that NH staff, likely due to greater mobility, are important to prioritize in vaccination efforts to protect themselves and residents of their facilities from COVID-19 infections. Further, the CMS staff ratings were significant predictors of infection as well, which highlight the structural challenges that exist within and outside the context of a highly infectious and deadly pandemic. These results also provide insights to optimizing vaccination roll-out to best protect our communities most vulnerable residents.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Rowland W Pettit",
-        "author_inst": "Baylor College of Medicine"
-      },
-      {
-        "author_name": "Bo Peng",
-        "author_inst": "Baylor College of Medicine"
-      },
-      {
-        "author_name": "Patrick Yu",
-        "author_inst": "Corporate Medical Advisors, Houston, Texas, USA"
-      },
-      {
-        "author_name": "Peter Matos",
-        "author_inst": "Corporate Medical Advisors, Houston, Texas, USA"
-      },
-      {
-        "author_name": "Alexander L. Greninger",
-        "author_inst": "Laboratory Medicine, University of Washington"
+        "author_name": "Stephen Scroggins",
+        "author_inst": "Saint Louis University"
       },
       {
-        "author_name": "Julie McCashin",
-        "author_inst": "International S.O.S., Houston, TX"
+        "author_name": "Matthew Ellis",
+        "author_inst": "Washington University St. Louis"
       },
       {
-        "author_name": "Christopher Ian Amos",
-        "author_inst": "Baylor College of Medicine"
+        "author_name": "Enbal Shacham",
+        "author_inst": "Saint Louis University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.09.17.21263743",
@@ -538421,45 +540420,153 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.09.14.21262977",
-    "rel_title": "Spatiotemporal analyses illuminate the competitive advantage of a SARS-CoV-2 variant of concern over a variant of interest",
+    "rel_doi": "10.1101/2021.09.14.21263153",
+    "rel_title": "Evolution of COVID-19 mortality over time: results from the Swiss hospital surveillance system (CH-SUR)",
     "rel_date": "2021-09-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.14.21262977",
-    "rel_abs": "The emergence of novel SARS-CoV-2 variants in late 2020 and early 2021 raised alarm worldwide and prompted reassessment of the management, surveillance, and projected future of COVID-19. Mutations that confer competitive advantages by increasing transmissibility or immune evasion have been associated with the localized dominance of single variants. Thus, elucidating the evolutionary and epidemiological dynamics among novel variants is essential for understanding the trajectory of the COVID-19 pandemic. Here we show the interplay between B.1.1.7 (Alpha) and B.1.526 (Iota) in New York (NY) from December 2020 to April 2021 through phylogeographic analyses, space-time scan statistics, and cartographic visualization. Our results indicate that B.1.526 likely evolved in the Bronx in late 2020, providing opportunity for an initial foothold in the heavily interconnected New York City (NYC) region, as evidenced by numerous exportations to surrounding locations. In contrast, B.1.1.7 became dominant in regions of upstate NY where B.1.526 had limited presence, suggesting that B.1.1.7 was able to spread more efficiently in the absence of B.1.526. Clusters discovered from the spatial-time scan analysis supported the role of competition between B.1.526 and B.1.1.7 in NYC in March 2021 and the outsized presence of B.1.1.7 in upstate NY in April 2021. Although B.1.526 likely delayed the rise of B.1.1.7 in NYC, B.1.1.7 became the dominant variant in the Metro region by the end of the study period. These results reveal the advantages endemicity may grant to a variant (founder effect), despite the higher fitness of an introduced lineage. Our research highlights the dynamics of inter-variant competition at a time when B.1.617.2 (Delta) is overtaking B.1.1.7 as the dominant lineage worldwide. We believe our combined spatiotemporal methodologies can disentangle the complexities of shifting SARS-CoV-2 variant landscapes at a time when the evolution of variants with additional fitness advantages is impending.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.14.21263153",
+    "rel_abs": "BackgroundWhen comparing the periods of time during and after the first wave of the ongoing SARS-CoV-2/COVID-19 pandemic in Europe, the associated COVID-19 mortality seems to have decreased substantially. Various factors could explain this trend, including changes in demographic characteristics of infected persons, and the improvement of case management. To date, no study has been performed to investigate the evolution of COVID-19 in-hospital mortality in Switzerland, while also accounting for risk factors.\n\nMethodsWe investigated the trends in COVID-19 related mortality (in-hospital and in-intermediate/intensive-care) over time in Switzerland, from February 2020 to May 2021, comparing in particular the first and the second wave. We used data from the COVID-19 Hospital-based Surveillance (CH-SUR) database. We performed survival analyses adjusting for well-known risk factors of COVID-19 mortality (age, sex and comorbidities) and accounting for competing risk.\n\nResultsOur analysis included 16,030 episodes recorded in CH-SUR, with 2,320 reported deaths due to COVID-19 (13.0% of included episodes). We found that overall in-hospital mortality was lower during the second wave of COVID-19 compared to the first wave (HR 0.71, 95% CI 0.69 - 0.72, p-value < 0.001), a decrease apparently not explained by changes in demographic characteristics of patients. In contrast, mortality in intermediate and intensive care significantly increased in the second wave compared to the first wave (HR 1.48, 95% CI 1.42 - 1.55, p-value < 0.001), with significant changes in the course of hospitalisation between the first and the second wave.\n\nConclusionWe found that, in Switzerland, COVID-19 mortality decreased among hospitalised persons, whereas it increased among patients admitted to intermediate or intensive care, when comparing the second wave to the first wave. We put our findings in perspective with changes over time in case management, treatment strategy, hospital burden and non-pharmaceutical interventions. Further analyses of the potential effect of virus variants and of vaccination on mortality would be crucial to have a complete overview of COVID-19 mortality trends throughout the different phases of the pandemic.",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Alexis Russell",
-        "author_inst": "Laboratory of Viral Diseases, Wadsworth Center, New York State Department of Health"
+        "author_name": "Maroussia Roelens",
+        "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"
       },
       {
-        "author_name": "Collin O'Connor",
-        "author_inst": "Division of Epidemiology, New York State Department of Health"
+        "author_name": "Alexis Martin",
+        "author_inst": "Swiss Tropical and Public Health Institute, Basel, Switzerland ; University of Basel, Basel, Switzerland"
       },
       {
-        "author_name": "Erica Lasek-Nesselquist",
-        "author_inst": "Bioinformatics Core, Wadsworth Center, New York State Department of Health"
+        "author_name": "Brian Friker",
+        "author_inst": "Veterinary Public Health Institute, University of Bern, Bern, Switzerland"
       },
       {
-        "author_name": "Jonathan Plitnick",
-        "author_inst": "Laboratory of Viral Diseases, Wadsworth Center, New York State Department of Health"
+        "author_name": "Filipe Maximiano Sousa",
+        "author_inst": "Veterinary Public Health Institute, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Amaury Thiabaud",
+        "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"
+      },
+      {
+        "author_name": "Beatriz Vidondo",
+        "author_inst": "Veterinary Public Health Institute, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Valentin Buchter",
+        "author_inst": "Swiss Federal Office of Public Health, Bern, Switzerland"
+      },
+      {
+        "author_name": "C\u00e9line Gardiol",
+        "author_inst": "Swiss Federal Office of Public Health, Bern, Switzerland"
+      },
+      {
+        "author_name": "Jasmin Vonlanthen",
+        "author_inst": "Swiss Federal Office of Public Health, Bern, Switzerland"
+      },
+      {
+        "author_name": "Carlo Balmelli",
+        "author_inst": "Infection Control Programme, EOC Hospitals, Ticino, Switzerland"
+      },
+      {
+        "author_name": "Manuel Battegay",
+        "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland"
+      },
+      {
+        "author_name": "Christoph Berger",
+        "author_inst": "Division of Infectious Diseases, and Children's Research Centre, University Children's Hospital Zurich, Zurich, Switzerland"
+      },
+      {
+        "author_name": "Michael Buettcher",
+        "author_inst": "Paediatric Infectious Diseases, Department of Paediatrics, Children's Hospital, Cantonal Hospital Lucerne, Lucerne, Switzerland"
+      },
+      {
+        "author_name": "Alexia Cusini",
+        "author_inst": "Department of Infectious Diseases, Cantonal Hospital Graubuenden, Chur, Switzerland"
+      },
+      {
+        "author_name": "Domenica Flury",
+        "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St Gallen, St Gallen, Switzerland"
+      },
+      {
+        "author_name": "Ulrich Heininger",
+        "author_inst": "Infectious Diseases and Vaccinology, University of Basel Children's Hospital, Basel, Switzerland"
+      },
+      {
+        "author_name": "Anita Niederer-Loher",
+        "author_inst": "Children's Hospital of Eastern Switzerland, St Gallen, Switzerland"
+      },
+      {
+        "author_name": "Thomas Riedel",
+        "author_inst": "Department of Paediatrics, Cantonal Hospital Graubuenden, Chur, Switzerland"
+      },
+      {
+        "author_name": "Peter W. Schreiber",
+        "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland"
+      },
+      {
+        "author_name": "Rami Sommerstein",
+        "author_inst": "Department of Infectious Diseases, Bern University Hospital (Inselspital), Bern, Switzerland ; Infectious Diseases and Hospital Hygiene, Hirslanden Central Swit"
+      },
+      {
+        "author_name": "Nicolas Troillet",
+        "author_inst": "Service of Infectious Diseases, Central Institute, Valais Hospitals, Sion, Switzerland"
+      },
+      {
+        "author_name": "Sara Tschudin-Sutter",
+        "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland"
+      },
+      {
+        "author_name": "Pauline Vetter",
+        "author_inst": "Geneva Center for Emerging Viral Diseases, Geneva University Hospitals, Geneva, Switzerland"
+      },
+      {
+        "author_name": "Sara Bernhard-Stirnemann",
+        "author_inst": "Children's Hospital Aarau, Aarau, Switzerland"
       },
       {
-        "author_name": "John P Kelly",
-        "author_inst": "Applied Genomic Technology Core, Wadsworth Center, New York State Department of Health"
+        "author_name": "Natascia Corti",
+        "author_inst": "Unit of General Internal Medicine, Hirslanden Clinic, Zurich, Switzerland"
+      },
+      {
+        "author_name": "Roman Gaudenz",
+        "author_inst": "Internal Medicine and Infectiology, Cantonal Hospital Nidwalden, Stans, Switzerland"
+      },
+      {
+        "author_name": "Jonas Marschall",
+        "author_inst": "Department of Infectious Diseases, Bern University Hospital (Inselspital), Bern, Switzerland"
+      },
+      {
+        "author_name": "Yvonne Nussbaumer-Ochsner",
+        "author_inst": "Clinic for Internal Medicine, Cantonal Hospital, Hospitals Schaffhausen, Switzerland"
       },
       {
-        "author_name": "Daryl M Lamson",
-        "author_inst": "Laboratory of Viral Diseases, Wadsworth Center, New York State Department of Health"
+        "author_name": "Laurence Senn",
+        "author_inst": "Service of Preventive Medicine, Lausanne University Hospital, CHUV, Lausanne, Switzerland"
+      },
+      {
+        "author_name": "Danielle Vuichard-Gysin",
+        "author_inst": "Division of Infectious Diseases and Hospital Hygiene, Thurgau Hospital Group Munsterlingen and Frauenfeld, Switzerland"
       },
       {
-        "author_name": "Kirsten St George",
-        "author_inst": "Laboratory of Viral Diseases, Wadsworth Center, New York State Department of Health"
+        "author_name": "Petra Zimmermann",
+        "author_inst": "Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland ; Department of Paediatrics, Fribourg Hospital HFR, Fribourg, Switzerland"
+      },
+      {
+        "author_name": "Franziska Zucol",
+        "author_inst": "Paediatric Infectious Diseases, Department of Paediatrics, Cantonal Hospital Winterthur, Winterthur, Switzerland"
+      },
+      {
+        "author_name": "Anne Iten",
+        "author_inst": "Service of Prevention and Infection Control, Directorate of Medicine and Quality, University Hospital Geneva, HUG, Geneva, Switzerland"
+      },
+      {
+        "author_name": "Olivia Keiser",
+        "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -540715,97 +542822,121 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.09.13.21263487",
-    "rel_title": "SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population",
+    "rel_doi": "10.1101/2021.09.09.21263348",
+    "rel_title": "Robust clinical detection of SARS-CoV-2 variants by RT-PCR/MALDI-TOF multi-target approach",
     "rel_date": "2021-09-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.13.21263487",
-    "rel_abs": "We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.",
-    "rel_num_authors": 20,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263348",
+    "rel_abs": "The COVID-19 pandemic sparked rapid development of SARS-CoV-2 diagnostics. However, emerging variants pose the risk for target dropout and false-negative results secondary to primer/probe binding site (PBS) mismatches. The Agena MassARRAY(R) SARS-CoV-2 Panel combines RT-PCR and MALDI-TOF mass-spectrometry to probe for five targets across N and ORF1ab genes, which provides a robust platform to accommodate PBS mismatches in divergent viruses. Herein, we utilize a deidentified dataset of 1,262 SARS-CoV-2-positive specimens from Mount Sinai Health System (New York City) from December 2020 through April 2021 to evaluate target results and corresponding sequencing data. Overall, the level of PBS mismatches was greater in specimens with target dropout. Of specimens with N3 target dropout, 57% harbored an A28095T substitution that is highly-specific for the alpha (B.1.1.7) variant of concern. These data highlight the benefit of redundancy in target design and the potential for target performance to illuminate the dynamics of circulating SARS-CoV-2 variants.",
+    "rel_num_authors": 26,
     "rel_authors": [
       {
-        "author_name": "Jia Wei",
-        "author_inst": "University of Oxford"
+        "author_name": "Matthew M. Hernandez",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Koen B. Pouwels",
-        "author_inst": "University of Oxford"
+        "author_name": "Radhika Banu",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Nicole Stoesser",
-        "author_inst": "University of Oxford"
+        "author_name": "Ana S. Gonzalez-Reiche",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Philippa C. Matthews",
-        "author_inst": "University of Oxford"
+        "author_name": "Adriana van de Guchte",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Ian Diamond",
-        "author_inst": "Office for National Statistics"
+        "author_name": "Zenab Khan",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Ruth Studley",
-        "author_inst": "Office for National Statistics"
+        "author_name": "Paras Shrestha",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Emma Rourke",
-        "author_inst": "Office for National Statistics"
+        "author_name": "Liyong Cao",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Duncan Cook",
-        "author_inst": "Office for National Statistics"
+        "author_name": "Feng Chen",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "John I Bell",
-        "author_inst": "University of Oxford"
+        "author_name": "Huanzhi Shi",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "John N Newton",
-        "author_inst": "Public Health England"
+        "author_name": "Ayman Hanna",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Jeremy Farrar",
-        "author_inst": "Wellcome Trust"
+        "author_name": "Hala Alshammary",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Alison Howarth",
-        "author_inst": "University of Oxford"
+        "author_name": "Shelcie Fabre",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Brian D. Marsden",
-        "author_inst": "University of Oxford"
+        "author_name": "Angela Amoako",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Sarah Hoosdally",
-        "author_inst": "University of Oxford"
+        "author_name": "Ajay Obla",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "E Yvonne Jones",
-        "author_inst": "University of Oxford"
+        "author_name": "Bremy Alburquerque",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "David I Stuart",
-        "author_inst": "University of Oxford"
+        "author_name": "Luz Helena Pati\u00f1o",
+        "author_inst": "Universidad del Rosario"
       },
       {
-        "author_name": "Derrick W. Crook",
-        "author_inst": "University of Oxford"
+        "author_name": "Juan David Ram\u00edrez",
+        "author_inst": "Universidad del Rosario"
       },
       {
-        "author_name": "Tim E.A. Peto",
-        "author_inst": "University of Oxford"
+        "author_name": "Robert Sebra",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "A.Sarah Walker",
-        "author_inst": "University of Oxford"
+        "author_name": "Melissa R. Gitman",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "David W. Eyre",
-        "author_inst": "University of Oxford"
+        "author_name": "Michael D. Nowak",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Carlos Cordon-Cardo",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Ted E. Schutzbank",
+        "author_inst": "Agena Bioscience"
+      },
+      {
+        "author_name": "Viviana Simon",
+        "author_inst": "Icahn School of Medicine"
+      },
+      {
+        "author_name": "Harm van Bakel",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Emilia M. Sordillo",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Alberto E. Paniz Mondolfi",
+        "author_inst": "Icahn School of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -542733,79 +544864,79 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.09.10.21263072",
-    "rel_title": "VALIDATION OF A SALIVA-BASED TEST FOR THE MOLECULAR DIAGNOSIS OF SARS-CoV-2 INFECTION",
+    "rel_doi": "10.1101/2021.09.14.460356",
+    "rel_title": "Rapid Identification of Neutralizing Antibodies against SARS-CoV-2 Variants by mRNA Display",
     "rel_date": "2021-09-15",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.10.21263072",
-    "rel_abs": "BackgroundSince the beginning of the pandemic, clinicians and researchers have been searching for alternative tests to improve screening and diagnosis of SARS-CoV-2 infection (Y. Yang et al., medRxiv 2020; W. Wang et al., 2020.3786; A Senok et al., Infect Drug Resist 2020). Currently, the gold standard for virus identification is the nasopharyngeal (NP) swab (N. Sethuraman et al., JAMA 2020; A.J. Jamal et al Clinical Infect Disease 2021). Saliva samples, however, offer clear practical and logistical advantages (K.K.W To et al, Clinical Microb and Infect; A.L. Wylle et al. N Engl J Med 2020; N. Matic et al, Eur J Clin 2021) but due to lack of collection, transport, and storage solutions, high-throughput saliva-based laboratory tests are difficult to scale up as a screening or diagnostic tool (D. Esser et al., Biomark Insights 2008; E. Kaufman et al., Crit Rev Oral Biol Med2002). With this study, we aimed to validate an intra-laboratory molecular detection method for SARS-CoV-2 on saliva samples collected in a new storage saline solution, comparing the results to NP swabs to determine the difference in sensitivity between the two tests.\n\nMethodsIn this study, 156 patients (cases) and 1005 asymptomatic subjects (controls) were enrolled and tested simultaneously for the detection of the SARS-CoV-2 viral genome by RT-PCR on both NP swab and saliva samples. Saliva samples were collected in a preservative and inhibiting saline solution (Biofarma Srl). Internal method validation was performed to standardize the entire workflow for saliva samples.\n\nResultsThe identification of SARS-CoV-2 conducted on saliva samples showed a clinical sensitivity of 95.1% and specificity of 97.8% compared to NP swabs. The positive predictive value (PPV) was 81% while the negative predictive value (NPV) was 99.5%. Test concordance was 97.6% (Cohens Kappa=0.86; 95% CI 0.81-0.91). The LoD of the test was 5 viral copies for both samples.\n\nConclusionsRT-PCR assays conducted on a stored saliva sample achieved similar performance to those on NP swabs and this may provide a very effective tool for population screening and diagnosis. Collection of saliva in a stabilizing solution makes the test more convenient and widely available; furthermore, the denaturing properties of the solution reduce the infective risks belonging to sample manipulation.",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.14.460356",
+    "rel_abs": "The increasing prevalence of SARS-CoV-2 variants with the ability to escape existing humoral protection conferred by previous infection and/or immunization necessitates the discovery of broadly-reactive neutralizing antibodies (nAbs). Utilizing mRNA display, we identified a set of antibodies against SARS-CoV-2 spike (S) proteins and characterized the structures of nAbs that recognized epitopes in the S1 subunit of the S glycoprotein. These structural studies revealed distinct binding modes for several antibodies, including targeting of rare cryptic epitopes in the receptor-binding domain (RBD) of S that interacts with angiotensin- converting enzyme 2 (ACE2) to initiate infection, as well as the S1 subdomain 1. A potent ACE2-blocking nAb was further engineered to sustain binding to S RBD with the E484K and L452R substitutions found in multiple SARS-CoV-2 variants. We demonstrate that mRNA display is a promising approach for the rapid identification of nAbs that can be used in combination to combat emerging SARS-CoV-2 variants.",
     "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Michela Bulfoni",
-        "author_inst": "Department of Medicine, University of Udine, Udine, Italy; Institute of Pathology, ASU FC, Udine, Italy"
+        "author_name": "Shiho Tanaka",
+        "author_inst": "ImmunityBio, Inc."
       },
       {
-        "author_name": "Emanuela Sozio",
-        "author_inst": "Infectious Disease Unit, Department of Medicine, ASU FC, Udine, Italy"
+        "author_name": "C. Anders Olson",
+        "author_inst": "ImmunityBio, Inc."
       },
       {
-        "author_name": "Barbara Marcon",
-        "author_inst": "Department of Laboratory Medicine, ASU FC, Udine, Italy"
+        "author_name": "Christopher O. Barnes",
+        "author_inst": "Division of Biology and Biological Engineering, California Institute of Technology"
       },
       {
-        "author_name": "Maria De Martino",
-        "author_inst": "Department of Medicine, University of Udine, Udine, Italy"
+        "author_name": "Wendy Higashide",
+        "author_inst": "ImmunityBio, Inc."
       },
       {
-        "author_name": "Daniela Cesselli",
-        "author_inst": "Department of Medicine, University of Udine, Udine, Italy; Institute of Pathology, ASU FC, Udine, Italy"
+        "author_name": "Marcos Gonzales",
+        "author_inst": "ImmunityBio, Inc."
       },
       {
-        "author_name": "Chiara De Carlo",
-        "author_inst": "Infectious Disease Unit, Department of Medicine, ASU FC, Udine, Italy"
+        "author_name": "Justin Taft",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Romina Martinella",
-        "author_inst": "Department of Laboratory Medicine, ASU FC, Udine, Italy"
+        "author_name": "Ashley Richardson",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Angelica Migotti",
-        "author_inst": "Department of Laboratory Medicine, ASU FC, Udine, Italy"
+        "author_name": "Marta Martin-Fernandez",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Eleonora Vania",
-        "author_inst": "Infectious Disease Unit, Department of Medicine, ASU FC, Udine, Italy"
+        "author_name": "Dusan Bogunovic",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Agnese Zanus-Fortes",
-        "author_inst": "Infectious Disease Unit, Department of Medicine, ASU FC, Udine, Italy"
+        "author_name": "Priyanthi N. P. Gnanapragasam",
+        "author_inst": "CalTech"
       },
       {
-        "author_name": "Jessica De Piero",
-        "author_inst": "Infectious Disease Unit, Department of Medicine, ASU FC, Udine, Italy"
+        "author_name": "Pamela Bjorkman",
+        "author_inst": "Caltech"
       },
       {
-        "author_name": "Emanuele Nencioni",
-        "author_inst": "Biofarma Srl"
+        "author_name": "Patricia R Spilman",
+        "author_inst": "ImmunityBio, Inc."
       },
       {
-        "author_name": "Carlo Tascini",
-        "author_inst": "Infectious Disease Unit, Department of Medicine, ASU FC, Udine, Italy; Department of Medicine, University of Udine, Udine, Italy"
+        "author_name": "Kayvan Niazi",
+        "author_inst": "ImmunityBio, Inc."
       },
       {
-        "author_name": "Miriam Isola",
-        "author_inst": "Department of Medicine, University of Udine, Udine, Italy"
+        "author_name": "Shahrooz Rabizadeh",
+        "author_inst": "ImmunityBio, Inc."
       },
       {
-        "author_name": "Francesco Curcio",
-        "author_inst": "Department of Laboratory Medicine, ASU FC, Udine, Italy; Department of Medicine, University of Udine, Udine, Italy"
+        "author_name": "Patrick Soon-Shiong",
+        "author_inst": "ImmunityBio, Inc."
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.09.12.21263456",
@@ -544447,43 +546578,119 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.09.07.21262725",
-    "rel_title": "SARS-COV2 mutant-specific T cells and neutralizing antibodies after vaccination and up to 1 year after infection",
+    "rel_doi": "10.1101/2021.09.10.21262710",
+    "rel_title": "Antibody responses to BNT162b2 mRNA vaccine: infection-naive individuals with abdominal obesity warrant attention",
     "rel_date": "2021-09-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.07.21262725",
-    "rel_abs": "ObjectiveWe investigated blood samples from fully SARS-CoV2-vaccinated subjects and from previously positive tested patients up to one year after infection with SARS-CoV2, and compared short- and long-term T cell and antibody responses, with a special focus on the recently emerged delta variant (B.1.617.2).\n\nMethods and ResultsIn 23 vaccinated subjects, we documented high anti-SARS-CoV2 spike protein receptor binding domain (RBD) antibody titers. Average virus neutralization by antibodies, assessed as inhibition of ACE2 binding to RBD, was 2.2-fold reduced for delta mutant vs. wild type (wt) RBD. The mean specific antibody titers were lower one year after natural infection than after vaccination; ACE2 binding to delta mutant vs. wt RBD was 1.65-fold reduced. In an additional group, omicron RBD binding was reduced compared to delta.\n\nSpecific CD4+ T cell responses were measured after stimulation with peptides pools from wt, alpha, beta, gamma, or delta variant SARS-CoV2 spike proteins by flow cytometric intracellular cytokine staining. There was no significant difference in cytokine production of IFN-{gamma}, TNF-, or IL-2 between vaccinated subjects. T cell responses to wt or mutant SARS-CoV2 spike were significantly weaker after natural occurring infections compared to those in vaccinated individuals.\n\nConclusionAntibody neutralisation of the delta mutant was reduced compared to wt, as assessed in a novel inhibition assay with a finger prick blood drop. Strong CD4 T cell responses were present against wt and mutant SARS-CoV2 variants, including the delta (B.1.617.2) strain, in fully vaccinated individuals, whereas they were partly weaker 1 year after natural infection. Hence, immune responses after vaccination are stronger compared to those after naturally occurring infection, pointing out the need of the vaccine to overcome the pandemic.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.10.21262710",
+    "rel_abs": "ObjectiveThe excess of visceral adipose tissue might hinder and delay the immune response. How people with abdominal obesity will respond to mRNA vaccines against SARS-CoV-2 is yet to be established. We evaluated SARS-CoV-2-specific antibody responses after the first and second dose of the BNT162b2 mRNA vaccine comparing the response of individuals affected by abdominal obesity (AO) to those without, discerning between individuals with or without prior infection.\n\nMethodsIgG neutralizing antibodies against the Trimeric complex (IgG-TrimericS) were measured at four time points: at baseline, at day 21 after vaccine dose-1, at one month and three months after dose-2. Nucleocapsid antibodies were assessed to detect prior SARS-CoV-2 infection. Waist circumference was measured to determine abdominal obesity.\n\nResultsBetween the first and third month after vaccine dose-2, the drop in IgG-TrimericS levels was more remarkable in individuals with AO compared to those without AO (2.44 fold [95%CI: 2.22-2.63] vs 1.82 fold [95%CI: 1.69-1.92], respectively, p<0.001). Multiple linear regression confirmed this result even when adjusting for possible confounders (p<0.001).\n\nConclusionsOur findings highlight the need to extend the duration of serological monitoring of antibody levels in infection-naive individuals with abdominal obesity, a higher-risk population category in terms of possible weaker antibody response.",
+    "rel_num_authors": 25,
     "rel_authors": [
       {
-        "author_name": "Jennifer R Richardson",
-        "author_inst": "ISAR Bioscience"
+        "author_name": "ALEXIS ELIAS MALAVAZOS",
+        "author_inst": "Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy; Department of Bio"
+      },
+      {
+        "author_name": "Sara Basilico",
+        "author_inst": "Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy;"
+      },
+      {
+        "author_name": "Gianluca Iacobellis",
+        "author_inst": "Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Miami, FL, USA"
+      },
+      {
+        "author_name": "Valentina Milani",
+        "author_inst": "Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy"
+      },
+      {
+        "author_name": "Rosanna Cardani",
+        "author_inst": "Biobank BioCor, Service of Laboratory Medicine1-Clinical Pathology, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Federico Boniardi",
+        "author_inst": "Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Carola Dubini",
+        "author_inst": "Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Ilaria Prandoni",
+        "author_inst": "Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Gloria Capitanio",
+        "author_inst": "Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Laura Valentina Renna",
+        "author_inst": "Biobank BioCor, Service of Laboratory Medicine1-Clinical Pathology, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Sara Boveri",
+        "author_inst": "Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy"
+      },
+      {
+        "author_name": "Matteo Carrara",
+        "author_inst": "Residency program in Clinical Pathology and Clinical Biochemistry, University of Milano, Milan, Italy."
+      },
+      {
+        "author_name": "Giovanni Spuria",
+        "author_inst": "Residency program in Clinical Pathology and Clinical Biochemistry, University of Milano, Milan, Italy."
+      },
+      {
+        "author_name": "Maria Teresa Cuppone",
+        "author_inst": "Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Aurelia D'Acquisto",
+        "author_inst": "Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Luca Carpinelli",
+        "author_inst": "Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
+      },
+      {
+        "author_name": "Marta Sacchi",
+        "author_inst": "Service of Laboratory Medicine, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
       },
       {
-        "author_name": "Ralph Goetz",
-        "author_inst": "ISAR Bioscience"
+        "author_name": "Lelio Morricone",
+        "author_inst": "Endocrinology Unit, Clinical Nutrition and Cardiovascular Prevention Service, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
       },
       {
-        "author_name": "Vanessa Mayr",
-        "author_inst": "ISAR Bioscience"
+        "author_name": "Francesco Secchi",
+        "author_inst": "Department of Biomedical Sciences for Health, University of Milano, Milan, Italy."
       },
       {
-        "author_name": "Martin J Lohse",
-        "author_inst": "ISAR Bioscience"
+        "author_name": "Elena Costa",
+        "author_inst": "Service of Laboratory Medicine, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
       },
       {
-        "author_name": "Hans-Peter Holthoff",
-        "author_inst": "ISAR Bioscience"
+        "author_name": "Lorenzo Menicanti",
+        "author_inst": "Scientific Directorate, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy."
       },
       {
-        "author_name": "Martin Ungerer",
-        "author_inst": "ISAR Bioscience"
+        "author_name": "Enzo Nisoli",
+        "author_inst": "Department of Medical Biotechnology and Translational Medicine, Centre for Study and Research on Obesity, University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Michele Olivo Carruba",
+        "author_inst": "Department of Medical Biotechnology and Translational Medicine, Centre for Study and Research on Obesity, University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Federico Ambrogi",
+        "author_inst": "Department of Clinical Sciences and Community Health, University of Milano, Milan, Italy."
+      },
+      {
+        "author_name": "Massimiliano Marco Corsi Romanelli",
+        "author_inst": "Operative Unit of Laboratory Medicine1-Clinical Pathology, Department of Pathology and Laboratory Medicine, IRCCS Policlinico San Donato, San Donato Milanese, M"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "endocrinology"
   },
   {
     "rel_doi": "10.1101/2021.09.09.21263355",
@@ -546553,111 +548760,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.09.13.460111",
-    "rel_title": "Therapeutic efficacy of an oral nucleoside analog of remdesivir against SARS-CoV-2 pathogenesis in mice.",
+    "rel_doi": "10.1101/2021.09.13.460130",
+    "rel_title": "Elucidation of the interactions between SARS-CoV-2 Spike protein and wild and mutant types of IFITM proteins by in silico methods",
     "rel_date": "2021-09-13",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.13.460111",
-    "rel_abs": "The COVID-19 pandemic remains uncontrolled despite the rapid rollout of safe and effective SARS-CoV-2 vaccines, underscoring the need to develop highly effective antivirals. In the setting of waning immunity from infection and vaccination, breakthrough infections are becoming increasingly common and treatment options remain limited. Additionally, the emergence of SARS-CoV-2 variants of concern with their potential to escape therapeutic monoclonal antibodies emphasizes the need to develop second-generation oral antivirals targeting highly conserved viral proteins that can be rapidly deployed to outpatients. Here, we demonstrate the in vitro antiviral activity and in vivo therapeutic efficacy of GS-621763, an orally bioavailable prodrug of GS-441524, the parental nucleoside of remdesivir, which targets the highly conserved RNA-dependent RNA polymerase. GS-621763 exhibited significant antiviral activity in lung cell lines and two different human primary lung cell culture systems. The dose-proportional pharmacokinetic profile observed after oral administration of GS-621763 translated to dose-dependent antiviral activity in mice infected with SARS-CoV-2. Therapeutic GS-621763 significantly reduced viral load, lung pathology, and improved pulmonary function in COVID-19 mouse model. A direct comparison of GS-621763 with molnupiravir, an oral nucleoside analog antiviral currently in human clinical trial, proved both drugs to be similarly efficacious. These data demonstrate that therapy with oral prodrugs of remdesivir can significantly improve outcomes in SARS-CoV-2 infected mice. Thus, GS-621763 supports the exploration of GS-441524 oral prodrugs for the treatment of COVID-19 in humans.",
-    "rel_num_authors": 23,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.13.460130",
+    "rel_abs": "COVID-19 is a viral disease that has been a threat to the whole world since 2019. Although effective vaccines against the disease have been developed, there are still points to be clarified about the mechanism of SARS-CoV-2, which is the causative agent of COVID-19. In this study, we determined the binding energies and the bond types of complexes formed by open (6VYB) and closed (6VXX) forms of the Spike protein of SARS-CoV-2 and wild and mutant forms of IFITM1, IFITM2, and IFITM3 proteins using the molecular docking approach. First, all missense SNPs were found in the NCBI Single Nucleotide Polymorphism database (dbSNP) for IFITM1, IFITM2, and IFITM3 and analyzed with SIFT, PROVEAN, PolyPhen-2, SNAP2, Mutation Assessor, and PANTHER cSNP web-based tools to determine their pathogenicity. When at least four of these analysis tools showed that the SNP had a pathogenic effect on the protein product, this SNP was saved for further analysis. Delta delta G (DDG) and protein stability analysis for amino acid changes were performed in the web-based tools I-Mutant, MUpro, and SAAFEC-SEQ. The structural effect of amino acid change on the protein product was made using the HOPE web-based tool. HawkDock server was used for molecular docking and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis and binding energies of all complexes were calculated. BIOVIA Discovery Studio program was utilized to visualize the complexes. Hydrogen bonds, salt bridges, and non-bonded contacts between Spike and IFITM protein chains in the complexes were detected with the PDBsum web-based tool. The best binding energy among the 6VYB-IFITM wild protein complexes belong to 6VYB-IFITM1 (-46.16 kcal/mol). Likewise, among the 6VXX-IFITM wild protein complexes, the most negative binding energy belongs to 6VXX-IFITM1 (-52.42 kcal/mol). An interesting result found in the study is the presence of hydrogen bonds between the cytoplasmic domain of the IFITM1 wild protein and the S2 domain of 6VYB. Among the Spike-IFITM mutant protein complexes, the best binding energy belongs to the 6VXX-IFITM2 N63S complex (-50.77 kcal/mol) and the worst binding energy belongs to the 6VXX-IFITM3 S50T complex (4.86 kcal/mol).\n\nThe study suggests that IFITM1 protein may act as a receptor for SARS-CoV-2 Spike protein. Assays must be advanced from in silico to in vitro for the determination of the receptor-ligand interactions between IFITM proteins and SARS-CoV-2.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Alexandra Schafer",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "David R Martinez",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "John J Won",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "Fernanado R Moreira",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "Ariane J Brown",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "Kendra L Gully",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "Rao Kalla",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Kwon Chun",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Venice Du Pont",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Darius Babusis",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Jennifer Tang",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Eisuke Murakami",
-        "author_inst": "Gilead Sciences, Inc"
+        "author_name": "Nazli Irmak Giritlioglu",
+        "author_inst": "Yildiz Technical University, Graduate Schools of Science and Engineering"
       },
       {
-        "author_name": "Raju Subramanian",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Kimberly T Barrett",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Blake J. Bleier",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Roy Bannister",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Joy Y. Feng",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "John P. Bilello",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Tomas Cihlar",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Richard L. Mackman",
-        "author_inst": "Gilead Sciences, Inc"
-      },
-      {
-        "author_name": "Stephanie A. Montgomery",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "Ralph S. Baric",
-        "author_inst": "University of North Carolina at Chapel Hill"
-      },
-      {
-        "author_name": "Timothy P. Sheahan",
-        "author_inst": "University of North Carolina at Chapel Hill"
+        "author_name": "Gizem Koprululu Kucuk",
+        "author_inst": "Yeditepe University, Graduate School of Natural and Applied Sciences"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "microbiology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.09.13.459777",
@@ -548243,31 +550366,87 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2021.09.11.459891",
-    "rel_title": "Phylogenetic evidence for asparagine to aspartic acid protein editing of N-glycosylated SARS-CoV-2 viral proteins by NGLY1 deglycosylation/deamidation suggests an unusual vaccination strategy",
+    "rel_doi": "10.1101/2021.09.06.21263168",
+    "rel_title": "Coronavirus disease (COVID-19) associated Mucormycosis: An Anaesthesiologist's Perspective",
     "rel_date": "2021-09-12",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.11.459891",
-    "rel_abs": "Many viral proteins, including multiple SARS-CoV-2 proteins, are secreted via the endoplasmic reticulum, and viral particles are assembled and exported in ER-associated replication compartments. Viral coat proteins such as the SARS-CoV-2 Spike protein are N-glycosylated at NxS/T sites as they enter the ER. N-glycosylated sites in many eukaryotic proteins are deglycosylated by the NGLY1/PNG-1 deglycosylation enzyme which also deamidates the N-glycosylated asparagine to aspartic acid, thus editing the target protein sequence. Proteomic analysis of mammalian cell lines has revealed deamidation of many host N-glycosylated asparagines to aspartic acid by NGLY1/PNG-1 on peptides that are presented by mammalian HLA for immune surveillance. The key client protein for NGLY1/PNG-1 deglycosylation and N to D protein editing was revealed by genetic analysis of C. elegans proteasome regulation to be the intact endoplasmic reticulum-transiting SKN-1A transcription factor. Strikingly, an analysis of cancer cell genetic dependencies for growth revealed that the mammalian orthologue of SKN-1A, NRF1 (also called NFE2L1) is required by a highly correlated set of cell lines as NGLY1/PNG-1, supporting that NGLY1/PNG-1 and NRF1 act in the same pathway. NGLY1/PNG-1 edits N-glycosylated asparagines on the intact SKN-1 protein as it is retrieved by ERAD from the ER to in turn activate the transcription of target proteasomal genes. The normal requirement for NGLY1/PNG-1 editing of SKN-1A can be bypassed by a genomic substituion of N to D in four NxS/T N-glycosylation motifs of SKN-1A. Thus NGLY1/PNG-1-mediated N to D protein editing is more than a degradation step for the key client protein for proteasomal homeostasis in C. elegans or tumor growth in particular mammalian cell lines, SKN-1A/NRF1. In addition, such N to D substitutions in NxS/T N-glycosylation motifs occur in evolution: N to D substitutions are observed in phylogenetic comparisons of SKN-1A between nematode species that diverged hundreds of millions of years ago or of the vertebrate NRF1 between disparate vertebrates. Genomic N to D mutations bypass the many steps in N-glycosylation in the ER and deglycosylation-based editing of N to D, perhaps based on differences in the competency of divergent species for various N-glycosylation or deglycosylation steps.\n\nWe surveyed the N-glycosylation sites in coronavirus proteins for such phylogenetic evidence for N to D protein editing in viral life cycles, and found evidence for preferential N to D residue substitutions in NxS/T N-glycosylation sites in comparisons of the genome sequences of hundreds of coronaviruses. This suggests that viruses use NGLY1/PNG-1 in some hosts, for example humans, to edit particular N-glycosylated residues to aspartic acid, but that in other hosts, often in bats, an N to D substitution mutation in the virus genome is selected. Single nucleotide mutations in Asp or Asn codons can produce viruses with N to D or D to N substitutions that might be selected in different animal hosts from the population of viral variants produced in any previous host. NGLY1/PNG-1 has been implicated in viral immunity in mammalian cell culture, favoring this hypothesis.\n\nBecause of the phylogenetic evidence that the NGLY1/PNG-1 editing of protein sequences has functional importance for SKN-1A/NRF1 and viruses, and because most immunization protocols do not address the probable editing and functional importance of N-glycosylated aspargines to aspartic acid in normal viral infections, we suggest that immunization with viral proteins engineered to substitute D at genomically encoded NxS/T sites of N-glycosylated viral proteins that show a high frequency of N to D substitution in viral phylogeny may enhance immunological response to peptide antigens. Such genomically-edited peptides would not require ER-localization for N-glycosylation or other cell compartment localization for NGLY1/PNG-1 N to D protein editing. In addition, such N to D edited protein vaccines could be produced in bacteria since N-glycosylation and deglycosylation which do not occur in bacteria would no longer be required to immunize with a D-substituted peptide. Bacterially-expressed vaccines would be much lower cost and with fewer failure modes than attenuated viral vaccines or recombinant animal viruses produced in chicken eggs, mammalian tissue culture cells, or delivered by mRNA vectors to the patient directly. Because N to D edited peptides are clearly produced by NGLY1/PNG-1, and may be and presented by mammalian HLA, such peptides may more robustly activate T-cell killing or B-cell maturation to mediate more robust viral immunity.",
-    "rel_num_authors": 3,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.06.21263168",
+    "rel_abs": "PurposeAlthough unexpected airway difficulties are reported in patients with mucormycosis, the literature on airway management in patients with mucormycosis associated with Coronavirus disease is sparse.\n\nMethodsIn this retrospective case record review of 57 patients who underwent surgery for mucormycosis associated with coronavirus disease, we aimed to evaluate the demographics, airway management, procedural data, and mortality records.\n\nResultsForty-one (71.9%) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) patients had a diagnosis of rhino-orbital mucormycosis, and 2 (3.5%) patients had a diagnosis of palatal mucormycosis. A total of 44 (77.2%) patients had co-morbidities. The most common co-morbidities were diabetes mellitus in 42 (73.6%) patients, followed by hypertension in 21 (36.8%) patients, and acute kidney injury in 14 (28.1%) patients. We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 (92.9%) patients. In our study, mortality occurred in 7 (12.3%) patients. The median (range) mortality time was 60 (27-74) days. The median (range) time to hospital discharge was 53.5 (10-85) days. The median [interquartile range] age of discharged versus expired patients was 47.5 [41,57.5] versus 64 [47,70] years (P = 0.04), and median (interquartile range) D-dimer levels in discharged versus expired patients was 364 [213, 638] versus 2448 [408,3301] ng/mL (P = 0.03).\n\nConclusionIn patients undergoing surgery for mucormycosis associated with the coronavirus disease, airway management was easy to slightly difficult in most patients. Perioperative complications can be minimized by taking timely and precautionary measures.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Gary Ruvkun",
-        "author_inst": "Massachusetts General Hospital and Harvard Medical School"
+        "author_name": "Prashant Sirohiya",
+        "author_inst": "National Cancer Institute, All India Institute of Medical Sciences, New Delhi"
       },
       {
-        "author_name": "Ruslan Sadreyev",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Saurabh Vig",
+        "author_inst": "AIIMS"
       },
       {
-        "author_name": "Fei Ji",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Tanmay Mathur",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Jitendra Kumar Meena",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Smriti Panda",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Gitartha Goswami",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Raghav Gupta",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Abhilash Konkimalla",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Dheeraj Kondamudi",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Nishkarsh Gupta",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Brajesh Kumar Ratre",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Ram Singh",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Balbir Kumar",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Anuja Pandit",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Kapil Sikka",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Alok Thakar",
+        "author_inst": "AIIMS"
+      },
+      {
+        "author_name": "Sushma Bhatnagar",
+        "author_inst": "AIIMS"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "new results",
-    "category": "genetics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "anesthesia"
   },
   {
     "rel_doi": "10.1101/2021.09.06.21263173",
@@ -550245,79 +552424,51 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.09.02.21263033",
-    "rel_title": "Epidemic Models for COVID-19 during the First Wave from February to May 2020: a Methodological Review",
+    "rel_doi": "10.1101/2021.09.09.21263328",
+    "rel_title": "COVID-19 Vaccine Concerns about Safety, Effectiveness and Policies in the United States, Canada, Sweden, and Italy among Unvaccinated Individuals",
     "rel_date": "2021-09-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21263033",
-    "rel_abs": "We review epidemiological models for the propagation of the COVID-19 pandemic during the early months of the outbreak: from February to May 2020. The aim is to propose a methodological review that highlights the following characteristics: (i) the epidemic propagation models, (ii) the modeling of intervention strategies, (iii) the models and estimation procedures of the epidemic parameters and (iv) the characteristics of the data used. We finally selected 80 articles from open access databases based on criteria such as the theoretical background, the reproducibility, the incorporation of interventions strategies, etc. It mainly resulted to phenomenological, compartmental and individual-level models. A digital companion including an online sheet, a Kibana interface and a markdown document is proposed. Finally, this work provides an opportunity to witness how the scientific community reacted to this unique situation.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263328",
+    "rel_abs": "Despite the effectiveness of the COVID-19 vaccine, global vaccination distribution efforts have thus far had varying levels of success. Vaccine hesitancy remains a threat to vaccine uptake. This study has four objectives: 1) describe and compare vaccine hesitancy proportions by country; 2) categorize vaccine-related concerns; 3) rank vaccine-related concerns; and 4) compare vaccine-related concerns by country and hesitancy status in four countries- the United States, Canada, Sweden, and Italy. Using the Pollfish survey platform, we sampled 1000 respondents in Canada, Sweden, and Italy and 750 respondents in the United States between May 21-28, 2021. Results showed vaccine related concerns varied across three topical areas- vaccine safety and government control, vaccine effectiveness and population control, and freedom. For each thematic area, the top concern was statistically significantly different in each country and among the hesitant and non-hesitant subsamples within each county. Understanding the specific concerns among individuals when it comes to the COVID-19 vaccine can help to inform public communications and identify which, if any, salient narratives, are global.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Marie Garin",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-91190 Gif-sur-Yvette, France"
-      },
-      {
-        "author_name": "Myrto Limnios",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, F-91190 Gif-sur-Yvette, France"
-      },
-      {
-        "author_name": "Alice Nicolai",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
-      },
-      {
-        "author_name": "Ioannis Bargiotas",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
-      },
-      {
-        "author_name": "Olivier Boulant",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
-      },
-      {
-        "author_name": "Stephen E. Chick",
-        "author_inst": "INSEAD, Boulevard de Constance, 77300 Fontainebleau, France"
-      },
-      {
-        "author_name": "Amir Dib",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
-      },
-      {
-        "author_name": "Theodoros Evgeniou",
-        "author_inst": "INSEAD, Boulevard de Constance, 77300 Fontainebleau, France"
+        "author_name": "Rachael Piltch-Loeb",
+        "author_inst": "Harvard TH Chan School of Public Health"
       },
       {
-        "author_name": "Mathilde Fekom",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
+        "author_name": "Nigel Harriman",
+        "author_inst": "Harvard TH Chan School of Public Health"
       },
       {
-        "author_name": "Argyris Kalogeratos",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
+        "author_name": "Julia Healey",
+        "author_inst": "Harvard TH Chan School of Public Health"
       },
       {
-        "author_name": "Christophe Labourdette",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
+        "author_name": "Marco Bonetti",
+        "author_inst": "Carlo F. Dondena Research Center and Bocconi Institute for Data Science and Analytics, Bocconi University"
       },
       {
-        "author_name": "Anton Ovchinnikov",
-        "author_inst": "INSEAD, Boulevard de Constance, 77300 Fontainebleau, France and Smith School of Business, Queen's University, Kingston, ON, K7L3N6, Canada"
+        "author_name": "Veronica Toffolutti",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Rapha\u00ebl Porcher",
-        "author_inst": "Universit\u00e9 de Paris CRESS, INSERM, INRA, 75004 Paris, France"
+        "author_name": "Marcia Testa",
+        "author_inst": "Harvard TH Chan School of Public Health"
       },
       {
-        "author_name": "Camille Pouchol",
-        "author_inst": "MAP5 Laboratory, FP2M, CNRS FR 2036, Universit\u00e9 de Paris, 75006 Paris, France"
+        "author_name": "Max Su",
+        "author_inst": "Harvard TH Chan School of Public Health"
       },
       {
-        "author_name": "Nicolas Vayatis",
-        "author_inst": "Universit\u00e9 Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli"
+        "author_name": "Elena Savoia",
+        "author_inst": "Harvard TH Chan School of Public Health"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.09.10.459800",
@@ -552383,135 +554534,39 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.09.08.459480",
-    "rel_title": "Targeted isolation of panels of diverse human broadly neutralizing antibodies against SARS-like viruses",
+    "rel_doi": "10.1101/2021.09.08.459260",
+    "rel_title": "Artemisia annua hot-water extracts show potent activity in vitro against Covid-19 variants including delta",
     "rel_date": "2021-09-08",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.08.459480",
-    "rel_abs": "The emergence of current SARS-CoV-2 variants of concern (VOCs) and potential future spillovers of SARS-like coronaviruses into humans pose a major threat to human health and the global economy 1-7. Development of broadly effective coronavirus vaccines that can mitigate these threats is needed 8, 9. Notably, several recent studies have revealed that vaccination of recovered COVID-19 donors results in enhanced nAb responses compared to SARS-CoV-2 infection or vaccination alone 10-13. Here, we utilized a targeted donor selection strategy to isolate a large panel of broadly neutralizing antibodies (bnAbs) to sarbecoviruses from two such donors. Many of the bnAbs are remarkably effective in neutralization against sarbecoviruses that use ACE2 for viral entry and a substantial fraction also show notable binding to non-ACE2-using sarbecoviruses. The bnAbs are equally effective against most SARS-CoV-2 VOCs and many neutralize the Omicron variant. Neutralization breadth is achieved by bnAb binding to epitopes on a relatively conserved face of the receptor binding domain (RBD) as opposed to strain-specific nAbs to the receptor binding site that are commonly elicited in SARS-CoV-2 infection and vaccination 14-18. Consistent with targeting of conserved sites, select RBD bnAbs exhibited in vivo protective efficacy against diverse SARS-like coronaviruses in a prophylaxis challenge model. The generation of a large panel of potent bnAbs provides new opportunities and choices for next-generation antibody prophylactic and therapeutic applications and, importantly, provides a molecular basis for effective design of pan-sarbecovirus vaccines.",
-    "rel_num_authors": 29,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.08.459260",
+    "rel_abs": "Ethnopharmacological relevanceFor millennia in Southeast Asia, Artemisia annua L. was used to treat \"fever\". This medicinal plant is effective against numerous infectious microbial and viral diseases and is used by many global communities as a source of artemisinin derivatives that are first-line drugs to treat malaria.\n\nAim of the StudyThe SARS-CoV-2 (Covid-19) global pandemic has killed millions and evolved numerous variants, with delta being the most transmissible to date and causing break-through infections of vaccinated individuals. We further queried the efficacy of A. annua cultivars against new variants.\n\nMaterials and MethodsUsing Vero E6 cells, we measured anti-SARS-CoV-2 activity of dried-leaf hot-water A. annua extracts of four cultivars, A3, BUR, MED, and SAM, to determine their efficacy against five fully infectious variants of the virus: alpha (B.1.1.7), beta (B.1.351), gamma (P.1), delta (B.1.617.2), and kappa (B.1.617.1).\n\nResultsIn addition to being effective against the original wild type WA1, A. annua cultivars A3, BUR, MED and SAM were also potent against all five variants. IC50 and IC90 values based on measured artemisinin content ranged from 0.3-8.4 M and 1.4-25.0 M, respectively. The IC50 and IC90 values based on dried leaf weight (DW) used to make the tea infusions ranged from 11.0-67.7 g DW and 59.5-160.6 g DW, respectively. Cell toxicity was insignificant at a leaf dry weight of [&le;]50 g in the extract of any cultivar.\n\nConclusionsResults suggest that oral consumption of A. annua hot-water extracts (tea infusions), could provide a cost-effective therapy to help stave off the rapid global spread of these variants, buying time for broader implementation of vaccines.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Wan-ting He",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Rami Musharrafieh",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Ge Song",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Katharina Dueker",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Longping V. Tse",
-        "author_inst": "Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA."
-      },
-      {
-        "author_name": "David R. Martinez",
-        "author_inst": "Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA."
-      },
-      {
-        "author_name": "Alexandra Schafer",
-        "author_inst": "Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA."
-      },
-      {
-        "author_name": "Sean Callaghan",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Peter Yong",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Nathan Beutler",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Jonathan L. Torres",
-        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Reid M. Volk",
-        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Panpan Zhou",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Meng Yuan",
-        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Hejun Liu",
-        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Fabio Anzanello",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Tazio Capozzola",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Mara Parren",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Elijah Garcia",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Stephen A. Rawlings",
-        "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Davey M. Smith",
-        "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Ian A. Wilson",
-        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Yana Safonova",
-        "author_inst": "Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA"
-      },
-      {
-        "author_name": "Andrew B. Ward",
-        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
-      },
-      {
-        "author_name": "Thomas Rogers",
-        "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA."
+        "author_name": "Manoj S Nair",
+        "author_inst": "Columbia University"
       },
       {
-        "author_name": "Ralph S. Baric",
-        "author_inst": "Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA."
+        "author_name": "Yaoxing Huang",
+        "author_inst": "Columbia University"
       },
       {
-        "author_name": "Lisa E. Gralinski",
-        "author_inst": "Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA."
+        "author_name": "David A Fidock",
+        "author_inst": "Columbia University"
       },
       {
-        "author_name": "Dennis R. Burton",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+        "author_name": "Melissa Towler",
+        "author_inst": "Worcester Polytechnic Institute"
       },
       {
-        "author_name": "Raiees Andrabi",
-        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+        "author_name": "Pamela Weathers",
+        "author_inst": "Worcester Polytechnic Institute"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.09.08.459464",
@@ -554169,31 +556224,59 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.09.03.21257002",
-    "rel_title": "Long COVID: Assessment of Neuropsychiatric Symptoms in Children and Adolescents - A Clinical Data Analysis",
+    "rel_doi": "10.1101/2021.09.02.21263038",
+    "rel_title": "COVID-19 Vaccine Efficacy in a Diverse Urban Healthcare Worker Population",
     "rel_date": "2021-09-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.03.21257002",
-    "rel_abs": "COVID-19 infections in adults often result in medical, neuropsychiatric, and unspecific symptoms, called Long COVID, and the premorbid functional status cannot be achieved. Regarding the course in children and adolescents, however, reliable data are not yet available.\n\nObjective380 children and adolescents/young adults aged between 6 and 21 years, being treated for various psychiatric diseases in an outpatient clinical service, were examined for COVID-19 infections and Long COVID symptoms following a structured protocol.\n\nResultsThree patients had COVID-19; one patient had symptoms of Long COVID in his medical history, but they could not be objectivized in an in-depth neuropsychiatric and neuropsychological assessment.\n\nConclusionsLong COVID seems to occur rarely in children and adolescents. Objectivizing the symptoms is a difficult task that requires various diagnostic considerations.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21263038",
+    "rel_abs": "ObjectiveTo investigate COVID-19 vaccine efficacy (VE) among healthcare workers (HCWs) in an ethnically diverse community healthcare system, during its initial immunization campaign.\n\nMethodsHCWs of the system were retrospectively included from the beginning of a COVID-19 vaccination program (December 16, 2020) until March 31, 2021. Those with a prior COVID-19 infection before December 15 were excluded. The Occupational Health department of the system ran a COVID-19 screening and testing referral program for workers, consistently throughout the study period. A master database had been established and updated comprising of the demographics, COVID-19 PCR assays, and vaccinations of each HCW. Andersen-Gill extension of the Cox models were built to estimate the VE of fully/partially vaccinated person-days at risk.\n\nResultsAmong the 4317 eligible HCWs, 3249 (75%) received any vaccination during the study period. Vaccinated HCWs were older, less likely to be Black/African American, Hispanic/Latino or identify as two or more races, and more likely to be medical providers. After adjusting for age, sex, race, and the statewide background incidence at the time of vaccination, we observed a VE of 80.2% (95% CI: 57.5-90.8%) for [greater double equals]14 days after the first dose of Pfizer/Moderna, and 95.5% (95% CI: 88.2-98.3%) among those fully vaccinated (i.e. [greater double equals]14 days after the second dose of Pfizer/Moderna or the single dose of J&J/Janssen).\n\nConclusionCOVID-19 vaccine effectiveness in the real world is promising, and these data in concert with culturally appropriate may decrease vaccine hesitancy.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Jan Froelich",
-        "author_inst": "Central Institute of Mental Health Department of Child and Adolescent Psychiatry, University of Heidelberg - Faculty of Medicine Mannheim"
+        "author_name": "Eirini Iliaki",
+        "author_inst": "Occupational Medicine, Cambridge Health Alliance, Harvard Medical School, Cambridge MA, USA"
       },
       {
-        "author_name": "Tobias Banaschewski",
-        "author_inst": "Central Institute of Mental Health Department of Child and Adolescent Psychiatry, University of Heidelberg - Faculty of Medicine Mannheim"
+        "author_name": "Fan-Yun Lan",
+        "author_inst": "Occupational Medicine, Cambridge Health Alliance, Harvard Medical School, Cambridge MA, USA"
       },
       {
-        "author_name": "Annabelle Ulmer",
-        "author_inst": "Practice for Child and Adolescent Psychiatry and Psychotherapy Dr. Dr. Jan Froelich"
+        "author_name": "Costas A. Christophi",
+        "author_inst": "Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Limassol, Cyprus"
+      },
+      {
+        "author_name": "Guido Guidotti",
+        "author_inst": "Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, MA, USA"
+      },
+      {
+        "author_name": "Alexander D. Jobrack",
+        "author_inst": "Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, MA, USA"
+      },
+      {
+        "author_name": "Jane Buley",
+        "author_inst": "Occupational Medicine, Cambridge Health Alliance, Harvard Medical School, Cambridge MA, USA"
+      },
+      {
+        "author_name": "Neetha Nathan",
+        "author_inst": "Occupational Medicine, Cambridge Health Alliance, Harvard Medical School, Cambridge MA, USA"
+      },
+      {
+        "author_name": "Rebecca Osgood",
+        "author_inst": "Pathology, Cambridge Health Alliance, Harvard Medical School, Cambridge MA, USA"
+      },
+      {
+        "author_name": "Lou Ann Bruno-Murtha",
+        "author_inst": "Infection Prevention and Infectious Diseases, Cambridge Health Alliance, Harvard Medical School, Cambridge MA, USA"
+      },
+      {
+        "author_name": "Stefanos N. Kales",
+        "author_inst": "Occupational Medicine, Cambridge Health Alliance, Harvard Medical School, Cambridge MA, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.09.03.21263076",
@@ -555659,55 +557742,87 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.09.03.458854",
-    "rel_title": "The genetics of eating behaviors: research in the age of COVID-19",
-    "rel_date": "2021-09-05",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.03.458854",
-    "rel_abs": "How much pleasure we take in eating is more than just how much we enjoy the taste of food. Food involvement - the amount of time we spend on food beyond the immediate act of eating and tasting - is key to the human food experience. We took a biological approach to test whether food-related behaviors, together capturing food involvement, have genetic components and are partly due to inherited variation. We collected data via an internet survey from a genetically informative sample of 419 adult twins (114 monozygotic twin pairs, 31 dizygotic twin pairs, and 129 singletons). Because we conducted this research during the pandemic, we also ascertained how many participants had experienced COVID-19-associated loss of taste and smell. Since these respondents had previously participated in research in person, we measured their level of engagement to evaluate the quality of their online responses. Additive genetics explained 16-44% of the variation in some measures of food involvement, most prominently various aspects of cooking, suggesting some features of the human food experience may be inborn. Other features reflected shared (early) environment, captured by respondents twin status. About 6% of participants had a history of COVID-19 infection, many with transitory taste and smell loss, but all but one had recovered before the survey. Overall, these results suggest that people may have inborn as well as learned variations in their involvement with food. We also learned to adapt to research during a pandemic by considering COVID-19 status and measuring engagement in online studies of human eating behavior.",
-    "rel_num_authors": 9,
+    "rel_doi": "10.1101/2021.08.27.21262422",
+    "rel_title": "Characteristics associated with COVID-19 vaccine uptake among adults in England (08 December to 17 May 2021)",
+    "rel_date": "2021-09-04",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.27.21262422",
+    "rel_abs": "ObjectiveTo determine characteristics associated with COVID-19 vaccine coverage among individuals aged 50 years and above in England since the beginning of the programme.\n\nDesignObservational cross-sectional study assessed by logistic regression and mean prevalence margins.\n\nSettingCOVID-19 vaccinations delivered in England from 08 December 2020 - 17 May 2021.\n\nParticipants30,624,257/ 61,967,781 (49.4%) and 17,360,045/ 61,967,781 (28.1%) individuals in England were recorded as vaccinated in the National Immunisation Management System with a first dose and a second dose of a COVID-19 vaccine, respectively.\n\nInterventionsVaccination status with COVID-19 vaccinations.\n\nMain Outcome MeasuresProportion, adjusted odds ratios and mean prevalence margins for individuals not vaccinated with dose 1 among those aged 50-69 years old and dose 1 and 2 among those aged 70 years old and above.\n\nResultsAmong individuals aged 50 years and above, Black/African/Caribbean ethnic group was the least likely of all ethnic groups to be vaccinated with dose 1 of the COVID-19 vaccine. However, among those aged 70 years and above, the odds of not having dose 2 was 5.53 (95% CI 5.42 to 5.63) and 5.36 (90% CI 5.29 to 5.43) greater among Pakistani and Black/African/Caribbean compared to White British ethnicity, respectively. The odds of not receiving dose 2 was 1.18 (95% CI 1.16 to 1.20) higher among individuals who lived in a care home compared to those who did not. This was the opposite to that observed for dose 1, where the odds of not being vaccinated was significantly higher among those not living in a care home (0.89 (95% CI 0.87 to 0.91)).\n\nConclusionsWe found that there are characteristics associated with low COVID-19 vaccine coverage. Inequalities, such as ethnicity are a major contributor to suboptimal coverage and tailored interventions are required to improve coverage and protect the population from SARS-CoV-2.\n\nArticle summaryO_ST_ABSStrengths and Limitations of this studyC_ST_ABSO_LIThis is the is the first study assessing characteristics associated with COVID-19 vaccine coverage for all individuals aged 50 years and above in England.\nC_LIO_LIThis study uses data from the National Immunisation Management System (NIMS) which is based on all individuals in England with a registered NHS number.\nC_LIO_LIThis centralised national system captures individual level data for both vaccination status and demographic characteristics and allows for linkage to other datasets such as health care worker and care home resident status.\nC_LIO_LIThis study does not include those without an NHS number and, therefore, it is possible we have underestimated the number of vaccines delivered and odds of not being vaccinated for characteristics such as ethnic groups where we have seen the greatest impact.\nC_LIO_LIResidual errors in data entry on the point of care apps at the vaccination sites may have also occurred, though these errors are not likely to be widespread.\nC_LI",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Mackenzie E. Hannum",
-        "author_inst": "Monell Chemical Senses Center"
+        "author_name": "Elise Tessier",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Cailu Lin",
-        "author_inst": "Monell Chemical Senses Center"
+        "author_name": "Yuma Rai",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Katherine A Bell",
-        "author_inst": "Monell Chemical Senses Center"
+        "author_name": "Eleanor Clarke",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Aurora K Toskala",
-        "author_inst": "Monell Chemical Senses Center"
+        "author_name": "Anissa Lakhani",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Riley R Koch",
-        "author_inst": "Monell Chemical Senses Center"
+        "author_name": "Camille Tsang",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Tharaka Galaniha",
-        "author_inst": "University of Massachusetts Amherst"
+        "author_name": "Ashley Makwana",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Alissa Nolden",
-        "author_inst": "University of Massachusetts Amherst"
+        "author_name": "Heather Heard",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Danielle R. Reed",
-        "author_inst": "Monell Chemical Senses Center"
+        "author_name": "Tim Rickeard",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Paule Valery Joseph",
-        "author_inst": "National Institutes of Health"
+        "author_name": "Shreya Lakhani",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Partho Roy",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Michael Edelstein",
+        "author_inst": "Bar Ilan University"
+      },
+      {
+        "author_name": "Mary Ramsay",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Jamie Lopez Bernal",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Joanne White",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Nick Andrews",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Colin Campbell",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Julia Stowe",
+        "author_inst": "Public Health England"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "genetics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.09.03.458951",
@@ -557621,35 +559736,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.30.21262341",
-    "rel_title": "Modelling the potential role of super spreaders on COVID-19 transmission dynamics",
+    "rel_doi": "10.1101/2021.09.01.458644",
+    "rel_title": "Co-expression analysis to identify key modules and hub genes associated with COVID19 in Platelets",
     "rel_date": "2021-09-02",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.30.21262341",
-    "rel_abs": "Superspreading phenomenon has been observed in many infectious diseases and contributes significantly to public health burden in many countries. Superspreading events have recently been reported in the transmission of the COVID-19 pandemic. The present study uses a set of nine ordinary differential equations to investigate the impact of superspreading on COVID-19 dynamics. The model developed in this study addresses the heterogeineity in infectiousness by taking into account two forms of transmission rate functions for superspreaders based on clinical (infectivity level) and social or environmental (contact level). The basic reproduction number has been derived and the contribution of each infectious compartment towards the generation of new COVID-19 cases is ascertained. Data fitting was performed and parameter values were estimated within plausible ranges. Numerical simulations performed suggest that control measures that decrease the effective contact radius and increase the transmission rate exponent will be greatly beneficial in the control of COVID-19 in the presence of superspreading phenomena.",
-    "rel_num_authors": 4,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.01.458644",
+    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWThe severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is a highly contagious virus that causes a severe respiratory disease known as Corona virus disease 2019 (COVID19). Indeed, COVID19 increases the risk of cardiovascular occlusive/thrombotic events and is linked to poor outcomes. The pathophysiological processes underlying COVID19-induced thrombosis are complex, and remain poorly understood. To this end, platelets play important roles in regulating our cardiovascular system, including via contributions to coagulation and inflammation. There is an ample of evidence that circulating platelets are activated in COVID19 patients, which is a primary driver of the thrombotic outcome observed in these patients. However, the comprehensive molecular basis of platelet activation in COVID19 disease remains elusive, which warrants more investigation. Hence, we employed gene co-expression network analysis combined with pathways enrichment analysis to further investigate the aforementioned issues. Our study revealed three important gene clusters/modules that were closely related to COVID19. Furthermore, enrichment analysis showed that these three modules were mostly related to platelet metabolism, protein translation, mitochondrial activity, and oxidative phosphorylation, as well as regulation of megakaryocyte differentiation, and apoptosis, suggesting a hyperactivation status of platelets in COVID19. We identified the three hub genes from each of three key modules according to their intramodular connectivity value ranking, namely: COPE, CDC37, CAPNS1, AURKAIP1, LAMTOR2, GABARAP MT-ND1, MT-ND5, and MTRNR2L12. Collectively, our results offer a new and interesting insight into platelet involvement in COVID19 disease at the molecular level, which might aid in defining new targets for treatment of COVID19-induced thrombosis.\n\nkey pointsO_LICo-expression analysis of platelet RNAseq from COVID19 patients show distinct clusters of genes (modules) that are highly correlated to COVID19 disease.\nC_LIO_LIIdentifying these modules might help in understanding the mechanism of thrombosis in COVID19 patients\nC_LI",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Josiah Mushanyu",
-        "author_inst": "University of zimbabwe"
+        "author_name": "Ahmed B. Alarabi",
+        "author_inst": "Department of Pharmacy Practice, Irma Lerma Rangel College of Pharmacy, Texas A&M University, Kingsville, Texas, USA"
       },
       {
-        "author_name": "Williams Chukwu",
-        "author_inst": "University of Johannesburg"
+        "author_name": "Attayeb Mohsen",
+        "author_inst": "Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research (ArCHER), National Institutes of Biomedical Innovation, Health a"
       },
       {
-        "author_name": "Farai Nyabadza",
-        "author_inst": "University of Johannesburg"
+        "author_name": "Kenji Mizuguchi",
+        "author_inst": "Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research (ArCHER), National Institutes of Biomedical Innovation, Health a"
+      },
+      {
+        "author_name": "Fatima Z. Alshbool",
+        "author_inst": "Department of Pharmacy Practice, Irma Lerma Rangel College of Pharmacy, Texas A&M University, Kingsville, Texas, USA."
       },
       {
-        "author_name": "Gift Muchatibaya",
-        "author_inst": "university of Zimbabwe"
+        "author_name": "Fadi T. Khasawneh",
+        "author_inst": "Department of Pharmaceutical Sciences, Irma Lerma Rangel College of Pharmacy, Texas A&M University, Kingsville, Texas, USA."
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "systems biology"
   },
   {
     "rel_doi": "10.1101/2021.09.01.458475",
@@ -559583,37 +561702,21 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.24.21262245",
-    "rel_title": "Symptomatology associated with the diffusion of the SARS-CoV-2 Lambda variant in Peru: An infodemiologic analysis",
+    "rel_doi": "10.1101/2021.08.23.21262413",
+    "rel_title": "Towards the global equilibrium of COVID-19: statistical analysis of country-level data",
     "rel_date": "2021-08-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262245",
-    "rel_abs": "The SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) Lambda variant rapidly diffused across Peru following its identification in December 2020, and had now spread worldwide. In this study, we investigated infodemiologic trends in symptomatology associated with the Coronavirus Disease 2019 (COVID-19) following the spread of SARS-CoV-2 Lambda variant in Peru, enabling infodemiologic surveillance of SARS-CoV-2 in regions with high circulation of this new variant. Weekly Google Trends scores were obtained for key symptom keywords between March 1st, 2020 and July 4th, 2021, whilst case count data were obtained from Peruvian Ministry of Health. Multiple time series linear regression was used to assess trends in each score series, using the week of December 27th as cutoff for emergence of the Lambda variant. The significance of such trends was tested for each time period, before and after the cutoff date. A total 2,075,484 confirmed SARS-CoV-2 infections in Peru in relation to Google Trends data were analyzed. After Lambda variant emergence, searches for \"diarrhea\" demonstrated a change from a negative to positive correlation with weekly case counts and anticipated dynamic changes in case counts by 1-5 weeks. Searches for \"shortness of breath\" and \"headache\" remained consistently positively correlated to weekly case counts before and after Lambda emergence. No changes in searches for other common cold symptoms were observed, while no specific trends were observed for \"taste loss\" or \"smell loss\". Diarrhea, headache, and shortness of breath appear to be the most important symptoms for infodemiologic tracking the current outbreak in Peru and other regions with high circulation of SARS-CoV-2 Lambda variant.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262413",
+    "rel_abs": "ObjectivesThe time-varying effect of COVID-19 on a population of a given country or territory can be measured by the Reproduction Number (R) and the Case Fatality Rate (CFR). In our study, we explore the dynamics of these two measures to test whether the virus has reached its equilibrium point and to identify the main factors explaining the current R and CFR variability across countries.\n\nDesignA retrospective study of publicly available country-level data.\n\nSettingFifty countries having the highest number of confirmed COVID-19 cases at the end of September 2021.\n\nParticipantsAggregated data including 213 976 306 COVID-19 cases confirmed in the selected fifty countries from the start of the epidemic to September 30, 2021.\n\nPrimary and secondary outcome measuresThe daily values of COVID-19 R and CFR measures were estimated using country-level data from the Our World in Data website.\n\nResultsThe mean values of country-level moving averages of R and CFR went down from 1.118 and 6.3%, respectively, on June 30, 2020 to 1.083 and 3.6% on September 30, 2020 and to 1.015 and 1.8% by September 30, 2021. In parallel, the 10% to 90% inter-percentile range of R and CFR moving averages decreased from 0.288 and 13.3%, respectively, on June 30, 2020, to 0.151 and 7.7% on September 30, 2020, and to 0.107 and 3.3% by September 30, 2021. According to a comparison of the country-level 180-day moving averages of R and CFR calculated on September 30, 2021, an increase of 1% in the Delta variant share is associated with an increase of 0.0009 (95% CI 0.000 to 0.002) in the average Reproduction Number R, while an increase of 1% in the total percentage of confirmed COVID-19 cases per countrys population is associated with a decrease of 0.005 (95% CI 0.000 to 0.010) in the average R. Also, an increase of 1% in the total percentage of fully vaccinated people per countrys population is associated with a decrease of 0.04% (95% CI 0.01% to 0.06%) in the average CFR. Other virological, demographic, economic, immunization, or stringency factors were not statistically significantly associated with either R or CFR across the explored countries.\n\nConclusionsThe slow decrease in the country-level moving averages of R, approaching the level of 1.0 and accompanied by repeated outbreaks (\"waves\") in various countries, may indicate that COVID-19 has reached its point of a stable endemic equilibrium. A regression analysis implies that only a prohibitively high level of herd immunity (about 63%) may stop the endemic by reaching a stable disease-free equilibrium. It also appears that fully vaccinating about 70% of a countrys population should be sufficient for bringing the CFR close to the level of a seasonal flu (about 0.1%). Thus, while the currently available vaccines prove to be effective in reducing the mortality from the existing COVID-19 variants, they are unlikely to stop the spread of the virus in the foreseeable future. It is noteworthy that no statistically significant effects of government measures restricting the peoples behavior (such as lockdowns) were found in the analyzed data.\n\nStrengths and limitations of this studyO_LIIn this study, we have explored the long-term trends in country-level Reproduction Number and the Case Fatality Rate of COVID-19.\nC_LIO_LIOur study also investigated the long-term statistical dependence of the COVID-19 Reproduction Number and the Case Fatality Rate on epidemiological, demographic, economic, immunization, and government policy factors in each country.\nC_LIO_LIThe findings of this study may have important implications for the health policy-makers worldwide.\nC_LIO_LIThe officially reported numbers of daily COVID-19 confirmed cases depend on the local testing policy and usually underestimate the true number of carriers in the population.\nC_LIO_LIThe officially reported numbers of daily COVID-19 deaths in some countries may include all deceased individuals who tested positive for COVID-19, disregarding their actual cause of death, and exclude victims who were not tested for COVID-19.\nC_LI",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Brandon Michael Henry",
-        "author_inst": "Clinical Laboratory, Division of Nephrology and Hypertension, Cincinnati Children Hospital Medical Center, Cincinnati, OH, USA"
-      },
-      {
-        "author_name": "Maria Helena Santos de Oliveira",
-        "author_inst": "Department of Biostatistics, State University of Maringa, Maringa, Brazil"
-      },
-      {
-        "author_name": "Thais Barbosa de Oliveira",
-        "author_inst": "Department of Biostatistics, State University of Maringa, Maringa, Brazil"
-      },
-      {
-        "author_name": "Kin Israel Notarte",
-        "author_inst": "Faculty of Medicine and Surgery, University of Santo Tomas, Manila 1008, Philippines"
-      },
-      {
-        "author_name": "Giuseppe Lippi",
-        "author_inst": "Section of Clinical Biochemistry, Department of Neuroscience, Biomedicine and Movement, University of Verona, Verona, Italy"
+        "author_name": "Mark Last",
+        "author_inst": "Ben-Gurion University of the Negev"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -561749,31 +563852,35 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.08.20.21261687",
-    "rel_title": "Randomized trials on non-pharmaceutical interventions for COVID-19 as of August 2021: a meta-epidemiological analysis",
+    "rel_doi": "10.1101/2021.08.29.458083",
+    "rel_title": "Allosteric regulation of 3CL protease of SARS-CoV-2 and SARS-CoV observed in the crystal structure ensemble",
     "rel_date": "2021-08-30",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.20.21261687",
-    "rel_abs": "BackgroundNumerous non-pharmaceutical interventions (NPIs) were taken worldwide to contain the spread of the COVID-19 pandemic. We aimed at providing an overview of randomized trials assessing NPIs to prevent COVID-19.\n\nMethodsWe included all randomized trials assessing NPIs to prevent COVID-19 in any country and setting registered in ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform using the COVID-evidence platform (until 17 August 2021). We searched for corresponding publications in MEDLINE/PubMed, Google Scholar, the Living Overview of Evidence platform (L-OVE), and the Cochrane COVID-19 registry as well as for results posted in registries.\n\nResultsWe identified 41 randomized trials. Of them, 11 were completed (26.8%) including 7 with published results. The 41 trials planned to recruit a median of 1,700 participants (IQR, 588 to 9,500, range 30 to 35,256,399) with a median planned duration of 8 months (IQR, 3 to 14, range 1 to 24). Most came from the United States (n=11, 26.8%). The trials mostly assessed protective equipment (n=11, 26.8%), COVID-19-related information and education programs (n=9, 22.0%), access to mass events under specific safety measures (n=5, 12.2%), testing and screening strategies (n=5, 12.2%), and hygiene management (n=5, 12.2%).\n\nConclusionsWorldwide, 41 randomized trials assessing NPIs have been initiated with published results available to inform policy decisions for only 7 of them. A long-term research agenda including behavioral, environmental, social, and systems level interventions is urgently needed to guide policies and practices in the current and future public health emergencies.",
-    "rel_num_authors": 3,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.29.458083",
+    "rel_abs": "The 3C-like protease (3CLpro) of SARS-CoV-2 is a potential therapeutic target for COVID-19. Importantly, it has an abundance of structural information solved as a complex with various drug candidate compounds. Collecting these crystal structures (83 Protein Data Bank (PDB) entries) together with those of the highly homologous 3CLpro of SARS-CoV (101 PDB entries), we constructed the crystal structure ensemble of 3CLpro to analyze the dynamic regulation of its catalytic function. The structural dynamics of the 3CLpro dimer observed in the ensemble were characterized by the motions of four separate loops (the C-loop, E-loop, H-loop, and Linker) and the C-terminal domain III on the rigid core of the chymotrypsin fold. Among the four moving loops, the C-loop (also known as the oxyanion binding loop) causes the order (active)-disorder (collapsed) transition, which is regulated cooperatively by five hydrogen bonds made with the surrounding residues. The C-loop, E-loop, and Linker constitute the major ligand binding sites, which consist of a limited variety of binding residues including the substrate binding subsites. Ligand binding causes a ligand size dependent conformational change to the E-loop and Linker, which further stabilize the C-loop via the hydrogen bond between the C-loop and E-loop. The T285A mutation from SARS-CoV 3CLpro to SARS-CoV-2 3CLpro significantly closes the interface of the domain III dimer and allosterically stabilizes the active conformation of the C-loop via hydrogen bonds with Ser1 and Gly2; thus, SARS-CoV-2 3CLpro seems to have increased activity relative to that of SARS-CoV 3CLpro.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Julian Hirt",
-        "author_inst": "Department of Clinical Research, University Hospital Basel, University of Basel"
+        "author_name": "Akinori Kidera",
+        "author_inst": "Yokohama City University"
       },
       {
-        "author_name": "Perrine Janiaud",
-        "author_inst": "Department of Clinical Research, University Hospital Basel, University of Basel"
+        "author_name": "Kei Moritsugu",
+        "author_inst": "Yokohama City University"
       },
       {
-        "author_name": "Lars G. Hemkens",
-        "author_inst": "Department of Clinical Research, University Hospital Basel, University of Basel"
+        "author_name": "Toru Ekimoto",
+        "author_inst": "Yokohama City University"
+      },
+      {
+        "author_name": "Mitsunori Ikeguchi",
+        "author_inst": "Yokohama City University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2021.08.29.21262789",
@@ -563451,33 +565558,29 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.08.25.21262636",
-    "rel_title": "Impact of Covid-19 Pandemic on Racial/Ethnic Differences in Mortality by Cause of Death",
+    "rel_doi": "10.1101/2021.08.25.21262614",
+    "rel_title": "Democratic governance and excess mortality during the COVID-19 pandemic",
     "rel_date": "2021-08-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.25.21262636",
-    "rel_abs": "ObjectivesTo quantify changes in all-cause and cause-specific mortality by race and ethnicity between 2019 and 2020.\n\nMethodsUsing 2019 and 2020 provisional death counts from the National Center for Health Statistics and population estimates from the US Census Bureau, we estimate age-standardized death rates by race/ethnicity and attribute changes in mortality to various causes of death. We also examine how patterns of change across racial/ethnic groups vary by age and sex.\n\nResultsCovid-19 death rates in 2020 were highest in the Hispanic community whereas Black individuals had the largest increase in all-cause mortality between 2019 and 2020. Increases in mortality from heart disease, diabetes, and external causes of death accounted for the adverse trend in all-cause mortality within the Black population. Percentage increases in all-cause mortality were similar for men and women and for ages 25-64 and 65+ for Black and White populations, but increases were greatest for working-aged men among the Hispanic population.\n\nConclusionsExamining increases in non-Covid-19 causes of death is essential for fully capturing both the direct and indirect impact of the Covid-19 pandemic on racial/ethnic mortality disparities.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.25.21262614",
+    "rel_abs": "BackgroundExcess mortality has been used to assess the health impact of COVID-19 across countries. Democracies aim to build trust in government and enable checks and balances on decision-making, which may be useful in a pandemic. On the other hand, democratic governments have been criticised as slow to enforce restrictive policies and being overly influenced by public opinion. This study sought to understand whether strength of democratic governance is associated with the variation in excess mortality observed across countries during the pandemic.\n\nMethodsThrough linking open-access datasets we constructed univariable and multivariable linear regression models investigating the association between country EIU Democracy Index (representing strength of democratic governance on a scale of 0 to 10) and excess mortality rates, from February 2020 to May 2021. We stratified our analysis into high-income and low and middle-income country groups and adjusted for several important confounders.\n\nResultsAcross 78 countries, the mean EIU democracy index was 6.74 (range 1.94 to 9.81) and the mean excess mortality rate was 128 per 100,000 (range -55 to 503 per 100,000). A one-point increase in EIU Democracy Index was associated with a decrease in excess mortality of 26.3 per 100,000 (p=0.002), after accounting for COVID-19 cases, age [&ge;] 65, gender, prevalence of cardiovascular disease, universal health coverage and the strength of early government restrictions. This association was particularly strong in high-income countries ({beta} -47.5, p<0.001) but non-significant in low and middle-income countries ({beta} -10.8, p=0.40).\n\nConclusionsSocio-political factors related to the way societies are governed have played an important role in mitigating the overall health impact of COVID-19. Given the omission of such considerations from outbreak risk assessment tools, and their particular significance in high-income countries rated most highly by such tools, this study strengthens the case to broaden the scope of traditional pandemic risk assessment.\n\nKey MessagesO_ST_ABSWhat is already known?C_ST_ABSO_LIPrevious studies have found that as countries become more democratic they experience a decline in rates of infant and child mortality, infections such as tuberculosis, and non-communicable diseases.\nC_LIO_LIIn Europe, more democratic countries were initially more reluctant to adopt restrictive COVID-19 measures that could conflict with democratic principles, including lockdowns.\nC_LI\n\nWhat are the new findings?O_LIWe found that a one-point increase in EIU Democracy Index was associated with a decrease in excess mortality of 26.3 per 100,000 (p=0.002), after accounting for several confounders including demographics, numbers of cases and the strength of early government responses.\nC_LIO_LIThis association was particularly significant in high-income countries ({beta} - 47.5, p<0.001), suggesting that way societies are governed has played an important role in mitigating the impact of COVID-19.\nC_LI\n\nWhat do the new findings imply?O_LIGiven the omission of social, political and cultural considerations from outbreak risk assessment tools, and criticisms of such tools that have failed to accurately reflect the observed impact of the pandemic across high-income countries, this study builds on the case to broaden of the scope of traditional pandemic risk assessment.\nC_LIO_LIFuture research into the mechanisms underlying our findings will help to understand and address the complex and deep-rooted vulnerabilities countries face in a protracted and large-scale public health emergency.\nC_LI",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Anneliese N. Luck",
-        "author_inst": "Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA"
-      },
-      {
-        "author_name": "Samuel H. Preston",
-        "author_inst": "Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA"
+        "author_name": "Vageesh Jain",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Irma T. Elo",
-        "author_inst": "Department of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, USA"
+        "author_name": "Jonathan Clarke",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Andrew C. Stokes",
-        "author_inst": "Department of Global Health, Boston University School of Public Health, Boston, MA, USA"
+        "author_name": "Thomas Beaney",
+        "author_inst": "Imperial College London"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -565697,53 +567800,61 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.08.23.21262477",
-    "rel_title": "Low risk of SARS-CoV-2 transmission via fomite, even in cold-chain",
+    "rel_doi": "10.1101/2021.08.23.21262499",
+    "rel_title": "Comparative analyses of all FDA EUA-approved rapid antigen tests and RT-PCR for COVID-19 quarantine and surveillance-based isolation",
     "rel_date": "2021-08-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262477",
-    "rel_abs": "BackgroundCountries continue to debate the need for decontamination of cold-chain food packaging to reduce possible SARS-CoV-2 fomite transmission among workers. While laboratory-based studies demonstrate persistence of SARS-CoV-2 on surfaces, the likelihood of fomite-mediated transmission under real-life conditions is uncertain.\n\nMethodsUsing a quantitative risk assessment model, we simulated in a frozen food packaging facility 1) SARS-CoV-2 fomite-mediated infection risks following worker exposure to contaminated plastic packaging; and 2) reductions in these risks attributed to masking, handwashing, and vaccination.\n\nFindingsIn a representative facility with no specific interventions, SARS-CoV-2 infection risk to a susceptible worker from contact with contaminated packaging was 2{middle dot}8 x 10-3 per 1h-period (95%CI: 6{middle dot}9 x 10-6, 2{middle dot}4 x 10-2). Implementation of standard infection control measures, handwashing and masks (9{middle dot}4 x 10-6 risk per 1h-period, 95%CI: 2{middle dot}3 x 10-8, 8{middle dot}1 x 10-5), substantially reduced risk (99{middle dot}7%). Vaccination of the susceptible worker (two doses Pfizer/Moderna, vaccine effectiveness: 86-99%) combined with handwashing and masking reduced risk to less than 1{middle dot}0 x 10-6. Simulating increased infectiousness/transmissibility of new variants (2-, 10-fold viral shedding) among a fully vaccinated workforce, handwashing and masks continued to mitigate risk (2{middle dot}0 x 10-6 -1{middle dot}1 x 10-5 risk per 1h-period). Decontamination of packaging in addition to these interventions reduced infection risks to below the 1{middle dot}0 x 10-6 risk threshold.\n\nInterpretationFomite-mediated SARS-CoV-2 infection risks were very low under cold-chain conditions. Handwashing and masking provide significant protection to workers, especially when paired with vaccination.\n\nFundingU.S. Department of Agriculture",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.23.21262499",
+    "rel_abs": "BackgroundRapid antigen (RA) tests are being increasingly employed to detect SARS-CoV-2 infections in quarantine and surveillance. Prior research has focused on RT-PCR testing, a single RA test, or generic diagnostic characteristics of RA tests in assessing testing strategies.\n\nMethodsFor 18 RA tests with emergency use authorization from the United States of America FDA and an RT-PCR test, we conducted a comparative analysis of the post-quarantine transmission, the effective reproduction number during serial testing, and the false-positive rates. To quantify the extent of transmission, we developed an analytical mathematical framework informed by COVID-19 infectiousness, test specificity, and temporal diagnostic sensitivity data.\n\nResultsWe demonstrate that the relative effectiveness of RA and RT-PCR tests in reducing post-quarantine transmission depends on the quarantine duration and the turnaround time of testing results. For quarantines of two days or shorter, conducting a RA test on exit from quarantine reduces onward transmission more than a single RT-PCR test (with a 24-h delay) conducted upon exit. Applied to a complementary approach of performing serial testing at a specified frequency paired with isolation of positives, we have shown that RA tests outperform RT-PCR with a 24-h delay. The results from our modeling framework are consistent with quarantine and serial testing data collected from a remote industry setting.\n\nConclusionsThese RA test-specific results are an important component of the tool set for policy decision-making, and demonstrate that judicious selection of an appropriate RA test can supply a viable alternative to RT-PCR in efforts to control the spread of disease.\n\nPlain language summaryPrevious research has determined optimal timing for testing in quarantine and the utility of different frequencies of testing for disease surveillance using RT-PCR and generalized rapid antigen tests.\n\nHowever, these strategies can depend on the specific rapid antigen test used. By examining 18 rapid antigen tests, we demonstrate that a single rapid antigen test performs better than RT-PCR when quarantines are two days or less in duration. In the context of disease surveillance, the ability of a rapid antigen test to provide results quickly counteracts its lower sensitivity with potentially more false positives. These analytical results based on highly controlled test validation were consistent with real-world data obtained from quarantine and serial testing in an industrial setting.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Julia S. Sobolik",
-        "author_inst": "Emory University"
+        "author_name": "Chad R Wells",
+        "author_inst": "CIDMA"
       },
       {
-        "author_name": "Elizabeth T. Sajewski",
-        "author_inst": "Emory University"
+        "author_name": "Abhishek Pandey",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Lee-Ann Jaykus",
-        "author_inst": "North Carolina State University"
+        "author_name": "Seyed Moghadas",
+        "author_inst": "York University"
       },
       {
-        "author_name": "D. Kane Cooper",
-        "author_inst": "Emory University"
+        "author_name": "Burton H. Singer",
+        "author_inst": "University of Florida"
       },
       {
-        "author_name": "Ben A. Lopman",
-        "author_inst": "Emory University"
+        "author_name": "Gary Krieger",
+        "author_inst": "NewFields E&E"
       },
       {
-        "author_name": "Alicia NM. Kraay",
-        "author_inst": "Emory University"
+        "author_name": "Richard J.L. Heron",
+        "author_inst": "BP"
       },
       {
-        "author_name": "P. Barry Ryan",
-        "author_inst": "Emory University"
+        "author_name": "David E. Turner",
+        "author_inst": "BP"
       },
       {
-        "author_name": "Jodie L. Guest",
-        "author_inst": "Emory University"
+        "author_name": "Justin P. Abshire",
+        "author_inst": "HSE Specialties, BHP Petroleum"
       },
       {
-        "author_name": "Amy Webb-Girard",
-        "author_inst": "Emory University"
+        "author_name": "Kimberly M. Phillips",
+        "author_inst": "BHP"
       },
       {
-        "author_name": "Juan S. Leon",
-        "author_inst": "Emory University"
+        "author_name": "A. Michael Donoghue",
+        "author_inst": "BHP"
+      },
+      {
+        "author_name": "Alison P. Galvani",
+        "author_inst": "Center for Infectious Disease Modeling and Analysis"
+      },
+      {
+        "author_name": "Jeffrey P. Townsend",
+        "author_inst": "Yale University"
       }
     ],
     "version": "1",
@@ -567779,109 +569890,57 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.19.21262139",
-    "rel_title": "Predominance of antibody-resistant SARS-CoV-2 variants in vaccine breakthrough cases from the San Francisco Bay Area, California",
+    "rel_doi": "10.1101/2021.08.24.21262415",
+    "rel_title": "Comparing SARS-CoV-2 natural immunity to vaccine-induced immunity: reinfections versus breakthrough infections",
     "rel_date": "2021-08-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.19.21262139",
-    "rel_abs": "Associations between vaccine breakthrough cases and infection by SARS coronavirus 2 (SARS-CoV-2) variants have remained largely unexplored. Here we analyzed SARS-CoV-2 whole-genome sequences and viral loads from 1,373 persons with COVID-19 from the San Francisco Bay Area from February 1 to June 30, 2021, of which 125 (9.1%) were vaccine breakthrough infections. Fully vaccinated were more likely than unvaccinated persons to be infected by variants carrying mutations associated with decreased antibody neutralization (L452R, L452Q, E484K, and/or F490S) (78% versus 48%, p = 1.96e-08), but not by those associated with increased infectivity only (N501Y) (85% versus 77%, p = 0.092). Differences in viral loads were non-significant between unvaccinated and fully vaccinated persons overall (p = 0.99) and according to lineage (p = 0.09 - 0.78). Viral loads were significantly higher in symptomatic as compared to asymptomatic vaccine breakthrough cases (p < 0.0001), and symptomatic vaccine breakthrough infections had similar viral loads to unvaccinated infections (p = 0.64). In 5 cases with available longitudinal samples for serologic analyses, vaccine breakthrough infections were found to be associated with low or undetectable neutralizing antibody levels attributable to immunocompromised state or infection by an antibody-resistant lineage. Taken together, our results suggest that vaccine breakthrough infecions are overrepresnted by circulating antibody-resistant SARS-CoV-2 variants, and that symptomatic breakthrough infections may potentially transmit COVID-19 as efficiently as unvaccinated infections, regardless of the infecting lineage.",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262415",
+    "rel_abs": "BackgroundReports of waning vaccine-induced immunity against COVID-19 have begun to surface. With that, the comparable long-term protection conferred by previous infection with SARS-CoV-2 remains unclear.\n\nMethodsWe conducted a retrospective observational study comparing three groups: (1)SARS-CoV-2-naive individuals who received a two-dose regimen of the BioNTech/Pfizer mRNA BNT162b2 vaccine, (2)previously infected individuals who have not been vaccinated, and (3)previously infected and single dose vaccinated individuals. Three multivariate logistic regression models were applied. In all models we evaluated four outcomes: SARS-CoV-2 infection, symptomatic disease, COVID-19-related hospitalization and death. The follow-up period of June 1 to August 14, 2021, when the Delta variant was dominant in Israel.\n\nResultsSARS-CoV-2-naive vaccinees had a 13.06-fold (95% CI, 8.08 to 21.11) increased risk for breakthrough infection with the Delta variant compared to those previously infected, when the first event (infection or vaccination) occurred during January and February of 2021. The increased risk was significant (P<0.001) for symptomatic disease as well. When allowing the infection to occur at any time before vaccination (from March 2020 to February 2021), evidence of waning natural immunity was demonstrated, though SARS-CoV-2 naive vaccinees had a 5.96-fold (95% CI, 4.85 to 7.33) increased risk for breakthrough infection and a 7.13-fold (95% CI, 5.51 to 9.21) increased risk for symptomatic disease. SARS-CoV-2-naive vaccinees were also at a greater risk for COVID-19-related-hospitalizations compared to those that were previously infected.\n\nConclusionsThis study demonstrated that natural immunity confers longer lasting and stronger protection against infection, symptomatic disease and hospitalization caused by the Delta variant of SARS-CoV-2, compared to the BNT162b2 two-dose vaccine-induced immunity. Individuals who were both previously infected with SARS-CoV-2 and given a single dose of the vaccine gained additional protection against the Delta variant.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Venice Servellita",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Alicia Sotomayor-Gonzalez",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Amelia Gliwa",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Erika Torres",
-        "author_inst": "Color Genomics"
-      },
-      {
-        "author_name": "Noah Brazer",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Alicia Zhou",
-        "author_inst": "Color Genomics"
-      },
-      {
-        "author_name": "Katherine Hernandez",
-        "author_inst": "San Francisco Department of Public Health"
-      },
-      {
-        "author_name": "Madeline Sankaran",
-        "author_inst": "San Francisco Department of Public Health"
-      },
-      {
-        "author_name": "Baolin Wang",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Daniel Wong",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Candace Wang",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Yueyuan Zhang",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Kevin Reyes",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Dustin Glasner",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Sivan Gazit",
+        "author_inst": "Maccabi Healthcare Services"
       },
       {
-        "author_name": "Wayne Deng",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Roei Shlezinger",
+        "author_inst": "Kahn Sagol Maccabi (KSM) Research & Innovation Center, Maccabi Healthcare Services, Tel Aviv, 68125, Israel."
       },
       {
-        "author_name": "Jessica Streithorst",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Galit Perez",
+        "author_inst": "Kahn Sagol Maccabi (KSM) Research & Innovation Center, Maccabi Healthcare Services, Tel Aviv, 68125, Israel."
       },
       {
-        "author_name": "Steve Miller",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Roni Lotan",
+        "author_inst": "Kahn Sagol Maccabi (KSM) Research & Innovation Center, Maccabi Healthcare Services, Tel Aviv, 68125, Israel."
       },
       {
-        "author_name": "Edwin Frias",
-        "author_inst": "Abbott Laboratories"
+        "author_name": "Asaf Peretz",
+        "author_inst": "Internal Medicine COVID-19 Ward, Samson Assuta Ashdod University Hospital, Ashdod Israel"
       },
       {
-        "author_name": "John Hackett",
-        "author_inst": "Abbott Laboratories"
+        "author_name": "Amir Ben-Tov",
+        "author_inst": "Kahn Sagol Maccabi (KSM) Research & Innovation Center, Maccabi Healthcare Services, Tel Aviv, 68125, Israel"
       },
       {
-        "author_name": "Susan Philip",
-        "author_inst": "San Francisco Department of Public Health"
+        "author_name": "Dani Cohen",
+        "author_inst": "Sackler Faculty of Medicine, School of Public Health, Tel Aviv University, Tel Aviv, Israel"
       },
       {
-        "author_name": "Scott Topper",
-        "author_inst": "Color Genomics"
+        "author_name": "Khitam Muhsen",
+        "author_inst": "Sackler Faculty of Medicine, School of Public Health, Tel Aviv University, Tel Aviv, Israel"
       },
       {
-        "author_name": "Darpun Sachdev",
-        "author_inst": "San Francisco Department of Public Health"
+        "author_name": "Gabriel Chodick",
+        "author_inst": "Maccabitech Institute for Research and Innovation, Maccabi Healthcare Services, Israel"
       },
       {
-        "author_name": "Charles Y Chiu",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Tal Patalon",
+        "author_inst": "Kahn Sagol Maccabi (KSM) Research & Innovation Center, Maccabi Healthcare Services, Tel Aviv, 68125, Israel"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -569584,23 +571643,95 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.08.16.21262150",
-    "rel_title": "The IHME vs Me: Modeling USA CoVID-19 Spread, Early Data to the Fifth Wave",
+    "rel_doi": "10.1101/2021.08.18.21262061",
+    "rel_title": "Closed Doors: Predictors of Stress, Anxiety, Depression, and PTSD During the Onset of COVID-19 Pandemic in Brazil",
     "rel_date": "2021-08-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.16.21262150",
-    "rel_abs": "Epidemiologists have never had such high-quality real-time pandemic data. Modeling CoVID-19 pandemic data became a predictive tool in-stead of an afterwards analysis. How early CoVID-19 model predictions impacted US Government policies and practices is first reviewed here as an important part of the pandemic history. It spurred independent modeling efforts, such as this, to help develop a better understanding of CoVID-19 spread, and to provide a substitute for the IHME (Institute for Health Metrics & Evaluation, U. Washington) 4-month predictions for the expected pandemic evolution, which they had to revise every couple of weeks. Our alternative model, which was developed over the course of several earlier medrxiv.org preprints, is shown here to provide a good description for the entire USA CoVID-19 pandemic to date, covering: (1) the original CoVID-19 wave [3/21/20-6/07/20], (2) the Summer 2020 Resurgence [6/07/20-9/25/20], (3) the large Winter 2020 Resurgence [9/25/20-3/19/21], (4) a small Spring 2021 \"Fourth Wave\", [3/19/21-6/07/21], and (5) the present-day Summer 2021 \"Fifth Wave\" [6/07/21-present], which the USA is now in the midst of. Our analysis of the initial \"Fifth Wave\" data shows that this wave presently has the capacity to infect virtually all susceptible non-vaccinated persons who practice NO Mask-Wearing and minimal Social Distancing.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.18.21262061",
+    "rel_abs": "BackgroundThe rise of mental health problems in the population directly or indirectly by the COVID-19 pandemic is a major concern. The aim of this study was to investigate and compare independent predictors of symptoms of stress, anxiety, depression, and post-traumatic stress disorder (PTSD) in Brazilians, one month after the implementation of measures of social distancing.\n\nMethodsIt was a cross-sectional study, performed through a web-based survey. Depression, Anxiety, and Stress Scale (DASS-21) and PTSD Checklist for DSM-5 (PCL-5) were the outcomes. Data were gathered regarding demographics, social distancing, economic problems, exposure to the news of the pandemic, psychiatric history, sleep disturbances, traumatic situations, and substance use. The Alcohol Use Disorders Identification Test - Consumption (AUDIT-C) was also included. Predictors of symptoms were investigated through hierarchical multiple linear regression.\n\nResultOf a sample of 3,587 participants, approximately two-thirds considered that their mental health worsened after the beginning of the social restriction measures. The most important predictors of the symptoms investigated were the intensity of the distress related to pandemic news, younger age, current psychiatric diagnosis, trouble sleeping, emotional abuse or violence, and economic problems.\n\nLimitationsThe convenience sample assessed online may have limited external validity. It does not represent the northern regions of the country and most participants was white wealthier females.\n\nConclusionsThese results confirm the hypothesis that a pandemic would have important impacts on the mental health of the population and indicate the level of distress related to the media as an important predictor of psychological suffering.\n\nHighlightsO_LIDistress triggered by news was the main predictor of psychological symptoms\nC_LIO_LISleeping problems were strong indicators of mental health problems\nC_LIO_LIPeople with ongoing psychiatric disorders are especially vulnerable\nC_LIO_LIMeasures to prevent interpersonal trauma and financial loss are crucial\nC_LIO_LIYoung people may experience great suffering at the onset of the pandemic\nC_LI",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Genghmun Eng",
-        "author_inst": "Retired Scientist"
+        "author_name": "Vitor Crestani Calegaro",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Luis F Ramos-Lima",
+        "author_inst": "Universidade Federal do Rio Grande do Sul"
+      },
+      {
+        "author_name": "Mauricio Scopel Hoffmann",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Gustavo Zoratto",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Natalia Kerber",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Fernanda C Dala Costa",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Vitor Daniel Picinin",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Julia Kochler",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Leonardo Rodrigues",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Luisa Maciel",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Luiza Elizabete Braun",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Fernando Leite Girardi",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Gabriel O Cecatto",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Leopoldo Pompeo Weber",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Bruna Fragoso Rodrigues",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Alessandra N Bertolazi",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Juliana Motta de Oliveira",
+        "author_inst": "Universidade Federal de Santa Maria"
+      },
+      {
+        "author_name": "Bianca Lorenzi Negretto",
+        "author_inst": "Instituto de Psiquiatria de Santa Catarina"
+      },
+      {
+        "author_name": "Andrea Feijo de Mello",
+        "author_inst": "Universidade Federal de Sao Paulo"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2021.08.18.21262217",
@@ -571594,55 +573725,43 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.08.23.457408",
-    "rel_title": "Deep immune profiling of the maternal-fetal interface with mild SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2021.08.23.457328",
+    "rel_title": "Presence and Stability of SARS-CoV-2 on Environmental Currency and Money Cards",
     "rel_date": "2021-08-23",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.23.457408",
-    "rel_abs": "Pregnant women are an at-risk group for severe COVID-19, though the majority experience mild/asymptomatic disease. Although severe COVID-19 has been shown to be associated with immune activation at the maternal-fetal interface even in the absence of active viral replication, the immune response to asymptomatic/mild COVID-19 remains unknown. Here, we assessed immunological adaptations in both blood and term decidua from 9 SARS-exposed pregnant women with asymptomatic/mild disease and 15 pregnant SARS-naive women. In addition to selective loss of tissue-resident decidual macrophages, we report attenuation of antigen presentation and type I IFN signaling but upregulation of inflammatory cytokines and chemokines in blood monocyte derived decidual macrophages. On the other hand, infection was associated with remodeling of the T cell compartment with increased frequencies of activated CD69+ tissue-resident T cells and decreased abundance of Tregs. Interestingly, frequencies of cytotoxic CD4 and CD8 T cells increased only in the blood, while CD8 effector memory T cells were expanded in the decidua. In contrast to decidual macrophages, signatures of type I IFN signaling were increased in decidual T cells. Finally, T cell receptor diversity was significantly reduced with infection in both compartments, albeit to a much greater extent in the blood. The resulting aberrant immune activation in the placenta, even with asymptomatic disease may alter the exquisitely sensitive developing fetal immune system, leading to long-term adverse outcomes for offspring.",
-    "rel_num_authors": 9,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.23.457328",
+    "rel_abs": "The highly contagious nature of SARS-CoV-2 has led to several studies on the transmission of the virus. A little studied potential fomite of great concern in the community is currency, which has been shown to harbor microbial pathogens in several studies. Since the onset of the COVID-19 pandemic, many businesses in the United States have limited the use of banknotes in favor of credit cards. However, SARS-CoV-2 has shown greater stability on plastic in several studies. Herein, the stability of SARS-CoV-2 at room temperature on banknotes, money cards and coins was investigated. In vitro studies with live virus suggested SARS-CoV-2 was highly unstable on banknotes, showing an initial rapid reduction in viable virus and no viral detection by 24 hours. In contrast, SARS-CoV-2 was far more stable on money cards with live virus detected after 48 hours. Environmental swabbing of currency and money cards on and near the campus of Brigham Young University supported these results, with no detection of SARS-CoV-2 RNA on banknotes, and a low level on money cards. No viable virus was detected on either. These preliminary results suggest that the use of money cards over banknotes in order to slow the spread of this virus may be ill-advised. These findings should be investigated further through larger environmental studies involving more locations.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Suhas Sureshchandra",
-        "author_inst": "University of California Irvine"
-      },
-      {
-        "author_name": "Michael Z. Zulu",
-        "author_inst": "University of California Irvine"
-      },
-      {
-        "author_name": "Brianna Doratt",
-        "author_inst": "University of California Irvine"
-      },
-      {
-        "author_name": "Allen Jankeel",
-        "author_inst": "University of California Irvine"
+        "author_name": "Colleen Newey",
+        "author_inst": "Brigham Young University-Provo: Brigham Young University"
       },
       {
-        "author_name": "Delia Tifrea",
-        "author_inst": "University of California,Irvine"
+        "author_name": "Abigail  T Olausson",
+        "author_inst": "Brigham Young University-Provo: Brigham Young University"
       },
       {
-        "author_name": "Robert A Edwards",
-        "author_inst": "University of California Irvine"
+        "author_name": "Alyssa Applegate",
+        "author_inst": "Brigham Young University-Provo: Brigham Young University"
       },
       {
-        "author_name": "Monica Rincon",
-        "author_inst": "Oregon Health and Sciences University"
+        "author_name": "Ann  Aubrey Reid",
+        "author_inst": "Brigham Young University-Provo: Brigham Young University"
       },
       {
-        "author_name": "Nicole E. Marshall",
-        "author_inst": "Oregon Health and Science University"
+        "author_name": "Richard  A Robison",
+        "author_inst": "Brigham Young University-Provo: Brigham Young University"
       },
       {
-        "author_name": "Ilhem Messaoudi",
-        "author_inst": "University of California Irvine"
+        "author_name": "Julianne  H. Grose",
+        "author_inst": "Brigham Young University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.08.19.21262292",
@@ -573388,43 +575507,63 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.14.21262042",
-    "rel_title": "Longitudinal monitoring of SARS-CoV-2-specific immune responses",
+    "rel_doi": "10.1101/2021.08.15.21262087",
+    "rel_title": "The impact of ongoing COVID-19 lockdown on family finances and mental health",
     "rel_date": "2021-08-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.14.21262042",
-    "rel_abs": "The Lower Austrian Wachau region was an early COVID-19 hotspot of infection. As previously reported, in June 2020, after the first peak of infections, we determined that 8.5% and 9.0% of the participants in Wei{beta}enkirchen and surrounding communities in the Wachau region were positive for SARS-CoV-2-specific immunoglobulin G (IgG) and immunoglobulin A (IgA) antibodies, respectively. Here, we present novel data obtained eight months later (February 2021) from Wei{beta}enkirchen, after the second peak of infection, with 25.0% (138/552) and 23.6% (130/552) of participants that are positive for IgG and IgA, respectively. In participants with previous IgG/IgA positivity (June 2020), we observed a 24% reduction in IgG levels, whereas the IgA levels remained stable in February 2021. This subgroup was further analyzed for SARS-CoV-2-induced T cell activities. Although 76% (34/45) and 76% (34/45) of IgG positive and IgA positive participants, respectively, showed specific T cell activities, those were not significantly correlated with the levels of IgG or IgA. Thus, the analyses of antibodies cannot surrogate the measurement of T cell activities. For a comprehensive view on SARS-CoV-2-triggered immune responses, the measurement of different classes of antibodies should be complemented with the determination of T cell activities.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.15.21262087",
+    "rel_abs": "ObjectivesIn 2020, Australias successful COVID-19 public health restrictions comprised a national  initial lockdown (March-May), and  ongoing lockdown (July-November) for metropolitan Victorian residents only. We evaluated the relationships between ongoing lockdown and family finances and mental health.\n\nMethodsIn the June and September 2020 Royal Childrens Hospital National Child Health Polls, caregivers of children in Victoria and New South Wales reported: job/income loss; material deprivation (inability to pay for essential items); income-poverty; mental health (Kessler-6); perceived impact on caregiver/child mental health; and caregiver/child coping. Data from N=1207/902 caregivers in June/September were analysed using Difference-in-Difference modelling (New South Wales provided the comparator).\n\nResultsDuring Victorias ongoing lockdown, job/income loss increased by 11% (95%CI: 3-18%); Kessler-6 poor mental health by 6% (95%CI: -0.3-12%) and perceived negative mental health impacts by 14% for caregivers (95%CI: 6-23%) and 12% for children (95%CI: 4-20%). Female (versus male) caregivers, metropolitan (versus regional/rural) families, and families with elementary school-aged children (versus pre-/high-school) were most affected.\n\nConclusionsOngoing lockdown was associated with negative experiences of mental health, employment, and income, but not deprivation or poverty, likely because of government income supplements introduced early in the pandemic. Future lockdowns require planned responses to outbreaks, and evidence-informed financial and mental health supports.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Heike Rebholz",
-        "author_inst": "Danube Private University"
+        "author_name": "Anna Price",
+        "author_inst": "Centre for Community Child Health, Murdoch Children's Research Institute"
       },
       {
-        "author_name": "Ralf J. Braun",
-        "author_inst": "Danube Private University"
+        "author_name": "Diana Contreras-Su\u00e1rez",
+        "author_inst": "Melbourne Institute: Applied Economic & Social Research"
       },
       {
-        "author_name": "Titas Saha",
-        "author_inst": "Danube Private University"
+        "author_name": "Anna Zhu",
+        "author_inst": "RMIT University"
       },
       {
-        "author_name": "Oliver Harzer",
-        "author_inst": "Danube Private University"
+        "author_name": "Natalie Schreurs",
+        "author_inst": "Centre for Community Child Health, Murdoch Children's Research Institute"
       },
       {
-        "author_name": "Miriam Schneider",
-        "author_inst": "Danube Private University"
+        "author_name": "Mary-Anne Measey",
+        "author_inst": "Royal Children's Hospital, Melbourne"
       },
       {
-        "author_name": "Dennis Ladage",
-        "author_inst": "Danube Private University"
+        "author_name": "Susan Woolfenden",
+        "author_inst": "University of NSW"
+      },
+      {
+        "author_name": "Jade Burley",
+        "author_inst": "University of NSW"
+      },
+      {
+        "author_name": "Hannah Bryson",
+        "author_inst": "Centre for Community Child Health, Murdoch Children's Research Institute"
+      },
+      {
+        "author_name": "Daryl Efron",
+        "author_inst": "Royal Children's Hospital, Melbourne"
+      },
+      {
+        "author_name": "Anthea Rhodes",
+        "author_inst": "Royal Children's Hospital, Melbourne"
+      },
+      {
+        "author_name": "Sharon Goldfeld",
+        "author_inst": "Centre for Community Child Health, Murdoch Children's Research Institute"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.08.16.21262115",
@@ -575226,87 +577365,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.08.13.21262039",
-    "rel_title": "A sensitive and rapid wastewater test for SARS-COV-2 and its use for the early detection of a cluster of cases in a remote community",
+    "rel_doi": "10.1101/2021.08.14.21261996",
+    "rel_title": "Association between interruption to medical care and sickness presenteeism during the COVID-19 pandemic: a cross-sectional study in Japan",
     "rel_date": "2021-08-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.13.21262039",
-    "rel_abs": "Throughout the COVID-19 pandemic, wastewater surveillance has been used to monitor trends in SARS-CoV-2 prevalence in the community. A major challenge in establishing wastewater surveillance programs, especially in remote areas, is the need for a well-equipped laboratory for sample analysis. Currently, no options exist for rapid, sensitive, mobile, and easy-to-use wastewater tests for SARS-CoV-2. The performance of the GeneXpert System, which offers cartridge-based, rapid molecular clinical testing for SARS-CoV-2 in a portable platform, was evaluated using wastewater as the input. The GeneXpert demonstrated a SARS-CoV-2 limit of detection in wastewater below 32 copies/mL with a sample processing time of less than an hour. Using wastewater samples collected from multiple sites across Canada during February and March 2021, a high overall agreement (97.8%) was observed between the GeneXpert assay and laboratory-developed tests regarding the presence or absence of SARS-CoV-2. Additionally, with the use of centrifugal filters the detection threshold of the GeneXpert system was improved to <10 copies/mL in wastewater. Finally, to support on-site wastewater surveillance, GeneXpert testing was implemented in Yellowknife, a remote community in Northern Canada where its use successfully alerted public health authorities to undetected transmission of COVID-19. The identification of SARS-CoV-2 in wastewater triggered clinical testing of recent travelers and identification of new COVID-19 cases/clusters. Taken together, these results suggest the GeneXpert is a viable option for surveillance of SARS-CoV-2 in wastewater in locations that do not have access to established testing laboratories.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.14.21261996",
+    "rel_abs": "ObjectivesThis study examined the relationship between interruption to routine medical care during the coronavirus disease 2019 pandemic and sickness presenteeism among workers in Japan.\n\nMethodsA cross-sectional study using data obtained from an internet monitor questionnaire was conducted. Interruption to medical care was defined based on the response \"I have not been able to go to the hospital or receive treatment as scheduled.\" The fraction of sickness presenteeism days in the past 30 days was employed as the primary outcome. A fractional logit model was used for analysis to treat bounded data.\n\nResultsOf the 27,036 participants, 17,526 (65%) were workers who did not require routine medical care, 8,451 (31%) were using medical care as scheduled, and 1,059 (4%) experienced interrupted medical care. The adjusted odds ratio (aOR) of sickness presenteeism was significantly higher among workers who experienced interrupted medical care (3.44; 95% confidence interval [CI]: 3.04-3.89) than those who did not require routine medical care. In terms of symptoms, the highest aOR was observed among workers with mental health symptoms (aOR: 5.59, 95%CI: 5.04-6.20).\n\nConclusionsThis study suggests the importance of continuing necessary treatment during a pandemic to prevent presenteeism.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Jade Daigle",
-        "author_inst": "Public Health Agency of Canada"
-      },
-      {
-        "author_name": "Kathleen Racher",
-        "author_inst": "Government of the Northwest Territories"
-      },
-      {
-        "author_name": "Justin Hazenberg",
-        "author_inst": "Government of the Northwest Territories"
-      },
-      {
-        "author_name": "Allan Yeoman",
-        "author_inst": "Government of the Northwest Territories"
-      },
-      {
-        "author_name": "Heather Hannah",
-        "author_inst": "Government of the Northwest Territories"
-      },
-      {
-        "author_name": "Diep Duong",
-        "author_inst": "Government of the Northwest Territories"
-      },
-      {
-        "author_name": "Umar Mohammed",
-        "author_inst": "Public Health Agency of Canada"
-      },
-      {
-        "author_name": "Dave Spreitzer",
-        "author_inst": "Public Health Agency of Canada"
-      },
-      {
-        "author_name": "Branden S. J. Gregorchuk",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Makoto Okawara",
+        "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
       },
       {
-        "author_name": "Breanne M. Head",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Tomohiro Ishimaru",
+        "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
       },
       {
-        "author_name": "Adrienne F. A. Meyers",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Seiichiro Tateishi",
+        "author_inst": "Department of Occupational Medicine, School of Medicine, University of Occupational and Environmental Health, Japan"
       },
       {
-        "author_name": "Paul A. Sandstrom",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Ayako Hino",
+        "author_inst": "Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
       },
       {
-        "author_name": "Anil Nichani",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Mayumi Tsuji",
+        "author_inst": "Department of Environmental Health, School of Medicine, University of Occupational and Environmental Health, Japan"
       },
       {
-        "author_name": "James I. Brooks",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Akira Ogami",
+        "author_inst": "Department of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
       },
       {
-        "author_name": "Michael R. Mulvey",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Tomohisa Nagata",
+        "author_inst": "Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Jap"
       },
       {
-        "author_name": "Chand S. Mangat",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Shinya Matsuda",
+        "author_inst": "Department of Preventive Medicine and Community Health, School of Medicine, University of Occupational and Environmental Health, Japan"
       },
       {
-        "author_name": "Michael G. Becker",
-        "author_inst": "Public Health Agency of Canada"
+        "author_name": "Yoshihisa Fujino",
+        "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "occupational and environmental health"
   },
   {
     "rel_doi": "10.1101/2021.08.16.21262016",
@@ -576832,81 +578939,93 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.10.21261836",
-    "rel_title": "Efficacy and Safety of Ayurveda Intervention AYUSH 64 as add-on therapy for patients with COVID 19 infections: An open labelled, Parallel Group, Randomized controlled clinical trial",
+    "rel_doi": "10.1101/2021.08.15.21262000",
+    "rel_title": "Seasonal betacoronavirus antibodies expansion post BNT161b2 vaccination associates with reduced SARS-CoV-2 VoCs neutralization",
     "rel_date": "2021-08-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261836",
-    "rel_abs": "The authors have withdrawn this manuscript because they found a serious issue in data-analysis which leads to wrong interpretation of the results. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.15.21262000",
+    "rel_abs": "SARS-CoV-2 vaccination is known to induce antibodies that recognize also variants of concerns (VoCs) of the virus. However, epidemiological and laboratory evidences indicate that these antibodies have a reduce neutralization ability against VoCs. We studied binding and neutralizing antibodies against the Spike RBD and S2 domains of the Wuhan-Hu-1 virus and its alpha and beta VoCs and of seasonal betacoronaviruses (HKU1 and OC43) in a cohort of 31 health care workers vaccinated with BNT162b2-Comirnaty and prospectively followed post-vaccination. The study of sequential samples collected up to 64 days post-vaccination showed that serological assays measuring IgG against Wuhan-Hu-1 antigens were a poor proxy for VoCs neutralization. In addition, in subjects who had asymptomatic or mild COVID-19 prior to vaccination the loss of nAbs following disease can be rapid and protection from re-infection post-vaccination is often no better than in naive subjects. Interestingly, in health care workers naive for SARS-CoV-2 infection, vaccination induced a rapid and transient reactivation of pre-existing seasonal coronaviruses IgG responses that was associated with a subsequent reduced ability to neutralize some VoCs.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Pankaj Bhardwaj",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Stefania Dispinseri",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Pawan Kumar Godatwar",
-        "author_inst": "National Institute of Ayurveda, Jaipur, Rajasthan"
+        "author_name": "Ilaria Marzinotto",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Jaykaran Charan",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Cristina Brigatti",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Sanjeev Sharma",
-        "author_inst": "National Institute of Ayurveda, Jaipur, Rajasthan"
+        "author_name": "Maria Franca Pirillo",
+        "author_inst": "Istituto Superiore di Sanit\u00e0"
       },
       {
-        "author_name": "Shazia Shafi",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Monica Tolazzi",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Nishant Chauhan",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Elena Bazzigaluppi",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Pratibha Vyas",
-        "author_inst": "NIIR NCD Jodhpur"
+        "author_name": "Andrea Canitano",
+        "author_inst": "Istituto Superiore di Sanit\u00e0"
       },
       {
-        "author_name": "Naveen Dutt",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Martina Borghi",
+        "author_inst": "Istituto Superiore di Sanit\u00e0"
       },
       {
-        "author_name": "Naresh Midha",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Alessandra Gallinaro",
+        "author_inst": "Istituto Superiore di Sanit\u00e0"
       },
       {
-        "author_name": "Ramniwas Jalandra",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Roberta Caccia",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Meenakshi Sharma",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Riccardo Vercesi",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Vijaya Lakshmi Nag",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Paul F McKay",
+        "author_inst": "Imperial College"
       },
       {
-        "author_name": "Suman Sharma",
-        "author_inst": "National Institute of Ayurveda, Jaipur, Rajasthan"
+        "author_name": "Fabio Ciceri",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Sarvesh Kumar Singh",
-        "author_inst": "National Institute of Ayurveda Jaipur"
+        "author_name": "Lorenzo Piemonti",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       },
       {
-        "author_name": "Praveen Sharma",
-        "author_inst": "All India Institute of Medical Sciences Jodhpur"
+        "author_name": "Donatella Negri",
+        "author_inst": "Istituto Superiore di Sanit\u00e0"
       },
       {
-        "author_name": "Sanjeev Misra",
-        "author_inst": "All India Institute of Medical Sciences, Jodhpur"
+        "author_name": "Paola Cinque",
+        "author_inst": "IRCCS Ospedale San Raffaele"
+      },
+      {
+        "author_name": "Andrea Cara",
+        "author_inst": "Istituto Superiore di Sanit\u00e0"
+      },
+      {
+        "author_name": "Vito Lampasona",
+        "author_inst": "IRCCS Ospedale San Raffaele"
+      },
+      {
+        "author_name": "Gabriella Scarlatti",
+        "author_inst": "IRCCS Ospedale San Raffaele"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -578566,43 +580685,59 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2021.08.11.21261946",
-    "rel_title": "A Novel Convolutional Neural Network for COVID-19 detection and classification using Chest X-Ray images",
+    "rel_doi": "10.1101/2021.08.11.21261793",
+    "rel_title": "Development and use analysis of 'gestioemocional.cat', a web app for promoting emotional self-care and access to professional mental health resources during the covid-19 pandemic",
     "rel_date": "2021-08-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.11.21261946",
-    "rel_abs": "The early and rapid diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), the main cause of fatal pandemic coronavirus disease 2019 (COVID-19), with the analysis of patients chest X-ray (CXR) images has life-saving importance for both patients and medical professionals. In this research a very simple novel and robust deep-learning convolutional neural network (CNN) model with less number of trainable-parameters is proposed to assist the radiologists and physicians in the early detection of COVID-19 patients. It also helps to classify patients into COVID-19, pneumonia and normal on the bases of analysis of augmented X-ray images. This augmented dataset contains 4803 COVID-19 from 686 publicly available chest X-ray images along with 5000 normal and 5000 pneumonia samples. These images are divided into 80% training and 20 % validation. The proposed CNN model is trained on training dataset and then tested on validation dataset. This model has a promising performance with a mean accuracy of 92.29%, precision of 99.96%, Specificity of 99.85% along with Sensitivity value of 85.92%. The result can further be improved if more data of expert radiologist is publically available.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.11.21261793",
+    "rel_abs": "BackgroundQuarantines and nationwide lockdowns dictated for containing the spread of the COVID-19 pandemic may lead to distress and increase the frequency of anxiety and depression symptoms among the general population. During the national lockdown of the first wave of the COVID-19 outbreak in Spain, we developed and launched a Web App (Gestioemocional.cat) to promote emotional self-care in the general population and facilitate contact with healthcare professionals.\n\nMethodsGestioemocional.cat targeted all individuals aged 18 years or more and was designed by adapting the contents of a mobile App for adjuvant treatment of post-traumatic stress disorder (i.e., the PTSD Coach App) to the general population and the pandemic/lockdown scenario. We retrospectively assessed the utilization pattern of the Web App using data systematically retrieved from Google Analytics. Data were grouped into three time periods, defined using a join point analysis of COVID-19 incidence in our area: first wave, between-wave period, and second wave.\n\nResultsThe resulting Web App, maintains the navigation structure of the PTSD Coach App, with three main modules: tools for emotional self-care, a self-assessment test, and professional resources for on-demand contact. The self-assessment test combines the Patient Health Questionnaire-2 (PHQ-2) and the 7-item Generalized Anxiety Disorder Scale (GAD-7) and offers professional contact in the advent of a high level of depression and anxiety; contact is prioritized according to a screening questionnaire administered at the time of obtaining individual consent to be contacted. The tools for emotional self-care can be accessed either on-demand or symptom-driven. The utilization analysis showed a high number of weekly accesses during the first wave. In this period, press releases regarding critical events of the pandemic progression and government decisions on containment measures were followed by a utilization peak, irrespective of the sense (i.e., positive or negative) of the information. Positive information pieces (e.g., relaxation of containment measures due to a reduction of COVID-19 cases) resulted in a sharp increase in utilization immediately after information release, followed by a successive decline in utilization. The second wave was characterized by a lower and less responsive utilization of the Web App.\n\nConclusionsmHealth tools may help the general population coping with stressful conditions associated with the pandemic scenario. Future studies shall investigate the effectiveness of these tools among the general population[-]including individuals without diagnosed mental illnesses[-]and strategies to reach as many people as possible.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Muhammad Talha Nafees",
-        "author_inst": "University of Engineering and Technology Peshawar"
+        "author_name": "Sara Guila Fidel-Kinori",
+        "author_inst": "Vall d'Hebron University Hospital, Barcelona, Spain"
       },
       {
-        "author_name": "Irshad ullah",
-        "author_inst": "University of Engineering and Technology Peshawar"
+        "author_name": "Gerard Carot-Sans",
+        "author_inst": "Catalan Health Service, Barcelona, Spain"
       },
       {
-        "author_name": "Muhammad Rizwan",
-        "author_inst": "University of Engineering and Technology Peshawar"
+        "author_name": "Andr\u00e9s Cuartero-Barbanoj",
+        "author_inst": "Sistema d'Emerg\u00e8ncies M\u00e8diques, L'Hospitalet de Llobregat, Spain"
       },
       {
-        "author_name": "Maaz ullah",
-        "author_inst": "University of Engineering and Technology Peshawar"
+        "author_name": "Dami\u00e0 Valero",
+        "author_inst": "Catalan Health Service, Barcelona, Spain"
       },
       {
-        "author_name": "Muhammad Irfanullah Khan",
-        "author_inst": "University of Engineering and Technology Peshawar"
+        "author_name": "Jordi Piera-Jim\u00e9nez",
+        "author_inst": "Catalan Health Service, Barcelona, Spain"
+      },
+      {
+        "author_name": "Rosa Rom\u00e0-Monf\u00e0",
+        "author_inst": "Catalan Health Service, Barcelona, Spain"
+      },
+      {
+        "author_name": "Elisabet Garcia-Ribatallada",
+        "author_inst": "Catalan Health Service, Barcelona, Spain"
+      },
+      {
+        "author_name": "Pol P\u00e9rez-Sust",
+        "author_inst": "Catalan Health Service, Barcelona, Spain"
+      },
+      {
+        "author_name": "Jordi Blanch-Andreu",
+        "author_inst": "Catalan Health Service, Barcelona, Spain"
       },
       {
-        "author_name": "Muhammad Farhan",
-        "author_inst": "University of Engineering and Technology Peshawar"
+        "author_name": "Josep Antoni Ramos-Quiroga",
+        "author_inst": "Vall d'Hebron University Hospital, Barcelona, Spain"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "radiology and imaging"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2021.08.12.21261462",
@@ -580444,39 +582579,43 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.12.456168",
-    "rel_title": "SARS-CoV-2 spike opening dynamics and energetics reveal the individual roles of glycans and their collective impact",
+    "rel_doi": "10.1101/2021.08.13.456066",
+    "rel_title": "SARS-CoV-2 Neutralization in Commercial Lots of Plasma-derived Immunoglobulin",
     "rel_date": "2021-08-13",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.12.456168",
-    "rel_abs": "The trimeric spike (S) glycoprotein, which protrudes from the SARS-CoV-2 viral envelope, binds to human ACE2, initiated by at least one protomers receptor binding domain (RBD) switching from a \"down\" (closed) to an \"up\" (open) state. Here, we used large-scale molecular dynamics simulations and two-dimensional replica exchange umbrella sampling calculations with more than a thousand windows and an aggregate total of 160 {micro}s of simulation to investigate this transition with and without glycans. We find that the glycosylated spike has a higher barrier to opening and also energetically favors the down state over the up state. Analysis of the S-protein opening pathway reveals that glycans at N165 and N122 interfere with hydrogen bonds between the RBD and the N-terminal domain in the up state, while glycans at N165 and N343 can stabilize both the down and up states. Finally we estimate how epitope exposure for several known antibodies changes along the opening path. We find that the BD-368-2 antibodys epitope is continuously exposed, explaining its high efficacy.",
-    "rel_num_authors": 5,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.13.456066",
+    "rel_abs": "IntroductionPatients suffering from primary or secondary immunodeficiency (PID or SID) face times of increased insecurity and discomfort in the light of the raging COVID-19 pandemic, not knowing if and to what extent their comorbidities impact the course of a potential SARS-CoV-2 infection. Furthermore, recently available vaccination options might not be amenable or effective for all patients of this heterogeneous population. Therefore, these patients often rely on passive immunization with plasma-derived, intravenous or subcutaneous immunoglobulin (IVIG/SCIG).\n\nWhether the ongoing COVID-19 pandemic and/or the progress in vaccination programs lead to increased and potentially protective titers in plasma-derived immunoglobulins (Ig) indicated, e.g., for humoral immunodeficiency remains a pressing question for this patient population.\n\nPurposeWe investigated SARS-CoV-2 reactivity of US plasma-derived IVIG/SCIG products from the end of 2020 until 06/2021 as well as in convalescent plasma (CP) from 05/2020 to 08/2020 to determine whether potentially neutralizing antibody titers may be present.\n\nMethodsFinal containers of IVIG/SCIG and CP donations were analyzed by commercial ELISA for anti-SARS-CoV-2 S1-receptor binding domain (RBD) IgG as well as microneutralization assay using a patient-derived SARS-CoV-2 (D614G) isolate. Neutralization capacities of 313 plasma single donations and 119 plasma-derived IVIG/SCIG lots were determined. Results obtained from both analytical methods were normalized against the WHO International Standard. Finally, based on dense pharmacokinetic (PK) profiles of an IVIG preparation from previously published investigations, possible steady-state plasma levels of SARS-CoV-2 neutralization capacities were approximated based on currently measured anti-SARS-CoV-2 potencies in IVIG/SCIG preparations.\n\nResultsCP donations presented with a high variability with regards to anti-SARS-CoV-2 reactivity in ELISA as well as in neutralization testing. While approximately 50% of convalescent donations were none/low neutralizing, approximately 10% were at or above 1000 IU/mL.\n\nIVIG/SCIG lots derived from pre-pandemic plasma donations did not show neutralizing capacities of SARS-CoV-2. Lots produced between 12/2020 and 06/2021, entailing plasma donations after the emergence of SARS-CoV-2 showed a rapid and constant increase in anti-SARS-CoV-2 reactivity and neutralization capacity over time. While lot-to-lot variability was substantial, neutralization capacity increased from a mean of 20 IU/mL in 12/2020 to 505 IU/mL in 06/2021 with a maximum of 864 IU/mL for the most recent lots.\n\nPharmacokinetic extrapolations, based on non-compartmental superposition principles using steady-state reference profiles from previously published PK investigations on IVIG in PID, yielded potential steady-state trough plasma levels of 16 IU/mL of neutralizing SARS-CoV-2 IgG based on the average final container concentration from 05/2021 of 216 IU/mL. Maximum extrapolated trough levels could reach 64 IU/mL based on the latest maximal final container potency tested in 06/2021.\n\nConclusionsSARS-CoV-2 reactivity and neutralization capacity in IVIG/SCIG produced from US plasma rapidly and in part exponentially increased in the first half of 2021. The observed increase of final container potencies is likely trailing the serological status of the US donor population in terms of COVID-19 convalescence and vaccination by at least 5 months due to production lead times and should in principle continue at least until fall 2021. In summary, the data support rapidly increasing levels of anti-SARS-CoV-2 antibodies in IVIG/SCIG products implicating that a certain level of protection could be possible against COVID-19 for regularly substituted PID/SID patients. Nevertheless, more research is still needed to confirm which plasma levels are needed to provide protection against SARS-CoV-2 infection in immune-compromised patients.\n\nPlain Language SummaryPeople with deficiencies in their immune system often have an insufficient antibody response to antigens, e.g., bacteria, viruses, or vaccines. These patients therefore often receive antibodies from healthy people to replace the missing antibodies and build a first line of defense against infections. These antibodies (also called immunoglobulins (Ig)) are prepared from plasma of healthy donors, the liquid fraction of the blood without cells. This plasma is then split up in pharmaceutical production into its protein components. One of these is immunoglobulin G (IgG), which is the protein family that neutralizes/inactivates infectious agents as well as marks these infectious agents so they can be recognized by other parts of the immune system. With the ongoing COVID-19 pandemic and the severe to fatal outcomes for certain patient groups, especially people with impaired immunity, these patients and their physicians are interested in whether their antibody replacement therapy also confers protection against SARS-CoV-2 infection. We analyzed the capability of plasma-derived Ig lots to (i) recognize SARS-CoV-2 protein by ELISA method as well as (ii) neutralize SARS-CoV-2 by neutralization studies using the actual virus under biosafety level 3 (BSL-3) conditions. Here we show increasing anti-SARS-CoV-2 activity over time of manufactured Ig lots produced between 12/2020 and 06/2021. The most recent lots had a neutralizing activity of up to 864 IU/mL. Considering that the USA represents Octapharmas main plasma source, the progress in vaccination levels together with the evolution of the COVID-19 pandemic in this country suggests that the IVIG/SCIG neutralization capacities against SARS-CoV-2 might still increase and could potentially meet a level where antibody plasma concentrations in the patient confer immune protection.\n\nKey PointsO_LIPatients with humoral immunodeficiency rely on plasma-derived immunoglobulin for passive immunization against numerous pathogens.\nC_LIO_LISARS-CoV-2 neutralization capacities of plasma-derived immunoglobulins have increased over time with the ongoing COVID-19 pandemic and vaccination campaigns.\nC_LIO_LIPlasma-derived immunoglobulin in prophylactic use for immunodeficient patients could potentially protect against SARS-CoV-2 infection in the future.\nC_LI",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Yui Tik Pang",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Andreas Volk",
+        "author_inst": "Octapharma Biopharmaceuticals GmbH, Virus and Prion Validation, Frankfurt, Germany"
       },
       {
-        "author_name": "Atanu Acharya",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Caroline Covini-Souris",
+        "author_inst": "Octapharma Pharmazeutika Produktionsgesellschaft m.b.H., R&D Plasma, Vienna, Austria"
       },
       {
-        "author_name": "Diane Lynch",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Denis Kuehnel",
+        "author_inst": "Octapharma Biopharmaceuticals GmbH, Virus and Prion Validation, Frankfurt, Germany"
       },
       {
-        "author_name": "Anna Pavlova",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Christian de Mey",
+        "author_inst": "ACPS-Network GmbH, Wiesbaden, Germany"
       },
       {
-        "author_name": "James Gumbart",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Juergen Roemisch",
+        "author_inst": "Octapharma Pharmazeutika Produktionsgesellschaft m.b.H., R&D Plasma, Vienna, Austria"
+      },
+      {
+        "author_name": "Torben Schmidt",
+        "author_inst": "Octapharma Biopharmaceuticals GmbH, Virus and Prion Validation, Frankfurt, Germany"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "biophysics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.08.13.456258",
@@ -582726,123 +584865,59 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.08.10.21261847",
-    "rel_title": "Replacement of the Alpha variant of SARS-CoV-2 by the Delta variant in Lebanon between April and June 2021",
+    "rel_doi": "10.1101/2021.08.10.21261860",
+    "rel_title": "Heterogeneity in COVID-19 Pandemic-Induced Lifestyle Stressors Predicts Mental Health in Adults and Children in the US and UK",
     "rel_date": "2021-08-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261847",
-    "rel_abs": "BackgroundThe COVID-19 pandemic continues to expand globally, with case numbers rising in many areas of the world, including the Eastern Mediterranean Region. Lebanon experienced its largest wave of COVID-19 infections from January to April 2021. Limited genomic surveillance was undertaken, with just twenty six SARS-CoV-2 genomes available for this period, nine of which were from travellers from Lebanon detected by other countries. Additional genome sequencing is thus needed to allow surveillance of variants in circulation.\n\nMethodsNine hundred and five SARS-CoV-2 genomes were sequenced using the ARTIC protocol. The genomes were derived from SARS-CoV-2-positive samples, selected retrospectively from the sentinel COVID-19 surveillance network, to capture diversity of location, sampling time, gender, nationality and age.\n\nResultsAlthough sixteen PANGO lineages were circulating in Lebanon in January 2021, by February there were just four, with the Alpha variant accounting for 97% of samples. In the following two months, all samples contained the Alpha variant. However, this had changed dramatically by June and July, when all samples belonged to the Delta variant.\n\nDiscussionThis study provides a ten-fold increase in the number of SARS-CoV-2 genomes available from Lebanon. The Alpha variant, first detected in the UK, rapidly swept through Lebanon, causing the countrys largest wave to date, which peaked in January 2021. The Alpha variant was introduced to Lebanon multiple times despite travel restrictions, but the source of these introductions remains uncertain. The Delta variant was detected in Gambia in travellers from Lebanon in mid-May, suggesting community transmission in Lebanon several weeks before this variant was detected in the country. Prospective sequencing in June/July 2021 showed that the Delta variant had completely replaced the Alpha variant in under six weeks.",
-    "rel_num_authors": 26,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261860",
+    "rel_abs": "Identifying predictors of mental health symptoms after the initial phase of the pandemic may inform the development of targeted interventions to reduce its negative long-term mental health consequences. In the current study, we aimed to simultaneously evaluate the prospective influence of life change stress, personal COVID-19 impact, prior mental health, worry about COVID-19, state-level indicators of pandemic threat, and socio-demographic factors on mood and anxiety symptoms in November 2020 among adults and children in the US and UK. We used a longitudinal cohort study using the Coronavirus Health Impact Survey (CRISIS) collected at 3 time points: an initial assessment in April 2020 (\"April\"), a reassessment 3 weeks later (\"May\"), and a 7-month follow-up in November 2020 (\"November\"). Online surveys were collected in the United States and United Kingdom by Prolific Academic, a survey recruitment service, with a final sample of 859 Adults and 780 children (collected via parent report). We found subtypes of pandemic-related life change stress in social and economic domains derived through Louvain Community Detection. We assessed recalled mood and perceived mental health prior to the pandemic; worries about COVID-19; personal and family impacts of COVID-19; and socio-demographic characteristics. Levels of mood symptoms in November 2020 measured with the circumplex model of affect. We found 3 life change stress subtypes among adults and children: Lower Social/Lower Economic (adults and children), Higher Social/Higher Economic (adults and children), Lower Social/Higher Economic (adults), and Intermediate Social/Lower Economic (children). Overall, mood symptoms decreased between April and November 2020, but shifting from lower to higher-stress subtypes between time points was associated with increasing symptoms. For both adults and children, the most informative predictors of mood symptoms in November identified by conditional random forest models were prior mood and perceived mental health, worries about COVID, and sources of life change. The relative importance of these predictors was the most prominent difference in findings between adults and children, with lifestyle changes stress regarding friendships being more predictive of mood outcomes than worries about COVID in children. In the US, objective state-level indicators of COVID-19 threat were less predictive of November mood than these other predictors. We found that in addition to the well-established influences of prior mood and worry, heterogeneous subtypes of pandemic-related stress were differentially associated with mood after the initial phase of the pandemic. Greater research on diverse patterns of pandemic experience may elucidate modifiable targets for treatment and prevention.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Georgi Merhi",
-        "author_inst": "Lebanese American University, Department of Natural Sciences, School of Arts and Sciences, Byblos-Lebanon"
-      },
-      {
-        "author_name": "Alexander J Trotter",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Leonardo de Oliveira Martins",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Jad Koweyes",
-        "author_inst": "Lebanese American University, Department of Natural Sciences, School of Arts and Sciences, Byblos-Lebanon"
-      },
-      {
-        "author_name": "Thanh Le-Viet",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Hala Abou Naja",
-        "author_inst": "Ministry of Public Health, Epidemiologial Surveillance Program, Museum square, Beirut, Lebanon"
-      },
-      {
-        "author_name": "Mona Al Buaini",
-        "author_inst": "National Influenza Centre Research Laboratory, Rafic Hariri University Hospital, Beirut, Lebanon"
-      },
-      {
-        "author_name": "Sophie J Prosolek",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Nabil-Fareed Alikhan",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Martin Lott",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Tatiana Tohmeh",
-        "author_inst": "Ministry of Public Health, Epidemiologial Surveillance Program, Museum square, Beirut, Lebanon"
-      },
-      {
-        "author_name": "Bassam Badran",
-        "author_inst": "Laboratory of Molecular Biology and Cancer Immunology, Faculty of Sciences, Lebanese University"
-      },
-      {
-        "author_name": "Orla J Jupp",
-        "author_inst": "University of East Anglia, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Sarah Gardner",
-        "author_inst": "University of East Anglia, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Matthew W Felgate",
-        "author_inst": "University of East Anglia, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Kate A Makin",
-        "author_inst": "University of East Anglia, Norwich, Norfolk, UK"
-      },
-      {
-        "author_name": "Janine M Wilkinson",
-        "author_inst": "University of East Anglia, Norwich, Norfolk, UK"
+        "author_name": "Aki Nikolaidis",
+        "author_inst": "Child Mind Institute"
       },
       {
-        "author_name": "Rachael Stanley",
-        "author_inst": "Norfolk and Norwich University Hospital, Norwich, Norfolk, UK"
+        "author_name": "Jacob DeRosa",
+        "author_inst": "Child Mind Institute"
       },
       {
-        "author_name": "Abdul K Sesay",
-        "author_inst": "MRC Unit The Gambia at LHSTM, Fajara, Gambia"
+        "author_name": "Mirelle Kass",
+        "author_inst": "Child Mind Institute"
       },
       {
-        "author_name": "Mark A Webber",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
+        "author_name": "Irene Droney",
+        "author_inst": "Child Mind Institute"
       },
       {
-        "author_name": "Rose K Davidson",
-        "author_inst": "University of East Anglia, Norwich, Norfolk, UK"
+        "author_name": "Lindsay Alexander",
+        "author_inst": "Child Mind Institute"
       },
       {
-        "author_name": "Nada Ghosn",
-        "author_inst": "Ministry of Public Health, Epidemiologial Surveillance Program, Museum square, Beirut, Lebanon"
+        "author_name": "Adriana Di Martino",
+        "author_inst": "Child Mind Institute"
       },
       {
-        "author_name": "Mark Pallen",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
+        "author_name": "Evelyn Bromet",
+        "author_inst": "Stony Brook University"
       },
       {
-        "author_name": "Hamad Hasan",
-        "author_inst": "Ministry of Public Health, Beirut, Lebanon"
+        "author_name": "Kathleen Merikangas",
+        "author_inst": "National Institute of Mental Health"
       },
       {
-        "author_name": "Andrew J Page",
-        "author_inst": "Quadram Institute Bioscience, Norwich Research Park, Norwich, Norfolk, UK"
+        "author_name": "Michael Milham",
+        "author_inst": "Child Mind Institute"
       },
       {
-        "author_name": "Sima Tokajian",
-        "author_inst": "Lebanese American University, Department of Natural Sciences, School of Arts and Sciences, Byblos-Lebanon"
+        "author_name": "Diana Paksarian",
+        "author_inst": "National Institute of Mental Health"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2021.08.10.21261816",
@@ -584631,53 +586706,33 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.09.21261555",
-    "rel_title": "Mixed invasive molds among COVID-19 patients",
+    "rel_doi": "10.1101/2021.08.05.21261562",
+    "rel_title": "Cryptic Transmission of the Delta Variant AY.3 Sublineage of SARS-CoV-2 among Fully Vaccinated Patients on an Inpatient Ward",
     "rel_date": "2021-08-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.09.21261555",
-    "rel_abs": "PurposeDue to surge in COVID cases during the second wave of the COVID pandemic, the healthcare system collapsed in India with shortage of hospital beds, injudicious use of steroids and other immunomodulators, and poor glycaemic monitoring among a population with pre-existing risk of diabetes. Fungal epidemic was announced amid COVID pandemic with several cases of COVID-associated mucormycosis and aspergillosis being reported. But, there is no data regarding mixed fungal infections in COVID patients.\n\nMaterials and MethodsThe study presented a series of ten consecutive cases with dual invasive molds in patients infected with SARS-CoV-2. Among patients hospitalized with the diagnosis of COVID in May 2021 at a tertiary care center in North India, ten microbiologically confirmed dual/mixed COVID-associated mucor-aspergillosis (CAMA) were evaluated.\n\nResultsAll patients were diabetics with the majority having severe COVID pneumonia (6/10, 60%) either on admission or in the past one month, whilst two were each of moderate (20%) and mild (20%) categories of COVID. The patients were managed with amphotericin-B along with surgical intervention. In this case series, 70% of all CAMA (Rhizopus arrhizus with Aspergillus flavus in seven and Aspergillus fumigatus in three patients) patients survived, connoting the critical importance of a high index of clinical suspicion and accurate microbiological diagnosis for managing invasive molds.\n\nConclusionsMixed fungal infections i.e. CAMA during COVID and post-COVID periods may be an emerging disease. This outbreak is seen particularly in such patients with uncontrolled diabetes, on steroids, or cocktail therapy, or living in unhygienic environments.We believe that our findings would help gain a better insight into the risk and progression of invasive fungal mixed infections among COVID patients and thus play a pivotal role in diagnosing, classifying, and implementing an effective management strategy for treating similar cases in the future.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.05.21261562",
+    "rel_abs": "BackgroundRecent reports indicate that vaccination is effective in reducing symptomatic infection with the Delta variant of SARS-CoV-2 (DV) but is less protective against asymptomatic transmission of DV in outpatients than for earlier variants.\n\nHere we report cryptic transmission associated with high DV viral load among vaccinated patients on an inpatient medical-surgical ward.\n\nMethodsThis observational study included all persons diagnosed with breakthrough SARS-CoV-2 infections at the VA Boston Healthcare System (VABHS) from March 11, 2021 to July 31, 2021, including those tested for surveillance, admission, symptoms, and as part of an outbreak investigation in July 2021. SARS-CoV-2 infection was diagnosed by reverse-transcription polymerase chain reaction (PCR) (Cepheid). Variants were identified by MassARRAY SARS-CoV-2 Variant Panel (36-plex PCR, Agena BioScience) for most breakthrough cases after June 2021 Viral genomic sequencing was performed by the Jackson Laboratory.\n\nResultsAn inpatient was diagnosed with asymptomatic DV infection on routine pre-discharge testing. Contact tracing detected infection in 6 of 38 patients (15.8%), 1 of 168 staff (0.6%), and 1 of 6 visitors (16.7%). Infection at the time of diagnosis was asymptomatic in 4 proximate, vaccinated patients, 1 vaccinated visitor, and 1 vaccinated employee caring for 1 undiagnosed, infected, vaccinated patient. Patients were unmasked, whereas staff wore surgical masks. PCR cycle threshold (Ct) for breakthrough infections indicated more than 1000-fold higher viral load for DV (Ct:21.7{+/-}4.3; n=15) than for earlier variants (Ct: 31.8{+/-}10.9, n=12; p=.003 (t-test)).\n\nConclusionThese findings demonstrate transmission of DV with high viral load between vaccinated inpatients, the continued efficacy of masking and vaccination for protecting healthcare personnel, and the potential need for post-admission surveillance to prevent cryptic DV transmission.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Vanya Singh",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "Katherine Linsenmeyer",
+        "author_inst": "VA Boston Healthcare System and Boston University School of Medicine"
       },
       {
-        "author_name": "Amber Prasad",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Prasan Kumar Panda",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Manjunath Totaganti",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Amit Tyagi",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "Kalpana Gupta",
+        "author_inst": "VA Boston HCS and Boston University School of Medicine"
       },
       {
-        "author_name": "Abhinav Thaduri",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Shalini Rao",
-        "author_inst": "AIIMS Rishikesh"
-      },
-      {
-        "author_name": "Mukesh Bairwa",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "Rebecca Madjarov",
+        "author_inst": "VA Boston Healthcare System"
       },
       {
-        "author_name": "Ashok K Singh",
-        "author_inst": "AIIMS Rishikesh"
+        "author_name": "Michael E. Charness",
+        "author_inst": "VA Boston Healthcare System and Harvard Medical School"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -586521,83 +588576,67 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.08.09.455656",
-    "rel_title": "Reprogramming of the intestinal epithelial-immune cell interactome during SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2021.08.08.455468",
+    "rel_title": "A Tethered Ligand Assay to Probe SARS-CoV-2:ACE2 Interactions",
     "rel_date": "2021-08-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.09.455656",
-    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents an unprecedented worldwide health problem. Although the primary site of infection is the lung, growing evidence points towards a crucial role of the intestinal epithelium. Yet, the exact effects of viral infection and the role of intestinal epithelial-immune cell interactions in mediating the inflammatory response are not known. In this work, we apply network biology approaches to single-cell RNA-seq data from SARS-CoV-2 infected human ileal and colonic organoids to investigate how altered intracellular pathways upon infection in intestinal enterocytes leads to modified epithelial-immune crosstalk. We point out specific epithelial-immune interactions which could help SARS-CoV-2 evade the immune response. By integrating our data with existing experimental data, we provide a set of epithelial ligands likely to drive the inflammatory response upon infection. Our integrated analysis of intra- and inter-cellular molecular networks contribute to finding potential drug targets, and suggest using existing anti-inflammatory therapies in the gut as promising drug repurposing strategies against COVID-19.",
-    "rel_num_authors": 16,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.08.455468",
+    "rel_abs": "SARS-CoV-2 infections are initiated by attachment of the receptor-binding domain (RBD) on the viral Spike protein to angiotensin-converting enzyme-2 (ACE2) on human host cells. This critical first step occurs in dynamic environments, where external forces act on the binding partners and multivalent interactions play critical roles, creating an urgent need for assays that can quantitate SARS-CoV-2 interactions with ACE2 under mechanical load and in defined geometries. Here, we introduce a tethered ligand assay that comprises the RBD and the ACE2 ectodomain joined by a flexible peptide linker. Using magnetic tweezers and atomic force spectroscopy as highly complementary single-molecule force spectroscopy techniques, we investigate the RBD:ACE2 interaction over the whole physiologically relevant force range. We combine the experimental results with steered molecular dynamics simulations and observe and assign fully consistent unbinding and unfolding events across the three techniques, enabling us to establish ACE2 unfolding as a molecular fingerprint. Measuring at forces of 2-5 pN, we quantify the force dependence and kinetics of the RBD:ACE2 bond in equilibrium. We show that the SARS-CoV-2 RBD:ACE2 interaction has higher mechanical stability, larger binding free energy, and a lower dissociation rate in comparison to SARS-CoV-1, which helps to rationalize the different infection patterns of the two viruses. By studying how free ACE2 outcompetes tethered ACE2, we show that our assay is sensitive to prevention of bond formation by external binders. We expect our results to provide a novel way to investigate the roles of mutations and blocking agents for targeted pharmaceutical intervention.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Martina Poletti",
-        "author_inst": "Earlham Institute / Quadram Institute"
-      },
-      {
-        "author_name": "Agatha Treveil",
-        "author_inst": "Earlham Institute, Norwich, UK"
-      },
-      {
-        "author_name": "Leila Gul",
-        "author_inst": "Earlham Institute, Norwich UK"
-      },
-      {
-        "author_name": "Dezso Modos",
-        "author_inst": "Quadram Institute, Norwich, UK"
-      },
-      {
-        "author_name": "Matthew Madgwick",
-        "author_inst": "Earlham Institute"
+        "author_name": "Magnus S. Bauer",
+        "author_inst": "LMU Munich"
       },
       {
-        "author_name": "Marton Olbei",
-        "author_inst": "Earlham Institute, Norwich, UK"
+        "author_name": "Sophia Gruber",
+        "author_inst": "LMU Munich"
       },
       {
-        "author_name": "Balazs Bohar",
-        "author_inst": "Earlham Institute, Norwich, UK"
+        "author_name": "Adina Hausch",
+        "author_inst": "LMU Munich"
       },
       {
-        "author_name": "Alberto Valdeolivas",
-        "author_inst": "Heidelberg University, Heidelberg, Germany"
+        "author_name": "Lukas F. Milles",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Denes Turei",
-        "author_inst": "Heidelberg University, Heidelberg, Germany"
+        "author_name": "Thomas Nicolaus",
+        "author_inst": "LMU Munich"
       },
       {
-        "author_name": "Bram Verstockt",
-        "author_inst": "KU Leuven, Leuven, Belgium"
+        "author_name": "Leonard C. Schendel",
+        "author_inst": "LMU Munich"
       },
       {
-        "author_name": "Sergio Triana",
-        "author_inst": "European Molecular Biology Laboratory, Heidelberg, Germany"
+        "author_name": "Pilar Lopez Navajas",
+        "author_inst": "Biological Research Center Margarita Salas"
       },
       {
-        "author_name": "Theodore Alexandrov",
-        "author_inst": "University of California San Diego, La Jolla, CA, USA"
+        "author_name": "Erik Procko",
+        "author_inst": "University of Illinois at Urbana-Champaign"
       },
       {
-        "author_name": "Julio Saez-Rodriguez",
-        "author_inst": "Heidelberg University, Heidelberg, Germany"
+        "author_name": "Daniel Lietha",
+        "author_inst": "Biological Research Center Margarita Salas"
       },
       {
-        "author_name": "Megan L Stanifer",
-        "author_inst": "Heidelberg University Hospital, Heidelberg, Germany"
+        "author_name": "Rafael C. Bernardi",
+        "author_inst": "Auburn University"
       },
       {
-        "author_name": "Steeve Boulant",
-        "author_inst": "Heidelberg University Hospital, Heidelberg, Germany"
+        "author_name": "Hermann E. Gaub",
+        "author_inst": "LMU Munich"
       },
       {
-        "author_name": "Tamas Korcsmaros",
-        "author_inst": "Earlham Institute / Quadram Institute"
+        "author_name": "Jan Lipfert",
+        "author_inst": "LMU Munich"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2021.08.08.455562",
@@ -588639,43 +590678,47 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.08.05.21261627",
-    "rel_title": "Systematic review protocol exploring the impact of the COVID-19 pandemic on the wellbeing of general practitioners",
+    "rel_doi": "10.1101/2021.08.04.21261576",
+    "rel_title": "When do elementary students need masks in school? Model-estimated risk of in-school SARS-CoV-2 transmission and related infections among household members before and after student vaccination",
     "rel_date": "2021-08-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.05.21261627",
-    "rel_abs": "BackgroundOver recent years chronic stress and burnout have been reported by doctors working in general practice in the UK NHS and internationally. The COVID-19 pandemic has changed general practitioners working lives - adding potential pressures from avoiding infection and addressing pent-up demand for care, but also changing processes such as rapidly taking up remote consultations. To date, there has been a focus on exploring the impact of the pandemic on the wellbeing of hospital clinicians. No registered systematic reviews currently focus on exploring the impact of the pandemic on the mental health and wellbeing of general practitioners.\n\nAims and objectivesTo synthesise the current international evidence base exploring the impact of COVID-19 on the mental health and wellbeing of general practitioners, and which factors are associated with their reported mental health and wellbeing during the pandemic.\n\nMethodsIn this paper we report a systematic review protocol, following PRISMA guidance. In our search strategy we will identify primary research studies or systematic reviews exploring the mental health and wellbeing of general practitioners during the COVID-19 pandemic in four databases (MEDLINE, Embase, PsychInfo and Medrxiv) and Google Scholar. We will hand-search reference lists and grey literature.\n\nTwo reviewers will undertake all stages including study selection, data extraction and quality assessment, with arbitration by a third reviewer where necessary. We will use standardised quality assessment tools to ensure transparency and reduce bias in quality assessment. Depending on the quality of included studies, we may undertake a sensitivity analysis by excluding studies from narrative synthesis that are rated as low quality using the checklists.\n\nWe will describe the findings across studies using narrative thematic data synthesis, and if sufficiently homogenous data are identified, we will pool quantitative findings through meta-analysis.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261576",
+    "rel_abs": "BackgroundWhile CDC guidance for K-12 schools recommends indoor masking regardless of vaccination status, final decisions about masking in schools will be made at the local and state level. The impact of the removal of mask restrictions, however, on COVID-19 outcomes for elementary students, educators/staff, and their households is not well known.\n\nMethodsWe used a previously published agent-based dynamic transmission model of SARS-CoV-2 in K-12 schools to simulate an elementary school with 638 students across 12 scenarios: combinations of three viral infectiousness levels (reflecting wild-type virus, alpha variant, and delta variant) and four student vaccination levels (0%, 25%, 50% and 70% coverage). For each scenario, we varied observed community COVID-19 incidence (0 to 50 cases/100,000 people/day) and mitigation effectiveness (0-100% reduction to in-school secondary attack rate), and evaluated two outcomes over a 30 day period: (1) the probability of at least one in-school transmission, and (2) average increase in total infections among students, educators/staff, and their household members associated with moving from more to less intensive mitigation measures.\n\nResultsOver 30 days in the simulated elementary school, the probability of at least one in-school SARS-CoV-2 transmission and the number of estimated additional infections in the immediate school community associated with changes in mitigation measures varied widely. In one scenario with the delta variant and no student vaccination, assuming that baseline mitigation measures of simple ventilation and handwashing reduce the secondary attack rate by 40%, if decision-makers seek to keep the monthly probability of an in-school transmission below 50%, additional mitigation (e.g., masking) would need to be added at a community incidence of approximately 2/100,000/day. Once students are vaccinated, thresholds shift substantially higher.\n\nLimitationsThe interpretation of model results should be limited by the uncertainty in many of the parameters, including the effectiveness of individual mitigation interventions and vaccine efficacy against the delta variant, and the limited scope of the model beyond the school community. Additionally, the assumed case detection rate (33% of cases detected) may be too high in areas with decreased testing capacity.\n\nConclusionDespite the assumption of high adult vaccination, the risks of both in-school SARS-CoV-2 transmission and resulting infections among students, educators/staff, and their household members remain high when the delta variant predominates and students are unvaccinated. Mitigation measures or vaccinations for students can substantially reduce these risks. These findings underscore the potential role for responsive plans, where mitigation is deployed based on local COVID-19 incidence and vaccine uptake.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Laura Jefferson",
-        "author_inst": "University of York"
+        "author_name": "John Giardina",
+        "author_inst": "Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA"
       },
       {
-        "author_name": "Su Golder",
-        "author_inst": "University of York"
+        "author_name": "Alyssa Bilinski",
+        "author_inst": "Department of Health Services, Policy, and Practice and Department of Biostatistics, Brown School of Public Health, Providence, RI, USA"
       },
       {
-        "author_name": "Veronica Dale",
-        "author_inst": "University of York"
+        "author_name": "Meagan C. Fitzpatrick",
+        "author_inst": "Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD"
       },
       {
-        "author_name": "Holly Essex",
-        "author_inst": "University of York"
+        "author_name": "Emily A. Kendall",
+        "author_inst": "Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, MD"
       },
       {
-        "author_name": "Elizabeth McHugh",
-        "author_inst": "University of York"
+        "author_name": "Benjamin P. Linas",
+        "author_inst": "Boston University Schools of Medicine and Public Health, Boston Medical Center, Boston, MA"
       },
       {
-        "author_name": "Karen Bloor",
-        "author_inst": "University of York"
+        "author_name": "Joshua Salomon",
+        "author_inst": "Center for Health Policy and Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, CA"
+      },
+      {
+        "author_name": "Andrea L. Ciaranello",
+        "author_inst": "Division of Infectious Disease and Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.08.02.21260667",
@@ -590545,55 +592588,43 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.08.06.455424",
-    "rel_title": "Small-molecule ligands can inhibit -1 programmed ribosomal frameshifting in a broad spectrum of coronaviruses",
+    "rel_doi": "10.1101/2021.08.06.455384",
+    "rel_title": "The Inherent Flexibility of Receptor Binding Domains in SARS-CoV-2 Spike Protein",
     "rel_date": "2021-08-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.06.455424",
-    "rel_abs": "Recurrent outbreaks of novel zoonotic coronavirus (CoV) diseases since 2000 have high-lighted the importance of developing therapeutics with broad-spectrum activity against CoVs. Because all CoVs use -1 programmed ribosomal frameshifting (-1 PRF) to control expression of key viral proteins, the frameshift signal in viral mRNA that stimulates -1 PRF provides a promising potential target for such therapeutics. To test the viability of this strategy, we explored a group of 6 small-molecule ligands, evaluating their activity against the frameshift signals from a panel of representative bat CoVs--the most likely source of future zoonoses--as well as SARS-CoV-2 and MERS-CoV. We found that whereas some ligands had notable activity against only a few of the frameshift signals, the serine protease inhibitor nafamostat suppressed -1 PRF significantly in several of them, while having limited to no effect on -1 PRF caused by frameshift signals from other viruses used as negative controls. These results suggest it is possible to find small-molecule ligands that inhibit -1 PRF specifically in a broad spectrum of CoVs, establishing the frameshift signal as a viable target for developing pan-coronaviral therapeutics.",
-    "rel_num_authors": 9,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.06.455384",
+    "rel_abs": "Spike (S) protein is the primary antigenic target for neutralization and vaccine development for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It decorates the virus surface and undergoes large conformational changes of its receptor binding domain (RBD) to enter the host cell, as the abundant structural studies suggest. Here, we observe Down, one-Up, one-Open, and two-Up-like structures in enhanced molecular dynamics simulations without pre-defined reaction coordinates. The RBDA transition from Down to one-Up is supported by transient salt-bridges between RBDA and RBDC and by the glycan at N343B. Reduced interactions between RBDA and RBDB induce the RBDB motions toward two-Up. Glycan shielding for neutralizing antibodies is the weakest in one-Open. Cryptic pockets are revealed at the RBD interfaces in intermediate structures between Down and one-Up. The inherent flexibility in S-protein is, thus, essential for the structure transition and shall be considered for antiviral drug rational design or vaccine development.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Sneha Munshi",
-        "author_inst": "University of Alberta"
-      },
-      {
-        "author_name": "Krishna Neupane",
-        "author_inst": "University of Alberta"
-      },
-      {
-        "author_name": "Sandaru M Ileperuma",
-        "author_inst": "University of Alberta"
-      },
-      {
-        "author_name": "Matthew TJ Halma",
-        "author_inst": "University of Alberta"
+        "author_name": "Hisham M. Dokainish",
+        "author_inst": "Riken"
       },
       {
-        "author_name": "Jamie A Kelly",
-        "author_inst": "University of Maryland"
+        "author_name": "Suyong Re",
+        "author_inst": "National Institutes of Biomedical Innovation, Health, and Nutrition"
       },
       {
-        "author_name": "Clarissa F Halpern",
-        "author_inst": "University of Maryland"
+        "author_name": "Takaharu Mori",
+        "author_inst": "Riken"
       },
       {
-        "author_name": "Jonathan D. Dinman",
-        "author_inst": "University of Maryland"
+        "author_name": "Chigusa Kobayashi",
+        "author_inst": "Riken"
       },
       {
-        "author_name": "Sarah Loerch",
-        "author_inst": "University of California Santa Cruz"
+        "author_name": "Jaewoon Jung",
+        "author_inst": "Riken"
       },
       {
-        "author_name": "Michael T Woodside",
-        "author_inst": "University of Alberta"
+        "author_name": "Yuji Sugita",
+        "author_inst": "Riken"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2021.08.06.455405",
@@ -592751,83 +594782,119 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.08.04.21261538",
-    "rel_title": "Association between obesity and hospitalization in mild COVID-19 young adult outpatients in Brazil: a prospective cohort study",
+    "rel_doi": "10.1101/2021.08.05.455290",
+    "rel_title": "SARS-CoV-2 variants of concern have acquired mutations associated with an increased spike cleavage",
     "rel_date": "2021-08-05",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261538",
-    "rel_abs": "Background/ObjectivesThe aim of this study was to evaluate the association between obesity and hospitalization in mild COVID-19 adult outpatients in Brazil.\n\nSubjects/MethodsAdults with signs and symptoms suggestive of acute SARS-CoV-2 infection who sought two hospitals (one public and one private) emergency department (ED) were prospectively enrolled. Patients with confirmed COVID-19 at inclusion were followed by phone calls at day (D) D7, D14 and D28. Multivariable logistic regression models were employed to explore the association between obesity and other potential predictors for hospitalization.\n\nResultsA total of 1,050 participants were screened, 310 were diagnosed with COVID-19 by RT-PCR. Median age was 37.4 (IQR 29.8-45.0) years, and 186 (60.0%) were female. Duration of symptoms was 3.0 (IQR 2.0-5.0) days, and 10.0 (IQR 8.0-12.0) was the median number of symptoms at inclusion. A total of 98 (31.6%) were obese, and 243 (78.4%) had no previous medical conditions. Twenty three participants (23/310, 7.4%) required hospitalization during the period. After adjusting, obesity (BMI[&ge;]30.0 kg/m2) (OR=2.69, 95%CI 1.63-4.83, P<0.001) and older age (OR=1.05, 95%CI 1.01-1.09, P<0.001), were significantly associated with higher risks of hospitalization.\n\nConclusionsObesity, followed by aging, was the main factor associated with hospital admission for COVID-19 in a young population in a low-middle income country. Our findings highlighted the need for actions to promote additional protection for obese population, such as vaccination, and to encourage lifestyle changes.",
-    "rel_num_authors": 16,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.05.455290",
+    "rel_abs": "For efficient cell entry and membrane fusion, SARS-CoV-2 spike (S) protein needs to be cleaved at two different sites, S1/S2 and S2 by different cellular proteases such as furin and TMPRSS2. Polymorphisms in the S protein can affect cleavage, viral transmission, and pathogenesis. Here, we investigated the role of arising S polymorphisms in vitro and in vivo to understand the emergence of SARS-CoV-2 variants. First, we showed that the S:655Y is selected after in vivo replication in the mink model. This mutation is present in the Gamma Variant Of Concern (VOC) but it also occurred sporadically in early SARS-CoV-2 human isolates. To better understand the impact of this polymorphism, we analyzed the in vitro properties of a panel of SARS-CoV-2 isolates containing S:655Y in different lineage backgrounds. Results demonstrated that this mutation enhances viral replication and spike protein cleavage. Viral competition experiments using hamsters infected with WA1 and WA1-655Y isolates showed that the variant with 655Y became dominant in both direct infected and direct contact animals. Finally, we investigated the cleavage efficiency and fusogenic properties of the spike protein of selected VOCs containing different mutations in their spike proteins. Results showed that all VOCs have evolved to acquire an increased spike cleavage and fusogenic capacity despite having different sets of mutations in the S protein. Our study demonstrates that the S:655Y is an important adaptative mutation that increases viral cell entry, transmission, and host susceptibility. Moreover, SARS-COV-2 VOCs showed a convergent evolution that promotes the S protein processing.",
+    "rel_num_authors": 25,
     "rel_authors": [
       {
-        "author_name": "Ivaine Tais Sauthier Sartor",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Alba Escalera",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Caroline Nespolo David",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Ana S. Gonzalez-Reiche",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Gabriela Heiden Telo",
-        "author_inst": "School of Medicine, Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Brazil"
+        "author_name": "Sadaf Aslam",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Gabriela Oliveira Zavaglia",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Ignacio Mena",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Ingrid Rodrigues Fernandes",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Rebecca L. Pearl",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Luciane Beatriz Kern",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Manon Laporte",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Marcia Polese-Bonatto",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Andrea Fossati",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Thais Raupp Azevedo",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Raveen Rathnasinghe",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Amanda Paz Santos",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "Hala Alshammary",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Walquiria Aparecida Ferreira Almeida",
-        "author_inst": "General Coordination, National Immunization Program, Brazilian Ministry of Health, Brasilia, Brazil"
+        "author_name": "Adriana van de Guchte",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Victor Bertollo Gomes Porto",
-        "author_inst": "General Coordination, National Immunization Program, Brazilian Ministry of Health, Brasilia, Brazil"
+        "author_name": "Mehdi Bouhaddou",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Fernanda Hammes Varela",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil; School of Medicine, Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre,"
+        "author_name": "Thomas Kehrer",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Marcelo Comerlato Scotta",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil; School of Medicine, Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre,"
+        "author_name": "Lorena Zuliani-Alvarez",
+        "author_inst": "University of California San Francisco"
       },
       {
-        "author_name": "Regis Goulart Rosa",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil"
+        "author_name": "David A. Meekins",
+        "author_inst": "Kansas State University"
       },
       {
-        "author_name": "Renato T Stein",
-        "author_inst": "Social Responsibility, Hospital Moinhos de Vento, Porto Alegre, Brazil; School of Medicine, Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre,"
+        "author_name": "Velmurugan Balaraman",
+        "author_inst": "Kansas State University"
       },
       {
-        "author_name": "- COVIDa study group",
-        "author_inst": ""
+        "author_name": "Chester McDowell",
+        "author_inst": "Kansas State University"
+      },
+      {
+        "author_name": "Juergen  A Richt",
+        "author_inst": "Kansas State University"
+      },
+      {
+        "author_name": "Goran Bajic",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Emilia Mia Sordillo",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Nevan Krogan",
+        "author_inst": "University of California San Francisco"
+      },
+      {
+        "author_name": "Viviana Simon",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Randy A. Albrecht",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Harm van Bakel",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Adolfo Garcia-Sastre",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Teresa Aydillo",
+        "author_inst": "Icahn School of Medicine at Mount Sinai Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.08.05.455262",
@@ -594345,175 +596412,63 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.08.02.21261379",
-    "rel_title": "An adaptive randomized controlled trial of non-invasive respiratory strategies in acute respiratory failure patients with COVID-19",
+    "rel_doi": "10.1101/2021.08.02.21261504",
+    "rel_title": "SARS-CoV-2 antibody binding and neutralization in dried blood spot eluates and paired plasma",
     "rel_date": "2021-08-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.02.21261379",
-    "rel_abs": "BackgroundBoth continuous positive airway pressure (CPAP) and high-flow nasal oxygenation (HFNO) have been recommended for acute respiratory failure in COVID-19. However, uncertainty exists regarding effectiveness and safety.\n\nMethodsIn the Recovery-Respiratory Support multi-center, three-arm, open-label, adaptive, randomized controlled trial, adult hospitalized patients with acute respiratory failure due to COVID-19, deemed suitable for treatment escalation, were randomly assigned to receive CPAP, HFNO, or conventional oxygen therapy. Comparisons were made between each intervention and conventional oxygen therapy. The primary outcome was a composite of tracheal intubation or mortality within 30-days.\n\nResultsOver 13-months, 1272 participants were randomized and included in the analysis (380 (29.9%) CPAP; 417 (32.8%) HFNO; 475 (37.3%) conventional oxygen therapy). The need for tracheal intubation or mortality within 30-days was lower in the CPAP group (CPAP 137 of 377 participants (36.3%) vs conventional oxygen therapy 158 of 356 participants (44.4%); unadjusted odds ratio 0.72; 95% CI 0.53 to 0.96, P=0.03). There was no difference between HFNO and conventional oxygen therapy (HFNO 184 of 414 participants (44.4%) vs conventional oxygen therapy 166 of 368 participants (45.1%); unadjusted odds ratio 0.97; 95% CI 0.73 to 1.29, P=0.85).\n\nConclusionsCPAP, compared with conventional oxygen therapy, reduced the composite outcome of intubation or death within 30 days of randomisation in hospitalized adults with acute respiratory failure due to COVID-19. There was no effect observed, compared with conventional oxygen therapy, with the use of HFNO.\n\n(Funded by the UK National Institute for Health Research; ISRCTN 16912075).",
-    "rel_num_authors": 39,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.02.21261504",
+    "rel_abs": "Widescale assessment of SARS-CoV-2-specific antibodies is critical to understanding population seroprevalence, correlates of protection, and the longevity of vaccine-elicited responses. Most SARS-CoV-2 studies characterize antibody responses in plasma/sera. While reliable and broadly used, these samples pose several logistical restrictions such as requiring venipuncture for collection and cold chain for transportation and storage. Dried blood spots (DBS) overcome these barriers as they can be self-collected by fingerstick and mailed and stored at ambient temperature. Here, we evaluate the suitability of DBS for SARS-CoV-2 antibody assays by comparing several antibody responses between paired plasma and DBS from SARS-CoV-2 convalescent and vaccinated individuals. We found that DBS not only reflected plasma antibody binding by ELISA and epitope profiles using phage-display, but also yielded SARS-CoV-2 neutralization titers that highly correlated with paired plasma. Neutralization measurement was further streamlined by adapting assays to a high-throughput 384-well format. This study supports the adoption of DBS for numerous SARS-CoV-2 binding and neutralization assays.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Gavin D Perkins",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK; University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
-      },
-      {
-        "author_name": "Chen Ji",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK"
-      },
-      {
-        "author_name": "Bronwen A Connolly",
-        "author_inst": "Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry and Biomedical Science, Queens University Belfast, Belfast, UK; Lane Fox Cli"
-      },
-      {
-        "author_name": "Keith Couper",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK; University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
-      },
-      {
-        "author_name": "Ranjit Lall",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK"
-      },
-      {
-        "author_name": "J Kenneth Baillie",
-        "author_inst": "Roslin Institute, University of Edinburgh, Midlothian, UK; MRC Human Genetics Unit, Institute for Genetics and Molecular Medicine, University of Edinburgh, Edin"
-      },
-      {
-        "author_name": "Judy M Bradley",
-        "author_inst": "Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry and Biomedical Science, Queens University Belfast, Belfast, UK"
-      },
-      {
-        "author_name": "Paul Dark",
-        "author_inst": "NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester, UK; Salford Royal Hospital, Northern Care Alliance NHS Group, Manchester, UK"
-      },
-      {
-        "author_name": "Chirag Dave",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
-      },
-      {
-        "author_name": "Anthony De Soyza",
-        "author_inst": "Population and Health Science Institute, NIHR Biomedical Research Centre, Newcastle, University, Newcastle Upon Tyne, UK; Newcastle-Upon-Tyne Hospitals NHS Foun"
-      },
-      {
-        "author_name": "Anna V Dennis",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
-      },
-      {
-        "author_name": "Anne Devrell",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK; Research Champion Team, West Midlands Clinical Research Network, Wolv"
-      },
-      {
-        "author_name": "Sara Fairbairn",
-        "author_inst": "Grange University Hospital, Aneurin Bevan University Health Board, Cwmbran, UK"
-      },
-      {
-        "author_name": "Hakim Ghani",
-        "author_inst": "Watford General Hospital, West Hertfordshire Hospitals NHS Trust, Watford, UK"
-      },
-      {
-        "author_name": "Ellen A Gorman",
-        "author_inst": "Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry and Biomedical Science, Queens University Belfast, Belfast, UK"
-      },
-      {
-        "author_name": "Christopher A Green",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
-      },
-      {
-        "author_name": "Nicholas Hart",
-        "author_inst": "Lane Fox Clinical Respiratory Physiology Research Centre, Guys and St.Thomas NHS Foundation Trust, London, UK; Centre for Human and Applied Physiological Scienc"
-      },
-      {
-        "author_name": "Siew Wan Hee",
-        "author_inst": "Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK"
-      },
-      {
-        "author_name": "Zoe Kimbley",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
-      },
-      {
-        "author_name": "Shyam Madathil",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
-      },
-      {
-        "author_name": "Nicola McGowan",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK"
-      },
-      {
-        "author_name": "Benjamin Messer",
-        "author_inst": "Newcastle-Upon-Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK"
-      },
-      {
-        "author_name": "Jay Naisbitt",
-        "author_inst": "Fairfield General Hospital, Pennine Acute Hospitals NHS Trust, Northern Care Alliance NHS Group, Bury, UK"
-      },
-      {
-        "author_name": "Chloe Norman",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK"
-      },
-      {
-        "author_name": "Dhruv Parekh",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Inflammation and Ageing, School of Medical and Dental Sciences, University of"
-      },
-      {
-        "author_name": "Emma M Parkin",
-        "author_inst": "Fairfield General Hospital, Pennine Acute Hospitals NHS Trust, Northern Care Alliance NHS Group, Bury, UK"
-      },
-      {
-        "author_name": "Jaimin Patel",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Inflammation and Ageing, School of Medical and Dental Sciences, University of"
-      },
-      {
-        "author_name": "Scott E Regan",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK"
-      },
-      {
-        "author_name": "Clare Ross",
-        "author_inst": "Imperial College Healthcare NHS Trust, London, UK"
+        "author_name": "Hannah L. Itell",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Anthony J Rostron",
-        "author_inst": "Sunderland Royal Hospital, South Tyneside and Sunderland NHS Foundation Trust, Sunderland, UK; Translational and Clinical Research Institute, Newcastle Universi"
+        "author_name": "Haidyn Weight",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Mohammad Saim",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
+        "author_name": "Carolyn S. Fish",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Anita K Simonds",
-        "author_inst": "Royal Brompton and Harefield Hospital, Guys and St Thomas NHS Foundation Trust, London, UK"
+        "author_name": "Jennifer K. Logue",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Emma Skilton",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK"
+        "author_name": "Nicholas Franko",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Nigel Stallard",
-        "author_inst": "Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK"
+        "author_name": "Caitlin R. Wolf",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Michael Steiner",
-        "author_inst": "Institute for Lung Health, NIHR BRC Respiratory Medicine, Department of Respiratory Sciences, University of Leicester, Leicester, UK"
+        "author_name": "Denise J. McCulloch",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Rama Vancheeswaran",
-        "author_inst": "Watford General Hospital, West Hertfordshire Hospitals NHS Trust, Watford, UK"
+        "author_name": "Jared Galloway",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Joyce Yeung",
-        "author_inst": "Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK; University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK"
+        "author_name": "Frederick A. Matsen IV",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Daniel F McAuley",
-        "author_inst": "Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry and Biomedical Science, Queens University Belfast, Belfast, UK; Royal Victor"
+        "author_name": "Helen Y. Chu",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "- Recovery- RS collaborators",
-        "author_inst": ""
+        "author_name": "Julie Overbaugh",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "intensive care and critical care medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.07.30.21261372",
@@ -596483,69 +598438,125 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.07.30.21261383",
-    "rel_title": "COVID-19 Vaccine Uptake among U.S. Child Care Providers",
+    "rel_doi": "10.1101/2021.07.29.21261312",
+    "rel_title": "COVID-ONE-humoral immune: The One-stop Database for COVID-19-specific Antibody Responses and Clinical Parameters",
     "rel_date": "2021-08-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.30.21261383",
-    "rel_abs": "STRUCUTRED ABSTRACTO_ST_ABSObjectivesC_ST_ABSEnsuring a high COVID-19 vaccine uptake among U.S. child care providers is crucial to mitigating the public health implications of child-to-staff and staff-to-child transmission of SARS-CoV-2; however, the vaccination rate among this group is unknown.\n\nMethodsTo characterize the vaccine uptake among U.S. child care providers, we conducted a cross-sectional survey of the child care workforce. Providers were identified through various national databases and state registries. A link to the survey was sent via email between May 26 and June 23, 2021. Out of 44,771 potential respondents, 21,663 responded (48.4%).\n\nResultsOverall COVID-19 vaccine uptake among U.S. child care providers (78.1%, 95% CI [77.3% to 78.9%]) was higher than that of the U.S. adult population (65%). Vaccination rates varied from 53.5% to 89.4% between states. Vaccine uptake differed significantly (p < .01) based on respondent age (70.0% for ages 25-34, 91.5% for ages 75-84), race (70.0% for Black or African Americans, 92.5% for Asian-Americans), annual household income (70.7% for <$35,000, 85.0% for>$75,000), and childcare setting (72.9% for home-based, 79.7% for center-based).\n\nConclusionsCOVID-19 vaccine uptake among U.S. child care providers was higher than that of the general U.S. adult population. Those who were younger, lower income, Black or African American, resided in states either in the Mountain West or the South, and/or worked in home-based childcare programs reported the lowest rates of vaccination; state public health leaders and lawmakers should prioritize these subgroups for placement on the policy agenda to realize the largest gains in vaccine uptake among providers.\n\nTables of Contents SummaryThis article describes the results of a national survey of childcare providers to determine the overall COVID-19 vaccine uptake and the gaps in vaccine coverage.\n\nWhats Known on This SubjectEnsuring a high COVID-19 vaccine uptake among U.S. child care providers is crucial to mitigating the public health implications of child-to-staff and staff-to-child transmission of SARS-CoV-2; however, the vaccination rate among this group is unknown.\n\nWhat This Study AddsWhile the vaccine uptake among U.S. child care providers was higher than that of U.S. adults, certain subgroups continue to warrant focused attention for outreach and/or placement on the policy agenda.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.29.21261312",
+    "rel_abs": "Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the \"START\" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.",
+    "rel_num_authors": 28,
     "rel_authors": [
       {
-        "author_name": "Kavin Patel",
-        "author_inst": "Yale University"
+        "author_name": "Zhaowei Xu",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "Amyn A. Malik",
-        "author_inst": "Yale University"
+        "author_name": "Yang Li",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "Aiden Lee",
-        "author_inst": "Yale University"
+        "author_name": "Qing Lei",
+        "author_inst": "Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Madeline Klotz",
-        "author_inst": "Yale University"
+        "author_name": "Likun Huang",
+        "author_inst": "Fujian Key Laboratory of Crop Breeding by Design, Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agricult"
       },
       {
-        "author_name": "John Eric Humphries",
-        "author_inst": "Yale University"
+        "author_name": "Dan-yun Lai",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "Thomas Murray",
-        "author_inst": "Yale University"
+        "author_name": "Shu-juan Guo",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "David Wilkinson",
-        "author_inst": "Yale University"
+        "author_name": "He-wei Jiang",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "Mehr Shafiq",
-        "author_inst": "Yale University"
+        "author_name": "Hongyan Hou",
+        "author_inst": "Department of Clinical Laboratory, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Inci Yildirim",
-        "author_inst": "Yale University"
+        "author_name": "Yun-xiao Zheng",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "Jad Elharake",
-        "author_inst": "Yale University"
+        "author_name": "Xue-ning Wang",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "Rachel Diaz",
-        "author_inst": "Yale University"
+        "author_name": "Jiaoxiang Wu",
+        "author_inst": "Tongren Hospital, Shanghai Jiao Tong University School of Medicine"
       },
       {
-        "author_name": "Chin Reyes",
-        "author_inst": "Yale University"
+        "author_name": "Ming-liang Ma",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       },
       {
-        "author_name": "Saad Omer",
-        "author_inst": "Yale University"
+        "author_name": "Bo Zhang",
+        "author_inst": "Department of Clinical Laboratory, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Walter Gilliam",
-        "author_inst": "Yale University"
+        "author_name": "Hong Chen",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
+      },
+      {
+        "author_name": "Caizheng Yu",
+        "author_inst": "Department of Public Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Jun-biao Xue",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
+      },
+      {
+        "author_name": "Hai-nan Zhang",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
+      },
+      {
+        "author_name": "Huan Qi",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
+      },
+      {
+        "author_name": "Siqi Yu",
+        "author_inst": "Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University"
+      },
+      {
+        "author_name": "Mingxi Lin",
+        "author_inst": "Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University"
+      },
+      {
+        "author_name": "Yandi Zhang",
+        "author_inst": "Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xiaosong Lin",
+        "author_inst": "Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Zongjie Yao",
+        "author_inst": "Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Huiming Sheng",
+        "author_inst": "Tongren Hospital, Shanghai Jiao Tong University School of Medicine"
+      },
+      {
+        "author_name": "Ziyong Sun",
+        "author_inst": "Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Feng Wang",
+        "author_inst": "Department of Clinical Laboratory, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xionglin Fan",
+        "author_inst": "Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Sheng-ce Tao",
+        "author_inst": "Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong Universit"
       }
     ],
     "version": "1",
@@ -598513,51 +600524,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.07.28.21261138",
-    "rel_title": "Estimates of Single Dose and Full Dose BNT162b2 Vaccine Effectiveness among USAF Academy cadets, 1 Mar - 1 May 2021",
+    "rel_doi": "10.1101/2021.07.28.21261286",
+    "rel_title": "Variations in Non-Pharmaceutical Interventions by State Correlate with COVID-19 Disease Outcomes",
     "rel_date": "2021-07-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.28.21261138",
-    "rel_abs": "Beginning in early March 2021 and continuing through May 2021, the USAF Academy began vaccinating cadets for protection against the SARS-CoV-2 virus with the BNT162b2 (Pfizer-BioNTech) mRNA vaccine. During this period, vaccination of the almost 4200 cadet population increased from 3% to 85% and prevalence of COVID-19 in the cadet population was constant at approximately 0.4% as indicated by weekly surveillance testing. In this study, vaccine effectiveness at preventing infection is estimated by comparing infection risk as a function of time since vaccination. A statistically significant four-fold reduction in infection risk was observed 14 days after the first vaccine dose and an eleven-fold reduction in infection risk was observed in fully vaccinated cadets. Overall, the Pfizer-BioNTech vaccine was 91% (95% confidence interval = 55-99%) effective at preventing infection in healthy young adults (17-26 years of age) in a university setting and military training environment.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.28.21261286",
+    "rel_abs": "The COVID-19 pandemic highlighted the lack of understanding around effective public health interventions to curtail the spread of an emerging respiratory virus. Here, we examined the public health approaches implemented by each state to limit the spread and burden of COVID-19. Our analysis revealed that stronger statewide interventions positively correlated with fewer COVID-19 deaths, but some neighboring states with distinct intervention strategies had similar SARS-CoV-2 case trajectories. Additionally, more than two weeks is needed to observe an impact on SARS-CoV-2 cases after an intervention is implemented. These data provide a critical framework to inform future interventions during emerging pandemics.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Douglas P Wickert",
-        "author_inst": "USAF Academy"
+        "author_name": "Annika J Avery",
+        "author_inst": "Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine"
       },
       {
-        "author_name": "Erin Almand",
-        "author_inst": "US Air Force Academy"
+        "author_name": "Jiayi Wang",
+        "author_inst": "Statistics and Data Science Department, Carnegie Mellon University"
       },
       {
-        "author_name": "Christopher A Cullenbine",
-        "author_inst": "USAF Academy"
+        "author_name": "Xinyu Ma",
+        "author_inst": "Statistics and Data Science Department, Carnegie Mellon University"
       },
       {
-        "author_name": "Odaro J Huckstep",
-        "author_inst": "USAF Academy"
+        "author_name": "Qingkai Pan",
+        "author_inst": "Statistics and Data Science Department, Carnegie Mellon University"
       },
       {
-        "author_name": "Joseph Rohrer",
-        "author_inst": "USAF Academy"
+        "author_name": "Elizabeth E McGrady",
+        "author_inst": "Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine"
       },
       {
-        "author_name": "John C Sitko",
-        "author_inst": "USAF Academy"
+        "author_name": "Zongyuan Yuan",
+        "author_inst": "Statistics and Data Science Department, Carnegie Mellon University"
       },
       {
-        "author_name": "James Jordan Steel",
-        "author_inst": "USAF Academy"
+        "author_name": "Yuqing Liang",
+        "author_inst": "Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine"
       },
       {
-        "author_name": "Steven Hasstedt",
-        "author_inst": "USAF Academy"
+        "author_name": "Rebecca Nugent",
+        "author_inst": "Statistics and Data Science Department, Carnegie Mellon University"
+      },
+      {
+        "author_name": "Seema S Lakdawala",
+        "author_inst": "Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.07.28.21261228",
@@ -600395,37 +602410,89 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.07.27.21261221",
-    "rel_title": "Changes in household food security, access to health services, and income in northern Lao PDR during the COVID-19 pandemic",
+    "rel_doi": "10.1101/2021.07.28.21261212",
+    "rel_title": "An investigation of spatial-temporal patterns and predictions of the COVID-19 pandemic in Colombia, 2020-2021",
     "rel_date": "2021-07-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.27.21261221",
-    "rel_abs": "BackgroundThe COVID-19 pandemic is expected to exacerbate food insecurity in low- and middle-income countries, through loss of income and disrupted food supply chains. Lao PDR has among the highest rates of malnutrition in Southeast Asia. We assessed the relative difficulty in meeting food needs during the COVID-19 pandemic in rural districts of Luang Prabang Province, Lao PDR compared to before; determined associations between pandemic-associated difficulties in food access and household, maternal and child food security; and identified resiliency-promoting strategies.\n\nMethodsIn November 2020, households (N = 1,122) with children under five years were interviewed. Respondents reported the relative ease of access of food and health care as well as changes in income and expenditures compared to before March 2020. We used generalized linear models with cluster robust standard errors to assess univariate and multivariate associations.\n\nResultsNearly four-fifths (78.5%) found it harder to meet household food needs during the pandemic. The most common reasons were increased food prices (51.2%), loss of income (45.3%), and decreased food availability (36.6%). Adjusting for demographics, households with increased difficulty meeting food needs had lower food consumption scores and child dietary diversity. Over 85% of households lost income during the pandemic. Decreased expenditures was associated with reliance on more extreme coping strategies to meet food needs. The households who experienced no change in meeting food needs produced a greater percentage of their food from homegrown methods (4.22% more, 95% CI: 1.28, 7.15), than households who found it more difficult. We estimated that decreases in child bodyweight by 0.5 - 1% would increase wasting in this population by 1.7 - 2.1 percentage points.\n\nConclusionsPandemic-associated shocks may have large effects on malnutrition prevalence. Action is needed to mitigate consequences of the pandemic on nutrition. Local food production and safety net programs that offset income losses may help.\n\nSummary BoxO_ST_ABSWhat is already known?C_ST_ABSThe COVID-19 pandemic has disrupted food supply chains and livelihoods, causing concerns that a global nutrition crisis is imminent and prompting leaders from United Nations agencies to issue an immediate call to action to direct funds towards prevention of child malnutrition. While documented COVID-19 transmission in Lao PDR was lower than that of surrounding counties, malnutrition rates are high, particularly in the northern province of Luang Prabang, which is heavily reliant on tourism for livelihoods.\n\nWhat are the new findings?Nearly four-fifths of those interviewed in Luang Prabang Province, Lao PDR reported that it was harder to meet their households food needs, compared to before the pandemic, with 51% attributing the reason to increased food prices. Over 85% of households reported losing income. Lower expenditures and increased difficulty obtaining food were both associated with lower household food consumption scores and higher household coping strategies, in adjusted analyses. Households who obtained a greater proportion of their foods through home production appeared more resilient than households who obtained a greater proportion of their foods through purchasing.\n\nWhat do the new findings imply?The pandemic may deeply exacerbate food insecurity in Lao PDR, potentially leading to increases in child wasting. Increased local food production and establishment of safety net programs that offset income losses may be two strategies that address this problem among this population.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.28.21261212",
+    "rel_abs": "Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 4,240,982 cases and 106,544 deaths as of June 30, 2021. This motivates an investigation of the SARS-CoV-2 transmission dynamics at the national and regional level using case incidence data. Mathematical models are employed to estimate the transmission potential and perform short-term forecasts of the COVID-19 epidemic trajectory in Colombia. Furthermore, geographic heterogeneity of COVID-19 in Colombia is examined along with the analysis of mobility and social media trends, showing that the increase in mobility in July 2020 and January 2021 were correlated with surges in case incidence. The estimation of national and regional reproduction numbers shows sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Moreover, most recent estimates of reproduction number are >1.0 at the national and regional levels as of May 30, 2021. Further, the 30-day ahead short-term forecasts obtained from Richards model present a sustained decline in case counts in contrast to the sub-epidemic and GLM model. Nevertheless, our spatial analysis in Colombia shows distinct variations in incidence rate patterns across different departments that can be grouped into four distinct clusters. Lastly, the correlation of social media trends and adherence to social distancing measures is observed by the fact that a spike in the number of tweets indicating the stay-at-home orders was observed in November 2020 when the case incidence had already plateaued.\n\nAuthor summaryAs the COVID-19 pandemic continues to spread across Colombia, studies highlighting the intensity of the pandemic become imperative for appropriate resource allocation and informing public health policies. In this study we utilize mathematical models to infer the transmission dynamics of SARS-CoV-2 at the regional and national level as well as short-term forecast the COVID-19 epidemic trajectory. Moreover, we examine the geographic heterogeneity of the COVID-19 case incidence in Colombia along with the analysis of mobility and social media trends in relation to the observed COVID-19 case incidence in the country. The estimates of reproduction numbers at the national and regional level show sustained disease transmission as of May 30, 2021. Moreover, the 30-day ahead short-term forecasts for the most recent time-period (June 1-June 30, 2021) generated from the mathematical models needs to be interpreted with caution as the Richards model point towards a sustained decline in case incidence contrary to the GLM and sub-epidemic wave model. Nevertheless, the spatial analysis in Colombia shows distinct variations in incidence rate patterns across different departments that can be grouped into four distinct clusters. Lastly, the social media and mobility trends explain the occurrence of case resurgences over the time.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Jennifer R Head",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Amna Tariq",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Tsira Chakhaia",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Sushma Dahal",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Alexander Ewing",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Xinyi Hua",
+        "author_inst": "Georgia Southern University"
+      },
+      {
+        "author_name": "Sylvia K. Ofori",
+        "author_inst": "Georgia Southern University"
       },
       {
-        "author_name": "Phetsavanh Chanthavilay",
-        "author_inst": "University of Health Sciences, Vientiane, Lao PDR"
+        "author_name": "Olaseni Prince",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Argita Salindri",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Ayotomiwa Ezekiel Adeniyi",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Juan M. Banda",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Pavel Skums",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Ruiyan Luo",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Leidy Y. Lara-Diaz",
+        "author_inst": "Universidad de Concepcion, Concepcion, Chile"
+      },
+      {
+        "author_name": "Raimund Burger",
+        "author_inst": "Universidad de Concepcion, Concepcion, Chile"
+      },
+      {
+        "author_name": "Isaac Chun-Hai Fung",
+        "author_inst": "Georgia Southern University"
       },
       {
-        "author_name": "Helen Catton",
-        "author_inst": "Save the Children International, Lao PDR"
+        "author_name": "Eunha Shim",
+        "author_inst": "Soongsil University"
       },
       {
-        "author_name": "Ammaline Vongsitthi",
-        "author_inst": "Save the Children International, Lao PDR"
+        "author_name": "Alexander Kirpich",
+        "author_inst": "Georgia State University"
       },
       {
-        "author_name": "Kelley Khamphouxay",
-        "author_inst": "Save the Children International, Lao PDR"
+        "author_name": "Anuj Srivastava",
+        "author_inst": "Florida State University"
       },
       {
-        "author_name": "Niphone Simphaly",
-        "author_inst": "Luang Prabang Provincial Health Department, Lao PDR"
+        "author_name": "Gerardo Chowell",
+        "author_inst": "Georgia State University"
       }
     ],
     "version": "1",
@@ -602125,83 +604192,67 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.07.25.21260838",
-    "rel_title": "Doxycycline is a safe alternative to Hydroxychloroquine + Azithromycin to prevent clinical worsening and hospitalization in mild COVID-19 patients: An open label randomized clinical trial (DOXYCOV)",
-    "rel_date": "2021-07-29",
+    "rel_doi": "10.1101/2021.07.25.21260967",
+    "rel_title": "Influence of Novel Coronavirus COVID-19 and HIV: A Scoping Review of Hospital Course and Symptomatology",
+    "rel_date": "2021-07-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.25.21260838",
-    "rel_abs": "ObjectiveWe aimed to compare the safety and efficacy of a doxycycline-based regimen against the national standard guidelines (Hydroxychloroquine plus Azithromycin) for the treatment of mild symptomatic COVID-19.\n\nMethodsWe conducted an open-label, randomized, non-inferiority trial, in Cameroon comparing Doxycycline 100mg, twice daily for 7 days versus Hydroxychloroquine, 400 mg daily for 5 days and Azithromycin 500mg at day 1 and 250mg from day 2 through 5, in mild COVID-19 patients. Clinical improvement, biological parameters and adverse events were assessed. The primary outcome was the proportion of clinical cure at day 3, 10 and 30. Non-inferiority was determined by the clinical cure rate between protocols with a 20 percentage points margin.\n\nResults194 participants underwent randomization and were treated with Doxycycline (n=97) or Hydroxychloroquine-Azithromycin (n=97). At day 3, 74/92 (80.4%) participants on Doxycycline versus 77/95 (81.1%) on Hydroxychloroquine-Azithromycin -based protocols were asymptomatic (p=0.91). At day 10, 88/92 (95.7%) participants on Doxycycline versus 93/95 (97.9%) on Hydroxychloroquine-Azithromycin were asymptomatic (p=0.44). At day 30 all participants were asymptomatic. SARS-CoV2 PCR was negative at Day 10 in 60/92 (65.2%) participants allocated to Doxycycline and 63/95 (66.3%) participants allocated to Hydroxychloroquine-Azithromycin. None of the participants were admitted for worsening of the disease after treatment initiation.\n\nConclusionDoxycycline 100 mg twice daily for 7 days is as effective and safe as Hydroxychloroquine-Azithromycin, for preventing clinical worsening of mild symptomatic or asymptomatic COVID-19, and achieving virological suppression.\n\nStrengths and Limitations[tpltrtarr] This study is one of the first randomized trial, assessing the efficacy and tolerance of Doxycycline to treat COVID-19\n[tpltrtarr]It is one of the first to evaluate disease progression and need to hospitalization in mild or asymptomatic COVID-19\n[tpltrtarr]Patients will not receive identical treatments\n[tpltrtarr]Doxycycline has advantages in terms of availability, safety and cost compared to Hydroxychloroquine and Azytromycin\n[tpltrtarr]Though this study has encounter 7 lost to follow-up, this does not have a major influence on our results\n[tpltrtarr]These data will assist clinicians in their daily practice, and provide a new tool for the fight against COVID-19",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.25.21260967",
+    "rel_abs": "BackgroundAn outbreak of novel coronavirus (SARS- CoV-2) was observed on December 2019 in Wuhan, China which led to a global pandemic declared in March 2020. As a consequence, it imposed delirious consequences in patients with underlying co - morbid conditions that make them immunocompromised. The purpose of this paper is to provide an in - depth review of influence of COVID - 19 in patients with underlying HIV in terms of mortality and hospitalization.\n\nAuthors also aim to provide a thorough risk analysis of hospitalization, ICU admission and mortality of PLWH and COVID-19. The secondary objective was to analyze the CD4+ count variations and outcome of COVID - 19 and to correlate if ART provided a protective role. Authors also aim to provide an evaluation of typical clinical presentation of COVID-19 in PLWH. ART is found to show activity against SARS-CoV-2 in vitro, and there is some similarity in the structure of HIV-1 gp41 and S2 proteins of SARS-CoV since they both belong to +ssRNA type.\n\nMethodsWe conducted a literature review using search engines namely, Cochrane, PubMed and Google Scholar. The following keywords were targeted: \"COVID-19,\" \"SARS-CoV-2,\" and \"HIV.\" We included case reports, case series, and cohort (retrospective and prospective) studies. We excluded clinical trials and review articles. We came across 23 articles that met the inclusion criteria. PRISMA guidelines were followed for study acquisition (Fig. 9).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=176 SRC=\"FIGDIR/small/21260967v1_fig9.gif\" ALT=\"Figure 9\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@1df3963org.highwire.dtl.DTLVardef@30c4c8org.highwire.dtl.DTLVardef@1c729a4org.highwire.dtl.DTLVardef@7f0543_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFig.9C_FLOATNO PRISMA guidelines for study acquisition\n\nC_FIG ResultsFrom the 23 studies, we found a total of 651 PLWH with confirmed COVID-19 (549, 91, and 11 in cohorts, case series, and case reports, respectively). The overall risk of hospital admission from pooled data of the 23 reviewed articles was 69.13% (450/651), ICU admission was 12.90% (84/651) in total infected patients, and 18.67% (84/450) among hospitalized patients. The overall case fatality rate from the 23 reviewed articles was 11.21 (73/651).A weak positive correlation was found between CD4+ counts and hospital admissions in case series and case reports, while the weak negative correlation was found in cohorts. For mortality, there was a negative weak association in the cohorts and in case series, while a weak positive was seen in case reports (Fig.7). We assessed the presenting symptoms of PLWH with COVID-19, and our review demonstrated this group does not greatly differ from the rest of the population, as their common presenting symptoms were cough, fever, and SOB.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC=\"FIGDIR/small/21260967v1_fig7.gif\" ALT=\"Figure 7\">\nView larger version (37K):\norg.highwire.dtl.DTLVardef@132a333org.highwire.dtl.DTLVardef@1788387org.highwire.dtl.DTLVardef@10335a5org.highwire.dtl.DTLVardef@1b70c29_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFig.7C_FLOATNO Results: As scoping review of HIV and COVID-19\n\nC_FIG ConclusionOur results indicated that there was a high rate of hospitalization, ICU admission, and mortality among patients living with HIV and COVID-19. PLWH needs to be noted as a high-risk group for COVID-19 complications and severity. We recommend that PLWH be closely monitored by their physicians and strictly adhere to antiretroviral therapy and standard universal COVID-19 precautions.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Eugene Sobngwi",
-        "author_inst": "University of Yaounde 1"
-      },
-      {
-        "author_name": "Sylvain Zemsi",
-        "author_inst": "RSD Institute"
-      },
-      {
-        "author_name": "Magellan Guewo-Fokeng",
-        "author_inst": "RSD Institute"
-      },
-      {
-        "author_name": "Jean Claude Katte",
-        "author_inst": "RSD Institute"
-      },
-      {
-        "author_name": "Charles Kouanfack",
-        "author_inst": "Yaounde Central Hospital"
+        "author_name": "Mona Sheikh",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Liliane Mfeukeu-Kuate",
-        "author_inst": "Yaounde Central Hospital"
+        "author_name": "Shavy Nagpal",
+        "author_inst": "The Research Institute of St. Joe's Hamilton"
       },
       {
-        "author_name": "Armel Zemsi",
-        "author_inst": "Yaounde Central Hospital"
+        "author_name": "Madiha Zaidi",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Yves Wasnyo",
-        "author_inst": "RSD Institute"
+        "author_name": "Rupalakshmi Vijayan",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Antoinette Assiga-Ntsama",
-        "author_inst": "Yaounde Central Hospital"
+        "author_name": "Wanessa Matos",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Jean Arnaud Ndi-Manga",
-        "author_inst": "RSD Institute"
+        "author_name": "Neguemadji Ngardig Ngaba",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Joelle S Tambekou",
-        "author_inst": "RSD Institute"
+        "author_name": "Lordstrong Akano",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "William Ngatchou",
-        "author_inst": "University of Douala, Faculty of Medicine and Pharmaceutical Sciences"
+        "author_name": "Shazia Q. Shah",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Charlotte Moussi-Omgba",
-        "author_inst": "Ministry of Public Health Cameroon"
+        "author_name": "Samia Jahan",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Jean-Claude Mbanya",
-        "author_inst": "Yaounde Central Hospital"
+        "author_name": "Camille Go",
+        "author_inst": "Larkin Hospital"
       },
       {
-        "author_name": "Pierre Ongolo-Zogo",
-        "author_inst": "Yaounde Central Hospital"
+        "author_name": "Sindhu Thevuthasan",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       },
       {
-        "author_name": "Pierre-Joseph Fouda",
-        "author_inst": "Yaounde Central Hospital"
+        "author_name": "George Michel",
+        "author_inst": "Department of Medicine, Larkin Community Hospital South Miami, Florida, US"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pharmacology and therapeutics"
+    "category": "hiv aids"
   },
   {
     "rel_doi": "10.1101/2021.07.26.21261082",
@@ -604219,119 +606270,63 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2021.07.27.453843",
-    "rel_title": "Molecular Pathophysiology of Cardiac Injury and Cardiac Microthrombi in Fatal COVID-19: Insights from Clinico-histopathologic and Single Nuclei RNA Sequencing Analyses",
+    "rel_doi": "10.1101/2021.07.27.453973",
+    "rel_title": "Executable Network of SARS-CoV-2-Host Interaction Predicts Drug Combination Treatments",
     "rel_date": "2021-07-27",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.27.453843",
-    "rel_abs": "Cardiac injury is associated with critical COVID-19, yet its etiology remains debated. To elucidate the pathogenic mechanisms of COVID-19-associated cardiac injury, we conducted a single-center prospective cohort study of 69 COVID-19 decedents. Of six cardiac histopathologic features, microthrombi was the most commonly detected (n=48, 70%). We tested associations of cardiac microthrombi with biomarkers of inflammation, cardiac injury, and fibrinolysis and with in-hospital antiplatelet therapy, therapeutic anticoagulation, and corticosteroid treatment, while adjusting for multiple clinical factors, including COVID-19 therapies. Higher peak ESR and CRP during hospitalization were independently associated with higher odds of microthrombi. Using single nuclei RNA-sequence analysis, we discovered an enrichment of pro-thrombotic/anti-fibrinolytic, extracellular matrix remodeling, and immune-potentiating signaling amongst cardiac fibroblasts in microthrombi-positive COVID-19 hearts relative to microthrombi-negative COVID-19. Non-COVID-19 non-failing hearts were used as reference controls. Our cumulative findings identify the specific transcriptomic changes in cardiac fibroblasts as salient features of COVID-19-associated cardiac microthrombi.",
-    "rel_num_authors": 25,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.27.453973",
+    "rel_abs": "The COVID-19 pandemic has pushed healthcare systems globally to a breaking point. The urgent need for effective and affordable COVID-19 treatments calls for repurposing combinations of approved drugs. The challenge is to identify which combinations are likely to be most effective and at what stages of the disease. Here, we present the first disease-stage executable signalling network model of SARS-CoV-2-host interactions used to predict effective repurposed drug combinations for treating early- and late-stage severe disease. Using our executable model, we performed in silico screening of 9870 pairs of 140 potential targets and have identified 12 new drug combinations. Camostat and Apilimod were predicted to be the most promising combination in effectively supressing viral replication in the early stages of severe disease and were validated experimentally in human Caco-2 cells. Our study further demonstrates the power of executable mechanistic modelling to enable rapid pre-clinical evaluation of combination therapies tailored to disease progression. It also presents a novel resource and expandable model system that can respond to further needs in the pandemic.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Nobuaki Fukuma",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Michelle L Hulke",
-        "author_inst": "Masonic Medical Research Institute"
-      },
-      {
-        "author_name": "Michael I Brener",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Stephanie Golob",
-        "author_inst": "Department of Medicine, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Robert Zilinyi",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Zhipeng Zhou",
-        "author_inst": "Cardiovascular Research Foundation"
-      },
-      {
-        "author_name": "Christos Tzimas",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Ilaria Russo",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Claire McGroder",
-        "author_inst": "Division of Pulmonary, Allergy & Critical Care Medicine, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Ryan Pfeiffer",
-        "author_inst": "Masonic Medical Research Institute"
-      },
-      {
-        "author_name": "Alexander Chong",
-        "author_inst": "Division of Infectious Diseases, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Geping Zhang",
-        "author_inst": "Department of Pathology, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Daniel Burkhoff",
-        "author_inst": "Cardiovascular Research Foundation"
-      },
-      {
-        "author_name": "Martin B Leon",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Mathew Maurer",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Rowan Howell",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Jeffrey W Moses",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Matthew A Clarke",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Anne-Catrin Uhlemann",
-        "author_inst": "Division of Infectious Diseases, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Ann-Kathrin Reuschl",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Hanina Hibshoosh",
-        "author_inst": "Department of Pathology, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Tianyi Chen",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Nil Uriel",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Sean Abott-Imboden",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Matthias J Szabolcs",
-        "author_inst": "Department of Pathology, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Mervyn Singer",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Bj\u00f6rn Redfors",
-        "author_inst": "Cardiovascular Research Foundation"
+        "author_name": "David M Lowe",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Charles C Marboe",
-        "author_inst": "Department of Pathology, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Clare L Bennett",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Matthew R Baldwin",
-        "author_inst": "Division of Pulmonary, Allergy & Critical Care Medicine, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Benjamin Chain",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Nathan R Tucker",
-        "author_inst": "Masonic Medical Research Institute"
+        "author_name": "Clare Jolly",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Emily J Tsai",
-        "author_inst": "Division of Cardiology, New York Presbyterian - Columbia University Irving Medical Center"
+        "author_name": "Jasmin Fisher",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "pathology"
+    "category": "systems biology"
   },
   {
     "rel_doi": "10.1101/2021.07.24.21261074",
@@ -606289,27 +608284,35 @@
     "category": "gastroenterology"
   },
   {
-    "rel_doi": "10.1101/2021.07.22.21260878",
-    "rel_title": "Mental Health of HBCU College Students during the COVID-19 Pandemic",
+    "rel_doi": "10.1101/2021.07.22.21260793",
+    "rel_title": "A spatio-temporal study of state-wide case-fatality risks during the first wave of the COVID-19 pandemic in Mexico",
     "rel_date": "2021-07-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21260878",
-    "rel_abs": "ObjectiveThis study investigated rates and predictors of mental health issues (e.g., depression and anxiety) in a sample of college students currently attending a historically Black college/university (HBCU) during the COVID-19 pandemic.\n\nParticipants/Methods98 undergraduate students (81 female and 17 male) completed an online survey containing questions about demographics, socioeconomic status, academic characteristics, and pandemic-related concerns. The survey also included PHQ-9 and GAD-7 questionnaires to evaluate depression and anxiety, respectively.\n\nResults49% of students met the clinical cutoff for depression, 39% for anxiety, and 52% for depression and/or anxiety. Significant predictors of meeting the cutoffs included parental job loss/hour reduction, being a senior, and feeling that the pandemic negatively impacted daily life, among other factors. Demographic variables (age, gender, etc.) had no effect.\n\nConclusionHBCU students show high rates of depression and anxiety during the COVID-19 pandemic, which may be predicted based on the students academic, socioeconomic, and pandemic-related concerns.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21260793",
+    "rel_abs": "We study case-fatality risks (risks of dying in sick individuals) corresponding to the first wave of the COVID-19 pandemic in Mexico. Spatio-temporal analysis by state were performed, mainly from April to September 2020, including descriptive analyses through mapping and time series representations, and the fit of linear mixed models and time series clustering to analyze trends by state. The association of comorbidities and other variables with the risks were studied by fitting a spatial panel data linear model (splm). As results, we observed that on average the greatest risks were reached by July, and that highest risks were observed in some states, Baja California Norte, Chiapas, and Sonora; interestingly, some densely populated states, as Mexico City, had lower values. Different trends by state were observed, and a four-order polynomial, including fixed and random effects, was necessary to model them. The most general structure is one in which the risks increase and then decrease and was observed in states belonging to two clusters; however, there is a cluster corresponding to states with a retarded increase, and another in which increasing risks through time were observed. A cyclic behavior in terms of states having a second increasing trend was observed. Finally, according to the splm, percentage of men, being in the group of 50 years and over, chronic kidney disease failure, cardiovascular disease, asthma, and hypertension were positively associated with the case-fatality risks. This analysis may provide valuable insight into COVID-19 dynamics in future outbreaks, as well as the determinants of these trends at a state level; and, by combining spatial and temporal information, provide a better understanding of COVID-19 case-fatality.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Sharron Xuanren Wang",
-        "author_inst": "Delaware State University"
+        "author_name": "Ricardo Ram\u00edrez-Aldana",
+        "author_inst": "Instituto Nacional de Geriatria"
       },
       {
-        "author_name": "Jarid Goodman",
-        "author_inst": "Delaware State University"
+        "author_name": "Lizbeth Naranjo",
+        "author_inst": "Departamento de Matem\u00e1ticas, Facultad de Ciencias, Universidad Nacional Aut\u00f3noma de M\u00e9xico"
+      },
+      {
+        "author_name": "Juan Carlos Gomez-Verjan",
+        "author_inst": "Instituto Nacional de Geriatr\u00eda"
+      },
+      {
+        "author_name": "Omar Yaxmehen Bello-Chavolla",
+        "author_inst": "Instituto Nacional de Geriatria"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.07.23.21260991",
@@ -608263,39 +610266,1355 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.07.19.21260721",
-    "rel_title": "Present knowledge, attitude, practice, and fear level of Bangladeshi people towards covid-19 after one year of the pandemic situation: a web-based cross-sectional study.",
+    "rel_doi": "10.1101/2021.07.21.21260624",
+    "rel_title": "New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations",
     "rel_date": "2021-07-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260721",
-    "rel_abs": "In the earlier phase of the pandemic situation, the governments of Bangladesh badly suffered to adhere their people to preventive measures probably due to less knowledge and attitude towards covid-19. To tackle the second wave of coronavirus, the governments again enforced an array of preventive measures, but still encountering the same problem after a year of the pandemic situation. In an attempt to find out the reasons behind this, our study aimed to assess the present knowledge, attitude, practice, and fear level of the people. A cross-sectional study was conducted from 15th to 25th April 2021. A total of 402 participants met all the inclusion criteria and were considered for performing all statistical analyses (Descriptive statistics, Mann-Whitney U test, Kruskal-Wallis H test, Multiple logistic regression, Spearman rank-order correlation). Out of 402 participants, more than 90% participants were students and all were adults aged 16 to 30. 84.6%, 65.7%, 54%, and 21.6% participants had more adequate knowledge, more positive attitude, more frequent practice, and moderate to high fear towards covid-19, respectively. Knowledge, attitude, practice, and fear were interrelated directly or indirectly. It was found knowledgeable participants were more likely to have more positive attitude (OR = 2.12, 95% CI = 1.14-3.95, P < 0.05) and very less fear (OR = 1.98, 95% CI = 1.02-3.82, P < 0.05). More positive attitude was found as a good predictor of more frequent practice (OR = 4.33, 95% CI = 2.66-7.04, P < 0.001), and very less fear had same negative impact on both attitude (OR = 0.48, 95% CI = 0.25-0.91, P < 0.05) and practice (OR = 0.48, 95% CI = 0.27-0.85, P < 0.05). Our findings reflect that knowledge level has elevated but attitude level subsided, and practice level stayed same as was in the earlier phase of pandemic and people are no longer panicked.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.21.21260624",
+    "rel_abs": "Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic [~]0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.",
+    "rel_num_authors": 334,
     "rel_authors": [
       {
-        "author_name": "Tahsin Ahmed Rupok",
-        "author_inst": "Department of Pharmacy, University of Rajshahi, Rajshahi-6205, Bangladesh."
+        "author_name": "Frauke Degenhardt",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "David Ellinghaus",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Simonas Juzenas",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Jon Lerga-Jaso",
+        "author_inst": "Institut de Biotecnologia i de Biomedicina, Universitat Autonoma de Barcelona, Bellaterra (Barcelona), Spain"
+      },
+      {
+        "author_name": "Mareike Wendorff",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Douglas Maya-Miles",
+        "author_inst": "Hospital Universitario Virgen del Rocio de Sevilla, Sevilla, Spain"
+      },
+      {
+        "author_name": "Florian Uellendahl-Werth",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Hesham ElAbd",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Malte Christoph Ruehlemann",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Jatin Arora",
+        "author_inst": "Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Onur Oezer",
+        "author_inst": "Research Group for Evolutionary Immunogenomics, Max Planck Institute for Evolutionary Biology, Ploen, Germany"
+      },
+      {
+        "author_name": "Ole Bernt Lenning",
+        "author_inst": "Research Department, Stavanger University Hospital"
+      },
+      {
+        "author_name": "Ronny Myhre",
+        "author_inst": "Norwegian Institute of Public Health, Division of Health Data and Digitalization, Department of Genetics and Bioinformatics (HDGB) Oslo, Norway"
+      },
+      {
+        "author_name": "May Sissel Vadla",
+        "author_inst": "Randaberg Municipality, Norway"
+      },
+      {
+        "author_name": "Eike Matthias Wacker",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Lars Wienbrandt",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Aaron Blandino Ortiz",
+        "author_inst": "Department of Intensive Care, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of Alcala, Madrid, S"
+      },
+      {
+        "author_name": "Adolfo de Salazar",
+        "author_inst": "Ibs.Granada Instituto de Investigacion Biosanitaria, Granada, Spain"
+      },
+      {
+        "author_name": "Adolfo Garrido Chercoles",
+        "author_inst": "Osakidetza Basque Health Service, Donostialdea Integrated Health Organisation, Clinical Biochemistry Department, San Sebastian, Spain"
+      },
+      {
+        "author_name": "Adriana Palom",
+        "author_inst": "Vall d'Hebron Institut de Recerca (VHIR), Vall B24Hebron Hospital Universitari, Barcelona, Spain"
+      },
+      {
+        "author_name": "Agustin Ruiz",
+        "author_inst": "Research Center and Memory Clinic. Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Spain"
+      },
+      {
+        "author_name": "Alba-Estela Garcia-Fernandez",
+        "author_inst": "Department of Biochemistry, University Hospital Vall d'Hebron, Barcelona, Spain"
+      },
+      {
+        "author_name": "Albert Blanco-Grau",
+        "author_inst": "Department of Biochemistry, University Hospital Vall d'Hebron, Barcelona, Spain"
+      },
+      {
+        "author_name": "Alberto Mantovani",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Alberto Zanella",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Aleksander Rygh Holten",
+        "author_inst": "Department of Acute Medicine, Oslo University Hospital, Oslo, Norway"
+      },
+      {
+        "author_name": "Alena Mayer",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Alessandra Bandera",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Alessandro Cherubini",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Alessandro Protti",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Alessio Aghemo",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Alessio Gerussi",
+        "author_inst": "European Reference Network on Hepatological Diseases (ERN RARE-LIVER), San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Alfredo Ramirez",
+        "author_inst": "Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University "
+      },
+      {
+        "author_name": "Alice Braun",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Almut Nebel",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Ana Barreira",
+        "author_inst": "Liver Unit, Department of Internal Medicine, Hospital Universitari Vall d'Hebron, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain"
+      },
+      {
+        "author_name": "Ana Lleo",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Ana Teles",
+        "author_inst": "Research Group for Evolutionary Immunogenomics, Max Planck Institute for Evolutionary Biology, Ploen, Germany"
+      },
+      {
+        "author_name": "Anders Kildal",
+        "author_inst": "Department of Anesthesiology and Intensive Care, University Hospital of North Norway, Tromso, Norway"
+      },
+      {
+        "author_name": "Andrea Biondi",
+        "author_inst": "Pediatric Departement and Centro Tettamanti- European Reference Network (ERN) PaedCan, EuroBloodNet, MetabERN-University of Milano-Bicocca-Fondazione MBBM/Osped"
+      },
+      {
+        "author_name": "Andrea Caballero-Garralda",
+        "author_inst": "Biochemistry Department, Echevarne Laboratory, Sant Cugat del Valles, Barcelona, Spain"
+      },
+      {
+        "author_name": "Andrea Ganna",
+        "author_inst": "Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland"
+      },
+      {
+        "author_name": "Andrea Gori",
+        "author_inst": "Centre for Multidisciplinary Research in Health Science (MACH), University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Andreas Glueck",
+        "author_inst": "Klinik fuer Innere Medizin I, Universitaetsklinikum Schleswig-Holstein, Campus Kiel, Germany"
+      },
+      {
+        "author_name": "Andreas Lind",
+        "author_inst": "Department of Microbiology, Oslo University Hospital, Oslo, Norway"
+      },
+      {
+        "author_name": "Anja Tanck",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Anke Hinney",
+        "author_inst": "Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg-Essen, Essen, Germany"
+      },
+      {
+        "author_name": "Anna Carreras Carreras Nolla",
+        "author_inst": "Genomes for Life-GCAT lab. Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Anna Ludovica Fracanzani",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Anna Peschuck",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Annalisa Cavallero",
+        "author_inst": "Laboratory of Microbiology, San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Anne Ma Dyrhol-Riise",
+        "author_inst": "Department of Infectious diseases, Oslo University Hospital, Oslo, Norway"
+      },
+      {
+        "author_name": "Antonella Ruello",
+        "author_inst": "Humanitas Gavazzeni-Castelli, Bergamo, Italy"
+      },
+      {
+        "author_name": "Antonio Julia",
+        "author_inst": "Vall d'Hebron Institut de Recerca (VHIR), Vall d'Hebron Hospital Universitari, Barcelona, Spain"
+      },
+      {
+        "author_name": "Antonio Muscatello",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Antonio Pesenti",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Antonio Voza",
+        "author_inst": "Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy"
+      },
+      {
+        "author_name": "Ariadna Rando-Segura",
+        "author_inst": "Microbiology Department, Hospital Universitari Vall d'Hebron, Barcelona, Spain"
+      },
+      {
+        "author_name": "Aurora Solier",
+        "author_inst": "Department of Respiratory Diseases, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of Alcala, Cen"
+      },
+      {
+        "author_name": "Axel Schmidt",
+        "author_inst": "Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany"
+      },
+      {
+        "author_name": "Beatriz Cortes",
+        "author_inst": "Genomes for Life-GCAT lab. Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Beatriz Mateos",
+        "author_inst": "Department of Gastroenterology, Hospital Universitario Ramon y Cajal, University of Alcala, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid,"
+      },
+      {
+        "author_name": "Beatriz Nafria-Jimenez",
+        "author_inst": "Osakidetza Basque Health Service, Donostialdea Integrated Health Organisation, Clinical Biochemistry Department, San Sebastian, Spain"
+      },
+      {
+        "author_name": "Benedikt Schaefer",
+        "author_inst": "Medical University of Innsbruck, Department of Medicine I, Gastroenterology, Hepatology and Endocrinology, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Bjoern Jensen",
+        "author_inst": "Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Duesseldorf, Medical Faculty Heinrich Heine University, Duesseldorf, Ger"
+      },
+      {
+        "author_name": "Carla Bellinghausen",
+        "author_inst": "Department of Respiratory Medicine and Allergology, University Hospital, Goethe University, Frankfurt am Main, Germany"
+      },
+      {
+        "author_name": "Carlo Maj",
+        "author_inst": "Institute of Genomic Statistics and Bioinformatics, University Hospital Bonn, Medical Faculty University of Bonn, Venusberg-Campus 1, Bonn, Germany"
+      },
+      {
+        "author_name": "Carlos Ferrando",
+        "author_inst": "Centro de Investigacion Biomedica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain"
+      },
+      {
+        "author_name": "Carmen de la Horra",
+        "author_inst": "University of Sevilla, Sevilla, Spain"
+      },
+      {
+        "author_name": "Carmen Quereda",
+        "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of Alcala, Madr"
+      },
+      {
+        "author_name": "Carsten Skurk",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Charlotte Thibeault",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Chiara Scollo",
+        "author_inst": "Department of Transfusion Medicine and Haematology Laboratory, San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Christian Herr",
+        "author_inst": "Department of Internal Medicine V, Pneumology, Allergology and Intensive Care Medicine, University Hospital Saarland, Homburg/Saar, Germany"
+      },
+      {
+        "author_name": "Christoph D Spinner",
+        "author_inst": "Technical University of Munich, School of Medicine, University Hospital rechts der Isar, Department of Internal Medicine II, Munich, Germany"
+      },
+      {
+        "author_name": "Christoph Gassner",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Christoph Lange",
+        "author_inst": "Respiratory Medicine & International Health, University of Luebeck, Luebeck, Germany"
+      },
+      {
+        "author_name": "Cinzia Hu",
+        "author_inst": "Internal Medicine Department,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Cinzia Paccapelo",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Clara Lehmann",
+        "author_inst": "Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany"
+      },
+      {
+        "author_name": "Claudio Angelini",
+        "author_inst": "Humanitas Clinical and Research Center, IRCCS, Milan, Italy"
+      },
+      {
+        "author_name": "Claudio Cappadona",
+        "author_inst": "Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy"
+      },
+      {
+        "author_name": "Clinton Azuure",
+        "author_inst": "Research Group for Evolutionary Immunogenomics, Max Planck Institute for Evolutionary Biology, Ploen, Germany"
+      },
+      {
+        "author_name": "Cristiana Bianco",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Cristina Cea",
+        "author_inst": "Department of Biochemistry, University Hospital Vall d'Hebron, Barcelona, Spain"
+      },
+      {
+        "author_name": "Cristina Sancho",
+        "author_inst": "Osakidetza Basque Health Service, Basurto University Hospital, Respiratory Service, Bilbao, Spain"
+      },
+      {
+        "author_name": "Dag Arne Lihaug Hoff",
+        "author_inst": "Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway"
+      },
+      {
+        "author_name": "Daniela Galimberti",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Daniele Prati",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "David Haschka",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "David Jimenez",
+        "author_inst": "Department of Respiratory Diseases, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of Alcala, Cen"
+      },
+      {
+        "author_name": "David Pestana",
+        "author_inst": "Department of Anesthesiology and Critical Care, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of"
+      },
+      {
+        "author_name": "David Toapanta",
+        "author_inst": "Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Eduardo Muniz-Diaz",
+        "author_inst": "Immunohematology Department, Banc de Sang i Teixits, Autonomous University of Barcelona, Barcelona, Spain"
+      },
+      {
+        "author_name": "Elena Azzolini",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Elena Sandoval",
+        "author_inst": "Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Eleonora Binatti",
+        "author_inst": "European Reference Network on Hepatological Diseases (ERN RARE-LIVER), San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Elio Scarpini",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Elisa T Helbig",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Elisabetta Casalone",
+        "author_inst": "Department of Medical Sciences, Universita degli Studi di Torino, Turin, Italy"
+      },
+      {
+        "author_name": "Eloisa Urrechaga",
+        "author_inst": "Osakidetza Basque Health Service, Galdakao Hospital, Respiratory Service, Galdakao, Spain"
+      },
+      {
+        "author_name": "Elvezia Maria Paraboschi",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Emanuele Pontali",
+        "author_inst": "Department of Infectious Diseases, E.O. Ospedali Galliera, Genova, Italy"
+      },
+      {
+        "author_name": "Enric Reverter",
+        "author_inst": "Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Enrique J Calderon",
+        "author_inst": "University of Sevilla, Sevilla, Spain"
+      },
+      {
+        "author_name": "Enrique Navas",
+        "author_inst": "Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of Alcala, Madr"
+      },
+      {
+        "author_name": "Erik Solligard",
+        "author_inst": "Geminicenter for Sepsis Research, Institute of Circulation and Medical Imaging (ISB), NTNU, Trondheim, Norway"
+      },
+      {
+        "author_name": "Ernesto Contro",
+        "author_inst": "Accident & Emergency and Emergency Medicine Unit, San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Eunate Arana-Arri",
+        "author_inst": "Biocruces Bizkaia Health Research Institute, Barakaldo, Spain"
+      },
+      {
+        "author_name": "Fatima Aziz",
+        "author_inst": "Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Federico Garcia",
+        "author_inst": "Microbiology Unit. Hospital Universitario Clinico San Cecilio, Granada, Spain"
+      },
+      {
+        "author_name": "Felix Garcia Sanchez",
+        "author_inst": "Histocompatibilidad y Biologia Molecular, Centro de Transfusion de Madrid, Madrid, Spain"
+      },
+      {
+        "author_name": "Ferruccio Ceriotti",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Filippo Martinelli-Boneschi",
+        "author_inst": "Dino Ferrari Center, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Flora Peyvandi",
+        "author_inst": "University of Milan, Department of Pathophysiology and Transplantation, Milan, Italy"
+      },
+      {
+        "author_name": "Florian Kurth",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Francesco Blasi",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Respiratory Unit, Milan, Italy"
+      },
+      {
+        "author_name": "Francesco Malvestiti",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Francisco J Medrano",
+        "author_inst": "Instituto de Biomedicina de Sevilla (IBIS), Sevilla, Spain"
+      },
+      {
+        "author_name": "Francisco Mesonero",
+        "author_inst": "Department of Gastroenterology, Hospital Universitario Ramon y Cajal, University of Alcala, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid,"
+      },
+      {
+        "author_name": "Francisco Rodriguez-Frias",
+        "author_inst": "Vall d'Hebron Institut de Recerca (VHIR), Vall d'Hebron Hospital Universitari, Barcelona, Spain"
+      },
+      {
+        "author_name": "Frank Hanses",
+        "author_inst": "Emergency Department, University Hospital Regensburg, Regensburg, Germany"
+      },
+      {
+        "author_name": "Fredrik Mueller",
+        "author_inst": "Institute of Clinical Medicine, University of Oslo, Oslo, Norway"
+      },
+      {
+        "author_name": "Georg Hemmrich-Stanisak",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Giacomo Bellani",
+        "author_inst": "Department Emergency, Anesthesia and Intensive Care, San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Giacomo Grasselli",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Gianni Pezzoli",
+        "author_inst": "Fondazione Grigioni per il Morbo di Parkinson and Parkinson Institute, ASST Gaetano Pini-CTO, Milan, Italy"
+      },
+      {
+        "author_name": "Giorgio Costantino",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Giovanni Albano",
+        "author_inst": "Humanitas Gavazzeni-Castelli, Bergamo, Italy"
+      },
+      {
+        "author_name": "Giulia Cardamone",
+        "author_inst": "Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy"
+      },
+      {
+        "author_name": "Giuseppe Bellelli",
+        "author_inst": "School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy"
+      },
+      {
+        "author_name": "Giuseppe Citerio",
+        "author_inst": "School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy"
+      },
+      {
+        "author_name": "Giuseppe Foti",
+        "author_inst": "Department Emergency, Anesthesia and Intensive Care, San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Giuseppe Lamorte",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Giuseppe Matullo",
+        "author_inst": "Department of Medical Sciences, Universita degli Studi di Torino, Turin, Italy"
+      },
+      {
+        "author_name": "Guido Baselli",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Hayato Kurihara",
+        "author_inst": "Humanitas Clinical and Research Center, IRCCS, Milan, Italy"
+      },
+      {
+        "author_name": "Holger Neb",
+        "author_inst": "Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Frankfurt am Main, Germany"
+      },
+      {
+        "author_name": "Ilaria My",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Ingo Kurth",
+        "author_inst": "Institute of Human Genetics, Medical Faculty, RWTH Aachen University, Aachen, Germany"
+      },
+      {
+        "author_name": "Isabel Hernandez",
+        "author_inst": "Research Center and Memory Clinic. Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Spain"
+      },
+      {
+        "author_name": "Isabell Pink",
+        "author_inst": "Department of Pneumology, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Itziar de Rojas",
+        "author_inst": "Research Center and Memory Clinic. Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Spain"
+      },
+      {
+        "author_name": "Ivan Galvan-Femenia",
+        "author_inst": "Genomes for Life-GCAT lab. Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Jan Cato Holter",
+        "author_inst": "Institute of Clinical Medicine, University of Oslo, Oslo, Norway"
+      },
+      {
+        "author_name": "Jan Egil Afset",
+        "author_inst": "Department of Medical Microbiology, Clinic of Laboratory Medicine, St. Olavs hospital, Trondheim, Norway"
+      },
+      {
+        "author_name": "Jan Heyckendorf",
+        "author_inst": "Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany"
+      },
+      {
+        "author_name": "Jan Kaessens",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Jan Kristian Damas",
+        "author_inst": "Department of Infectious Diseases, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway"
+      },
+      {
+        "author_name": "Jan Rybniker",
+        "author_inst": "Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany"
+      },
+      {
+        "author_name": "Janine Altmueller",
+        "author_inst": "Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany"
+      },
+      {
+        "author_name": "Javier Ampuero",
+        "author_inst": "University of Sevilla, Sevilla, Spain"
+      },
+      {
+        "author_name": "Javier Martin",
+        "author_inst": "Institute of Parasitology and Biomedicine Lopez-Neyra, CSIC, Granada, Spain"
+      },
+      {
+        "author_name": "Jeanette Erdmann",
+        "author_inst": "Institute for Cardiogenetics, University of Luebeck, Luebeck, Germany"
+      },
+      {
+        "author_name": "Jesus M Banales",
+        "author_inst": "Department of Liver and Gastrointestinal Diseases, Biodonostia Health Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EH"
+      },
+      {
+        "author_name": "Joan Ramon Badia",
+        "author_inst": "Respiratory ICU, Institut Clinic Respiratory, Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Joaquin Dopazo",
+        "author_inst": "Bioinformatics Area, Fundacion Progreso y Salud, and Institute of Biomedicine of Sevilla (IBIS), Sevilla, Spain"
+      },
+      {
+        "author_name": "Jochen Schneider",
+        "author_inst": "Technical University of Munich, School of Medicine, University Hospital rechts der Isar, Department of Internal Medicine II, Munich, Germany"
+      },
+      {
+        "author_name": "Jonas Bergan",
+        "author_inst": "Department of Research, Ostfold Hospital Trust, Gralum, Norway"
+      },
+      {
+        "author_name": "Jordi Barretina",
+        "author_inst": "Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Joern Walter",
+        "author_inst": "Department of Genetics & Epigenetics, Saarland University, Saarbruecken, Germany"
+      },
+      {
+        "author_name": "Jose Hernandez Quero",
+        "author_inst": "Ibs.Granada Instituto de Investigacion Biosanitaria, Granada, Spain"
+      },
+      {
+        "author_name": "Josune Goikoetxea",
+        "author_inst": "Infectious Diseases Service, Osakidetza, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain"
+      },
+      {
+        "author_name": "Juan Delgado",
+        "author_inst": "University of Sevilla, Sevilla, Spain"
+      },
+      {
+        "author_name": "Juan M Guerrero",
+        "author_inst": "University of Sevilla, Sevilla, Spain"
+      },
+      {
+        "author_name": "Julia Fazaal",
+        "author_inst": "Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany"
+      },
+      {
+        "author_name": "Julia Kraft",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Julia Schroeder",
+        "author_inst": "Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany"
+      },
+      {
+        "author_name": "Kari Risnes",
+        "author_inst": "Department of Research, St Olav Hospital, Trondheim University Hospital, Trondheim, Norway"
+      },
+      {
+        "author_name": "Karina Banasik",
+        "author_inst": "Novo Nordisk Foundation Center for Protein Research, Disease Systems Biology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denm"
+      },
+      {
+        "author_name": "Karl Erik Mueller",
+        "author_inst": "Medical Department, Drammen Hospital, Vestre Viken Hospital Trust, Norway"
+      },
+      {
+        "author_name": "Karoline I Gaede",
+        "author_inst": "Research Center Borstel, BioMaterialBank Nord, Germany"
+      },
+      {
+        "author_name": "Koldo Garcia-Etxebarria",
+        "author_inst": "Department of Liver and Gastrointestinal Diseases, Biodonostia Health Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EH"
+      },
+      {
+        "author_name": "Kristian Tonby",
+        "author_inst": "Department of Infectious diseases, Oslo University Hospital, Oslo, Norway"
+      },
+      {
+        "author_name": "Lars Heggelund",
+        "author_inst": "Department of Clinical Science, University of Bergen, Bergen, Norway"
+      },
+      {
+        "author_name": "Laura Izquierdo-Sanchez",
+        "author_inst": "Biodonostia Health Research Institute, Donostia University Hospital, San Sebastian, Spain"
+      },
+      {
+        "author_name": "Laura Rachele Bettini",
+        "author_inst": "Pediatric Departement and Centro Tettamanti- European Reference Network (ERN) PaedCan, EuroBloodNet, MetabERN-University of Milano-Bicocca-Fondazione MBBM/Osped"
+      },
+      {
+        "author_name": "Lauro Sumoy",
+        "author_inst": "Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Leif Erik Sander",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Lena J Lippert",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Leonardo Terranova",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Lindokuhle Nkambule",
+        "author_inst": "Analytic & Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA"
+      },
+      {
+        "author_name": "Lisa Knopp",
+        "author_inst": "Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Duesseldorf, Medical Faculty Heinrich Heine University, Duesseldorf, Ger"
+      },
+      {
+        "author_name": "Lise Tuset Gustad",
+        "author_inst": "Clinic of Medicine and Rehabilitation, Levanger Hospital, Nord-Trondelag Hospital Trust, Levanger, Norway"
+      },
+      {
+        "author_name": "Lucia Garbarino",
+        "author_inst": "HLA Laboratory, E.O. Ospedali Galliera, Genova, Italy"
+      },
+      {
+        "author_name": "Luigi Santoro",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Luis Tellez",
+        "author_inst": "Department of Gastroenterology, Hospital Universitario Ramon y Cajal, University of Alcala, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid,"
+      },
+      {
+        "author_name": "Luisa Roade",
+        "author_inst": "Universitat Autonoma de Barcelona, Bellatera, Spain"
+      },
+      {
+        "author_name": "Mahnoosh Ostadreza",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Maider Intxausti",
+        "author_inst": "Osakidetza Basque Health Service, Basurto University Hospital, Respiratory Service, Bilbao, Spain"
+      },
+      {
+        "author_name": "Manolis Kogevinas",
+        "author_inst": "ISGlobal, Barcelona, Spain"
+      },
+      {
+        "author_name": "Mar Riveiro-Barciela",
+        "author_inst": "Universitat Autonoma de Barcelona, Bellatera, Spain"
+      },
+      {
+        "author_name": "Marco Schaefer",
+        "author_inst": "Stefan-Morsch-Stiftung, Birkenfeld, Germany"
+      },
+      {
+        "author_name": "Mari EK Niemi",
+        "author_inst": "Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland"
+      },
+      {
+        "author_name": "Maria A Gutierrez-Stampa",
+        "author_inst": "Osakidetza, OSI Donostialdea, Altza Primary Care, Biodonostia Health Research Institute, San Sebastian, Spain"
+      },
+      {
+        "author_name": "Maria Carrabba",
+        "author_inst": "Internal Medicine Department,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Maria E Figuera Basso",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Maria Grazia Valsecchi",
+        "author_inst": "Center of Bioinformatics, Biostatistics and Bioimaging, School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy"
+      },
+      {
+        "author_name": "Maria Hernandez-Tejero",
+        "author_inst": "Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Maria JGT Vehreschild",
+        "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt & Goethe University Frankfurt, Frankfurt am Main, Germany"
+      },
+      {
+        "author_name": "Maria Manunta",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Marialbert Acosta-Herrera",
+        "author_inst": "Institute of Parasitology and Biomedicine Lopez-Neyra, CSIC, Granada, Spain"
+      },
+      {
+        "author_name": "Mariella D'Angio",
+        "author_inst": "Pediatric Departement and Centro Tettamanti- European Reference Network (ERN) PaedCan, EuroBloodNet, MetabERN-University of Milano-Bicocca-Fondazione MBBM/Osped"
+      },
+      {
+        "author_name": "Marina Baldini",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Marina Cazzaniga",
+        "author_inst": "Phase 1 Research Centre, ASST Monza, School of Medicine and Surgery, University of Milano-Bicocca, Italy"
+      },
+      {
+        "author_name": "Marit M Grimsrud",
+        "author_inst": "Research Institute for Internal Medicine, Division of Surgery, Inflammatory Diseases and Transplantation, Oslo University Hospital Rikshospitalet and University"
+      },
+      {
+        "author_name": "Markus Cornberg",
+        "author_inst": "Department of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Markus M Noethen",
+        "author_inst": "Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany"
+      },
+      {
+        "author_name": "Marta Marquie",
+        "author_inst": "Research Center and Memory Clinic. Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Spain"
+      },
+      {
+        "author_name": "Massimo Castoldi",
+        "author_inst": "Humanitas Gavazzeni-Castelli, Bergamo, Italy"
+      },
+      {
+        "author_name": "Mattia Cordioli",
+        "author_inst": "Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland"
+      },
+      {
+        "author_name": "Maurizio Cecconi",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Mauro D'Amato",
+        "author_inst": "Gastrointestinal Genetics Lab, CIC bioGUNE, BRTA, Derio, Spain"
+      },
+      {
+        "author_name": "Max Augustin",
+        "author_inst": "German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany"
+      },
+      {
+        "author_name": "Melissa Tomasi",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Merce Boada",
+        "author_inst": "Research Center and Memory Clinic. Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Spain"
+      },
+      {
+        "author_name": "Michael Dreher",
+        "author_inst": "Department of Pneumology and Intensive Care Medicine, University Hospital Aachen, Germany"
+      },
+      {
+        "author_name": "Michael J Seilmaier",
+        "author_inst": "Munich Clinic Schwabing, Academic Teaching Hospital, Ludwig-Maximilians-University (LMU), Munich, Germany"
+      },
+      {
+        "author_name": "Michael Joannidis",
+        "author_inst": "Division of Intensive Care and Emergency Medicine, Department of Internal Medicine, Medical University Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Michael Wittig",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Michela Mazzocco",
+        "author_inst": "HLA Laboratory, E.O. Ospedali Galliera, Genova, Italy"
+      },
+      {
+        "author_name": "Michele Ciccarelli",
+        "author_inst": "Humanitas Clinical and Research Center, IRCCS, Milan, Italy"
+      },
+      {
+        "author_name": "Miguel Rodriguez-Gandia",
+        "author_inst": "Department of Gastroenterology, Hospital Universitario Ramon y Cajal, University of Alcala, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid,"
+      },
+      {
+        "author_name": "Monica Bocciolone",
+        "author_inst": "Humanitas Clinical and Research Center, IRCCS, Milan, Italy"
+      },
+      {
+        "author_name": "Monica Miozzo",
+        "author_inst": "Internal Medicine Department,Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Natale Imaz-Ayo",
+        "author_inst": "Biocruces Bizkaia Health Research Institute, Barakaldo, Spain"
+      },
+      {
+        "author_name": "Natalia Blay",
+        "author_inst": "Genomes for Life-GCAT lab. Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Natalia Chueca",
+        "author_inst": "Microbiology Unit. Hospital Universitario Clinico San Cecilio, Granada, Spain"
+      },
+      {
+        "author_name": "Nicola Montano",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Nicole Braun",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Nicole Ludwig",
+        "author_inst": "Center of Human and Molecular Biology, Department of Human Genetics, University Hospital Saarland, Homburg/Saar, Germany"
+      },
+      {
+        "author_name": "Nikolaus Marx",
+        "author_inst": "Department of Internal Medicine I, RWTH Aachen University Hospital, Aachen, Germany"
+      },
+      {
+        "author_name": "Nilda Martinez",
+        "author_inst": "Department of Anesthesiology, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid, Spain"
+      },
+      {
+        "author_name": "Oliver A Cornely",
+        "author_inst": "Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany"
+      },
+      {
+        "author_name": "Oliver Witzke",
+        "author_inst": "Department of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Essen, Germany"
+      },
+      {
+        "author_name": "Orazio Palmieri",
+        "author_inst": "Gastroenterology Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy"
+      },
+      {
+        "author_name": "Paola Faverio",
+        "author_inst": "Pulmonary Unit, San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Paoletta Preatoni",
+        "author_inst": "Humanitas Clinical and Research Center, IRCCS, Milan, Italy"
+      },
+      {
+        "author_name": "Paolo Bonfanti",
+        "author_inst": "School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy"
+      },
+      {
+        "author_name": "Paolo Omodei",
+        "author_inst": "Humanitas Clinical and Research Center, IRCCS, Milan, Italy"
+      },
+      {
+        "author_name": "Paolo Tentorio",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Pedro Castro",
+        "author_inst": "Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Pedro M Rodrigues",
+        "author_inst": "Department of Liver and Gastrointestinal Diseases, Biodonostia Health Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EH"
+      },
+      {
+        "author_name": "Pedro Pablo Espana",
+        "author_inst": "Osakidetza Basque Health Service, Galdakao Hospital, Respiratory Service, Galdakao, Spain"
+      },
+      {
+        "author_name": "Per Hoffmann",
+        "author_inst": "Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany"
+      },
+      {
+        "author_name": "Philip Rosenstiel",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Philipp Schommers",
+        "author_inst": "Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany"
+      },
+      {
+        "author_name": "Phillip Suwalski",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Raul de Pablo",
+        "author_inst": "Department of Intensive Care, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of Alcala, Madrid, S"
+      },
+      {
+        "author_name": "Ricard Ferrer",
+        "author_inst": "Intensive Care Department, Vall d'Hebron University Hospital, SODIR-VHIR research group, Barcelona, Spain"
+      },
+      {
+        "author_name": "Robert Bals",
+        "author_inst": "Department of Internal Medicine V, Pneumology, Allergology and Intensive Care Medicine, University Hospital Saarland, Homburg/Saar, Germany"
+      },
+      {
+        "author_name": "Roberta Gualtierotti",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Rocio Gallego-Duran",
+        "author_inst": "Instituto de Biomedicina de Sevilla (IBIS), Sevilla, Spain"
+      },
+      {
+        "author_name": "Rosa Nieto",
+        "author_inst": "Department of Respiratory Diseases, Hospital Universitario Ramon y Cajal, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), University of Alcala, Cen"
+      },
+      {
+        "author_name": "Rossana Carpani",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Ruben Morilla",
+        "author_inst": "Consejo Superior de Investigaciones cientificas, Sevilla, Spain"
+      },
+      {
+        "author_name": "Salvatore Badalamenti",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Sammra Haider",
+        "author_inst": "Department of Medicine, More & Romsdal Hospital Trust, Molde, Norway"
+      },
+      {
+        "author_name": "Sandra Ciesek",
+        "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany"
+      },
+      {
+        "author_name": "Sandra May",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Sara Bombace",
+        "author_inst": "Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy"
+      },
+      {
+        "author_name": "Sara Marsal",
+        "author_inst": "Vall d'Hebron Institut de Recerca (VHIR), Vall d'Hebron Hospital Universitari, Barcelona, Spain"
+      },
+      {
+        "author_name": "Sara Pigazzini",
+        "author_inst": "Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland"
+      },
+      {
+        "author_name": "Sebastian Klein",
+        "author_inst": "Division of Intensive Care and Emergency Medicine, Department of Internal Medicine, Medical University Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Serena Pelusi",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Sibylle Wilfling",
+        "author_inst": "Zentrum fuer Humangenetik Regensburg, Regensburg, Germany"
+      },
+      {
+        "author_name": "Silvano Bosari",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Sonja Volland",
+        "author_inst": "Hannover Unified Biobank, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Soren Brunak",
+        "author_inst": "Novo Nordisk Foundation Center for Protein Research, Disease Systems Biology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denm"
+      },
+      {
+        "author_name": "Soumya Raychaudhuri",
+        "author_inst": "Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Stefan Schreiber",
+        "author_inst": "Klinik fuer Innere Medizin I, Universitaetsklinikum Schleswig-Holstein, Campus Kiel, Germany"
+      },
+      {
+        "author_name": "Stefanie Heilmann-Heimbach",
+        "author_inst": "Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany"
+      },
+      {
+        "author_name": "Stefano Aliberti",
+        "author_inst": "Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy"
+      },
+      {
+        "author_name": "Stephan Ripke",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Susanne Dudman",
+        "author_inst": "Institute of Clinical Medicine, University of Oslo, Oslo, Norway"
+      },
+      {
+        "author_name": "Tanja Wesse",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Tenghao Zheng",
+        "author_inst": "School of Biological Sciences, Monash University, Clayton, VIC, Australia"
+      },
+      {
+        "author_name": "Thomas Bahmer",
+        "author_inst": "Klinik fuer Innere Medizin I, Universitaetsklinikum Schleswig-Holstein, Campus Kiel, Germany"
+      },
+      {
+        "author_name": "Thomas Eggermann",
+        "author_inst": "Institute of Human Genetics, Medical Faculty, RWTH Aachen University, Aachen, Germany"
+      },
+      {
+        "author_name": "Thomas Illig",
+        "author_inst": "Hannover Unified Biobank, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Thorsten Brenner",
+        "author_inst": "Department of Anesthesiology and Intensive Care Medicine, University Hospital Essen, University Duisburg-Essen, Essen, Germany"
+      },
+      {
+        "author_name": "Tomas Pumarola",
+        "author_inst": "Department of Microbiology, University Hospital Vall d'Hebron, Barcelona, Spain"
+      },
+      {
+        "author_name": "Torsten Feldt",
+        "author_inst": "Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Duesseldorf, Medical Faculty Heinrich Heine University, Duesseldorf, Ger"
+      },
+      {
+        "author_name": "Trine Folseraas",
+        "author_inst": "Norwegian PSC Research Center, Department of Transplantation Medicine, Division of Surgery, Inflammatory Diseases and Transplantation, Oslo University Hospital "
+      },
+      {
+        "author_name": "Trinidad Gonzalez Cejudo",
+        "author_inst": "Biochemistry Unit. Hospital Universitario Clinico San Cecilio, Granada, Spain"
+      },
+      {
+        "author_name": "Ulf Landmesser",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin Institute of Health, Berlin Germany"
+      },
+      {
+        "author_name": "Ulrike Protzer",
+        "author_inst": "Institute of Virology, Technical University Munich/Helmholtz Zentrum Muenchen, Munich, Germany"
+      },
+      {
+        "author_name": "Ute Hehr",
+        "author_inst": "Zentrum fuer Humangenetik Regensburg, Regensburg, Germany"
+      },
+      {
+        "author_name": "Valeria Rimoldi",
+        "author_inst": "Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy"
+      },
+      {
+        "author_name": "Valter Monzani",
+        "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy"
+      },
+      {
+        "author_name": "Vegard Skogen",
+        "author_inst": "Department of Infectious Diseases, University Hospital of North Norway, Tromso, Norway"
+      },
+      {
+        "author_name": "Verena Keitel",
+        "author_inst": "Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Duesseldorf, Medical Faculty Heinrich Heine University, Duesseldorf, Ger"
+      },
+      {
+        "author_name": "Verena Kopfnagel",
+        "author_inst": "Hannover Unified Biobank, Hannover Medical School, Hannover, Germany"
+      },
+      {
+        "author_name": "Vicente Friaza",
+        "author_inst": "Consejo Superior de Investigaciones cientificas, Sevilla, Spain"
+      },
+      {
+        "author_name": "Victor Andrade",
+        "author_inst": "Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University "
+      },
+      {
+        "author_name": "Victor Moreno",
+        "author_inst": "Catalan Institute of Oncology (ICO), Barcelona, Spain"
+      },
+      {
+        "author_name": "Wolfgang Albrecht",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Wolfgang Peter",
+        "author_inst": "Stefan-Morsch-Stiftung, Birkenfeld, Germany"
+      },
+      {
+        "author_name": "Wolfgang Poller",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Xavier Farre",
+        "author_inst": "Genomes for Life-GCAT lab. Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Xiaoli Yi",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Xiaomin Wang",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Yascha Khodamoradi",
+        "author_inst": "Department of Internal Medicine, Infectious Diseases, University Hospital Frankfurt & Goethe University Frankfurt, Frankfurt am Main, Germany"
+      },
+      {
+        "author_name": "Zehra Karadeniz",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Anna Latiano",
+        "author_inst": "Gastroenterology Unit, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy"
+      },
+      {
+        "author_name": "Siegfried Goerg",
+        "author_inst": "Institute of Transfusionsmedicine, University Hospital Schleswig-Holstein (UKSH), Germany"
+      },
+      {
+        "author_name": "Petra Bacher",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Philipp Koehler",
+        "author_inst": "Department I of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany"
+      },
+      {
+        "author_name": "Florian Tran",
+        "author_inst": "Institute of Clinical Molecular Biology, Christian-Albrechts-University, Kiel, Germany"
+      },
+      {
+        "author_name": "Heinz Zoller",
+        "author_inst": "Medical University of Innsbruck, Department of Medicine I, Gastroenterology, Hepatology and Endocrinology, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Eva C Schulte",
+        "author_inst": "Institute of Virology, Technical University Munich/Helmholtz Zentrum Muenchen, Munich, Germany"
+      },
+      {
+        "author_name": "Bettina Heidecker",
+        "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany"
+      },
+      {
+        "author_name": "Kerstin U Ludwig",
+        "author_inst": "Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany"
+      },
+      {
+        "author_name": "Javier Fernandez",
+        "author_inst": "Hospital Clinic, University of Barcelona, and IDIBAPS, Barcelona, Spain"
+      },
+      {
+        "author_name": "Manuel Romero-Gomez",
+        "author_inst": "Centro de Investigacion Biomedica en Red en Enfermedades Hepaticas y Digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), Madrid, Spain"
+      },
+      {
+        "author_name": "Agustin Albillos",
+        "author_inst": "Department of Gastroenterology, Hospital Universitario Ramon y Cajal, University of Alcala, Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid,"
+      },
+      {
+        "author_name": "Pietro Invernizzi",
+        "author_inst": "European Reference Network on Hepatological Diseases (ERN RARE-LIVER), San Gerardo Hospital, Monza, Italy"
+      },
+      {
+        "author_name": "Maria Buti",
+        "author_inst": "Universitat Autonoma de Barcelona, Bellatera, Spain"
+      },
+      {
+        "author_name": "Stefano Duga",
+        "author_inst": "Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy"
+      },
+      {
+        "author_name": "Luis Bujanda",
+        "author_inst": "Department of Liver and Gastrointestinal Diseases, Biodonostia Health Research Institute, Donostia University Hospital, University of the Basque Country (UPV/EH"
+      },
+      {
+        "author_name": "Johannes R Hov",
+        "author_inst": "Section for Gastroenterology, Department of Transplantation Medicine, Division for Cancer Medicine, Surgery and Transplantation, Oslo University Hospital Riksho"
+      },
+      {
+        "author_name": "Tobias L Lenz",
+        "author_inst": "Research Group for Evolutionary Immunogenomics, Max Planck Institute for Evolutionary Biology, Ploen, Germany"
+      },
+      {
+        "author_name": "Rosanna Asselta",
+        "author_inst": "IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy"
+      },
+      {
+        "author_name": "Rafael de Cid",
+        "author_inst": "Genomes for Life-GCAT lab. Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain"
+      },
+      {
+        "author_name": "Luca Valenti",
+        "author_inst": "University of Milan, Milan, Italy"
+      },
+      {
+        "author_name": "Tom Hemming Karlsen",
+        "author_inst": "Norwegian PSC Research Center, Department of Transplantation Medicine, Division of Surgery, Inflammatory Diseases and Transplantation, Oslo University Hospital "
+      },
+      {
+        "author_name": "Mario Caceres",
+        "author_inst": "Institut de Biotecnologia i de Biomedicina, Universitat Autonoma de Barcelona, Bellaterra (Barcelona), Spain"
+      },
+      {
+        "author_name": "Andre Franke",
+        "author_inst": "University Hospital Schleswig-Holstein (UKSH), Campus Kiel, Germany"
+      },
+      {
+        "author_name": "- COVICAT study group",
+        "author_inst": ""
+      },
+      {
+        "author_name": "- Covid-19 Aachen Study (COVAS)",
+        "author_inst": ""
       },
       {
-        "author_name": "Sunandan Dey",
-        "author_inst": "Department of Pharmacy, University of Rajshahi, Rajshahi-6205, Bangladesh."
+        "author_name": "- Pa COVID-19 Study Group",
+        "author_inst": ""
       },
       {
-        "author_name": "Rashni Agarwala",
-        "author_inst": "Department of Pharmacy, Islamic University, Kushtia-7003, Bangladesh."
+        "author_name": "- The Humanitas COVID-19 Task Force",
+        "author_inst": ""
       },
       {
-        "author_name": "Md. Nurnobi Islam",
-        "author_inst": "Department of Chemistry, Shahjalal University of  Science & Technology, Sylhet-3114, Bangladesh."
+        "author_name": "- The Humanitas Gavazzeni COVID-19 Task Force",
+        "author_inst": ""
       },
       {
-        "author_name": "Bayezid Bostami",
-        "author_inst": "Department of Pharmacy, University of Rajshahi, Rajshahi-6205, Bangladesh."
+        "author_name": "- Norwegian SARS-CoV-2 Study group",
+        "author_inst": ""
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "genetic and genomic medicine"
   },
   {
     "rel_doi": "10.1101/2021.07.21.21260961",
@@ -609821,91 +613140,203 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.07.20.21260558",
-    "rel_title": "Intentions to participate in cervical and colorectal cancer screening during the COVID-19 pandemic: a mixed-methods study",
+    "rel_doi": "10.1101/2021.07.19.21260139",
+    "rel_title": "Plasma cell-free DNA promise disease monitoring and tissue injury assessment of COVID-19",
     "rel_date": "2021-07-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.20.21260558",
-    "rel_abs": "Worldwide, cancer screening faced significant disruption in 2020 due to the COVID-19 pandemic. If this has led to changes in public attitudes towards screening and reduced intention to participate, there is a risk of long-term adverse impact on cancer outcomes. In this study, we examined previous participation and future intentions to take part in cervical and colorectal cancer (CRC) screening following the first national lockdown in the UK.\n\nOverall, 7543 adults were recruited to a cross-sectional online survey in August-September 2020. Logistic regression analyses were used to identify correlates of strong screening intentions among 2,319 participants eligible for cervical screening and 2,502 eligible for home-based CRC screening. Qualitative interviews were conducted with a sub-sample of 30 participants. Verbatim transcripts were analysed thematically.\n\nOf those eligible, 74% of survey participants intended to attend cervical screening and 84% intended to complete home-based CRC screening when next invited. Thirty percent and 19% of the cervical and CRC samples respectively said they were less likely to attend a cancer screening appointment now than before the pandemic. Previous non-participation was the strongest predictor of low intentions for cervical (aOR 26.31, 95% CI: 17.61-39.30) and CRC (aOR 67.68, 95% CI: 33.91-135.06) screening. Interview participants expressed concerns about visiting healthcare settings but were keen to participate when screening programmes resumed.\n\nIntentions to participate in future screening were high and strongly associated with previous engagement in both programmes. As screening services recover, it will be important to monitor participation and to ensure people feel safe to attend.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260139",
+    "rel_abs": "COVID-19 is a huge threat to global health. Due to the lack of definitive etiological therapeutics currently, effective disease monitoring is of high clinical value for better healthcare and management of the large number of COVID-19 patients. In this study, we recruited 37 COVID-19 patients, collected 176 blood samples upon diagnosis and during treatment, and analyzed cell-free DNA (cfDNA) in these samples. We report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA characteristics reflect patient-specific physiological conditions during treatment. Further analysis on tissue origin tracing of cfDNA reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, we demonstrate the translational merit of cfDNA as valuable analyte for effective disease monitoring, as well as tissue injury assessment in COVID-19 patients.",
+    "rel_num_authors": 46,
     "rel_authors": [
       {
-        "author_name": "Rebecca Wilson",
-        "author_inst": "Cardiff University"
+        "author_name": "Xin Jin",
+        "author_inst": "BGI-Shenzhen"
       },
       {
-        "author_name": "Harriet Quinn-Scoggins",
-        "author_inst": "Cardiff University"
+        "author_name": "Yanqun Wang",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Yvonne Moriarty",
-        "author_inst": "Cardiff University"
+        "author_name": "Jinjin Xu",
+        "author_inst": "BGI-Shenzhen"
       },
       {
-        "author_name": "Jacqueline Hughes",
-        "author_inst": "Cardiff University"
+        "author_name": "Yimin Li",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Mark Goddard",
-        "author_inst": "Cardiff University"
+        "author_name": "Fanjun Cheng",
+        "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Rebecca Cannings-John",
-        "author_inst": "Cardiff University"
+        "author_name": "Yuxue Luo",
+        "author_inst": "BGI-Shenzhen"
       },
       {
-        "author_name": "Victoria Whitelock",
-        "author_inst": "Cancer Research UK"
+        "author_name": "Haibo Zhou",
+        "author_inst": "The Sixth Affiliated Hospital of Guangzhou Medical University"
       },
       {
-        "author_name": "Katriina L Whitaker",
-        "author_inst": "University of Surrey"
+        "author_name": "Shanwen Lin",
+        "author_inst": "Yangjiang People Hospital"
       },
       {
-        "author_name": "Detelina Grozeva",
-        "author_inst": "Cardiff University"
+        "author_name": "Fei Xiao",
+        "author_inst": "Department of Infectious Diseases, Guangdong Provincial Key Laboratory of Biomedical Imaging, Guangdong Provincial Engineering Research Center of Molecular Imag"
       },
       {
-        "author_name": "Julia Townson",
-        "author_inst": "Cardiff University"
+        "author_name": "Lu Zhang",
+        "author_inst": "Institute of Infectious disease, Guangzhou Eighth People's Hospital of Guangzhou Medical University"
       },
       {
-        "author_name": "Kirstie Osborne",
-        "author_inst": "Cancer Research UK"
+        "author_name": "Yu Lin",
+        "author_inst": "BGI-Shenzhen"
       },
       {
-        "author_name": "Stephanie Smits",
-        "author_inst": "Cardiff University"
+        "author_name": "Zhaoyong Zhang",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Michael Robling",
-        "author_inst": "Cardiff University"
+        "author_name": "Yan Jin",
+        "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Julie Hepburn",
-        "author_inst": "Public Involvement Community, Health and Care Research Wales"
+        "author_name": "Fang Zheng",
+        "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Graham Moore",
-        "author_inst": "Cardiff University"
+        "author_name": "Wei Chen",
+        "author_inst": "School of Medicine, South China University of Technology"
       },
       {
-        "author_name": "Ardiana Gjini",
-        "author_inst": "Public Health Wales"
+        "author_name": "Airu Zhu",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Kate Brain",
-        "author_inst": "Cardiff University"
+        "author_name": "Ye Tao",
+        "author_inst": "BGI-Shenzhen"
       },
       {
-        "author_name": "Jo Waller",
-        "author_inst": "Kings College London"
+        "author_name": "Jingxian Zhao",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Tingyou Kuo",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Yuming Li",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Lingguo Li",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Liyan Wen",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Rijing Ou",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Fang Li",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Long Lin",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Yanjun Zhang",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Jing Sun",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Hao Yuan",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Zhen Zhuang",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Haixi Sun",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Zhao Chen",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Jie Li",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Jianfen Zhuo",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Dongsheng Chen",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Shengnan Zhang",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Yuzhe Sun",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Peilan Wei",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Jinwei Yuan",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Tian Xu",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Huanming Yang",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Jian Wang",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Xun Xu",
+        "author_inst": "BGI-Shenzhen"
+      },
+      {
+        "author_name": "Nanshan Zhong",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Yonghao Xu",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+      },
+      {
+        "author_name": "Kun Sun",
+        "author_inst": "Shenzhen Bay Laboratory"
+      },
+      {
+        "author_name": "Jincun Zhao",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "oncology"
+    "category": "genetic and genomic medicine"
   },
   {
     "rel_doi": "10.1101/2021.07.19.21260758",
@@ -611735,417 +615166,101 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.07.19.21260779",
-    "rel_title": "Surveillance of SARS-CoV-2 variants in Argentina: detection of Alpha, Gamma, Lambda, Epsilon and Zeta in locally transmitted and imported cases",
+    "rel_doi": "10.1101/2021.07.19.21260759",
+    "rel_title": "Development and validation of a prognostic model for COVID-19: a population-based cohort study in Iceland",
     "rel_date": "2021-07-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260779",
-    "rel_abs": "Molecular surveillance of SARS-CoV-2 variants was performed on a total of 2,406 samples from the capital city and nine provinces of Argentina, during 30 epidemiological weeks (EW) that covered the end of the first wave and the beginning of the ongoing second wave of the COVID-19 pandemic in the country (EW 44/2020 to EW 20/2021). The surveillance strategy was mainly based on Sanger sequencing of a Spike coding region that allows the simultaneous identification of signature mutations associated with worldwide circulating variants. In addition, whole SARS-CoV-2 genome sequences were obtained from 456 samples. The main variants found were Gamma, Lambda and Alpha, and to a lesser extent, Zeta and Epsilon. Whereas Gamma dominated in different regions of the country, both Gamma and Lambda prevailed in the most populated area, the metropolitan region of Buenos Aires (MABA), although showing a heterogeneous distribution along this region. This cost-effective surveillance protocol allowed for a rapid response in a limited access to resources scenario, added information on the expansion of the Lambda variant in South America and contributed to the implementation of public health measures to control the disease spread in Argentina.",
-    "rel_num_authors": 101,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260759",
+    "rel_abs": "BackgroundThe severity of SARS-CoV-2 infection varies from asymptomatic state to severe respiratory failure and the clinical course is difficult to predict. The aim of the study was to develop a prognostic model to predict the severity of COVID-19 at the time of diagnosis and determine risk factors for severe disease.\n\nMethodsAll SARS-CoV-2-positive adults in Iceland were prospectively enrolled into a telehealth service at diagnosis. A multivariable proportional-odds logistic regression model was derived from information obtained during the enrollment interview with those diagnosed before May 1, 2020 and validated in those diagnosed between May 1 and December 31, 2020. Outcomes were defined on an ordinal scale; no need for escalation of care during follow-up, need for outpatient visit, hospitalization, and admission to intensive care unit (ICU) or death. Risk factors were summarized as odds ratios (OR) adjusted for confounders identified by a directed acyclic graph.\n\nResultsThe prognostic model was derived from and validated in 1,625 and 3,131 individuals, respectively. In total, 375 (7.9%) only required outpatient visits, 188 (4.0%) were hospitalized and 50 (1.1%) were either admitted to ICU or died due to complications of COVID-19. The model included age, sex, body mass index (BMI), current smoking, underlying conditions, and symptoms and clinical severity score at enrollment. Discrimination and calibration were excellent for outpatient visit or worse (C-statistic 0.75, calibration intercept 0.04 and slope 0.93) and hospitalization or worse (C-statistic 0.81, calibration intercept 0.16 and slope 1.03). Age was the strongest risk factor for adverse outcomes with OR of 75-compared to 45-year-olds, ranging from 5.29-17.3. Higher BMI consistently increased the risk and chronic obstructive pulmonary disease and chronic kidney disease correlated with worse outcomes.\n\nConclusionOur prognostic model can accurately predict the outcome of SARS-CoV-2 infection using information that is available at the time of diagnosis.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Carolina Torres",
-        "author_inst": "Universidad de Buenos Aires, Facultad de Farmacia y Bioquimica, Instituto de Investigaciones en Bacteriologia y Virologia Molecular (IBaViM), Buenos Aires, Arge"
-      },
-      {
-        "author_name": "Laura Mojsiejczuk",
-        "author_inst": "Universidad de Buenos Aires, Facultad de Farmacia y Bioquimica, Instituto de Investigaciones en Bacteriologia y Virologia Molecular (IBaViM), Buenos Aires, Arge"
-      },
-      {
-        "author_name": "Dolores Acuna",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Buenos"
-      },
-      {
-        "author_name": "Sofia Alexay",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Ariel Amadio",
-        "author_inst": "Instituto de Investigacion de la Cadena Lactea (IDICAL) INTA-CONICET. Ruta 34 km 227, Rafaela (2300), Santa Fe, Argentina; Consejo Nacional de Investigaciones C"
-      },
-      {
-        "author_name": "Paula Aulicino",
-        "author_inst": "Laboratorio de Biologia Celular y Retrovirus. Hospital de Pediatria Prof. Juan P. Garrahan, CABA, Argentina; Consejo Nacional de Investigaciones Cientificas y T"
-      },
-      {
-        "author_name": "Humberto Debat",
-        "author_inst": "Instituto de Patologia Vegetal, Centro de Investigaciones Agropecuarias, Instituto Nacional de Tecnologia Agropecuaria (IPAVE-CIAP-INTA), Camino 60 Cuadras Km 5"
-      },
-      {
-        "author_name": "Franco Fernandez",
-        "author_inst": "Instituto de Patologia Vegetal, Centro de Investigaciones Agropecuarias, Instituto Nacional de Tecnologia Agropecuaria (IPAVE-CIAP-INTA), Camino 60 Cuadras Km 5"
-      },
-      {
-        "author_name": "Stephanie Goya",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Guido Konig",
-        "author_inst": "Instituto de Biotecnologia/Instituto de Agrobiotecnologia y Biologia Molecular (INTA-CONICET), Hurlingham, Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Mercedes Nabaes Jodar",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Buenos"
-      },
-      {
-        "author_name": "Luis Pianciola",
-        "author_inst": "Laboratorio Central ciudad de Neuquen, Ministerio de Salud, Neuquen, Argentina"
-      },
-      {
-        "author_name": "Sofia Bengoa",
-        "author_inst": "Instituto de Biotecnologia/Instituto de Agrobiotecnologia y Biologia Molecular (INTA-CONICET), Hurlingham, Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Marco Cacciahue",
-        "author_inst": "Instituto de Biotecnologia/Instituto de Agrobiotecnologia y Biologia Molecular (INTA-CONICET), Hurlingham, Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Cecilia Camussone",
-        "author_inst": "Instituto de Investigacion de la Cadena Lactea (IDICAL) INTA-CONICET. Ruta 34 km 227, Rafaela (2300), Santa Fe, Argentina"
-      },
-      {
-        "author_name": "Maria Jose Dus Santos",
-        "author_inst": "Instituto de Virologia e Innovaciones Tecnologicas (INTA-CONICET), Hurlingham, Buenos Aires, Argentina; Laboratorio de Diagnostico-UNIDAD COVID- Universidad Nac"
-      },
-      {
-        "author_name": "Maria Florencia Eberhardt",
-        "author_inst": "Instituto de Investigacion de la Cadena Lactea (IDICAL) INTA-CONICET. Ruta 34 km 227, Rafaela (2300), Santa Fe, Argentina; Consejo Nacional de Investigaciones C"
-      },
-      {
-        "author_name": "Ailen Fernandez",
-        "author_inst": "Laboratorio Central ciudad de Neuquen, Ministerio de Salud, Neuquen, Argentina"
-      },
-      {
-        "author_name": "Maria Ines Gismondi",
-        "author_inst": "Instituto de Biotecnologia/Instituto de Agrobiotecnologia y Biologia Molecular (INTA-CONICET), Hurlingham, Buenos Aires, Argentina; Universidad Nacional de Luja"
-      },
-      {
-        "author_name": "Matias Irazoqui",
-        "author_inst": "Instituto de Investigacion de la Cadena Lactea (IDICAL) INTA-CONICET. Ruta 34 km 227, Rafaela (2300), Santa Fe, Argentina;  Consejo Nacional de Investigaciones "
-      },
-      {
-        "author_name": "Silvina Lusso",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Nathalie Marquez",
-        "author_inst": "Instituto de Patologia Vegetal, Centro de Investigaciones Agropecuarias, Instituto Nacional de Tecnologia Agropecuaria (IPAVE-CIAP-INTA), Camino 60 Cuadras Km 5"
-      },
-      {
-        "author_name": "Marianne Munoz",
-        "author_inst": "Unidad de Genomica del Instituto de Biotecnologia/Instituto de Agrobiotecnologia y biologia Molecular (INTA-CONICET), Hurlingham, Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Monica Natale",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Belen Pisano",
-        "author_inst": "Instituto de Virologia Dr. J. M. Vanella, Facultad de Ciencias Medicas, Universidad Nacional de Cordoba; Consejo Nacional de Investigaciones Cientificas y Tecni"
-      },
-      {
-        "author_name": "Andrea Puebla",
-        "author_inst": "Instituto de Biotecnologia/Instituto de Agrobiotecnologia y Biologia Molecular (INTA-CONICET), Hurlingham, Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Viviana Re",
-        "author_inst": "Instituto de Virologia Dr. J. M. Vanella, Facultad de Ciencias Medicas, Universidad Nacional de Cordoba; Consejo Nacional de Investigaciones Cientificas y Tecni"
-      },
-      {
-        "author_name": "Ezequiel Sosa",
-        "author_inst": "Instituto de Quimica Biologica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), CONICET, Ciudad de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Jonathan Zaiat",
-        "author_inst": "Instituto de Quimica Biologica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), CONICET, Ciudad de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Sebastian Zunino",
-        "author_inst": "Laboratorio de Virologia Molecular, Hospital Blas L. Dubarry de Mercedes, provincia de Buenos Aires, Argentina; Universidad Nacional de Lujan, Departamento de C"
-      },
-      {
-        "author_name": "Dario Do porto",
-        "author_inst": "Instituto de Quimica Biologica de la Facultad de Ciencias Exactas y Naturales (IQUIBICEN), CONICET, Ciudad de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Maria Elina Acevedo",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Cristina Alvarez Lopez",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Maria Laura Alvarez",
-        "author_inst": "Laboratorio del Hospital Zonal Dr. Ramon Carrillo, San Carlos De Bariloche, provincia de Rio Negro, Argentina"
-      },
-      {
-        "author_name": "Patricia Angeleri",
-        "author_inst": "Comite Operativo de Emergencia COVID, Ministerio de Salud de la Ciudad Autonoma de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Andres Angelletti",
-        "author_inst": "Laboratorio de salud publica, Facultad de Ciencias Exactas, UNLP, La Plata, Provincia de Buenos Aires, Argentina; Laboratorio de Virologia, HIEAyC San Juan de D"
-      },
-      {
-        "author_name": "Manuel Arca",
-        "author_inst": "Laboratorio de Virologia del Hospital JJ Urquiza, Concepcion del Uruguay, provincia de Entre Rios, Argentina"
-      },
-      {
-        "author_name": "Gabriela Barbas",
-        "author_inst": "Secretaria de Prevencion y Promocion, Ministerio de Salud de la provincia de Cordoba, Argentina."
-      },
-      {
-        "author_name": "Ana Bertone",
-        "author_inst": "Laboratorio de la Direccion de Epidemiologia, Santa Rosa, provincia de La Pampa, Argentina."
-      },
-      {
-        "author_name": "Agustina Bonnet",
-        "author_inst": "Laboratorio de Virologia del Hospital JJ Urquiza, Concepcion del Uruguay, provincia de Entre Rios, Argentina"
-      },
-      {
-        "author_name": "Ignacio Bourlot",
-        "author_inst": "Laboratorio de biologia molecular del Hospital Centenario, Gualeguaychu, provincia de Entre Rios, Argentina."
-      },
-      {
-        "author_name": "Alejandro Castello",
-        "author_inst": "Plataforma de Servicios Biotecnologicos; UTTIPP/PSB, Bernal, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Gonzalo Castro",
-        "author_inst": "Laboratorio Central de la Provincia de Cordoba, Ministerio de Salud la provincia de Cordoba, Argentina."
-      },
-      {
-        "author_name": "Carolina Ceriani",
-        "author_inst": "Laboratorio de Virologia de la Facultad de Veterinaria de la Universidad Nacional del Centro de la provincia de Buenos Aires (UNCPBA), Tandil, provincia de Buen"
-      },
-      {
-        "author_name": "Carlos Cimino",
-        "author_inst": "Instituto Nacional de Epidemiologia Dr. Jara (Mar del Plata, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Julian Cipelli",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Maria Colmeiro",
-        "author_inst": "Laboratorio de Virologia, HIEAyC \"San Juan de Dios\", La Plata, provincia de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Andres Cordero",
-        "author_inst": "Laboratorio de salud publica, Facultad de Ciencias Exactas, UNLP, La Plata, Provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Carolina Cristina",
-        "author_inst": "Centro de Investigaciones Basicas y Aplicadas, UNNOBA, Junin, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Sofia Di Bella",
-        "author_inst": "Laboratorio de Virologia, HIEAyC San Juan de Dios, La Plata, provincia de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Regina Ercole",
-        "author_inst": "Laboratorio de Virologia, HIEAyC San Juan de Dios, La Plata, provincia de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Yesica Espasandin",
-        "author_inst": "Laboratorio del Hospital Zonal Dr. Ramon Carrillo, San Carlos De Bariloche, provincia de Rio Negro, Argentina"
-      },
-      {
-        "author_name": "Carlos Espul",
-        "author_inst": "Direccion de epidemiologia y Red de Laboratorios del Ministerio de Salud de la provincia de Mendoza, Argentina."
-      },
-      {
-        "author_name": "Andrea Falaschi",
-        "author_inst": "Direccion de epidemiologia y Red de Laboratorios del Ministerio de Salud de la provincia de Mendoza, Argentina."
-      },
-      {
-        "author_name": "Facundo Fernandez Moll",
-        "author_inst": "Centro de Investigaciones Basicas y Aplicadas, UNNOBA, Junin, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Andrea Gatelli",
-        "author_inst": "Laboratorio de Virologia, HIEAyC San Juan de Dios, La Plata, provincia de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Sandra Goni",
-        "author_inst": "Plataforma de Servicios Biotecnologicos; UTTIPP/PSB, Bernal, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Maria E Jofre",
-        "author_inst": "Laboratorio de Biologia Molecular Bolivar, LABBO, Bolivar, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Jose Jaramillo",
-        "author_inst": "Laboratorio de Virologia Molecular, Hospital Blas L. Dubarry de Mercedes, provincia de Buenos Aires, Argentina"
-      },
-      {
-        "author_name": "Natalia Labarta",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina"
-      },
-      {
-        "author_name": "Maria A Lacaze",
-        "author_inst": "Programa Laboratorio de Salud Publica Dr Dalmiro Perez Laborda, Ministerio de Salud de la provincia de San Luis, Argentina."
-      },
-      {
-        "author_name": "Rocio Larreche",
-        "author_inst": "Laboratorio de Biologia Molecular Bolivar, LABBO, Bolivar, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Viviana Leiva",
-        "author_inst": "Laboratorio de Biologia Molecular Bolivar, LABBO, Bolivar, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Gustavo Levin",
-        "author_inst": "Laboratorio de biologia molecular del Hospital Centenario, Gualeguaychu, provincia de Entre Rios, Argentina."
-      },
-      {
-        "author_name": "Erica Luczak",
-        "author_inst": "Laboratorio del Hospital Interzonal General de Agudos Evita, Lanus, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Marcelo Mandile",
-        "author_inst": "Plataforma de Servicios Biotecnologicos; UTTIPP/PSB, Bernal, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Carla Massone",
-        "author_inst": "Laboratorio de Virologia Molecular, Hospital Blas L. Dubarry de Mercedes, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Melina Mazzeo",
-        "author_inst": "Laboratorio Central ciudad de Neuquen, Ministerio de Salud, Neuquen, Argentina"
-      },
-      {
-        "author_name": "Carla Medina",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina."
-      },
-      {
-        "author_name": "Belen Monaco",
-        "author_inst": "Laboratorio de Virologia Molecular, Hospital Blas L. Dubarry de Mercedes, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Luciana Montoto",
-        "author_inst": "Laboratorio de Biologia Molecular Hospital Pedro de Elizalde, Cuidad Autonoma de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Viviana Mugna",
-        "author_inst": "Laboratorio Central, ciudad de Santa Fe, provincia de Santa Fe. Argentina."
-      },
-      {
-        "author_name": "Alejandra Musto",
-        "author_inst": "Laboratorio del Hospital Interzonal General de Agudos Evita, Lanus, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Guillermo Ojeda",
-        "author_inst": "Laboratorio Central, ciudad de Santa Fe, provincia de Santa Fe. Argentina."
-      },
-      {
-        "author_name": "Carolina Pintos",
-        "author_inst": "Laboratorio Central ciudad de Neuquen, Ministerio de Salud, Neuquen, Argentina."
-      },
-      {
-        "author_name": "Marcia Pozzati",
-        "author_inst": "Laboratorio de Biologia Molecular, Hospital Cosme Argerich, Cuidad Autonoma de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Marilina Rahhal",
-        "author_inst": "Laboratorio de Hospital El Cruce Dr. Nestor C. Kirchner, CEMET, Florencio Varela, provincia de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Claudia Rechimont",
-        "author_inst": "Laboratorio de la Direccion de Epidemiologia, Santa Rosa, provincia de La Pampa, Argentina."
-      },
-      {
-        "author_name": "Federico Remes Lenicov",
-        "author_inst": "Instituto de Investigaciones Biomedicas en Retrovirus y Sida, CONICET-UBA, Cuidad Autonoma de Buenos Aires, Argentina."
-      },
-      {
-        "author_name": "Gabriela Rompato",
-        "author_inst": "Laboratorio Central, ciudad de Santa Fe, provincia de Santa Fe. Argentina."
+        "author_name": "Elias Eythorsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Vanesa Seery",
-        "author_inst": "Instituto de Investigaciones Biomedicas en Retrovirus y Sida, CONICET-UBA, Cuidad Autonoma de Buenos Aires, Argentina."
+        "author_name": "Valgerdur Bjarnadottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Leticia Siri",
-        "author_inst": "Laboratorio de biologia molecular del Hospital Centenario, Gualeguaychu, provincia de Entre Rios, Argentina."
+        "author_name": "Hrafnhildur Linnet Runolfsdottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Julieta Spina",
-        "author_inst": "Laboratorio de Biologia Molecular. Hospital Dr. Hector Cura, Olavarria, provincia de Buenos Aires, Argentina."
+        "author_name": "Dadi Helgason",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Cintia Streitenberger",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina."
+        "author_name": "Ragnar Freyr Ingvarsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Ariel Suarez",
-        "author_inst": "Departamento de Biologia y genetica molecular; IACA Laboratorios, Bahia Blanca, provincia de Buenos Aires, Argentina."
+        "author_name": "Helgi K Bjornsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Jorgelina Suarez",
-        "author_inst": "Centro de Investigaciones Basicas y Aplicadas, UNNOBA, Junin, provincia de Buenos Aires, Argentina."
+        "author_name": "Lovisa Bjork Olafsdottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Paula Sujanski",
-        "author_inst": "Comite Operativo de Emergencia COVID, Ministerio de Salud de la Ciudad Autonoma de Buenos Aires, Argentina."
+        "author_name": "Solveig Bjarnadottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Juan M Talia",
-        "author_inst": "Programa Laboratorio de Salud Publica Dr Dalmiro Perez Laborda, Ministerio de Salud de la provincia de San Luis, Argentina."
+        "author_name": "Arnar Snaer Agustsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Clara Theaux",
-        "author_inst": "Laboratorio de Biologia molecular del Hospital General de Agudos Dr. Carlos G. Durand, Cuidad Autonoma de Buenos Aires, Argentina."
+        "author_name": "Kristin Oskarsdottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Guillermo Thomas",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina."
+        "author_name": "Hrafn Hliddal Thorvaldsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Marina Ticeira",
-        "author_inst": "Laboratorio de Biologia Molecular Bolivar, LABBO, Bolivar, provincia de Buenos Aires, Argentina."
+        "author_name": "Gudrun Kristjansdottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Estefania Tittarelli",
-        "author_inst": "Departamento de Biologia y genetica molecular; IACA Laboratorios, Bahia Blanca, provincia de Buenos Aires, Argentina."
+        "author_name": "Aron Hjalti Bjornsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Rosana Toro",
-        "author_inst": "Laboratorio de salud publica, Facultad de Ciencias Exactas, UNLP, La Plata, Provincia de Buenos Aires, Argentina."
+        "author_name": "Arna R Emilsdottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Osvaldo Uez",
-        "author_inst": "Instituto Nacional de Epidemiologia Dr. Jara (Mar del Plata, provincia de Buenos Aires, Argentina."
+        "author_name": "Brynja Armannsdottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Maria B Zaffanella",
-        "author_inst": "Laboratorio de Biologia Molecular. Hospital Dr. Hector Cura, Olavarria, provincia de Buenos Aires, Argentina."
+        "author_name": "Olafur Gudlaugsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Cecilia Ziehm",
-        "author_inst": "Laboratorio Central ciudad de Neuquen, Ministerio de Salud, Neuquen, Argentina."
+        "author_name": "Sif Hansdottir",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Martin Zubieta",
-        "author_inst": "Laboratorio de Hospital El Cruce Dr. Nestor C. Kirchner, CEMET, Florencio Varela, provincia de Buenos Aires, Argentina."
+        "author_name": "Magnus Gottfredsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "- PAIS Consortium",
-        "author_inst": "-"
+        "author_name": "Agnar Bjarnason",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Alicia Mistchenko",
-        "author_inst": "Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez, CABA, Argentina; Comision de Investigaciones Cientificas de la provincia de Buenos Aires, Arg"
+        "author_name": "Martin I Sigurdsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Laura Valinotto",
-        "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Buenos Aires, Argentina; Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez"
+        "author_name": "Olafur S Indridason",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       },
       {
-        "author_name": "Mariana Viegas",
-        "author_inst": "Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Buenos Aires, Argentina; Laboratorio de Virologia, Hospital de Ninos Dr. Ricardo Gutierrez"
+        "author_name": "Runolfur Palsson",
+        "author_inst": "Landspitali - The National University Hospital of Iceland"
       }
     ],
     "version": "1",
@@ -613873,63 +616988,43 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2021.07.22.453287",
-    "rel_title": "Competent immune responses to SARS-CoV-2 variants in older adults following mRNA vaccination",
+    "rel_doi": "10.1101/2021.07.20.21260892",
+    "rel_title": "Variation in SARS-CoV-2 bioaerosol production in exhaled breath",
     "rel_date": "2021-07-22",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.22.453287",
-    "rel_abs": "Aging is associated with a reduced magnitude of primary immune responses to vaccination and constriction of immune receptor repertoire diversity. Clinical trials demonstrated high efficacy of mRNA based SARS-CoV-2 vaccines in older adults but concerns about virus variant escape have not been well addressed. We have conducted an in-depth analysis of humoral and cellular immunity against an early-pandemic viral isolate and compared that to the P.1. (Gamma) and B.1.617.2 (Delta) variants in <50 and >55 age cohorts of mRNA vaccine recipients. We have further measured neutralizing antibody titers for B.1.617.1 (Kappa) and B.1.595; a SARS-CoV-2 isolate bearing Spike mutation E484Q. As reported, robust immunity required the second dose of vaccine. Older vaccinees manifested robust cellular immunity against early-pandemic SARS-CoV-2 and more recent variants, which remained statistically comparable to the adult group. The older cohort had lower neutralizing capacity at the first time point following the second dose, but at later time points immunity was indistinguishable between them. While the duration of these immune responses remains to be determined over longer periods of time, these results provide reasons for optimism regarding vaccine protection of older adults against SARS-CoV-2 variants and inform thinking about boost vaccination with variant vaccines.\n\neTOC summaryVaccine responses are often diminished with aging, but we found strong responses to SARS-CoV-2 in older adults following mRNA vaccination. T cell responses were not diminished when confronted by SARS-CoV-2 variants. Neutralizing Ab were reduced but not more than those in adults.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=73 SRC=\"FIGDIR/small/453287v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (16K):\norg.highwire.dtl.DTLVardef@1091655org.highwire.dtl.DTLVardef@1996173org.highwire.dtl.DTLVardef@ccf2f9org.highwire.dtl.DTLVardef@163ed22_HPS_FORMAT_FIGEXP  M_FIG C_FIG Created with BioRender.com",
-    "rel_num_authors": 11,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.20.21260892",
+    "rel_abs": "Using face mask bioaerosol sampling, we found substantial variation between individuals in SARS-CoV-2 copies exhaled over a 15-minute period, which moderately correlated with nasal swab viral load. Talking was associated with a median of 2 log10 greater exhaled viral copies. Exposure varies substantially between individuals but may be risk stratified by nasal swab viral load and whether the exposure involved conversation.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Mladen Jergovi\u0107",
-        "author_inst": "University of Arizona"
-      },
-      {
-        "author_name": "Jennifer L. Uhrlaub",
-        "author_inst": "University of Arizona"
-      },
-      {
-        "author_name": "Makiko Watanabe",
-        "author_inst": "University of Arizona"
-      },
-      {
-        "author_name": "Christine M. Bradshaw",
-        "author_inst": "University of Arizona"
-      },
-      {
-        "author_name": "Lisa M. White",
-        "author_inst": "University of Arizona"
-      },
-      {
-        "author_name": "Bonnie J. LaFleur",
-        "author_inst": "University of Arizona"
+        "author_name": "Renu Verma",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA"
       },
       {
-        "author_name": "Taylor Edwards",
-        "author_inst": "University of Arizona"
+        "author_name": "Eugene Kim",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA"
       },
       {
-        "author_name": "Ryan Sprissler",
-        "author_inst": "University of Arizona"
+        "author_name": "Nicholas Degner",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA"
       },
       {
-        "author_name": "Michael Worobey",
-        "author_inst": "University of Arizona"
+        "author_name": "Katharine S. Walter",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA"
       },
       {
-        "author_name": "Deepta Bhattacharya",
-        "author_inst": "University of Arizona"
+        "author_name": "Upinder Singh",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Dept of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA"
       },
       {
-        "author_name": "Janko Nikolich-\u017dugich",
-        "author_inst": "University of Arizona"
+        "author_name": "Jason R Andrews",
+        "author_inst": "Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "immunology"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.07.20.21260871",
@@ -615579,47 +618674,71 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2021.07.20.453118",
-    "rel_title": "Integrin activation is an essential component of SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2021.07.20.453054",
+    "rel_title": "Discovery of nanobodies against SARS-CoV-2 and an uncommon neutralizing mechanism",
     "rel_date": "2021-07-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.20.453118",
-    "rel_abs": "Cellular entry of coronaviruses depends on binding of the viral spike (S) protein to a specific cellular receptor, the angiotensin-converting enzyme 2 (ACE2). Furthermore, the viral spike protein expresses an RGD motif, suggesting that cell surface integrins may be attachment co-receptors. However, using infectious SARS-CoV-2 requires a biosafety level 3 laboratory (BSL-3), which limits the techniques that can be used to study the mechanism of cell entry. Here, we UV-inactivated SARS-CoV-2 and fluorescently labeled the envelope membrane with octadecyl rhodamine B (R18) to explore the role of integrin activation in mediating both cell entry and productive infection. We used flow cytometry and confocal fluorescence microscopy to show that fluorescently labeled SARS-CoV-2R18 particles engage basal-state integrins. Furthermore, we demonstrate that Mn2+, which activates integrins and induces integrin extension, enhances cell binding and entry of SARS-CoV-2R18 in proportion to the fraction of integrins activated. We also show that one class of integrin antagonist, which binds to the I MIDAS site and stabilizes the inactive, closed conformation, selectively inhibits the engagement of SARS-CoV-2R18 with basal state integrins, but is ineffective against Mn2+-activated integrins. At the same time, RGD-integrin antagonists inhibited SARS-CoV-2R18 binding regardless of integrin activity state. Integrins transmit signals bidirectionally:  inside-out signaling primes the ligand binding function of integrins via a talin dependent mechanism and  outside-in signaling occurs downstream of integrin binding to macromolecular ligands. Outside-in signaling is mediated by G13 and induces cell spreading, retraction, migration, and proliferation. Using cell-permeable peptide inhibitors of talin, and G13 binding to the cytoplasmic tail of an integrins {beta} subunit, we further demonstrate that talin-mediated signaling is essential for productive infection by SARS-CoV-2.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.20.453054",
+    "rel_abs": "SARS-CoV-2 and its variants continue to threaten public health. The virus recognizes the host cell by attaching its Spike receptor-binding domain (RBD) to the host receptor ACE2. Therefore, RBD is a primary target for neutralizing antibodies and vaccines. Here we report the isolation, and biological and structural characterization of two single-chain antibodies (nanobodies, DL4 and DL28) from RBD-immunized alpaca. Both nanobodies bind Spike with affinities that exceeded the detection limit (picomolar) of the biolayer interferometry assay and neutralize the original SARS-CoV- 2 strain with IC50 of 0.086 g mL-1 (DL4) and 0.385 g mL-1 (DL28). DL4 and a more potent, rationally designed mutant, neutralizes the Alpha variant as potently as the original strain but only displays marginal activity against the Beta variant. By contrast, the neutralizing activity of DL28, when in the Fc-fused divalent form, was less affected by the mutations in the Beta variant (IC50 of 0.414 g mL-1 for Alpha, 1.060 g mL-1 for Beta). Crystal structure studies reveal that DL4 blocks ACE2-binding by direct competition, while DL28 neutralizes SARS-CoV-2 by an uncommon mechanism through which DL28 distorts the receptor-binding motif in RBD and hence prevents ACE2-binding. Our work provides two neutralizing nanobodies for potential therapeutic development and reveals an uncommon mechanism to design and screen novel neutralizing antibodies against SARS-CoV-2.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Peter Simons",
-        "author_inst": "University of New Mexico"
+        "author_name": "Dianfan Li",
+        "author_inst": "Chinese Academy of Sciences"
       },
       {
-        "author_name": "Derek Rinaldi",
-        "author_inst": "University of New Mexico"
+        "author_name": "Tingting Li",
+        "author_inst": "CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences (CAS)"
       },
       {
-        "author_name": "Virginie Bondu",
-        "author_inst": "University of New Mexico"
+        "author_name": "Bingjie Zhou",
+        "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institut Pasteur of Shanghai CAS"
       },
       {
-        "author_name": "Alison Kell",
-        "author_inst": "University of New Mexico"
+        "author_name": "Zhipu Luo",
+        "author_inst": "Soochow University"
       },
       {
-        "author_name": "Steven Bradfute",
-        "author_inst": "University of New Mexico"
+        "author_name": "Yanling Lai",
+        "author_inst": "CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences (CAS)"
       },
       {
-        "author_name": "Diane Lidke",
-        "author_inst": "University of New Mexico"
+        "author_name": "Suqiong Huang",
+        "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institut Pasteur of Shanghai CAS"
       },
       {
-        "author_name": "Tione Buranda",
-        "author_inst": "University of New Mexico School of Medicine"
+        "author_name": "Yuanze Zhou",
+        "author_inst": "Nanjing Crycision Biotech Co., Ltd."
+      },
+      {
+        "author_name": "Anupriya Gautam",
+        "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institut Pasteur of Shanghai CAS"
+      },
+      {
+        "author_name": "Salome Bourgeau",
+        "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institut Pasteur of Shanghai CAS"
+      },
+      {
+        "author_name": "Shurui Wang",
+        "author_inst": "Nanjing Crycision Biotech Co., Ltd"
+      },
+      {
+        "author_name": "Juan Bao",
+        "author_inst": "State Key Laboratory of Molecular Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology"
+      },
+      {
+        "author_name": "Jingquan Tan",
+        "author_inst": "Nanjing Crycision Biotech Co., Ltd"
+      },
+      {
+        "author_name": "Dimitri Lavillette",
+        "author_inst": "Institut Pasteur Shanghai Chine Academy of Sciences"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "cell biology"
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2021.07.21.453140",
@@ -617405,33 +620524,45 @@
     "category": "emergency medicine"
   },
   {
-    "rel_doi": "10.1101/2021.07.15.21260543",
-    "rel_title": "Understanding Adverse Population Sentiment Towards the Spread of COVID-19 in the United States",
+    "rel_doi": "10.1101/2021.07.15.21260346",
+    "rel_title": "Elderly acceptance of telemedicine use in Hong Kong during and after the COVID-19 pandemic: a cross-sectional cohort survey",
     "rel_date": "2021-07-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.15.21260543",
-    "rel_abs": "BackgroundDuring the ongoing COVID-19 pandemic, the immediate threat of illness and mortality is not the only concern. In the United States, COVID-19 is not only causing physical suffering to patients, but also great levels of adverse sentiment (e.g., fear, panic, anxiety) among the public. Such secondary threats can be anticipated and explained through sentiment analysis of social media, such as Twitter.\n\nMethodsWe obtained a dataset of geotagged tweets on the topic of COVID-19 in the contiguous United States during the period of 11/1/2019 - 9/15/2020. We classified each tweet into \"adverse\" and \"non-adverse\" using the NRC Emotion Lexicon and tallied up the counts for each category per county per day. We utilized the space-time scan statistic to find clusters and a three-stage regression approach to identify socioeconomic and demographic correlates of adverse sentiment.\n\nResultsWe identified substantial spatiotemporal variation in adverse sentiment in our study area/period. After an initial period of low-level adverse sentiment (11/1/2019 - 1/15/2020), we observed a steep increase and subsequent fluctuation at a higher level (1/16/2020 - 9/15/2020). The number of daily tweets was low initially (11/1/2019 - 1/22/2020), followed by spikes and subsequent decreases until the end of the study period. The space-time scan statistic identified 12 clusters of adverse sentiment of varying size, location, and strength. Clusters were generally active during the time period of late March to May/June 2020. Increased adverse sentiment was associated with decreased racial/ethnic heterogeneity, decreased rurality, higher vulnerability in terms of minority status and language, and housing type and transportation.\n\nConclusionsWe utilized a dataset of geotagged tweets to identify the spatiotemporal patterns and the spatial correlates of adverse population sentiment during the first two waves of the COVID-19 pandemic in the United States. The characteristics of areas with high adverse sentiment may be relevant for communication of containment measures. The combination of spatial clustering and regression can be beneficial for understanding of the ramifications of COVID-19, as well as disease outbreaks in general.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.15.21260346",
+    "rel_abs": "BackgroundTelemedicine services worldwide have experienced an unprecedented boom since the beginning of the COVID-19 pandemic. Multiple studies have noted telemedicine as an effective alternative to traditional face-to-face management of patients. This study provides insight into public perception and impression of telemedicine in Hong Kong, specifically among the elderly who are the most vulnerable to COVID-19.\n\nMethodsFace-to-face surveys were conducted on elderly relatives of current medical students at the Chinese University of Hong Kong who were aged [&ge;] 60 years. The survey included socio-demographic details; past medical history; and concerns towards telemedicine use. Univariate and multivariable regression analyses were conducted to examine statistically significant associations. The primary outcomes are consideration of telemedicine use during: (1) a severe outbreak; and (2) after the COVID-19 pandemic.\n\nResults109 surveys were conducted. Multivariable regression analyses revealed that expectation of government subsidies for telemedicine services was the strongest common driver, and also the only positive independent predictors of telemedicine use for both during a severe outbreak, as well as after the COVID-19 pandemic. No negative independent predictors of telemedicine use during severe outbreak were found. Negative independent predictors of telemedicine use after the COVID-19 pandemic included old age, and living in the New Territories.\n\nConclusionsGovernment support such as telemedicine-specific subsidies will be crucial in promoting telemedicine use in Hong Kong both during a severe outbreak and after the current COVID-19 pandemic. Robust dissemination of information regarding the pros and cons of telemedicine towards the public, especially towards the elderly population, is warranted.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Alexander Hohl",
-        "author_inst": "Department of Geography, University of Utah"
+        "author_name": "Maxwell Chun Yin Choi",
+        "author_inst": "Faculty of Medicine, The Chinese University of Hong Kong"
+      },
+      {
+        "author_name": "Shing Him Chu",
+        "author_inst": "Faculty of Medicine, The Chinese University of Hong Kong"
+      },
+      {
+        "author_name": "Lok Lam Siu",
+        "author_inst": "Faculty of Medicine, The Chinese University of Hong Kong"
+      },
+      {
+        "author_name": "Anakin Gajy Tse",
+        "author_inst": "Faculty of Medicine, The Chinese University of Hong Kong"
       },
       {
-        "author_name": "Moongi Choi",
-        "author_inst": "Department of Geography, University of Utah"
+        "author_name": "Justin Che Yuen Wu",
+        "author_inst": "Division of Gastroenterology and Hepatology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong"
       },
       {
-        "author_name": "Richard Medina",
-        "author_inst": "Department of Geography, University of Utah"
+        "author_name": "Hong Fung",
+        "author_inst": "CUHK Medical Centre"
       },
       {
-        "author_name": "Neng Wan",
-        "author_inst": "Department of Geography, University of Utah"
+        "author_name": "Billy Chi Fai Chiu",
+        "author_inst": "CUHK Medical Centre"
       },
       {
-        "author_name": "Ming Wen",
-        "author_inst": "Department of Sociology, University of Utah"
+        "author_name": "Vincent Chung Tong Mok",
+        "author_inst": "Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong"
       }
     ],
     "version": "1",
@@ -619399,47 +622530,103 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2021.07.17.452576",
-    "rel_title": "Mutation-induced Changes in the Receptor-binding Interface of the SARS-CoV-2 Delta Variant B.1.617.2 and Implications for Immune Evasion",
+    "rel_doi": "10.1101/2021.07.16.452733",
+    "rel_title": "One mucosal administration of a live attenuated recombinant COVID-19 vaccine protects non-human primates from SARS-CoV-2",
     "rel_date": "2021-07-19",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.17.452576",
-    "rel_abs": "While the vaccination efforts against SARS-CoV-2 infections are ongoing worldwide, new genetic variants of the virus are emerging and spreading. Following the initial surges of the Alpha (B.1.1.7) and the Beta (B.1.351) variants, a more infectious Delta variant (B.1.617.2) is now surging, further deepening the health crises caused by the pandemic. The sharp rise in cases attributed to the Delta variant has made it especially disturbing and is a variant of concern. Fortunately, current vaccines offer protection against known variants of concern, including the Delta variant. However, the Delta variant has exhibited some ability to dodge the immune system as it is found that neutralizing antibodies from prior infections or vaccines are less receptive to binding with the Delta spike protein. Here, we investigated the structural changes caused by the mutations in the Delta variants receptor-binding interface and explored the effects on binding with the ACE2 receptor as well as with neutralizing antibodies. We find that the receptor-binding {beta}-loop-{beta} motif adopts an altered but stable conformation causing separation in some of the antibody binding epitopes. Our study shows reduced binding of neutralizing antibodies and provides a possible mechanism for the immune evasion exhibited by the Delta variant.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.16.452733",
+    "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 global pandemic. SARS-CoV-2 is an enveloped RNA virus that relies on its trimeric surface glycoprotein, spike, for entry into host cells. Here we describe the COVID-19 vaccine candidate MV-014-212, a live attenuated, recombinant human respiratory syncytial virus (RSV) expressing a chimeric SARS-CoV-2 spike as the only viral envelope protein. MV-014-212 was attenuated and immunogenic in African green monkeys (AGMs). One mucosal administration of MV-014-212 in AGMs protected against SARS-CoV-2 challenge, reducing by more than 200- fold the peak shedding of SARS-CoV-2 in the nose. MV-014-212 elicited mucosal immunity in the nose and neutralizing antibodies in serum that exhibited cross-neutralization against two virus variants of concern. Intranasally delivered, live attenuated vaccines such as MV-014-212 entail low-cost manufacturing suitable for global deployment. MV-014-212 is currently in phase 1 clinical trials as a single-dose intranasal COVID-19 vaccine.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Prabin Baral",
-        "author_inst": "Florida International University"
+        "author_name": "Mariana F. Tioni",
+        "author_inst": "Meissa Vaccines"
       },
       {
-        "author_name": "Nisha Bhattarai",
-        "author_inst": "Florida International University"
+        "author_name": "Robert Jordan",
+        "author_inst": "Bill & Melinda Gates Foundation, Seattle WA 98102"
       },
       {
-        "author_name": "Md Lokman Hossen",
-        "author_inst": "Florida International University"
+        "author_name": "Angie Silva Pena",
+        "author_inst": "Meissa Vaccines Inc, Redwood City, CA 94065"
       },
       {
-        "author_name": "Vitalii Stebliankin",
-        "author_inst": "Florida International University"
+        "author_name": "Aditya Garg",
+        "author_inst": "Meissa Vaccines Inc, Redwood City, CA 94065"
       },
       {
-        "author_name": "Bernard Gerstman",
-        "author_inst": "Florida International University"
+        "author_name": "Danlu Wu",
+        "author_inst": "Meissa Vaccines Inc, Redwood City, CA 94065"
       },
       {
-        "author_name": "Giri Narasimhan",
-        "author_inst": "Florida International University"
+        "author_name": "Shannon I. Phan",
+        "author_inst": "Meissa Vaccines Inc, Redwood City, CA 94065"
       },
       {
-        "author_name": "Prem P Chapagain",
-        "author_inst": "Florida International University"
+        "author_name": "Xing Cheng",
+        "author_inst": "Meissa Vaccines Inc, Redwood City, CA 94065"
+      },
+      {
+        "author_name": "Jack Greenhouse",
+        "author_inst": "BIOQUAL Inc., Rockville, MD 20850"
+      },
+      {
+        "author_name": "Tatyana Orekov",
+        "author_inst": "BIOQUAL Inc., Rockville, MD 20850"
+      },
+      {
+        "author_name": "Daniel Valentin",
+        "author_inst": "BIOQUAL Inc., Rockville, MD 20850"
+      },
+      {
+        "author_name": "Swagata Kar",
+        "author_inst": "BIOQUAL Inc., Rockville, MD 20850"
+      },
+      {
+        "author_name": "Laurent Pessaint",
+        "author_inst": "BIOQUAL Inc., Rockville, MD 20850"
+      },
+      {
+        "author_name": "Hanne Andersen",
+        "author_inst": "BIOQUAL Inc., Rockville, MD 20850"
+      },
+      {
+        "author_name": "Christopher C. Stobart",
+        "author_inst": "Department of Biological Sciences, Butler University, Indianapolis, IN 46208"
+      },
+      {
+        "author_name": "Melissa H. Bloodworth",
+        "author_inst": "Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232"
+      },
+      {
+        "author_name": "R. Stokes Peebles Jr.",
+        "author_inst": "Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232. Department of "
+      },
+      {
+        "author_name": "Yang Liu",
+        "author_inst": "Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston TX 77550"
+      },
+      {
+        "author_name": "Xuping Xie",
+        "author_inst": "Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston TX 77550"
+      },
+      {
+        "author_name": "Pei-Yong Shi",
+        "author_inst": "Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston TX 77550"
+      },
+      {
+        "author_name": "Martin L. Moore",
+        "author_inst": "Meissa Vaccines Inc, Redwood City, CA 94065"
+      },
+      {
+        "author_name": "Roderick S. Tang",
+        "author_inst": "Meissa Vaccines Inc, Redwood City, CA 94065"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "biophysics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.07.16.452709",
@@ -621369,27 +624556,43 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.07.11.21260318",
-    "rel_title": "Harnessing the Wisdom of the Crowd to Forecast Incident and Cumulative COVID-19 Mortality in the United States",
+    "rel_doi": "10.1101/2021.07.12.21258827",
+    "rel_title": "Olfactory detection of human odorant signatures in Covid patients by trained dogs",
     "rel_date": "2021-07-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.11.21260318",
-    "rel_abs": "BackgroundForecasting models have played a pivotal role in health policy decision making during the coronavirus disease-2019 (COVID-19) pandemic. A combined forecast from multiple models will be typically more accurate than an individual forecast, but there are few examples of studies of combined forecasts of COVID-19 data, focusing mainly on simple mean and median  ensembles and involving short forecast evaluation periods. We aimed to investigate the accuracy of different ways of combining probabilistic forecasts of weekly COVID-19 mortality data, including two weighted methods that we developed previously, on an extended dataset and new dataset, and evaluate over a period of 52 weeks.\n\nMethodsWe considered 95% interval and point forecasts of weekly incident and cumulative COVID-19 mortalities between 16 May 2020 and 8 May 2021 in multiple locations in the United States. We compared the accuracy of simple and more complex combining methods, as well as individual models.\n\nResultsThe average of the forecasts from the individual models was consistently more accurate than the average performance of these models (the mean combination), which provides a fundamental motivation for combining. Weighted combining performed well for both incident and cumulative mortalities, and for both interval and point forecasting. Our inverse score with tuning method was the most accurate overall. The median combination was a leading method in the last quarter for both mortalities, and it was consistently more accurate than the mean combination for point forecasting. For interval forecasts of cumulative mortality, the mean performed better than the median. The best performance of the leading individual model was in point forecasting.\n\nConclusionsCombining forecasts can improve the contribution of probabilistic forecasting to health policy decision making during epidemics, and, when there are sufficient historical data on forecast accuracy, weighted combining provides the most accurate method.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21258827",
+    "rel_abs": "The objective of the study was to verify the ability of specially trained dogs to detect the odour of people ill with COVID-19 and, at the same time, to use the outcome of this research in the future, whether in combatting a similar pandemic or in the field of medicine in the shape of a biological detector in uncovering different diseases. Our key assumption was that the disease will change the active odour signature of the individuals just like other diseases (TBC, malaria, tumours, etc.). The pilot study was conducted in two places, based on the same protocolar methods, and it included four specially trained detection dogs in total. For the first phase of the project, we obtained 156 positive and 72 negative odour samples primarily from a hospital. Each detection dog involved in the study was imprinted with the smell samples of Covid-positive people. The first experiment only involved two dogs. With the other two dogs, the phase of imprinting a specific smell was longer, possibly because these dogs were burdened with previous training. During a presentation of 100 randomised positive samples, the experimental dogs showed a 95% reliability rate. Data from this pilot study show that specially trained dogs are able to detect and identify the odour samples of people infected with the SARS-CoV-2 coronavirus.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Kathryn S Taylor",
-        "author_inst": "University of Oxford"
+        "author_name": "Lenka Vlachova",
+        "author_inst": "Search and Rescue Czech Republic"
       },
       {
-        "author_name": "James W Taylor",
-        "author_inst": "University of Oxford"
+        "author_name": "Gustav Hotovy",
+        "author_inst": "Search and Rescue Czech Republic"
+      },
+      {
+        "author_name": "Jiri Slechta",
+        "author_inst": "Search and Rescue Czech Republic"
+      },
+      {
+        "author_name": "Roman Vana",
+        "author_inst": "Search and Rescue Czech Republic"
+      },
+      {
+        "author_name": "Milena Vokralova",
+        "author_inst": "Search and Rescue Czech Republic"
+      },
+      {
+        "author_name": "Jiri Zeman",
+        "author_inst": "Search and Rescue Czech Republic"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.07.12.21260387",
@@ -622943,33 +626146,57 @@
     "category": "cardiovascular medicine"
   },
   {
-    "rel_doi": "10.1101/2021.07.12.21260345",
-    "rel_title": "Factors associated with transmission in COVID-19 outbreaks in long-term care facilities",
+    "rel_doi": "10.1101/2021.07.12.21260358",
+    "rel_title": "Increase in SARS-CoV-2 seroprevalence in healthy blood donors after the second wave of COVID-19 pandemic in South-Eastern Italy: evidence for asymptomatic young individuals as potential virus spreaders",
     "rel_date": "2021-07-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260345",
-    "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a disproportionate impact on residents in long-term care facilities (LTCFs). Through our experience and data from managing COVID-19 exposures and outbreaks in LTCFs in the Fraser Health region in British Columbia, Canada, we identified risk factors associated with outbreak severity to inform current outbreak management strategies and future pandemic preparedness planning efforts.\n\nMethodsWe used a retrospective cohort study design to evaluate the association between non-modifiable factors (facility building, organization level, and resident population characteristics), modifiable factors (assessments for infection prevention and control (IPC) and public health measures), and severity of COVID-19 outbreaks (attack rate) in LTCFs. We modelled the COVID-19 attack rates in LTCF outbreaks using negative binomial regression models.\n\nResultsFrom March 1, 2020 to January 10, 2021, a total of 145 exposures to at least one confirmed case of COVID-19 in 82 LTCFs occurred. For every item not met in the assessment tool, a 22% increase in the attack rate was observed (rate ratio 1.2 [95% CI 1.1 - 1.4]) after adjusting for other risk factors such as age of the facility, index case type (resident vs. staff) and proportion of single bed rooms.\n\nConclusionOur findings highlight the importance of assessing IPC and public health measures for outbreak management. They also demonstrate the important modifiable and non-modifiable risk factors associated with COVID-19 outbreaks in our jurisdiction. We hope these findings will inform ongoing outbreak management and future pandemic planning efforts.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260358",
+    "rel_abs": "BackgroundItaly has been the first among western countries to experience SARS-CoV-2 spread during which the southern regions were also heavily affected by the pandemic. To understand and monitor properly the evolution of COVID-19 pandemic, population based seroprevalence studies are a valid tool for the infection rates and effective prevalence of the SARS-CoV-2.\n\nAimIn this prospective study, we assessed the changes in SARS-CoV-2 seroprevalence rates among non-vaccinated blood donors in South-Eastern Italy over May 2020 to March 2021.\n\nMethods8,183 healthy blood donors referring to the Transfusion Center at the University Hospital \"Riuniti\" of Foggia (Italy) for blood donation in the period May 2020-March 2021 were tested for anti-SARS-CoV-2 antibodies by Ortho Clinical Diagnostics VITROS(R) 3600. None of the considered subjects had a diagnosed symptomatic COVID-19 infection.\n\nResultsOverall, 516 resulted positive for anti-SARS-CoV-2 IgG antibodies (6.3%, 95% CI, 0.03-0.15%), 387 (4.7%) were male and 129 (1.7%) female. A statistically significant increase in the seropositive population was found from May 2020 to March 2021 (Fishers p<0.001). The difference of the seroprevalence was significant in terms of age but not sex (2-sided p<0.05 for age; 2-sided p>0.05 for sex) in both groups.\n\nConclusionOur study shows a significant increase in the SARS-CoV-2 seroprevalence among blood donors and suggests a potential role of asymptomatic individuals in continuing the spread of the pandemic. These results may contribute to establishing containment measures and priorities in vaccine campaigns.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Rohit Vijh",
-        "author_inst": "School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada"
+        "author_name": "Francescopaolo Antonucci",
+        "author_inst": "Ospedali Riuniti University Hospital, Foggia, Italy"
       },
       {
-        "author_name": "Carmen H Ng",
-        "author_inst": "Office of the Medical Health Officer, Fraser Health"
+        "author_name": "jose Ramon fiore",
+        "author_inst": "University of Foggia, Foggi, iTALY"
       },
       {
-        "author_name": "Mehdi Shirmaleki",
-        "author_inst": "Office of the Medical Health Officer, Fraser Health"
+        "author_name": "lucia de feo",
+        "author_inst": "Ospedali Riuniti Foggia, Foggia, Italy"
       },
       {
-        "author_name": "Aamir Bharmal",
-        "author_inst": "Office of the Medical Health Officer, Fraser Health"
+        "author_name": "tommaso granato",
+        "author_inst": "ospedaliriunitifoggia, foggia, italy"
+      },
+      {
+        "author_name": "Mariantonietta Di Stefano",
+        "author_inst": "University of Foggia, Foggia, Italy"
+      },
+      {
+        "author_name": "giuseppina faleo",
+        "author_inst": "University of Foggia, Foggia, Italy"
+      },
+      {
+        "author_name": "ahmad mohamed farhan",
+        "author_inst": "University of Dammam, Dammam,, Saudi Arabia"
+      },
+      {
+        "author_name": "maurizio margaglione",
+        "author_inst": "University of Foggia, Foggia, Italy"
+      },
+      {
+        "author_name": "michele centra",
+        "author_inst": "Ospedali riuniti foggia, foggia, Italy"
+      },
+      {
+        "author_name": "teresa antonia santantonio",
+        "author_inst": "university of foggia, foggia, italy"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -625000,47 +628227,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.07.10.21260293",
-    "rel_title": "Plasma P-selectin is an early marker of thromboembolism in COVID-19",
+    "rel_doi": "10.1101/2021.07.11.21260148",
+    "rel_title": "ONLINE QUERIES AS A CRITERION FOR EVALUATION OF THE EPIDEMIOLOGICAL STATUS AND EFFECTIVENESS OF COVID-19 EPIDEMIC CONTROL MEASURES",
     "rel_date": "2021-07-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.10.21260293",
-    "rel_abs": "Coagulopathy and thromboembolism are known complications of SARS-CoV-2 infection. The mechanisms of COVID-19-associated hematologic complications involve endothelial cell and platelet dysfunction and have been intensively studied. We leveraged a prospectively collected acute COVID-19 biorepository to study the association of plasma levels of a comprehensive list of coagulation proteins with the occurrence of venous thromboembolic events (VTE). We included in our analysis 305 subjects with confirmed SARS-CoV-2 infection who presented to an urban Emergency Department with acute respiratory distress during the first COVID-19 surge in 2020; 13 (4.2%) were subsequently diagnosed with venous thromboembolism during hospitalization. Serial samples were obtained and assays were performed on two highly-multiplexed proteomic platforms. Nine coagulation proteins were differentially expressed in patients with thromboembolic events. P-selectin, a cell adhesion molecule on the surface of activated endothelial cells, displayed the strongest association with the diagnosis of VTE, independent of disease severity (p=0.0025). This supports the importance of endothelial activation in the mechanistic pathway of venous thromboembolism in COVID-19. P-selectin together with D-dimer upon hospital presentation provided better discriminative ability for VTE diagnosis than D-dimer alone.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.11.21260148",
+    "rel_abs": "Monitoring online queries can provide early and accurate information about the spread of COVID-19 in the population and about the effectiveness of COVID-19 epidemic control measures.\n\nThe purpose of the studyAssessment of significance of online queries regarding smell impairment to evaluate the epidemiological status and effectiveness of COVID-19 epidemic control measures.\n\nMaterials and methodsWeekly online queries from Yandex Russian users regarding smell impairment were analysed in regions and large cities of Russia from 16/3/2020 to 21/2/2021. A total of 81 regions of Russia and several large cities, such as Moscow, St. Petersburg, and Nizhny Novgorod, were included in the study.\n\nResultsA strong positive direct correlation (r>0.7) was found between the number of smell-related queries in Yandex new cases of COVID-19 in 59 out of 85 Russian regions and large cities (70%). During the \"first\" peak of COVID-19 incidence in Russia (April-May 2020), the increase in the number of smell-related queries outpaced the increase in the number of new cases by 1-2 weeks in 23 out of 59 regions of Russia. During the \"second\" peak of COVID-19 incidence in Russia (October-December 2020), the increase in the number of smell-related queries outpaced the increase in the number of new cases by 1-2 weeks in 36 regions of Russia, including Moscow. We also estimated the increase in the query/new case ratio during the \"second\" peak of incidence for 45 regions. It was found that the query/new case ratio increased by more than 100% in 24 regions. The regions where the increase in queries was more than 160% compared to new infection cases during the \"second\" peak of incidence demonstrated significantly higher search activity related to levofloxacin than the regions where the increase in queries was lower than 160% compared to the increase in new infection cases.\n\nConclusionThe sudden interest in smell impairment and growing frequency of online queries among the population can be used as an indicator of the spread of coronavirus infection among the population as well as for evaluation of the effectiveness of COVID-19 epidemic control measures.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Bank Gabor Fenyves",
-        "author_inst": "Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA, Department of Emergency Medicine, Semmelweis University, Budapest, Hungary"
+        "author_name": "Kuvat Momynaliev",
+        "author_inst": "Central Research Institute of Epidemiology of the Federal Service for Customers Rights Protection and Human Well-Being Surveillance, Moscow, Russia"
       },
       {
-        "author_name": "Arnav Mehta",
-        "author_inst": "Broad Institute of MIT and Harvard"
+        "author_name": "Dimash Khoroshun",
+        "author_inst": "Central Research Institute of Epidemiology of the Federal Service for Customers Rights Protection and Human Well-Being Surveillance, Moscow, Russia"
       },
       {
-        "author_name": "- MGH COVID-19 Collection & Processing Team",
-        "author_inst": "-"
-      },
-      {
-        "author_name": "Kyle Kays",
-        "author_inst": "Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA"
-      },
-      {
-        "author_name": "Marcia Goldberg",
-        "author_inst": "Department of Medicine, Harvard Medical School, Boston, MA, USA"
-      },
-      {
-        "author_name": "Nir Hacohen",
-        "author_inst": "Broad Institute and Massachusetts General Hospital"
-      },
-      {
-        "author_name": "Michael Filbin",
-        "author_inst": "Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA"
+        "author_name": "Vasiliy Akimkin",
+        "author_inst": "Central Research Institute of Epidemiology, Russian Federal Service for Supervision of Consumer Rights Protection and Human Well-Being, Moscow, Russia"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "cardiovascular medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.07.11.21260325",
@@ -626794,69 +630005,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.07.09.21260247",
-    "rel_title": "Spatiotemporal droplet dispersion measurements demonstrate face masks reduce risks from singing: results from the COvid aNd FacEmaSkS Study (CONFESS)",
+    "rel_doi": "10.1101/2021.07.12.21259864",
+    "rel_title": "Evidence of SARS-Cov-2-specific memory B cells six months after vaccination with BNT162b2 mRNA vaccine",
     "rel_date": "2021-07-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.09.21260247",
-    "rel_abs": "BackgroundCOVID-19 has restricted singing in communal worship. We sought to understand variations in droplet transmission and the impact of wearing face masks.\n\nMethodsUsing rapid laser planar imaging, we measured droplets while participants exhaled, said  hello or  snake, sang a note or  Happy Birthday, with and without surgical face masks. We measured mean velocity magnitude (MVM), time averaged droplet number (TADN) and maximum droplet number (MDN). Multilevel regression models were used.\n\nResultsIn 20 participants, sound intensity was 71 Decibels (dB) for speaking and 85 dB for singing (p<0.001). MVM was similar for all tasks with no clear hierarchy between vocal tasks or people and >85% reduction wearing face masks. Droplet transmission varied widely, particularly for singing. Masks decreased TADN by 99% (p<0.001) and MDN by 98% (p<0.001) for singing and 86-97% for other tasks. Masks reduced variance by up to 48%. When wearing a mask, neither singing task transmitted more droplets than exhaling.\n\nConclusionsWide variation exists for droplet production. This significantly reduced when wearing face masks. Singing during religious worship wearing a face mask appears as safe as exhaling or talking. This has implications for UK public health guidance during the COVID-19 pandemic.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21259864",
+    "rel_abs": "SARS-CoV-2 mRNA vaccines have demonstrated high efficacy and immunogenicity, but limited information is currently available on memory B cells generation and long-term persistence. Here, we investigated Spike-specific memory B cells and humoral responses in 145 subjects, up to six months after the BNT162b2 vaccine (Comirnaty) administration. Spike-specific antibody titers peaked 7 days after the second dose and significant titers and neutralizing activity were still observed after six months, despite a progressive decline over time. Concomitant to antibody reduction, Spike-specific memory B cells, mostly IgG class-switched, increased in blood of vaccinees and persisted six months after vaccination. Following in vitro restimulation, circulating memory B cells reactivated and produced Spike-specific antibodies. A high frequency of Spike-specific IgG+ plasmablasts, identified by computational analysis 7 days after boost, positively correlated with the generation of IgG+ memory B cells at six months.\n\nThese data demonstrate that mRNA BNT162b2 vaccine elicits strong B cell immunity with Spike-specific memory B cells that still persist six months after vaccination, playing a crucial role for rapid response to SARS-CoV-2 virus encounter.\n\nOne Sentence SummarymRNA BNT162b2 vaccine elicits persistent spike-specific memory B cells crucial for rapid response to SARS-CoV-2 virus encounter",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Kai Man Alexander Ho",
-        "author_inst": "University College London"
+        "author_name": "Annalisa Ciabattini",
+        "author_inst": "Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "Hywel Davies",
-        "author_inst": "University College London"
+        "author_name": "Gabiria Pastore",
+        "author_inst": "Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "Ruth Epstein",
-        "author_inst": "University College London Hospitals NHS Foundation Trust"
+        "author_name": "Fabio Fiorino",
+        "author_inst": "Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "Paul Bassett",
-        "author_inst": "Statsconsultancy Ltd"
+        "author_name": "Jacopo Polvere",
+        "author_inst": "Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "Aine Hogan",
-        "author_inst": "University College London"
+        "author_name": "Simone Lucchesi",
+        "author_inst": "Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "Yusuf Kabir",
-        "author_inst": "University College London"
+        "author_name": "Elena Pettini",
+        "author_inst": "Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "John Rubin",
-        "author_inst": "University College London Hospitals NHS Foundation Trust"
+        "author_name": "Stefano Auddino",
+        "author_inst": "Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "Gee Yen Shin",
-        "author_inst": "University College London Hospitals NHS Foundation Trust"
+        "author_name": "Ilaria Rancan",
+        "author_inst": "Department of Medical Biotechnologies, University of Siena, Siena, Italy; Department of Medical Sciences, Infectious and Tropical Diseases Unit, University Hosp"
       },
       {
-        "author_name": "Jonathan Reid",
-        "author_inst": "University of Bristol"
+        "author_name": "Miriam Durante",
+        "author_inst": "Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       },
       {
-        "author_name": "Ryo Torii",
-        "author_inst": "University College London"
+        "author_name": "Michele Miscia",
+        "author_inst": "Department of Medical Biotechnologies, University of Siena; Siena, Italy; Department of Medical Sciences, Infectious and Tropical Diseases Unit, University Hosp"
       },
       {
-        "author_name": "Manish Tiwari",
-        "author_inst": "University College London"
+        "author_name": "Barbara Rossetti",
+        "author_inst": "Department of Medical Sciences, Infectious and Tropical Diseases Unit, University Hospital of Siena; Siena, Italy"
       },
       {
-        "author_name": "Ramanarayanan Balachandran",
-        "author_inst": "University College London"
+        "author_name": "Massimiliano Fabbiani",
+        "author_inst": "Department of Medical Sciences, Infectious and Tropical Diseases Unit, University Hospital of Siena; Siena, Italy"
       },
       {
-        "author_name": "Laurence Lovat",
-        "author_inst": "University College London"
+        "author_name": "Francesca Montagnani",
+        "author_inst": "Department of Medical Biotechnologies, University of Siena; Siena, Italy; Department of Medical Sciences, Infectious and Tropical Diseases Unit, University Hosp"
+      },
+      {
+        "author_name": "Donata Medaglini",
+        "author_inst": "Laboratory of Molecular Microbiology and Biotechnology, Department of Medical Biotechnologies, University of Siena; Siena, Italy"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -628664,55 +631879,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.07.11.451855",
-    "rel_title": "The SARS-CoV-2 spike reversibly samples an open-trimer conformation exposing novel epitopes",
+    "rel_doi": "10.1101/2021.07.08.21259912",
+    "rel_title": "Efficacy and safety of Andrographis paniculata extract in patients with mild COVID-19: A randomized controlled trial",
     "rel_date": "2021-07-11",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.11.451855",
-    "rel_abs": "Current COVID-19 vaccines and many clinical diagnostics are based on the structure and function of the SARS-CoV-2 spike ectodomain. Using hydrogen deuterium exchange mass spectrometry, we have uncovered that, in addition to the prefusion structure determined by cryo-EM, this protein adopts an alternative conformation that interconverts slowly with the canonical prefusion structure. This new conformation--an open trimer-- contains easily accessible RBDs. It exposes the conserved trimer interface buried in the prefusion conformation, thus exposing potential epitopes for pan-coronavirus antibody and ligand recognition. The population of this state and kinetics of interconversion are modulated by temperature, receptor binding, antibody binding, and sequence variants observed in the natural population. Knowledge of the structure and populations of this conformation will help improve existing diagnostics, therapeutics, and vaccines.\n\nOne Sentence SummaryAn alternative conformation of SARS-CoV-2 spike ectodomain modulated by temperature, binding, and sequence variants.",
-    "rel_num_authors": 9,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.08.21259912",
+    "rel_abs": "ObjectivesTo assess the efficacy and safety of Andrographis paniculata extract (APE) in adults with mild COVID-19.\n\nMethodsSixty-three adults aged 18-60 years, without co-morbidity, with laboratory-confirmed mild COVID-19, were randomized 1:1 to receive APE (60 mg andrographolide, t.i.d, for 5 days) or placebo within 24 hours after admission, plus standard supportive care. The outcomes were clinical recovery rates by Day 5 using self-assessment scores, pneumonia by chest X-rays, nasopharyngeal SARS-CoV-2 detection by rRT-PCR on Day 5, changes of serum CRP levels, and adverse drug reactions. Chest X-rays and blood tests for CRP, liver and renal function, were performed on Days 1, 3, and 5.\n\nResultsBaseline characteristics of patients in the APE-treatment (n=29) and placebo-control (n=28) groups were comparable. None had self-assessment scores showing complete clinical recovery by Day 5. Pneumonia occurred in 0/29 (0%) versus 3/28 (10.7%), (p=0.112). On Day 5, patients with SARS-CoV-2 detection were 10/29 (34.5%) versus 16/28 (57.1%), (p=0.086); patients with CRP >10 mg/L were 0/29 (0%) versus 5/28 (17.9%), (p=0.023), for APE-treatment and placebo-control groups, respectively. All three patients with pneumonia had substantially rising serum CRP; and high CRP levels on Day 5. None had evidence of hematologic, hepatic or renal impairment.\n\nConclusionEven though the study was limited by small sample size, our findings suggested promising efficacy and safety of the APE-treatment regimen in adults with mild COVID-19. Further studies, with adequate power to assure these findings, are required.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Shawn M Costello",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Kulthanit Wanaratna",
+        "author_inst": "Thai Traditional Medicines Research Institute"
       },
       {
-        "author_name": "Sophie R Shoemaker",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Pornvimol Leethong",
+        "author_inst": "Samutprakarn Hospital, Ministry of Public Heath, Thailand"
       },
       {
-        "author_name": "Helen T Hobbs",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Nitapha Inchai",
+        "author_inst": "Department of Thai Traditional and Alternative Medicine, Ministry of Public Heath, Thailand"
       },
       {
-        "author_name": "Annalee W Nguyen",
-        "author_inst": "University of Texas at Austin"
+        "author_name": "Wararath Chueawiang",
+        "author_inst": "Department of Thai Traditional and Alternative Medicine, Ministry of Public Heath, Thailand"
       },
       {
-        "author_name": "Ching-Lin Hsieh",
-        "author_inst": "University of Texas at Austin"
+        "author_name": "Pantitra Sriraksa",
+        "author_inst": "Department of Thai Traditional and Alternative Medicine, Ministry of Public Heath, Thailand"
       },
       {
-        "author_name": "Jennifer A Maynard",
-        "author_inst": "University of Texas at Austin"
-      },
-      {
-        "author_name": "Jason S McLellan",
-        "author_inst": "University of Texas at Austin"
-      },
-      {
-        "author_name": "John E Pak",
-        "author_inst": "Chan Zuckerberg Biohub"
+        "author_name": "Anutida Tabmee",
+        "author_inst": "Department of Thai Traditional and Alternative Medicine, Ministry of Public Heath, Thailand"
       },
       {
-        "author_name": "Susan Marqusee",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Sayomporn Sirinavin",
+        "author_inst": "Division of Infectious Diseases, Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Thailand"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "biophysics"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.07.06.21260086",
@@ -630358,31 +633565,83 @@
     "category": "neuroscience"
   },
   {
-    "rel_doi": "10.1101/2021.07.06.21260112",
-    "rel_title": "COVID-19 Due to Wild-Type SARS-CoV-2 More Prevalent in Adolescents and Youth than in Older Adults Based on 19 US States in Fall 2020 Prior to Vaccine Availability",
+    "rel_doi": "10.1101/2021.06.30.21259763",
+    "rel_title": "Which children and young people are at higher risk of severe disease and death after SARS-CoV-2 infection: a systematic review and individual patient meta-analysis",
     "rel_date": "2021-07-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21260112",
-    "rel_abs": "PURPOSEIn a prior study, we examined data from six US states during Summer 2020, and found that prevalence of COVID-19 for adolescents and youth was significantly greater than for older adults (p<.00001) as was a prevalence-related measure: Number of cases observed / Number of cases expected (p<.005). We now extended our study to more states in Fall 2020 to confirm the prevalence relationships we found previously. Vaccines were still not available as of Fall 2020. Presumably, the SARS-CoV-2 strain circulating at the time was the wild-type lineage since no variants were reported in the US until the end of December 2020.\n\nMETHODSWe examined data from 19 U.S. states experiencing surges in cases to determine prevalence of COVID-19, and a prevalence-related measure: [Number of cases observed in a given age group] / [Number of cases expected in the age group based on population demographics].\n\nRESULTSIn 16 of the 19 states, we found that: (1) prevalence of COVID-19 for adolescents and youth was significantly greater than for older adults (p-values ranged from p<0.00001 to p = 0.0175; (2) the ratio of cases observed to cases expected was significantly greater in adolescents and youth than in older adults (p-values ranging from p< 0.00001 to p = 0.004).\n\nCONCLUSIONSOur results are consistent with our previous study in Summer 2020. The finding of lower prevalence in older adults cannot be attributed to access to vaccination since our data are from Fall 2020 when vaccinations were not yet available. Our findings with the SARS-CoV-2 wild-type strain are consistent with the findings currently being reported in the UK for the delta variant. In both studies, prevalence in adolescents and youth exceeded that in older adults. The UK findings are more pronounced perhaps because that study transpired following months of vaccinations of older adults whereas ours occurred before vaccinations were available.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.30.21259763",
+    "rel_abs": "BackgroundWe aimed to use individual patient data to describe pre-existing factors associated with severe disease, primarily admission to critical care, and death secondary to SARS-CoV-2 infection in children and young people (CYP) in hospital.\n\nMethodsWe searched Pubmed, European PMC, Medline and Embase for case series and cohort studies that included all CYP admitted to hospital with [&ge;]30 CYP with SARS-CoV-2 or [&ge;]5 CYP with PIMS-TS or MIS-C. Eligible studies contained 1) details of age, sex, ethnicity or co-morbidities, and 2) an outcome which included admission to critical care, mechanical invasive ventilation, cardiovascular support, or death. Studies reporting outcomes in more restricted grouping of co-morbidities were eligible for narrative review. Authors of eligible studies were approached for individual patient data (IPD). We used random effects meta-analyses for aggregate study-level data and multilevel mixed effect models for IPD data to examine risk factors (age, sex, comorbidities) associated with admission to critical care and death. Data shown are odds ratios and 95% confidence intervals (CI).\n\nFindings81 studies were included, 57 in the meta-analysis (of which 22 provided IPD) and 26 in the narrative synthesis. Most studies had an element of bias in their design or reporting. Sex was not associated with critical care or death. Compared with CYP aged 1-4 years, infants had increased odds of admission to critical care (OR 1.63 (95% CI 1.40-1.90)) and death (OR 2.08 (1.57-2.86)). Odds of death were increased amongst CYP over 10 years (10-14 years OR 2.15 (1.54-2.98); >14 years OR 2.15 (1.61-2.88)).\n\nNumber of comorbid conditions was associated with increased odds of admission to critical care and death for COVID-19 in a dose-related fashion. For critical care admission odds ratios were: 1 comorbidity 1.49 (1.45-1.53); 2 comorbidities 2.58 (2.41-2.75); [&ge;]3 comorbidities 2.97 (2.04-4.32), and for death: 1 comorbidity 2.15 (1.98-2.34); 2 comorbidities 4.63 (4.54-4.74); [&ge;]3 co-morbidities 4.98 (3.78-6.65). Odds of admission to critical care were increased for all co-morbidities apart from asthma (0.92 (0.91-0.94)) and malignancy (0.85 (0.17-4.21)) with an increased odds of death in all co-morbidities considered apart from asthma. Neurological and cardiac comorbidities were associated with the greatest increase in odds of severe disease or death. Obesity increased the odds of severe disease and death independently of other comorbidities.\n\nInterpretationHospitalised CYP at greatest vulnerability of severe disease or death from SARS-CoV-2 infection are infants, teenagers, those with cardiac or neurological conditions, or 2 or more comorbid conditions, and those who are obese. These groups should be considered higher priority for vaccination and for protective shielding when appropriate. Whilst odds ratios were high, the absolute increase in risk for most comorbidities was small compared to children without underlying conditions.\n\nFundingRH is in receipt of a funded fellowship from Kidney Research UK. JW is in receipt of a Medical Research Council Fellowship.\n\nPutting Research Into ContextO_ST_ABSEvidence before this studyC_ST_ABSThe risk factors for severe disease following SARS-CoV-2 infection in adults has been extensively studied and reported, with good evidence that increasing age, non-white ethnicity, male gender and co-morbidities increase the risk. SARS-CoV-2 infection in children and young people (CYP) infrequently results in hospital admission and very rarely causes severe disease and death, making it difficult to discern the impact of a range of potential risk factors for severe disease in the many small to moderate sized published studies. More recent larger publications have aimed to address this question in specific populations but the global experience has not been described. We searched Pubmed, European PMC, Medline and Embase from the 1st January 2020 to 21st May 2021 for case series and cohort studies that included all CYP admitted to hospital with 30 children with reverse transcriptase-PCR confirmed SARS-CoV-2 or 5 CYP defined as having PIMS-TS or MIS-C. 57 studies met the eligibility criteria for meta-analysis.\n\nAdded value of this studyTo our knowledge, this is the first meta-analysis to use individual patient data to compare the odds and risk of critical care admission and death in CYP with COVID-19 and PIMS-TS. We find that the odds of severe disease in hospitalised children is increased in those with multiple co-morbidities, cardiac and neurological co-morbidities and those who are obese. However, the additional risk compared to children without co-morbidity is small.\n\nImplications of all the available evidenceSevere COVID-19 and PIMS-TS, whilst rare, can occur in CYP. We have identified pre-existing risk factors for severe disease after SARS-CoV-2 and recommend that those with co-orbidities which place them in the highest risk groups are prioritised for vaccination.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Barbara T Rumain",
-        "author_inst": "New York Medical College"
+        "author_name": "Rachel Harwood",
+        "author_inst": "Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool"
       },
       {
-        "author_name": "Moshe Schneiderman",
-        "author_inst": "SUNY Downstate College of Medicine"
+        "author_name": "Helen Yan",
+        "author_inst": "Medical School, UCL, London"
       },
       {
-        "author_name": "Allan Geliebter",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Nish Talawila Da Camara",
+        "author_inst": "Royal College of Paediatrics and Child Health, London"
+      },
+      {
+        "author_name": "Clare Smith",
+        "author_inst": "NHS England and NHS Improvement, London"
+      },
+      {
+        "author_name": "Joseph Ward",
+        "author_inst": "UCL Great Ormond St. Institute of Child Health, London"
+      },
+      {
+        "author_name": "Catrin Tudur-Smith",
+        "author_inst": "Department of Statistics, University of Liverpool, Liverpool"
+      },
+      {
+        "author_name": "Michael Linney",
+        "author_inst": "University Hospitals Sussex NHS Foundation Trust"
+      },
+      {
+        "author_name": "Matthew Clark",
+        "author_inst": "NHS England and NHS Improvement, London"
+      },
+      {
+        "author_name": "Elizabeth Whittaker",
+        "author_inst": "Imperial College London, London"
+      },
+      {
+        "author_name": "Defne Saatci",
+        "author_inst": "Imperial College London, London"
+      },
+      {
+        "author_name": "Peter J Davis",
+        "author_inst": "Paediatric Intensive Care Unit, Bristol Royal Hospital for Children, Bristol"
+      },
+      {
+        "author_name": "Karen Luyt",
+        "author_inst": "Bristol Medical School, University of Bristol, Bristol"
+      },
+      {
+        "author_name": "Elizabeth S Draper",
+        "author_inst": "PICANet, Department of Health Sciences, University of Leicester, Leicester"
+      },
+      {
+        "author_name": "Simon Kenny",
+        "author_inst": "NHS England and NHS Improvement, London"
+      },
+      {
+        "author_name": "Lorna K Fraser",
+        "author_inst": "Martin House Research Centre, Dept of Health Sciences, University of York"
+      },
+      {
+        "author_name": "Russell M Viner",
+        "author_inst": "UCL Great Ormond St. Institute of Child Health, London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2021.07.07.21260156",
@@ -632196,89 +635455,249 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.07.06.21259473",
-    "rel_title": "Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar",
+    "rel_doi": "10.1101/2021.07.08.21259776",
+    "rel_title": "Effectiveness of SARS-CoV-2 mRNA Vaccines for Preventing Covid-19 Hospitalizations in the United States",
     "rel_date": "2021-07-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21259473",
-    "rel_abs": "As the national reference laboratory for febrile illness in Madagascar, we processed samples from the first epidemic wave of COVID-19, between March and September 2020. We fit generalized additive models to cycle threshold (Ct) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-Ct value infections temporally coincident with peak epidemic growth rates estimated in real time from publicly-reported incidence data and retrospectively from our own laboratory testing data across three administrative regions. We additionally demonstrate a statistically significant effect of duration of time since infection onset on Ct value, suggesting that Ct value can be used as a biomarker of the stage at which an individual is sampled in the course of an infection trajectory. As an extension, the population-level Ct distribution at a given timepoint can be used to estimate population-level epidemiological dynamics. We illustrate this concept by adopting a recently-developed, nested modeling approach, embedding a within-host viral kinetics model within a population-level Susceptible-Exposed-Infectious-Recovered (SEIR) framework, to mechanistically estimate epidemic growth rates from cross-sectional Ct distributions across three regions in Madagascar. We find that Ct-derived epidemic growth estimates slightly precede those derived from incidence data across the first epidemic wave, suggesting delays in surveillance and case reporting. Our findings indicate that public reporting of Ct values could offer an important resource for epidemiological inference in low surveillance settings, enabling forecasts of impending incidence peaks in regions with limited case reporting.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.08.21259776",
+    "rel_abs": "BackgroundAs SARS-CoV-2 vaccination coverage increases in the United States (US), there is a need to understand the real-world effectiveness against severe Covid-19 and among people at increased risk for poor outcomes.\n\nMethodsIn a multicenter case-control analysis of US adults hospitalized March 11 - May 5, 2021, we evaluated vaccine effectiveness to prevent Covid-19 hospitalizations by comparing odds of prior vaccination with an mRNA vaccine (Pfizer-BioNTech or Moderna) between cases hospitalized with Covid-19 and hospital-based controls who tested negative for SARS-CoV-2.\n\nResultsAmong 1210 participants, median age was 58 years, 22.8% were Black, 13.8% were Hispanic, and 20.6% had immunosuppression. SARS-CoV-2 lineage B.1.1.7 was most common variant (59.7% of sequenced viruses). Full vaccination (receipt of two vaccine doses [&ge;]14 days before illness onset) had been received by 45/590 (7.6%) cases and 215/620 (34.7%) controls. Overall vaccine effectiveness was 86.9% (95% CI: 80.4 to 91.2%). Vaccine effectiveness was similar for Pfizer-BioNTech and Moderna vaccines, and highest in adults aged 18-49 years (97.3%; 95% CI: 78.9 to 99.7%). Among 45 patients with vaccine-breakthrough Covid hospitalizations, 44 (97.8%) were [&ge;]50 years old and 20 (44.4%) had immunosuppression. Vaccine effectiveness was lower among patients with immunosuppression (59.2%; 95% CI: 11.9 to 81.1%) than without immunosuppression (91.3%; 95% CI: 85.5 to 94.7%).\n\nConclusionDuring March-May 2021, SARS-CoV-2 mRNA vaccines were highly effective for preventing Covid-19 hospitalizations among US adults. SARS-CoV-2 vaccination was beneficial for patients with immunosuppression, but effectiveness was lower in the immunosuppressed population.",
+    "rel_num_authors": 58,
     "rel_authors": [
       {
-        "author_name": "Soa Fy Andriamandimby",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Mark W. Tenforde",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Cara E. Brook",
-        "author_inst": "Cara Brook"
+        "author_name": "Manish M. Patel",
+        "author_inst": "US Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Norosoa H Razanajatovo",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Adit A. Ginde",
+        "author_inst": "University of Colorado School of Medicine"
       },
       {
-        "author_name": "Jean-Marius Rakotondramanga",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "David J. Douin",
+        "author_inst": "University of Colorado School of Medicine"
       },
       {
-        "author_name": "Fidisoa Rasambainarivo",
-        "author_inst": "Princeton University"
+        "author_name": "H. Keipp Talbot",
+        "author_inst": "Vanderbilt University Medical Center"
       },
       {
-        "author_name": "Vaomalala Raharimanga",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Jonathan D. Casey",
+        "author_inst": "Vanderbilt University Medical Center"
       },
       {
-        "author_name": "Iony M. Razanajatovo",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Nicholas M. Mohr",
+        "author_inst": "University of Iowa"
       },
       {
-        "author_name": "Reziky Mangahasimbola",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Anne Zepeski",
+        "author_inst": "University of Iowa"
       },
       {
-        "author_name": "Richter L Razafindratsimandresy",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Manjusha Gaglani",
+        "author_inst": "Baylor Scott and White Health, Texas A&M University College of Medicine"
       },
       {
-        "author_name": "Santatra Randrianarisoa",
-        "author_inst": "University of Antananarivo"
+        "author_name": "Tresa McNeal",
+        "author_inst": "Baylor Scott and White Health, Texas A&M University College of Medicine"
       },
       {
-        "author_name": "Barivola Bernardson",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Shekhar Ghamande",
+        "author_inst": "Baylor Scott and White Health, Texas A&M University College of Medicine"
       },
       {
-        "author_name": "Joelinotahina H Rabarison",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Nathan I. Shapiro",
+        "author_inst": "Beth Israel Deaconess Medical Center"
       },
       {
-        "author_name": "Mirella Randrianarisoa",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Kevin W. Gibbs",
+        "author_inst": "Wake Forest School of Medicine"
       },
       {
-        "author_name": "Frederick S Nasolo",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "D. Clark Files",
+        "author_inst": "Wake Forest School of Medicine"
       },
       {
-        "author_name": "Roger M Rabetombosoa",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "David N. Hager",
+        "author_inst": "Johns Hopkins University School of Medicine"
       },
       {
-        "author_name": "Rindra V Randremanana",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Arber Shehu",
+        "author_inst": "Johns Hopkins University School of Medicine"
       },
       {
-        "author_name": "Jean-Michel Heraud",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Matthew E. Prekker",
+        "author_inst": "Hennepin County Medical Center"
       },
       {
-        "author_name": "Philippe G Dussart",
-        "author_inst": "Institut Pasteur de Madagascar"
+        "author_name": "Heidi L. Erickson",
+        "author_inst": "Hennepin County Medical Center"
+      },
+      {
+        "author_name": "Matthew C. Exline",
+        "author_inst": "The Ohio State University"
+      },
+      {
+        "author_name": "Michelle N. Gong",
+        "author_inst": "Montefiore Health System, Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Amira Mohamed",
+        "author_inst": "Montefiore Health System, Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Daniel J. Henning",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "Jay S. Steingrub",
+        "author_inst": "Baystate Medical Center"
+      },
+      {
+        "author_name": "Ithan D. Peltan",
+        "author_inst": "Intermountain Medical Center"
+      },
+      {
+        "author_name": "Samuel M. Brown",
+        "author_inst": "Intermountain Medical Center"
+      },
+      {
+        "author_name": "Emily T. Martin",
+        "author_inst": "University of Michigan"
+      },
+      {
+        "author_name": "Arnold S. Monto",
+        "author_inst": "University of Michigan"
+      },
+      {
+        "author_name": "Akram Khan",
+        "author_inst": "Oregon Health and Sciences University"
+      },
+      {
+        "author_name": "C. Terri Hough",
+        "author_inst": "Oregon Health and Sciences University"
+      },
+      {
+        "author_name": "Laurence Busse",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Caitlin C. ten Lohuis",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Abhijit Duggal",
+        "author_inst": "Cleveland Clinic"
+      },
+      {
+        "author_name": "Jennifer G. Wilson",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Alexandra June Gordon",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Nida Qadir",
+        "author_inst": "University of California-Los Angeles"
+      },
+      {
+        "author_name": "Steven Y. Chang",
+        "author_inst": "University of California-Los Angeles"
+      },
+      {
+        "author_name": "Christopher Mallow",
+        "author_inst": "University of Miami"
+      },
+      {
+        "author_name": "Hayley B. Gershengorn",
+        "author_inst": "University of Miami"
+      },
+      {
+        "author_name": "Hilary M. Babcock",
+        "author_inst": "Washington University"
+      },
+      {
+        "author_name": "Jennie H. Kwon",
+        "author_inst": "Washington University"
+      },
+      {
+        "author_name": "Natasha Halasa",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "James D. Chappell",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Adam S. Lauring",
+        "author_inst": "University of Michigan"
+      },
+      {
+        "author_name": "Carlos G. Grijalva",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Todd W. Rice",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Ian D. Jones",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "William B. Stubblefield",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Adrienne Baughman",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Kelsey N. Womack",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Christopher J. Lindsell",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Kimerly W. Hart",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Yuwei Zhu",
+        "author_inst": "Vanderbilt University Medical Center"
+      },
+      {
+        "author_name": "Samantha M. Olson",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Meagan Stephenson",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Stephanie J. Schrag",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Miwako Kobayashi",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Jennifer R. Verani",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Wesley H. Self",
+        "author_inst": "Vanderbilt University Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -634050,67 +637469,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.07.03.21259953",
-    "rel_title": "High resolution linear epitope mapping of the receptor binding domain of SARS-CoV-2 spike protein in COVID-19 mRNA vaccine recipients.",
+    "rel_doi": "10.1101/2021.07.03.21254541",
+    "rel_title": "Anticoagulants and Antiplatelets in COVID-19: Impact on Survival and Thromboembolism Development",
     "rel_date": "2021-07-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21259953",
-    "rel_abs": "The prompt rollout of the coronavirus disease (COVID-19) messenger RNA (mRNA) vaccine is facilitating population immunity, which shall become more dominant than natural infection-induced immunity. At the beginning of the vaccine era, understanding the epitope profiles of vaccine-elicited antibodies will be the first step in assessing functionality of vaccine-induced immunity. In this study, the high-resolution linear epitope profiles of Pfizer-BioNTech COVID-19 mRNA vaccine recipients and COVID-19 patients were delineated by using microarrays mapped with overlapping peptides of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. The vaccine-induced antibodies targeting RBD had broader distribution across the RBD than that induced by the natural infection. Thus, relatively lower neutralizability was observed when a half-maximal neutralization titer measured in vitro by live virus neutralization assays was normalized to a total anti-RBD IgG titer. However, mutation panel assays targeting the SARS-CoV-2 variants of concern have shown that the vaccine-induced epitope variety, rich in breadth, may grant resistance against future viral evolutionary escapes, serving as an advantage of vaccine-induced immunity.\n\nImportanceEstablishing vaccine-based population immunity has been the key factor in attaining herd protection. Thanks to expedited worldwide research efforts, the potency of messenger RNA vaccines against the coronavirus disease 2019 (COVID-19) is now incontestable. The next debate is regarding the coverage of SARS-CoV-2 variants. At the beginning of this vaccine era, it is of importance to describe the similarities and differences between the immune responses of COVID-19 vaccine recipients and naturally infected individuals. In this study, we demonstrated that the antibody profiles of vaccine recipients are richer in variety, targeting a key protein of the invading virus, than those of naturally infected individuals. Yet vaccine-elicited antibodies included more non-neutralizing antibodies than infection-elicited, their breadth in antibody variations suggested possible resilience against future SARS-CoV-2 variants. The antibody profile achieved by vaccinations in naive individuals pose important insight into the first step towards vaccine-based population immunity.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21254541",
+    "rel_abs": "BackgroundHigher rates of venous and arterial thromboembolism have been noted in coronavirus disease-2019 (COVID-19). There has been limited research on the impact of anticoagulant and antiplatelet choice in COVID-19.\n\nMethodsThis was a single-centre retrospective cohort study of 933 patients with COVID-19 infection presenting between 01/02/2020 and 31/05/2020. Survival time at 90 days post-diagnosis and thromboembolism development were the measured outcomes.\n\nResultsOf 933 total patients, mean age was 68 years and 54.4% were male. 297 (31.8%) did not survive at 90 days. A Cox proportional hazards model analysis found no statistically significant relationship between anticoagulant or antiplatelet choice and survival (p<0.05).\n\n57 (6.3%) developed thromboembolism. Antiplatelet choice was not shown to have a statistically significant relationship with thromboembolism development. Warfarin and direct oral anticoagulant (DOAC) use did not have a statistically significant impact on thromboembolism development (p<0.05). Therapeutic low-molecular-weight heparin (LMWH) use was associated with increased thromboembolism risk (Odds ratio = 14.327, 95% CI 1.904 - 107.811, p = 0.010).\n\nConclusionsAntiplatelet choice was shown to have no impact on survival or thromboembolism development in COVID-19. Anticoagulant choice did not impact survival or thromboembolism development, aside from LMWH. Therapeutic LMWH use was associated with increased risk of thromboembolism. However, it should be noted that the sample size for patients using therapeutic LMWH was small (n=4), and there may be confounding variables affecting both LMWH use and thromboembolism development. These findings should be repeated with a larger sample of patients using therapeutic LMWH with additional adjustment for cofounding variables.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Yuko Nitahara",
-        "author_inst": "Osaka City University"
-      },
-      {
-        "author_name": "Yu Nakagama",
-        "author_inst": "Osaka City University"
-      },
-      {
-        "author_name": "Natsuko Kaku",
-        "author_inst": "Osaka City University"
-      },
-      {
-        "author_name": "Katherine Candray",
-        "author_inst": "Osaka City University"
-      },
-      {
-        "author_name": "Yu Michimuko",
-        "author_inst": "Osaka City University"
-      },
-      {
-        "author_name": "Evariste Tshibangu-Kabamba",
-        "author_inst": "Osaka City University"
-      },
-      {
-        "author_name": "Akira Kaneko",
-        "author_inst": "Osaka City University"
-      },
-      {
-        "author_name": "Hiromasa Yamamoto",
-        "author_inst": "Osaka City University"
+        "author_name": "Thomas Salmon",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
       },
       {
-        "author_name": "Yasumitsu Mizobata",
-        "author_inst": "Osaka City University"
+        "author_name": "Mitchell Titley",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
       },
       {
-        "author_name": "Hiroshi Kakeya",
-        "author_inst": "Osaka City University"
+        "author_name": "Zaid Noori",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
       },
       {
-        "author_name": "Mayo Yasugi",
-        "author_inst": "Osaka Prefecture University"
+        "author_name": "Mark Crosby",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
       },
       {
-        "author_name": "Yasutoshi Kido",
-        "author_inst": "Osaka City University"
+        "author_name": "Rajiv Sankaranarayanan",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "cardiovascular medicine"
   },
   {
     "rel_doi": "10.1101/2021.07.07.21260121",
@@ -635768,25 +639159,53 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.07.05.21260050",
-    "rel_title": "Progressive Increase in Virulence of Novel SARS-CoV-2 Variants in Ontario, Canada, February to June, 2021",
+    "rel_doi": "10.1101/2021.07.06.21260055",
+    "rel_title": "Critical timing for triggering public health interventions to prevent COVID-19 resurgence: a mathematical modelling study",
     "rel_date": "2021-07-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.05.21260050",
-    "rel_abs": "BackgroundThe period from February to June 2021 was one during which initial wild-type SARS-CoV-2 strains were supplanted in Ontario, Canada, first by variants of concern (VOC) with the N501Y mutation (Alpha/B1.1.17, Beta/B.1.351 and Gamma/P.1 variants), and then by the Delta/B.1.617 variant. The increased transmissibility of these VOCs has been documented but data for increased virulence is limited. We used Ontarios COVID-19 case data to evaluate the virulence of these VOCs compared to non-VOC SARS-CoV-2 infections, as measured by risk of hospitalization, intensive care unit (ICU) admission, and death.\n\nMethodsWe created a retrospective cohort of people in Ontario testing positive for SARS-CoV-2 and screened for VOCs, with dates of test report between February 7 and June 27, 2021 (n=212,332). We constructed mixed effects logistic regression models with hospitalization, ICU admission, and death as outcome variables. Models were adjusted for age, sex, time, vaccination status, comorbidities, and pregnancy status. Health units were included as random intercepts.\n\nResultsCompared to non-VOC SARS-CoV-2 strains, the adjusted elevation in risk associated with N501Y-positive variants was 52% (43-62%) for hospitalization; 89% (67-116%) for ICU admission; and 51% (30-74%) for death. Increases with Delta variant were more pronounced: 108% (80-138%) for hospitalization; 234% (164-331%) for ICU admission; and 132% (47-230%) for death.\n\nInterpretationThe progressive increase in transmissibility and virulence of SARS-CoV-2 VOCs will result in a significantly larger, and more deadly, pandemic than would have occurred in the absence of VOC emergence.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21260055",
+    "rel_abs": "To prevent the catastrophic health and economic consequences from COVID-19 epidemics, some nations have aimed for no community transmission outside of quarantine. To achieve this, governments have had to respond rapidly to outbreaks with public health interventions. But the exact characteristics of an outbreak that trigger these measures differ and are poorly defined. We used existing data from epidemics in Australia to establish a practical model to assist stakeholders in making decisions about the optimal timing and extent of interventions. We found that the number of reported cases on the day that interventions commenced strongly predicted the size of the outbreaks. We quantified how effective interventions were at containing outbreaks in relation to the number of cases at the time the interventions commenced. We also found that containing epidemics from novel variants that had higher transmissibility would require more stringent interventions that commenced earlier. In contrast, increasing vaccination coverage would enable more relaxed interventions. Our model highlights the importance of early and decisive action in the early phase of an outbreak if governments aimed for zero community transmission, although new variants and vaccination coverage may change this.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "David Fisman",
-        "author_inst": "University of Toronto"
+        "author_name": "Zhuoru Zou",
+        "author_inst": "Xi'an Jiaotong University Health Science Centre"
       },
       {
-        "author_name": "Ashleigh Tuite",
-        "author_inst": "University of Toronto"
+        "author_name": "Christopher K Fairley",
+        "author_inst": "Monash University"
+      },
+      {
+        "author_name": "Mingwang Shen",
+        "author_inst": "Xi'an Jiaotong University"
+      },
+      {
+        "author_name": "Nick Scott",
+        "author_inst": "Burnet Institute"
+      },
+      {
+        "author_name": "Xianglong Xu",
+        "author_inst": "Monash University"
+      },
+      {
+        "author_name": "Zengbin Li",
+        "author_inst": "Xi'an Jiaotong University Health Science Centre"
+      },
+      {
+        "author_name": "Rui Li",
+        "author_inst": "Xi'an Jiaotong University Health Science Centre"
+      },
+      {
+        "author_name": "Guihua Zhuang",
+        "author_inst": "Xi'an Jiaotong University Health Science Centre"
+      },
+      {
+        "author_name": "Lei Zhang",
+        "author_inst": "Melboune Sexual Health Centre"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -637834,59 +641253,43 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.07.05.21260021",
-    "rel_title": "Knowledge, attitude, and practice related to the COVID-19 pandemic among undergraduate medical students in Indonesia: a nationwide cross-sectional study",
+    "rel_doi": "10.1101/2021.07.04.21259985",
+    "rel_title": "Covid-19 Vaccination in Pregnancy: A Systematic Review",
     "rel_date": "2021-07-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.05.21260021",
-    "rel_abs": "IntroductionThe potential role of medical students in raising awareness during public health emergencies has been acknowledged. To further explore their potentials as public educators and role models for the communities during the coronavirus disease 2019 (COVID-19) pandemic, a study is conducted to assess the knowledge, attitude, and practice of these students toward COVID-19.\n\nMethodsAn online cross-sectional survey was conducted among undergraduate medical students in Indonesia. Socio-demographical characteristics, social interaction history, information-seeking behavior, as well as knowledge, attitude, and practice toward COVID-19 were collected through a self-reported questionnaire. A p-value of <0.05 indicated statistical significance.\n\nResultsOut of 4870 respondents, 64.9% and 51.5% had positive attitude and practice toward COVID-19 while only 29.8% had adequate knowledge. Knowledge was slightly positively correlated with attitude and practice ({rho}=0.074 and {rho}=0.054, respectively; both p<0.001), while attitude was weakly correlated with practice ({rho}=0.234, p<0.001). Several factors including age, sex, place of residence, institution type, academic level, family income, history of chronic illness, prior volunteering experience, and perceptual awareness on COVID-19 were significantly associated with either knowledge, attitude, and/or practice toward COVID-19. Furthermore, health institutions and the governments press releases, as well as health expert opinions were deemed as the most reliable sources of COVID-19-related information - yet trivially none of these sources were associated with knowledge, attitude, and practice in the study population.\n\nConclusionMany undergraduate medical students in Indonesia had positive attitude and practice against COVID-19, yet only a few had adequate knowledge. This warrants further interventions to keep them updated with COVID-19 evidence to maximize their potentials in raising public awareness on COVID-19.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.04.21259985",
+    "rel_abs": "ObjectivePregnancy is a risk factor for severe Covid-19. Looking for safe vaccines that evoke protective maternal and fetal antibody response is important.\n\nMethodsWe searched from registries (ClinicalTrials.gov, the WHO Clinical Trial Registry, and the EU Clinical Trial Registry) and databases (MEDLINE, ScienceDirect, Cochrane Library, Proquest, and Springer) up until June 20, 2021. Articles were selected based on inclusion and exclusion criteria after duplicates were removed. Infection rate, maternal antibody response, placental antibody transfer, and adverse events were described. This systematic review was performed with quality assessment and semi-quantitative synthesis according to PRISMA guidelines.\n\nResultsTwelve observational studies with a total of 40.509 pregnant women included. The mRNA based vaccines (Pfizer-BioNTech and Moderna) can prevent future SARS-CoV-2 infections (p=0.0004). Both vaccines did not affect pregnancy, delivery, and neonatal outcomes. The most commonly encountered adverse reactions are injection-site pain, fatigue, and headache but only transient. Antibody responses were rapid after the prime dose of vaccines. After booster, antibody responses were higher and associated with better placental antibody transfer. Longer intervals between first vaccination dose and delivery were also associated with higher antibody fetal IgG and better antibody transfer ratio.\n\nConclusionsThe Pfizer-BioNTech and Moderna vaccines are efficacious for preventing future SARS-CoV-2 infections. These vaccines can be considered as a safe option for pregnancy and their fetus. Two doses of vaccines were recommended for more robust maternal and fetal antibody responses. Longer latency was associated with higher fetal antibody responses.\n\nSystematic Review RegistrationPROSPERO (CRD42021261684)",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Imam Adli",
-        "author_inst": "Facullty of Medicine Universitas Indonesia"
-      },
-      {
-        "author_name": "Indah Suci Widyahening",
-        "author_inst": "Faculty of Medicine Universitas Indonesia"
-      },
-      {
-        "author_name": "Gilbert Lazarus",
-        "author_inst": "Faculty of Medicine, Universitas Indonesia"
-      },
-      {
-        "author_name": "Jason Phowira",
-        "author_inst": "Faculty of Medicine Universitas Indonesia"
-      },
-      {
-        "author_name": "Lyanna Azzahra",
-        "author_inst": "Faculty of Medicine Universitas Indonesia"
+        "author_name": "Nando Reza Pratama",
+        "author_inst": "Faculty of Medicine, Airlangga University"
       },
       {
-        "author_name": "Bagas Ariffandi",
-        "author_inst": "Faculty of Medicine Universitas Indonesia"
+        "author_name": "Ifan Ali Wafa",
+        "author_inst": "Faculty of Medicine, Airlangga University"
       },
       {
-        "author_name": "Aziz Muhammad Putera",
-        "author_inst": "Faculty of Medicine Universitas Indonesia"
+        "author_name": "David Setyo Budi",
+        "author_inst": "Faculty of Medicine, Airlangga University"
       },
       {
-        "author_name": "David Nugraha",
-        "author_inst": "Faculty of Medicine Universitas Airlangga"
+        "author_name": "Manesha Putra",
+        "author_inst": "University of Colorado Anschutz School of Medicine"
       },
       {
-        "author_name": "Nico Gamalliel",
-        "author_inst": "Faculty of Medicine Universitas Indonesia"
+        "author_name": "Manggala Pasca Wardhana",
+        "author_inst": "Faculty of Medicine, Airlangga University"
       },
       {
-        "author_name": "Ardi Findyartini",
-        "author_inst": "Faculty of Medicine Universitas Indonesia"
+        "author_name": "Citrawati Dyah Kencono Wungu",
+        "author_inst": "Faculty of Medicine, Airlangga University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "medical education"
+    "category": "obstetrics and gynecology"
   },
   {
     "rel_doi": "10.1101/2021.07.05.21260022",
@@ -639484,59 +642887,155 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.07.06.21259749",
-    "rel_title": "Application of nasal spray containing dimethyl sulfoxide (DSMO) and ethanol during the COVID-19 pandemic may protect healthcare workers: A randomized controlled trials",
+    "rel_doi": "10.1101/2021.07.05.451222",
+    "rel_title": "Broadly neutralizing antibodies to SARS-related viruses can be readily induced in rhesus macaques",
     "rel_date": "2021-07-06",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21259749",
-    "rel_abs": "BackgroundCoronavirus pandemic has affected a large population worldwide. Currently, the standard care for individuals who are exposed is supportive care, symptomatic management, and isolation. The aim of our study was to evaluate effects of combined use of ethanol and DMSO as a nasal spray in preventing COVID-19.\n\nMethodsWe conducted a randomized controlled trial on volunteer healthcare workers of medical centers that were at the forefront of the fight against COVID-19 in Shahroud, Iran. Two hundred and thirty-two participants were randomly assigned to intervention and control groups to receive DMSO/ethanol or routine care, respectively. The subjects were followed for 4 weeks to determine the incidence of COVID-19 infection in each group based on the RT-qPCR test. Finally, absolute risk difference and relative risk were calculated to evaluate the effect of DMSO in prevent COVID-19.\n\nResultsThe results showed that the incidence of COVID-19 in the control group and intervention group were 0.07 and 0.008, respectively. The relative risk (RR) was 0.12 (0.9-0.02) according to the incidence rate in the two groups.\n\nConclusioncombined application of DMSO and ethanol in healthcare providers can considerably prevent COVID-19.",
-    "rel_num_authors": 10,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.05.451222",
+    "rel_abs": "To prepare for future coronavirus (CoV) pandemics, it is desirable to generate vaccines capable of eliciting neutralizing antibody responses against multiple CoVs. Because of the phylogenetic similarity to humans, rhesus macaques are an animal model of choice for many virus-challenge and vaccine-evaluation studies, including SARS-CoV-2. Here, we show that immunization of macaques with SARS-CoV-2 spike (S) protein generates potent receptor binding domain cross- neutralizing antibody (nAb) responses to both SARS-CoV-2 and SARS-CoV-1, in contrast to human infection or vaccination where responses are typically SARS-CoV-2-specific. Furthermore, the macaque nAbs are equally effective against SARS-CoV-2 variants of concern. Structural studies show that different immunodominant sites are targeted by the two primate species. Human antibodies generally target epitopes strongly overlapping the ACE2 receptor binding site (RBS), whereas the macaque antibodies recognize a relatively conserved region proximal to the RBS that represents another potential pan-SARS-related virus site rarely targeted by human antibodies. B cell repertoire differences between the two primates appear to significantly influence the vaccine response and suggest care in the use of rhesus macaques in evaluation of vaccines to SARS-related viruses intended for human use.\n\nONE SENTENCE SUMMARYBroadly neutralizing antibodies to an unappreciated site of conservation in the RBD in SARS- related viruses can be readily induced in rhesus macaques because of distinct properties of the naive macaque B cell repertoire that suggest prudence in the use of the macaque model in SARS vaccine evaluation and design.",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Ali Hosseinzadeh",
-        "author_inst": "Shahroud University of medical sciences"
+        "author_name": "Wan-ting He",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Abbas Tavakkolian",
-        "author_inst": "Islamic Azad University, Shahroud Branch, Shahroud, Iran."
+        "author_name": "Meng Yuan",
+        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Vahid Kia",
-        "author_inst": "Shahroud University of Medical Sciences"
+        "author_name": "Sean Callaghan",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Hossein Ebrahimi",
-        "author_inst": "Shahroud University School of Medical Sciences"
+        "author_name": "Rami Musharrafieh",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Hossein Sheibani",
-        "author_inst": "Shahroud University School of Medical Sciences"
+        "author_name": "Ge Song",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Ehsan Binesh",
-        "author_inst": "Shahroud University School of Medical Sciences"
+        "author_name": "Murillo Silva",
+        "author_inst": "Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"
       },
       {
-        "author_name": "Reza Jafari",
-        "author_inst": "Shahroud University of Medical Sciences"
+        "author_name": "Nathan Beutler",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Seyed Mohammad Mirrezaie",
-        "author_inst": "Shahroud University School of Medical Sciences"
+        "author_name": "Wen-Hsin Lee",
+        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Moslem Jafarisani",
-        "author_inst": "Shahroud University of medical Sciences"
+        "author_name": "Peter Yong",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       },
       {
-        "author_name": "Mohammad Hassan Emamian",
-        "author_inst": "Shahroud University of Medical Sciences"
+        "author_name": "Jonathan L. Torres",
+        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Mariane Melo",
+        "author_inst": "Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"
+      },
+      {
+        "author_name": "Panpan Zhou",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Fangzhu Zhao",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Xueyong Zhu",
+        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Linghang Peng",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Deli Huang",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Fabio Anzanello",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "James Ricketts",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Mara Parren",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Elijah Garcia",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Melissa Ferguson",
+        "author_inst": "Alpha Genesis, Yemassee, SC 29945, USA"
+      },
+      {
+        "author_name": "William Rinaldi",
+        "author_inst": "Alpha Genesis, Yemassee, SC 29945, USA"
+      },
+      {
+        "author_name": "Stephen A. Rawlings",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "David Nemazee",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Davey M. Smith",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Bryan Briney",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Yana Safonova",
+        "author_inst": "Computer Science and Engineering Department, University of California, San Diego (UCSD), La Jolla, CA 92037, USA"
+      },
+      {
+        "author_name": "Thomas Rogers",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, University of California, San Diego, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Shane Crotty",
+        "author_inst": "Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA 92037, USA"
+      },
+      {
+        "author_name": "Darrell J. Irvine",
+        "author_inst": "Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"
+      },
+      {
+        "author_name": "Andrew B. Ward",
+        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Ian A. Wilson",
+        "author_inst": "Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Dennis R. Burton",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
+      },
+      {
+        "author_name": "Raiees Andrabi",
+        "author_inst": "Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.07.01.21259785",
@@ -641034,25 +644533,85 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.07.03.21259959",
-    "rel_title": "Efficacy and safety of cyclosporine in the management of coronavirus disease 2019: A protocol for systematic review and meta-analysis",
+    "rel_doi": "10.1101/2021.07.02.21259665",
+    "rel_title": "Assessment and Modeling of COVID-19 Outcomes in a Longitudinal Cohort of Hospitalized Adults",
     "rel_date": "2021-07-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.03.21259959",
-    "rel_abs": "IntroductionCyclosporine may improve the clinical course and outcomes of Coronavirus disease 2019 (COVID-19) due to its antiviral and anti-cytokine effects as shown in vitro. A few ongoing trials are exploring the benefit of adding it to the standard of care (SOC) of COVID-19 patients.\n\nObjectivesThe primary objective is to evaluate the severity of COVID-19, determined by oxygen saturation, intensive care unit (ICU) admission, or the World Health Organization COVID-19 clinical severity scale in patients treated with oral or intravenous cyclosporine added to SOC compared SOC alone or placebo. Secondary objectives include mortality, length of hospitalization, length of ICU stay, and laboratory measurements as well as the safety outcomes of cyclosporine.\n\nMethodologyA systematic review and meta-analysis of randomized clinical trials and observational studies that compared cyclosporine to placebo or SOC in COVID-19 patients will be conducted. PubMed, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, Google Scholar, and ClinicalTrials.gov will be explored for studies that satisfy pre-specified inclusion criteria. Quality assessment of all included studies will be performed. Meta-analyses will be done utilizing random effect models to estimate the effect of cyclosporine on the severity of COVID-19. Heterogeneity will be assessed utilizing Q statistics. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines will be followed.\n\nResultsThe result of this synthesis will inform potential changes in the management of COVID-19 patients, especially regarding the role of calcineurin inhibitors. Additionally, it will serve as hypothesis generating for potential future prospective studies.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.02.21259665",
+    "rel_abs": "BackgroundWhile several demographic and clinical correlates of Coronavirus Disease 2019 (COVID-19) outcome have been identified, they remain imprecise tools for clinical management of disease. Furthermore, there are limited data on how these factors are associated with virological and immunological parameters over time.\n\nMethods and FindingsNasopharyngeal swabs and blood samples were longitudinally collected from a cohort of 58 hospitalized adults with COVID-19 in Chicago, Illinois between March 27 and June 9, 2020. Samples were assessed for SARS-CoV-2 viral load, viral genotype, viral diversity, and antibody titer. Demographic and clinical information, including patient blood tests and several composite measures of disease severity, were extracted from electronic health records. All parameters were assessed for association with three patient outcome groups: discharge without intensive care unit (ICU) admission (n = 23), discharge with ICU admission (n = 29), and COVID-19 related death (n = 6). Higher age, male sex, and higher body mass index (BMI) were significantly associated with ICU admission. At hospital admission, higher 4C Mortality scores and lactate dehydrogenase (LDH) levels were likewise associated with ICU admission. Longitudinal trends in Deterioration Index (DI) score, Modified Early Warning Score (MEWS), and serum neutrophil count were also associated with ICU admission, though only the retrospectively calculated median DI score was predictive of death. While viral load and genotype were not significantly associated with outcome in this study, viral load did correlate positively with C-reactive protein levels and negatively with D-dimer, lymphocyte count, and antibody titer. Intra-host viral genetic diversity resulted in changes in viral genotype in some participants over time, though intra-host evolution was not associated with outcome. A stepwise-generated multivariable model including BMI, lymphocyte count at admission, and neutrophil count at admission was sufficient to predict outcome with a 0.82 accuracy rate in this cohort.\n\nConclusionsThese studies suggest that COVID-19 disease severity and poor outcomes among hospitalized patients are likely driven by dysfunctional host responses to infection and underlying co-morbid conditions rather than SARS-CoV-2 viral loads. Several parameters, including 4C mortality score, LDH levels, and DI score, were ultimately predictive of participant outcome and warrant further exploration in larger cohort studies for use in clinical management and risk assessment. Finally, the prevalence of intra-host diversity and viral evolution in hospitalized patients suggests a mechanism for population-level change, further emphasizing the need for effective antivirals to suppress viral replication and to avoid the emergence of new variants.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Ibtihal Abdallah",
-        "author_inst": "Clinical Pharmacy Department, Hamad General Hospital, Hamad Medical Corporation"
+        "author_name": "Lacy M Simons",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Ramon Lorenzo-Redondo",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Meg Gibson",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Mohamed Aabdien",
-        "author_inst": "Community Medicine Training Program, Medical Education, Hamad Medical Corporation"
+        "author_name": "Sarah L Kinch",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Mohammed Danjuma",
-        "author_inst": "Division of General Internal Medicine, Weill Cornell affliated-Hamad General Hospital, Hamad Medical Corporation"
+        "author_name": "Jacob P Vandervaart",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Nina L Reiser",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Mesut Eren",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Elizabeth Lux",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Elizabeth McNally",
+        "author_inst": "Northwestern University Feinberg School of Medicine"
+      },
+      {
+        "author_name": "Anat R Tambur",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Douglas E Vaughan",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Kelly R Bachta",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Alexis R. Demonbreun",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Karla J.F. Satchell",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Chad J Achenbach",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Egon A Ozer",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Michael G Ison",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Judd F. Hultquist",
+        "author_inst": "Northwestern University Feinberg School of Medicine"
       }
     ],
     "version": "1",
@@ -642704,105 +646263,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.29.21259605",
-    "rel_title": "The SARS-CoV-2 receptor-binding domain expressed in Pichia pastoris as a candidate vaccine antigen",
+    "rel_doi": "10.1101/2021.06.28.21259452",
+    "rel_title": "Persistent symptoms following SARS-CoV-2 infection in a random community sample of 508,707 people",
     "rel_date": "2021-07-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.29.21259605",
-    "rel_abs": "1.The effort to develop vaccines based on economically accessible technological platforms available by developing countries vaccine manufacturers is essential to extend the immunization to the whole world population and to achieve the desired herd immunity, necessary to end the COVID-19 pandemic. Here we report on the development of a SARS-CoV-2 receptor-binding domain (RBD) protein, expressed in yeast Pichia pastoris. The RBD was modified with addition of flexible N- and C-terminal amino acid extensions aimed to modulate the protein/protein interactions and facilitate protein purification. Fermentation with yeast extract culture medium yielded 30-40 mg/L. After purification by immobilized metal ion affinity chromatography and hydrophobic interaction chromatography, the RBD protein was characterized by mass-spectrometry, circular dichroism, and binding affinity to angiotensin-converting enzyme 2 (ACE2) receptor. The recombinant protein shows high antigenicity with convalescent human sera and also with sera from individuals vaccinated with the Pfizer-BioNTech mRNA or Sputnik V adenoviral-based vaccines. The RBD protein stimulates IFN{gamma}, IL-2, IL-6, IL-4, and TNF in mice secreting splenocytes from PBMC and lung CD3+ enriched cells. Immunogenicity studies with 50 {micro}g of the recombinant RBD formulated with alum, induce high levels of binding antibodies in mice and non-human primates, assessed by ELISA plates covered with RBD protein expressed in HEK293T cells. The mouse sera inhibited the RBD binding to ACE2 receptor in an in-vitro test and show neutralization of SARS-CoV-2 infection of Vero E6 cells. These data suggest that the RBD recombinant protein expressed in yeast P. pastoris is suitable as a vaccine candidate against COVID-19.\n\nHighlightsO_LIThe RBD protein (C-RBD-H6 PP) is expressed with high purity in P. pastoris.\nC_LIO_LIPhysico-chemical characterization confirms the right folding of the protein.\nC_LIO_LIThe recombinant protein shows high antigenicity with sera from convalescents.\nC_LIO_LIThe sera from animals inhibit the RBD-ACE2 binding and neutralize the virus.\nC_LIO_LIThe C-RBD-H6 protein stimulates IFN{gamma}, IL-2, IL-6, IL-4, and TNF in mice.\nC_LI",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259452",
+    "rel_abs": "BackgroundLong COVID, describing the long-term sequelae after SARS-CoV-2 infection, remains a poorly defined syndrome. There is uncertainty about its predisposing factors and the extent of the resultant public health burden, with estimates of prevalence and duration varying widely.\n\nMethodsWithin rounds 3-5 of the REACT-2 study, 508,707 people in the community in England were asked about a prior history of COVID-19 and the presence and duration of 29 different symptoms. We used uni-and multivariable models to identify predictors of persistence of symptoms (12 weeks or more). We estimated the prevalence of symptom persistence at 12 weeks, and used unsupervised learning to cluster individuals by symptoms experienced.\n\nFindingsAmong the 508,707 participants, the weighted prevalence of self-reported COVID-19 was 19.2% (95% CI: 19.1,19.3). 37.7% of 76,155 symptomatic people post COVID-19 experienced at least one symptom, while 14.8% experienced three or more symptoms, lasting 12 weeks or more. This gives a weighted population prevalence of persistent symptoms of 5.75% (5.68, 5.81) for one and 2.22% (2.1, 2.26) for three or more symptoms. Almost a third of people (8,771/28,713 [30.5%]) with at least one symptom lasting 12 weeks or more reported having had severe COVID-19 symptoms (\"significant effect on my daily life\") at the time of their illness, giving a weighted prevalence overall for this group of 1.72% (1.69,1.76). The prevalence of persistent symptoms was higher in women than men (OR: 1.51 [1.46,1.55]) and, conditional on reporting symptoms, risk of persistent symptoms increased linearly with age by 3.5 percentage points per decade of life. Obesity, smoking or vaping, hospitalisation, and deprivation were also associated with a higher probability of persistent symptoms, while Asian ethnicity was associated with a lower probability. Two stable clusters were identified based on symptoms that persisted for 12 weeks or more: in the largest cluster, tiredness predominated, while in the second there was a high prevalence of respiratory and related symptoms.\n\nInterpretationA substantial proportion of people with symptomatic COVID-19 go on to have persistent symptoms for 12 weeks or more, which is age-dependent. Clinicians need to be aware of the differing manifestations of Long COVID which may require tailored therapeutic approaches. Managing the long-term sequelae of SARS-CoV-2 infection in the population will remain a major challenge for health services in the next stage of the pandemic.\n\nFundingThe study was funded by the Department of Health and Social Care in England.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSRecent systematic reviews have documented the wide range of symptoms and reported prevalence of persistent symptoms following COVID-19. A dynamic review of Long COVID studies (NIHR Evidence) in March 2021 summarised the literature on the prevalence of persistent symptoms after acute COVID19, and reported that most studies (14) were of hospitalised patients, with higher prevalence of persistent symptoms compared with two community-based studies. There was limited evidence from community studies beyond 12 weeks. Another systematic review reported a median of over 70% of people with symptoms lasting at least 60 days. A review of risk factors for Long COVID found consistent evidence for an increased risk amongst women and those with high body mass index (BMI) but inconsistent findings on the role of age and little evidence concerning risks among different socioeconomic or ethnic groups which are often not well captured in routine healthcare records. Long COVID is increasingly recognised as heterogenous, likely underpinned by differing biological mechanisms, but there is not yet consensus on defining subtypes of the condition.\n\nAdded value of this studyThis community-based study of over half a million people was designed to be representative of the adult population of England. A random sample of adults ages 18 years and above registered with a GP were invited irrespective of previous access to services for COVID-19, providing an estimate of population prevalence that was representative of the whole population. The findings show substantial declines in symptom prevalence over the first 12 weeks following Covid-19, reported by nearly one fifth of respondents, of whom over a third remained symptomatic at 12 weeks and beyond, with little evidence for decline thereafter.\n\nRisk factors identified for persistent symptoms (12 weeks or more) suggestive of Long COVID confirm some previous findings - an increased risk in women, obese and overweight individuals and those hospitalised for COVID-19, with strong evidence for an increasing risk with age. Additional evidence was found for an increased risk in those with lower income, smoking or vaping and healthcare or care home workers. A lower risk was found in those of Asian ethnicity.\n\nClustering identified two distinct groups of individuals with different symptom profiles at 12 weeks, highlighting the heterogeneity of clinical presentation. The smaller cluster had higher prevalence of respiratory and related symptoms, while for those in the larger cluster tiredness was the dominant symptom, with lower prevalence of organ-specific symptoms.\n\nImplications of available evidenceThere is a high prevalence of persistent symptoms beyond 12 weeks after acute COVID-19, with little evidence of decline thereafter. This highlights the needs for greater support for patients, both through specialised services and, for those from low-income settings, financial support. The understanding that there are distinct clusters of persistent symptoms, the most common of which is dominated by fatigue, is important for the recognition and clinical management of the condition outside of specialised services.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Miladys Limonta-Fernandez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba"
-      },
-      {
-        "author_name": "Glay Chinea-Santiago",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Alejandro Miguel Martin-Dunn",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Diamile Gonzalez-Roche",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Monica Bequet-Romero",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Gabriel Marquez-Perera",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Isabel Gonzalez-Moya",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Camila Canaan-Haden-Ayala",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Ania Cabrales-Rico",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Luis Ariel Espinosa-Rodriguez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Yassel Ramos-Gomez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Ivan Andujar-Martinez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Luis Javier Gonzalez-Lopez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Mariela Perez de la Iglesia",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Jesus Zamora-Sanchez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
-      },
-      {
-        "author_name": "Otto Cruz-Sui",
-        "author_inst": "Civilian Defense Scientific Research Center, Carretera de Jamaica y Autopista Nacional, San Jose de las Lajas, Mayabeque, Cuba"
+        "author_name": "Matthew Whitaker",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Gilda Lemos-Perez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
+        "author_name": "Joshua Elliott",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Gleysin Cabrera-Herrera",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
+        "author_name": "Marc Chadeau-Hyam",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Jorge Valdes-Hernandez",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
+        "author_name": "Steven Riley",
+        "author_inst": "Dept Inf Dis Epi, Imperial College"
       },
       {
-        "author_name": "Eduardo Martinez-Diaz",
-        "author_inst": "Biotechnology and Pharmaceutical Industries Group, BioCubaFarma, Ave. Independencia 8126, esq. a Calle 100. Boyeros. La Habana, Cuba."
+        "author_name": "Ara Darzi",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Eulogio Pimentel-Vazquez",
-        "author_inst": "Biotechnology and Pharmaceutical Industries Group, BioCubaFarma, Ave. Independencia 8126, esq. a Calle 100. Boyeros. La Habana, Cuba."
+        "author_name": "Graham Cooke",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Marta Ayala-Avila",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
+        "author_name": "Helen Ward",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Gerardo Guillen-Nieto",
-        "author_inst": "Center for Genetic Engineering and Biotechnology, CIGB, Ave. 31 E/ 158 y 190, La Habana 10600, Cuba."
+        "author_name": "Paul Elliott",
+        "author_inst": "Imperial College London School of Public Health"
       }
     ],
     "version": "1",
@@ -644810,119 +648309,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.06.28.21259384",
-    "rel_title": "Comparison of Mental Health Symptom Changes from pre-COVID-19 to COVID-19 by Sex or Gender: A Systematic Review and Meta-analysis",
+    "rel_doi": "10.1101/2021.06.27.21259131",
+    "rel_title": "Face mask use and associated factors among students in rural Eastern Uganda amidst the COVID-19 pandemic",
     "rel_date": "2021-07-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259384",
-    "rel_abs": "ImportanceWomen and gender-diverse individuals have faced disproportionate socioeconomic burden during COVID-19. There have been reports that this has translated into greater negative changes in mental health, but this has been based on cross-sectional research that has not accounted for pre-COVID-19 differences.\n\nObjectiveTo compare mental health symptom changes since pre-COVID-19 by sex or gender.\n\nData SourcesMEDLINE, PsycINFO, CINAHL, EMBASE, Web of Science, China National Knowledge Infrastructure, Wanfang, medRxiv, and Open Science Framework (December 31, 2019 to August 30, 2021).\n\nStudy SelectionEligible studies compared mental health symptom changes from pre-COVID-19 to COVID-19 by sex or gender.\n\nData Extraction and SynthesisData was extracted by a single reviewer with validation by a second reviewer. Adequacy of study methods and reporting was assessed using an adapted version of the Joanna Briggs Institute Checklist for Prevalence Studies. A restricted maximum-likelihood random-effects meta-analyses was conducted.\n\nMain Outcomes and MeasuresAnxiety symptoms, depression symptoms, general mental health, and stress measured continuously or dichotomously.\n\nResults12 studies (10 unique cohorts) were included. All compared females or women to males or men; none included gender-diverse individuals. Continuous symptom change differences were not statistically significant for depression (standardized mean difference [SMD]= 0.12, 95% CI -0.09 to 0.33; 4 studies, 4,475 participants; I2=69.0%) and stress (SMD= - 0.10, 95% CI -0.21 to 0.01; 4 studies, 1,533 participants; I2=0.0%), but anxiety (SMD= 0.15, 95% CI 0.07 to 0.22; 4 studies, 4,344 participants; I2=3.0%) and general mental health (SMD= 0.15, 95% CI 0.12 to 0.18; 3 studies, 15,692 participants; I2=0.0%) worsened more among females or women than males or men during COVID-19. There were no significant differences in changes in proportion above a cut-off: anxiety (difference= -0.05, 95% CI -0.20 to 0.11; 1 study, 217 participants), depression (difference= 0.12, 95% CI -0.03 to 0.28; 1 study, 217 participants), general mental health (difference= -0.03, 95% CI -0.09 to 0.04; 3 studies, 18,985 participants; I2=94.0%), stress (difference= 0.04, 95% CI -0.10 to 0.17; 1 study, 217 participants).\n\nConclusion and RelevanceMental health outcomes did not differ or were worse by amounts below thresholds for clinical significance for women compared to men.\n\nRegistrationPROSPERO (CRD42020179703).\n\nKEY MESSAGESO_ST_ABSQuestionC_ST_ABSDid mental health symptoms worsen more for females or women than males or men in COVID-19?\n\nFindingsWe reviewed almost 65,000 citations and identified 12 studies that provided data to directly compare mental health symptom changes from pre-COVID-19 to during COVID-19 for females or women versus males or men. Statistically significant, but small, sex- or gender-based differences were found in 2 of 8 mental health outcomes.\n\nMeaningMental health changes among females or women were not significantly different from males or men for most outcomes, and differences that were identified were small and less than minimally important difference thresholds.",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.27.21259131",
+    "rel_abs": "BackgroundThe Corona Virus Disease of 2019 (COVID-19) has gravely affected several aspects of national and global society, including education. Given the risk it poses, the Government of Uganda (GOU) adopted and recommended face mask use as one of the preventive measures to limit its transmission in communities. However, there is limited data on the levels of face mask usage and associated factors among students in schools in Uganda. This study aimed at assessing the face mask usage and associated factors among students in schools in rural Eastern Uganda amidst the COVID-19 pandemic.\n\nMethodsA cross sectional quantitative descriptive study was conducted among 423 students in schools in rural Eastern Uganda. Multi-stage sampling method was employed in the selection of study participants. The data was collected by trained data collectors using structured questionnaires pre-installed on ODK enabled smart phones. The data entered was cleaned using Excel 2016 and exported to Stata14.0 statistical software (Statacorp, College station, Texas, USA) for analysis. Bivariate and multivariable logistic regression analyses were employed using 95% CI (confidence interval). Variables with p-value < 0.20 and those with literature backup evidence were included in the multivariable model. Variables with p-value < 0.05 were considered to be statistically significant. This study revealed that less than three quarters (62.3%) wore face masks correctly.\n\nResultsAlmost all, 98.9% of the participants mentioned that they wore face masks due to fear of missing classes and 49.0% disagreed that they were vulnerable to COVID-19. Students in boarding schools (AOR = 1.61, 95%CI: 1.05-2.47), those who believed that they were vulnerable to COVID-19 (AOR = 1.70, 95%CI: 1.11-2.10), and those who disagreed that masks are uncomfortable (AOR = 1.62, 95%CI: 1.06-2.46) were more likely to wear facemasks correctly.\n\nConclusionThis study revealed that more than a third of the students did not wear face masks correctly. Correct wearing of face masks was associated with being in a boarding school, belief that they were susceptible to COVID-19, and disagreeing that masks were uncomfortable. This therefore highlights the need for sensitization programmes in academic institutions in order to improve students perceptions toward COVID-19 and face masks, and consequently increase correct face mask usage in schools.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Tiffany Dal Santo",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Ying Sun",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Yin Wu",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Chen He",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Yutong Wang",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Xiaowen Jiang",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Kexin Li",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Olivia Bonardi",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Ankur Krishnan",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Jill T. Boruff",
-        "author_inst": "Schulich Library of Physical Sciences, Life Sciences, and Engineering, McGill University"
-      },
-      {
-        "author_name": "Danielle B. Rice",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Sarah Markham",
-        "author_inst": "Department of Biostatistics and Health Informatics, King's College London"
-      },
-      {
-        "author_name": "Brooke Levis",
-        "author_inst": "Centre for Prognosis Research, School of Medicine, Keele University"
-      },
-      {
-        "author_name": "Marleine Azar",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Dipika Neupane",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Amina Tasleem",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Anneke Yao",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
-      },
-      {
-        "author_name": "Ian Thombs-Vite",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
+        "author_name": "Denis Mwesige",
+        "author_inst": "Faculty of Science and Technology, Cavendish University Uganda"
       },
       {
-        "author_name": "Branka Agic",
-        "author_inst": "Centre for Addiction and Mental Health"
-      },
-      {
-        "author_name": "Christine Fahim",
-        "author_inst": "Li Ka Shing Knowledge Institute, Unity Health Toronto"
+        "author_name": "Aisha Nalugya",
+        "author_inst": "Department of Disease control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University"
       },
       {
-        "author_name": "Michael S. Martin",
-        "author_inst": "School of Epidemiology and Public Health, University of Ottawa"
+        "author_name": "Douglas Bulafu",
+        "author_inst": "Elevate Research and Health Services Limited"
       },
       {
-        "author_name": "Sanjeev Sockalingam",
-        "author_inst": "Centre for Addiction and Mental Health"
+        "author_name": "Arnold Tigaiza",
+        "author_inst": "Elevate Research and Health Services Limited"
       },
       {
-        "author_name": "Gustavo Turecki",
-        "author_inst": "Department of Psychology, McGill University"
+        "author_name": "Bridget Tamale Nagawa",
+        "author_inst": "Elevate Research and Health Services Limited"
       },
       {
-        "author_name": "Andrea Benedetti",
-        "author_inst": "Department of Epidemiology, Biostatistics and Occupational Health, McGill University"
+        "author_name": "Emmanuel Balinda",
+        "author_inst": "Elevate Research and Health Services Limited"
       },
       {
-        "author_name": "Brett B Thombs",
-        "author_inst": "Lady Davis Institute for Medical Research, Jewish General Hospital"
+        "author_name": "Abel Wilson Walekhwa",
+        "author_inst": "Department of Disease control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.06.28.21259028",
@@ -647080,63 +650507,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.28.21259628",
-    "rel_title": "Rotation-based schedules in elementary schools to prevent COVID-19 spread: A simulation study",
+    "rel_doi": "10.1101/2021.06.28.21259620",
+    "rel_title": "The Evolution of Young People's Mental Health during COVID-19: Evidence from four Low-and-Middle-Income-Countries",
     "rel_date": "2021-07-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259628",
-    "rel_abs": "BackgroundRotations of schoolchildren on a weekly basis is one of the nonpharmaceutical interventions often considered in the covid-19 pandemic. This study aims to investigate the impact of different types of rotations in various testing contexts.\n\nMethodsWe built an agent-based model of interactions among pupils and teachers based on an online survey in an elementary school in Prague, Czechia. This model contains 624 schoolchildren and 55 teachers (679 nodes) and about 27 thousands social contacts (edges) in 10 layers. The layers reflect different types of contacts (in classroom, cafeteria etc.) as described in the survey. On this multi-graph structure we run a modified SEIR model of the covid-19 dynamics. The parameters of the model are calibrated on data from the outbreak in the Czech Republic in the period March to June 2020.\n\nFindingsThere are three main findings in our paper.\n\nO_LIWeekly rotations of in-class and distance learning reduce the spread of covid-19 by 75-81% and thus represent an effective preventative measure in school setting.\nC_LIO_LIRegular antigen testing twice a week, or weekly PCR testing, significantly reduces infections even when using tests with a lower sensitivity: tests with a 40% sensitivity reduce infections by more than 50 percent.\nC_LIO_LIThe density of revealed contact graphs for older pupils is 1.5 times higher than the younger pupils graph, the teachers network is yet an order of magnitude denser. Consequently, the infection transmission between teachers is highly overproportional in our school. Moreover, teachers act as bridges connecting clusters of classes, especially in the secondary grade where they are responsible for 14-18% of infections, in comparison to 8-11% in primary grade.\nC_LI\n\nInterpretationWeekly rotations with regular testing are a highly effective non-pharmaceutical intervention for the prevention of covid-19 spread in schools and a way to keep schools open during an epidemic or to reopen them as the epidemiological situation improves.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259620",
+    "rel_abs": "BackgroundThough COVID-19 presents less risk to young people of serious morbidity or mortality, the resulting economic crisis has impacted their livelihoods. There is relatively little evidence on young peoples mental health in Low-and-Middle-Income-Countries (LMICs) as the pandemic has progressed.\n\nMethodsTwo consecutive phone-surveys (August/October and November/December 2020) in Ethiopia, India, Peru and Vietnam interviewed around 9,000 participants of a 20-year cohort study who grew up in poverty (now aged 19 and 26). We investigate how young peoples mental health has evolved in the four countries during the pandemic. Rates of (at least mild) anxiety (depression) measured by GAD-7 (PHQ-8) were compared across countries; between males/females, and food secure/food insecure households.\n\nResultsOverall, rates of at least mild anxiety (depression) significantly decreased in all countries but Ethiopia as infection rates fell. However, young people in food insecure households report high rates of anxiety and depression and have not shown consistent improvements. Food insecure households are poorer, and have significantly more children (p<0.05) except in Ethiopia.\n\nConclusionsFood insecurity has increased during the COVID-19 pandemic and is negatively associated with young peoples mental health. Urgent support is needed for the most vulnerable.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Cyril Brom",
-        "author_inst": "Faculty of Mathematics and Physics, Charles University"
-      },
-      {
-        "author_name": "Tomas Diviak",
-        "author_inst": "School of Social Sciences, University of Manchester"
-      },
-      {
-        "author_name": "Jakub Drbohlav",
-        "author_inst": "Ministry of Education, Youth and Sports of the Czech Republic"
-      },
-      {
-        "author_name": "Vaclav Korbel",
-        "author_inst": "CERGE-EI"
-      },
-      {
-        "author_name": "Rene Levinsky",
-        "author_inst": "CERGE-EI"
-      },
-      {
-        "author_name": "Roman Neruda",
-        "author_inst": "The Czech Academy of Sciences, Institute of Computer Science"
-      },
-      {
-        "author_name": "Gabriela Suchoparova",
-        "author_inst": "The Czech Academy of Sciences, Institute of Computer Science"
+        "author_name": "Catherine Porter",
+        "author_inst": "Lancaster University"
       },
       {
-        "author_name": "Josef Slerka",
-        "author_inst": "Faculty of Arts, Charles University"
+        "author_name": "Annina Hittmeyer",
+        "author_inst": "Oxford Department of International Development, University of Oxford"
       },
       {
-        "author_name": "Martin Smid",
-        "author_inst": "The Czech Academy of Sciences, Institute of Information Theory and Automation"
+        "author_name": "Marta Favara",
+        "author_inst": "Oxford Department of International Development, University of Oxford"
       },
       {
-        "author_name": "Jan Trnka",
-        "author_inst": "Third Faculty of Medicine, Charles University"
+        "author_name": "Douglas Scott",
+        "author_inst": "Oxford Department of International Development, University of Oxford"
       },
       {
-        "author_name": "Petra Vidnerova",
-        "author_inst": "The Czech Academy of Sciences, Institute of Computer Science"
+        "author_name": "Alan S\u00e1nchez",
+        "author_inst": "Grupo de An\u00e1lisis para el Desarrollo (GRADE)"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.06.28.21259558",
@@ -648798,79 +652201,55 @@
     "category": "cell biology"
   },
   {
-    "rel_doi": "10.1101/2021.06.30.450617",
-    "rel_title": "Detection of potential new SARS-CoV-2 Gamma-related lineage in Tocantins shows the spread and ongoing evolution of P.1 in Brazil",
+    "rel_doi": "10.1101/2021.06.30.450547",
+    "rel_title": "Computational saturation mutagenesis of SARS-CoV-1 spike glycoprotein: stability, binding affinity, and comparison with SARS-CoV-2",
     "rel_date": "2021-06-30",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.30.450617",
-    "rel_abs": "After more than a year of the pandemic situation of COVID-19, the United Kingdom (UK), South Africa, and Brazil became the epicenter of new lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Variants of Concern (VOCs) were identified through a continuous genomic surveillance global effort, the B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), and P.1 (Gamma) harboring a constellation set of mutations. This research aims to: (i) report the predominance of the Gamma (P.1) lineage presenting the epidemiological situation of the SARS-CoV-2 genomic surveillance at the state of Tocantins, and (ii) describe the emergence of possible new mutations and viral variants with the potential new lineage (P1-related) represented by 8 genomes from the Tocantins harboring the mutation L106F in ORF3a. At the moment, 6,687 SARS-CoV-2 genomes from GISAID carry this mutation. The whole-genome sequencing has an important role in understanding the evolution and genomic diversity of SARS-CoV-2, thus, the continuous monitoring will help in the control measures and restrictions imposed by the secretary of health of the state to prevent the spread of variants.",
-    "rel_num_authors": 15,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.30.450547",
+    "rel_abs": "Severe Acute respiratory syndrome coronavirus (SARS-CoV-1) attaches to the host cell surface to initiate the interaction between the receptor-binding domain (RBD) of its spike glycoprotein (S) and the human Angiotensin-converting enzyme (hACE2) receptor. SARS-CoV-1 mutates frequently because of its RNA genome, which challenges the antiviral development. Here, we performed computational saturation mutagenesis of the S protein of SARS-CoV-1 to identify the residues crucial for its functions. We used the structure-based energy calculations to analyze the effects of the missense mutations on the SARS-CoV-1 S stability and the binding affinity with hACE2. The sequence and structure alignment showed similarities between the S proteins of SARS-CoV-1 and SARS-CoV-2. Interestingly, we found that target mutations of S protein amino acids generate similar effects on their stabilities between SARS-CoV-1 and SARS-CoV-2. For example, G839W of SARS-CoV-1 corresponds to G857W of SARS-CoV-2, which decrease the stability of their S glycoproteins. The viral mutation analysis of the two different SARS-CoV-1 isolates showed that mutations, T487S and L472P, weakened the S-hACE2 binding of the 2003-2004 SARS-CoV-1 isolate. In addition, the mutations of L472P and F360S destabilized the 2003-2004 viral isolate. We further predicted that many mutations on N-linked glycosylation sites would increase the stability of the S glycoprotein. Our results can be of therapeutic importance in the design of antivirals or vaccines against SARS-CoV-1 and SARS-CoV-2.\n\nAuthor SummarySevere acute respiratory syndrome coronavirus (SARS-CoV-1) is an RNA virus that undergoes frequent mutations, which may result in more virulent SARS-CoV-1 variants. To prevent another pandemic in the future, scientists must understand the mechanisms of viral mutations and predict if any variants could become a dominant. The infection of SARS-CoV-1 in cells is largely depending on the interactions of the viral Spike (S) and human angiotensin-converting enzyme 2 (hACE2). We applied a computational method to predict S missense mutations that will make SARS-CoV-1 more virulent. We are interested in the variants that can change SARS-CoV-1 spike protein stability and/or change the virus-receptor interactions. We mutated each residue of SARS-CoV-1 spike to all possible amino acids; we calculated the differences between the folding energy and binding energy of each variant and the wildtype and identified the target S mutations with significant effects on protein stability and protein-protein interaction. We found some viral mutations could destabilize S and weaken S-hACE2 binding of SARS-CoV-1 isolate. Our results show that the computational saturation mutagenesis is a reliable approach in the analysis and prediction of missense mutations.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Ueric Jose Borges de Souza",
-        "author_inst": "Bioinformatics and Biotechnology Laboratory, Campus of Gurupi, Federal University of Tocantins, Gurupi, Tocantins, 77410-570, Brazil."
-      },
-      {
-        "author_name": "Raissa Nunes dos Santos",
-        "author_inst": "Bioinformatics and Biotechnology Laboratory, Campus of Gurupi, Federal University of Tocantins, Gurupi, Tocantins, 77410-570, Brazil."
-      },
-      {
-        "author_name": "Fernando Lucas Melo",
-        "author_inst": "Baculovirus Laboratory, Department of Cell Biology, Institute of Biological Sciences, University of Brasilia, Brasilia, Distrito Federal, 70910-900, Brazil."
-      },
-      {
-        "author_name": "Aline Belmok",
-        "author_inst": "Baculovirus Laboratory, Department of Cell Biology, Institute of Biological Sciences, University of Brasilia, Brasilia, Distrito Federal, 70910-900, Brazil."
-      },
-      {
-        "author_name": "Jucimaria Dantas Galvao",
-        "author_inst": "Central Public Health Laboratory of the State of Tocantins, Palmas, Tocantins, 77054-970, Brazil"
-      },
-      {
-        "author_name": "Sirlene Borges Damasceno",
-        "author_inst": "Central Public Health Laboratory of the State of Tocantins, Palmas, Tocantins, 77054-970, Brazil"
-      },
-      {
-        "author_name": "Tereza Cristina Vieira de Rezende",
-        "author_inst": "Central Public Health Laboratory of the State of Tocantins, Palmas, Tocantins, 77054-970, Brazil"
+        "author_name": "Adebiyi Sobitan",
+        "author_inst": "Howard University College of Arts and Sciences"
       },
       {
-        "author_name": "Miguel de Souza Andrade",
-        "author_inst": "Baculovirus Laboratory, Department of Cell Biology, Institute of Biological Sciences, University of Brasilia, Brasilia, Distrito Federal, 70910-900, Brazil"
+        "author_name": "Vidhyanand Mahase",
+        "author_inst": "Howard University College of Arts and Sciences"
       },
       {
-        "author_name": "Bergmann Morais Ribeiro",
-        "author_inst": "Baculovirus Laboratory, Department of Cell Biology, Institute of Biological Sciences, University of Brasilia, Brasilia, Distrito Federal, 70910-900, Brazil"
+        "author_name": "Raina Rhoades",
+        "author_inst": "Howard University College of Arts and Sciences"
       },
       {
-        "author_name": "Jose Carlos Ribeiro Junior",
-        "author_inst": "Postgraduate Program in Animal Health and Public Health in the Tropics, Federal University of Tocantins, Araguaina, Tocantins, 77804-970, Brazil"
+        "author_name": "Dejaun Williams",
+        "author_inst": "Howard University College of Arts and Sciences"
       },
       {
-        "author_name": "Rogerio Fernandes Carvalho",
-        "author_inst": "Postgraduate Program in Animal Health and Public Health in the Tropics, Federal University of Tocantins, Araguaina, Tocantins, 77804-970, Brazil"
+        "author_name": "Dongxiao Liu",
+        "author_inst": "Howard University College of Medicine"
       },
       {
-        "author_name": "Monike da Silva Oliveira",
-        "author_inst": "Postgraduate Program in Tropical Medicine and Public Health, Federal University of Goias, Goiania, Goias, 74690-900, Brazil."
+        "author_name": "Yixin Xie",
+        "author_inst": "The University of Texas at El Paso"
       },
       {
-        "author_name": "Isac Gabriel Cunha dos Santos",
-        "author_inst": "Postgraduate Program in Animal Health and Public Health in the Tropics, Federal University of Tocantins, Araguaina, Tocantins, 77804-970, Brazil"
+        "author_name": "Lin Li",
+        "author_inst": "The University of Texas at El Paso"
       },
       {
-        "author_name": "Fernando Rosado Spilki",
-        "author_inst": "One Health Laboratory, Feevale Techpark, Feevale University, Campo Bom, Rio Grande do Sul, 93700-000, Brazil and Molecular Microbiology Laboratory, Feevale Univ"
+        "author_name": "Qiyi Tang",
+        "author_inst": "Howard University College of Medicine"
       },
       {
-        "author_name": "Fabricio Souza Campos",
-        "author_inst": "Bioinformatics and Biotechnology Laboratory, Campus of Gurupi, Federal University of Tocantins, Gurupi, Tocantins, 77410-570, Brazil"
+        "author_name": "Shaolei Teng",
+        "author_inst": "Howard University College of Arts and Sciences"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "genomics"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.06.29.450452",
@@ -651040,109 +654419,21 @@
     "category": "pediatrics"
   },
   {
-    "rel_doi": "10.1101/2021.06.24.21259087",
-    "rel_title": "Pre-activated anti-viral innate immunity in the upper airways controls early SARS-CoV-2 infection in children",
+    "rel_doi": "10.1101/2021.06.23.21259394",
+    "rel_title": "Macro-Level Drivers of SARS-CoV-2 Transmission: A Data-Driven Analysis of Factors Contributing to Epidemic Growth During the First Wave of outbreaks in the United States",
     "rel_date": "2021-06-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.24.21259087",
-    "rel_abs": "Children are consistently reported to have reduced SARS-CoV-2 infection rates and a substantially lower risk for developing severe COVID-19. However, the molecular mechanisms underlying protection against COVID-19 in younger age groups remain widely unknown. Here, we systematically characterized the single-cell transcriptional landscape in the upper airways in SARS-CoV-2 negative and age-matched SARS-CoV-2 positive children (n=42) and corresponding samples from adults (n=44), covering an age range of four weeks to 77 years. Children displayed higher basal expression of the relevant pattern recognition receptor (PRR) pathways in upper airway epithelial cells, macrophages, and dendritic cells, resulting in stronger innate antiviral responses upon SARS-CoV-2 infection compared to adults. We further detected distinct immune cell subpopulations with an overall dominance of neutrophils and a population of cytotoxic T cells occurring predominantly in children. Our study provides evidence that the airway epithelial and mucosal immune cells of children are pre-activated and primed for virus sensing, resulting in a stronger early innate antiviral responses to SARS-CoV-2 infection compared to adults.",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.23.21259394",
+    "rel_abs": "BackgroundMany questions remain unanswered about how SARS-CoV-2 transmission is influenced by aspects of the economy, environment, and health. A better understanding of how these factors interact can help us to design early health prevention and control strategies, and develop better predictive models for public health risk management of SARS-CoV-2. This study examines the associations between COVID-19 epidemic growth and macro-level determinants of transmission such as climate, socio-economic factors, demographic factors, and population health, during the first wave of outbreaks in the United States.\n\nMethodsA spatial-temporal data-set was created by collating information from a variety of data sources including the Johns Hopkins Universitys Centre for Systems Science and Engineering, the United States Census Bureau, the USDA Economic Research Service, the United States EPA, the National Climatic Data Center, the CDC and the Oxford COVID-19 Government Response Tracker (OxCGRT). A unique data-driven study design was implemented that allows us to assess the relationship between COVID-19 case and death epidemic doubling times and explanatory variables using a Generalized Additive Model (GAM).\n\nResultsThe main factors associated with case doubling times are higher population density, home overcrowding, manufacturing, and recreation industries. Poverty was also an important predictor of faster epidemic growth perhaps because of factors associated with in-work poverty-related conditions, although poverty is also a predictor of poor population health which is likely driving case and death reporting. Air pollution and diabetes were other important drivers of case reporting. Warmer temperatures are associated with slower epidemic growth, which is most likely explained by human behaviors associated with warmer locations i.e ventilating homes and workplaces. and socializing outdoors. The main factors associated with death doubling times were population density, poverty older age, diabetes, and air pollution. Temperature was also slightly significant slowing death doubling times.\n\nConclusionsSuch findings help underpin current understanding of the disease epidemiology and also supports current policy and advice recommending ventilation of homes, work-spaces, and schools, along with social distancing and mask-wearing. The results also suggest that states which adopted more stringent containment measures early on did have some success suppressing the virus. We can presume that if this was replicated at a federal level, much better outcomes would have been observed across the United States.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Jennifer Loske",
-        "author_inst": "Molecular Epidemiology Unit, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Jobst R\u00f6hmel",
-        "author_inst": "Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Soeren Lukassen",
-        "author_inst": "Center for Digital Health, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Sebastian Stricker",
-        "author_inst": "Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Vladimir Gon\u00e7alves Magalh\u00e3es",
-        "author_inst": "Research group Dynamics of Early Viral Infection and the Innate Antiviral Response, division F170, German Cancer Research Center (DKFZ)"
-      },
-      {
-        "author_name": "Johannes Liebig",
-        "author_inst": "Center for Digital Health, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Robert Lorenz Chua",
-        "author_inst": "Center for Digital Health, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Loreen Th\u00fcrmann",
-        "author_inst": "Molecular Epidemiology Unit, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Marey Messingschlager",
-        "author_inst": "Molecular Epidemiology Unit, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Anke Seegebarth",
-        "author_inst": "Molecular Epidemiology Unit, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Bernd Timmermann",
-        "author_inst": "Max Planck Institute for Molecular Genetics, Berlin"
-      },
-      {
-        "author_name": "Sven Klages",
-        "author_inst": "Max Planck Institute for Molecular Genetics, Berlin"
-      },
-      {
-        "author_name": "Markus Ralser",
-        "author_inst": "Institute of Biochemistry, Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Birgit Sawitzki",
-        "author_inst": "Institute of Medical Immunology,  Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Leif Erik Sander",
-        "author_inst": "Department of Infectious Diseases and Respiratory Medicine,  Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Victor M Corman",
-        "author_inst": "Institute of Virology, Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Christian Conrad",
-        "author_inst": "Center for Digital Health, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Sven Laudi",
-        "author_inst": "Department of Anesthesiology and Intensive Care, University Hospital Leipzig"
-      },
-      {
-        "author_name": "Marco Binder",
-        "author_inst": "Research group Dynamics of Early Viral Infection and the Innate Antiviral Response, division F170, German Cancer Research Center (DKFZ),"
-      },
-      {
-        "author_name": "Saskia Trump",
-        "author_inst": "Molecular Epidemiology Unit, Berlin Institute of Health at Charite - Universitatsmedizin Berlin Center for Digital Health, Berlin Institute of Health at Charite"
-      },
-      {
-        "author_name": "Roland Eils",
-        "author_inst": "Center for Digital Health, Berlin Institute of Health at Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Marcus Mall",
-        "author_inst": "Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Charite - Universitatsmedizin Berlin"
-      },
-      {
-        "author_name": "Irina Lehmann",
-        "author_inst": "Molecular Epidemiology Unit, Berlin Institute of Health at Charite - Universitatsmedizin Berlin Center for Digital Health, Berlin Institute of Health at Charite"
+        "author_name": "Matthew Watts",
+        "author_inst": "ICTA-UAB"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -653894,25 +657185,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.06.24.21259444",
-    "rel_title": "Early warning signals predict emergence of COVID-19 waves",
+    "rel_doi": "10.1101/2021.06.24.21259469",
+    "rel_title": "Monitoring SARS-CoV-2 Populations in Wastewater by Amplicon Sequencing and Using the Novel Program SAM Refiner",
     "rel_date": "2021-06-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.24.21259444",
-    "rel_abs": "Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the initial emergence of disease outbreaks, offering hope that policy makers can make predictive rather than reactive management decisions. Here, using daily COVID-19 case data in combination with a novel, sequential analysis, we show that composite EWSs consisting of variance, autocorrelation, and return rate not only pre-empt the initial emergence of COVID-19 in the UK by 14 to 29 days, but also the following wave six months later. We also predict there is a high likelihood of a third wave as of the data available on 9th June 2021. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policy makers to improve the accuracy of time critical decisions based solely upon surveillance data.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.24.21259469",
+    "rel_abs": "Sequencing SARS-CoV-2 from wastewater has become a useful tool in monitoring the spread of variants. We use a novel computation workflow with SARS-CoV-2 amplicon sequencing in order to track wastewater populations of the virus. As part of this workflow, we developed a program for both variant reporting and removal of PCR generated chimeric sequences. With these methods, we are able to track viral population dynamics over time. We observe the emergence of the variants of concern B.1.1.7 and P.1, and their displacement of the D614G B.1 variant.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Duncan A O'Brien",
-        "author_inst": "University of Bristol"
+        "author_name": "Devon A Gregory",
+        "author_inst": "University of Missouri"
       },
       {
-        "author_name": "Christopher F Clements",
-        "author_inst": "University of Bristol"
+        "author_name": "Chris G Wieberg",
+        "author_inst": "MO Department of Natural Resources"
+      },
+      {
+        "author_name": "Jeff Wenzel",
+        "author_inst": "MO Department of Health and Senior Services"
+      },
+      {
+        "author_name": "Chung-Ho Lin",
+        "author_inst": "University of Missouri"
+      },
+      {
+        "author_name": "Marc C Johnson",
+        "author_inst": "University of Missouri"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -655540,55 +658843,95 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.24.21259218",
-    "rel_title": "Long-term course of humoral and cellular immune responses in outpatients after SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2021.06.22.21259316",
+    "rel_title": "Investigating phenotypes of pulmonary COVID-19 recovery: a longitudinal observational prospective multicenter trial",
     "rel_date": "2021-06-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.24.21259218",
-    "rel_abs": "Characterisation of the naturally acquired B and T cell immune responses to SARS-CoV-2 is important for the development of public health and vaccination strategies to manage the burden of COVID-19 disease. We conducted a prospective, longitudinal analysis in COVID-19 recovered patients at various time points over a 10-month period in order to determine how circulating antibody levels and interferon-gamma (IFN-{gamma}) release by peripheral blood cells change over time following natural infection.\n\nFrom March 2020 till January 2021, we enrolled 412 adults mostly with mild or moderate disease course. At each study visit, subjects donated peripheral blood for testing of anti-SARS-CoV-2 IgG antibodies and IFN-{gamma} release after SARS-CoV-2 S-protein stimulation. Anti-SARS-CoV-2 IgG antibodies were identified in 316/412 (76.7%) of the patients and 215/412 (52.2%) had positive neutralizing antibody levels. Likewise, in 274/412 (66.5 %) positive IFN-{gamma} release and IgG antibodies were detected. With respect to time after infection, both IgG antibody levels and IFN-{gamma} concentrations decreased by about half within three hundred days. Statistically, IgG and IFN-{gamma} production were closely associated, but on an individual basis we observed patients with high antibody titres but low IFN-{gamma} levels and vice versa.\n\nOur data suggest that immunological reaction is acquired in most individuals after infection with SARS-CoV-2 and is sustained in the majority of patients for at least 10 months after infection. Since no robust marker for protection against COVID-19 exists so far, we recommend utilizing both, IgG and IFN-{gamma} release for an individual assessment of immunity status.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.22.21259316",
+    "rel_abs": "BackgroundCOVID-19 is associated with long-term pulmonary symptoms and may result in chronic pulmonary impairment. The optimal procedures to prevent, identify, monitor, and treat these pulmonary sequelae are elusive.\n\nResearch questionTo characterize the kinetics of pulmonary recovery, risk factors and constellations of clinical features linked to persisting radiological lung findings after COVID-19.\n\nStudy design and methodsA longitudinal, prospective, multicenter, observational cohort study including COVID-19 patients (n = 108). Longitudinal pulmonary imaging and functional readouts, symptom prevalence, clinical and laboratory parameters were collected during acute COVID-19 and at 60-, 100- and 180-days follow-up visits. Recovery kinetics and risk factors were investigated by logistic regression. Classification of clinical features and study participants was accomplished by k-means clustering, the k-nearest neighbors (kNN), and naive Bayes algorithms.\n\nResultsAt the six-month follow-up, 51.9% of participants reported persistent symptoms with physical performance impairment (27.8%) and dyspnea (24.1%) being the most frequent. Structural lung abnormalities were still present in 45.4% of the collective, ranging from 12% in the outpatients to 78% in the subjects treated at the ICU during acute infection. The strongest risk factors of persisting lung findings were elevated interleukin-6 (IL6) and C-reactive protein (CRP) during recovery and hospitalization during acute COVID-19. Clustering analysis revealed association of the lung lesions with increased anti-S1/S2 antibody, IL6, CRP, and D-dimer levels at the early follow-up suggesting non-resolving inflammation as a mechanism of the perturbed recovery.\n\nFinally, we demonstrate the robustness of risk class assignment and prediction of individual risk of delayed lung recovery employing clustering and machine learning algorithms.\n\nInterpretationSeverity of acute infection, and systemic inflammation is strongly linked to persistent post-COVID-19 lung abnormality. Automated screening of multi-parameter health record data may assist the identification of patients at risk of delayed pulmonary recovery and optimize COVID-19 follow-up management.\n\nClinical Trial RegistrationClinicalTrials.gov: NCT04416100",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Julia Schiffner",
-        "author_inst": "University of Luebeck, Center for Infection and Inflammation Research, Luebeck, Germany"
+        "author_name": "Thomas Sonnweber",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
       },
       {
-        "author_name": "Insa Backhaus",
-        "author_inst": "Institute of Medical Sociology, Centre for Health and Society, Medical Faculty and University Hospital, Heinrich-Heine-University, Duesseldorf, Germany"
+        "author_name": "Piotr Tymoszuk",
+        "author_inst": "Data Analytics As a Service Tirol"
       },
       {
-        "author_name": "Jens Rimmele",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
+        "author_name": "Sabina Sachanic",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
       },
       {
-        "author_name": "Soeren Schulz",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
+        "author_name": "Anna Boehm",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
       },
       {
-        "author_name": "Till Moehlenkamp",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
+        "author_name": "Alex Pizzini",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
       },
       {
-        "author_name": "Julia Maria Klemens",
-        "author_inst": "Institute for Experimental Immunology, affiliated to EUROIMMUN Medizinische Labordiagnostika AG, Luebeck, Germany"
+        "author_name": "Anna Luger",
+        "author_inst": "Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria"
       },
       {
-        "author_name": "Dorinja Zapf",
-        "author_inst": "Institute for Experimental Immunology, affiliated to EUROIMMUN Medizinische Labordiagnostika AG, Luebeck, Germany"
+        "author_name": "Christoph Schwabl",
+        "author_inst": "Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria"
       },
       {
-        "author_name": "Werner Solbach",
-        "author_inst": "University of Luebeck, Center for Infection and Inflammation Research, Luebeck, Germany"
+        "author_name": "Manfred Nairz",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
       },
       {
-        "author_name": "Alexander Mischnik",
-        "author_inst": "Health Protection Authority, Luebeck, Germany"
+        "author_name": "Kurz Katharina",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Sabine Koppelstaetter",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Magdalena Aichner",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Puchner Bernhard",
+        "author_inst": "The Karl Landsteiner Institute, Reha Zentrum Muenster, Muenster, Austria"
+      },
+      {
+        "author_name": "Alexander Egger",
+        "author_inst": "Central Institute of Medical and Chemical Laboratory Diagnostics, University Hospital Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Gregor Hoermann",
+        "author_inst": "Central Institute of Medical and Chemical Laboratory Diagnostics, University Hospital Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Ewald Ewald Woell",
+        "author_inst": "Department of Internal Medicine, St. Vinzenz Hospital, Zams, Austria"
+      },
+      {
+        "author_name": "Guenter Weiss",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Gerlig Widmann",
+        "author_inst": "Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Ivan Tancevski",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
+      },
+      {
+        "author_name": "Judith Loeffler-Ragg",
+        "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck, Innsbruck, Austria"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.06.21.21259213",
@@ -657294,17 +660637,41 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2021.06.23.449627",
-    "rel_title": "E484K and N501Y SARS-CoV 2 Spike Mutants Increase ACE2 Recognition but Reduce Affinity for Neutralizing Antibody",
+    "rel_doi": "10.1101/2021.06.23.449535",
+    "rel_title": "Integrative COVID-19 Biological Network Inference with Probabilistic Core Decomposition",
     "rel_date": "2021-06-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.23.449627",
-    "rel_abs": "SARS-CoV2 mutants emerge as variants of concern (VOC) due to altered selection pressure and rapid replication kinetics. Among them, lineages B.1.1.7, B.1.351, and P.1 contain a key mutation N501Y. B.1.135 and P.1 lineages have another mutation, E484K. Here, we decode the effect of these two mutations on the host receptor, ACE2, and neutralizing antibody (B38) recognition. The gain in binding affinity for the N501Y RBD mutant to the ACE2 is attributed to improved {pi}-{pi} stacking and {pi}-cation interactions. The enhanced receptor affinity of the E484K mutant is caused due to the formation of a specific hydrogen bond and salt-bridge interaction with Glu75 of ACE2. Notably, both the mutations reduce the binding affinity for B38 due to the loss of several hydrogen-bonding interactions. The insights obtained from the study are crucial to interpret the increased transmissibility and reduction in the neutralization efficacy of rapidly emerging SARS-CoV2 VOCs.",
-    "rel_num_authors": 1,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.23.449535",
+    "rel_abs": "The SARS-CoV-2 coronavirus is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein-protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database, the PPI network, and other experimentally validated results. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the integrated experimentally validated results in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs, and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The majority types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to the integrated experimentally validated nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Sandipan Chakraborty",
-        "author_inst": "Amity University, Kolkata"
+        "author_name": "Yang Guo",
+        "author_inst": "University of Victoria"
+      },
+      {
+        "author_name": "Fatemeh Esfahani",
+        "author_inst": "University of Victoria"
+      },
+      {
+        "author_name": "Xiaojian Shao",
+        "author_inst": "National Research Council Canada"
+      },
+      {
+        "author_name": "Venkatesh Srinivasan",
+        "author_inst": "University of Victoria"
+      },
+      {
+        "author_name": "Alex Thomo",
+        "author_inst": "University of Victoria"
+      },
+      {
+        "author_name": "Li Xing",
+        "author_inst": "University of Saskatchewan"
+      },
+      {
+        "author_name": "Xuekui Zhang",
+        "author_inst": "University of Victoria"
       }
     ],
     "version": "1",
@@ -658976,39 +662343,243 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.23.449583",
-    "rel_title": "The Influence of Public Health Faculty on College and University Plans during the COVID-19 Pandemic",
-    "rel_date": "2021-06-23",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.23.449583",
-    "rel_abs": "The purpose of this study was to determine whether the institutional presence of public health faculty within colleges and universities influenced operational plans for the fall semester of 2020. Using cross-sectional data collected by the College Crisis Initiative of Davidson College, six levels of instructional modalities (ranked from least to most restrictive) were compared between Council on Education of Public Health (CEPH)-accredited and non-CEPH-accredited 4-year institutions. Institutions with CEPH-accredited schools and programs were more likely to select some restrictive teaching modalities: 63.8% more likely to use hybrid/hyflex or more restrictive and 66.9% more likely to be primarily online (with some in person) or more restrictive. However, having CEPH-accredited programs did not push institutions to the most restrictive modalities. COVID-19 cases in county, enrollment, and political affiliation of the state governor were also found to influence instructional modality selection. While any ecological study has certain limitations, this study demonstrates that college and university fall plans appear to have been influenced by the presence of CEPH-accredited schools and programs of public health, and/or the input of their faculty. The influence of relevant faculty expertise on institutional decision-making can help inform college and university responses to future crises.",
-    "rel_num_authors": 5,
+    "rel_doi": "10.1101/2021.06.18.21258477",
+    "rel_title": "The polarity and specificity of SARS-CoV2 -specific T lymphocyte responses determine disease susceptibility",
+    "rel_date": "2021-06-22",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.18.21258477",
+    "rel_abs": "Optimal vaccination and immunotherapy against coronavirus disease COVID-19 relies on the in-depth comprehension of immune responses determining the individual susceptibility to be infected by SARS-CoV-2 and to develop severe disease. We characterized the polarity and specificity of circulating SARS-CoV-2-specific T cell responses against whole virus lysates or 186 unique peptides derived from the SARS-CoV-2 or SARS-CoV-1 ORFeome on 296 cancer-bearing and 86 cancer-free individuals who were either from the pre-COVID-19 era (67 individuals) or contemporary COVID-19-free (237 individuals) or who developed COVID-19 (78 individuals) in 2020/21. The ratio between the prototypic T helper 1 (TH1) cytokine, interleukin-2, and the prototypic T helper 2 (TH2) cytokine, interleukin-5 (IL-5), released from SARS-CoV-2-specific memory T cells measured in early 2020, among SARS-CoV-2-negative persons, was associated with the susceptibility of these individuals to develop PCR-detectable SARS-CoV-2 infection in late 2020 or 2021. Of note, T cells from individuals who recovered after SARS-CoV-2 re-infection spontaneously produced elevated levels of IL-5 and secreted the immunosuppressive TH2 cytokine interleukin-10 in response to SARS-CoV-2 lysate, suggesting that TH2 responses to SARS-CoV-2 are inadequate. Moreover, individuals susceptible to SARS-CoV-2 infection exhibited a deficit in the TH1 peptide repertoire affecting the highly mutated receptor binding domain (RBD) amino acids (331-525) of the spike protein. Finally, current vaccines successfully triggered anti-RBD specific TH1 responses in 88% healthy subjects that were negative prior to immunization. These findings indicate that COVID-19 protection relies on TH1 cell immunity against SARS-CoV-2 S1-RBD which in turn likely drives the phylogenetic escape of the virus. The next generation of COVID-19 vaccines should elicit high-avidity TH1 (rather than TH2)-like T cell responses against the RBD domain of current and emerging viral variants.",
+    "rel_num_authors": 56,
     "rel_authors": [
       {
-        "author_name": "David A Johnson",
-        "author_inst": "University of Louisville, School of Public Heath and Information Sciences"
+        "author_name": "Jean-Eudes FAHRNER",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Le Kremlin-Bic\u00eatre, France. Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France. Tran"
+      },
+      {
+        "author_name": "Agathe CARRIER",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "- Lyon COVID study group",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "Eric DE SOUSA",
+        "author_inst": "ImmunoTherapy/ImmunoSurgery, Champalimaud Foundation, Lisboa, Portugal."
       },
       {
-        "author_name": "Meredith Cahill",
-        "author_inst": "University of Louisville, School of Public Health and Information Sciences"
+        "author_name": "Damien DRUBAY",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement de Biostatistique et d'Epid\u00e9miologie, Gustave Roussy, Universit\u00e9 Paris-Saclay, Villejuif, France."
       },
       {
-        "author_name": "Sara Choate",
-        "author_inst": "University of Louisville, School of Public Health and Information Sciences"
+        "author_name": "Agathe DUBUISSON",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
       },
       {
-        "author_name": "Dave Roelfs",
-        "author_inst": "University of Louisville, College of Arts and Sciences, Department of Sociology"
+        "author_name": "Arthur GERAUD",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France. D\u00e9partement d'Innovation Th\u00e9rapeutique et d'Essais Pr\u00e9coc"
+      },
+      {
+        "author_name": "Anne-Ga\u00eblle GOUBET",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France. Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9d"
+      },
+      {
+        "author_name": "Gladys FERRERE",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
       },
       {
-        "author_name": "Sarah E Walsh",
-        "author_inst": "Eastern Michigan University, School of Health Sciences"
+        "author_name": "Yacine HADDAD",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Imran LAHMAR",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France. Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9d"
+      },
+      {
+        "author_name": "Marine MAZZENGA",
+        "author_inst": "Gustave Roussy, Villejuif, France 3Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Clea MELENOTTE",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Marion PICARD",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Cassandra THELEMAQUE",
+        "author_inst": "Gustave Roussy, Villejuif, France 3Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Luigi CERBONE",
+        "author_inst": "Gustave Roussy, Villejuif, France 9D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Joana R. L\u00c9RIAS",
+        "author_inst": "ImmunoTherapy/ImmunoSurgery, Champalimaud Foundation, Lisboa, Portugal."
+      },
+      {
+        "author_name": "Ariane LAPARRA",
+        "author_inst": "Gustave Roussy, Villejuif, France 9D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France. D\u00e9partement d'Innovation Th\u00e9rapeutique et d'Essais Pr\u00e9co"
+      },
+      {
+        "author_name": "Alice BERNARD",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France. D\u00e9partement d'Innovation Th\u00e9rapeutique et d'Essais Pr\u00e9coc"
+      },
+      {
+        "author_name": "Beno\u00eet KLOECKNER",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Marianne GAZZANO",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Fran\u00e7ois-Xavier DANLOS",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France.  Gustave Roussy, Villejuif, France3Institut National de la Sant\u00e9 et de la Recherche M\u00e9"
+      },
+      {
+        "author_name": "Safae TERRISSE",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Carolina ALVES COSTA SILVA",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France. Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9d"
+      },
+      {
+        "author_name": "Eugenie PIZZATO",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Caroline FLAMENT",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Pierre LY",
+        "author_inst": "Gustave Roussy, Villejuif, France 3Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, UMR1015, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Eric TARTOUR",
+        "author_inst": "Department of Immunology, H\u00f4pital Europ\u00e9en Georges Pompidou, AP-HP, Paris, France. 15PARCC, INSERM U970"
+      },
+      {
+        "author_name": "Lydia MEZIANI",
+        "author_inst": "Gustave Roussy, Villejuif, France"
+      },
+      {
+        "author_name": "Abdelhakim AHMED-BELKACEM",
+        "author_inst": "Univ Paris Est Creteil, INSERM U955, IMRB, Creteil, France"
+      },
+      {
+        "author_name": "Makoto MIYARA",
+        "author_inst": "Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, U1135, Centre d'Immunologie et des Maladies Infectieuses, H\u00f4pital Piti\u00e9-Salp\u00eatri\u00e8re, Assistance Publi"
+      },
+      {
+        "author_name": "Guy Gorochov",
+        "author_inst": "Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, U1135, Centre d'Immunologie et des Maladies Infectieuses, H\u00f4pital Piti\u00e9-Salp\u00eatri\u00e8re, Assistance Publi"
+      },
+      {
+        "author_name": "Fabrice BARLESI",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France. Aix Marseille University, CNRS, INSERM, CRCM, Marseille, "
+      },
+      {
+        "author_name": "Caroline PRADON",
+        "author_inst": "Gustave Roussy, Villejuif, France Centre de ressources biologiques, ET-EXTRA, Gustave Roussy, Villejuif, France. 20D\u00e9partement de Biologie M\u00e9dicale et Pathologi"
+      },
+      {
+        "author_name": "Emmanuelle GALLOIS",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement de Biologie M\u00e9dicale et Pathologie M\u00e9dicales, service de microbiologie, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Fanny POMMERET",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement Interdisciplinaire d'Organisation des Parcours Patients, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Emeline COLOMBA",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Pernelle LAVAUD",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Eric DEUTSCH",
+        "author_inst": "Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9dicale, U1030, Gustave Roussy, Villejuif, France. D\u00e9partement de Radioth\u00e9ra"
+      },
+      {
+        "author_name": "Bertrand GACHOT",
+        "author_inst": "Gustave Roussy, Villejuif, France Service de Pathologie Infectieuse, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Jean-Philippe SPANO",
+        "author_inst": "Department of Medical Oncology, Piti\u00e9-Salp\u00eatri\u00e8re Hospital, APHP, Sorbonne Universit\u00e9, Paris, France"
+      },
+      {
+        "author_name": "Mansouria Merad",
+        "author_inst": "Service de m\u00e9decine aigu\u00eb d'urgence en canc\u00e9rologie, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Florian SCOTTE",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement Interdisciplinaire d'Organisation des Parcours Patients, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Aur\u00e9lien MARABELLE",
+        "author_inst": "D\u00e9partement d'Oncologie M\u00e9dicale, Gustave Roussy, Villejuif, France. D\u00e9partement d'Innovation Th\u00e9rapeutique et d'Essais Pr\u00e9coces (DITEP), Gustave Roussy, Villej"
+      },
+      {
+        "author_name": "Frank GRISCELLI",
+        "author_inst": "Gustave Roussy, Villejuif, France D\u00e9partement de Biologie M\u00e9dicale et Pathologie M\u00e9dicales, service de microbiologie, Gustave Roussy, Villejuif, France."
+      },
+      {
+        "author_name": "Jean-Yves BLAY",
+        "author_inst": "Centre L\u00e9on B\u00e9rard, Lyon, France. Universit\u00e9 Claude Bernard, Lyon, France.34Unicancer, Paris, France"
+      },
+      {
+        "author_name": "Jean-Charles SORIA",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France. 2Gustave Roussy, Villejuif, France"
+      },
+      {
+        "author_name": "Fabrice ANDRE",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France. 2Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9"
+      },
+      {
+        "author_name": "Mathieu Chevalier",
+        "author_inst": "INSERM UMR 976, Institut de recherche Saint-Louis, Universit\u00e9 de Paris, Paris, France"
+      },
+      {
+        "author_name": "Sophie CAILLAT-ZUCMAN",
+        "author_inst": "Laboratory of Immunology, AP-HP, H\u00f4pital Saint Louis, INSERM UMR1149, Universit\u00e9 de Paris, Paris, France"
+      },
+      {
+        "author_name": "Florence FENOLLAR",
+        "author_inst": "Institut Hospitalo-Universitaire M\u00e9diterran\u00e9e Infection, Marseille, France"
+      },
+      {
+        "author_name": "Bernard LA SCOLA",
+        "author_inst": "Institut Hospitalo-Universitaire M\u00e9diterran\u00e9e Infection, Marseille, France."
+      },
+      {
+        "author_name": "Guido KROEMER",
+        "author_inst": "Centre de Recherche des Cordeliers, Equipe labelisee par la Ligue contre le cancer, Universite de Paris, Sorbonne Universite, Inserm U1138, Institut Universitai"
+      },
+      {
+        "author_name": "Markus MAEURER",
+        "author_inst": "13ImmunoTherapy/ImmunoSurgery, Champalimaud Foundation, Lisboa, Portugal. 45Medizinische Klinik, Johannes Gutenberg University Mainz, Germany. 46Division of Inf"
+      },
+      {
+        "author_name": "Lisa DEROSA",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France. 2Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9"
+      },
+      {
+        "author_name": "Laurence ZITVOGEL",
+        "author_inst": "Universit\u00e9 Paris-Saclay, Facult\u00e9 de M\u00e9decine, Le Kremlin-Bic\u00eatre, France. Gustave Roussy, Villejuif, France Institut National de la Sant\u00e9 et de la Recherche M\u00e9d"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "scientific communication and education"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.06.21.449165",
@@ -660110,39 +663681,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.06.19.21258892",
-    "rel_title": "Breastfeeding mother-child clinical outcomes after COVID-19 vaccination",
+    "rel_doi": "10.1101/2021.06.21.449352",
+    "rel_title": "Cytoplasmic tail truncation of SARS-CoV-2 Spike protein enhances titer of pseudotyped vectors but masks the effect of the D614G mutation",
     "rel_date": "2021-06-22",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.19.21258892",
-    "rel_abs": "This is a prospective cohort study of 88 lactating women in Singapore who received two doses of BNT162b2 vaccination (Pfizer/BioNTech), whereby outcomes of mother-child dyads within 28 days after the second vaccine dose were determined through a structured questionnaire. Minimal effects related to breastfeeding were reported in this cohort; 3 of 88 (3.4%) women had mastitis with 1 of 88 (1.1%) women experiencing breast engorgement. We report an incidence of lymphadenopathy in our cohort at 5 of 88 (5.7%). Reassuringly, there was no change in reported breastmilk supply after vaccination. The most common side effect was pain/redness/swelling at the injection site, which was experienced by 57 of 88 (64.8%) women. There were no serious adverse events of anaphylaxis and hospital admissions. No adverse symptoms were reported in 67 of 88 (76.1%) breastfed children.\n\nWhats known on this subjectTwo studies reported no serious adverse effects in both mother-child dyads after mRNA COVID-19 vaccination in mothers. Up to 61.9-67% lactating women experienced minor side effects.\n\nWhat this study addsWe report an incidence of lymphadenopathy in our cohort at 5.7% as opposed to 0.3% from the Pfizer-BioNTech COVID-19 trial. Reassuringly, there was no change in reported milk supply after vaccination. Minimal effects related to breastfeeding were reported in this cohort; 3 (3.4%) women had mastitis with 1 person experiencing breast engorgement. The most common side effect was pain/redness/swelling at the injection site at 64.8%, which was experienced by 57 of 88 (65%) women. No adverse symptoms were reported in the breastfed children.",
-    "rel_num_authors": 5,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.21.449352",
+    "rel_abs": "The high pathogenicity of SARS-CoV-2 requires it to be handled under biosafety level 3 conditions. Consequently, Spike protein pseudotyped vectors are a useful tool to study viral entry and its inhibition, with retroviral, lentiviral (LV) and vesicular stomatitis virus (VSV) vectors the most commonly used systems. Methods to increase the titer of such vectors commonly include concentration by ultracentrifugation and truncation of the Spike protein cytoplasmic tail. However, limited studies have examined whether such a modification also impacts the proteins function. Here, we optimized concentration methods for SARS-CoV-2 Spike pseudotyped VSV vectors, finding that tangential flow filtration produced vectors with more consistent titers than ultracentrifugation. We also examined the impact of Spike tail truncation on transduction of various cell types and sensitivity to convalescent serum neutralization. We found that tail truncation increased Spike incorporation into both LV and VSV vectors and resulted in enhanced titers, but had no impact on sensitivity to convalescent serum inhibition. In addition, we analyzed the effect of the D614G mutation, which became a dominant SARS-CoV-2 variant early in the pandemic. Our studies revealed that, similar to the tail truncation, D614G independently increases Spike incorporation and vector titers, but that this effect is masked by also including the cytoplasmic tail truncation. Therefore, the use of full-length Spike protein, combined with tangential flow filtration, is recommended as a method to generate high titer pseudotyped vectors that retain native Spike protein functions.\n\nIMPORTANCEPseudotyped viral vectors are useful tools to study the properties of viral fusion proteins, especially those from highly pathogenic viruses. The Spike protein of SARS-CoV-2 has been investigated using pseudotyped lentiviral and VSV vector systems, where truncation of its cytoplasmic tail is commonly used to enhance Spike incorporation into vectors and to increase the titers of the resulting vectors. However, our studies have shown that such effects can also mask the phenotype of the D614G mutation in the ectodomain of the protein, which was a dominant variant early in the COVID-19 pandemic. To better ensure the authenticity of Spike protein phenotypes when using pseudotyped vectors, we therefore recommend using full-length Spike proteins, combined with tangential flow filtration methods of concentration, if higher titer vectors are required.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Jia Ming Low",
-        "author_inst": "National University Hospital of Singapore"
+        "author_name": "Hsu-Yu Chen",
+        "author_inst": "University of Southern California"
       },
       {
-        "author_name": "Le Ye Lee",
-        "author_inst": "National University Hospital of Singapore"
+        "author_name": "Chun Huang",
+        "author_inst": "University of Southern California"
       },
       {
-        "author_name": "Yvonne Peng Mei Ng",
-        "author_inst": "National University Hospital of Singapore"
+        "author_name": "Lu Tian",
+        "author_inst": "University of Southern California"
       },
       {
-        "author_name": "Youjia Zhong",
-        "author_inst": "National University Hospital of Singapore"
+        "author_name": "Xiaoli Huang",
+        "author_inst": "University of Southern California"
       },
       {
-        "author_name": "Zubair Amin",
-        "author_inst": "National University Hospital of Singapore"
+        "author_name": "Chennan Zhang",
+        "author_inst": "University of Southern California"
+      },
+      {
+        "author_name": "George Nicholas Llewellyn",
+        "author_inst": "University of Southern California"
+      },
+      {
+        "author_name": "Geoffrey L. Rogers",
+        "author_inst": "University of Southern California"
+      },
+      {
+        "author_name": "Ya-Wen Chen",
+        "author_inst": "University of Southern California"
+      },
+      {
+        "author_name": "Paula M. Cannon",
+        "author_inst": "University of Southern California"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "pediatrics"
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.06.22.449355",
@@ -661844,25 +665431,53 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.06.15.21258529",
-    "rel_title": "The impact of temperature on the transmission potential and virulence of COVID-19 in Tokyo, Japan",
+    "rel_doi": "10.1101/2021.06.18.21258649",
+    "rel_title": "Large-scale screening of asymptomatic for SARS-CoV-2 variants of concern and rapid P.1 takeover, Curitiba, Brazil",
     "rel_date": "2021-06-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258529",
-    "rel_abs": "BackgroundAssessing the impact of temperature on COVID-19 epidemiology is critical for implementing non-pharmaceutical interventions. However, few studies have accounted for the nature of contagious diseases, i.e., their dependent happenings.\n\nAimWe aimed to quantify the impact of temperature on the transmissibility and virulence of COVID-19 in Tokyo, Japan. We employed two epidemiological measurements of transmissibility and severity: the effective reproduction number (Rt) and case fatality risk (CFR).\n\nMethodsWe used empirical surveillance data and meteorological data in Tokyo to estimate the Rt and time-delay adjusted CFR and to subsequently assess the nonlinear and delay effect of temperature on Rt and time-delay adjusted CFR.\n\nResultsFor Rt at low temperatures, the cumulative relative risk (RR) at first temperature percentile (3.3{degrees}C) was 1.3 (95% confidence interval (CI): 1.1-1.7). As for the virulence to humans, moderate cold temperatures were associated with higher CFR, and CFR also increased as the temperature rose. The cumulative RR at the 10th and 99th percentiles of temperature (5.8{degrees}C and 30.8{degrees}C) for CFR were 3.5 (95%CI: 1.3-10) and 6.4 (95%CI: 4.1-10.1).\n\nConclusionsThis study provided information on the effects of temperature on the COVID-19 epidemiology using Rt and time-delay adjusted CFR. Our results suggest the importance to take precautions to avoid infection in both cold and warm seasons to avoid severe cases of COVID-19. The results and proposed framework will also help in assessing possible seasonal course of COVID-19 in the future.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.18.21258649",
+    "rel_abs": "To provide a safer environment for individuals working on-site at the Federal University of Parana, Curitiba, Brazil, we performed a large-scale mass testing SARS-CoV-2 program coupled with variant genotyping using two PCR-based approaches. We observed a fast dominance of the Gamma variant, displacing other variants in less than three months.\n\nArticle Summary LineCoronavirus variants of concern may use asymptomatic population as silent spreaders to perform a fast displacement of previous established strains.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Lisa Yamasaki",
-        "author_inst": "Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Douglas Adamoski",
+        "author_inst": "Universidade Federal do Parana"
       },
       {
-        "author_name": "Hiroaki Murayama",
-        "author_inst": "International University of Health and Welfare"
+        "author_name": "Jaqueline Carvalho de Oliveira",
+        "author_inst": "Universidade Federal do Parana"
       },
       {
-        "author_name": "Masahiro Hashizume",
-        "author_inst": "Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo"
+        "author_name": "Ana Claudia Bonatto",
+        "author_inst": "Universidade Federal do Parana"
+      },
+      {
+        "author_name": "Roseli Wassem",
+        "author_inst": "Universidade Federal do Parana"
+      },
+      {
+        "author_name": "Meri Bordignon Nogueira",
+        "author_inst": "Universidade Federal do Parana"
+      },
+      {
+        "author_name": "Sonia Mara Raboni",
+        "author_inst": "Universidade Federal do Parana"
+      },
+      {
+        "author_name": "Edvaldo da Silva Trindade",
+        "author_inst": "Universidade Federal do Parana"
+      },
+      {
+        "author_name": "Emanuel Maltempi de Souza",
+        "author_inst": "Universidade Federal do Parana"
+      },
+      {
+        "author_name": "- SCB-UFPR COVID-19 team",
+        "author_inst": "Universidade Federal do Parana"
+      },
+      {
+        "author_name": "Daniela Fiori Gradia",
+        "author_inst": "Universidade Federal do Parana"
       }
     ],
     "version": "1",
@@ -664097,51 +667712,59 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.06.17.448816",
-    "rel_title": "Structural basis for the interaction of SARS-CoV-2 virulence factor nsp1 with Pol \u03b1 - Primase",
+    "rel_doi": "10.1101/2021.06.18.449086",
+    "rel_title": "Differences in IgG antibody responses following BNT162b2 and mRNA-1273 Vaccines",
     "rel_date": "2021-06-19",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.17.448816",
-    "rel_abs": "The molecular mechanisms that drive the infection by the SARS-CoV-2 coronavirus - the causative agent of the COVID-19 (Coronavirus disease-2019) pandemic - are under intense current scrutiny, to understand how the virus operates and to uncover ways in which the disease can be prevented or alleviated.\n\nRecent cell-based analyses of SARS-CoV-2 protein - protein interactions have mapped the human proteins targeted by the virus. The DNA polymerase  - primase complex or primosome - responsible for initiating DNA synthesis in genomic duplication - was identified as a target of nsp1 (non structural protein 1), a major virulence factor in the SARS-CoV-2 infection.\n\nHere, we report the biochemical characterisation of the interaction between nsp1 and the primosome and the cryoEM structure of the primosome - nsp1 complex. Our data provide a structural basis for the reported interaction between the primosome and nsp1. They suggest that Pol  - primase plays a part in the immune response to the viral infection, and that its targeting by SARS-CoV-2 aims to interfere with such function.",
-    "rel_num_authors": 8,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.18.449086",
+    "rel_abs": "Studies examining antibody responses by vaccine brand are lacking and may be informative for optimizing vaccine selection, dosage, and regimens. The purpose of this study is to assess IgG antibody responses following immunization with BNT162b2 (30 g S protein) and mRNA-1273 (100 g S protein) vaccines. A cohort of clinicians at a non-for-profit organization is being assessed clinically and serologically following immunization with BNT162b2 or mRNA-1273. IgG responses were measured at the Remington Laboratory by an IgG against the SARS-CoV-2 spike protein-receptor binding domain. Mixed-effect linear (MEL) regression modeling was used to examine whether the SARS-CoV-2 IgG level differed by vaccine brand, dosage, or days since vaccination. Among 532 SARS-CoV-2 seronegative participants, 530 (99.6%) seroconverted with either vaccine. After adjustments for age and gender MEL regression modeling revealed that the average IgG increased after the second dose compared to the first dose (p<0.001). Overall, titers peaked at week six for both vaccines. Titers were significantly higher for mRNA-1273 vaccine on days 14-20 (p < 0.05), 42-48 (p < 0.01), 70-76 (p < 0.05), 77-83 (p < 0.05), and higher for BNT162b2 vaccine on days 28-34 (p < 0.001). In two participants taking immunosuppressive drugs SARS-CoV-2 IgG remained negative. mRNA-1273 elicited both earlier and higher IgG antibody responses than BNT162b2, possibly due to the higher S-protein delivery. Prospective clinical and serological follow-up of defined cohorts such as this may prove useful in determining antibody protection and whether differences in antibody kinetics between the vaccines have manufacturing relevance and clinical significance.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Mairi L Kilkenny",
-        "author_inst": "University of Cambridge"
+        "author_name": "Jose Gilberto Montoya",
+        "author_inst": "Palo Alto Medical Foundation"
       },
       {
-        "author_name": "Charlotte E Veale",
-        "author_inst": "University of Cambridge"
+        "author_name": "Amy E Adams",
+        "author_inst": "Palo Alto Foundation Medical Group"
       },
       {
-        "author_name": "Amir Guppy",
-        "author_inst": "University of Cambridge"
+        "author_name": "Valerie Bonetti",
+        "author_inst": "Palo Alto Medical Foundation"
       },
       {
-        "author_name": "Steven W Hardwick",
-        "author_inst": "University of Cambridge"
+        "author_name": "Sien Deng",
+        "author_inst": "Center for Health Systems Research, Sutter Health, Palo Alto Medical Foundation Research Institute"
       },
       {
-        "author_name": "Dimitri Y Chirgadze",
-        "author_inst": "University of Cambridge"
+        "author_name": "Nan A Link",
+        "author_inst": "Palo Alto Foundation Medical Group"
       },
       {
-        "author_name": "Neil J Rzechorzek",
-        "author_inst": "Francis Crick Institute"
+        "author_name": "Suzanne Pertsch",
+        "author_inst": "Palo Alto Foundation Medical Group"
       },
       {
-        "author_name": "Joseph D Maman",
-        "author_inst": "University of Cambridge"
+        "author_name": "Kjerstie Olson",
+        "author_inst": "Dr Jack S. Remington Laboratory for Specialty Diagnostics"
       },
       {
-        "author_name": "Luca Pellegrini",
-        "author_inst": "University of Cambridge"
+        "author_name": "Martina Li",
+        "author_inst": "Center for Health Systems Research, Sutter Health, Palo Alto Medical Foundation Research Institute"
+      },
+      {
+        "author_name": "Ellis C Dillon",
+        "author_inst": "Center for Health Systems Research, Sutter Health, Palo Alto Medical Foundation Research Institute"
+      },
+      {
+        "author_name": "Dominick L. Frosch",
+        "author_inst": "Center for Health Systems Research, Sutter Health, Palo Alto Medical Foundation Research Institute"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "new results",
-    "category": "biophysics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.06.18.449054",
@@ -665867,55 +669490,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.06.15.21258928",
-    "rel_title": "Benefits of Surveillance Testing and Quarantine in a SARS-CoV-2 Vaccinated Population of Students on a University Campus",
+    "rel_doi": "10.1101/2021.06.16.21258981",
+    "rel_title": "Remdesivir to treat COVID-19: can dosing be optimized?",
     "rel_date": "2021-06-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258928",
-    "rel_abs": "Surveillance testing and quarantine have been effective measures for limiting SARS-CoV-2 transmission on university campuses. However, the importance of these measures needs to be re-evaluated in the context of a complex and rapidly changing environment that includes vaccines, variants, and waning immunity. Also, recent guidelines from the CDC suggest that vaccinated students do not need to participate in surveillance testing. We used an agent-based SEIR model to evaluate the utility of surveillance testing and quarantine in a fully vaccinated student population where vaccine effectiveness may be impacted by the type of vaccination, the presence of variants, and the loss of vaccine-induced or natural immunity over time. We found that weekly surveillance testing at 90% vaccine effectiveness only marginally reduces viral transmission as compared to no testing. However, at 50%-75% effectiveness, surveillance testing can provide over 10-fold reduction in the number of infections on campus over the course of the semester. We also show that a 10-day quarantine protocol for exposures has limited effect on infections until vaccine effectiveness drops to 50%, and that increased surveillance testing for exposures is at least as effective as quarantine at limiting infections. Together these findings provide a foundation for universities to design appropriate mitigation protocols for the 2021-2022 academic year.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.16.21258981",
+    "rel_abs": "The antiviral remdesivir has been approved by regulatory bodies such as EMA and FDA for the treatment of COVID-19. However, its efficacy is debated and toxicity concerns might limit the therapeutic range of this drug. Computational models that aid in balancing efficacy and toxicity would be of great help. Parametrizing models is difficult because the prodrug remdesivir is metabolized to its active form (RDV-TP) upon cell entry, which complicates dose-activity relationships.\n\nHere, we employ a computational model that allows predicting drug efficacy based on the binding affinity of RDV-TP for its target polymerase in SARS-CoV-2. We identify an optimal infusion rate to maximize remdesivir efficacy. We also assess drug efficacy in suppressing both wild-type and resistant strains, and thereby selection of resistance.\n\nOur results differ from predictions using prodrug dose-response curves (pseudo-EC50s). We expect that reaching 90% inhibition (EC90) is insufficient to suppress SARS-CoV-2 in lungs. While standard dosing mildly inhibits viral polymerase and therefore likely reduces morbidity, we also expect selection for resistant mutants for most realistic parameter ranges. To increase efficacy and safeguard against resistance, we recommend continuing remdesivir use with companion antivirals and/or with dosing regimens that substantially increase the levels of RDV-TP.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Francis C. Motta",
-        "author_inst": "Department of Mathematical Sciences, Florida Atlantic University"
-      },
-      {
-        "author_name": "Kevin A. McGoff",
-        "author_inst": "Department of Mathematics and Statistics, University of North Carolina, Charlotte"
-      },
-      {
-        "author_name": "Anastasia Deckard",
-        "author_inst": "Office of Information Technology, Duke University"
-      },
-      {
-        "author_name": "Cameron R. Wolfe",
-        "author_inst": "Department of Medicine, Duke University School of Medicine"
-      },
-      {
-        "author_name": "M. Anthony Moody",
-        "author_inst": "Department of Pediatrics, Duke University School of Medicine"
-      },
-      {
-        "author_name": "Kyle Cavanaugh",
-        "author_inst": "Department of Family Medicine, Duke University School of Medicine"
-      },
-      {
-        "author_name": "Thomas N. Denny",
-        "author_inst": "Duke Human Vaccine Institute & Department of Medicine, Duke University School of Medicine"
-      },
-      {
-        "author_name": "John Harer",
-        "author_inst": "Department of Mathematics, Duke University"
+        "author_name": "Jessica M Conway",
+        "author_inst": "Penn State"
       },
       {
-        "author_name": "Steven B. Haase",
-        "author_inst": "Department of Biology, Duke University & Department of Medicine, Duke University School of Medicine"
+        "author_name": "Pia Abel zur Wiesch",
+        "author_inst": "Penn State"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pharmacology and therapeutics"
   },
   {
     "rel_doi": "10.1101/2021.06.16.21259019",
@@ -668265,67 +671860,55 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.15.448611",
-    "rel_title": "SARS-CoV-2 Viral Replication in a High Throughput Human Primary Epithelial Airway Organ Model",
+    "rel_doi": "10.1101/2021.06.12.21258829",
+    "rel_title": "The Spectre of SARS-CoV-2 in the Ambient Urban Natural Water in Ahmedabad and Guwahati: A Tale of Two Cities",
     "rel_date": "2021-06-16",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.15.448611",
-    "rel_abs": "COVID-19 emerged as a worldwide pandemic early in 2020, and at this writing has caused over 170 million cases and 3.7 million deaths worldwide, and almost 600,000 deaths in the United States. The rapid development of several safe and highly efficacious vaccines stands as one of the most extraordinary achievements in modern medicine, but the identification and administration of efficacious therapeutics to treat patients suffering from COVID-19 has been far less successful. A major factor limiting progress in the development of effective treatments has been a lack of suitable preclinical models for the disease, currently reliant upon various animal models and in vitro culture of immortalized cell lines. Here we report the first successful demonstration of SARS-CoV-2 infection and viral replication in a human primary cell-based organ-on-chip, leveraging a recently developed tissue culture platform known as PREDICT96. This successful demonstration of SARS-CoV-2 infection in human primary airway epithelial cells derived from a living donor represents a powerful new pathway for disease modeling and an avenue for screening therapeutic candidates in a high throughput platform.",
-    "rel_num_authors": 12,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.12.21258829",
+    "rel_abs": "COVID-19 positive patients can egest live SARS-CoV-2 virus and viral genome fragments through faecal matter and urine, raising concerns about viral transmission through faecal-oral route and/or contaminated aerosolized water. These worries are heightened in many low and middle income nations, where raw sewage is often dumped into surface waterways and open defecation betide. In this manuscript, we attempt to discern the presence of SARS-CoV-2 genetic material (ORF-1ab, N and S genes) in two urban cities of India viz., Ahmedabad, in western India with several WWTPs; and Guwahati in the north-eastern part of the country with no such treatment plants. The study was carried out to establish applicability of WBE for COVID-19 surveillance as a potential tool for public health monitoring at the community level. 25.8% and 20% of the surface water samples had detectable SARS-CoV-2 RNA load in Ahmedabad and Guwahati, respectively. The high concentration of gene (ORF-1ab - 800 copies/L for Sabarmati river, Ahmedabad and S-gene - 565 copies/L for Bharalu urban river, Guwahati) found in natural waters indicates WWTPs do not always completely remove the genetic material of the virus. The study shows the applicability of WBE surveillance of COVID-19 in cities with low sanitation as well as in rural areas. The method used in this study cannot detect the live viruses, hence further research is required to evaluate the transmission implication of COVID-19 via ambient water, if any.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC=\"FIGDIR/small/21258829v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@19a51dborg.highwire.dtl.DTLVardef@743707org.highwire.dtl.DTLVardef@1c8b608org.highwire.dtl.DTLVardef@26cd43_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LINatural urban waters show the presence of SARS-CoV-2 RNA.\nC_LIO_LILake water receiving runoff containing SARS-CoV-2 genes reflected positive sign early\nC_LIO_LIViral RNA in surface water reflects incomplete removal of gene fragments in WWTPs.\nC_LIO_LIResidence time and fate owing to viral RNA in natural waters needs further research.\nC_LI",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Christine R Fisher",
-        "author_inst": "Draper"
-      },
-      {
-        "author_name": "Felix Mba Medie",
-        "author_inst": "Draper"
-      },
-      {
-        "author_name": "Rebeccah J Luu",
-        "author_inst": "Draper"
-      },
-      {
-        "author_name": "Rob Gaibler",
-        "author_inst": "Draper"
+        "author_name": "Manish Kumar",
+        "author_inst": "IIT Gandhinagar"
       },
       {
-        "author_name": "Caitlin R Miller",
-        "author_inst": "Draper"
+        "author_name": "Payal Mazumder",
+        "author_inst": "IIT Guwahati, India"
       },
       {
-        "author_name": "Thomas J Mulhern",
-        "author_inst": "Draper"
+        "author_name": "Jyoti Prakash Deka",
+        "author_inst": "Guwahati University, Assam, India"
       },
       {
-        "author_name": "Vidhya Vijayakumar",
-        "author_inst": "Draper"
+        "author_name": "Vaibhav Srivastava",
+        "author_inst": "IIT Gandhinagar, India"
       },
       {
-        "author_name": "Elizabeth Marr",
-        "author_inst": "Draper"
+        "author_name": "Chandan Mahanta",
+        "author_inst": "IIT Guwahati, India"
       },
       {
-        "author_name": "Jehan Alladina",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Ritusmita Goswami",
+        "author_inst": "TISS, Guwahati"
       },
       {
-        "author_name": "Benjamin Medoff",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Shilangi Gupta",
+        "author_inst": "IIT Gandhinagar"
       },
       {
-        "author_name": "Jeffrey T Borenstein",
-        "author_inst": "Draper"
+        "author_name": "Madhvi Joshi",
+        "author_inst": "GBRC, Gandhinagar, India"
       },
       {
-        "author_name": "Ashley L Gard",
-        "author_inst": "Draper"
+        "author_name": "Algappan Ramanathan",
+        "author_inst": "JNU, New Delhi, India"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "bioengineering"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.06.16.448640",
@@ -670134,33 +673717,49 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.15.21258346",
-    "rel_title": "Antibody response after a single dose of ChAdOx1-nCOV (Covishield) vaccine in subjects with prior SARS-CoV2 infection: Is a single dose sufficient?",
+    "rel_doi": "10.1101/2021.06.14.21258871",
+    "rel_title": "SARS-CoV-2 Spike protein binding of glycated serum albumin - its potential role in the pathogenesis of the COVID-19 clinical syndromes and bias towards individuals with pre-diabetes/type 2 diabetes & metabolic diseases.",
     "rel_date": "2021-06-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258346",
-    "rel_abs": "It is crucial to know whether a single dose of vaccine against SARS-CoV-2 is sufficient to elicit immune response in previously infected people in India. A total of 121 participants (baseline seropositive 46 and seronegative 75) were included to study the immune response to ChAdOx1-nCOV (Covishield) vaccine in previously infected or uninfected people. IgG antibodies were estimated at three different time intervals, i.e. pre-vaccination, 25-35 days post 1st vaccination and 25-35 days post 2nd vaccination. The IgG antibody titre was significantly high among previous seropositive subjects with single dose of vaccine compared to seronegative group with both doses of vaccine respectively (4.59{+/-}1.04 vs 3.08{+/-}1.22, p-value: <0.0001).\n\nIn conclusion, a single dose of Covishield(R) vaccine might be sufficient to induce an effective immune responsein subjects with prior SARS-CoV2 infection. Stratifying vacinees based on their SARS-CoV2 IgG antibody titre before vaccination would help in meeting the increasing vaccine demand and could be effective to circumvent further wave of the pandemic in India.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258871",
+    "rel_abs": "Since the immune response to SARS-CoV2 infection requires antibody recognition of the Spike protein, we used MagMix, a semi-automated magnetic rack to reproducibly isolate patient plasma proteins bound to a pre-fusion stabilised Spike and nucleocapsid proteins conjugated to magnetic beads. Once eluted, MALDI-ToF mass spectrometry identified a range of immunoglobulins, but also in Spike protein magnetic beads we found a high affinity for human serum albumin. Careful mass comparison revealed a preferential capture of advanced glycation end product (AGE) glycated human serum albumin by the pre-fusion Spike protein.\n\nThe ability of bacteria and viruses to surround themselves with serum proteins is a recognised process of immune evasion. A lower serum albumin concentration is a reported feature of COVID-19 patients with severe symptoms and high probability of death. This binding preference of the Spike protein for AGE glycated serum albumin may contribute to immune evasion and influence the severity & pathology of SARS-COV2 towards acute respiratory distress. Thus, it can be hypothesised, contributing to the symptom severity bias and mortality risk for the elderly and those with (pre)diabetic and atherosclerotic/metabolic diseases who contract SARS-CoV2 infections.\n\nGraphic abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC=\"FIGDIR/small/21258871v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (43K):\norg.highwire.dtl.DTLVardef@2d9e7org.highwire.dtl.DTLVardef@1300c4corg.highwire.dtl.DTLVardef@1776193org.highwire.dtl.DTLVardef@a6ffc6_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Biswajyoti Borkakoty",
-        "author_inst": "ICMR Regional Medical Research Centre NE Region"
+        "author_name": "Jason K Iles",
+        "author_inst": "MAP Sciences"
+      },
+      {
+        "author_name": "Raminta Zmuidinaite",
+        "author_inst": "MAP Sciences"
       },
       {
-        "author_name": "Mandakini Das Sarmah",
-        "author_inst": "ICMR Regional Medical Research Centre NE Region"
+        "author_name": "Christoph Saddee",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Chandra Kanta Bhattacharjee",
-        "author_inst": "ICMR Regional Medical Research Centre NE Region"
+        "author_name": "Anna Gardiner",
+        "author_inst": "MAP Sciences"
       },
       {
-        "author_name": "Nargis Bali",
-        "author_inst": "Sher-i- Kasmir Institute of Medical Science, Jammu and Kasmir, India"
+        "author_name": "Jonathan Lacy",
+        "author_inst": "MAP Sciences"
       },
       {
-        "author_name": "Gayatri Gogoi",
-        "author_inst": "Assam Medical College and Hospital, Dibrugarh, Assam, India"
+        "author_name": "Stephen Harding",
+        "author_inst": "The Binding Site Group"
+      },
+      {
+        "author_name": "Jernej Ule",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Debra Roblett",
+        "author_inst": "The Francis Crick Insitute"
+      },
+      {
+        "author_name": "Raymond Kruse Iles",
+        "author_inst": "MAP Sciences"
       }
     ],
     "version": "1",
@@ -671373,43 +674972,59 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.11.21258564",
-    "rel_title": "Chronic fatigue and post-exertional malaise in people living with long COVID",
+    "rel_doi": "10.1101/2021.06.11.21258445",
+    "rel_title": "Estimating the Burden of SARS-CoV-2 among the Rohingya Refugees",
     "rel_date": "2021-06-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.11.21258564",
-    "rel_abs": "PurposePeople living with long COVID describe a high symptom burden, and a more detailed assessment of chronic fatigue and post-exertional malaise (PEM) may inform the development of rehabilitation recommendations. The aims of this study were to use validated questionnaires to measure the severity of fatigue and compare this with normative data and thresholds for clinical relevance in other diseases; measure and describe the impact of PEM; and assess symptoms of dysfunctional breathing, self-reported physical activity/sitting time, and health-related quality of life.\n\nMethodsThis was an observational study involving an online survey for adults living with long COVID (data collection from February-April, 2021) following a confirmed or suspected SARS-CoV-2 infection. Questionnaires included the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-F) and DePaul Symptom Questionnaire-Post-Exertional Malaise.\n\nResultsAfter data cleaning, n=213 participants were included in the analysis. Participants primarily identified as women (85.5%), aged 40-59 (78.4%), who had been experiencing long COVID symptoms for [&ge;]6 months (72.3%). The total FACIT-F score was 18{+/-}10 (where the score can range from 0-52, and a lower score indicates more severe fatigue), and 71.4% were experiencing chronic fatigue. Post-exertional symptom exacerbation affected most participants, and 58.7% met the scoring thresholds used in people living with myalgic encephalomyelitis/chronic fatigue syndrome. PEM occurred alongside a reduced capacity to work, be physically active, and function both physically and socially.\n\nConclusionLong COVID is characterized by chronic fatigue that is clinically relevant and is at least as severe as fatigue in several other clinical conditions, including cancer. PEM appears to be a common and significant challenge for the majority of this patient group. Patients, researchers, and allied health professionals are seeking information on safe rehabilitation for people living with long COVID, particularly regarding exercise. Fatigue and post-exertional symptom exacerbation must be monitored and reported in studies involving interventions for people with long COVID.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.11.21258445",
+    "rel_abs": "BackgroundSince the emergence of the COVID-19 pandemic, substantial concern has surrounded its impact among the Rohingya refugees living in the Kutupalong-Balukhali refugee camps in Bangladesh. Early modeling work projected a massive outbreak was likely after an introduction of the SARS-CoV-2 virus into the camps. Despite this, only 317 laboratory-confirmed cases and 10 deaths were reported through October 2020. While these official numbers portray a situation where the virus has been largely controlled, other sources contradict this, suggesting the low reported numbers to be a result of limited care seeking and testing, highlighting a population not willing to seek care or be tested. SARS-CoV-2 seroprevalence estimates from similar a timeframe in India (57%) and Bangladesh (74%) further sow doubt that transmission had been controlled. Here we explore multiple data sources to understand the plausibility of a much larger SARS-CoV-2 outbreak among the Rohingya refugees.\n\nMethodsWe used a mixed approach to analyze SARS-CoV-2 transmission using multiple available datasets. Using data from reported testing, cases, and deaths from the World Health Organization (WHO) and from WHOs Emergency Warning, Alert, and Response System, we characterized the probabilities of care seeking, testing, and being positive if tested. Unofficial death data, including reported pre-death symptoms, come from a community-based mortality survey conducted by the International Organization for Migration (IOM),) in addition to community health worker reported deaths. We developed a probabilistic inference framework, drawing on these data sources, to explore three scenarios of what might have happened among the Rohingya refugees.\n\nResultsAmong the 144 survey-identified deaths, 48 were consistent with suspected COVID-19. These deaths were consistent with viral exposures during Ramadan, a period of increased social contacts, and coincided with a spike in reported cases and testing positivity in June 2020. The age profile of suspected COVID-19 deaths mirrored that expected. Through the probability framework, we find that under each scenario, a substantial outbreak likely occurred, though the cumulative size and timing vary considerably. In conjunction with the reported and suspected deaths, the data suggest a large outbreak could have occurred early during spring 2020. Furthermore, while many mild and asymptomatic infections likely occurred, death data analyzed suggest there may have been significant unreported mortality.\n\nConclusionsWith the high population density, inability to home isolate adequately, and limited personal protective equipment, infection prevention and control in the Rohingya population is extremely challenging. Despite the low reported numbers of cases and deaths, our results suggest an early large-scale outbreak is consistent with multiple sources of data, particularly when accounting for limited care seeking behavior and low infection severity among this young population. While the currently available data do not allow us to estimate the precise incidence, these results indicate substantial unrecognized SARS-CoV-2 transmission may have occurred in these camps. However, until serological testing provides more conclusive evidence, we are only able to speculate about the extent of transmission among the Rohingya.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Rosie Twomey",
-        "author_inst": "University of Calgary"
+        "author_name": "Shaun A Truelove",
+        "author_inst": "Departments of International Health and Epidemiology, Johns Hopkins Bloomberg School of Public Health"
       },
       {
-        "author_name": "Jessica DeMars",
-        "author_inst": "Breath Well Physio"
+        "author_name": "Sonia A Hegde",
+        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health"
       },
       {
-        "author_name": "Kelli Franklin",
-        "author_inst": "Patient Partner"
+        "author_name": "Lori Niehaus",
+        "author_inst": "Department of International Health, Johns Hopkins Bloomberg School of Public Health"
       },
       {
-        "author_name": "S. Nicole Culos-Reed",
-        "author_inst": "University of Calgary"
+        "author_name": "Natalya Kostandova",
+        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health"
       },
       {
-        "author_name": "Jason Weatherald",
-        "author_inst": "University of Calgary"
+        "author_name": "Chiara Altare",
+        "author_inst": "Department of International Health, Johns Hopkins Bloomberg School of Public Health, Center for Humanitarian Health"
       },
       {
-        "author_name": "James G Wrightson",
-        "author_inst": "University of Calgary"
+        "author_name": "V. Bhargavi Rao",
+        "author_inst": "Medecins Sans Frontieres (MSF), London, UK"
+      },
+      {
+        "author_name": "Julianna Smith",
+        "author_inst": "MSF, Cox's Bazar, Bangladesh"
+      },
+      {
+        "author_name": "Philipp du Cros",
+        "author_inst": "Burnett Institute, Melbourne, Australia"
+      },
+      {
+        "author_name": "Andrew S. Azman",
+        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health; MSF, Geneva, Switzerland"
+      },
+      {
+        "author_name": "Paul Spiegel",
+        "author_inst": "Department of International Health, Johns Hopkins Bloomberg School of Public Health, Center for Humanitarian Health"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.06.10.21255008",
@@ -673179,39 +676794,51 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2021.06.08.21258533",
-    "rel_title": "The impact of co-circulating pathogens on SARS-CoV-2/COVID-19 surveillance. How concurrent epidemics may decrease true SARS-CoV-2 percent positivity.",
+    "rel_doi": "10.1101/2021.06.10.21254528",
+    "rel_title": "NEWS-2 score assessment of inpatient referral during the COVID 19 epidemic",
     "rel_date": "2021-06-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258533",
-    "rel_abs": "BackgroundCirculation of non-SARS-CoV-2 respiratory viruses during the COVID-19 pandemic may alter quality of COVID-19 surveillance, with possible consequences for real-time analysis and delay in implementation of control measures. Here, we assess the impact of an increased circulation of other respiratory viruses on the monitoring of positivity rates of SARS-CoV-2 and interpretation of surveillance data.\n\nMethodsUsing a multi-pathogen Susceptible-Exposed-Infectious-Recovered (SEIR) transmission model formalizing co-circulation of SARS-CoV-2 and another respiratory we assess how an outbreak of secondary virus may inflate the number of SARS-CoV-2 tests and affect the interpretation of COVID-19 surveillance data. Using simulation, we assess to what extent the use of multiplex PCR tests on a subsample of symptomatic individuals can support correction of the observed SARS-CoV-2 percent positive during other virus outbreaks and improve surveillance quality.\n\nResultsModel simulations demonstrated that a non-SARS-CoV-2 epidemic creates an artificial decrease in the observed percent positivity of SARS-CoV-2, with stronger effect during the growth phase, until the peak is reached. We estimate that performing one multiplex test for every 1,000 COVID-19 tests on symptomatic individuals could be sufficient to maintain surveillance of other respiratory viruses in the population and correct the observed SARS-CoV-2 percent positive.\n\nConclusionsThis study highlights that co-circulating respiratory viruses can disrupt SARS-CoV-2 surveillance. Correction of the positivity rate can be achieved by using multiplex PCR, and a low number of samples is sufficient to avoid bias in SARS-CoV-2 surveillance.\n\nSummaryCOVID-19 surveillance indicators may be impacted by increased co-circulation of other respiratory viruses delaying control measure implementation. Continued surveillance through multiplex PCR testing in a subsample of the symptomatic population may play a role in fixing this problem.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.10.21254528",
+    "rel_abs": "AimTo manage patients with suspected coronavirus disease (COVID-19) when they arrive at the hospital emergency department (ED), a clinical severity score is required to quickly identify patients requiring immediate hospital admission and close monitoring. The aim of this study was to evaluate, within the context of the pandemic, the performance of National Early Warning Score 2 (NEWS-2) to anticipate the admission of patients with suspected COVID-19 to a specialised emergency care unit.\n\nMethodsThis retrospective study was conducted on patients presenting at the COVID-19 entrance of the ED of the Vert-Galant private hospital (Paris, France) during the first national pandemic peak from March 20 to April 20, 2020. All patients completed a questionnaire and clinical data and vital signs were recorded. Statistical analysis and modelling were used to estimate the ability of different scores (NEWS-2, qSOFA, CRB-65) to predict hospital emergency admission and/or early COVID-19 diagnosis.\n\nResultsNEWS-2, with a cut off value of 5, predicted hospital admission with 82% sensitivity, 98% specificity and an area under the curve (AUC) of 96%. NEWS-2 was superior to qSOFA and CRB-65 scores for predicting hospital admission of COVID-19 patients. Multilinear or logistic regression analysis of clinical data did not improve this result.\n\nConclusionNEWS-2 is an excellent score to predict hospital admission of COVID-19 patients.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Aleksandra Kovacevic",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Valerie FAURE",
+        "author_inst": "Emergency Department, Hopital prive du Vert Galant Groupe Ramsey, Tremblay en France, France. tel. +33 1 86869300"
       },
       {
-        "author_name": "Rosalind M Eggo",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Marc SOURIS",
+        "author_inst": "Unit\u00e9 Mixte de Recherche Unit\u00e9 des virus \u00e9mergents (UVE Aix-Marseille Univ-IRD 190-INSERM 1207), Marseille 13005 France"
       },
       {
-        "author_name": "Marc Baguelin",
-        "author_inst": "Imperial College London"
+        "author_name": "Arnaud WILMET",
+        "author_inst": "Health for Development (H4D), 92 avenue Kl\u00e9ber, 75116 Paris, France"
       },
       {
-        "author_name": "Matthieu Domenech de Cell\u00e8s",
-        "author_inst": "Max Planck Institute for Infection Biology"
+        "author_name": "Franck BAUDINO",
+        "author_inst": "Health for Development (H4D), 92 avenue Kl\u00e9ber, 75116 Paris, France"
       },
       {
-        "author_name": "Lulla Opatowski",
-        "author_inst": "Univ Versailles Saint Quentin / Institut Pasteur / Inserm"
+        "author_name": "Albert BRIZIO",
+        "author_inst": "SMUR, Hopital Delafontaine, Centre Hospitalier de Saint Denis, Saint Denis, France"
+      },
+      {
+        "author_name": "Christopher MALHAIRE",
+        "author_inst": "Emergency Department, Hopital priv\u00e9 du Vert Galant Groupe Ramsey, Tremblay en France, France. tel. +33 1 86869300"
+      },
+      {
+        "author_name": "Francois-Xavier PECCAUD",
+        "author_inst": "Emergency Department, H\u00f4pital priv\u00e9 du Vert Galant Groupe Ramsey, Tremblay en France, France. tel. +33 1 86869300"
+      },
+      {
+        "author_name": "Jean-Paul GONZALEZ",
+        "author_inst": "School of Medicine, Georgetown University, Department of Microbiology & Immunology, Washington, DC 20057 USA."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "emergency medicine"
   },
   {
     "rel_doi": "10.1101/2021.06.08.21258523",
@@ -674941,89 +678568,129 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.06.11.448011",
-    "rel_title": "B.1.1.7 and B.1.351 SARS-CoV-2 variants display enhanced Spike-mediated fusion",
+    "rel_doi": "10.1101/2021.06.10.447999",
+    "rel_title": "A combination of RBD and NTD neutralizing antibodies limits the generation of SARS-CoV-2 spike neutralization-escape mutants",
     "rel_date": "2021-06-11",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.11.448011",
-    "rel_abs": "Severe COVID-19 is characterized by lung abnormalities, including the presence of syncytial pneumocytes. Syncytia form when SARS-CoV-2 spike protein expressed on the surface of infected cells interacts with the ACE2 receptor on neighbouring cells. The syncytia forming potential of spike variant proteins remain poorly characterized. Here, we first assessed Alpha and Beta spread and fusion in cell cultures. Alpha and Beta replicated similarly to D614G reference strain in Vero, Caco-2, Calu-3 and primary airway cells. However, Alpha and Beta formed larger and more numerous syncytia. Alpha, Beta and D614G fusion was similarly inhibited by interferon induced transmembrane proteins (IFITMs). Individual mutations present in Alpha and Beta spikes differentially modified fusogenicity, binding to ACE2 and recognition by monoclonal antibodies. We further show that Delta spike also triggers faster fusion relative to D614G. Thus, SARS-CoV-2 emerging variants display enhanced syncytia formation.\n\nSynopsisThe Spike protein of the novel SARS-CoV-2 variants are comparative more fusogenic than the earlier strains. The mutations in the variant spike protein differential modulate syncytia formation, ACE2 binding, and antibody escape.\n\nO_LIThe spike protein of Alpha, Beta and Delta, in the absence of other viral proteins, induce more syncytia than D614G\nC_LIO_LIThe ACE2 affinity of the variant spike proteins correlates to their fusogenicity\nC_LIO_LIVariant associated mutations P681H, D1118H, and D215G augment cell-cell fusion, while antibody escape mutation E484K, K417N and {Delta}242-244 hamper it.\nC_LIO_LIVariant spike-mediated syncytia formation is effectively restricted by IFITMs\nC_LI",
-    "rel_num_authors": 18,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.10.447999",
+    "rel_abs": "Most known SARS-CoV-2 neutralizing antibodies (nAbs), including those approved by the FDA for emergency use, inhibit viral infection by targeting the receptor-binding domain (RBD) of the spike (S) protein. Variants of concern (VOC) carrying mutations in the RBD or other regions of S reduce the effectiveness of many nAbs and vaccines by evading neutralization. Therefore, therapies that are less susceptible to resistance are urgently needed. Here, we characterized the memory B-cell repertoire of COVID-19 convalescent donors and analyzed their RBD and non-RBD nAbs. We found that many of the non-RBD-targeting nAbs were specific to the N-terminal domain (NTD). Using neutralization assays with authentic SARS-CoV-2 and a recombinant vesicular stomatitis virus carrying SARS-CoV-2 S protein (rVSV-SARS2), we defined a panel of potent RBD and NTD nAbs. Next, we used a combination of neutralization-escape rVSV-SARS2 mutants and a yeast display library of RBD mutants to map their epitopes. The most potent RBD nAb competed with hACE2 binding and targeted an epitope that includes residue F490. The most potent NTD nAb epitope included Y145, K150 and W152. As seen with some of the natural VOC, the neutralization potencies of COVID-19 convalescent sera were reduced by 4-16-fold against rVSV-SARS2 bearing Y145D, K150E or W152R spike mutations. Moreover, we found that combining RBD and NTD nAbs modestly enhanced their neutralization potential. Notably, the same combination of RBD and NTD nAbs limited the development of neutralization-escape mutants in vitro, suggesting such a strategy may have higher efficacy and utility for mitigating the emergence of VOC.\n\nImportanceThe US FDA has issued emergency use authorizations (EUAs) for multiple investigational monoclonal antibody (mAb) therapies for the treatment of mild to moderate COVID-19. These mAb therapeutics are solely targeting the receptor binding domain of the SARS-CoV-2 spike protein. However, the N-terminal domain of the spike protein also carries crucial neutralizing epitopes. Here, we show that key mutations in the N-terminal domain can reduce the neutralizing capacity of convalescent COVID-19 sera. We report that a combination of two neutralizing antibodies targeting the receptor binding and N-terminal domains may have higher efficacy and is beneficial to combat the emergence of virus variants.",
+    "rel_num_authors": 28,
     "rel_authors": [
       {
-        "author_name": "Maaran Michael Rajah",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Denise Haslwanter",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Mathieu Hubert",
-        "author_inst": "Institut Pasteur"
+        "author_name": "M. Eugenia Dieterle",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Elodie Bishop",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Anna Z. Wec",
+        "author_inst": "Adimab LLC"
       },
       {
-        "author_name": "Nell Saunders",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Mrunal Sakharkar",
+        "author_inst": "Adimab LLC"
       },
       {
-        "author_name": "R\u00e9my Robinot",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Catalina Florez",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Ludivine Grzelak",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Karen Tong",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Delphine Planas",
-        "author_inst": "Institut Pasteur"
+        "author_name": "C. Garrett Rappazzo",
+        "author_inst": "Adimab LLC"
       },
       {
-        "author_name": "Jeremy Dufloo",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Gorka Lasso",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Stacy Gellenoncourt",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Olivia Vergnolle",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Alice Bongers",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Ariel S. Wirchnianski",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Marija Zivaljic",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Robert H. Bortz III",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Cyril Planchais",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Ethan Laudermilch",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Florence Guivel-Benhassine",
-        "author_inst": "Institut Pasteur"
+        "author_name": "J. Maximilian Fels",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Fran\u00e7oise Porrot",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Amanda Mengotto",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Hugo Mouquet",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Ryan J Malonis",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Lisa Chakrabarti",
-        "author_inst": "Institut Pasteur"
+        "author_name": "George I Georgiev",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Julian Buchrieser",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Jose Quiroz",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Olivier Schwartz",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Daniel Wrapp",
+        "author_inst": "University of Texas at Austin"
+      },
+      {
+        "author_name": "Nianshuang Wang",
+        "author_inst": "University of Texas"
+      },
+      {
+        "author_name": "Jason Barnhill",
+        "author_inst": "United States Military Academy at West Point"
+      },
+      {
+        "author_name": "John M Dye",
+        "author_inst": "US Army Medical Research Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Jason S. McLellan",
+        "author_inst": "The University of Texas at Austin"
+      },
+      {
+        "author_name": "Johanna P. Daily",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Jonathan R. Lai",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Andrew S Herbert",
+        "author_inst": "USAMRIID"
+      },
+      {
+        "author_name": "Laura Walker",
+        "author_inst": "Adimab LLC"
+      },
+      {
+        "author_name": "Kartik Chandran",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Rohit K. Jangra",
+        "author_inst": "Albert Einstein College of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
     "category": "microbiology"
   },
@@ -676831,27 +680498,63 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.06.06.21258425",
-    "rel_title": "Functional dependence of COVID-19 growth rate on lockdown conditions and rate of vaccination.",
+    "rel_doi": "10.1101/2021.06.09.21258609",
+    "rel_title": "Depressive and anxiety symptoms and COVID-19-related factors among men and women in Nigeria",
     "rel_date": "2021-06-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.06.21258425",
-    "rel_abs": "It is shown that derived from the solution of differential equations analytical model adequately describes development epidemics with changes in both lockdown conditions and the effective rate of mass vaccination of the population. As in previous studies, the control calculations are in good agreement with observations at all stages of epidemic growth. One of the two model coefficients is uniquely related to the lockdown efficiency parameter. We obtained an approximate correlation between this parameter and the main conditions of lockdown, in particular, physical distancing, reduction in social contacts and strictness of the mask regime.\n\nThe calculation of the incident over a seven-day period using the proposed model is in good agreement with the observational data. Analysis of both curves shows that a better agreement can be obtained by taking into account the lag time of the epidemic response of about 10 days.\n\nFrom the reverse calculation a time-varying curve of the infection rate associated with the \"new\" virus strain under mutation conditions is obtained, which is qualitatively confirmed by the sequencing data.\n\nBased on these studies, it is possible to conclude that the ASILV analytical model developed here can be used to reliably and promptly predict epidemic development under conditions of lockdown and mass vaccination without the use of numerical methods.\n\nThe functional relationships identified allow us to conduct a rapid analysis of the impact of each of the model parameters on the overall process of the epidemic.\n\nIn contrast to previous studies, the calculations of the proposed model were performed using EXCEL, rather than a standard calculator. This is due to the need to account for multiple changes in lockdown conditions and vaccination rates.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.09.21258609",
+    "rel_abs": "Despite the greater adverse economic impacts in low and middle-income (LAMI) compared to high-income countries, fewer studies have investigated the associations between COVID-19-related stressor and mental health in LAMI countries. The objectives of this study were to determine the associations between COVID-19-related stressors and anxiety and depressive symptoms while controlling for known risk and protective factors and to investigate any sex differences. An online survey was carried out to assess sociodemographic, psychosocial (previous mental health conditions, sexual orientation, intimate partner violence and perceived social support) and COVID-19-related variables. Hierarchical linear regression was carried out with anxiety and depressive symptoms as separate outcomes. Of the COVID-19-related factors, testing positive for COVID-19 infection, having COVID-19 symptoms, having other medical conditions, self-isolating due to COVID-19 symptoms, worry about infection, perception of the pandemic as a threat to income and isolation during the lockdown were significantly associated with higher anxiety and depressive symptoms. Of these, worry about infection, isolation during lockdown and disruption due to the pandemic retained independent associations with both outcomes. The variance in anxiety and depressive symptoms explained by COVID-19-related factors was larger in women (6.1% and respectively) compared to men (6.1% and respectively). COVID-19-related stressors are associated with higher anxiety and depressive symptoms, with these effects being larger in men compared to women. Enhancing social support can be an affordable strategy to mitigate this risk but this needs to be investigated using appropriate designs.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Felix Mairanowski",
-        "author_inst": "Husmann Rus"
+        "author_name": "Olakunle Ayokunmi Oginni",
+        "author_inst": "Department of Mental Health, Obafemi Awolowo University, Ile-Ife, Nigeria"
       },
       {
-        "author_name": "Denis Below",
-        "author_inst": "Potsdam Universitet"
+        "author_name": "Ibidunni O Oloniniyi",
+        "author_inst": "Department of Mental Health, Obafemi Awolowo University, Ile-Ife, Nigeria"
+      },
+      {
+        "author_name": "Olanrewaju Ibigbami",
+        "author_inst": "Department of Mental Health, Obafemi Awolowo University, Ile-Ife, Nigeria"
+      },
+      {
+        "author_name": "Victor Ugo",
+        "author_inst": "Mentally Aware Nigeria Initiative and United for Global Mental Health. London, United Kingdom"
+      },
+      {
+        "author_name": "Ayomipo Amiola",
+        "author_inst": "Mental Health Unit, Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria"
+      },
+      {
+        "author_name": "Adedotun Ogunbajo",
+        "author_inst": "Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United State of America"
+      },
+      {
+        "author_name": "Oladoyin Esan",
+        "author_inst": "Mental Health Unit, Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria"
+      },
+      {
+        "author_name": "Aderopo Adelola",
+        "author_inst": "Mental Health Unit, Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria"
+      },
+      {
+        "author_name": "Oluwatosin Daropale",
+        "author_inst": "Health Centre, Joseph Ayo Babalola University, Ikeji, Osun, Nigeria"
+      },
+      {
+        "author_name": "Matthew Ebuka",
+        "author_inst": "Mental Health Unit, Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria"
+      },
+      {
+        "author_name": "Boladale Mapayi",
+        "author_inst": "Department of Mental Health, Obafemi Awolowo University, Ile-Ife, Nigeria"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2021.06.08.21258593",
@@ -678849,151 +682552,39 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.06.09.447527",
-    "rel_title": "Second Generation Antibodies Neutralize Emerging SARS-CoV-2 Variants of Concern",
+    "rel_doi": "10.1101/2021.06.09.21258553",
+    "rel_title": "Analysis of cell-mediated immunity in people with long Covid.",
     "rel_date": "2021-06-09",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.09.447527",
-    "rel_abs": "Recently emerged SARS-CoV-2 variants show resistance to some antibodies that were authorized for emergency use. We employed hybridoma technology combined with authentic virus assays to develop second-generation antibodies, which were specifically selected for their ability to neutralize new variants of SARS-CoV-2. AX290 and AX677, two monoclonal antibodies with non-overlapping epitopes, exhibit subnanomolar or nanomolar affinities to the receptor binding domain of the viral Spike protein carrying amino acid substitutions N501Y, N439K, E484K, K417N, and a combination N501Y/E484K/K417N found in the circulating virus variants. The antibodies showed excellent neutralization of an authentic SARS-CoV-2 virus representing strains circulating in Europe in spring 2020 and also the variants of concern B.1.1.7 and B.1.351. Finally, the combination of the two antibodies prevented the appearance of escape mutations of the authentic SARS-CoV-2 virus. The neutralizing properties were fully reproduced in chimeric mouse-human versions, which may represent a promising tool for COVID-19 therapy.",
-    "rel_num_authors": 33,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.09.21258553",
+    "rel_abs": "IntroductionThe objective of this study is to analyse the specific immune response against SARS-CoV-2 in those affected by Long Covid (LC), attributable to T cells (cell-mediated immunity) and to carry out a parallel analysis of the humoral response and lymphocyte typing.\n\nMethodologyDescriptive cross-sectional study of 74 patients with LC for at least 4 months since diagnosis. The collected data were: information on the COVID-19 episode and the persistent symptoms, medical history and a specific cell-mediated immunity to SARS-CoV-2 through flow cytometry, assessing the release of interferon-gamma (IFN-{gamma}) by T4 lymphocytes, T8 lymphocytes and NK cells. Descriptive and comparative analyses were carried out.\n\nResultsPatients with LC had negative serology for Covid-19 in 89% of cases but 96% showed specific cellular immunity to SARS-CoV-2 an average of 9.5 months after infection: 89% of this response corresponded to T8 lymphocytes, 58% to NK cells, and 51% to T4 lymphocyte (20% negligibly positive). Most of them had altered immune cell typing and we found that T4 lymphocyte counts were low in 34% of cases and NK cell high in 64%. Macrophage populations were detected in the peripheral blood of 7% of them. Patients displayed a higher percentage of illnesses related to &[Prime]abnormal&[Prime] immune responses, either preceding SARS-CoV-2 infection (43%) or following it in 23% of cases.\n\nConclusionThe immune system appears to have an important involvement in the development of LC and viral persistence could be the cause or consequence of it. Further analysis with a control group should be performed.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Branislav Kovacech",
-        "author_inst": "AXON COVIDAX a. s., Slovakia"
-      },
-      {
-        "author_name": "Lubica Fialova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Peter Filipcik",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Monika Zilkova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
+        "author_name": "Nerea Montes",
+        "author_inst": "Long Covid Autonomous Communities Together Spain (Investigation group) & Aragon Health Service"
       },
       {
-        "author_name": "Rostislav Skrabana",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
+        "author_name": "\u00c8lia Dom\u00e8nech",
+        "author_inst": "Long Covid Autonomous Communities Together Spain (Investigation group)"
       },
       {
-        "author_name": "Natalia Paulenka-Ivanovova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
+        "author_name": "Silvia Guerrero",
+        "author_inst": "Long Covid Autonomous Communities Together Spain (Investigation group)"
       },
       {
-        "author_name": "Andrej Kovac",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Denisa Palova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Gabriela Paulikova Rolkova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Katarina Tomkova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Natalia Turic Csokova",
-        "author_inst": "Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Karina Markova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Michaela Skrabanova",
-        "author_inst": "Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Kristina Sinska",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Neha Basheer",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Petra Majerova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Jozef Hanes",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Vojtech Parrak",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Michal Prcina",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Ondrej Cehlar",
-        "author_inst": "Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Martin Cente",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia; Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Juraj Piestansky",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Michal Fresser",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
-      },
-      {
-        "author_name": "Michal Novak",
-        "author_inst": "Axon Neuroscience SE, Cyprus"
-      },
-      {
-        "author_name": "Monika Slavikova",
-        "author_inst": "Biomedical Research Center, Institute of Virology, Slovak Academy of Sciences, Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Kristina Borsova",
-        "author_inst": "Biomedical Research Center, Institute of Virology, Slovak Academy of Sciences, Bratislava, Slovakia; Department of Microbiology and Virology, Faculty of Natural"
-      },
-      {
-        "author_name": "Viktoria Cabanova",
-        "author_inst": "Biomedical Research Center, Institute of Virology, Slovak Academy of Sciences, Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Bronislava Brejova",
-        "author_inst": "Department of Computer Science, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Tomas Vinar",
-        "author_inst": "Department of Applied Informatics, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Jozef Nosek",
-        "author_inst": "Department of Biochemistry, Faculty of Natural Sciences, Comenius University in Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Boris Klempa",
-        "author_inst": "Biomedical Research Center, Institute of Virology, Slovak Academy of Sciences, Bratislava, Slovakia"
-      },
-      {
-        "author_name": "Norbert Zilka",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
+        "author_name": "Barbara Olivan-Blazquez",
+        "author_inst": "Institute for Health Research Arag\u00f3n (IIS Arag\u00f3n) & University of Zaragoza, Zaragoza, Spain"
       },
       {
-        "author_name": "Eva Kontsekova",
-        "author_inst": "Axon Neuroscience R&D Services SE, Slovakia"
+        "author_name": "Rosa Magall\u00f3n-Botaya",
+        "author_inst": "Institute for Health Research Aragon (IIS Aragon) & University of Zaragoza, Zaragoza, Spain"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "allergy and immunology"
   },
   {
     "rel_doi": "10.1101/2021.06.02.21258223",
@@ -680907,25 +684498,37 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2021.06.05.21258407",
-    "rel_title": "Prediction of severe COVID-19 cases requiring intensive care in Osaka, Japan",
+    "rel_doi": "10.1101/2021.06.04.21257951",
+    "rel_title": "Early Epidemiological Evidence of Public Health Value of WA Notify, a Smartphone-based Exposure Notification Tool: Modeling COVID-19 Cases Averted in Washington State",
     "rel_date": "2021-06-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.05.21258407",
-    "rel_abs": "BackgroundTo avoid exhaustion of medical resources by COVID-19 care, policy-makers must predict care needs, specifically estimating the proportion of severe cases likely to require intensive care. In Osaka prefecture, Japan, the number of these severe cases exceeded the capacity of ICU units prepared for COVID-19 from mid-April, 2021.\n\nObjectiveThis study used a statistical model to elucidate dynamics of severe cases in Osaka and validated the model through prospective testing.\n\nMethodsThe study extended from April 3, 2020 through April 26, 2021 in Osaka prefecture, Japan prefecture. We regressed the number of severe cases on the number of severe cases the day prior and the newly onset patients of more than 21 days prior.\n\nResultsWe selected the number of severe cases the day prior and the number of newly onset patients on 21 and 28 days prior as explanatory variables for explaining the number of severe cases based on the adjusted determinant coefficient. The adjusted coefficient of determination was greater than 0.995 and indicated good fit. Prospective out of sample three-week prediction forecast the peak date precisely, but the level was not t.\n\nDiscussion and ConclusionA reason for the gap in the prospective prediction might be the emergence of variant strains.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.04.21257951",
+    "rel_abs": "BackgroundSecure and anonymous smartphone-based exposure notification tools are recently developed public health interventions that aim to reduce COVID-19 transmission and supplement traditional public health suriveillance. We assessed the impact of Washington States exposure notification tool, WA Notify, in mitigating the spread of COVID-19 during its first four months of implementation.\n\nMethodsDue to the constraints of privacy-preservation, aggregate metrics and disparate data sources were utilized to estimate the number of COVID-19 cases averted based on a modelling approach adapted from Wymant et al (2021) using the following parameters: number of notifications generated; the probability that a notified individual goes on to become a case; expected fraction of transmissions preventable by strict quarantine after notification; actual adherence to quarantine; and expected size of the full transmission chain if a contact had not been notified.\n\nResultsThe model was run on a range of secondary attack rates (5.1%-13.706%) and quarantine effectiveness (53% and 64%). Assuming a 12.085% secondary attack rate and 53% quarantine effectiveness, the model shows that 5,500 cases (central 95% range of sensitivity analyses 2,800-8,200) were averted statewide during the first four months of its implementation. Based on an estimated COVID-19 case fatality of 1.4%, WA Notify saved 40-115 lives during the study period.\n\nConclusionsThese findings demonstrate the value of exposure notification tools as a novel public health intervention to mitigate the spread of COVID-19 in the U.S. As new variants emerge and non-essential travel bans are lifted, exposure notification tools may continue to play a valuable role in limiting the spread of COVID-19.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Junko Kurita",
-        "author_inst": "Tokiwa University, Ibaraki, Japan"
+        "author_name": "Courtney Segal",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Tamie Sugawara",
-        "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan"
+        "author_name": "Zhehao Zhang",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Yasushi Ohkusa",
-        "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan"
+        "author_name": "Bryant T Karras",
+        "author_inst": "Washington State Department of Health"
+      },
+      {
+        "author_name": "Debra Revere",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "Gregory Zane",
+        "author_inst": "Washington State Department of Health"
+      },
+      {
+        "author_name": "Janet G Baseman",
+        "author_inst": "University of Washington"
       }
     ],
     "version": "1",
@@ -682505,123 +686108,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.06.03.21258307",
-    "rel_title": "Loss of recognition of SARS-CoV-2 B.1.351 variant spike epitopes but overall preservation of T cell immunity",
+    "rel_doi": "10.1101/2021.06.04.447160",
+    "rel_title": "Drug Repurposing for the SARS-CoV-2 Papain-Like Protease",
     "rel_date": "2021-06-06",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258307",
-    "rel_abs": "SARS-CoV-2 variants have emerged that escape neutralization and potentially impact vaccine efficacy. T cell responses play a role in protection from reinfection and severe disease, but the potential for spike mutations to affect T cell immunity is poorly studied. We assessed both neutralizing antibody and T cell responses in 44 South African COVID-19 patients infected either with B.1.351, now dominant in South Africa, or infected prior to its emergence ( first wave), to provide an overall measure of immune evasion. We show for the first time that robust spike-specific CD4 and CD8 T cell responses were detectable in B.1.351-infected patients, similar to first wave patients. Using peptides spanning only the B.1.351 mutated regions, we identified CD4 T cell responses targeting the wild type peptides in 12/22 (54.5%) first wave patients, all of whom failed to recognize corresponding B.1.351-mutated peptides (p=0.0005). However, responses to the mutated regions formed only a small proportion (15.7%) of the overall CD4 response, and few patients (3/44) mounted CD8 responses that targeted the mutated regions. First wave patients showed a 12.7 fold reduction in plasma neutralization of B.1.351. This study shows that despite loss of recognition of immunodominant CD4 epitope(s), overall CD4 and CD8 T cell responses to B.1.351 are preserved. These observations may explain why, despite substantial loss of neutralizing antibody activity against B.1.351, several vaccines have retained the ability to protect against severe COVID-19 disease.\n\nOne Sentence SummaryT cell immunity to SARS-CoV-2 B.1.351 is preserved despite some loss of variant epitope recognition by CD4 T cells.",
-    "rel_num_authors": 26,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.04.447160",
+    "rel_abs": "As the pathogen of COVID-19, SARS-CoV-2 encodes two essential cysteine proteases that process the pathogens two large polypeptide translates ORF1a and ORF1ab in human host cells to form 15 functionally important, mature nonstructural proteins. One of the two enzymes, papain-like protease or PLpro, also possesses deubiquitination and deISGylation activities that suppresses host innate immune responses toward SARS-CoV-2 infection. Therefore, PLpro is a potential COVID-19 drug target. To repurpose drugs for PLpro, we experimentally screened 33 deubiquitinase and 37 cysteine protease inhibitors on their inhibition of PLpro. Our results showed that 15 deubiquitinase and 1 cysteine protease inhibitors exhibit potent inhibition of PLpro at 200 M. More comprehensive characterizations revealed 7 inhibitors GRL0617, SJB2-043, TCID, DUB-IN-1, DUB-IN-3, PR-619, and S130 with an IC50 value below 60 M and four inhibitors GRL0617, SJB2-043, TCID, and PR-619 with an IC50 value below 10 M. Among four inhibitors with an IC50 value below 10 M, SJB2-043 is the most unique in that it doesnt fully inhibit PLpro but has an outstanding IC50 value of 0.56 M. SJB2-043 likely binds to an allosteric site of PLpro to convene its inhibition effect, which needs to be further investigated. As a pilot study, the current work indicates that COVID-19 drug repurposing by targeting PLpro holds promises but in-depth analysis of repurposed drugs is necessary to avoid omitting allosteric inhibitors.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Catherine Riou",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Roanne Keeton",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Thandeka Moyo-Gwete",
-        "author_inst": "National Institute for Communicable Diseases"
-      },
-      {
-        "author_name": "Tandile Hermanus",
-        "author_inst": "National Institute for Communicable Diseases"
-      },
-      {
-        "author_name": "Prudence Kgagudi",
-        "author_inst": "National Institute for Communicable Diseases"
-      },
-      {
-        "author_name": "Richard Baguma",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Houriiyah Tegally",
-        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP)"
-      },
-      {
-        "author_name": "Deelan Doolabh",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Arash Iranzadeh",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Lynn Tyers",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Hygon Mutavhatsindi",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Marius Tincho",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Ntombi Benede",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Gert Marais",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Lionel Chinhoyi",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Mathilda Mennen",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Sango Skelem",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Elsa Bruyn",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Cari Stek",
-        "author_inst": "University of Cape Town"
+        "author_name": "Chia-Chuan D Cho",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "- SA-CIN",
-        "author_inst": ""
+        "author_name": "Shuhua G Li",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "Tulio de Oliveira",
-        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP)"
+        "author_name": "Kai S Yang",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "Carolyn Williamson",
-        "author_inst": "University of Cape Town"
+        "author_name": "Tyler J Lalonde",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "Penny Moore",
-        "author_inst": "National Institute for Communicable Diseases"
+        "author_name": "Ge Yu",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "Robert Wilkinson",
-        "author_inst": "University of Cape Town"
+        "author_name": "Yuchen Qiao",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "Ntobeko Ntusi",
-        "author_inst": "University of Cape Town"
+        "author_name": "Shiqing Xu",
+        "author_inst": "Texas A&M University"
       },
       {
-        "author_name": "Wendy Burgers",
-        "author_inst": "University of Cape Town"
+        "author_name": "Wenshe Ray Liu",
+        "author_inst": "Texas A&M University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by_nc",
+    "type": "new results",
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2021.06.03.21258248",
@@ -684235,59 +687766,35 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.06.03.446942",
-    "rel_title": "Visualization of SARS-CoV-2 infection dynamic",
+    "rel_doi": "10.1101/2021.06.04.447114",
+    "rel_title": "Sub-Picomolar Detection of SARS-CoV-2 RBD via Computationally-Optimized Peptide Beacons",
     "rel_date": "2021-06-04",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.03.446942",
-    "rel_abs": "Replication-competent recombinant viruses expressing reporter genes provide valuable tools to investigate viral infection. Low levels of reporter gene expressed from previous reporter-expressing rSARS-CoV-2 have jeopardized their use to monitor the dynamics of SARS-CoV-2 infection in vitro or in vivo. Here, we report an alternative strategy where reporter genes were placed upstream of the viral nucleocapsid gene followed by a 2A cleavage peptide. The higher levels of reporter expression using this strategy resulted in efficient visualization of rSARS-CoV-2 in infected cultured cells and K18 hACE2 transgenic mice. Importantly, real-time viral infection was readily tracked using a non-invasive in vivo imaging system and allowed us to rapidly identify antibodies which are able to neutralize SARS-CoV-2 infection in vivo. Notably, these reporter-expressing rSARS-CoV-2 retained wild-type virus like pathogenicity in vivo, supporting their use to investigate viral infection, dissemination, pathogenesis and therapeutic interventions for the treatment of SARS-CoV-2 in vivo.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.04.447114",
+    "rel_abs": "The novel coronavirus SARS-CoV-2 continues to pose a significant global health threat. Along with vaccines and targeted therapeutics, there is a critical need for rapid diagnostic solutions. In this work, we employ deep learning-based protein design to engineer molecular beacons that function as conformational switches for high sensitivity detection of the SARS-CoV-2 spike protein receptor binding domain (S-RBD). The beacons contain two peptides, together forming a heterodimer, and a binding ligand between them to detect the presence of S-RBD. In the absence of S-RBD (OFF), the peptide beacons adopt a closed conformation that opens when bound to the S-RBD and produces a fluorescence signal (ON), utilizing a fluorophore-quencher pair at the two ends of the heterodimer stems. Two candidate beacons, C17LC21 and C21LC21, can detect the S-RBD with limits of detection (LoD) in the sub-picomolar range. We envision that these beacons can be easily integrated with on-chip optical sensors to construct a point-of-care diagnostic platform for SARS-CoV-2.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Chengjin Ye",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Kevin Chiem",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Jun-Gyu Park",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Jesus Silvas",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Desarey Morales Vasquez",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Jordi B Torrelles",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "James Kobie",
-        "author_inst": "University of Alabama at Birmingham"
+        "author_name": "Soumya P. Tripathy",
+        "author_inst": "MIT Media Lab"
       },
       {
-        "author_name": "Mark R Walter",
-        "author_inst": "University of Alabama at Birmingham"
+        "author_name": "Manvitha Ponnapati",
+        "author_inst": "MIT Media Lab"
       },
       {
-        "author_name": "Juan C de la Torre",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Joseph M Jacobson",
+        "author_inst": "MIT Media Lab"
       },
       {
-        "author_name": "Luis Martinez-Sobrido",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Pranam Chatterjee",
+        "author_inst": "MIT Media Lab"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "new results",
-    "category": "microbiology"
+    "category": "bioengineering"
   },
   {
     "rel_doi": "10.1101/2021.06.04.447090",
@@ -686193,117 +689700,25 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2021.06.01.21258172",
-    "rel_title": "Humoral and cellular immune response against SARS-CoV-2 variants following heterologous and homologous ChAdOx1 nCoV-19/BNT162b2 vaccination.",
+    "rel_doi": "10.1101/2021.06.01.21258150",
+    "rel_title": "Ten months of temporal variation in the clinical journey of hospitalised patients with COVID-19: an observational cohort",
     "rel_date": "2021-06-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.01.21258172",
-    "rel_abs": "Cerebral venous thrombosis was reported as a rare but serious adverse event in young and middle-aged vaccinees following immunization with AstraZenecas ChAdOx1-nCov-19 vaccine. As a consequence, several European governments recommended using this vaccine only in individuals older than 60 years leaving millions of ChAd primed individuals with the decision to either receive a second shot of ChAd or a heterologous boost with mRNA-based vaccines. However, such combinations have not been tested so far. We used Hannover Medical Schools COVID-19 Contact (CoCo) Study cohort of health care professionals (HCP) to monitor ChAd primed immune responses before and three weeks after booster with ChAd or BioNTech/Pfizers BNT162b2. Whilst both vaccines boosted prime-induced immunity, BNT induced significantly higher frequencies of Spike-specific CD4 and CD8 T cells and, in particular, high titers of neutralizing antibodies against the B.1.1.7, B.1.351 and the P.1 variants of concern of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2).",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.01.21258150",
+    "rel_abs": "BackgroundThere is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an ongoing infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high density unit (HDU), while novel treatment modalities may reduce the time course of illness. On the other hand, limited resources at times of high demand may lead to rationing of resources, with less beneficial consequences. Despite little evidence on how the values of such variables change over the course of a crisis (such as the current COVID-19 pandemic), they may nevertheless be used as proxies for disease severity, outcome measures for clinical trials, and to inform planning and logistics. We hypothesise that variation of this kind has been present over the first year of the pandemic.\n\nMethods and FindingsWe investigate such time trends in an extremely large international cohort of 142,540 patients with symptom onset of, or hospital admission for, COVID-19 during 2020. The variables investigated are time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, case fatality ratio (CFR) and total length of hospital stay. Time from hospital symptom onset to hospital admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December. ICU/HDU admission was more frequent from June to August, while there were only modest time trends in time from hospital admission to ICU/HDU. The CFR was lowest from June to August, a trend mostly driven by patients with no ICU/HDU admission. Raw numbers for overall hospital stay showed little overall variation over the time period, but further examination reveals a clear decline in time to discharge for ICU/HDU survivors. The main limitations are that these are predominantly severe COVID-19 cases, and that there are temporal, spatial and demographic biases present in an observational study of this kind.\n\nConclusionsOur results establish that variables of these kinds have limitations when used as outcome measures in a rapidly-evolving situation.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Joana Barros-Martins",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Swantje Hammerschmidt",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Anne Cossmann",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Ivan Odak",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Metodi V Stankov",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Gema Morillas Ramos",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Alexandra Jablonka",
-        "author_inst": "Hannover Medical  School"
-      },
-      {
-        "author_name": "Annika Heidemann",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Christiane Ritter",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Michaela Friedrichsen",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Christian R Schultze-Florey",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Inga Ravens",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Willenzon Stefanie",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Anja Bubke",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Jasmin Ristenpart",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Anika Janssen",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "George Ssebyatika",
-        "author_inst": "University of Luebeck"
-      },
-      {
-        "author_name": "Guenter Bernhardt",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Jan R Muench",
-        "author_inst": "Ulm University"
-      },
-      {
-        "author_name": "Markus Hoffmann",
-        "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut fur Primatenforschung"
-      },
-      {
-        "author_name": "Stefan Poehlmann",
-        "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut fur Primatenforschung"
-      },
-      {
-        "author_name": "Thomas Krey",
-        "author_inst": "University of Luebeck"
-      },
-      {
-        "author_name": "Berislav Bosnjak",
-        "author_inst": "Hannover Medical School"
-      },
-      {
-        "author_name": "Reinhold Foerster",
-        "author_inst": "Hannover Medical School"
+        "author_name": "Matthew Hall",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Georg MN Behrens",
-        "author_inst": "Hannover Medical School"
+        "author_name": "- ISARIC Clinical Characterisation Group",
+        "author_inst": ""
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -688195,61 +691610,69 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2021.05.29.21258010",
-    "rel_title": "Rapid and sustained decline in CXCL-10 (IP-10) annotates clinical outcomes following TNF-\u03b1 antagonist therapy in hospitalized patients with severe and critical COVID-19 respiratory failure",
+    "rel_doi": "10.1101/2021.05.25.21257820",
+    "rel_title": "The Female Predominant Persistent Immune Dysregulation of the Post COVID Syndrome: A Cohort Study",
     "rel_date": "2021-06-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.29.21258010",
-    "rel_abs": "BackgroundA feed-forward pathological signaling loop generated by TNF and IFN-{gamma} in inflamed lung tissue, driving CXCL-10 (IP-10) and CXCL-9 chemokine-mediated activated T-cell and monocyte/macrophage tissue recruitment, may define, sustain and amplify the inflammatory biology of lethal COVID-19 respiratory failure.\n\nMethodsTo assess TNF-antagonist therapy, 18 hospitalized adults with hypoxic respiratory failure and COVID-19 pneumonia received single-dose infliximab-abda therapy 5mg/kg intravenously between April and December 2020. The primary endpoint was time to increase in oxygen saturation to fraction of inspired oxygen ratio (SpO2/FiO2) by [&ge;] 50 compared to baseline and sustained for 48 hours. Secondary endpoints included 28-day mortality, dynamic cytokine profiles (Human Cytokine 48-Plex Discovery Assay, Eve Technologies), secondary infections, duration of supplemental oxygen support and hospitalization.\n\nFindingsPatients were predominantly in critical respiratory failure (15/18, 83%), male (14/18, 78%), above 60 years (median 63 yrs, range 31-80), race-ethnic minorities (13/18, 72%), lymphopenic (13/18, 72%), steroid-treated (17/18, 94%), with a median ferritin of 1953ng/ml. Sixteen patients (89%) met the primary endpoint within a median of 4 days, 15/18 (83%) recovered from respiratory failure, and 14/18 (78%) were discharged in a median of 8 days and were alive at 28-day follow-up. Deaths among three patients [&ge;] 65yrs age with pre-existing lung disease or multiple comorbidities were attributed to secondary lung infection. Mean plasma IP-10 levels declined sharply from 9183 pg/ml to 483 pg/ml at Day 3 and further to 146 pg/ml at Day 14/discharge. Significant declines in IFN-{gamma}, TNF, IL-27, CRP and ferritin were specifically observed at Day 3 whereas other cytokines were unmodified. IL-6 levels declined sharply among patients with baseline levels >10 pg/ml. Among 13 lymphopenic patients, six (46%) had resolution of lymphopenia by day 3, and 11 by day 14. CXCR3-ligand (IP-10 and CXCL-9) declines were strongly correlated among patients with lymphopenia reversal (Day 3, Pearson r: 0.98, p-value: 0.0006).\n\nInterpretationConsistent with a pathophysiological role of TNF, the clinical and cytokine data indicate that infliximab-abda may rapidly abrogate pathological inflammatory signaling to facilitate clinical recovery in severe and critical COVID-19. Randomized studies are required to formally assess mortality outcomes. Funding: National Center for Advancing Translational Sciences",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.25.21257820",
+    "rel_abs": "ObjectiveTo describe the clinical data from the first 107 patients seen in the Mayo Clinic Post COVID-19 Care Clinic (PCOCC).\n\nPatients and MethodsAfter IRB approval, we reviewed the charts of 107 patients seen between January 19, 2021 and April 29, 2021 in the Mayo Clinic Post COVID Care Clinic (PCOCC) in order to describe the first 107 patients treated through the Mayo Clinic PCOCC. Data was abstracted from the electronic medical record into a standardized database to facilitate analysis. Phenotypes of patients seen in the PCOCC clinic were identified by expert review of predominant symptom clusters.\n\nResultsThe majority of patients seen in our clinic were female (75%, 80/107), and the median age at presentation was 47 years (interquartile range [IQR] 37, 55). All had Post Acute Sequelae of SARS-CoV-2 infection (PASC) with six clinical phenotypes being identified - fatigue predominant (n=68), dyspnea predominant (n=23), myalgia predominant (n=6), orthostasis predominant (n=6), chest pain predominant (n=3), and headache predominant (n=1). The fatigue-predominant phenotype was more common in women (84%, p=0.006) and the dyspnea-predominant phenotype was more common in men (52%, p=0.002). IL-6 was elevated in 61% of patients (69% of women, p=0.0046) which was statistically discordant with elevation in CRP and ESR which was identified in 17% and 20% of cases respectively (p<0.001). Four PASC phenotypes (fatigue-predominant, myalgia-predominant, orthostasis predominant, and headache-predominant) were associated with central sensitization (CS), and higher IL-6 levels than those phenotypes not associated with CS (p=0.013). Patients with CS phenotypes after COVID-19 infection (post COVID syndrome) were predominantly female (80%, p=0.0085).\n\nConclusionIn our post COVID clinic, we observed several distinct clinical phenotypes. Fatigue-predominance was the most common presentation and was associated with elevated IL-6 levels and female gender. Dyspnea-predominance was more common in men and was not associated with elevated IL-6 levels. IL-6 levels were significantly elevated in patients with PASC and discordant with ESR and CRP, particularly in those with central sensitization phenotypes.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Hilal Hachem",
-        "author_inst": "Tufts Medical Center, Boston MA (current affiliation: Northern Light Cancer Institute,Bangor ME)"
+        "author_name": "Ravindra Ganesh",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Amandeep Godara",
-        "author_inst": "Tufts Medical Center, Boston MA (current affiliation: University of Utah, Salt Lake City, UT)"
+        "author_name": "Stephanie L Grach",
+        "author_inst": "Mayo Clinic School of Graduate Medical Education"
       },
       {
-        "author_name": "Courtney Schroeder",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Dennis M Bierle",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Daniel Fein",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Bradley R Salonen",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Hashim Mann",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Nerissa M Collins",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Christian Lawlor",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Avni Y Joshi",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Jill Marshall",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Neal D Boeder Jr.",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Andreas Klein",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Christopher V Anstine",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Deborah Poutsiaka",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Michael R Mueller",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Janis L Breeze",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Elizabeth C Wight",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Raghav Joshi",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Ivana T Croghan",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Paul Mathew",
-        "author_inst": "Tufts Medical Center"
+        "author_name": "Andrew D Badley",
+        "author_inst": "Mayo Clinic"
+      },
+      {
+        "author_name": "Rickey E Carter",
+        "author_inst": "Mayo Clinic"
+      },
+      {
+        "author_name": "Ryan T Hurt",
+        "author_inst": "Mayo Clinic"
       }
     ],
     "version": "1",
@@ -689961,43 +693384,79 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.05.28.21258008",
-    "rel_title": "College Students' COVID-19 Vaccine Beliefs and Intentions: Implications for interventions",
+    "rel_doi": "10.1101/2021.05.31.21257656",
+    "rel_title": "Acute kidney injury in hospitalized patients due to COVID-19",
     "rel_date": "2021-06-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21258008",
-    "rel_abs": "On college campuses, effective management of vaccine-preventable transmissible pathogens requires understanding student vaccination intentions. This is necessary for developing and tailoring health messaging to maximize uptake of health information and vaccines. The current study explored students beliefs and attitudes about vaccines in general, and the new COVID-19 vaccines specifically. This study provides insights into effective health messaging needed to rapidly increase COVID-19 vaccination on college campuses--information that will continue to be informative in future academic years across a broad scope of pathogens. Data were collected via an online cohort survey of college students aged 18 years and older residing on or near the campus of a large public university during fall 2020. Overall, we found COVID-19 vaccine hesitancy in college students correlated strongly with some concerns about vaccines in general as well as with concerns specific to COVID-19 vaccines. Taken together, these results provide further insight for message development and delivery, and can inform more effective interventions to advance critical public health outcomes on college campuses beyond the current pandemic.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.31.21257656",
+    "rel_abs": "The incidence of acute kidney injury (AKI) in hospitalized patients with coronavirus disease 2019 (COVID-19) is variable, being associated with worse outcomes. The objectives of the study were to evaluate the incidence, risk factors and impact of AKI in subjects hospitalized for COVID-19 in two third- level hospitals in Cordoba, Argentina.\n\nA retrospective cohort study was conducted. 448 adults who were consecutively hospitalized for COVID-19 between March and the end of October 2020 at Hospital Privado Universitario de Cordoba and Hospital Raul Angel Ferreyra were included. The incidence of AKI was 19% (n = 85). 50.6% presented AKI stage 1 (n=43), 20% stage 2 (n=17) and 29.4% stage 3 (n=25, of which 18 required renal replacement therapy). In the multivariate analysis, the variables that were independently associated with AKI were: age (adjusted Odd ratio -aOR- =1.30, 95%CI=1.04-1.63, p=0.022), history of chronic kidney disease (aOR=9.92, 95%CI=4.52-21.77, p<0.001), blood neutrophil count at admission (aOR=1.09, 95%CI=1.01-1.18, p=0.037) and requirement for mechanical ventilation (MV) (aOR=6.69, 95%CI=2.24-19.9, p=0.001). AKI was associated with longer hospitalization, greater admission and length of stay in the intensive care unit, a positive association with bacterial superinfection, sepsis, respiratory distress syndrome, MV requirement and mortality (mortality with AKI=47.1% vs without AKI=12.4%, p<0.001). AKI was independently associated with higher mortality (aOR=3.32, 95%CI=1.6-6.9, p=0.001).\n\nIn conclusion, the incidence of AKI in adults hospitalized for COVID-19 was 19% and had a clear impact on morbidity and mortality. Local predisposing factors for AKI were identified.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Meg L Small",
-        "author_inst": "Penn State University"
+        "author_name": "Pehu\u00e9n Fern\u00e1ndez",
+        "author_inst": "Department of Nephrology, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
       },
       {
-        "author_name": "Robert Lennon",
-        "author_inst": "Penn State University"
+        "author_name": "Emanuel Jos\u00e9 Saad",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
       },
       {
-        "author_name": "John Dziak",
-        "author_inst": "Penn State University"
+        "author_name": "Augusto Douthat",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
       },
       {
-        "author_name": "Rachel A Smith",
-        "author_inst": "Penn State University"
+        "author_name": "Federico Ariel Marucco",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
       },
       {
-        "author_name": "Gillian Sommerville",
-        "author_inst": "Penn State University"
+        "author_name": "Mar\u00eda Celeste Heredia",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
       },
       {
-        "author_name": "Nita Bharti",
-        "author_inst": "Penn State University"
+        "author_name": "Ayel\u00e9n Tarditi Barra",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Silvina Trinidad Rodriguez Bonazzi",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Melani Zlotogora",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Mar\u00eda Antonella Correa Barovero",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Sof\u00eda Villada",
+        "author_inst": "Department of Infectious Diseases, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Juan Pablo Maldonado",
+        "author_inst": "Department of Nephrology, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Juan Pablo Caeiro",
+        "author_inst": "Department of Infectious Diseases, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Ricardo Arturo Albertini",
+        "author_inst": "Department of Internal Medicine, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Jorge Luis De La Fuente",
+        "author_inst": "Department of Nephrology, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
+      },
+      {
+        "author_name": "Walter Guillermo Douthat",
+        "author_inst": "Department of Nephrology, Hospital Privado Universitario de C\u00f3rdoba, C\u00f3rdoba, Argentina"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "nephrology"
   },
   {
     "rel_doi": "10.1101/2021.05.30.21256718",
@@ -691379,39 +694838,35 @@
     "category": "pharmacology and therapeutics"
   },
   {
-    "rel_doi": "10.1101/2021.05.28.21257993",
-    "rel_title": "The UGT2A1/UGT2A2 locus is associated with COVID-19-related anosmia",
+    "rel_doi": "10.1101/2021.05.28.21258007",
+    "rel_title": "Temporal stability and detection sensitivity of the dry swab-based diagnosis of SARS-CoV-2",
     "rel_date": "2021-05-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21257993",
-    "rel_abs": "Loss of sense of smell is a characteristic symptom of infection with SARS-CoV-2. However, specific mechanisms linking infection with loss of smell are poorly understood. Using self-reported symptom data from the 23andMe COVID-19 study, we describe the demographic patterns associated with COVID-19 related anosmia, and find the symptom is more often reported in women and younger respondents, and less often by those of East Asian and African American ancestry compared to those of European ancestry. We ran a trans-ethnic genome-wide association study (GWAS) comparing loss of smell or taste (n=47,298) with no loss of smell or taste (n=22,543) among those with a positive SARS-CoV-2 test result. We identified an association (rs7688383) in the vicinity of the UGT2A1 and UGT2A2 genes (OR=1.115, p-value=4x10-15), which have been linked to olfactory function. These results may shed light on the biological mechanisms underlying COVID-19 related anosmia.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21258007",
+    "rel_abs": "The rapid spread and evolution of various strains of SARS-CoV-2, the virus responsible for COVID-19, continues to challenge the disease controlling measures globally. Alarming concern is, the number of second wave infections surpassed the first wave and the onset of severe symptoms manifesting rapidly. In this scenario, testing of maximum population in less time and minimum cost with existing diagnostic amenities is the only possible way to control the spread of the virus. The previously described RNA extraction-free methods using dry swab have been shown to be advantageous in these critical times by different studies. In this work, we show the temporal stability and performance of the dry swab viral detection method at two different temperatures. Contrived dry swabs holding serially diluted SARS-CoV-2 strains A2a and A3i at 25{degrees}C (room temperature; RT) and 4{degrees}C were subjected to direct RT-PCR and compared with standard VTM-RNA based method. The results clearly indicate that dry swab method of RNA detection is as efficient as VTM-RNA-based method in both strains, when checked for up to 72 hours. The lesser CT values of dry swab samples in comparison to that of the VTM-RNA samples suggest better sensitivity of the method within 48 hours of time. The results collectively suggest that dry swab samples are stable at RT for 24 hours and the detection of SARS-CoV-2 RNA by RT-PCR do not show variance from VTM-RNA. This extraction free, direct RT-PCR method holds phenomenal standing in the present life-threatening circumstances due to SARS-CoV-2.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Janie F. Shelton",
-        "author_inst": "23andMe"
-      },
-      {
-        "author_name": "Anjali J. Shastri",
-        "author_inst": "23andMe"
+        "author_name": "Gokulan CG",
+        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "- The 23andMe COVID-19 Team",
-        "author_inst": ""
+        "author_name": "Uday Kiran",
+        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Stella Aslibekyan",
-        "author_inst": "23andMe"
+        "author_name": "Santosh Kumar Kuncha",
+        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Adam Auton",
-        "author_inst": "23andMe"
+        "author_name": "Rakesh K Mishra",
+        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "genetic and genomic medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.05.31.21257910",
@@ -693004,75 +696459,103 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.05.26.21257854",
-    "rel_title": "Corowa-kun: Impact of a COVID-19 vaccine information chatbot on vaccine hesitancy, Japan 2021",
+    "rel_doi": "10.1101/2021.05.29.443900",
+    "rel_title": "Broadening a SARS-CoV-1 neutralizing antibody for potent SARS-CoV-2 neutralization through directed evolution",
     "rel_date": "2021-05-30",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257854",
-    "rel_abs": "BackgroundFew studies have assessed how mobile messenger apps affect COVID-19 vaccine hesitancy. We created a COVID-19 vaccine information chatbot in a popular messenger app in Japan to answer commonly asked questions.\n\nMethodsLINE is the most popular messenger app in Japan. Corowa-kun, a free chatbot, was created in LINE on February 6, 2021. Corowa-kun provides instant, automated answers to frequently asked COVID-19 vaccine questions. In addition, a cross-sectional survey assessing COVID-19 vaccine hesitancy was conducted via Corowa-kun during April 5-12, 2021.\n\nResultsA total of 59,676 persons used Corowa-kun during February-April 2021. Of them, 10,192 users (17%) participated in the survey. Median age was 55 years (range 16-97), and most were female (74%). Intention to receive a COVID-19 vaccine increased from 59% to 80% after using Corowa-kun (p < 0.01). Overall, 20% remained hesitant: 16% (1,675) were unsure, and 4% (364) did not intend to be vaccinated. Factors associated with vaccine hesitancy were: age 16 to 34 (odds ratio [OR] = 3.7, 95% confidential interval [CI]: 3.0-4.6, compared to age [&ge;]65), female sex (OR = 2.4, Cl: 2.1-2.8), and history of a previous vaccine side-effect (OR = 2.5, Cl: 2.2-2.9). Being a physician (OR = 0.2, Cl: 0.1-0.4) and having received a flu vaccine the prior season (OR = 0.4, Cl: 0.3-0.4) were protective.\n\nConclusionsCorowa-kun reduced vaccine hesitancy by providing COVID-19 vaccine information in a messenger app. Mobile messenger apps could be leveraged to increase COVID-19 vaccine acceptance.",
-    "rel_num_authors": 14,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.29.443900",
+    "rel_abs": "The emergence of SARS-CoV-2 underscores the need for strategies to rapidly develop neutralizing monoclonal antibodies that can function as prophylactic and therapeutic agents and to help guide vaccine design. Here, we demonstrate that engineering approaches can be used to refocus an existing neutralizing antibody to a related but resistant virus. Using a rapid affinity maturation strategy, we engineered CR3022, a SARS-CoV-1 neutralizing antibody, to bind SARS-CoV-2 receptor binding domain with >1000-fold improved affinity. The engineered CR3022 neutralized SARS-CoV-2 and provided prophylactic protection from viral challenge in a small animal model of SARS-CoV-2 infection. Deep sequencing throughout the engineering process paired with crystallographic analysis of an enhanced antibody elucidated the molecular mechanisms by which engineered CR3022 can accommodate sequence differences in the epitope between SARS-CoV-1 and SARS-CoV-2. The workflow described provides a blueprint for rapid broadening of neutralization of an antibody from one virus to closely related but resistant viruses.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Takaaki Kobayashi",
-        "author_inst": "University of Iowa Hospitals and Clinics"
+        "author_name": "Fangzhu Zhao",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Yuka Nishina",
-        "author_inst": "Juntendo University Faculty of Medicine"
+        "author_name": "Meng Yuan",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Hana Tomoi",
-        "author_inst": "MSc Public Health (Cand.), Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine"
+        "author_name": "Celina Keating",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Ko Harada",
-        "author_inst": "Okayama University Graduate School of Medicine"
+        "author_name": "Namir Shabaani",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Kyuto Tanaka",
-        "author_inst": "Kawasaki Municipal Hospital"
+        "author_name": "Oliver Limbo",
+        "author_inst": "IAVI"
       },
       {
-        "author_name": "Eiyu Matsumoto",
-        "author_inst": "University of Iowa Hospitals & Clinics"
+        "author_name": "Collin Joyce",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Kenta Horimukai",
-        "author_inst": "Jikei University Katsushika Medical Center"
+        "author_name": "Jordan Woehl",
+        "author_inst": "IAVI"
       },
       {
-        "author_name": "Jun Ishihara",
-        "author_inst": "Imperial College London"
+        "author_name": "Shawn Barman",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Shugo Sasaki",
-        "author_inst": "Saitama Medical University Hospital"
+        "author_name": "Alison Burns",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Kanako Inaba",
-        "author_inst": "Kanto Central Hospital"
+        "author_name": "Xueyong Zhu",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Kyosuke Seguchi",
-        "author_inst": "Kameda Medical Center"
+        "author_name": "Michael Ricciardi",
+        "author_inst": "George Washington University"
       },
       {
-        "author_name": "Hiromizu Takahashi",
-        "author_inst": "Juntendo University Faculty of Medicine"
+        "author_name": "Linghang Peng",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Jorge Salinas",
-        "author_inst": "University of Iowa Hospitals & Clinics"
+        "author_name": "Jessica Smith",
+        "author_inst": "IAVI"
       },
       {
-        "author_name": "Yuji Yamada",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Deli Huang",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "Bryan Briney",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "Devin Sok",
+        "author_inst": "IAVI"
+      },
+      {
+        "author_name": "David Nemazee",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "John Teiijaro",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "Ian A. Wilson",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "Dennis Burton",
+        "author_inst": "Scripps Institute"
+      },
+      {
+        "author_name": "Joseph G Jardine",
+        "author_inst": "IAVI"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "bioengineering"
   },
   {
     "rel_doi": "10.1101/2021.05.29.446267",
@@ -694710,99 +698193,39 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.05.28.446159",
-    "rel_title": "SARS-CoV-2 transmission via apical syncytia release from primary bronchial epithelia and infectivity restriction in children epithelia",
+    "rel_doi": "10.1101/2021.05.28.446020",
+    "rel_title": "Evaluating the risk of SARS-CoV-2 transmission to bats using a decision analytical framework",
     "rel_date": "2021-05-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.28.446159",
-    "rel_abs": "The beta-coronavirus SARS-CoV-2 is at the origin of a persistent worldwide pandemic. SARS-CoV-2 infections initiate in the bronchi of the upper respiratory tract and are able to disseminate to the lower respiratory tract eventually causing acute severe respiratory syndrome with a high degree of mortality in the elderly. Here we use reconstituted primary bronchial epithelia from adult and children donors to follow the infection dynamic following infection with SARS-CoV-2. We show that in bronchial epithelia derived from adult donors, infections initiate in multi-ciliated cells. Then, infection rapidly spread within 24-48h throughout the whole epithelia. Within 3-4 days, large apical syncytia form between multi-ciliated cells and basal cells, which dissipate into the apical lumen. We show that these syncytia are a significant source of the released infectious dose. In stark contrast to these findings, bronchial epithelia reconstituted from children donors are intrinsically more resistant to virus infection and show active restriction of virus spread. This restriction is paired with accelerated release of IFN compared to adult donors. Taken together our findings reveal apical syncytia formation as an underappreciated source of infectious virus for either local dissemination or release into the environment. Furthermore, we provide direct evidence that children bronchial epithelia are more resistant to infection with SARS-CoV-2 providing experimental support for epidemiological observations that SARS-CoV-2 cases fatality is linked to age.\n\nSignificance StatementBronchial epithelia are the primary target for SARS-CoV-2 infections. Our work uses reconstituted bronchial epithelia from adults and children. We show that infection of adult epithelia with SARS-CoV-2 is rapid and results in the synchronized release of large clusters of infected cells and syncytia into the apical lumen contributing to the released infectious virus dose. Infection of children derived bronchial epithelia revealed an intrinsic resistance to infection and virus spread, probably as a result of a faster onset of interferon secretion. Thus, our data provide direct evidence for the epidemiological observation that children are less susceptible to SARS-CoV-2.",
-    "rel_num_authors": 20,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.28.446020",
+    "rel_abs": "Preventing wildlife disease outbreaks is a priority issue for natural resource agencies, and management decisions can be urgent, especially in epidemic circumstances. With the emergence of SARS-CoV-2, wildlife agencies were concerned whether the activities they authorize might increase the risk of viral transmission from humans to North American bats but had a limited amount of time in which to make decisions. We provide a description of how decision analysis provides a powerful framework to analyze and re-analyze complex natural resource management problems as knowledge evolves. Coupled with expert judgment and avenues for the rapid release of information, risk assessment can provide timely scientific information for evolving decisions. In April 2020, the first rapid risk assessment was conducted to evaluate the risk of transmission of SARS-CoV-2 from humans to North American bats.\n\nBased on the best available information, and relying heavily on formal expert judgment, the risk assessment found a small possibility of transmission during summer work activities. Following that assessment, additional knowledge and data emerged, such as bat viral challenge studies, that further elucidated the risks of human-to-bat transmission and culminated in a second risk assessment in the fall of 2020. We update the first SARS-CoV-2 risk assessment with new estimates of little brown bat (Myotis lucifugus) susceptibility and new management alternatives, using findings from the prior two risk assessments and other empirical studies. We highlight the strengths of decision analysis and expert judgment not only to frame decisions and produce useful science in a timely manner, but also to serve as a framework to reassess risk as understanding improves. For SARS-CoV-2 risk, new knowledge led to an 88% decrease in the median number of bats estimated to be infected per 1000 encountered when compared to earlier results. The use of facemasks during, or a negative COVID-19 test prior to, bat encounters further reduced those risks. Using a combination of decision analysis, expert judgment, rapid risk assessment, and efficient modes of information distribution, we provide timely science support to decision makers for summer bat work in North America.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Guillaume Beucher",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France."
-      },
-      {
-        "author_name": "Marie-Lise Blondot",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France."
-      },
-      {
-        "author_name": "Alexis Celle",
-        "author_inst": "INSERM, Centre de Recherche Cardio-thoracique de Bordeaux, U1045, CIC 1401, Bordeaux, 33000, France.,"
-      },
-      {
-        "author_name": "Noemie Pied",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France"
-      },
-      {
-        "author_name": "Patricia Recordon-Pinson",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France"
-      },
-      {
-        "author_name": "Pauline Esteves",
-        "author_inst": "INSERM, Centre de Recherche Cardio-thoracique de Bordeaux, U1045, CIC 1401, Bordeaux, 33000, France.,"
-      },
-      {
-        "author_name": "Muriel Faure",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France."
-      },
-      {
-        "author_name": "Mathieu Metifiot",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France."
-      },
-      {
-        "author_name": "Sabrina Lacomme",
-        "author_inst": "University of Bordeaux, CNRS, Institute of Neurodegenerative Diseases, IINS, UMR 5293, Bordeaux, France, University of Bordeaux, CNRS, INSERM, Bordeaux Imaging "
-      },
-      {
-        "author_name": "Denis Dacheaux",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France."
-      },
-      {
-        "author_name": "Derrick  Roy Robinson",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France."
-      },
-      {
-        "author_name": "Gernot Laengst",
-        "author_inst": "Universitaet Regensburg"
-      },
-      {
-        "author_name": "Fabien Beaufils",
-        "author_inst": "INSERM, Centre de Recherche Cardio-thoracique de Bordeaux, U1045, CIC 1401, Bordeaux, 33000, France.,"
-      },
-      {
-        "author_name": "Marie-Edith Lafon",
-        "author_inst": "CHU de Bordeaux, Laboratoire de Virologie, 33000 Bordeaux, France"
-      },
-      {
-        "author_name": "Patrick Berger",
-        "author_inst": "INSERM, Centre de Recherche Cardio-thoracique de Bordeaux, U1045, CIC 1401, Bordeaux, 33000, France."
-      },
-      {
-        "author_name": "Marc Landry",
-        "author_inst": "University of Bordeaux, CNRS, Institute of Neurodegenerative Diseases, IINS, UMR 5293, Bordeaux, France, University of Bordeaux, CNRS, INSERM, Bordeaux Imaging "
+        "author_name": "Jonathan D Cook",
+        "author_inst": "U.S. Geological Survey"
       },
       {
-        "author_name": "Jean-Marie Denis Malvy",
-        "author_inst": "Department for infectious and tropical d ideales, University Hospital center Pellegrin, Bordeaux, & Inserm 1219, University of Bordeaux, Bordeaux, France"
+        "author_name": "Evan H. Cambell Grant",
+        "author_inst": "U.S. Geological Survey"
       },
       {
-        "author_name": "Thomas Trian",
-        "author_inst": "INSERM, Centre de Recherche Cardio-thoracique de Bordeaux, U1045, CIC 1401, Bordeaux, 33000, France."
+        "author_name": "Jeremy T. H. Coleman",
+        "author_inst": "U.S. Fish and Wildlife Service"
       },
       {
-        "author_name": "Marie-Line Andreola",
-        "author_inst": "Univ. Bordeaux, CNRS, MFP UMR 5234, F-33000 Bordeaux,  France"
+        "author_name": "Jonathan M. Sleeman",
+        "author_inst": "U.S. Geological Survey"
       },
       {
-        "author_name": "Harald Wodrich",
-        "author_inst": "Universite de Bordeaux"
+        "author_name": "Michael C. Runge",
+        "author_inst": "U.S. Geological Survey"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc0",
     "type": "new results",
-    "category": "microbiology"
+    "category": "ecology"
   },
   {
     "rel_doi": "10.1101/2021.05.28.446179",
@@ -696279,65 +699702,105 @@
     "category": "genetic and genomic medicine"
   },
   {
-    "rel_doi": "10.1101/2021.05.25.21257811",
-    "rel_title": "Fast Evaluation of Viral Emerging Risks (FEVER): A computational tool for biosurveillance, diagnostics, and mutation typing of emerging viral pathogens",
+    "rel_doi": "10.1101/2021.05.25.21257828",
+    "rel_title": "Correlation of the commercial anti-SARS-CoV-2 receptor binding domain antibody test with the chemiluminescent reduction neutralizing test and possible detection of antibodies to emerging variants",
     "rel_date": "2021-05-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.25.21257811",
-    "rel_abs": "Viral pathogen can rapidly evolve, adapt to novel hosts and evade human immunity. The early detection of emerging viral pathogens through biosurveillance coupled with rapid and accurate diagnostics are required to mitigate global pandemics. However, RNA viruses can mutate rapidly, hampering biosurveillance and diagnostic efforts. Here, we present a novel computational approach called FEVER (Fast Evaluation of Viral Emerging Risks) to design assays that simultaneously accomplish: 1) broad-coverage biosurveillance of an entire class of viruses, 2) accurate diagnosis of an outbreak strain, and 3) mutation typing to detect variants of public health importance. We demonstrate the application of FEVER to generate assays to simultaneously 1) detect sarbecoviruses for biosurveillance; 2) diagnose infections specifically caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); and 3) perform rapid mutation typing of the D614G SARS-CoV-2 spike variant associated with increased pathogen transmissibility. These FEVER assays had a high in silico recall (predicted positive) up to 99.7% of 525,708 SARS-CoV-2 sequences analyzed and displayed sensitivities and specificities as high as 92.4% and 100% respectively when validated in 100 clinical samples. The D614G SARS-CoV-2 spike mutation PCR test was able to identify the single nucleotide identity at position 23,403 in the viral genome of 96.6% SARS-CoV-2 positive samples without the need for sequencing. This study demonstrates the utility of FEVER to design assays for biosurveillance, diagnostics, and mutation typing to rapidly detect, track, and mitigate future outbreaks and pandemics caused by emerging viruses.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.25.21257828",
+    "rel_abs": "BackgroundSerological tests are beneficial for recognizing the immune response against SARS-CoV-2. To identify protective immunity, optimization of the chemiluminescent reduction neutralizing test (CRNT), using pseudotyped SARS-CoV-2, is critical. Whether commercial antibody tests are comparably accurate is unknown.\n\nMethodsSerum samples collected before variants were locally found were obtained from confirmed COVID-19 patients (n = 74), confirmed non-COVID-19 individuals (n = 179), and unscreened individuals (suspected healthy individuals, n = 229). The convalescent phase was defined as the period after day 10 from disease onset. The CRNT against pseudotyped viruses displaying the wild-type spike protein and a commercially available anti-receptor binding domain (RBD) antibody test were assayed. The CRNT was also assayed, using South African (SA) and United Kingdom (UK)-derived variants.\n\nResultsThe CRNT (cut off value, 50% inhibition) and the anti-RBD antibody test (cut off value, 0.8 U/mL) concurred regarding symptomatic COVID-19 patients in the convalescent phase and clearly differentiated between patients and suspected healthy individuals (sensitivity; 95.8% and 100%, specificity; 99.1% and 100%, respectively). Anti-RBD antibody test results correlated with neutralizing titer (r = 0.47, 95% CI 0.20-0.68). Compared with the wild-type, CRNT reduction was observed for the SA and UK-derived variants. Of the samples with [&ge;]100 U/mL by the anti-RBD antibody test, 77.8% and 88.9% showed [&ge;]50% neutralization against the UK and the SA variants, respectively.\n\nConclusionThe CRNT and commercial anti-RBD antibody test effectively classified convalescent COVID-19 patients. The strong positive results using the commercial antibody test can reflect neutralizing activity against emerging variants.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Zachary R Stromberg",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Yoshitomo Morinaga",
+        "author_inst": "University of Toyama"
       },
       {
-        "author_name": "James Theiler",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Hideki Tani",
+        "author_inst": "Toyama Institute of Health"
       },
       {
-        "author_name": "Brian T Foley",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Yasushi Terasaki",
+        "author_inst": "Toyama City Hospital"
       },
       {
-        "author_name": "Ad\u00e1n Myers y Guti\u00e9rrez",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Satoshi Nomura",
+        "author_inst": "Toyama City Hospital"
       },
       {
-        "author_name": "Attelia Hollander",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Hitoshi Kawasuji",
+        "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences"
       },
       {
-        "author_name": "Samantha J Courtney",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Takahisa Shimada",
+        "author_inst": "Toyama Institute of Health"
       },
       {
-        "author_name": "Alina Deshpande",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Emiko Igarashi",
+        "author_inst": "Toyama Institute of Health"
       },
       {
-        "author_name": "Ebany J Martinez-Finley",
-        "author_inst": "Presbyterian Healthcare Services"
+        "author_name": "Yumiko Saga",
+        "author_inst": "Toyama Institute of Health"
       },
       {
-        "author_name": "Jason Mitchell",
-        "author_inst": "Presbyterian Healthcare Services"
+        "author_name": "Yoshihiro Yoshida",
+        "author_inst": "University of Toyama"
       },
       {
-        "author_name": "Harshini Mukundan",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Rei Yasukochi",
+        "author_inst": "University of Toyama"
       },
       {
-        "author_name": "Karina Yusim",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Makito Kaneda",
+        "author_inst": "University of Toyama"
       },
       {
-        "author_name": "Jessica Z Kubicek-Sutherland",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Yushi Murai",
+        "author_inst": "University of Toyama"
+      },
+      {
+        "author_name": "Akitoshi Ueno",
+        "author_inst": "University of Toyama"
+      },
+      {
+        "author_name": "Yuki Miyajima",
+        "author_inst": "University of Toyama"
+      },
+      {
+        "author_name": "Yasutaka Fukui",
+        "author_inst": "University of Toyama"
+      },
+      {
+        "author_name": "Kentaro Nagaoka",
+        "author_inst": "University of Toyama"
+      },
+      {
+        "author_name": "Chikako Ono",
+        "author_inst": "Osaka University"
+      },
+      {
+        "author_name": "Yoshiharu Matsuura",
+        "author_inst": "Osaka University"
+      },
+      {
+        "author_name": "Takashi Fujimura",
+        "author_inst": "Toyama City Hospital"
+      },
+      {
+        "author_name": "Yoichi Ishida",
+        "author_inst": "Toyama City Hospital"
+      },
+      {
+        "author_name": "Kazunori Oishi",
+        "author_inst": "Toyama Institute of Health"
+      },
+      {
+        "author_name": "Yoshihiro Yamamoto",
+        "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -698413,49 +701876,29 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.05.24.21257465",
-    "rel_title": "Psychological factors underpinning vaccine willingness in Israel, Japan and Hungary",
+    "rel_doi": "10.1101/2021.05.21.21257612",
+    "rel_title": "COVID-19 vaccination hesitancy model: The impact of vaccine education on controlling the outbreak in the United States",
     "rel_date": "2021-05-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.24.21257465",
-    "rel_abs": "The rapid international spread of the SARS-CoV-2 virus 19 led to unprecedented attempts to develop and administer an effective vaccine. However, there is considerable vaccine hesitancy in some countries. We investigated willingness to vaccinate in three nations with historically different levels of vaccine willingness and attitudes: Israel, Japan and Hungary. Employing an ecological-systems approach we analysed associations between demographic factors and health status, individual cognitions, normative pressures, trust in government, belief in COVID-19 myths and willingness to be vaccinated, using data from three nationally representative samples (Israel, N=1011 (Jan 2021); Japan, N= 997 (Feb 2021); Hungary, N=1131 (Apr 2021)). In Israel 74% indicated a willingness to vaccinate, but only 51% in Japan and 31% in Hungary. Multigroup regression analyses indicated greater vaccine willingness amongst those who perceived benefits to vaccination, anticipated regret if not vaccinated and trusted the government. Multi-group latent class analysis of ten COVID-19 (mis)beliefs identified three classes of myths, with concerns about the alteration of DNA (Israel), allergies (Hungary) and catching COVID-19 from the vaccine (Japan) specific to vaccine willingness for each culture. Intervention campaigns should focus on increasing trust and addressing culturally specific myths while emphasising the individual and social group benefits of vaccination.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257612",
+    "rel_abs": "The coronavirus outbreak continues to pose a significant challenge to human lives globally. Many efforts have been made to develop vaccines to combat this virus. However, with the arrival of the COVID-19 vaccine, there is hesitancy and a mixed reaction toward getting the vaccine. We develop a mathematical model to analyze and investigate the impacts of education on individuals hesitant to get vaccinated. The findings indicate that vaccine education can substantially minimize the daily cumulative cases and deaths of COVID-19 in the United States. The results also show that vaccine education significantly increases the number of willing susceptible individuals, and with a high vaccination rate and vaccine effectiveness, the outbreak can be controlled in the US.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Robin Goodwin",
-        "author_inst": "University of Warwick"
-      },
-      {
-        "author_name": "Menachem Ben-Ezra",
-        "author_inst": "Ariel University"
-      },
-      {
-        "author_name": "Masahito Takahashi",
-        "author_inst": "Yamaguchi University Japan"
-      },
-      {
-        "author_name": "Lan Anh Nguyen Luu",
-        "author_inst": "Eotvos Lorand University Budapest"
-      },
-      {
-        "author_name": "Krisztina Borsfay",
-        "author_inst": "Eotvos Lorand University Budapest"
-      },
-      {
-        "author_name": "Monika Kovacs",
-        "author_inst": "Eotvos Lorand University Budapest"
+        "author_name": "Bismark Oduro",
+        "author_inst": "California University of Pennsylvania"
       },
       {
-        "author_name": "Wai Kai Hou",
-        "author_inst": "Education University Hong Kong"
+        "author_name": "Attou Miloua",
+        "author_inst": "California University of PA"
       },
       {
-        "author_name": "Yaira Hamama-Raz",
-        "author_inst": "Ariel University"
+        "author_name": "Ofosuhene O. Apenteng",
+        "author_inst": "National Food Institute, Technical University of Denmark"
       },
       {
-        "author_name": "Yafit Levin",
-        "author_inst": "University of Zurich"
+        "author_name": "Prince P. Osei",
+        "author_inst": "University of Haifa, Mount Carmel"
       }
     ],
     "version": "1",
@@ -700163,53 +703606,25 @@
     "category": "genetic and genomic medicine"
   },
   {
-    "rel_doi": "10.1101/2021.05.25.445601",
-    "rel_title": "Genomic Surveillance of COVID-19 Variants with Language Models and Machine Learning",
+    "rel_doi": "10.1101/2021.05.24.445517",
+    "rel_title": "Evolutionary Inference Predicts Novel ACE2 Protein Interactions Relevant to COVID-19 Pathologies",
     "rel_date": "2021-05-25",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.25.445601",
-    "rel_abs": "The global efforts to control COVID-19 are threatened by the rapid emergence of novel SARS-CoV-2 variants that may display undesirable characteristics such as immune escape, increased transmissibility or pathogenicity. Early prediction for emergence of new strains with these features is critical for pandemic preparedness. We present Strainflow, a supervised and causally predictive model using unsupervised latent space features of SARS-CoV-2 genome sequences. Strainflow was trained and validated on 0.9 million sequences for the period December, 2019 to June, 2021 and the frozen model was prospectively validated from July, 2021 to December, 2021. Strainflow captured the rise in cases two months ahead of the Delta and Omicron surges in most countries including the prediction of a surge in India as early as beginning of November, 2021. Entropy analysis of Strainflow unsupervised embeddings clearly reveals the explore-exploit cycles in genomic feature-space, thus adding interpretability to the deep learning based model. We also conducted codon-level analysis of our model for interpretability and biological validity of our unsupervised features. Strainflow application is openly available as an interactive web-application for prospective genomic surveillance of COVID-19 across the globe.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.24.445517",
+    "rel_abs": "Angiotensin-converting enzyme 2 (ACE2) is the cell receptor that the coronavirus SARS-CoV-2 binds to and uses to enter and infect human cells. COVID-19, the pandemic disease caused by the coronavirus, involves diverse pathologies beyond those of a respiratory disease, including micro-thrombosis (micro-clotting), cytokine storms, and inflammatory responses affecting many organ systems. Longer-term chronic illness can persist for many months, often well after the pathogen is no longer detected. A better understanding of the proteins that ACE2 interacts with can reveal information relevant to these disease manifestations and possible avenues for treatment. We have undertaken an approach to predict candidate ACE2 interacting proteins which uses evolutionary inference to identify a set of mammalian proteins that \"coevolve\" with ACE2. The approach, called evolutionary rate correlation (ERC), detects proteins that show highly correlated evolutionary rates during mammalian evolution. Such proteins are candidates for biological interactions with the ACE2 receptor. The approach has uncovered a number of key ACE2 protein interactions of potential relevance to COVID-19 pathologies. Some proteins have previously been reported to be associated with severe COVID-19, but are not currently known to interact directly with ACE2, while additional predicted novel ACE2 interactors are of potential relevance to the disease. Using reciprocal rankings of protein ERCs, we have identified strongly interconnected ACE2 associated protein networks relevant to COVID-19 pathologies. ACE2 has clear connections to coagulation pathway proteins, such as Coagulation Factor V and fibrinogen components FGG, FGB, and FGA, the latter possibly mediated through ACE2 connections to Clusterin (which clears misfolded extracellular proteins) and GPR141 (whose functions are relatively unknown). ACE2 also connects to proteins involved in cytokine signaling and immune response (e.g. IFNAR2, XCR1, and TLR8), and to Androgen Receptor (AR). The ERC prescreening approach has also elucidated possible functions for previously uncharacterized proteins and possible new functions for well-characterized ones. Suggestions are made for the validation of ERC predicted ACE2 protein interactions. We propose that ACE2 has novel protein interactions that are disrupted during SARS-CoV-2 infection, contributing to the spectrum of COVID-19 pathologies.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Sargun Nagpal",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
-      },
-      {
-        "author_name": "Ridam Pal",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
-      },
-      {
-        "author_name": "Ashima",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
-      },
-      {
-        "author_name": "Ananya Tyagi",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
-      },
-      {
-        "author_name": "Sadhana Tripathi",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
-      },
-      {
-        "author_name": "Aditya Nagori",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
-      },
-      {
-        "author_name": "Saad Ahmad",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
-      },
-      {
-        "author_name": "Hara Prasad Mishra",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
+        "author_name": "Austin Alves Varela",
+        "author_inst": "University of Rochester"
       },
       {
-        "author_name": "Rintu Kutum",
-        "author_inst": "Indraprastha Institute of Information Technology Delhi, India"
+        "author_name": "Sammy Cheng",
+        "author_inst": "University of Rochester"
       },
       {
-        "author_name": "Tavpritesh Sethi",
-        "author_inst": "Indraprastha Institute of Information Technology"
+        "author_name": "John Haynes Werren",
+        "author_inst": "University of Rochester"
       }
     ],
     "version": "1",
@@ -701937,131 +705352,55 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.05.20.21257542",
-    "rel_title": "The maladaptive vascular response in COVID-19 acute respiratory distress syndrome and recovery",
+    "rel_doi": "10.1101/2021.05.20.21256954",
+    "rel_title": "Efficacy and safety of novel probiotic formulation in adult Covid19 outpatients: a randomized, placebo-controlled clinical trial",
     "rel_date": "2021-05-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21257542",
-    "rel_abs": "Vascular injury is a menacing element of acute respiratory distress syndrome (ARDS) pathogenesis. To better understand the role of vascular injury in COVID-19 ARDS, we used lung autopsy immunohistochemistry and blood proteomics from COVID-19 subjects at distinct timepoints in disease pathogenesis, including a hospitalized cohort at risk of ARDS development (\"at risk\", N=59), an intensive care unit cohort with ARDS (\"ARDS\", N=31), and a cohort recovering from ARDS (\"recovery\", N=12). COVID-19 ARDS lung autopsy tissue revealed an association between vascular injury and platelet-rich microthrombi. This link guided the derivation of a protein signature in the at risk cohort characterized by lower expression of vascular proteins in subjects who died, an early signal of vascular limitation termed the maladaptive vascular response. These findings were replicated in COVID-19 ARDS subjects, as well as when bacterial and influenza ARDS patients (N=29) were considered, hinting at a common final pathway of vascular injury that is more disease (ARDS) then cause (COVID-19) specific, and may be related to vascular cell death. Among recovery subjects, our vascular signature identified patients with good functional recovery one year later. This vascular injury signature could be used to identify ARDS patients most likely to benefit from vascular targeted therapies.",
-    "rel_num_authors": 28,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21256954",
+    "rel_abs": "BackgroundProbiotics have been proposed as adjuvants for Coronavirus Disease 2019 (Covid19) but randomized controlled trials (RCT) are lacking.\n\nMethodsSingle-center, quadruple-blinded RCT. Symptomatic Covid 19 outpatients (aged 18 to 60 years) with positive SARS-CoV2 nucleic acids test were randomized to active (n=150; [&ge;]2x109 colony-forming units (CFU) of probiotic strains Lactiplantibacillus plantarum KABP022, KABP023 and KAPB033, plus strain Pediococcus acidilactici KABP021) or placebo (n=150), take orally once daily for 30 days. Oral acetaminophen was allowed and controlled as co-intervention. Primary endpoint included: i) proportion of patients in complete remission (both symptoms and nucleic acids test) or progressing to moderate or severe disease with hospitalization; ii) death rate and duration on Intensive Care Unit (ICU). Safety was assessed in all patients. This study is registered at ClinicalTrials.gov (NCT04517422).\n\nFindings300 subjects were randomized (median age 37.0 years [range 18 to 60], 161 [53.7%] women, 126 [42.0%] having known metabolic risk factors), and 293 completed the study (97.7%). Remission was achieved by 78 of 147 (53.1%) in the active group compared to 41 of 146 (28.1%) in placebo (P<0.0001; ARR=25.0% [95%CI 14.1-35.9%]), still significant after multiplicity correction for the primary endpoint. No hospitalizations or deaths occurred during the study, precluding the assessment of efficacy on these endpoints. No serious adverse events occurred during the study. Replication studies with this probiotic formula are warranted.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "David R Price",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Elisa Benedetti",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Katherine Hoffman",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Luis Gomez-Escobar",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Sergio Alvarez-Mulett",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Allyson Capili",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Hina Sarwath",
-        "author_inst": "Weill Cornell Medicine-Qatar"
-      },
-      {
-        "author_name": "Christopher N. Parkhurst",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Elyse LaFond",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Karissa Weidman",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Arjun Ravishankar",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Jin Gyu Cheong",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Richa Batra",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Mustafa Buyukozkan",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Kelsey Chetnik",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Imaani Easthausen",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Pedro Gutierrez-Castrellon",
+        "author_inst": "Centro de Investigacion Translacional en Ciencias de la Salud, Hospital General Dr. Manuel Gea Gonzalez (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Edward J. Schenck",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Tania Gandara-Marti",
+        "author_inst": "Centro de Investigacion Translacional en Ciencias de la Salud, Hospital General Dr. Manuel Gea Gonzalez (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Alexandra C. Racanelli",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Hasina Outtz Reed",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Jeffrey C. Laurence",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Steven Zvi Josefowicz",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Lindsay Lief",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Ana Teresa Abreu y Abreu",
+        "author_inst": "Hospital Angeles Pedregal (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Mary E. Choi",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Cesar D Nieto-Rufino",
+        "author_inst": "Centro de Investigacion Translacional en Ciencias de la Salud, Hospital General Dr. Manuel Gea Gonzalez (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Shahin Rafii",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Eduardo Lopez-Orduna",
+        "author_inst": "DiagnoMol SA (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Frank Schmidt",
-        "author_inst": "Weill Cornell Medicine-Qatar"
+        "author_name": "Irma Jimenez-Escobar",
+        "author_inst": "Centro de Investigacion Translacional en Ciencias de la Salud, Hospital General Dr. Manuel Gea Gonzalez (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Alain C. Borczuk",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Carlos Jimenez-Gutierrez",
+        "author_inst": "Centro de Investigacion Translacional en Ciencias de la Salud, Hospital General Dr. Manuel Gea Gonzalez (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Jan Krumsiek",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Gabriel Lopez-Vazquez",
+        "author_inst": "International Scientific Council for Probiotics (Mexico City, MEXICO)"
       },
       {
-        "author_name": "Augustine M. K. Choi",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Jordi Espadaler-Mazo",
+        "author_inst": "AB-BIOTICS SA (Barcelona, SPAIN)"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "respiratory medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.05.20.21257520",
@@ -704047,193 +707386,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.05.20.21256969",
-    "rel_title": "Implementation of a qPCR assay coupled with genomic surveillance for real-time monitoring of SARS-CoV-2 variants of concern.",
+    "rel_doi": "10.1101/2021.05.19.21257439",
+    "rel_title": "Rapid And high throughput RT-qPCR assay for identification and differentiation between SARS-CoV-2 variants B.1.1.7 and B.1.351",
     "rel_date": "2021-05-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.20.21256969",
-    "rel_abs": "We developed a genomic surveillance program for real-time monitoring of SARS-CoV-2 variants of concern in Uruguay. Here, we present the first results, including the proposed qPCR-VOC method, the general workflow and the report of the introduction and community transmission of the VOC P.1 in Uruguay in multiple independent events.",
-    "rel_num_authors": 45,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.19.21257439",
+    "rel_abs": "Emerging SARS-CoV-2 (SC-2) variants with increased infectivity and vaccine resistance are of major concern. Rapid identification of such variants is important for the public health activities and provide valuable data for epidemiological and policy decision making. We developed a multiplex quantitative RT-qPCR (qPCR) assay that can specifically identify and differentiate between the emerging B.1.1.7 and B.1.351 SC-2 variants. In a single assay, we combined four reactions: one that detects SC-2 RNA independently of the strain, one that detects the D3L mutation, which is specific to variant B.1.1.7, and one that detects the 242-244 deletion, which is specific to variant B.1.351. The fourth reaction identifies human RNAseP gene, serving as an endogenous control for RNA extraction integrity. We show that the strain-specific reactions target mutations that are strongly associated with the target variants, and not with other major known variants. The assays specificity was tested against a panel of respiratory pathogens (n=16), showing high specificity towards SC-2 RNA. The assays sensitivity was assessed using both In-vitro transcribed RNA and clinical samples, and was determined to be between 20 and 40 viral RNA copies per reaction. The assay performance was corroborated with Sanger and whole genome sequencing, showing complete agreement with the sequencing results. The new assay is currently implemented in the routine diagnostic work at the Central Virology Laboratory, and may be used in other laboratories to facilitate the diagnosis of these major worldwide circulating SC-2 variants.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Natalia Rego",
-        "author_inst": "Unidad de Bioinformatica, Institut Pasteur de Montevideo."
-      },
-      {
-        "author_name": "Alicia Costabile",
-        "author_inst": "Laboratorio de Evolucion Experimental de Virus, Institut Pasteur Montevideo; Centro de Innovacion en Vigilancia Epidemiologica, Institut Pasteur Montevideo"
-      },
-      {
-        "author_name": "Mercedes Paz",
-        "author_inst": "Centro de Innovacion en Vigilancia Epidemiologica, Institut Pasteur Montevideo"
-      },
-      {
-        "author_name": "Cecilia Salazar",
-        "author_inst": "Laboratorio de Genomica Microbiana, Institut Pasteur Montevideo"
-      },
-      {
-        "author_name": "Paula Perbolianachis",
-        "author_inst": "Laboratorio de Evolucion Experimental de Virus, Institut Pasteur Montevideo;  Laboratorio de Virologia Molecular, Facultad de Ciencias, UdelaR"
-      },
-      {
-        "author_name": "Lucia Spangemberg",
-        "author_inst": "Unidad de Bioinformatica, Institut Pasteur de Montevideo"
-      },
-      {
-        "author_name": "Ignacio Ferres",
-        "author_inst": "Laboratorio de Genomica Microbiana, Institut Pasteur Montevideo"
-      },
-      {
-        "author_name": "Rodrigo Arce",
-        "author_inst": "Laboratorio de Evolucion Experimental de Virus, Institut Pasteur Montevideo;  Laboratorio de Virologia Molecular, Facultad de Ciencias, UdelaR; Laboratorio Biol"
-      },
-      {
-        "author_name": "Alvaro Fajardo",
-        "author_inst": "Laboratorio de Evolucion Experimental de Virus, Institut Pasteur Montevideo;  Laboratorio de Virologia Molecular, Facultad de Ciencias, UdelaR"
-      },
-      {
-        "author_name": "Mailen Arleo",
-        "author_inst": "Laboratorio Biologia Molecular Sanatorio Americano"
-      },
-      {
-        "author_name": "Tania Possi",
-        "author_inst": "Laboratorio Biologia Molecular Sanatorio Americano"
-      },
-      {
-        "author_name": "Ines Bellini",
-        "author_inst": "Laboratorio Biologia Molecular Sanatorio Americano"
-      },
-      {
-        "author_name": "Lucia Bilbao",
-        "author_inst": "Departamento de Genomica, Instituto de Investigaciones Biologicas Clemente Estable.  Laboratorio de Biologia Molecular, Sanatorio Americano"
-      },
-      {
-        "author_name": "Natalia Reyes",
-        "author_inst": "Laboratorio Biologia Molecular Sanatorio Americano"
-      },
-      {
-        "author_name": "Maria Noel Bentancor",
-        "author_inst": "Laboratorio Biologia Molecular Sanatorio Americano"
-      },
-      {
-        "author_name": "Andres Lizosain",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
-      },
-      {
-        "author_name": "Maria Jose Benitez",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
-      },
-      {
-        "author_name": "Matias Castells",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
-      },
-      {
-        "author_name": "Matias Victoria",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
-      },
-      {
-        "author_name": "Leticia Maya",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
-      },
-      {
-        "author_name": "Viviana Bortagaray",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
-      },
-      {
-        "author_name": "Ana Moller",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
-      },
-      {
-        "author_name": "Gonzalo Bello",
-        "author_inst": "Laboratorio de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz  Fiocruz"
-      },
-      {
-        "author_name": "Ighor Arantes",
-        "author_inst": "Laboratorio de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz  Fiocruz"
-      },
-      {
-        "author_name": "Mariana Brandes",
-        "author_inst": "Unidad de Bioinformatica, Institut Pasteur de Montevideo"
-      },
-      {
-        "author_name": "Pablo Smircich",
-        "author_inst": "Departamento de Genomica, Instituto de Investigaciones Biologicas Clemente Estable.  Laboratorio de Interacciones Moleculares, Facultad de Ciencias, UdelaR."
-      },
-      {
-        "author_name": "Odhille Chappos",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
-      },
-      {
-        "author_name": "Melissa Duquia",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
-      },
-      {
-        "author_name": "Belen Gonzalez",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
-      },
-      {
-        "author_name": "Luciana Griffero",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
+        "author_name": "Oran Erster",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Mauricio Mendez",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
+        "author_name": "Ella Mendelson",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Maria Pia Techera",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
+        "author_name": "Virginia Levy",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Juan Zanetti",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
+        "author_name": "Areej Kabat",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Bernardina Rivera",
-        "author_inst": "Laboratorio de Diagnostico Molecular, Institut Pasteur de Montevideo"
+        "author_name": "Batya Mannasse",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Matias Maidana",
-        "author_inst": "Laboratorio de Diagnostico Molecular, Institut Pasteur de Montevideo"
+        "author_name": "Hadar Asraf",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Martina Alonso",
-        "author_inst": "Laboratorio de Diagnostico Molecular, Institut Pasteur de Montevideo"
+        "author_name": "Roberto Azar",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Cecilia Alonso",
-        "author_inst": "CENUR Este-Sede Rocha-UdelaR"
+        "author_name": "Yaniv Ali",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Julio Medina",
-        "author_inst": "Ministerio de Salud Publica (Uruguay) / Catedra de Enfermedades Infecciosas, Fac. de Medicina, UdelaR."
+        "author_name": "Rachel Shirazi",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Henry Albornoz",
-        "author_inst": "Ministerio de Salud Publica (Uruguay)"
+        "author_name": "Efrat Bucris",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Rodney Colina",
-        "author_inst": "Laboratorio de Virologia Molecular. Departamento de Ciencias Biologicas. Centro Universitario Regional del Litoral Norte. UdelaR"
+        "author_name": "Dana Bar-Ilan",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Veronica Noya",
-        "author_inst": "Laboratorio Biologia Molecular Sanatorio Americano"
+        "author_name": "Orna Mor",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Gregorio Iraola",
-        "author_inst": "Institut Pasteur de Montevideo"
+        "author_name": "Michal Mandelboim",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Tamara Fernandez-Calero",
-        "author_inst": "Unidad de Bioinformatica, Institut Pasteur de Montevideo"
+        "author_name": "Danit Sofer",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Gonzalo Andres Moratorio",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Shai Fleishon",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       },
       {
-        "author_name": "Pilar Moreno",
-        "author_inst": "Universidad de la Republica. Insitut Pasteur de Montevideo"
+        "author_name": "Neta S Zukerman",
+        "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health, Chaim Sheba Medical Center, Ramat Gan, Israel"
       }
     ],
     "version": "1",
@@ -705929,21 +709152,29 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.05.21.445152",
-    "rel_title": "The Role of ATP in the RNA Translocation Mechanism of SARS-CoV-2 NSP13 Helicase",
+    "rel_doi": "10.1101/2021.05.21.445090",
+    "rel_title": "Water-triggered, irreversible conformational change of SARS-CoV-2 main protease on passing from the solid state to aqueous solution",
     "rel_date": "2021-05-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.21.445152",
-    "rel_abs": "The COVID-19 pandemic has demonstrated the need to develop potent and transferable therapeutics to treat coronavirus infections. Numerous antiviral targets are being investigated, but non-structural protein 13 (nsp13) stands out as a highly conserved and yet under studied target. Nsp13 is a superfamily 1 (SF1) helicase that translocates along and unwinds viral RNA in an ATP dependent manner. Currently, there are no available structures of nsp13 from SARS-CoV-1 or SARS-CoV-2 with either ATP or RNA bound presenting a significant hurdle to the rational design of therapeutics. To address this knowledge gap, we have built models of SARS-CoV-2 nsp13 in Apo, ATP, ssRNA and ssRNA+ATP substrate states. Using 30 s of Gaussian accelerated molecular dynamics simulation (at least 6 s per substrate state), these models were confirmed to maintain substrate binding poses that are similar to other SF1 helicases. A gaussian mixture model and linear discriminant analysis structural clustering protocol was used to identify key aspects of the ATP-dependent RNA translocation mechanism. Namely, four RNA-nsp13 structures are identified that exhibit ATP-dependent populations and support the inch-worm mechanism for translocation. These four states are characterized by different RNA-binding poses for motifs Ia, IV and V and suggest a powerstroke-like motion of domain 2A relative to domain 1A. This structural and mechanistic insight of nsp13 RNA translocation presents novel targets for the further development of antivirals.",
-    "rel_num_authors": 2,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.21.445090",
+    "rel_abs": "The main protease from SARS-CoV-2 is a homodimer. Yet, a recent 0.1 ms long molecular dynamics simulation shows that it readily undergoes a symmetry breaking event on passing from the solid state to the aqueous solution. As a result, the subunits present distinct conformations of the binding pocket. By analysing this long time simulation, here we uncover a previously unrecognised role of water molecules in triggering the transition. Interestingly, each subunit presents a different collection of long-lived water molecules. Enhanced sampling methods performed here, along with machine learning approaches, further establish that the transition to the asymmetric state is essentially irreversible.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Ryan Weber",
-        "author_inst": "Colorado State University"
+        "author_name": "Narjes Ansari",
+        "author_inst": "Italian Institute of Technology"
       },
       {
-        "author_name": "Martin McCullagh",
-        "author_inst": "Oklahoma State University"
+        "author_name": "Valerio Rizzi",
+        "author_inst": "Italian Institute of Technology"
+      },
+      {
+        "author_name": "Paolo Carloni",
+        "author_inst": "Forschungszentrum Julich"
+      },
+      {
+        "author_name": "Michele Parrinello",
+        "author_inst": "Italian Institute of Technology"
       }
     ],
     "version": "1",
@@ -707863,175 +711094,59 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2021.05.14.21257058",
-    "rel_title": "Multicenter cohort study of multisystem inflammatory syndrome in children (MIS-C)",
+    "rel_doi": "10.1101/2021.05.13.21257067",
+    "rel_title": "Contact tracing indicators for COVID-19: rapid scoping review and conceptual framework",
     "rel_date": "2021-05-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.14.21257058",
-    "rel_abs": "BACKGROUNDSARS-CoV-2 infection can lead to multisystem inflammatory syndrome in children (MIS-C). We investigated risk factors for severe disease and explored changes in severity over time.\n\nMETHODSChildren up to 17 years of age admitted March 1, 2020 through March 7th, 2021 to 15 hospitals in Canada, Iran and Costa Rica with confirmed or probable MIS-C were included. Descriptive analysis and comparison by diagnostic criteria, country, and admission date was performed. Adjusted absolute average risks (AR) and risk differences (RD) were estimated for characteristics associated with ICU admission or cardiac involvement.\n\nRESULTSOf 232 cases (106 confirmed) with median age 5.8 years, 56% were male, and 22% had comorbidities. ICU admission occurred in 73 (31%) but none died. Median length of stay was 6 days (inter-quartile range 4-9). Children 6 to 12 years old had the highest AR for ICU admission (44%; 95% confidence interval [CI] 34-53). Initial ferritin greater than 500 mcg/L was associated with ICU admission. When comparing cases admitted up to October 31, 2020 to those admitted later, the AR for ICU admission increased from 25% (CI 17-33) to 37% (CI 29-46) and for cardiac involvement from 44% (CI 35-53) to 75% (CI 66-84). Risk estimates for ICU admission in the Canadian cohort demonstrated a higher risk in December 2020-March 2021 compared to March-May 2020 (RD 25%; 95%CI 7-44).\n\nINTERPRETATIONMIS-C occurred primarily in previously well children. Illness severity appeared to increase over time. Despite a high ICU admission incidence, most children were discharged within one week.",
-    "rel_num_authors": 39,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.13.21257067",
+    "rel_abs": "BackgroundContact tracing is one of the key interventions in response to the COVID-19 pandemic but its implementation varies widely across countries. There is little guidance on how to monitor contact tracing performance, and no systematic overview of indicators to assess contact tracing systems or conceptual framework for such indicators exists to date.\n\nMethodsWe conducted a rapid scoping review using a systematic literature search strategy in the peer-reviewed and grey literature as well as open source online documents. We developed a conceptual framework to map indicators by type (input, process, output, outcome, impact) and thematic area (human resources, financial resources, case investigation, contact identification, contact testing, contact follow up, case isolation, contact quarantine, transmission chain interruption, incidence reduction).\n\nResultsWe identified a total of 153 contact tracing indicators from 1,555 peer-reviewed studies, 894 studies from grey literature sources, and 15 sources from internet searches. Two-thirds of indicators were process indicators (102; 67%), while 48 (31%) indicators were output indicators. Only three (2%) indicators were input indicators. Indicators covered seven out of ten conceptualized thematic areas, with more than half being related to either case investigation (37; 24%) or contact identification (44; 29%). There were no indicators for the input area \"financial resources\", the outcome area \"transmission chain interruption\", and the impact area \"incidence reduction\".\n\nConclusionsAlmost all identified indicators were either process or output indicators focusing on case investigation, contact identification, case isolation or contact quarantine. We identified important gaps in input, outcome and impact indicators, which constrains evidence-based assessment of contact tracing systems. A universally agreed set of indicators is needed to allow for cross-system comparisons and to improve the performance of contact tracing systems.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Joanna Merckx",
-        "author_inst": "Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal"
-      },
-      {
-        "author_name": "Suzette Cooke",
-        "author_inst": "Department of Pediatrics, University of Calgary, Calgary, Alberta"
-      },
-      {
-        "author_name": "Tala El Tal",
-        "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario"
-      },
-      {
-        "author_name": "Ronald M. Laxer",
-        "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario"
-      },
-      {
-        "author_name": "Ari Bitnun",
-        "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario"
-      },
-      {
-        "author_name": "Shaun K Morris",
-        "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario"
-      },
-      {
-        "author_name": "E Ann Yeh",
-        "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario"
-      },
-      {
-        "author_name": "Carmen Yea",
-        "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario"
-      },
-      {
-        "author_name": "Peter Gill",
-        "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario"
-      },
-      {
-        "author_name": "Jesse Papenburg",
-        "author_inst": "Department of Pediatrics, McGill University, Montreal, Quebec"
-      },
-      {
-        "author_name": "Marie-Astrid Lefebvre",
-        "author_inst": "Department of Pediatrics, McGill University, Montreal, Quebec"
-      },
-      {
-        "author_name": "Rolando Ulloa-Gutierrez",
-        "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social; San Jose, Costa Rica"
-      },
-      {
-        "author_name": "Helena Brenes-Chacon",
-        "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social; San Jose, Costa Rica"
-      },
-      {
-        "author_name": "Adriana Yock-Corrales",
-        "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social; San Jose, Costa Rica"
-      },
-      {
-        "author_name": "Gabriela Ivankovich-Escoto",
-        "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social; San Jose, Costa Rica"
-      },
-      {
-        "author_name": "Alejandra Soriano-Fallas",
-        "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social; San Jose, Costa Rica"
-      },
-      {
-        "author_name": "Marcela Hernandez-de Mezerville",
-        "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social; San Jose, Costa Rica"
-      },
-      {
-        "author_name": "Tammie Dewan",
-        "author_inst": "Department of Pediatrics, University of Calgary, Calgary, Alberta"
-      },
-      {
-        "author_name": "Lea Restivo",
-        "author_inst": "Department of Pediatrics, University of Calgary, Calgary, Alberta"
-      },
-      {
-        "author_name": "Alireza Nateghian",
-        "author_inst": "Department of Pediatrics, Iran University of Medical Sciences, Tehran, Iran"
-      },
-      {
-        "author_name": "Behzad Haghighi Aski",
-        "author_inst": "Department of Pediatrics, Iran University of Medical Sciences, Tehran, Iran"
-      },
-      {
-        "author_name": "Ali Manafi",
-        "author_inst": "Department of Pediatrics, Iran University of Medical Sciences, Tehran, Iran"
-      },
-      {
-        "author_name": "Rachel Dwilow",
-        "author_inst": "Department of Pediatrics, University of Manitoba, Winnipeg, Manitoba"
-      },
-      {
-        "author_name": "Jared Bullard",
-        "author_inst": "Department of Pediatrics, University of Manitoba, Winnipeg, Manitoba"
-      },
-      {
-        "author_name": "Alison Lopez",
-        "author_inst": "Department of Pediatrics, University of British Columbia, Vancouver, BC"
-      },
-      {
-        "author_name": "Manish Sadarangani",
-        "author_inst": "Department of Pediatrics, University of British Columbia; Vaccine Evaluation Center, BC Childrens Hospital Research Institute, Vancouver, BC"
-      },
-      {
-        "author_name": "Ashley Roberts",
-        "author_inst": "Department of Pediatrics, University of British Columbia, Vancouver, BC"
-      },
-      {
-        "author_name": "Michelle Barton",
-        "author_inst": "Department of Pediatrics, Western University, London, Ontario"
-      },
-      {
-        "author_name": "Dara Petel",
-        "author_inst": "Department of Pediatrics, Western University, London, Ontario"
-      },
-      {
-        "author_name": "Nicole Le Saux",
-        "author_inst": "Department of Pediatrics, University of Ottawa, Ottawa, Ontario"
+        "author_name": "Florian Vogt",
+        "author_inst": "University of New South Wales"
       },
       {
-        "author_name": "Jennifer Bowes",
-        "author_inst": "Department of Pediatrics, University of Ottawa, Ottawa, Ontario"
+        "author_name": "Karishma Kurup",
+        "author_inst": "Independent public health consultant, New Delhi, India"
       },
       {
-        "author_name": "Rupeena Purewal",
-        "author_inst": "Department of Pediatrics, University of Saskatchewan, Saskatoon, Saskatchewan"
+        "author_name": "Paul Mussleman",
+        "author_inst": "University of Alabama at Birmingham, Birmingham, USA"
       },
       {
-        "author_name": "Janell Lautermilch",
-        "author_inst": "Department of Pediatrics, University of Saskatchewan, Saskatoon, Saskatchewan"
+        "author_name": "Caroline Habrun",
+        "author_inst": "University of New Mexico, New Mexico Emerging Infections Program, NM, USA"
       },
       {
-        "author_name": "Sarah Tehseen",
-        "author_inst": "Department of Pediatrics, University of Saskatchewan, Saskatoon, Saskatchewan"
+        "author_name": "Madeleine Crowe",
+        "author_inst": "World Health Organization, Health Emergencies Programme, Geneva, Switzerland"
       },
       {
-        "author_name": "Ann Bayliss",
-        "author_inst": "Department of Pediatrics, Trillium Health Partners, Mississauga, Ontario"
+        "author_name": "Alexandra Woodward",
+        "author_inst": "Global Emerging Infections Surveillance, Armed Forces Health Surveillance Division, U.S. Department of Defense, Silver Spring, Maryland, United States of Americ"
       },
       {
-        "author_name": "Jacqueline K. Wong",
-        "author_inst": "Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada"
+        "author_name": "Giovanna Jaramillo-Gutierrez",
+        "author_inst": "World Health Organization, Global Outbreak Alert & Response Network, Geneva, Switzerland"
       },
       {
-        "author_name": "Kirk Leifso",
-        "author_inst": "Department of Pediatrics, Queens University, Kingston, Ontario"
+        "author_name": "John Kaldor",
+        "author_inst": "The Kirby Institute, University of New South Wales, Sydney, NSW, Australia"
       },
       {
-        "author_name": "Cheryl Foo",
-        "author_inst": "Department of Pediatrics, Memorial University, St Johns, Newfoundland and Labrador"
+        "author_name": "Sirenda Vong",
+        "author_inst": "World Health Organization, World Health Emergencies, South East Asia Regional Office, New Delhi, India"
       },
       {
-        "author_name": "Joan Robinson",
-        "author_inst": "Department of Pediatrics, University of Alberta, Edmonton, Alberta"
+        "author_name": "Victor Del Rio Vilas",
+        "author_inst": "World Health Organization, World Health Emergencies, South East Asia Regional Office, New Delhi, India"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pediatrics"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.05.18.21257110",
@@ -709489,61 +712604,41 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.05.14.21257224",
-    "rel_title": "Surveillance of COVID-19 vaccination in US nursing homes, December 2020-April 2021",
+    "rel_doi": "10.1101/2021.05.13.21257164",
+    "rel_title": "KL-MOB Automated Covid-19 Recognition Using a Novel Approach Based on Image Enhancement and a Modified MobileNet CNN",
     "rel_date": "2021-05-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.14.21257224",
-    "rel_abs": "Unstructured AbstractMonitoring COVID-19 vaccination coverage among nursing home (NH) residents and staff is important to ensure high coverage and guide patient-safety policies. With the termination of the federal Pharmacy Partnership for Long-Term Care Program, another source of facility-based vaccination data is needed. We compared numbers of COVID-19 vaccinations administered to NH residents and staff reported by pharmacies participating in the temporary federal Pharmacy Partnership for Long-Term Care Program with those reported by NHs participating in new COVID-19 vaccination modules of CDCs National Healthcare Safety Network (NHSN). Pearson correlation coefficients comparing the number vaccinated between the two approaches were 0.89, 0.96, and 0.97 for residents and 0.74, 0.90, and 0.90 for staff, in the weeks ending January 3, 10, and 17, respectively. Based on subsequent NHSN reporting, vaccination coverage with [&ge;]1 vaccine dose reached 77% for residents and 50% for staff the week ending January 31 and plateaued through April 2021.\n\nThree-question summary boxO_LIWhat is the current understanding of the subject?\nBecause of high risk of disease, nursing home residents and staff were prioritized for COVID-19 vaccination when doses were limited.\nC_LIO_LIWhat does this report add to the literature?\nNational monitoring of nursing home residents and staff vaccination coverage through the CDC National Healthcare Safety Network (NHSN) correlated with vaccination administration reports from the federal Pharmacy Partnership for Long-Term Care Program in January 2021. NHSN-reported vaccination coverage rates plateaued from February through April 2021.\nC_LIO_LIWhat are the implications for public health practice?\nNHSN can track COVID-19 vaccination in nursing homes and help guide efforts to increase vaccine uptake in residents and staff.\nC_LI",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.13.21257164",
+    "rel_abs": "The emergence of the novel coronavirus pneumonia (Covid-19) pandemic at the end of 2019 led to chaos worldwide. The world breathed a sigh of relief when some countries announced that they had obtained the appropriate vaccine and gradually began to distribute it. Nevertheless, the emergence of another wave of this disease has returned us to the starting point. At present, early detection of infected cases has been the paramount concern of both specialists and health researchers. This paper aims to detect infected patients through chest x-ray images. The large dataset available online for Covid-19 (COVIDx) was used in this research. The dataset consists of 2,128 x-ray images of Covid-19 cases, 8,066 normal cases, and 5,575 cases of pneumonia. A hybrid algorithm was applied to improve image quality before conducting the neural network training process. This algorithm consisted of combining two different noise reduction filters in the images, followed by a contrast enhancement algorithm. In this paper, for Covid-19 detection, a novel convolution neural network (CNN) architecture, KL-MOB (Covid-19 detection network based on MobileNet structure), was proposed. KL-MOB performance was boosted by adding the Kullback-Leibler (KL) divergence loss function at the end when trained from scratch. The Kullback-Leibler (KL) divergence loss function was adopted as content-based image retrieval and fine-grained classification to improve the quality of image representation. This paper yielded impressive results, overall benchmark accuracy, sensitivity, specificity, and precision of 98.7%, 98.32%, 98.82%, and 98.37%, respectively. The promising results in this research may enable other researchers to develop modern and innovative methods to aid specialists. The tremendous potential of the method proposed in this research can also be utilized to detect Covid-19 quickly and safely in patients throughout the world.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Andrew I Geller",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Mundher Mohammed Taresh",
+        "author_inst": "Computer Science, College of Information Science and Engineering, Hunan university, Chang Sha, Hunan, China"
       },
       {
-        "author_name": "Daniel S Budnitz",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Ning bo Zhu",
+        "author_inst": "Computer Science, College of Information Science and Engineering, Hunan university,  Chang Sha, Hunan, China"
       },
       {
-        "author_name": "Heather Dubendris",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Asaad Shakir Hameed",
+        "author_inst": "Department of Mathematics, General Directorate of Thi-Qar Education, Ministry of education, Iraq"
       },
       {
-        "author_name": "Radhika Gharpure",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Modhi Lafta Mutar",
+        "author_inst": "Department of Mathematics, General Directorate of Thi-Qar Education, Ministry of education, Thi-Qar, Iraq"
       },
       {
-        "author_name": "Minn Minn Soe",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Hsiu Wu",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Elizabeth J Kalayil",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Andrea L Benin",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Talal Ahmed Ali Ali Ahmed Ali Ali",
+        "author_inst": "Computer Science, College of Information Science and Engineering, Hunan university,  Chang Sha, Hunan, China"
       },
       {
-        "author_name": "Suchita A Patel",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Megan C Lindley",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Ruth Link-Gelles",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Mohammed Alghaili",
+        "author_inst": "Computer Science, College of Information Science and Engineering, Hunan university, Chang Sha, Hunan, China"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -712743,157 +715838,237 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.05.18.21257267",
-    "rel_title": "Colchicine in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial",
+    "rel_doi": "10.1101/2021.05.16.21257283",
+    "rel_title": "Early Anakinra Treatment for COVID-19 Guided by Urokinase Plasminogen Receptor",
     "rel_date": "2021-05-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.18.21257267",
-    "rel_abs": "BackgroundColchicine has been proposed as a treatment for COVID-19 on the basis of its anti-inflammatory actions.\n\nMethodsIn this randomised, controlled, open-label trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19. Eligible and consenting adults were randomly allocated in a 1:1 ratio to either usual standard of care alone or usual standard of care plus colchicine twice daily for 10 days or until discharge (or one of the other treatment arms) using web-based simple (unstratified) randomisation with allocation concealment. The primary outcome was 28-day mortality. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 27 November 2020 and 4 March 2021, 5610 patients were randomly allocated to receive colchicine and 5730 patients to receive usual care alone. Overall, 1173 (21%) patients allocated to colchicine and 1190 (21%) patients allocated to usual care died within 28 days (rate ratio 1.01; 95% confidence interval [CI] 0.93-1.10; p=0.77). Consistent results were seen in all pre-specified subgroups of patients. There was no significant difference in duration of hospitalisation (median 10 days vs. 10 days) or the proportion of patients discharged from hospital alive within 28 days (70% vs. 70%; rate ratio 0.98; 95% CI 0.94-1.03; p=0.44). Among those not on invasive mechanical ventilation at baseline, there was no significant difference in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (25% vs. 25%; risk ratio 1.02; 95% CI 0.96-1.09; p=0.47).\n\nInterpretationIn adults hospitalised with COVID-19, colchicine was not associated with reductions in 28-day mortality, duration of hospital stay, or risk of progressing to invasive mechanical ventilation or death.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056). Wellcome Trust (Grant Ref: 222406/Z/20/Z) through the COVID-19 Therapeutics Accelerator.",
-    "rel_num_authors": 35,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.16.21257283",
+    "rel_abs": "BackgroundIn a previous open-label trial, early anakinra treatment guided by elevated soluble urokinase plasminogen activator receptor (suPAR) prevented progression of COVID-19 pneumonia into respiratory failure.\n\nMethodsIn the SAVE-MORE multicenter trial, 594 hospitalized patients with moderate and severe COVID-19 pneumonia and plasma suPAR 6 ng/ml or more and receiving standard-of-care were 1:2 randomized to subcutaneous treatment with placebo or 100 mg anakinra once daily for 10 days. The primary endpoint was the overall clinical status of the 11-point World Health Organization ordinal Clinical Progression Scale (WHO-CPS) at day 28. The changes of the WHO-CPS and of the sequential organ failure assessment (SOFA) score were the main secondary endpoints.\n\nResultsAnakinra-treated patients were distributed to lower strata of WHO-CPS by day 28 (adjusted odds ratio-OR 0.36; 95%CI 0.26-0.50; P<0.001); anakinra protected from severe disease or death (6 or more points of WHO-CPS) (OR: 0.46; P: 0.010). The median absolute decrease of WHO-CPS in the placebo and anakinra groups from baseline was 3 and 4 points respectively at day 28 (OR 0.40; P<0.0001); and 2 and 3 points at day 14 (OR 0.63; P: 0.003); the absolute decrease of SOFA score was 0 and 1 points (OR 0.63; P: 0.004). 28-day mortality decreased (hazard ratio: 0.45; P: 0.045). Hospital stay was shorter.\n\nConclusionsEarly start of anakinra treatment guided by suPAR provides 2.78 times better improvement of overall clinical status in moderate and severe COVID-19 pneumonia.\n\n(Sponsored by the Hellenic Institute for the Study of Sepsis ClinicalTrials.gov identifier, NCT04680949)",
+    "rel_num_authors": 55,
     "rel_authors": [
       {
-        "author_name": "Peter W Horby",
-        "author_inst": "Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom and International Severe Acute Res"
+        "author_name": "Evdoxia Kyriazopoulou",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Mark Campbell",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and Oxford University Hospitals NHS Foundation Trust, Oxford, United King"
+        "author_name": "Garyfallia Poulakou",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Enti Spata",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un"
+        "author_name": "Haralampos Milionis",
+        "author_inst": "University of Ioannina, Medical School"
       },
       {
-        "author_name": "Jonathan R Emberson",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un"
+        "author_name": "Simeon Metallidis",
+        "author_inst": "Aristotle University of Thessaloniki, Medical School"
       },
       {
-        "author_name": "Natalie Staplin",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un"
+        "author_name": "Georgios Adamis",
+        "author_inst": "G. Gennimatas General Hospital of Athens"
       },
       {
-        "author_name": "Guilherme Pessoa-Amorim",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+        "author_name": "Konstantinos Tsiakos",
+        "author_inst": "Sotiria General Hospital of Chest Diseases"
       },
       {
-        "author_name": "Leon Peto",
-        "author_inst": "Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom and Nuffield Department of Populat"
+        "author_name": "Archontoula Fragkou",
+        "author_inst": "Elpis General Hospital of Athens"
       },
       {
-        "author_name": "Martin Wiselka",
-        "author_inst": "Department of Infectious Diseases, University Hospital Leicester, Leicester, United Kingdom"
+        "author_name": "Aggeliki Rapti",
+        "author_inst": "Sotiria General Hospital of Chest Diseases"
       },
       {
-        "author_name": "Laura Wiffen",
-        "author_inst": "Portsmouth Hospitals University NHS Foundation Trust, Portsmouth, United Kingdom"
+        "author_name": "Christina Danoulari",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Simon Tiberi",
-        "author_inst": "Department of Infection, Barts Health NHS Trust, London, United Kingdom"
+        "author_name": "Massimo Fantoni",
+        "author_inst": "Fondazione Policlinico Gemelli IRCCS"
       },
       {
-        "author_name": "Ben Caplin",
-        "author_inst": "Department of Renal Medicine, University College London, London, United Kingdom and Royal Free London NHS Trust, London, United Kingdom"
+        "author_name": "Ioannis Kalomenidis",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Caroline Wroe",
-        "author_inst": "James Cook University Hospital, Middlesbrough, United Kingdom"
+        "author_name": "Georgios Chrysos",
+        "author_inst": "Tzaneio General Hospital of Piraeus"
       },
       {
-        "author_name": "Christopher Green",
-        "author_inst": "University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom"
+        "author_name": "Andrea Angheben",
+        "author_inst": "IRCSS Sacro Cuore Hospital"
       },
       {
-        "author_name": "Paul Hine",
-        "author_inst": "Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom"
+        "author_name": "Ilias Kainis",
+        "author_inst": "Sotiria General Hospital of Chest Diseases of Athens"
       },
       {
-        "author_name": "Benjamin Prudon",
-        "author_inst": "North Tees and Hartlepool NHS Foundation Trust, Hartlepool, United Kingdom"
+        "author_name": "Zoi Alexiou",
+        "author_inst": "Thriasio General Hospital of Eleusis"
       },
       {
-        "author_name": "Tina George",
-        "author_inst": "Basildon and Thurrock Hospitals NHS Foundation Trust, Basildon, United Kingdom"
+        "author_name": "Francesco Castelli",
+        "author_inst": "Brescia ASST Spedali Civili Hospital, University of Brescia"
       },
       {
-        "author_name": "Andrew Wight",
-        "author_inst": "Wirral University Teaching Hospital NHS Foundation Trust, Birkenhead, United Kingdom"
+        "author_name": "Francesco Saverio Serino",
+        "author_inst": "Hospital of Jesolo"
       },
       {
-        "author_name": "J Kenneth Baillie",
-        "author_inst": "Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom"
+        "author_name": "Petros Bakakos",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Buddha Basnyat",
-        "author_inst": "Oxford University Clinical Research Unit -Nepal, Patan Academy of Health Sciences, Kathmandu, Nepal"
+        "author_name": "Emanuele Nicastri",
+        "author_inst": "Spallanzani Institute of Rome"
       },
       {
-        "author_name": "Maya H Buch",
-        "author_inst": "Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom"
+        "author_name": "Vassiliki Tzavara",
+        "author_inst": "Korgialeneion-Benakeion General Hospital of Athens"
       },
       {
-        "author_name": "Lucy C Chappell",
-        "author_inst": "School of Life Course Sciences, King?s College London, London, United Kingdom"
+        "author_name": "Evangelos Kostis",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Jeremy N Day",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam and Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Univer"
+        "author_name": "Lorenzo Dagna",
+        "author_inst": "IRCCS Ospedale San Raffaele & Vita-Salute San Raffaele University"
       },
       {
-        "author_name": "Saul N Faust",
-        "author_inst": "NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, "
+        "author_name": "Panagiotis Koufargyris",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Raph L Hamers",
-        "author_inst": "Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia and Faculty of Medicine, University of Indonesia, Jakarta, Indonesia and Centre for Tropical Medicine "
+        "author_name": "Katerina Dimakou",
+        "author_inst": "Sotiria General Hospital of Chest Diseases"
       },
       {
-        "author_name": "Thomas Jaki",
-        "author_inst": "Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom and MRC Biostatistics Unit, University of Cambridge, Cambridge, United"
+        "author_name": "Glykeria Tzatzagou",
+        "author_inst": "Papageorgiou General Hospital of Thessaloniki"
       },
       {
-        "author_name": "Edmund Juszczak",
-        "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom"
+        "author_name": "Maria Chini",
+        "author_inst": "Korgialeneion-Benakeion General Hospital of Athens"
       },
       {
-        "author_name": "Katie Jeffery",
-        "author_inst": "Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom"
+        "author_name": "Matteo Bassetti",
+        "author_inst": "Ospedale Policlinico San Martino IRCCS and Department of Health Sciences, University of Genova"
       },
       {
-        "author_name": "Wei Shen Lim",
-        "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom and Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Notting"
+        "author_name": "Konstantina Katrini",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Alan Montgomery",
-        "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom"
+        "author_name": "Vasileios Kotsis",
+        "author_inst": "Aristotle University of Thessaloniki, Medical School"
       },
       {
-        "author_name": "Andrew Mumford",
-        "author_inst": "School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom"
+        "author_name": "George Tsoukalas",
+        "author_inst": "Sotiria General Hospital of Chest Diseases of Athens"
       },
       {
-        "author_name": "Kathryn Rowan",
-        "author_inst": "Intensive Care National Audit & Research Centre, London, United Kingdom"
+        "author_name": "Carlo Selmi",
+        "author_inst": "Humanitas Research Hospital of Milan"
       },
       {
-        "author_name": "Guy Thwaites",
-        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam and Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Univer"
+        "author_name": "Ioannis Bliziotis",
+        "author_inst": "Asklipieio General Hospital of Voula"
       },
       {
-        "author_name": "Marion Mafham",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+        "author_name": "Michael Samarkos",
+        "author_inst": "National and Kapodistrian University of Athens"
       },
       {
-        "author_name": "Richard Haynes",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and Oxford University Hospitals NHS Foundation Trust, Oxford, United King"
+        "author_name": "Michael Doumas",
+        "author_inst": "Aristotle University of Thessaloniki, Medical School"
       },
       {
-        "author_name": "Martin J Landray",
-        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom and MRC Population Health Research Unit, University of Oxford, Oxford, Un"
+        "author_name": "Sofia Ktena",
+        "author_inst": "National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Aikaterini Masgala",
+        "author_inst": "Konstantopouleio General Hospital of Athens"
+      },
+      {
+        "author_name": "Ilias Papanikolaou",
+        "author_inst": "General Hospital of Kerkyra"
+      },
+      {
+        "author_name": "Aikaterini Argyraki",
+        "author_inst": "Sotiria General Hospital of Chest Diseases of Athens"
+      },
+      {
+        "author_name": "Chiara Simona Cardellino",
+        "author_inst": "IRCSS Sacro Cuore Hospital"
+      },
+      {
+        "author_name": "Eleni-Ioanna Katsigianni",
+        "author_inst": "Hellenic Institute for the Study of Sepsis"
+      },
+      {
+        "author_name": "Efthymia Giannitsioti",
+        "author_inst": "Tzaneio General Hospital of Piraeus"
+      },
+      {
+        "author_name": "Antonella Cingolani",
+        "author_inst": "Fondazione Policlinico Gemelli IRCCS"
+      },
+      {
+        "author_name": "Karolina Akinosoglou",
+        "author_inst": "University of Patras Medical School"
+      },
+      {
+        "author_name": "Orestis Liatsis-Douvitsas",
+        "author_inst": "Hellenic Institute for the Study of Sepsis"
+      },
+      {
+        "author_name": "Styliani Symbardi",
+        "author_inst": "Thriasio General Hospital of Eleusis"
+      },
+      {
+        "author_name": "Maria Mouktaroudi",
+        "author_inst": "National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Giuseppe Ippolito",
+        "author_inst": "INMI Lazzaro Spallanzani IRCCS"
+      },
+      {
+        "author_name": "Eleni Florou",
+        "author_inst": "Hellenic Institute for the Study of Sepsis"
+      },
+      {
+        "author_name": "Antigone Kotsaki",
+        "author_inst": "National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Mihai Netea",
+        "author_inst": "Radboud University"
+      },
+      {
+        "author_name": "jesper eugen-olsen",
+        "author_inst": "Copenhagen University Hospital Hvidovre"
+      },
+      {
+        "author_name": "Miltiades Kyprianou",
+        "author_inst": "National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Periklis Panagopoulos",
+        "author_inst": "Democritus University of Thrace, Medical School"
+      },
+      {
+        "author_name": "George N Dalekos",
+        "author_inst": "National Expertise Center of Greece in Autoimmune Liver Diseases, General University Hospital of Larissa"
+      },
+      {
+        "author_name": "Evangelos Giamarellos-Bourboulis",
+        "author_inst": "National and Kapodistrian University of Athens"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -714633,59 +717808,63 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.05.15.21256976",
-    "rel_title": "Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Mogadishu, Somalia",
+    "rel_doi": "10.1101/2021.05.12.21257123",
+    "rel_title": "Occupation and COVID-19 mortality in England: a national linked data study of 14.3 million adults",
     "rel_date": "2021-05-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.15.21256976",
-    "rel_abs": "BackgroundWhile the impact of the COVID-19 pandemic has been well documented in high-income countries, much less is known about its impact in Somalia where health systems are weak and vital registration is under developed.\n\nMethodsWe used remote sensing and geospatial analysis to quantify the number of burials from January 2017 to September 2020 in Mogadishu. We imputed missing grave counts using surface area data. Simple interpolation and a generalised additive mixed growth model were used to predict both actual and counterfactual burial rates by cemetery and across Mogadishu during the most likely period of COVID-19 excess mortality and to compute excess burials. We also undertook a qualitative survey of key informants to determine the drivers of COVID-19 excess mortality.\n\nResultsBurial rates increased during the pandemic period with a ratio to pre-pandemic levels averaging 1.5-fold and peaking at 2.2-fold. When scaled to plausible range of baseline Crude Death Rates (CDR), excess death toll between January and September 2020 ranged between 3,200 and 11,800. When compared to burial records of the Barakaat Cemetery Committee our estimates were found to be lower.\n\nConclusionsOur study points to considerable under estimation of COVID-19 impact in Banadir and an overburdened public health system struggling to deal with the increasing severity of the epidemic in 2020.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.12.21257123",
+    "rel_abs": "ObjectiveTo estimate occupational differences in COVID-19 mortality, and test whether these are confounded by factors, such as regional differences, ethnicity and education or due to non-workplace factors, such as deprivation or pre-pandemic health.\n\nDesignRetrospective cohort study\n\nSettingPeople living in private households England\n\nParticipants14,295,900 people aged 40-64 years (mean age 52 years, 51% female) who were alive on 24 January 2020, living in private households in England in 2019, were employed in 2011, and completed the 2011 census.\n\nMain outcome measuresCOVID-19 related death, assessed between 24 January 2020 and 28 December 2020. We estimated age-standardised mortality rates per 100,000 person-years at risk (ASMR) stratified by sex and occupations. To estimate the effect of occupation due to work-related exposures, we used Cox proportional hazard models to adjust for confounding (region, ethnicity, education), as well as non-workplace factors that are related to occupation.\n\nResultsThere is wide variation between occupations in COVID-19 mortality. Several occupations, particularly those involving contact with patients or the public, show three-fold or four-fold risks. These elevated risks were greatly attenuated after adjustment for confounding and mediating non-workplace factors. For example, the hazard ratio (HR) for men working as taxi and cab drivers or chauffeurs changed from 4.60 [95%CI 3.62-5.84] to 1.47 [1.14-1.89] after adjustment. More generally, the overall HR for men working in essential occupations compared with men in non-essential occupations changed from 1.45 [1.34 - 1.56] to 1.22 [1.13 - 1.32] after adjustment. For most occupations, confounding and other mediating factors explained about 70% to 80% of the age-adjusted hazard ratios.\n\nConclusionsWorking conditions are likely to play a role in COVID-19 mortality, particularly in occupations involving contact with COVID-19 patients or the public. However, there is also a substantial contribution from non-workplace factors, including regional factors, socio-demographic factors, and pre-pandemic health.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Abdihamid Warsame",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Vahe Nafilyan",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Farah Bashiir",
-        "author_inst": "Somali Disaster Resilience Institute"
+        "author_name": "Piotr Pawelek",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Terri Freemantle",
-        "author_inst": "Satellite Applications Catapult"
+        "author_name": "Daniel Ayoubkhani",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Chris Williams",
-        "author_inst": "Satellite Applications Catapult"
+        "author_name": "Sarah Rhodes",
+        "author_inst": "School of Health Sciences, University of Manchester"
       },
       {
-        "author_name": "Yolanda Vazquez",
-        "author_inst": "Satellite Applications Catapult"
+        "author_name": "Lucy Pembrey",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Chris Reeve",
-        "author_inst": "Satellite Applications Catapult"
+        "author_name": "Melissa Matz",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Ahmed Aweis",
-        "author_inst": "Somali Disaster Resilience Institute"
+        "author_name": "Michel P Coleman",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Mohamed Ahmed",
-        "author_inst": "Somali Disaster Resilience Institute"
+        "author_name": "Claudia Allemani",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Francesco Checchi",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Ben Windsor-Shellard",
+        "author_inst": "Office for National Statistics"
       },
       {
-        "author_name": "Abdirisak Dalmar",
-        "author_inst": "Somali Disaster Resilience Institute"
+        "author_name": "Martie van Tongeren",
+        "author_inst": "School of Health Sciences, University of Manchester"
+      },
+      {
+        "author_name": "Neil Pearce",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.05.13.21257144",
@@ -716570,117 +719749,41 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.05.13.444010",
-    "rel_title": "Durability of mRNA-1273-induced antibodies against SARS-CoV-2 variants",
+    "rel_doi": "10.1101/2021.05.14.444076",
+    "rel_title": "The Spike Proteins of SARS-CoV-2 B.1.617 and B.1.618 Variants Identified in India Provide Partial Resistance to Vaccine-elicited and Therapeutic Monoclonal Antibodies.",
     "rel_date": "2021-05-16",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.13.444010",
-    "rel_abs": "SARS-CoV-2 mutations may diminish vaccine-induced protective immune responses, and the durability of such responses has not been previously reported. Here, we present a comprehensive assessment of the impact of variants B.1.1.7, B.1.351, P.1, B.1.429, and B.1.526 on binding, neutralizing, and ACE2-blocking antibodies elicited by the vaccine mRNA-1273 over seven months. Cross-reactive neutralizing responses were rare after a single dose of mRNA-1273. At the peak of response to the second dose, all subjects had robust responses to all variants. Binding and functional antibodies against variants persisted in most subjects, albeit at low levels, for 6 months after the primary series of mRNA-1273. Across all assays, B.1.351 had the greatest impact on antibody recognition, and B.1.1.7 the least. These data complement ongoing studies of clinical protection to inform the potential need for additional boost vaccinations.\n\nOne-Sentence SummaryMost mRNA-1273 vaccinated individuals maintained binding and functional antibodies against SARS-CoV-2 variants for 6 months.",
-    "rel_num_authors": 25,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.14.444076",
+    "rel_abs": "Highly transmissible SARS-CoV-2 variants recently identified in India designated B.1.617 and B.1.618 have mutations within the spike protein that may contribute to their increased transmissibility and that could potentially result in re-infection or resistance to vaccine-elicited antibody. B.1.617 encodes a spike protein with mutations L452R, E484Q, D614G and P681R while the B.1.618 spike has mutations {Delta}145-146, E484K and D614G. We generated lentiviruses pseudotyped by the variant proteins and determined their resistance to neutralization by convalescent sera, vaccine-elicited antibodies and therapeutic monoclonal antibodies. Viruses with B.1.617 and B.1.618 spike were neutralized with a 2-5-fold decrease in titer by convalescent sera and vaccine-elicited antibodies. The E484Q and E484K versions were neutralized with a 2-4-fold decrease in titer. Virus with the B.1.617 spike protein was neutralized with a 4.7-fold decrease in titer by the Regeneron monoclonal antibody cocktail as a result of the L452R mutation. The modest neutralization resistance of the variant spike proteins to vaccine elicited antibody suggests that current vaccines will remain protective against the B.1.617 and B.1.618 variants.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Amarendra Pegu",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Stephen D. Schmidt",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Chloe A. Talana",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Jim Albert",
-        "author_inst": "Emmes Company, Rockville, MD, USA."
-      },
-      {
-        "author_name": "Evan Anderson",
-        "author_inst": "Department of Medicine, Center for Childhood Infections and Vaccines (CCIV) of Childrens Healthcare of Atlanta and Emory University Department of Pediatrics, At"
-      },
-      {
-        "author_name": "Hamilton Bennett",
-        "author_inst": "Moderna, Inc., Cambridge, MA, USA."
-      },
-      {
-        "author_name": "Kizzmekia Corbett",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Britta Flach",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Lisa Jackson",
-        "author_inst": "Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA."
-      },
-      {
-        "author_name": "Brett Leav",
-        "author_inst": "Moderna, Inc., Cambridge, MA, USA."
-      },
-      {
-        "author_name": "Julie E. Ledgerwood",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Catherine J. Luke",
-        "author_inst": "Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA."
-      },
-      {
-        "author_name": "Mat Makowski",
-        "author_inst": "Emmes Company, Rockville, MD, USA."
-      },
-      {
-        "author_name": "Paul C. Roberts",
-        "author_inst": "Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA."
-      },
-      {
-        "author_name": "Mario Roederer",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Paulina Alejandra Rebolledo",
-        "author_inst": "Hope Clinic, Department of Medicine, Emory University School of Medicine, Decatur, GA, USA."
-      },
-      {
-        "author_name": "Christina A. Rostad",
-        "author_inst": "Department of Medicine, Center for Childhood Infections and Vaccines (CCIV) of Childrens Healthcare of Atlanta and Emory University Department of Pediatrics, At"
-      },
-      {
-        "author_name": "Nadine G. Rouphael",
-        "author_inst": "Hope Clinic, Department of Medicine, Emory University School of Medicine, Decatur, GA, USA."
-      },
-      {
-        "author_name": "Lingshu Wang",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
-      },
-      {
-        "author_name": "Eun Sung Yang",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
+        "author_name": "Takuya Tada",
+        "author_inst": "NYU Grossman School of Medicine"
       },
       {
-        "author_name": "John H. Beigel",
-        "author_inst": "Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA."
+        "author_name": "Hao Zhou",
+        "author_inst": "NYU Grossman School of Medicine"
       },
       {
-        "author_name": "Barney S. Graham",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
+        "author_name": "Belinda M Dcosta",
+        "author_inst": "NYU Grossman School of Medicine"
       },
       {
-        "author_name": "John R. Mascola",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
+        "author_name": "Marie I Samanovic",
+        "author_inst": "NYU Grossman School of Medicine"
       },
       {
-        "author_name": "Adrian McDermott",
-        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA; Vaccine Research Center,"
+        "author_name": "Mark J Mulligan",
+        "author_inst": "NYU Grossman School of Medicine"
       },
       {
-        "author_name": "Nicole A Doria-Rose",
-        "author_inst": "National Institutes of Health"
+        "author_name": "Nathaniel R Landau",
+        "author_inst": "NYU Grossman School of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_no",
     "type": "new results",
     "category": "immunology"
   },
@@ -718800,199 +721903,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.05.13.21256639",
-    "rel_title": "Efficacy of the NVX-CoV2373 Covid-19 Vaccine Against the B.1.1.7 Variant",
+    "rel_doi": "10.1101/2021.05.06.21256757",
+    "rel_title": "COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study",
     "rel_date": "2021-05-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.13.21256639",
-    "rel_abs": "BackgroundCovid-19 vaccines are urgently needed, especially against emerging variants. NVX-CoV2373 is a recombinant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 rS) nanoparticle vaccine containing trimeric full-length SARS-CoV-2 spike glycoprotein and Matrix-M adjuvant.\n\nMethodsA phase 3, randomized, observer-blinded, placebo-controlled trial was conducted in adults 18-84 years old who received two intramuscular 5-{micro}g doses, 21 days apart, of NVX-CoV2373 or placebo (1:1) across 33 sites in the United Kingdom. The primary efficacy endpoint was virologically confirmed symptomatic Covid-19 with onset 7 days after second vaccination in serologically negative participants.\n\nResultsA total of 15,187 participants were randomized, of whom 7569 received NVX-CoV2373 and 7570 received placebo; 27.2% were 65 years or older, 44.7% had comorbidities and 4.2% had baseline serological evidence of SARS-CoV-2. There were 10 cases of Covid-19 among NVX-CoV2373 recipients and 96 cases among placebo recipients, with symptom onset at least 7 days after second vaccination; NVX-CoV2373 was 89.7% (95% confidence interval, 80.2 to 94.6) effective in preventing Covid-19, with no hospitalizations or deaths reported. There were five cases of severe Covid-19, all in the placebo group. Post hoc analysis revealed efficacies of 96.4% (73.8 to 99.5) and 86.3% (71.3 to 93.5) against the prototype strain and B.1.1.7 variant, respectively. Vaccine efficacy was similar across subgroups, including participants with comorbidities and those [&ge;]65 years old. Reactogenicity was generally mild and transient. The incidence of serious adverse events was low and similar in the two groups.\n\nConclusionA two-dose regimen of NVX-CoV2373 conferred 89.7% protection against a blend of prototype and variant Covid-19, demonstrated high efficacy against the B.1.1.7 variant, and had a reassuring safety profile.\n\n(Funded by Novavax, Inc. EudraCT number, 2020-004123-16).",
-    "rel_num_authors": 45,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256757",
+    "rel_abs": "BackgroundA large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic. However, information on the rate of outbreak occurrences which helps to identify the type of workplaces that are more likely to experience an outbreak, or infection attack rates which estimates the potential extent of the virus transmission in an outbreak, has not yet been available to inform intervention strategies to limit transmission.\n\nObjectivesTo link datasets on workplace settings and COVID-19 workplace outbreaks in England in order to: identify the geographical areas and workplace sectors with a high rate of outbreaks; and compare infection attack rates by workplace size and sector.\n\nMethodsWe analysed Public Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, covering the time period of 18 May - 12 October 2020. The workplaces analysed excluded care homes, hospitals and educational settings. We calculated the workplace outbreak rates by nine English regions, 151 Upper Tier Local Authorities (UTLAs) and twelve industrial sectors, using National Population Database (NPD) data extracted in May 2019 on the total number of the relevant workplaces as the denominator. We also calculated the infection attack rates by enterprise size (small, medium, large) and industrial sector, using PHE Situations of Interest (SOI) data on the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator, and using NPD data on the number employed in that workplace as the denominator.\n\nResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone data, of which 1,305 were available for estimation of outbreak rates. The average outbreak rate was 66 per 100,000 workplaces. Of the nine geographical regions in England, the North West had the highest workplace outbreak rate (155/100,000 workplaces), based on 351 outbreaks. Of the UTLAs, the highest workplace outbreak rate was Blackburn with Darwen (387/100,000 workplaces). The industrial sector with the highest workplace outbreak rate was manufacturers and packers of food (1,672/100,000), based on 117 outbreaks: this was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.\n\nIn total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%).\n\nConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Seth Toback",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Paul T. Heath",
-        "author_inst": "Vaccine Institute, St. George's, University of London and St. Georges University Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "Eva P. Galiza",
-        "author_inst": "Vaccine Institute, St. George's, University of London and St. Georges University Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "David Baxter",
-        "author_inst": "Stockport NHS Foundation Trust, Stepping Hill Hospital"
-      },
-      {
-        "author_name": "Marta Boffito",
-        "author_inst": "Chelsea and Westminster Hospital NHS Foundation Trust and Imperial College London"
-      },
-      {
-        "author_name": "Duncan Browne",
-        "author_inst": "Royal Cornwall Hospital NHS Trust"
-      },
-      {
-        "author_name": "Fiona Burns",
-        "author_inst": "Institute for Global Health, University College London and Royal Free London NHS Foundation Trust"
-      },
-      {
-        "author_name": "David R. Chadwick",
-        "author_inst": "Centre for Clinical Infection, South Tees Hospitals NHS Foundation Trust, James Cook University Hospital"
-      },
-      {
-        "author_name": "Rebecca Clark",
-        "author_inst": "Layton Medical Centre"
-      },
-      {
-        "author_name": "Catherine Cosgrove",
-        "author_inst": "Vaccine Institute, St. Georges, University of London and St. Georges University Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "James Galloway",
-        "author_inst": "Centre for Rheumatic Disease, Kings College London"
-      },
-      {
-        "author_name": "Anna L. Goodman",
-        "author_inst": "Guy's and St Thomas' NHS Foundation Trust, University College London"
-      },
-      {
-        "author_name": "Amardeep Heer",
-        "author_inst": "Lakeside Healthcare Research, Lakeside Surgeries Corby"
-      },
-      {
-        "author_name": "Andrew Higham",
-        "author_inst": "University Hospitals of Morecambe Bay NHS Foundation Trust"
-      },
-      {
-        "author_name": "Shalini Iyengar",
-        "author_inst": "Accelerated Enrollment Solutions, Synexus Hexham, Hexham General Hospital"
-      },
-      {
-        "author_name": "Arham Jamal",
-        "author_inst": "Accelerated Enrollment Solutions, Synexus Thames Valley"
-      },
-      {
-        "author_name": "Christopher Jeanes",
-        "author_inst": "Norfolk and Norwich University Hospital NHS Foundation Trust"
-      },
-      {
-        "author_name": "Philip A. Kalra",
-        "author_inst": "Salford Royal NHS Foundation Trust, Northern Care Alliance"
-      },
-      {
-        "author_name": "Christina Kyriakidou",
-        "author_inst": "Accelerated Enrolment Solutions, Synexus Midlands"
-      },
-      {
-        "author_name": "Daniel F. McAuley",
-        "author_inst": "Wellcome-Wolfson Institute for Experimental Medicine, Queen's University of Belfast & Royal Victoria Hospital"
-      },
-      {
-        "author_name": "Agnieszka Meyrick",
-        "author_inst": "Accelerated Enrolment Solutions, Synexus Merseyside"
-      },
-      {
-        "author_name": "Angela M. Minassian",
-        "author_inst": "Centre for Clinical Vaccinology and Tropical Medicine, University of Oxford"
-      },
-      {
-        "author_name": "Jane Minton",
-        "author_inst": "St James's University Hospital, Leeds Teaching Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Patrick Moore",
-        "author_inst": "The Adam Practice, University Hospital Southampton NHS Foundation Trust"
-      },
-      {
-        "author_name": "Imrozia Munsoor",
-        "author_inst": "Accelerated Enrolment Solutions, Synexus Glasgow"
-      },
-      {
-        "author_name": "Helen Nicholls",
-        "author_inst": "Accelerated Enrolment Solutions, Synexus Wales"
-      },
-      {
-        "author_name": "Orod Osanlou",
-        "author_inst": "Bangor University and Betsi Cadwaladr University"
-      },
-      {
-        "author_name": "Jonathan Packham",
-        "author_inst": "University of Nottingham and Haywood Hospital, Midlands Partnership NHS Foundation Trust"
-      },
-      {
-        "author_name": "Carol Pretswell",
-        "author_inst": "Accelerated Enrolment Solutions, Synexus Lancashire"
-      },
-      {
-        "author_name": "Alberto San Francisco Ramos",
-        "author_inst": "Vaccine Institute, St. George's, University of London and St. Georges University Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "Dinesh Saralaya",
-        "author_inst": "National Institute for Health Research and Bradford Teaching Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "Ray P. Sheridan",
-        "author_inst": "Royal Devon & Exeter Hospital"
-      },
-      {
-        "author_name": "Richard Smith",
-        "author_inst": "East Suffolk and North Essex NHS Foundation Trust and University of Essex"
-      },
-      {
-        "author_name": "Roy L. Soiza",
-        "author_inst": "Aberdeen Royal Infirmary, NHS Grampian & Ageing Clinical and Experimental Research (ACER) Group, University of Aberdeen"
-      },
-      {
-        "author_name": "Pauline A. Swift",
-        "author_inst": "Epsom and St Helier University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Emma C Thomson",
-        "author_inst": "University of Glasgow"
-      },
-      {
-        "author_name": "Jeremy Turner",
-        "author_inst": "Norfolk and Norwich University Hospital NHS Foundation Trust"
-      },
-      {
-        "author_name": "Marianne Elizabeth Viljoen",
-        "author_inst": "Accelerated Enrolment Solutions, Synexus Manchester"
-      },
-      {
-        "author_name": "Gary Albert",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Iksung Cho",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Filip Dubovsky",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Yiqun Chen",
+        "author_inst": "Health and Safety Executive, UK"
       },
       {
-        "author_name": "Greg Glenn",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Timothy Aldridge",
+        "author_inst": "Health and Safety Executive, UK"
       },
       {
-        "author_name": "Joy Rivers",
-        "author_inst": "Novavax, Inc."
+        "author_name": "- UK COVID-19 National Core Studies Consortium",
+        "author_inst": ""
       },
       {
-        "author_name": "Andreana Robertson",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Claire F Ferraro",
+        "author_inst": "National Infection Service, Public Health England, UK"
       },
       {
-        "author_name": "Kathy Smith",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Fu-Meng Khaw",
+        "author_inst": "Public Health England, UK"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.05.07.21256821",
@@ -721466,67 +724409,59 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.05.06.21256738",
-    "rel_title": "The evaluation of a novel digital immunochromatographic assay with silver amplification to detect SARS-CoV-2",
+    "rel_doi": "10.1101/2021.05.12.21256693",
+    "rel_title": "Nanopore Sequencing of SARS-CoV-2: Comparison of Short and Long PCR-tiling Amplicon Protocols",
     "rel_date": "2021-05-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21256738",
-    "rel_abs": "IntroductionRapid antigen tests are convenient for diagnosing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); however, they have lower sensitivities than nucleic acid amplification tests. In this study, we evaluated the diagnostic performance of Quick Chaser(R) Auto SARS-CoV-2, a novel digital immunochromatographic assay that is expected to have higher sensitivity than conventional antigen tests.\n\nMethodsA prospective observational study was conducted between February 8 and March 24, 2021. We simultaneously obtained two nasopharyngeal samples, one for evaluation with the QuickChaser(R) Auto SARS-CoV-2 antigen test and the other for assessment with reverse transcription PCR (RT-PCR), considered the gold-standard reference test. The limit of detection (LOD) of the new antigen test was compared with those of four other commercially available rapid antigen tests.\n\nResultsA total of 1401 samples were analyzed. SARS-CoV-2 was detected by reference RT-PCR in 83 (5.9%) samples, of which 36 (43.4%) were collected from symptomatic patients. The sensitivity, specificity, positive predictive value, and negative predictive value were 74.7% (95% confidence interval (CI): 64.0-83.6%), 99.8% (95% CI: 99.5-100%), 96.9% (95% CI: 89.2-99.6%), and 98.4% (95% CI: 97.6-99.0%), respectively. When limited to samples with a cycle threshold (Ct) <30 or those from symptomatic patients, the sensitivity increased to 98.3% and 88.9%, respectively. The QuickChaser(R) Auto SARS-CoV-2 detected 34-120 copies/test, which indicated greater sensitivity than the other rapid antigen tests.\n\nConclusionsQuickChaser(R) Auto SARS-CoV-2 showed sufficient sensitivity and specificity in clinical samples of symptomatic patients. The sensitivity was comparable to RT-PCR in samples with Ct<30.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.12.21256693",
+    "rel_abs": "Surveillance of the SARS-CoV-2 variants including the quickly spreading mutants by rapid and near real-time sequencing of the viral genome provides an important tool for effective health policy decision making in the ongoing COVID-19 pandemic. Here we evaluated PCR-tiling of short ([~]400-bp) and long ([~]2 and [~]2.5-kb) amplicons combined with nanopore sequencing on a MinION device for analysis of the SARS-CoV-2 genome sequences. Analysis of several sequencing runs demonstrated that using the long amplicon schemes outperforms the original protocol based on the 400-bp amplicons. It also illustrated common artefacts and problems associated with this approach, such as uneven genome coverage, variable fraction of discarded sequencing reads, as well as the reads derived from the viral sub-genomic RNAs and/or human and bacterial contamination.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Yoko Kurihara",
-        "author_inst": "University of Tsukuba Hospital"
-      },
-      {
-        "author_name": "Yoshihiko Kiyasu",
-        "author_inst": "Tsukuba Medical Center Hospital"
-      },
-      {
-        "author_name": "Yusaku Akashi",
-        "author_inst": "Tsukuba Medical Center Hospital"
+        "author_name": "Brona Brejova",
+        "author_inst": "Department of Computer Science, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava"
       },
       {
-        "author_name": "Yuto Takeuchi",
-        "author_inst": "University of Tsukuba Hospital"
+        "author_name": "Kristina Borsova",
+        "author_inst": "Institute of Virology, Biomedical Research Center of the Slovak Academy of Sciences"
       },
       {
-        "author_name": "Kenji Narahara",
-        "author_inst": "Mizuho Medy Co., Ltd."
+        "author_name": "Viktoria Hodorova",
+        "author_inst": "Department of Biochemistry, Faculty of Natural Sciences, Comenius University in Bratislava"
       },
       {
-        "author_name": "Sunao Mori",
-        "author_inst": "Mizuho Medy Co., Ltd."
+        "author_name": "Viktoria Cabanova",
+        "author_inst": "Institute of Virology, Biomedical Research Center of the Slovak Academy of Sciences"
       },
       {
-        "author_name": "Tomonori Takeshige",
-        "author_inst": "Mizuho Medy Co., Ltd."
+        "author_name": "Askar Gafurov",
+        "author_inst": "Department of Computer Science, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava"
       },
       {
-        "author_name": "Shigeyuki Notake",
-        "author_inst": "Tsukuba Medical Center Hospital"
+        "author_name": "Dominika Fricova",
+        "author_inst": "Institute of Neuroimmunology, Slovak Academy of Sciences"
       },
       {
-        "author_name": "Atsuo Ueda",
-        "author_inst": "Tsukuba Medical Center Hospital"
+        "author_name": "Martina Nebohacova",
+        "author_inst": "Department of Biochemistry, Faculty of Natural Sciences, Comenius University in Bratislava"
       },
       {
-        "author_name": "Koji Nakamura",
-        "author_inst": "Tsukuba Medical Center Hospital"
+        "author_name": "Tomas Vinar",
+        "author_inst": "Department of Applied Informatics, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava"
       },
       {
-        "author_name": "Hiroichi Ishikawa",
-        "author_inst": "Tsukuba Medical Center Hospital"
+        "author_name": "Boris Klempa",
+        "author_inst": "Institute of Virology, Biomedical Research Center of the Slovak Academy of Sciences"
       },
       {
-        "author_name": "Hiromichi Suzuki",
-        "author_inst": "University of Tsukuba"
+        "author_name": "Jozef Nosek",
+        "author_inst": "Department of Biochemistry, Faculty of Natural Sciences, Comenius University in Bratislava"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.05.12.21256874",
@@ -723208,65 +726143,45 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.05.11.21257016",
-    "rel_title": "Comparative sensitivity evaluation for 122 CE-marked SARS-CoV-2 antigen rapid tests",
+    "rel_doi": "10.1101/2021.05.10.21256996",
+    "rel_title": "Quantifying the potential for dominant spread of SARS-CoV-2 variant B.1.351 in the United States",
     "rel_date": "2021-05-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21257016",
-    "rel_abs": "ObjectiveIndependent evaluation of the sensitivity of CE-marked SARS-CoV-2 antigen rapid diagnostic tests (Ag RDT) offered in Germany.\n\nMethodThe sensitivity of 122 Ag RDT was adressed using a common evaluation panel. Minimum sensitivity of 75% for panel members with CT<25 was used for differentiation of devices eligible for reimbursement in in the German healthcare system.\n\nResultsThe sensitivity of different SARS-CoV-2 Ag RDT varied over a wide range. The sensitivity limit of 75% for panel members with CT <25 was met by 96 of the 122 tests evaluated; 26 tests exhibited lower sensitivity, few of which were completely failing. Some devices exhibited high sensitivity, e.g. 100% for CT<30.\n\nConclusionThis comparative evaluation succeeded to distinguish less sensitive from better performing Ag RDT. Most of the Ag RDT evaluated appear to be suitable for fast identification of acute infections associated with high viral loads. Market access of SARS-CoV-2 Ag RDT should be based on minimal requirements for sensitivity and specificity.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.10.21256996",
+    "rel_abs": "Recent evidence suggests that some new SARS-CoV-2 variants with spike mutations, such as P.1 (Gamma) and B.1.617.2 (Delta), exhibit partial immune evasion to antibodies generated by natural infection or vaccination. By considering the Gamma and Delta variants in a multi-variant transmission dynamic model, we evaluated the dominance of these variants in the United States (US) despite mounting vaccination coverage and other circulating variants. Our results suggest that while the dominance of the Gamma variant is improbable, the Delta variant would become the most prevalent variant in the US, driving a surge in infections and hospitalizations. Our study highlights the urgency for accelerated vaccination and continued adherence to non-pharmaceutical measures until viral circulation is driven low.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Heinrich Scheiblauer",
-        "author_inst": "Paul-Ehrlich-Institute, Paul-Ehrlich-Str. 51-59, D-63225 Langen"
-      },
-      {
-        "author_name": "Angela Filomena",
-        "author_inst": "Paul-Ehrlich-Institute, Paul-Ehrlich-Str. 51-59, D-63225 Langen"
-      },
-      {
-        "author_name": "Andreas Nitsche",
-        "author_inst": "Robert Koch-Institute, Seestrasse 10, D-13353 Berlin"
-      },
-      {
-        "author_name": "Andreas Puyskens",
-        "author_inst": "Robert Koch-Institute, Seestrasse 10, D-13353 Berlin"
-      },
-      {
-        "author_name": "Victor Corman",
-        "author_inst": "Institute of Virology, Charite, Chariteplatz 1, D-10117 Berlin"
-      },
-      {
-        "author_name": "Christian Drosten",
-        "author_inst": "Institute of Virology, Charite, Chariteplatz 1, D-10117 Berlin"
+        "author_name": "Pratha Sah",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Katrin Zwirglmaier",
-        "author_inst": "Bundeswehr Institute of Microbiology, Neuherbergstr 11, D-80937 Munich"
+        "author_name": "Thomas N Vilches",
+        "author_inst": "York University"
       },
       {
-        "author_name": "Constanze Lange",
-        "author_inst": "LADR GmbH, Lauenburger Str. 67, D-21502 Geesthacht"
+        "author_name": "Affan Shoukat",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Petra Emmerich",
-        "author_inst": "Bernhard-Nocht Institute, Dep.Virology, Bernhard-Nocht Str. 74, D-20359 Hamburg"
+        "author_name": "Meagan C Fitzpatrick",
+        "author_inst": "University of Maryland"
       },
       {
-        "author_name": "Michael Mueller",
-        "author_inst": "MVZ Labor 28 GmbH, Mecklenburgische Str. 2, D-14197 Berlin"
+        "author_name": "Abhishek Pandey",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Olivia Knauer",
-        "author_inst": "Paul-Ehrlich-Institute, Paul-Ehrlich-Str. 51-59, D-63225 Langen"
+        "author_name": "Seyed M Moghadas",
+        "author_inst": "York University"
       },
       {
-        "author_name": "Micha Nuebling",
-        "author_inst": "Paul-Ehrlich-Institut"
+        "author_name": "Alison P. Galvani",
+        "author_inst": "Yale University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -725370,103 +728285,835 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.05.11.21256479",
-    "rel_title": "Communicable and non-communicable co-morbidities and the presentation of COVID-19 in an African setting of high HIV-1 and tuberculosis prevalence",
+    "rel_doi": "10.1101/2021.05.11.21256877",
+    "rel_title": "A blood atlas of COVID-19 defines hallmarks of disease severity and specificity",
     "rel_date": "2021-05-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21256479",
-    "rel_abs": "ObjectivesTo describe the presentation and outcome of SARS-CoV2 infection in an African setting of high non-communicable co-morbidity and also HIV-1 and tuberculosis prevalence.\n\nDesignCase control analysis with cases stratified by HIV-1 and tuberculosis status.\n\nSettingA single-centre observational case-control study of adults admitted to a South African hospital with proven SARS-CoV-2 infection or alternative diagnosis.\n\nParticipants104 adults with RT-PCR-proven SARS-CoV2 infection of which 55 (52.9%) were male and 31 (29.8%) HIV-1 co-infected. 40 adults (35.7% male, 30.9% HIV-1 co-infected) admitted during the same period with no RT-PCR or serological evidence of SARS-CoV2 infection and assigned alternative diagnoses. Additional in vitro data from prior studies of 72 healthy controls and 118 HIV-1 uninfected and infected persons participants enrolled to a prior study with either immune evidence of tuberculosis sensitization but no symptoms or microbiologically confirmed pulmonary tuberculosis.\n\nResultsTwo or more co-morbidities were present in 57.7% of 104 RT-PCR proven COVID-19 presentations, the commonest being hypertension (48%), type 2 diabetes mellitus (39%), obesity (31%) but also HIV-1 (30%) and active tuberculosis (14%). Amongst patients dually infected by tuberculosis and SARS-CoV-2, clinical features could be dominated by either SARS-CoV-2 or tuberculosis: lymphopenia was exacerbated, and some markers of inflammation (D-dimer and ferritin) elevated in singly SARS-CoV-2 infected patients were even further elevated (p < 0.05). HIV-1 and SARS-CoV2 co-infection resulted in lower absolute number and proportion of CD4 lymphocytes, with those in the lowest peripheral CD4 percentage strata exhibiting absent or lower antibody responses against SARS-CoV2. Death occurred in 30/104 (29%) of all COVID-19 patients and in 6/15 (40%) of patients with coincident SARS-CoV-2 and tuberculosis.\n\nConclusionsIn this South African setting, HIV-1 and tuberculosis are common co-morbidities in patients presenting with COVID-19. In environments in which tuberculosis is common, SARS-CoV-2 and tuberculosis may co-exist with clinical presentation being typical of either disease. Clinical suspicion of exacerbation of co-existent tuberculosis accompanying SARS-CoV-2 should be high.\n\nWhat is already known on this topic?It has been quite widely thought that Africa has been spared the worst effects of the COVID-19 pandemic. There are very few reported case series and no case-control studies comparing COVID-19 patients admitted to hospital to those admitted for other reasons. However several studies have indicated both HIV-1 and tuberculosis co-infection that are endemic in Africa constitute risk factors for poor outcome. In addition Africa is subject to demographic transition and the prevalence of non-communicable co-morbidities such as type 2 diabetes, hypertension and cardiovascular disease is rising rapidly. No study from Africa has described the clinical impact on the presentation of COVID-19 infection.\n\nWhat this study addsTwo or more co-morbidities were present in over half COVID-19 presentations, including HIV-1 (30%) and active tuberculosis (14%). Patients dually infected by tuberculosis and SARS-CoV-2, presented as either SARS-CoV-2 or tuberculosis. HIV-1 and SARS-CoV2 co-infection resulted in lower absolute number and proportion of CD4 lymphocytes, and those with low CD4 counts had absent or lower antibody responses against SARS-CoV2. Death occurred 29% of all COVID-19 patients and in 40% of patients with coincident SARS-CoV-2 and tuberculosis. Thus in environments in which tuberculosis is common, SARS-CoV-2 and tuberculosis may co-exist with clinical presentation being typical of either disease and clinical suspicion of exacerbation of co-existent tuberculosis accompanying SARS-CoV-2 should be high.",
-    "rel_num_authors": 21,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21256877",
+    "rel_abs": "Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.",
+    "rel_num_authors": 204,
     "rel_authors": [
       {
-        "author_name": "Elsa du Bruyn",
-        "author_inst": "University of Cape Town"
+        "author_name": "- The COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium",
+        "author_inst": ""
       },
       {
-        "author_name": "Cari Stek",
-        "author_inst": "University of Cape Town and Imperial College London"
+        "author_name": "David J Ahern",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Remy Daroowala",
-        "author_inst": "Imperial College London and University of Cape Town"
+        "author_name": "Zhichao Ai",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Qonita Said-Hartley",
-        "author_inst": "University of Cape Town"
+        "author_name": "Mark Ainsworth",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
       },
       {
-        "author_name": "Marvin Hsiao",
-        "author_inst": "University of Cape Town"
+        "author_name": "Chris Allan",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Rene Tina Goliath",
-        "author_inst": "University of Cape Town"
+        "author_name": "Alice Allcock",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Fatima Abrahams",
-        "author_inst": "University of Cape Town"
+        "author_name": "Azim Ansari",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Amanda Jackson",
-        "author_inst": "University of Cape Town"
+        "author_name": "Carolina V Arancibia-Carcamo",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sean Wasserman",
-        "author_inst": "University of Cape Town"
+        "author_name": "Dominik Aschenbrenner",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Brian Allwood",
-        "author_inst": "University of Stellenbosch"
+        "author_name": "Moustafa Attar",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Angharad G Davis",
-        "author_inst": "University College London, Francis Crick Institute, and University of Cape Town"
+        "author_name": "J. Kenneth Baillie",
+        "author_inst": "University of Edinburgh"
       },
       {
-        "author_name": "Rachel Lai",
-        "author_inst": "Imperial College London and Francis Crick Institute"
+        "author_name": "Eleanor Barnes",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Anna Kathleen Coussens",
-        "author_inst": "Walter and Eliza Hall Institute and University of Cape Town"
+        "author_name": "Rachael Bashford-Rogers",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Katalin Andrea Wilkinson",
-        "author_inst": "The Francis Crick Institute and University of Cape Town"
+        "author_name": "Archana Bashyal",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
       },
       {
-        "author_name": "Jantina De Vries",
-        "author_inst": "University of Cape Town"
+        "author_name": "Sally Beer",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
       },
       {
-        "author_name": "Nicki Tiffin",
-        "author_inst": "University of Cape Town"
+        "author_name": "Georgina Berridge",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Maddalena Cerrone",
-        "author_inst": "Imperial College London and Francis Crick Institute"
+        "author_name": "Amy Beveridge",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Ntobeko Ntusi",
-        "author_inst": "University of Cape Town"
+        "author_name": "Sagida Bibi",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Catherine Riou",
-        "author_inst": "University of Cape Town"
+        "author_name": "Tihana Bicanic",
+        "author_inst": "St George's University of London"
       },
       {
-        "author_name": "Robert J Wilkinson",
-        "author_inst": "University of Cape Town"
+        "author_name": "Luke Blackwell",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "- HIATUS investigators",
-        "author_inst": ""
+        "author_name": "Paul Bowness",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Andrew Brent",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Andrew Brown",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "John Broxholme",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "David Buck",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Katie L Burnham",
+        "author_inst": "Wellcome Sanger Institute"
+      },
+      {
+        "author_name": "Helen Byrne",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Susana Camara",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ivan Candido Ferreira",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Philip Charles",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Wentao Chen",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Yi-Ling Chen",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Amanda Chong",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Elizabeth Clutterbuck",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Mark Coles",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Christopher P Conlon",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Richard Cornall",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Adam P Cribbs",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Fabiola Curion",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Emma E Davenport",
+        "author_inst": "Wellcome Sanger Institute"
+      },
+      {
+        "author_name": "Neil Davidson",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Simon Davis",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Calliope Dendrou",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Julie Dequaire",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Lea Dib",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "James Docker",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Christina Dold",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Tao Dong",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Damien Downes",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alexander Drakesmith",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Susanna J Dunachie",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "David A Duncan",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Chris Eijsbouts",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Robert Esnouf",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alexis Espinosa",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Rachel Etherington",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Benjamin Fairfax",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Rory Fairhead",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Hai Fang",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Shayan Fassih",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Sally Felle",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Maria Fernandez Mendoza",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Ricardo Ferreira",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Roman Fischer",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Thomas Foord",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Aden Forrow",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "John Frater",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Anastasia Fries",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Veronica Gallardo Sanchez",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Lucy Garner",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Clementine Geeves",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Dominique Georgiou",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Leila Godfrey",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Tanya Golubchik",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Maria Gomez Vazquez",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Angie Green",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Hong Harper",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Heather A Harrington",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Raphael Heilig",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Svenja Hester",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Jennifer Hill",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Charles Hinds",
+        "author_inst": "Queen Mary University of London"
+      },
+      {
+        "author_name": "Clare Hird",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Ling-Pei Ho",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Renee Hoekzema",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Benjamin Hollis",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Jim Hughes",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Paula Hutton",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Matthew Jackson",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ashwin Jainarayanan",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Anna James-Bott",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Kathrin Jansen",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Katie Jeffery",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Elizabeth Jones",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Luke Jostins",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Georgina Kerr",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "David Kim",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Paul Klenerman",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Julian C Knight",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Vinod Kumar",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Piyush Kumar Sharma",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Prathiba Kurupati",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Andrew Kwok",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Angela Lee",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Aline Linder",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Teresa Lockett",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Lorne Lonie",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Maria Lopopolo",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Martyna Lukoseviciute",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Jian Luo",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Spyridoula Marinou",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Brian Marsden",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Jose Martinez",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Philippa Matthews",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Michalina Mazurczyk",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Simon McGowan",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Stuart McKechnie",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Adam Mead",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alexander J Mentzer",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Yuxin Mi",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Claudia Monaco",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ruddy Montadon",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Giorgio Napolitani",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Isar Nassiri",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alex Novak",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Darragh O'Brien",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Daniel O'Connor",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Denise O'Donnell",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Graham Ogg",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Lauren Overend",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Inhye Park",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ian Pavord",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Yanchun Peng",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Frank Penkava",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Mariana Pereira Pinho",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Elena Perez",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Andrew J Pollard",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Fiona Powrie",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Bethan Psaila",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "T. Phuong Quan",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Emmanouela Repapi",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Santiago Revale",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Laura Silva-Reyes",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Jean-Baptiste Richard",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Charlotte Rich-Griffin",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Thomas Ritter",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Christine S Rollier",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Matthew Rowland",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Fabian Ruehle",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Mariolina Salio",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Stephen N Sansom",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alberto Santos Delgado",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Tatjana Sauka-Spengler",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Ron Schwessinger",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Giuseppe Scozzafava",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Gavin Screaton",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Anna Seigal",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Malcolm G Semple",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Martin Sergeant",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Christina Simoglou Karali",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "David Sims",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Donal Skelly",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Hubert Slawinski",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alberto Sobrinodiaz",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Nikolaos Sousos",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Lizzie Stafford",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Lisa Stockdale",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Marie Strickland",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Otto Sumray",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Bo Sun",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Chelsea Taylor",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Stephen Taylor",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Adan Taylor",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Supat Thongjuea",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Hannah Thraves",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "John A Todd",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Adriana Tomic",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Orion Tong",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Amy Trebes",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Dominik Trzupek",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Felicia A Tucci",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Lance Turtle",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Irina Udalova",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Holm Uhlig",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Erinke van Grinsven",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Iolanda Vendrell",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Marije Verheul",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Alexandru Voda",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Guanlin Wang",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Lihui Wang",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Dapeng Wang",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Peter Watkinson",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Robert Watson",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Michael Weinberger",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Justin Whalley",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Lorna Witty",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Katherine Wray",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Luzheng Xue",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Hing Yuen Yeung",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Zixi Yin",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Rebecca K Young",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust"
+      },
+      {
+        "author_name": "Jonathan Youngs",
+        "author_inst": "St George's University of London"
+      },
+      {
+        "author_name": "Ping Zhang",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Yasemin-Xiomara Zurke",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "respiratory medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.05.08.21256866",
@@ -727300,39 +730947,43 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.05.07.21256743",
-    "rel_title": "Effect of using personal protective equipment during the COVID-19 pandemic on the quality indicators of screening colonoscopies.",
+    "rel_doi": "10.1101/2021.05.08.21256792",
+    "rel_title": "Yet another lockdown? A large-scale study on people's unwillingness to be confined during the first 5 months of the COVID-19 pandemic in Spain",
     "rel_date": "2021-05-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.07.21256743",
-    "rel_abs": "BackgroundCoronavirus Disease 2019 (COVID-19) has affected many facets of the practice of medicine including screening colonoscopies.\n\nAimsOur study looks to observe if there has been an effect on the quality of colonoscopies, as indicated by quality measures such as cecal intubation rate (CIR), cecal intubation time (CIT), scope withdrawal time (SWT) and adenoma detection rate (ADR) with the adoption of standard COVID-19 precautions.\n\nMethodsWe conducted a retrospective chart review to analyze the effects of the COVID-19 pandemic on screening colonoscopies. The study utilized data on CIR, CIT, SWT and ADR from outpatient, non-emergent procedures conducted at 3 endoscopy suites of St Lukes University Health Network. All inpatient and emergent procedures were excluded.\n\nResultsOur study demonstrated that the total number of screening colonoscopies was decreased between 2019 to 2020 (318 in 2019 vs 157 in 2020, p= 0.005). CIT (320{+/-}105 seconds in 2019 vs 392{+/-}107 seconds in 2020, p=0.001) and SWT (706{+/-}232 seconds in 2019 vs 830{+/-}241 seconds in 2020, p=0.001) were increased while CIR (98.2% in 2019 vs 96.6% in 2020, p=0.04) was decreased between 2019 and 2020 likely due to PPE introduction. ADR was similar between the two groups (38.23 (12.50-66.66) in 2019 vs 38.18(16.66-66.00) in 2020, p=0.8).\n\nConclusionOur study showed that quality indices for screening colonoscopies like CIR, CIT, and SWT were negatively impacted during the COVID-19 time period. ADR, however, were similar. Thus, the efficiency of the procedures was affected by the use of PPE but it did not affect the colonoscopys clinical benefit.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256792",
+    "rel_abs": "Population confinements have been one of the most widely adopted non-pharmaceutical interventions (NPIs) implemented by governments across the globe to help contain the spread of the SARS-CoV-2 virus. While confinement measures have been proven to be effective to reduce the number of infections, they entail significant economic and social costs. Thus, different policy makers and social groups have exhibited varying levels of acceptance of this type of measures. In this context, understanding the factors that determine the willingness of individuals to be confined during a pandemic is of paramount importance, particularly, to policy and decision-makers. In this paper, we study the factors that influence the unwillingness to be confined during the COVID-19 pandemic by means of a large-scale, online population survey deployed in Spain. We apply both quantitative (logistic regression) and qualitative (automatic pattern discovery) methods and consider socio-demographic, economic and psychological factors, together with the 14-day cumulative incidence per 100,000 inhabitants. Our analysis of 109,515 answers to the survey covers data spanning over a 5-month time period to shed light on the impact of the passage of time. We find evidence of pandemic fatigue as the percentage of those who report an unwillingness to be in confinement increases over time; we identify significant gender differences, with women being generally less likely than men to be able to sustain long-term confinement of at least 6 months; we uncover that the psychological impact was the most important factor to determine the willingness to be in confinement at the beginning of the pandemic, to be replaced by the economic impact as the most important variable towards the end of our period of study. Our results highlight the need to design gender and age specific public policies, to implement psychological and economic support programs and to address the evident pandemic fatigue as the success of potential future confinements will depend on the populations willingness to comply with them.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Subin G Chirayath",
-        "author_inst": "St. Luke's University Hospital"
+        "author_name": "Marina Martinez-Garcia",
+        "author_inst": "Jaume I University"
       },
       {
-        "author_name": "Janak Bahirwani",
-        "author_inst": "St. Luke's University Hospital"
+        "author_name": "Alejandro Rabasa",
+        "author_inst": "Miguel Hernandez University"
       },
       {
-        "author_name": "Parampreet Kaur",
-        "author_inst": "St. Luke's University Hospital"
+        "author_name": "Xavier Barber",
+        "author_inst": "Miguel Hernandez University"
       },
       {
-        "author_name": "Noel Martins",
-        "author_inst": "St. Luke's University Hospital"
+        "author_name": "Kristina Polotskaya",
+        "author_inst": "Miguel Hernandez University"
       },
       {
-        "author_name": "Ronak Modi",
-        "author_inst": "St. Luke's University Hospital"
+        "author_name": "Kristof Roomp",
+        "author_inst": "Microsoft"
+      },
+      {
+        "author_name": "Nuria Oliver",
+        "author_inst": "ELLIS Unit Alicante Foundation and Data-Pop Alliance"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "gastroenterology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.05.04.21255000",
@@ -729550,31 +733201,71 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.05.05.21256668",
-    "rel_title": "COVID-19: Affect recognition through voice analysis during the winter lockdown in Scotland",
+    "rel_doi": "10.1101/2021.05.05.21256677",
+    "rel_title": "SARS-CoV-2 RNA in urban wastewater samples to monitor the COVID-19 epidemic in Lombardy, Italy (March - June 2020)",
     "rel_date": "2021-05-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.05.21256668",
-    "rel_abs": "The COVID-19 pandemic has led to unprecedented restrictions in peoples lifestyle which have affected their psychological wellbeing. In this context, this paper investigates the use of social signal processing techniques for remote assessment of emotions. It presents a machine learning method for affect recognition applied to recordings taken during the COVID-19 winter lockdown in Scotland (UK). This method is exclusively based on acoustic features extracted from voice recordings collected through home and mobile devices (i.e. phones, tablets), thus providing insight into the feasibility of monitoring peoples psychological wellbeing remotely, automatically and at scale. The proposed model is able to predict affect with a concordance correlation coefficient of 0.4230 (using Random Forest) and 0.3354 (using Decision Trees) for arousal and valence respectively.\n\nClinical relevanceIn 2018/2019, 12% and 14% of Scottish adults reported depression and anxiety symptoms. Remote emotion recognition through home devices would support the detection of these difficulties, which are often underdiagnosed and, if untreated, may lead to temporal or chronic disability.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.05.21256677",
+    "rel_abs": "Wastewater-based viral surveillance is a promising approach to monitor the circulation of SARS-CoV-2 in the general population. The aim of this study was to develop an analytical method to detect SARS-CoV-2 RNA in urban wastewater, to be implemented in the framework of a surveillance network in the Lombardy region (Northern Italy). This area was the first hotspot of COVID-19 in Europe. Composite 24h samples were collected weekly in eight cities from end-March to mid-June 2020 (first peak of the epidemic). The method developed and optimized, involved virus concentration, using PEG centrifugation, and one-step real-time RT-PCR for analysis. SARS-CoV-2 RNA was identified in 65 (61%) out of 107 samples, and the viral concentrations (up to 2.1 E +05 copies/L) were highest in March-April. By mid-June, wastewater samples tested negative in all the cities. Viral loads were used for inter-city comparison and Brembate, Ranica and Lodi had the highest. The pattern of decrease of SARS-CoV-2 in wastewater was closely comparable to the decline of active COVID-19 cases in the population, reflecting the effect of lock-down. Wastewater surveillance of SARS-CoV-2 can integrate ongoing virological surveillance of COVID-19, providing information from both symptomatic and asymptomatic individuals, and monitoring the effect of health interventions.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Sofia de la Fuente Garcia",
-        "author_inst": "The University of Edinburgh"
+        "author_name": "Sara Castiglioni",
+        "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS"
       },
       {
-        "author_name": "Fasih Haider",
-        "author_inst": "The University of Edinburgh"
+        "author_name": "Silvia Schiarea",
+        "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS"
       },
       {
-        "author_name": "Saturnino Luz",
-        "author_inst": "The University of Edinburgh"
+        "author_name": "Laura Pellegrinelli",
+        "author_inst": "University of Milan"
+      },
+      {
+        "author_name": "Valeria Primache",
+        "author_inst": "University of Milan"
+      },
+      {
+        "author_name": "Cristina Galli",
+        "author_inst": "University of Milan"
+      },
+      {
+        "author_name": "Laura Bubba",
+        "author_inst": "University of Milan"
+      },
+      {
+        "author_name": "Federica Mancinelli",
+        "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS"
+      },
+      {
+        "author_name": "Marilisa Marinelli",
+        "author_inst": "Bio-Rad Laboratories"
+      },
+      {
+        "author_name": "Danilo Cereda",
+        "author_inst": "Regione Lombardia"
+      },
+      {
+        "author_name": "Emanuela Ammoni",
+        "author_inst": "Regione Lombardia"
+      },
+      {
+        "author_name": "Elena Pariani",
+        "author_inst": "University of Milan"
+      },
+      {
+        "author_name": "Ettore Zuccato",
+        "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS"
+      },
+      {
+        "author_name": "Sandro Binda",
+        "author_inst": "University of Milan"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.05.05.21256667",
@@ -731660,95 +735351,31 @@
     "category": "genetic and genomic medicine"
   },
   {
-    "rel_doi": "10.1101/2021.05.04.21256655",
-    "rel_title": "COVID-19 cases from the first local outbreak of SARS-CoV-2 B.1.1.7 variant in China presented more serious clinical features: a prospective, comparative cohort study",
+    "rel_doi": "10.1101/2021.05.04.21256635",
+    "rel_title": "Visual Exploratory Analysis of COVID-19 Pandemic: One Year After the Outbreak",
     "rel_date": "2021-05-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256655",
-    "rel_abs": "BackgroundThe SARS-CoV-2 B.1.1.7 variant which was first identified in the United Kingdom (U.K.) has increased sharply in numbers worldwide and was reported to be more contagious. On January 17, 2021, a COVID-19 clustered outbreak caused by B.1.1.7 variant occurred in a community in Daxing District, Beijing, China. Three weeks prior, another non-variant (lineage B.1.470) COVID-19 outbreak occurred in Shunyi District, Beijing. This study aimed to investigate the clinical features of B.1.1.7 variant infection.\n\nMethodsA prospective cohort study was conducted on COVID-19 cases admitted to Ditan hospital since January 2020. Data of 74 COVID-19 cases from two independent COVID-19 outbreaks in Beijing were extracted as study subjects from a Cloud Database established in Ditan hospital, which included 41 Shunyi cases (Shunyi B.1.470 group) and 33 Daxing cases (Daxing B.1.1.7 group) that have been hospitalized since December 25, 2020 and January 17, 2021, respectively. We conducted a comparison of the clinical characteristics, RT-qPCR results and genomic features between the two groups.\n\nFindingsCases from Daxing B.1.1.7 group (15 [45.5%] male; median age, 39 years [range, 30.5, 62.5]) and cases from Shunyi B.1.470 group (25 [61.0%] male; median age, 31 years [range, 27.5, 41.0]) had a statistically significant difference in median age (P =0.014). Seven clinical indicators of Daxing B.1.1.7 group were significantly higher than Shunyi B.1.470 group including patients having fever over 38{degrees}C (14/33 [46.43%] in Daxing B.1.1.7 group vs. 9/41 (21.95%) in Shunyi B.1.470 group [P = 0 .015]), C-reactive protein ([CRP, mg/L], 4.30 [2.45, 12.1] vs. 1.80, [0.85, 4.95], [P = 0.005]), Serum amyloid A ([SAA, mg/L], 21.50 [12.50, 50.70] vs. 12.00 [5.20, 26.95], [P = 0.003]), Creatine Kinase ([CK, U/L]), 110.50 [53.15,152.40] vs. 70.40 [54.35,103.05], [P = 0.040]), D-dimer ([DD, mg/L], 0.31 [0.20, 0.48] vs. 0.24 [0.17,0.31], [P = 0.038]), CD4+ T lymphocyte ([CD4+ T, mg/L], [P = 0.003]), and Ground-glass opacity (GGO) in lung (15/33 [45.45%] vs. 5/41 [12.20%], [P =0.001]). After adjusting for the age factor, B.1.1.7 variant infection was the risk factor for CRP (P = 0.045, Odds ratio [OR] 2.791, CI [1.025, 0.8610]), SAA (0.011, 5.031, [1.459, 17.354]), CK (0.034, 4.34, [0.05, 0.91]), CD4+ T (0.029, 3.31, [1.13, 9.71]), and GGO (0.005, 5.418, [1.656, 17.729]) of patients. The median Ct value of RT-qPCR tests of the N-gene target in the Daxing B.1.1.7 group was significantly lower than the Shunyi B.1.470 group (P=0.036). The phylogenetic analysis showed that only 2 amino acid mutations in spike protein were detected in B.1.470 strains while B.1.1.7 strains had 3 deletions and 7 mutations.\n\nInterpretationClinical features including a more serious inflammatory response, pneumonia and a possible higher viral load were detected in the cases infected with B.1.1.7 SARS-CoV-2 variant. It could therefore be inferred that the B.1.1.7 variant may have increased pathogenicity.\n\nFundingThe study was funded by the National Key Research and Development Program (grant nos.2020YFC0846200 and 2020YFC0848300) and National Natural Science Foundation of China (grant no. 82072295).",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256635",
+    "rel_abs": "BackgroundGovernments across the globe have taken different measures to handle the Covid-19 outbreak since it began in early 2020. Countries implemented various policies and restrictive measures to prevent transmission of the virus, reduce the impacts of the outbreak (i.e., individual, social, and economic), and provide effective control measures. Although it has been over one year since the outbreak started, few studies have examined the long-term effects of the pandemic. Furthermore, researchers need to examine which government intervention variables are the most, and least, effective. Such analysis is critical to determine the best practices in support of policy decisions.\n\nMethodsVisual exploratory data analysis (V-EDA) offers a user-friendly data visualization model to evaluate the impact of the pandemic. It allows one to observe visual patterns of trends. The V-EDA was conducted on one year data for the COVID-19 Pandemic, one year after the outbreak between 1 January and 31 December, 2020. The data were analyzed using the students t-test to verify if there was a statistical difference between two independent groups, and the Spearman test was also used to analyze the correlation coefficient between two quantitative datasets and their positive or negative inclination.\n\nFindingsWe found that high-testing countries had more cases per million than low-testing countries. For low-testing countries, however, there was a positive correlation between the testing level and the number of cases per million. This suggests that high-testing countries tested in a preventive manner while low-testing countries may have a higher number of cases than those confirmed. The poorest developing countries have reduced testing which can coincide with the reduction in new cases, which we did not observe in the high-testing countries. Among the restrictive measures analyzed, a higher population aged 70 or older and lower GDP per capita was related to a higher case fatality ratio. Restrictive measures reduce the number of new cases after four weeks, indicating the minimum time required for the measures to have a positive effect. Finally, public event cancellation, international travel control, school closing, contact tracing, and facial coverings were the most important measures to reduce virus spread. We observed that countries with the lowest number of cases had a higher stringency index.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Yang Song M.D.",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China"
-      },
-      {
-        "author_name": "Ziruo Ge M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Shuping Cui M.Sc.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China and Peking University, Ditan Teaching Hospital, Beijing, Ch"
-      },
-      {
-        "author_name": "Di Tian M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Gang Wan M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Shuangli Zhu B.Sc.",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China"
-      },
-      {
-        "author_name": "Xianbo Wang M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Yu Wang M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Xiang Zhao M.D.",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China"
-      },
-      {
-        "author_name": "Pan Xiang M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Yanli Xu M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Tingyu Zhang M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Long Liu M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Gang Liu M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Yanhai Wang M.Sc.",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China"
-      },
-      {
-        "author_name": "Jianbo Tan M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
-      },
-      {
-        "author_name": "Wei Zhang M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
+        "author_name": "Amril Nazir",
+        "author_inst": "Zayed University"
       },
       {
-        "author_name": "Wenbo Xu M.D.",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China"
+        "author_name": "Suleyman Ulusoy",
+        "author_inst": "American University of Ras Al Khaimah"
       },
       {
-        "author_name": "Zhihai Chen M.D.",
-        "author_inst": "Emergency department of COVID-19, Beijing Ditan Hospital, Capital Medical University, Beijing, China"
+        "author_name": "Lujaini Lotfi",
+        "author_inst": "AnalytiCray Solutions"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.05.04.21256662",
@@ -733778,53 +737405,121 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2021.05.01.21256182",
-    "rel_title": "Modelling upper respiratory viral load dynamics of SARS-CoV-2",
+    "rel_doi": "10.1101/2021.05.03.21256520",
+    "rel_title": "The BNT162b2 mRNA vaccine against SARS-CoV-2 reprograms both adaptive and innate immune responses",
     "rel_date": "2021-05-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.01.21256182",
-    "rel_abs": "Relationships between viral load, severity of illness, and transmissibility of virus, are fundamental to understanding pathogenesis and devising better therapeutic and prevention strategies for COVID-19. Here we present within-host modelling of viral load dynamics observed in the upper respiratory tract (URT), drawing upon 2172 serial measurements from 605 subjects, collected from 17 different studies. We developed a mechanistic model to describe viral load dynamics and host response, and contrast this with simpler mixed-effects regression analysis of peak viral load and its subsequent decline. We observed wide variation in URT viral load between individuals, over 5 orders of magnitude, at any given point in time since symptom onset. This variation was not explained by age, sex, or severity of illness, and these variables were not associated with the modelled early or late phases of immune-mediated control of viral load. We explored the application of the mechanistic model to identify measured immune responses associated with control of viral load. Neutralizing antibody correlated strongly with modelled immune-mediated control of viral load amongst subjects who produced neutralizing antibody. Our models can be used to identify host and viral factors which control URT viral load dynamics, informing future treatment and transmission blocking interventions.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.03.21256520",
+    "rel_abs": "The mRNA-based BNT162b2 protects against severe disease and mortality caused by SARS-CoV-2 through induction of specific antibody and T-cell responses. Much less is known about its broad effects on immune responses against other pathogens. In the present study, we investigated the specific adaptive immune responses induced by BNT162b2 vaccination against various SARS-CoV-2 variants, as well as its effects on the responsiveness of human immune cells upon stimulation with heterologous viral, bacterial, and fungal pathogens. BNT162b2 vaccination induced effective humoral and cellular immunity against SARS-CoV-2 that started to wane after six months. We also observed long-term transcriptional changes in immune cells after vaccination, as assessed by RNA sequencing. Additionally, vaccination with BNT162b2 modulated innate immune responses as measured by the production of inflammatory cytokines when stimulated with various microbial stimuli other than SARS-CoV-2, including higher IL-1/IL-6 release and decreased production of IFN-. Altogether, these data expand our knowledge regarding the overall immunological effects of this new class of vaccines and underline the need of additional studies to elucidate their effects on both innate and adaptive immune responses.",
+    "rel_num_authors": 26,
     "rel_authors": [
       {
-        "author_name": "Joseph D Challenger",
-        "author_inst": "Imperial College London"
+        "author_name": "Konstantin Fohse",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Cher Y Foo",
-        "author_inst": "Imperial College London"
+        "author_name": "Busra Geckin",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Yue Wu",
-        "author_inst": "University of Cambridge"
+        "author_name": "Martijn Zoodsma",
+        "author_inst": "Helmholtz Centre for Infection Research"
       },
       {
-        "author_name": "Ada WC Yan",
-        "author_inst": "Imperial College London"
+        "author_name": "Gizem Kilic",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Mahdi Moradi Marjaneh",
-        "author_inst": "Imperial College London"
+        "author_name": "Zhaoli Liu",
+        "author_inst": "Helmholtz-Zentrum fur Infektionsforschung GmbH"
       },
       {
-        "author_name": "Felicity Liew",
-        "author_inst": "Imperial College London"
+        "author_name": "Rutger J. Roring",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Ryan S Thwaites",
-        "author_inst": "Imperial College London"
+        "author_name": "Gijs J. Overheul",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Lucy C Okell",
-        "author_inst": "Imperial College London"
+        "author_name": "Josephine S. van de Maat",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Aubrey J Cunnington",
-        "author_inst": "Imperial College London"
+        "author_name": "Ozlem Bulut",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Jacobien J. Hoogerwerf",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Jaap ten Oever",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Elles Simonetti",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Heiner Schaal",
+        "author_inst": "Institut of Virology, University Hospital Dusseldorf"
+      },
+      {
+        "author_name": "Ortwin Adams",
+        "author_inst": "Institut of Virology, University Hospital Dusseldorf"
+      },
+      {
+        "author_name": "Lisa Muller",
+        "author_inst": "Institut of Virology, University Hospital Dusseldorf"
+      },
+      {
+        "author_name": "Philipp N. Ostermann",
+        "author_inst": "Institut of Virology, University Hospital Dusseldorf"
+      },
+      {
+        "author_name": "Frank L. van de Veerdonk",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Leo A. B. Joosten",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Bart L. Haagmans",
+        "author_inst": "Erasmus medical center Rotterdam, The Netherlands"
+      },
+      {
+        "author_name": "Reinout van Crevel",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Ronald P. van Rij",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Corine GeurtsvanKessel",
+        "author_inst": "Erasmus medical center Rotterdam, The Netherlands"
+      },
+      {
+        "author_name": "Marien I. de Jonge",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Yang Li",
+        "author_inst": "Centre for Individualised Infection Medicine (CiiM) & TWINCORE, joint ventures between the Helmholtz-Centre for Infection Research (HZI) and the Hannover Medica"
+      },
+      {
+        "author_name": "Jorge Dominguez-Andres",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
+      },
+      {
+        "author_name": "Mihai G. Netea",
+        "author_inst": "Radboud university medical center Nijmegen, The Netherlands"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -735763,71 +739458,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.05.05.442782",
-    "rel_title": "Combination Respiratory Vaccine Containing Recombinant SARS-CoV-2 Spike and QuadrivalentSeasonal Influenza Hemagglutinin Nanoparticles with Matrix-M Adjuvant",
+    "rel_doi": "10.1101/2021.05.04.442701",
+    "rel_title": "SARS-CoV-2 cell-to-cell infection is resistant to neutralizing antibodies",
     "rel_date": "2021-05-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.05.442782",
-    "rel_abs": "The 2019 outbreak of a severe respiratory disease caused by an emerging coronavirus, SARS-CoV-2, has spread globally with high morbidity and mortality. Co-circulating seasonal influenza has greatly diminished recently, but expected to return with novel strains emerging, thus requiring annual strain adjustments. We have developed a recombinant hemagglutinin (HA) quadrivalent nanoparticle influenza vaccine (qNIV) produced using an established recombinant insect cell expression system to produce nanoparticles. Influenza qNIV adjuvanted with Matrix-M was well-tolerated and induced robust antibody and cellular responses, notably against both homologous and drifted A/H3N2 viruses in Phase 1, 2, and 3 trials. We also developed a full-length SARS-CoV-2 spike protein vaccine which is stable in the prefusion conformation (NVX-CoV2373) using the same platform technology. In phase 3 clinical trials, NVX-CoV2373 is highly immunogenic and protective against the prototype strain and B.1.1.7 variant. Here we describe the immunogenicity and efficacy of a combination quadrivalent seasonal flu and COVID-19 vaccine (qNIV/CoV2373) in ferret and hamster models. The combination qNIV/CoV2373 vaccine produces high titer influenza hemagglutination inhibiting (HAI) and neutralizing antibodies against influenza A and B strains. The combination vaccine also elicited antibodies that block SARS-CoV-2 spike protein binding to the human angiotensin converting enzyme-2 (hACE2) receptor. Significantly, hamsters immunized with qNIV/CoV2373 vaccine and challenged with SARS-CoV-2 were protected against weight loss and were free of replicating SARS-CoV-2 in the upper and lower respiratory tract with no evidence of viral pneumonia. This study supports evaluation of qNIV/CoV2373 combination vaccine as a preventive measure for seasonal influenza and CoVID-19.\n\nHighlightsO_LICombination qNIV/CoV2373 vaccine induced protective hemagglutination inhibition (HAI) responses to seasonal influenza A and B unchanged when formulated with recombinant spike.\nC_LIO_LICombination qNIV/CoV2373 vaccine maintained clinical and virologic protection against experimental challenge with SARS-CoV-2.\nC_LIO_LICombination qNIV/CoV2373 vaccine showed no clinical or histological sign of enhanced disease following experimental challenge with SARS-CoV-2.\nC_LIO_LICombination qNIV/CoV2373 vaccine induced antibodies against SARS-CoV-2 neutralizing epitopes common between US-WA and B.1.352 variant.\nC_LI",
-    "rel_num_authors": 13,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.04.442701",
+    "rel_abs": "The COVID-19 pandemic caused by SARS-CoV-2 has posed a global threat to human lives and economics. One of the best ways to determine protection against the infection is to quantify the neutralizing activity of serum antibodies. Multiple assays have been developed to validate SARS-CoV-2 neutralization; most of them utilized lentiviral or vesicular stomatitis virus-based particles pseudotyped with the spike (S) protein, making them safe and acceptable to work with in many labs. However, these systems are only capable of measuring infection with purified particles. This study has developed a pseudoviral assay with replication-dependent reporter vectors that can accurately quantify the level of infection directly from the virus producing cell to the permissive target cell. Comparative analysis of cell-free and cell-to-cell infection revealed that the neutralizing activity of convalescent sera was more than tenfold lower in cell cocultures than in the cell-free mode of infection. As the pseudoviral system could not properly model the mechanisms of SARS-CoV-2 transmission, similar experiments were performed with replication-competent coronavirus, which detected nearly complete SARS-CoV-2 cell-to-cell infection resistance to neutralization by convalescent sera. Based on available studies, this is the first attempt to quantitatively measure SARS-CoV-2 cell-to-cell infection, for which the mechanisms are largely unknown. The findings suggest that this route of SARS-CoV-2 transmission could be of great importance for treatment and prevention of COVID-19.\n\nImportanceImmune surveillance of viral or bacterial infections is largely mediated by neutralizing antibodies. Antibodies against the SARS-CoV-2 spike protein are produced after vaccination or infection, but their titers only partly reflect the degree of protection against infection. To identify protective antibodies, a neutralization test with replicating viruses or pseudoviruses (PVs) is required. This study developed lentiviral-based PV neutralization assays that, unlike similar systems reported earlier, enable quantitative measurement of SARS-CoV-2 neutralization in cell cocultures. Using both PVs and replication-competent virus, it was demonstrated that SARS-CoV-2 cell-to-cell infection is considerably more resistant to serum neutralization than infection with purified viral particles. The tests are easy to set up in many labs, and are believed to be more informative for monitoring SARS-CoV-2 collective immunity or entry inhibitor screening.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Micheal J Massare",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Nita Patel",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Bin Zhou",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Natalia Kruglova",
+        "author_inst": "Institute of Gene Biology RAS"
       },
       {
-        "author_name": "Sonia Maciejewski",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Rhonda Flores",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Mimi Guebre-Xabier",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Jing-Hui Tian",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Alyse D Portnoff",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Louis Fries",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Vivek Shinde",
-        "author_inst": "Novavax, Inc."
-      },
-      {
-        "author_name": "Larry R Ellingsworth",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Andrei E. Siniavin",
+        "author_inst": "Ivanovsky Institute of Virology, Gamaleya National Center for Epidemiology and Microbiology"
       },
       {
-        "author_name": "Greg Glenn",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Vladimir A. Gushchin",
+        "author_inst": "Federal Research Centre for Epidemiology and Microbiology named after the honorary academician N.F. Gamaleya"
       },
       {
-        "author_name": "Gale Smith",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Dmitriy Mazurov",
+        "author_inst": "Institute of Gene Biology RAS"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.05.04.442686",
@@ -737737,51 +741396,51 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.30.21256377",
-    "rel_title": "Disordered eating and self-harm as risk factors for poorer mental health during the COVID-19 pandemic: A population-based cohort study",
+    "rel_doi": "10.1101/2021.05.04.442648",
+    "rel_title": "Immunolocalization studies of vimentin and ACE2 on the surface of cells exposed to SARS-CoV-2 Spike proteins",
     "rel_date": "2021-05-04",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.30.21256377",
-    "rel_abs": "BackgroundYoung adults and especially those with pre-existing mental health conditions, such as disordered eating and self-harm, appear to be at greater risk of developing metal health problems during the COVID-19 pandemic. However, it is unclear whether this increased risk is affected by any changes in lockdown restrictions, and whether any lifestyle changes could moderate this increased risk.\n\nMethodsIn a longitudinal UK-based birth cohort (The Avon Longitudinal Study of Parents and Children, ALSPAC) we assessed the relationship between pre-pandemic measures of disordered eating and self-harm and mental health during the COVID-19 pandemic in 2,657 young adults. Regression models examined the relationship between self-reported disordered eating, self-harm, and both disordered eating and self-harm at age 25 years and depressive symptoms, anxiety symptoms and mental wellbeing during a period of eased restrictions in the COVID-19 pandemic (May-July 2020) when participants were aged 27-29 years. Analyses were adjusted for sex, questionnaire completion date, pre-pandemic socioeconomic disadvantage and pre-pandemic mental health and wellbeing. We also examined whether lifestyle changes (sleep, exercise, alcohol, visiting green space, eating, talking with family/friends, hobbies, relaxation) in the initial UK lockdown (April-May 2020) moderated these associations.\n\nResultsPre-existing disordered eating, self-harm and comorbid disordered eating and self-harm were all associated with the reporting of a higher frequency of depressive symptoms and anxiety symptoms, and poorer mental wellbeing during the pandemic compared to individuals without disordered eating and self-harm. Associations remained when adjusting for pre-pandemic mental health measures. There was little evidence that interactions between disordered eating and self-harm exposures and lifestyle change moderators affected pandemic mental health and wellbeing.\n\nConclusionsYoung adults with pre-pandemic disordered eating, self-harm and comorbid disordered eating and self-harm were at increased risk for developing symptoms of depression, anxiety and poor mental wellbeing during the COVID-19 pandemic, even when accounting for pre-pandemic mental health. Lifestyle changes during the pandemic do not appear to alter this risk. A greater focus on rapid and responsive service provision is essential to reduce the impact of the pandemic on the mental health of these already vulnerable individuals.\n\nPlain English summaryThe aim of this project was to explore the mental health of young adults with disordered eating behaviours (such as fasting, vomiting/taking laxatives, binge-eating and excessive exercise) and self-harm during the COVID-19 pandemic. We analysed data from an established study that has followed children from birth (in 1991 and 1992) up to present day, including during the pandemic when participants were 28 years old. We looked at the relationship between disordered eating and/or self-harm behaviours from before the pandemic and mental health problems (symptoms of depression and anxiety) and mental wellbeing during the pandemic. We also explored whether there were any lifestyle changes (such as changes in sleep, exercise, visiting green space) that might be linked to better mental health and wellbeing in young adults with disordered eating and self-harm. We found that young adults with prior disordered eating and/or self-harm had more symptoms of depression and anxiety, and worse mental wellbeing than individuals without prior disordered eating or self-harm. However, lifestyle changes did not appear to affect mental health and wellbeing in these young adults. Our findings suggest that people with a history of disordered eating and/or self-harm were at high risk for developing mental health problems during the pandemic, and they will need help from mental health services.",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.04.442648",
+    "rel_abs": "The Spike protein from SARS-CoV-2 mediates docking of the virus onto cells and contributes to viral invasion. Several cellular receptors are involved in SARS-CoV-2 Spike docking at the cell surface, including ACE2 and neuropilin. The intermediate filament protein vimentin has been reported to be present at the surface of certain cells and act as a co-receptor for several viruses; furthermore, its potential involvement in interactions with Spike proteins has been proposed. Here we have explored the binding of Spike protein constructs to several cell types using low-temperature immunofluorescence approaches in live cells, to minimize internalization. Incubation of cells with tagged Spike S or Spike S1 subunit led to discrete dotted patterns at the cell surface, which showed scarce colocalization with a lipid raft marker, but consistent coincidence with ACE2. Under our conditions, vimentin immunoreactivity appeared as spots or patches unevenly distributed at the surface of diverse cell types. Remarkably, several observations including potential antibody internalization and adherence to cells of vimentin-positive structures present in the extracellular medium exposed the complexity of vimentin cell surface immunoreactivity, which requires careful assessment. Notably, overall colocalization of Spike and vimentin signals markedly varied with the cell type and the immunodetection sequence. In turn, vimentin-positive spots moderately colocalized with ACE2; however, a particular enrichment was detected at elongated structures positive for acetylated tubulin, consistent with primary cilia, which also showed Spike binding. Thus, these results suggest that vimentin-ACE2 interaction could occur at selective locations near the cell surface, including ciliated structures, which can act as platforms for SARS-CoV-2 docking.",
     "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Naomi Warne",
-        "author_inst": "University of Bristol"
+        "author_name": "Vasiliki Lalioti",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       },
       {
-        "author_name": "Jon Heron",
-        "author_inst": "University of Bristol"
+        "author_name": "Silvia Gonz\u00e1lez-Sanz",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       },
       {
-        "author_name": "Becky Mars",
-        "author_inst": "University of Bristol"
+        "author_name": "Irene Lois-Bermejo",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       },
       {
-        "author_name": "Alex Siu Fung Kwong",
-        "author_inst": "University of Bristol"
+        "author_name": "Patricia Gonz\u00e1lez-Jim\u00e9nez",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       },
       {
-        "author_name": "Francesca Solmi",
-        "author_inst": "UCL"
+        "author_name": "\u00c1lvaro Viedma-Poyatos",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       },
       {
-        "author_name": "Rebecca Pearson",
-        "author_inst": "Univeristy of Bristol"
+        "author_name": "Andrea Merino",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       },
       {
-        "author_name": "Paul Moran",
-        "author_inst": "University of Bristol"
+        "author_name": "Mar\u00eda A Pajares",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       },
       {
-        "author_name": "Helen Bould",
-        "author_inst": "University of Bristol"
+        "author_name": "Dolores P\u00e9rez-Sala",
+        "author_inst": "Centro de Investigaciones Biol\u00f3gicas Margarita Salas, CSIC"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "cell biology"
   },
   {
     "rel_doi": "10.1101/2021.04.30.442229",
@@ -739307,18 +742966,18 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.05.04.21256298",
-    "rel_title": "Fatal cytokine release syndrome by an aberrant FLIP/STAT3 axis",
+    "rel_doi": "10.1101/2021.05.04.21256489",
+    "rel_title": "COVID-19 VACCINE PERCEPTIONS AND DIFFERENCES BY SEX, AGE, AND EDUCATION: FINDINGS FROM A CROSS-SECTIONAL ASSESSMENT OF 1367 COMMUNITY ADULTS IN ONTARIO",
     "rel_date": "2021-05-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256298",
-    "rel_abs": "Inflammatory responses rapidly detect pathogen invasion and mount a regulated reaction. However, dysregulated anti-pathogen immune responses can provoke life-threatening inflammatory pathologies collectively known as cytokine release syndrome (CRS), exemplified by key clinical phenotypes unearthed during the SARS-Cov-2 pandemic. The underlying pathophysiology of CRS remains elusive. We found that FLIP, a protein that controls caspase-8 death pathways, was highly expressed in myeloid cells of COVID-19 lungs. FLIP controlled CRS by fueling a STAT3-dependent inflammatory program. Indeed, constitutive expression of a viral FLIP homologue in myeloid cells triggered a STAT3-linked, progressive and fatal inflammatory syndrome in mice, characterized by elevated cytokine output, lymphopenia, lung injury and multiple organ dysfunctions that mimicked human CRS. As STAT3-targeting approaches relieved inflammation, immune disorders, and organ failures in these mice, targeted intervention towards this pathway could suppress the lethal CRS inflammatory state.\n\nOne sentence summaryFLIP-expressing myeloid cells are key drivers of CRS through aberrant overexpression of STAT3 pathway. STAT3-targeting is effective in mitigating CRS like severe COVID-19.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256489",
+    "rel_abs": "BackgroundCOVID-19 is a global pandemic and vaccination efforts may be impeded by vaccine hesitancy. The present study examined willingness to receive COVID-19 vaccine, the associated reasons for willingness/unwillingness, and vaccine safety perceptions in a cross-sectional assessment of community adults in Ontario.\n\nMethods1367 individuals (60.3% female, M age = 38.6) completed an online assessment between January 15, 2021 and February 15, 2021. Perceptions were investigated in general and by age, sex and education.\n\nResultsOverall, 82.8% sample reported they were willing to receive a COVID-19 vaccine and 17.2% reported they were unwilling. The three most common reasons for unwillingness were long-term side effects (65.5%), immediate side effects (60.5%), and lack of trust in the vaccine (55.2%). Vaccine willingness significantly differed by sex and education level, with female participants and those with less than a bachelors degree being more likely to report unwillingness. Perception of COVID-19 vaccine safety was significantly lower (-10.7%) than vaccines in general and differed by age, sex and education, with females, older adults, and individuals with less than a bachelors degree reporting lower perceived COVID-19 vaccine safety.\n\nConclusionIn this sample of community adults, under one in five individuals was unwilling to receive a COVID-19 vaccine, but with higher rates in population subgroups. Targeting public health messaging to females and individuals with less than Bachelors degree, and addressing concerns about long-term and immediate side effects may increase vaccine uptake.",
     "rel_num_authors": 0,
     "rel_authors": null,
     "version": "1",
     "license": "",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.05.04.21256497",
@@ -740872,163 +744531,95 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.05.01.442279",
-    "rel_title": "Signaling through Fc\u03b3RIIA and the C5a-C5aR pathway mediates platelet hyperactivation in COVID-19",
+    "rel_doi": "10.1101/2021.05.03.441080",
+    "rel_title": "Human organoid systems reveal in vitro correlates of fitness for SARS-CoV-2 B.1.1.7",
     "rel_date": "2021-05-03",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.01.442279",
-    "rel_abs": "Patients with COVID-19 present with a wide variety of clinical manifestations. Thromboembolic events constitute a significant cause of morbidity and mortality in patients infected with SARS-CoV-2. Severe COVID-19 has been associated with hyperinflammation and pre-existing cardiovascular disease. Platelets are important mediators and sensors of inflammation and are directly affected by cardiovascular stressors. In this report, we found that platelets from severely ill, hospitalized COVID-19 patients exhibit higher basal levels of activation measured by P-selectin surface expression, and have a poor functional reserve upon in vitro stimulation. Correlating clinical features to the ability of plasma from COVID-19 patients to stimulate control platelets identified ferritin as a pivotal clinical marker associated with platelet hyperactivation. The COVID-19 plasma-mediated effect on control platelets was highest for patients that subsequently developed inpatient thrombotic events. Proteomic analysis of plasma from COVID-19 patients identified key mediators of inflammation and cardiovascular disease that positively correlated with in vitro platelet activation. Mechanistically, blocking the signaling of the Fc{gamma}RIIa-Syk and C5a-C5aR pathways on platelets, using antibody-mediated neutralization, IgG depletion or the Syk inhibitor fostamatinib, reversed this hyperactivity driven by COVID-19 plasma and prevented platelet aggregation in endothelial microfluidic chamber conditions, thus identifying these potentially actionable pathways as central for platelet activation and/or vascular complications in COVID-19 patients. In conclusion, we reveal a key role of platelet-mediated immunothrombosis in COVID-19 and identify distinct, clinically relevant, targetable signaling pathways that mediate this effect. These studies have implications for the role of platelet hyperactivation in complications associated with SARS-CoV-2 infection.\n\nCover illustration O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY\n\nOne-sentence summaryThe Fc{gamma}RIIA and C5a-C5aR pathways mediate platelet hyperactivation in COVID-19",
-    "rel_num_authors": 36,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.03.441080",
+    "rel_abs": "A new phase of the COVID-19 pandemic has started as several SARS-CoV-2 variants are rapidly emerging globally, raising concerns for increased transmissibility. As animal models and traditional in vitro systems may fail to model key aspects of the SARS-CoV-2 replication cycle, representative in vitro systems to assess variants phenotypically are urgently needed. We found that the British variant (clade B.1.1.7), compared to an ancestral SARS-CoV-2 clade B virus, produced higher levels of infectious virus late in infection and had a higher replicative fitness in human airway, alveolar and intestinal organoid models. Our findings unveil human organoids as powerful tools to phenotype viral variants and suggest extended shedding as a correlate of fitness for SARS-CoV-2.\n\nOne-Sentence SummaryBritish SARS-CoV-2 variant (clade B.1.1.7) infects organoids for extended time and has a higher fitness in vitro.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Sokratis A. Apostolidis",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Amrita Sarkar",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Heather M. Giannini",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Rishi R. Goel",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Divij Mathew",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Aae Suzuki",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Amy E. Baxter",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Allison R. Greenplate",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Cecile Alanio",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Mohamed Abdel-Hakeem",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Derek A. Oldridge",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Josephine R. Giles",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Jennifer E. Wu",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Zeyu Chen",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Yinghui Jane Huang",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Ajinkya Pattekar",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Sasikanth Manne",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Oliva Kuthuru",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Mart M Lamers",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "Jeanette Dougherty",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Tim I Breugem",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "Brittany Weiderhold",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Anna Z Mykytyn",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "Ariel R. Weisman",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Yiquan Wang",
+        "author_inst": "Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA"
       },
       {
-        "author_name": "Caroline A.G. Ittner",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Nathalie Groen",
+        "author_inst": "Single Cell Discoveries, Utrecht, The Netherlands."
       },
       {
-        "author_name": "Sigrid Gouma",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Kevin Knoops",
+        "author_inst": "The Maastricht Multimodal Molecular Imaging Institute, Maastricht University, Maastricht, Netherlands."
       },
       {
-        "author_name": "Debora Dunbar",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Debby Schipper",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "Ian Frank",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Jelte van der Vaart",
+        "author_inst": "Oncode Institute, Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center, Utrecht, The Netherlands."
       },
       {
-        "author_name": "Alexander C. Huang",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Charlotte D Koopman",
+        "author_inst": "Single Cell Discoveries, Utrecht, The Netherlands."
       },
       {
-        "author_name": "Laura A. Vella",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Jingshu Zhang",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "- The UPenn COVID Processing Unit",
-        "author_inst": "-"
+        "author_name": "Douglas C Wu",
+        "author_inst": "Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA"
       },
       {
-        "author_name": "John P. Reilly",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Petra B van den Doel",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "Scott E. Hensley",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Theo Bestebroer",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "Lubica Rauova",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Corine C GeurtsvanKessel",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       },
       {
-        "author_name": "Liang Zhao",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Peter J Peters",
+        "author_inst": "The Maastricht Multimodal Molecular Imaging Institute, Maastricht University, Maastricht, Netherlands."
       },
       {
-        "author_name": "Nuala J. Meyer",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Mauro J Muraro",
+        "author_inst": "Single Cell Discoveries, Utrecht, The Netherlands."
       },
       {
-        "author_name": "Mortimer Poncz",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Hans Clevers",
+        "author_inst": "Oncode Institute, Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Center, Utrecht, The Netherlands."
       },
       {
-        "author_name": "Charles S. Abrams",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Nicholas C Wu",
+        "author_inst": "Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA"
       },
       {
-        "author_name": "E John Wherry",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Bart L Haagmans",
+        "author_inst": "Viroscience Department, Erasmus Medical Center, Rotterdam, Netherlands."
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.05.01.442304",
@@ -742714,39 +746305,35 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.04.28.21256146",
-    "rel_title": "The causal effects of chronic air pollution on the intensity of COVID-19 disease: Some answers are blowing in the wind",
+    "rel_doi": "10.1101/2021.04.27.21256210",
+    "rel_title": "U.S. Regional Differences in Physical Distancing: Evaluating Racial and Socioeconomic Divides During the COVID-19 Pandemic",
     "rel_date": "2021-04-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.28.21256146",
-    "rel_abs": "The threats posed by COVID-19 have catalyzed a search by researchers across multiple disciplines for policy-relevant findings about critical risk factors. We contribute to this effort by providing causal estimates of the link between increased chronic ambient pollutant concentrations and the intensity of COVID-19 disease, as measured by deaths and hospitalizations in New York City from March through August, 2020. Given concerns about unobservable characteristics that contribute to both ambient air pollutant concentrations and the impacts of COVID-19 disease, we instrument for pollutant concentrations using the time spent downwind of nearby highways and estimate key causal relationships using two-stage least squares models. The causal links between increases in concentrations of our traffic-related air pollutants (PM2.5, NO2, and NO) and COVID-19 deaths are much larger than the correlations presented in recent observational studies. We find that a 0.16 g/m3 increase in average ambient PM2.5 concentration leads to an approximate 30% increase in COVID-19 deaths. This is the change in concentration associated with being downwind of a nearby highway. We see that this effect is mostly driven by residents with at least 75 years of age. In addition to emphasizing the importance of searching for causal relationships, our analysis highlights the value of increasing the density of pollution-monitoring networks and suggests potential benefits of further tightening of Clean Air Act amendments, as our estimated effects occur at concentrations well below thresholds set by the National Ambient Air Quality Standards.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.27.21256210",
+    "rel_abs": "Health varies by U.S. region of residence. Despite regional heterogeneity in the outbreak of COVID-19, regional differences in physical distancing behaviors over time are relatively unknown. This study examines regional variation in physical distancing trends during the COVID-19 pandemic and investigates variation by race and socioeconomic status (SES) within regions.\n\nData from the 2015-2019 five-year American Community Survey were matched with anonymized location pings data from over 20 million mobile devices (SafeGraph, Inc.) at the Census block group level. We visually present trends in the stay-at-home proportion by Census region, race, and SES throughout 2020 and conduct regression analyses to statistically examine these patterns.\n\nFrom March to December, the stay-at-home proportion was highest in the Northeast (0.25 in March to 0.35 in December) and lowest in the South (0.24 to 0.30). Across all regions, the stay-at-home proportion was higher in block groups with a higher percentage of Blacks, as Blacks disproportionately live in urban areas where stay-at-home rates were higher (0.009 [CI: 0.008, 0.009]). In the South, West, and Midwest, higher-SES block groups stayed home at the lowest rates pre-pandemic; however, this trend reversed throughout March before converging in the months following. In the Northeast, lower-SES block groups stayed home at comparable rates to higher-SES block groups during the height of the pandemic but diverged in the months following.\n\nDifferences in physical distancing behaviors exist across U.S. regions, with a pronounced Southern and rural disadvantage. Results can be used to guide reopening and COVID-19 mitigation plans.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Marc N Conte",
-        "author_inst": "Fordham University"
-      },
-      {
-        "author_name": "Matthew Gordon",
+        "author_name": "Emma Zang",
         "author_inst": "Yale University"
       },
       {
-        "author_name": "Nicole Swartwood",
-        "author_inst": "Harvard T.H. Chan School"
+        "author_name": "Jessica West",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Rachel Wilwerding",
-        "author_inst": "Fordham University"
+        "author_name": "Nathan Kim",
+        "author_inst": "Yale University"
       },
       {
-        "author_name": "Chu A. (Alex) Yu",
-        "author_inst": "Wake Forest University"
+        "author_name": "Christina Pao",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.04.29.21256267",
@@ -744314,39 +747901,43 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2021.04.28.21255760",
-    "rel_title": "SARS-CoV-2 infections in nasal epithelial cells from smokers versus non-smokers",
+    "rel_doi": "10.1101/2021.04.27.21255023",
+    "rel_title": "Large university with high COVID-19 incidence did not increase risk to non-student population",
     "rel_date": "2021-04-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.28.21255760",
-    "rel_abs": "Whether smoking exacerbates Coronavirus disease 2019 is still debated. Ex-vivo Infection of reconstituted epithelial tissues from smoker versus non-smoker donors suggested comparable susceptibility to SARS-CoV-2 in epithelia from both groups.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.27.21255023",
+    "rel_abs": "Large US colleges and universities that re-opened campuses in the fall of 2020 and the spring of 2021 experienced high per capita rates of COVID-19. Returns to campus were controversial because they posed a risk to the surrounding communities. A large university in Pennsylvania that returned to in-person instruction in the fall of 2020 and spring of 2021 reported high incidence of COVID-19 among students. However, the co-located non-student resident population in the county experienced fewer COVID-19 cases per capita than reported in neighboring counties. Activity patterns from mobile devices indicate that the non-student resident population near the university restricted their movements during the pandemic more than residents of neighboring counties. Preventing cases in student and non-student populations requires different, specifically targeted strategies.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Manel Essaidi-Laziosi",
-        "author_inst": "University of Geneva - Faculty of Medicine 1 rue Michel-Servet     CH-1211 Geneva 4"
+        "author_name": "Nita Bharti",
+        "author_inst": "The Pennsylvania State University"
       },
       {
-        "author_name": "Giulia Torriani",
-        "author_inst": "University of Geneva - Faculty of Medicine 1 rue Michel-Servet     CH-1211 Geneva 4"
+        "author_name": "Brian Lambert",
+        "author_inst": "The Pennsylvania State University"
       },
       {
-        "author_name": "Catia Alvarez",
-        "author_inst": "University of Geneva - Faculty of Medicine 1 rue Michel-Servet     CH-1211 Geneva 4"
+        "author_name": "Cara Exten",
+        "author_inst": "The Pennsylvania State University"
       },
       {
-        "author_name": "Laurent Kaiser",
-        "author_inst": "University of Geneva Hospitals"
+        "author_name": "Christina Faust",
+        "author_inst": "The Pennsylvania State University"
       },
       {
-        "author_name": "Isabella Eckerle",
-        "author_inst": "University Hospitals of Geneva"
+        "author_name": "Matthew Ferrari",
+        "author_inst": "The Pennsylvania State University"
+      },
+      {
+        "author_name": "Anthony Robinson",
+        "author_inst": "The Pennsylvania State University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.04.27.21255706",
@@ -746296,85 +749887,117 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2021.04.26.21255732",
-    "rel_title": "Deprivation and Exposure to Public Activities during the COVID-19 Pandemic in England and Wales",
+    "rel_doi": "10.1101/2021.04.25.21256067",
+    "rel_title": "Trends of SARS-CoV-2 antibody prevalence in selected regions across Ghana",
     "rel_date": "2021-04-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.26.21255732",
-    "rel_abs": "BackgroundDifferential exposure to public activities and non-household contacts may contribute to stark deprivation-related inequalities in SARS-CoV-2 infection and outcomes, but has not been directly investigated. We set out to investigate whether participants in Virus Watch - a large community cohort study based in England and Wales - reported different levels of exposure to public activities and non-household contacts during the Autumn-Winter phase of the COVID-19 pandemic according to postcode-level socioeconomic deprivation.\n\nMethodsParticipants (n=20120-25228 across surveys) reported their daily activities during three weekly periods in late November 2020, late December 2020, and mid-February 2021. Deprivation was quantified based on participants postcode of residence using English or Welsh Indices of Multiple Deprivation quintiles. We used Poisson mixed effect models with robust standard errors to estimate the relationship between deprivation and risk of exposure to public activities during each survey period.\n\nResultsRelative to participants in the least deprived areas, participants in the most deprived areas persistently exhibited elevated risk of exposure to vehicle sharing (aRR range across time points 1.73-8.52), public transport (aRR 3.13-5.73), work or education outside of the household (aRR 1.09-1.21), essential shops (aRR 1.09-1.13) and non-household contacts (aRR 1.15-1.19) across multiple survey periods.\n\nConclusionDifferential exposure to essential public activities in deprived communities is likely to contribute to inequalities in infection risk and outcomes during the COVID-19 pandemic. Public health interventions to reduce exposure during essential activities and financial and practical support to enable low-paid workers to stay at home during periods of intense transmission may reduce COVID-related inequalities.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.25.21256067",
+    "rel_abs": "To estimate the level of community exposure to SARS-CoV-2 in Ghana, we conducted phased seroprevalence studies of 2729 participants in selected locations across Ghana. Phase I screening (August 2020) covered a total of 1305 individuals screened at major markets/lorry stations, major shopping malls, hospitals and research institutions involved in COVID-19 work. The screening was performed using a strip-in-cassette lateral flow type Rapid Diagnostic Test (RDT) kit that simultaneously and separately detected IgM and IgG antibodies against SARS-CoV-2 nucleocapsid protein. In Phase I, 252/1305 (19%) tested positive for IgM or IgG or both. Exposure rate was significantly higher among individuals tested at markets/lorry stations (26.9%) compared to those at Shopping Malls (9.4%). The 41-60-years age group had the highest exposure rate (27.2%). People with only a basic level or no formal education had a higher exposure rate (26.2%) than those with tertiary level education (13.1%); and higher in informally employed workers (24.0%) than those in the formal sector (15.0%). Phases II and III screening activities in October and December 2020, respectively, showed no evidence of increased seroprevalence, indicating either a reduced transmission rate or loss of antibody expression in a subset of the participants. The Upper East region has the lowest exposure rate, with only 4 of 200 participants (2%) seropositivity. Phase IV screening in February 2021 showed that exposure rates in the upper income earners (26.2%) had almost doubled since August 2020, reflective of Ghanas second wave of symptomatic COVID-19 cases, which began in December 2020. The Phase IV results suggest that seroprevalence levels have become so high that the initial socioeconomic stratification of exposure has been lost. Overall, the data indicates a much higher COVID-19 seroprevalence in the Greater Accra Region than was officially acknowledged, likely implying a considerably lower case fatality rate than the current national figure of 0.84%. Additionally, the high exposure levels seen in the communities suggest that COVID-19 in Ghana still predominantly presents with none-to-mild symptoms. Our results lay the foundation for more extensive SARS-CoV-2 surveillance in Ghana and the West African sub-region, including deploying rapid antigen test kits in concert to determine the actual infection burden since antibody development lags infection.",
+    "rel_num_authors": 25,
     "rel_authors": [
       {
-        "author_name": "Sarah Beale",
-        "author_inst": "University College London"
+        "author_name": "Peter Kojo Quashie",
+        "author_inst": "West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana"
       },
       {
-        "author_name": "Isobel Braithwaite",
-        "author_inst": "University College London"
+        "author_name": "Joe Kimanthi Mutungi",
+        "author_inst": "West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana"
       },
       {
-        "author_name": "Annalan MD Navaratnam",
-        "author_inst": "University College London"
+        "author_name": "Francis Dzabeng",
+        "author_inst": "West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana"
       },
       {
-        "author_name": "Pia Hardelid",
-        "author_inst": "University College London"
+        "author_name": "Daniel Oduro-Mensah",
+        "author_inst": "University of Ghana"
       },
       {
-        "author_name": "Alison Rodger",
-        "author_inst": "University College London; Royal Free London NHS Foundation Trust,"
+        "author_name": "Precious C Opurum",
+        "author_inst": "West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana"
       },
       {
-        "author_name": "Anna Aryee",
-        "author_inst": "University College London"
+        "author_name": "Kesego Tapela",
+        "author_inst": "University of Ghana"
       },
       {
-        "author_name": "Thomas Edward Byrne",
-        "author_inst": "University College London"
+        "author_name": "Aniefiouk John Udoakang",
+        "author_inst": "West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana"
       },
       {
-        "author_name": "Wing Lam Erica Fong",
-        "author_inst": "University College London"
+        "author_name": "- WACCBIP COVID-19 Team",
+        "author_inst": "-"
       },
       {
-        "author_name": "Ellen Fragaszy",
-        "author_inst": "University College London"
+        "author_name": "Ivy Asante",
+        "author_inst": "Department of Virology, Noguchi Memorial Institute for Medical Research, University of Ghana"
       },
       {
-        "author_name": "Cyril Geismar",
-        "author_inst": "University College London"
+        "author_name": "Lily Paemka",
+        "author_inst": "Department of Biochemistry, Cell and Molecular Biology, University of Ghana"
       },
       {
-        "author_name": "Jana Kovar",
-        "author_inst": "University College London"
+        "author_name": "Frederick Kumi-Ansah",
+        "author_inst": "Cape Coast Teaching Hospital"
       },
       {
-        "author_name": "Vincent Nguyen",
-        "author_inst": "University College London"
+        "author_name": "Osbourne Quaye",
+        "author_inst": "Department of Biochemistry, Cell and Molecular Biology, University of Ghana"
       },
       {
-        "author_name": "Parth Patel",
-        "author_inst": "University College London"
+        "author_name": "Emmanuella Amoako",
+        "author_inst": "Cape Coast Teaching Hospital"
       },
       {
-        "author_name": "Madhumita Shrotri",
-        "author_inst": "University College London"
+        "author_name": "Ralph Armah",
+        "author_inst": "Department of Internal Medicine, Surgery, Pediatrics and Emergency Medicine, Greater Accra Regional Hospital"
       },
       {
-        "author_name": "Robert W Aldridge",
-        "author_inst": "University College London"
+        "author_name": "Charlyne Kilba",
+        "author_inst": "Department of Internal Medicine, Surgery, Pediatrics and Emergency Medicine, Greater Accra Regional Hospital"
       },
       {
-        "author_name": "Andrew C Hayward",
-        "author_inst": "University College London"
+        "author_name": "Nana Afia Boateng",
+        "author_inst": "Department of Internal Medicine, Surgery, Pediatrics and Emergency Medicine, Greater Accra Regional Hospital"
       },
       {
-        "author_name": "- Virus Watch Collaborative",
-        "author_inst": ""
+        "author_name": "Michael F Ofori",
+        "author_inst": "Immunology Department, Noguchi Memorial Institute for Medical Research, University of Ghana"
+      },
+      {
+        "author_name": "George Boateng Kyei",
+        "author_inst": "University of Ghana Medical Centre"
+      },
+      {
+        "author_name": "Yaw Bediako",
+        "author_inst": "West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana"
+      },
+      {
+        "author_name": "Nicaise T Ndam",
+        "author_inst": "UMR 216 MERIT-IRD, Universit\u00e9 de Paris"
+      },
+      {
+        "author_name": "James Abugri",
+        "author_inst": "C.K. Tedam University of Technology and Applied Sciences"
+      },
+      {
+        "author_name": "Patrick Ansah",
+        "author_inst": "Navrongo Health Research Centre, Navrongo, Upper East Region, Ghana"
+      },
+      {
+        "author_name": "William Kwabena Ampofo",
+        "author_inst": "Department of Virology, Noguchi Memorial Institute for Medical Research, University of Ghana"
+      },
+      {
+        "author_name": "Francisca Mutapi",
+        "author_inst": "13.\tNIHR Global Health Research Unit Tackling Infections to Benefit Africa (TIBA), and Institute of Immunology and Infection Research, School of Biological Scie"
+      },
+      {
+        "author_name": "Gordon A Awandare",
+        "author_inst": "West African Centre for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -748162,67 +751785,79 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.04.19.21255709",
-    "rel_title": "Perceived public health threat a key factor for willingness to get the COVID-19 vaccine in Australia",
+    "rel_doi": "10.1101/2021.04.19.21255714",
+    "rel_title": "Antibody response after COVID-19 mRNA vaccination in relation to age, sex, and side effects",
     "rel_date": "2021-04-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255709",
-    "rel_abs": "BackgroundVaccination rollout against COVID-19 has begun across multiple countries worldwide. Although the vaccine is free, rollout might still be compromised by hesitancy or concerns about COVID-19 vaccines.\n\nMethodsWe conducted two online surveys of Australian adults in April (during national lockdown; convenience cross-sectional sample) and November (virtually no cases of COVID-19; nationally representative sample) 2020, prior to vaccine rollout. We asked about intentions to have a potential COVID-19 vaccine (If a COVID-19 vaccine becomes available, I will get it) and free-text responses (November only).\n\nResultsAfter adjustment for differences in sample demographics, the estimated proportion agreeing to a COVID-19 vaccine if it became available in April (n=1146) was 76.2%. In November (n=2034) this was estimated at 71.4% of the sample; additional analyses identified that the variation was driven by differences in perceived public health threat between April and November. Across both surveys, female gender, being younger, having inadequate health literacy and lower education were associated with reluctance to be vaccinated against COVID-19. Lower perceived susceptibility to COVID-19, belief that data on the efficacy of vaccines is  largely made up, having lower confidence in government, and lower perception of COVID-19 as a public health threat, were also associated with reluctance to be vaccinated against COVID-19. The top three reasons for agreeing to vaccinate (November only) were to protect myself and others, moral responsibility, and having no reason not to get it. For those who were indifferent or disagreeing to vaccinate, safety concerns were the top reason, followed by indecision and lack of trust in the vaccine respectively.\n\nCONCLUSIONSThese findings highlight some factors related to willingness to accept a COVID-19 vaccine prior to one being available in Australia. Now that the vaccine is being offered, this study identifies key issues that can inform public health messaging to address vaccine hesitancy.\n\nHIGHLIGHTSO_LIPerceived public health threat is associated with intentions to vaccinate\nC_LIO_LIThose believing the efficacy of vaccines is made up were less willing to get vaccinated\nC_LIO_LITo protect myself and others was the top reason for getting the vaccine\nC_LIO_LISafety concerns was the top reason against getting the vaccine\nC_LI",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255714",
+    "rel_abs": "BackgroundThe mRNA vaccines for SARS-CoV2 have proven highly effective and are currently used to vaccinate all age groups against COVID-19. Despite their high efficacy in clinical trials, there is limited data on the impact of age, sex, and side effects on vaccine-induced immune responses.\n\nMethodsWe here studied the development of SARS-CoV-2 Spike protein RBD domain antibodies after two doses of the Pfizer-BioNTech Comirnaty mRNA vaccine in 118 healthy volunteers and correlated their immune response with age, sex, and side effects reported after the vaccinations.\n\nFindingsOur findings show a robust immune response to the Spike proteins RBD region after the first and the second vaccination dose. However, we also saw a decline of antibody levels at 6 weeks versus 1 week after the second dose, suggesting a waning of the immune response over time. Regardless of this, the antibody levels at 6 weeks after the second dose remained significantly higher than before the vaccination, after the first dose, or in COVID-19 convalescent individuals. We found a decreased vaccination efficacy but fewer adverse events in older individuals, and that mRNA vaccination is less efficient in older males whereas the detrimental impact of age on vaccination outcome is abolished in females at 6 weeks after the second dose.\n\nInterpretationThe Pfizer-BioNTech Comirnaty mRNA vaccine induces a strong immune response after two doses of vaccination but older individuals develop fewer side effects and decreased antibody levels at 6 weeks. The waning of anti-viral antibodies in particular in older male individuals suggests that both age and male sex act as risk factors in the immune response to the SARS-CoV-2 mRNA vaccine.\n\nFundingThe study was supported by the Centre of Excellence in Translational Genomics (EXCEGEN), and the Estonian Research Council grant PRG377 and SYNLAB Estonia.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe first studies addressing the immune responses in older individuals after the single-dose administration of the SARS-CoV-2 mRNA vaccines have been published. We searched PubMed and medRxiv for publications on the immune response of SARS-CoV-2-mRNA vaccines, published in English, using the search terms \"SARS-CoV-2\", \"COVID-19\", \"vaccine response\", \"mRNA vaccine\", up to April 15th, 2021. To date, most mRNA vaccine response studies have not been peer-reviewed, and data on the role of age, sex and side effects on SARS-CoV-2-mRNA vaccines in real vaccination situations is limited. Some studies have found a weaker immune response in older individuals after the first dose and these have been measured at a relatively short period (within 1-2 weeks) after the first dose but little longer-term evidence exists on the postvaccination antibody persistence. Even less information is available on sex differences or correlations with mRNA vaccine side effects.\n\nAdded value of this studyIn this study, we assessed the antibody response up to 6 weeks after the second dose of Pfizer-BioNTech Comirnaty mRNA vaccine in 118 individuals. Our findings show a strong initial immune response after the first dose and an even higher Spike RBD antibody levels at 1 week after the second dose, but these significantly declined at 6 weeks after the second dose. We also found a weaker immune response and faster waning of antibodies in older vaccinated individuals, which correlated with fewer side effects at the time of vaccinations. Furthermore, although overall female and male vaccinees responded similarly, we found that age-related waning of the vaccine-related antibodies was stronger amongst older males whereas in females the impact of age was lost at 6 weeks after the second dose.\n\nImplications of all the available evidenceNew mRNA vaccines are now applied worldwide as they have shown high efficacy in clinical trials. Our results show that two doses of Pfizer-BioNTech Comirnaty mRNA vaccine induce a strong antibody response to Spike RBD region but these high levels decline 1.5 months after the second dose in most of the vaccinated individuals. Nevertheless, even at 6 weeks after the second dose, they stay significantly higher than at prevaccination, after the first dose of vaccine, or in Covid-19 postinfection. These findings also implicate that fewer adverse effects may indicate lower antibody response after the vaccination and point to the need for more individualized vaccination protocols, in particular among older people.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Rachael H Dodd",
-        "author_inst": "The University of Sydney"
+        "author_name": "Paul Naaber",
+        "author_inst": "SYNLAB Eesti; University of Tartu"
       },
       {
-        "author_name": "Kristen Pickles",
-        "author_inst": "The University of Sydney"
+        "author_name": "Liina Tserel",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Erin Cvejic",
-        "author_inst": "The University of Sydney"
+        "author_name": "Kadri Kangro",
+        "author_inst": "Icosagen Cell Factory"
       },
       {
-        "author_name": "Samuel Cornell",
-        "author_inst": "The University of Sydney"
+        "author_name": "Epp Sepp",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Jennifer MJ Isautier",
-        "author_inst": "The University of Sydney"
+        "author_name": "Virge Jurjenson",
+        "author_inst": "SYNLAB Eesti"
       },
       {
-        "author_name": "Tessa Copp",
-        "author_inst": "The University of Sydney"
+        "author_name": "Ainika Adamson",
+        "author_inst": "SYNLAB Eesti"
       },
       {
-        "author_name": "Brooke Nickel",
-        "author_inst": "The University of Sydney"
+        "author_name": "Liis Haljasmagi",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Carissa Bonner",
-        "author_inst": "The University of Sydney"
+        "author_name": "Pauliina Rumm",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Carys Batcup",
-        "author_inst": "The University of Sydney"
+        "author_name": "Regina Maruste",
+        "author_inst": "University ofTartu"
       },
       {
-        "author_name": "Danielle M Muscat",
-        "author_inst": "The University of Sydney"
+        "author_name": "Jaanika Karner",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Julie Ayre",
-        "author_inst": "The University of Sydney"
+        "author_name": "Joachim M Gerhold",
+        "author_inst": "Icosagen Cell Factory"
       },
       {
-        "author_name": "Kirsten J McCaffery",
-        "author_inst": "The University of Sydney"
+        "author_name": "Anu Planken",
+        "author_inst": "Icosagen Cell Factory"
+      },
+      {
+        "author_name": "Mart Ustav",
+        "author_inst": "Icosagen Cell Factory"
+      },
+      {
+        "author_name": "Kai Kisand",
+        "author_inst": "University of Tartu"
+      },
+      {
+        "author_name": "Part Peterson",
+        "author_inst": "University of Tartu"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.04.19.21255738",
@@ -749787,53 +753422,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.24.21256054",
-    "rel_title": "High proportion of post-acute sequelae of SARS-CoV-2 infection in individuals 1-6 months after illness and association with disease severity in an outpatient telemedicine population",
+    "rel_doi": "10.1101/2021.04.26.21256131",
+    "rel_title": "SARS-CoV-2 subgenomic RNA kinetics in longitudinal clinical samples",
     "rel_date": "2021-04-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.24.21256054",
-    "rel_abs": "BackgroundIndividuals with coronavirus disease 2019 (COVID-19) may have persistent symptoms following their acute illness. The prevalence and predictors of these symptoms, termed post-acute sequelae of SARS-CoV-2 (PASC), are not fully described.\n\nMethodsParticipants discharged from an outpatient telemedicine program for COVID-19 were emailed a survey (1-6 months after discharge) about ongoing symptoms, acute illness severity, and quality of life. Standardized telemedicine notes from acute illness were used for covariates (comorbidities and provider-assessed symptom severity). Bivariate and multivariable analyses were performed to assess predictors of persistent symptoms.\n\nResultsTwo hundred and ninety patients completed the survey, of whom 115 (39.7%) reported persistent symptoms including fatigue (n= 59, 20.3%), dyspnea on exertion (n=41, 14.1%), and mental fog (n=39, 13.5%) among others. Proportion of persistent symptoms did not differ based on duration since illness (<90 days: n=32, 37.2% versus >90 days: n=80, 40.4%, p = 0.61). Predictors of persistent symptoms included provider-assessed moderate-severe illness (aOR 3.24, 95% CI 1.75, 6.02), female sex (aOR 1.99 95% 0.98, 4.04; >90 days out: aOR 2.24 95% CI 1.01, 4.95), and middle age (aOR 2.08 95% CI 1.07, 4.03). Common symptoms associated with reports of worse physical health included weakness, fatigue, myalgias, and mental fog.\n\nConclusionsSymptoms following acute COVID-19 are common and may be predicted by factors during the acute phase of illness. Fatigue and neuropsychiatric symptoms figured prominently. Select symptoms seem to be particularly associated with perceptions of physical health following COVID-19 and warrant specific attention on future studies of PASC.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.26.21256131",
+    "rel_abs": "BackgroundGiven the persistence of viral RNA in clinically recovered COVID-19 patients, subgenomic RNAs (sgRNA) have been reported as potential molecular viability markers for SARS-CoV-2. However, few data are available on their longitudinal kinetics, compared with genomic RNA (gRNA), in clinical samples.\n\nMethodsWe analyzed 536 samples from 205 patients with COVID-19 from placebo-controlled, outpatient trials of Peginterferon Lambda-1a (Lambda; n=177) and favipiravir (n=359). Nasal swabs were collected at three time points in the Lambda (Day 1, 4 and 6) and favipiravir (Day 1, 5, and 10) trials. N-gene gRNA and sgRNA were quantified by RT-qPCR. To investigate the decay kinetics in vitro, we measured gRNA and sgRNA in A549ACE2+ cells infected with SARS-CoV-2, following treatment with remdesivir or DMSO control.\n\nResultsAt six days in the Lambda trial and ten days in the favipiravir trial, sgRNA remained detectable in 51.6% (32/62) and 49.5% (51/106) of the samples, respectively. Cycle threshold (Ct) values for gRNA and sgRNA were highly linearly correlated (Pearsons r=0.87) and the rate of increase did not differ significantly in Lambda (1.36 cycles/day vs 1.36 cycles/day; p = 0.97) or favipiravir (1.03 cycles/day vs 0.94 cycles/day; p=0.26) trials. From samples collected 15-21 days after symptom onset, sgRNA was detectable in 48.1% (40/83) of participants. In SARS-CoV-2 infected A549ACE2+ cells treated with remdesivir, the rate of Ct increase did not differ between gRNA and sgRNA.\n\nConclusionsIn clinical samples and in vitro, sgRNA was highly correlated with gRNA and did not demonstrate different decay patterns to support its application as a viability marker.\n\nSummaryWe observed prolonged detection of subgenomic RNA in nasal swabs and equivalent decay rates to genomic RNA in both longitudinal nasal swabs and in remdesivir-treated A549ACE2+ cells infected with SARS-CoV-2. Taken together, these findings suggest that subgenomic RNA from SARS-CoV-2 is comparably stable to genomic RNA and that its detection is therefore not a more reliable indicator of replicating virus.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "James B O'Keefe",
-        "author_inst": "Emory University School of Medicine"
+        "author_name": "Renu Verma",
+        "author_inst": "Stanford School of Medicine"
       },
       {
-        "author_name": "H. Caroline Minton",
-        "author_inst": "Rollins School of Public Health, Emory University"
+        "author_name": "Eugene Kim",
+        "author_inst": "Stanford School of Medicine"
       },
       {
-        "author_name": "Mary Morrow",
-        "author_inst": "Emory Healthcare"
+        "author_name": "Giovanny Joel Martinez-Colon",
+        "author_inst": "Stanford School of Medicine"
       },
       {
-        "author_name": "Colin Johnson",
-        "author_inst": "Emory Healthcare"
+        "author_name": "Prasanna Jagannathan",
+        "author_inst": "STANFORD SCHOOL OF MEDICINE"
       },
       {
-        "author_name": "Miranda A Moore",
-        "author_inst": "Emory University School of Medicine"
+        "author_name": "Arjun Rustagi",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Ghazala A. D. O'Keefe",
-        "author_inst": "Emory University School of Medicine"
+        "author_name": "Julie Parsonnet",
+        "author_inst": "Stanford School of Medicine"
       },
       {
-        "author_name": "Karima Benameur",
-        "author_inst": "Emory University School of Medicine"
+        "author_name": "Hector Bonilla",
+        "author_inst": "Stanford University School of Medicine"
       },
       {
-        "author_name": "Jason Higdon",
-        "author_inst": "Emory University School of Medicine"
+        "author_name": "Chaitan Khosla",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Jessica K. Fairley",
-        "author_inst": "Emory University School of Medicine"
+        "author_name": "Marisa Holubar",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Aruna Subramanian",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Upinder Singh",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Yvonne Maldonado",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Catherine A Blish",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Jason R Andrews",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -751577,61 +755232,17 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.23.21255995",
-    "rel_title": "Regional opening strategies with commuter testing and containment of new SARS-CoV-2 variants",
+    "rel_doi": "10.1101/2021.04.22.21255941",
+    "rel_title": "Predicting the end of Covid-19 infection for various countries using a stochastic agent-based model taking into account vaccination rates and the new mutant",
     "rel_date": "2021-04-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.23.21255995",
-    "rel_abs": "BackgroundDespite the vaccination process in Germany, a large share of the population is still susceptible to SARS-CoV-2. In addition, we face the spread of novel variants. Until we overcome the pandemic, reasonable mitigation and opening strategies are crucial to balance public health and economic interests.\n\nMethodsWe model the spread of SARS-CoV-2 over the German counties by a graph-SIR-type, metapopulation model with particular focus on commuter testing. We account for political interventions by varying contact reduction values in private and public locations such as homes, schools, workplaces, and other. We consider different levels of lockdown strictness, commuter testing strategies, or the delay of intervention implementation. We conduct numerical simulations to assess the effectiveness of the different intervention strategies after one month. The virus dynamics in the regions (German counties) are initialized randomly with incidences between 75-150 weekly new cases per 100,000 inhabitants (red zones) or below (green zones) and consider 25 different initial scenarios of randomly distributed red zones (between 2 and 20 % of all counties). To account for uncertainty, we consider an ensemble set of 500 Monte Carlo runs for each scenario.\n\nResultsWe find that the strength of the lockdown in regions with out of control virus dynamics is most important to avoid the spread into neighboring regions. With very strict lockdowns in red zones, commuter testing rates of twice a week can substantially contribute to the safety of adjacent regions. In contrast, the negative effect of less strict interventions can be overcome by high commuter testing rates. A further key contributor is the potential delay of the intervention implementation. In order to keep the spread of the virus under control, strict regional lockdowns with minimum delay and commuter testing of at least twice a week are advisable. If less strict interventions are in favor, substantially increased testing rates are needed to avoid overall higher infection dynamics.\n\nConclusionsOur results indicate that local containment of outbreaks and maintenance of low overall incidence is possible even in densely populated and highly connected regions such as Germany or Western Europe. While we demonstrate this on data from Germany, similar patterns of mobility likely exist in many countries and our results are, hence, generalizable to a certain extent.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255941",
+    "rel_abs": "Using a stochastic, agent-based model, the course of infection since the first occurrence of a Covid-19 infection is simulated for various countries, taking into account the new, more infectious mutant and the vaccinations. The simulation shows that the course of infection for the United Kingdom (UK) and Israel is surprisingly good. For the other countries, an end date for the infection can be predicted based on the course of the simulation. For Germany, the course is calculated in a second scenario, assuming a higher vaccination rate.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Martin J Kuehn",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Daniel Abele",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Sebastian Binder",
-        "author_inst": "Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, Germany"
-      },
-      {
-        "author_name": "Kathrin Rack",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Margrit Klitz",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Jan Kleinert",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Jonas Gilg",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Luca Spataro",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Wadim Koslow",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Martin Siggel",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
-      },
-      {
-        "author_name": "Michael Meyer-Hermann",
-        "author_inst": "Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, Germany."
-      },
-      {
-        "author_name": "Achim Basermann",
-        "author_inst": "German Aerospace Center, Institute for Software Technology"
+        "author_name": "Manfred Karl Robert Eissler",
+        "author_inst": "Praxis Dres Eissler"
       }
     ],
     "version": "1",
@@ -753219,25 +756830,69 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.21.21255874",
-    "rel_title": "Evaluation of the sensitivity, accuracy and currency of the Cochrane COVID-19 Study Register for supporting rapid evidence synthesis production",
+    "rel_doi": "10.1101/2021.04.22.21255631",
+    "rel_title": "Risk Profile of Thanksgiving Gatherers and Subsequent SARS-CoV2 Testing and Diagnosis",
     "rel_date": "2021-04-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.21.21255874",
-    "rel_abs": "IntroductionThe Cochrane COVID-19 Study Register (CCSR) is a public, continually updated, curated database of COVID-19 study references. The aim of this study-based register is to support rapid and living evidence synthesis, including a project to build an evidence ecosystem of COVID-19 research (CEOsys). In November and December 2020 we conducted an evaluation of the CCSR for CEOsys, measured its performance and identified areas for improvement.\n\nMethodsFor the evaluation we generated a purposive sample of 286 studies from 20 reviews to calculate the CCSRs sensitivity (comprehensiveness), accuracy (correctly classified and linked studies) and currency (time to publish and process references).\n\nResultsThe CCSR had an overall sensitivity of 77.2%, with the highest sensitivity for interventional studies (94.4%) and lowest sensitivity for modelling studies (63.6%). The study register had 100% sensitivity for trial registry records, 86.5% for journal articles and 52.4% for preprints. 98.3% of references were correctly classified with regard to study type, and 93.4% with regard to study aim. 89% of studies were correctly linked. 81.4% of references were published to the register in under 30 days, with 0.5 day (median) for trial registry records, 2 days for journal articles and 56 days for preprints.\n\nConclusionThe CCSR had high sensitivity, accurate study classifications and short publishing times for journal articles and trial registry records. We identified that the CCSRs coverage and publishing times for preprints needed improvement. Finally, the evaluation illustrated the value of a study-based register for identifying additional study references for analysis in evidence synthesis.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255631",
+    "rel_abs": "BackgroundDuring Fall 2020 in the United States (U.S.), despite high COVID-19 case numbers and recommendations from public health officials not to travel and gather with individuals outside ones household, millions of people gathered for Thanksgiving. The objective of this study was to understand if individuals behaviors and risk perceptions influenced their decision to gather, and if they did gather, their subsequent test seeking and diagnoses.\n\nMethodsParticipants were part of the CHASING COVID Cohort study - a U.S. national prospective cohort. The study sample consisted of participants who completed routine questionnaires before and after Thanksgiving. Non-pharmaceutical interventions (NPIs) use informed behavioral risk scores and a score of perceived risk of COVID-19 were assigned to each participant. Multinomial logistic regression models were used to assess the association between higher risk behaviors and gathering with other households, and the association of gathering with subsequent testing and test positivity.\n\nResultsA total of 1,932 (40.5%) cohort participants spent Thanksgiving with individuals from at least one other household. Participants with higher behavioral risk scores had greater odds of gathering with one other household (aOR: 2.35, 95% CI: 2.0, 2.7), two other households (aOR: 4.54, 95% CI: 3.7, 5.6), and three or more other households (aOR: 5.44, 95% CI: 4.1, 7.2). Participants perceiving COVID-19 as a low-risk to themselves and others had greater odds of gathering with one other household (aOR: 1.12, 95% CI: 0.97, 1.3), two other households (aOR: 1.39, 95% CI: 1.1, 1.7), and three or more other households (aOR: 1.86, 95% CI: 1.4, 2.4). Those who spent Thanksgiving with one or more other households had 1.23 times greater odds (95% CI: 1.1, 1.4) of having a COVID-19 test afterward. There was no association between gathering for Thanksgiving and subsequent COVID-19 test positivity or developing COVID-19 symptoms.\n\nConclusionsThose who gathered with other households for Thanksgiving tended to engage in higher-risk activities. Thanksgiving gathering with other households was not associated with subsequently testing positive for COVID-19, but only a small proportion obtained post-travel testing. Public health messaging should emphasize behavior change strategies that promote safer gathering.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Maria-Inti Metzendorf",
-        "author_inst": "Cochrane Metabolic and Endocrine Disorders Group, Institute of General Practice, Medical Faculty of the Heinrich-Heine-University Duesseldorf"
+        "author_name": "William You",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Madhura S. Rane",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
       },
       {
-        "author_name": "Robin M Featherstone",
-        "author_inst": "Cochrane, Editorial and Methods Department, London, United Kingdom"
+        "author_name": "Rebecca Zimba",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA"
+      },
+      {
+        "author_name": "Amanda Berry",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Sarah G Kulkarni",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Drew A Westmoreland",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Angela Parcesepe",
+        "author_inst": "Department of Maternal and Child Health, Gillings School of Public Health, University of North Carolina"
+      },
+      {
+        "author_name": "Mindy Chang",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Andrew R Maroko",
+        "author_inst": "CUNY Graduate School of Public Health and Health Policy"
+      },
+      {
+        "author_name": "Shivani Kochhar",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Chloe Mirzayi",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Christian Grov",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY)"
+      },
+      {
+        "author_name": "Denis Nash",
+        "author_inst": "Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY);"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -754705,21 +758360,25 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.04.22.21255952",
-    "rel_title": "COVID-19 pandemic: Analyzing of different pandemic control strategies using saturation models",
+    "rel_doi": "10.1101/2021.04.22.21255953",
+    "rel_title": "COVID-19 pandemic: Analyzing of spreading behavior, the impact of restrictions and prevention measures in Germany and Japan.",
     "rel_date": "2021-04-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255952",
-    "rel_abs": "Since December 2019, the world is confronted with the outbreak of the respiratory disease COVID-19. At the beginning of 2020, the COVID-19 epidemic evolved into a pandemic, which continues to this day. Within many countries, several control strategies or combinations of them, like restrictions (e.g. lockdown actions), medical care (e.g. development of vaccine or medicaments) and medical prevention (e.g. hygiene concept), were established with the goal to control the pandemic. Depending on the chosen control strategy, the COVID-19 spreading behavior slowed down or approximately stopped for a defined time range. This phenomenon is called saturation effect and can be described by saturation models: E.g. a fundamental approach is Verhulst (1838). The model parameter allows the interpretation of the spreading speed (growth) and the saturation effect in a sound way. This paper shows results of a research study of the COVID-19 spreading behavior and saturation effects depending on different pandemic control strategies in different countries and time phases based on Johns Hopkins University data base (2020). The study contains the analyzing of saturation effects related to short time periods, e.g. possible caused by lockdown strategies, geographical influences and medical prevention activities. The research study is focusing on reference countries like Germany, Japan, Denmark, Iceland, Ireland and Israel.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255953",
+    "rel_abs": "In December 2019, the world was confronted with the outbreak of the respiratory disease COVID-19. The COVID-19 epidemic evolved at the beginning of 2020 into a pandemic, which continues to this day. The incredible speed of the spread and the consequences of the infection had a worldwide impact on societies and health systems. Governments enforced many measures to control the COVID-19 pandemic: Restrictions (e.g. lockdown), medical care (e.g. intensive care) and medical prevention (e.g. hygiene concept). This leads to a different spreading behavior of the COVID-19 pandemic, depending on measures. Furthermore, the spreading behavior is influenced by culture and geographical impacts. The spreading behavior of COVID-19 related to short time intervals can be described by Weibull distribution models, common in reliability engineering, in a sound way. The interpretation of the model parameters allows the assessment of the COVID-19 spreading characteristics. This paper shows results of a research study of the COVID-19 spreading behavior depending on different pandemic time phases within Germany and Japan. Both countries are industrial nations, but have many differences with respect to historical development, culture and geographical conditions. Consequently, the chosen government measures have different impacts on the control of the COVID-19 pandemic. The research study contains the analyses of different pandemic time intervals in Germany and Japan: The breakout phase in spring 2020 and subsequently following waves until winter season 2020/2021.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
         "author_name": "Stefan Bracke",
         "author_inst": "University of Wuppertal, Germany"
       },
       {
-        "author_name": "Lars Grams",
-        "author_inst": "University of Wuppertal, Germany"
+        "author_name": "Alicia Puls",
+        "author_inst": "University of Wuppertal"
+      },
+      {
+        "author_name": "Masato Inoue",
+        "author_inst": "Meiji University, Japan"
       }
     ],
     "version": "1",
@@ -756651,117 +760310,65 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.19.21255727",
-    "rel_title": "Prolonged activation of nasal immune cell populations and development of tissue-resident SARS-CoV-2 specific CD8 T cell responses following COVID-19",
+    "rel_doi": "10.1101/2021.04.19.21255723",
+    "rel_title": "B and T cell immune responses elicited by the BNT162b2 (Pfizer BioNTech) COVID-19 vaccine in nursing home residents",
     "rel_date": "2021-04-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255727",
-    "rel_abs": "The immune system plays a major role in Coronavirus Disease 2019 (COVID-19) pathogenesis, viral clearance and protection against re-infection. Immune cell dynamics during COVID-19 have been extensively documented in peripheral blood, but remain elusive in the respiratory tract. We performed minimally-invasive nasal curettage and mass cytometry to characterize nasal immune cells of COVID-19 patients during and 5-6 weeks after hospitalization. Contrary to observations in blood, no general T cell depletion at the nasal mucosa could be detected. Instead, we observed increased numbers of nasal granulocytes, monocytes, CD11c+ NK cells and exhausted CD4+ T effector memory cells during acute COVID-19 compared to age-matched healthy controls. These pro-inflammatory responses were found associated with viral load, while neutrophils also negatively correlated with oxygen saturation levels. Cell numbers mostly normalized following convalescence, except for persisting CD127+ granulocytes and activated T cells, including CD38+ CD8+ tissue-resident memory T cells. Moreover, we identified SARS-CoV-2 specific CD8+ T cells in the nasal mucosa in convalescent patients. Thus, COVID-19 has both transient and long-term effects on the immune system in the upper airway.",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21255723",
+    "rel_abs": "ObjectivesThe immunogenicity of the BNT162b2 COVID-19 vaccine is understudied in elderly people with comorbidities. We assessed SARS-CoV-2-S-targeted antibody and T cell responses following full vaccination in nursing home residents (NHR).\n\nMethodsWe recruited 60 NHR (44 female; median age, 87.5 years), of whom 10 had previously had COVID-19, and 18 healthy controls (15 female; median age, 48.5 years). Pre- and post-vaccination blood specimens were available for quantitation of total antibodies binding RBD and enumeration of SARS-CoV-2-S-reactive IFN-{gamma} CD4+ and CD8+ T cells by flow cytometry.\n\nResultsThe seroconversion rate in presumably SARS-CoV-2 naive NHR (95.3%), either with or without comorbidities, was similar to controls (94.4%). A robust booster effect was documented in NHR with prior COVID-19. Plasma antibody levels were higher in convalescent NHR than in individuals across the other two groups. A large percentage of NHR had SARS-CoV-2 S-reactive IFN-{gamma} CD8+ and/or CD4+ T cells at baseline, in contrast to healthy controls. Either CD8+ and/or CD4+ T-cell responses were documented in all control subjects after vaccination. Contrariwise, the percentage of NHR exhibiting detectable SARS-CoV-2 IFN-{gamma} CD8+ or CD4+ T-cell responses (or both), irrespective of their baseline SARS-CoV-2 infection status, dropped consistently after vaccination. Overall, SARS-CoV-2 IFN-{gamma} CD8+ and CD4+ T-cell responses in NHR decreased in post-vaccination specimens.\n\nConclusionThe BNT162b2 COVID-19 vaccine elicits robust SARS-CoV-2-S antibody responses in NHR. Nevertheless, the frequency and magnitude of detectable SARS-CoV-2 IFN-{gamma} T-cell responses after vaccination was lower in NHR compared to controls.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Anna H.E. Roukens",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Marion Konig",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Tim Dalebout",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Tamar Tak",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Shohreh Azimi",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Yvonne Kruize",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Cilia R. Pothast",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Renate S. Hagedoorn",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Sesmu M. Arbous",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Jaimie L.H. Zhang",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Maaike Verheij",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Corine Prins",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Anne M. Does van der",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Pieter S. Hiemstra",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Ignacio Torres",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "Jutte J.C. Vries de",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Eliseo Albert",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "Jacqueline J. Janse",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Estela Gimenez",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "Meta Roestenberg",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Maria Jesus Alcaraz",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "Sebenzile K. Myeni",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Pilar Botija",
+        "author_inst": "Direccion de Atencion Primaria, Departamento de Salud Clinico-Malvarrosa, Hospital Clinico Universitario de Valencia, Valencia, Spain."
       },
       {
-        "author_name": "Marjolein Kikkert",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Paula Amat",
+        "author_inst": "Hematology Service Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "Mirjam H.M. Heemskerk",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Maria Jose Remigia",
+        "author_inst": "Hematology Service Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "Maria Yazdanbakhsh",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Maria Jose Beltran",
+        "author_inst": "Direccion de Enfermeria, Departamento de Salud Clinico-Malvarrosa, Hospital Clinico Universitario de Valencia, Valencia, Spain."
       },
       {
-        "author_name": "Hermelijn H. Smits",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Celia Rodado",
+        "author_inst": "Comision Departamental de control de Residencias. Departamento de Salud Valencia Clinico Malvarrosa."
       },
       {
-        "author_name": "Simon P. Jochems",
-        "author_inst": "Leiden University Medical Center"
+        "author_name": "Dixie Huntley",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "- BEAT-COVID group",
-        "author_inst": ""
+        "author_name": "Beatriz Olea",
+        "author_inst": "Microbiology Service, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       },
       {
-        "author_name": "- COVID-19 LUMC group",
-        "author_inst": ""
+        "author_name": "David Navarro",
+        "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain."
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -758636,35 +762243,59 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.20.21255350",
-    "rel_title": "When can we safely return to normal? A novel method for identifying safe levels of NPIs in the context of COVID-19 vaccinations",
+    "rel_doi": "10.1101/2021.04.21.440801",
+    "rel_title": "Comparative Analysis of Emerging B.1.1.7+E484K SARS-CoV-2 isolates from Pennsylvania",
     "rel_date": "2021-04-21",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.20.21255350",
-    "rel_abs": "Over the course of the COVID-19 pandemic, governing bodies and individuals have relied on a variety of non-pharmaceutical interventions (NPIs) to control the transmission of SARS-CoV-2, which posed an acute threat to individuals well-being and consistently impacted economic activities in many countries worldwide. NPIs have been implemented at varying levels of severity and in response to widely-divergent perspectives of risk tolerance. Now, concurrently with the introduction of multiple SARS-CoV-2 vaccines, the world looks optimistically to a \"return to normality\". In this work, we propose a multi-disciplinary approach, combining transmission modeling with control and optimization theory, to examine how risk tolerance and vaccination rates will impact the safe return to normal behavior over the next few months. To this end, we consider a version of the Susceptible-Exposed-Infected-Recovered transmission model that accounts for hospitalizations, vaccinations, and loss of immunity. We then propose a novel control approach to calibrate the necessary level of NPIs at various geographical levels to guarantee that the number of hospitalizations does not exceed a given risk tolerance (i.e., a maximum allowable threshold). Our model and control objectives are calibrated and tailored for the state of Colorado, USA. Our results suggest that: (i) increasing risk tolerance can decrease the number of days required to discontinue all NPIs; (ii) increasing risk tolerance inherently increases COVID-19 deaths even in the context of vaccination; (iii) if the vaccination uptake in the population is 70% or less, then return to normal behavior within the next year may newly stress the healthcare system. Furthermore, by using a multi-region model accounting for travel, our simulations predict that: (iv) relaxation should take into account regional heterogeneity in transmission and travel; and (v) premature relaxation of NPIs, even if restricted only to low-density regions, will lead to exceeding hospitalization limits even when highly-populated regions implement full-closures. Although the simulations are performed for the state of Colorado, the proposed model of transmission and control methods are applicable to any area worldwide and can be utilized at any geographical granularity.",
-    "rel_num_authors": 4,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.21.440801",
+    "rel_abs": "Rapid whole genome sequencing of SARS-CoV-2 has presented the ability to detect new emerging variants of concern in near real time. Here we report the genome of a virus isolated in Pennsylvania in March 2021 that was identified as lineage B.1.1.7 (VOC-202012/01) that also harbors the E484K spike mutation, which has been shown to promote \"escape\" from neutralizing antibodies in vitro. We compare this sequence to the only 5 other B.1.1.7+E484K genomes from Pennsylvania, all of which were isolated in mid March. Beginning in February 2021, only a small number (n=60) of isolates with this profile have been detected in the US, and only a total of 253 have been reported globally (first in the UK in December 2020). Comparative genomics of all currently available high coverage B.1.1.7+E484K genomes (n=235) available on GISAID suggested the existence of 7 distinct groups or clonal complexes (CC; as defined by GNUVID) bearing the E484K mutation raising the possibility of 7 independent acquisitions of the E484K spike mutation in each background. Phylogenetic analysis suggested the presence of at least 3 distinct clades of B.1.1.7+E484K circulating in the US, with the Pennsylvanian isolates belonging to two distinct clades. Increased genomic surveillance will be crucial for detection of emerging variants of concern that can escape natural and vaccine induced immunity.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Gianluca Bianchin",
-        "author_inst": "University of Colorado Boulder"
+        "author_name": "Azad Ahmed",
+        "author_inst": "Drexel University College of Medicine"
       },
       {
-        "author_name": "Emiliano Dall'Anese",
-        "author_inst": "University of Colorado Boulder"
+        "author_name": "John Everett",
+        "author_inst": "Perelman School of Medicine, University of Pennsylvania, Philadelphia"
       },
       {
-        "author_name": "Jorge Ivan Poveda",
-        "author_inst": "University of Colorado Boulder"
+        "author_name": "Shantan Reddy",
+        "author_inst": "Perelman School of Medicine, University of Pennsylvania, Philadelphia"
+      },
+      {
+        "author_name": "Emilie Rabut",
+        "author_inst": "Hospital of the University of Pennsylvania"
+      },
+      {
+        "author_name": "Jasmine Deseignora",
+        "author_inst": "Hospital of the University of Pennsylvania"
+      },
+      {
+        "author_name": "Michael D. Feldman",
+        "author_inst": "Perelman School of Medicine, University of Pennsylvania"
+      },
+      {
+        "author_name": "Kyle G. Rodino",
+        "author_inst": "Perelman School of Medicine, University of Pennsylvania"
       },
       {
-        "author_name": "Andrea Buchwald",
-        "author_inst": "University of Colorado Anschutz"
+        "author_name": "Frederic Bushman",
+        "author_inst": "Perelman School of Medicine, University of Pennsylvania, Philadelphia"
+      },
+      {
+        "author_name": "Rebecca M. Harris",
+        "author_inst": "Perelman School of Medicine, University of Pennsylvania"
+      },
+      {
+        "author_name": "Josh Chang Mell",
+        "author_inst": "Drexel University College of Medicine"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "type": "new results",
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2021.04.21.21255676",
@@ -760362,33 +763993,45 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.04.14.21255448",
-    "rel_title": "Gender Differences in Health Protective Behaviors During the COVID-19 Pandemic in Taiwan: An Empirical Study",
+    "rel_doi": "10.1101/2021.04.14.21255490",
+    "rel_title": "Expectant parents' perceptions of healthcare and support during COVID-19 in the UK: A thematic analysis.",
     "rel_date": "2021-04-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.14.21255448",
-    "rel_abs": "IntroductionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection produces more severe symptoms and a higher mortality in men than in women. The role of biological sex in the immune response to SARS-CoV-2 is believed to explain this sex disparity. However, the contribution of gender factors that influence health protective behaviors and therefore health outcomes, remains poorly explored.\n\nMethodsWe assessed the contributions of gender in attitudes towards the COVID-19 pandemic, using a hypothetical influenza pandemic data from the 2014 Taiwan Social Change Survey. Participants were selected through a stratified, three-stage probability proportional-to-size sampling from across the nation, to fill in questionnaires that asked about their perception of the hypothetical pandemic, and intention to adopt health protective behaviors.\n\nResultsA total of 1,990 participants (median age 45.92 years, 49% women) were included. Significant gender disparities (p<0.001) were observed. The risk perception of pandemic (OR=1.28, 95% CI=1.21-1.35, p<0.001), older age (1.06, 95%=1.05-1.07, p<0.001), female gender (OR = 1.18, 95% CI = 1.09{square}1.27, p<0.001), higher education (OR=1.10, 95% CI=1.06-1.13, p<0.001), and larger family size (OR=1.09, 95% CI=1.06-1.15, p<0.001) were positively associated with health protective behaviors. The risk perception of pandemic (OR=1.25, 95% CI=1.15-1.36), higher education (OR=1.07, 95% CI=1.02-1.13, p<0.05), being married (OR=1.17, 95% CI=1.01-1.36, p<0.05), and larger family size (OR=1.33, 95% CI=1.25-1.42, p<0.001), were positively associated with intention to receive a vaccine. However, female gender was negatively associated with intention to receive a vaccine (OR=0.85, 95% CI=0.75-0.90, p<0.01) and to comply with contact-tracing (OR=0.95, 95% CI=0.90-1.00, p<0.05) compared to men. Living with children was also negatively associated with intention to receive vaccines (OR=0.77, 95% CI=0.66-0.90, p<0.001).\n\nConclusionThis study unveils gender differences in risk perception, health protective behaviors, vaccine hesitancy, and compliance with contact-tracing using a hypothetical viral pandemic. Gender-specific health education raising awareness of health protective behaviors may be beneficial to prevent future pandemics.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.14.21255490",
+    "rel_abs": "BackgroundIn response to the COVID-19 pandemic, expectant parents experienced changes in the availability and uptake of both NHS community and hospital-based healthcare.\n\nObjectiveTo examine how COVID-19 and its societal related restrictions have impacted the provision of healthcare support for pregnant women during the COVID-19 pandemic.\n\nMethodA thematic analysis using an inductive approach was undertaken of data from open-ended responses using data from the national COVID in Context of Pregnancy, Infancy and Parenting (CoCoPIP) Study online survey (N = 507 families).\n\nResultsThe overarching theme identified was the way in which the changes to healthcare provision increased parents anxiety levels, and feelings of not being supported. Five sub-themes, associated with the first wave of the pandemic, were identified: (1) rushed and/or fewer antenatal appointments, (2) lack of sympathy from healthcare workers, (3) lack of face-to-face appointments, (4) requirement to attend appointments without a partner, and (5) requirement to use PPE. A sentiment analysis, that used quantitative techniques, revealed participant responses to be predominantly negative (50.1%), with a smaller proportion of positive (21.8%) and neutral (28.1%) responses found.\n\nConclusionThis study provides evidence indicating that the changes to healthcare services for pregnant women during the pandemic increased feelings of anxiety and have left women feeling inadequately supported. Our findings highlight the need for compensatory social and emotional support for new and expectant parents while COVID-19 related restrictions continue to impact on family life and society.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Jasmine Tan",
-        "author_inst": "School of Medicine, National Taiwan University, Taipei, Taiwan"
+        "author_name": "Ezra Aydin",
+        "author_inst": "University of Cambridge"
       },
       {
-        "author_name": "Yilin Yoshida",
-        "author_inst": "Tulane Center of Excellence in Sex-Based Biology & Medicine, New Orleans, LA, USA"
+        "author_name": "Kevin A Glasgow",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Staci Weiss",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Topun Austin",
+        "author_inst": "University of Cambridge"
       },
       {
-        "author_name": "Kevin Sheng-Kai Ma",
-        "author_inst": "Department of Life Science, National Taiwan University, Taipei, Taiwan"
+        "author_name": "Mark Johnson",
+        "author_inst": "University of Cambridge"
       },
       {
-        "author_name": "Franck Mauvais-Jarvis",
-        "author_inst": "Tulane Center of Excellence in Sex-Based Biology & Medicine, New Orleans, LA, USA"
+        "author_name": "Jane Barlow",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Sarah Lloyd-Fox",
+        "author_inst": "University of Cambridge"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -762084,45 +765727,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.14.21255512",
-    "rel_title": "Assessing the Mortality Impact of the COVID-19 Pandemic in Florida State Prisons",
+    "rel_doi": "10.1101/2021.04.14.21255476",
+    "rel_title": "Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020",
     "rel_date": "2021-04-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.14.21255512",
-    "rel_abs": "BackgroundThe increased risk of COVID-19 infection among incarcerated individuals due to environmental hazards is well known and recent studies have highlighted the higher rates of infection and mortality prisoners in the United States face due to COVID-19. However, the impact of COVID-19 on all-cause mortality rates in incarcerated populations has not been studied.\n\nMethodsUsing data reported by the Florida Department of Corrections on prison populations and mortality events we conducted a retrospective cohort study of all individuals incarcerated in Florida state prisons between 2015 and 2020. We calculated excess deaths by estimating age-specific expected deaths from mortality trends in 2015 through 2019 and taking the difference between observed and expected deaths during the pandemic period. We calculated life table measures using standard demographic techniques and assessed significant yearly changes using bootstrapping.\n\nFindingsThe Florida Department of Corrections reported 510 total deaths from March 1, 2020 to December 31, 2020 among the state prison population. This was 42% higher (rate ratio 1.42, 95% CI 1.15 to 1.89) than the expected number of deaths in light of mortality rates for previous years. Reported COVID-19 deaths in a month were positively correlated with estimated excess deaths (80.4%, p <.01). Using age-specific mortality estimates, we found that life expectancy at age 20 declined by 4 years (95% CI 2.06-6.57) between 2019 and 2020 for the Florida prison population.\n\nInterpretationThe Florida prison population saw a significant increase in all-cause mortality during the COVID-19 pandemic period, leading to a decrease in life expectancy of more than four years. Life years lost by the Florida prison population were likely far greater than those lost by the general United States population, as reported by other studies. This difference in years lost highlights the need for increased interventions to protect vulnerable incarcerated populations during pandemics.\n\nFundingVital Projects Fund, Arnold Ventures, US Centers for Disease Control, Eunice Kennedy Shriver National Institute of Child Health and Human Development",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.14.21255476",
+    "rel_abs": "BackgroundAvailability of SARS-CoV-2 testing in the United States (U.S.) has fluctuated through the course of the COVID-19 pandemic, including in the U.S. state of Illinois. Despite substantial ramp-up in test volume, access to SARS-CoV-2 testing remains limited, heterogeneous, and insufficient to control spread.\n\nMethodsWe compared SARS-CoV-2 testing rates across geographic regions, over time, and by demographic characteristics (i.e., age and racial/ethnic groups) in Illinois during March through December 2020. We compared age-matched case fatality ratios and infection fatality ratios through time to estimate the fraction of SARS-CoV-2 infections that have been detected through diagnostic testing.\n\nResultsBy the end of 2020, initial geographic differences in testing rates had closed substantially. Case fatality ratios were higher in non-Hispanic Black and Hispanic/Latino populations in Illinois relative to non-Hispanic White populations, suggesting that tests were insufficient to accurately capture the true burden of COVID-19 disease in the minority populations during the initial epidemic wave. While testing disparities decreased during 2020, Hispanic/Latino populations consistently remained the least tested at 1.87 tests per 1000 population per day compared with 2.58 and 2.87 for non-Hispanic Black and non-Hispanic White populations, respectively, at the end of 2020. Despite a large expansion in testing since the beginning of the first wave of the epidemic, we estimated that over half (50-80%) of all SARS-CoV-2 infections were not detected by diagnostic testing and continued to evade surveillance.\n\nConclusionsSystematic methods for identifying relatively under-tested geographic regions and demographic groups may enable policymakers to regularly monitor and evaluate the shifting landscape of diagnostic testing, allowing officials to prioritize allocation of testing resources to reduce disparities in COVID-19 burden and eventually reduce SARS-CoV-2 transmission.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Neal Marquez",
-        "author_inst": "University of Washington"
+        "author_name": "Tobias M Holden",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Aaron Littman",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Reese AK Richardson",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Victoria Rossi",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Philip Arevalo",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Michael Everett",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Wayne A Duffus",
+        "author_inst": "CDC/IDPH"
       },
       {
-        "author_name": "Erika Tyagi",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Manuela Runge",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Hope Johnson",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Elena Whitney",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Sharon Dolovich",
-        "author_inst": "University of California Los Angeles"
+        "author_name": "Leslie Wise",
+        "author_inst": "Illinois Dept of Public Health"
+      },
+      {
+        "author_name": "Ngozi O Ezike",
+        "author_inst": "Illinois Dept of Public Health"
+      },
+      {
+        "author_name": "Sarah Patrick",
+        "author_inst": "Illinois Dept of Public Health"
+      },
+      {
+        "author_name": "Sarah Cobey",
+        "author_inst": "University of Chicago"
+      },
+      {
+        "author_name": "Jaline Gerardin",
+        "author_inst": "Northwestern University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -764398,69 +768057,69 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.13.21255396",
-    "rel_title": "Ultra-fast, high throughput and inexpensive detection of SARS-CoV-2 seroconversion",
+    "rel_doi": "10.1101/2021.04.12.21255330",
+    "rel_title": "Identification of natural SARS-CoV-2 infection in seroprevalence studies among vaccinated populations",
     "rel_date": "2021-04-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255396",
-    "rel_abs": "A technique allowing high throughput, fast and low-cost quantitative analysis of human IgG antibodies reacting to SARS-CoV-2 antigens will be required to understand the levels of protecting antibodies in the population raised in response to infections and/or to immunization. We described previously a fast, simple, and inexpensive Ni2+ magnetic bead immunoassay which allowed detection of human antibodies reacting against the SARS-CoV-2 nucleocapsid protein using a minimal amount of serum or blood. A major drawback of the previously described system was that it only processed 12 samples simultaneously. Here we describe a manually operating inexpensive 96 well plate magnetic extraction / homogenization process which allows high throughput analysis delivering results of 96 samples in chromogenic format in 12 minutes or in fluorescent ultrafast format which takes only 7 minutes. We also show that His tag antigen purification can be performed on the fly while loading antigens to the Ni2+ magnetic beads in a process which takes only 12 min reducing the pre analytical time and cost. Finally, we show that the magnetic bead immunoassay is antigen flexible and can be performed using either Nucleocapsid, Spike or Spike RBD. The method performed with low inter and intra assay variability using different antigens and detection modes and was able to deliver >99.5% specificity and >95% sensitivity for a cohort of 203 pre pandemic and 63 COVID-19 positive samples.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255330",
+    "rel_abs": "ImportanceIdentification of SARS-CoV-2 infection via antibody assays is important for monitoring natural infection rates. Most antibody assays cannot distinguish natural infection from vaccination.\n\nObjectiveTo assess the accuracy of a nucleocapsid-containing assay in identifying natural infection among vaccinated individuals.\n\nDesignA longitudinal cohort comprised of healthcare workers (HCW) in the Minneapolis/St. Paul metropolitan area was enrolled. Two rounds of seroprevalence studies separated by one month were conducted from 11/2020-1/2021. Capillary blood from round 1 and 2 was tested for IgG antibodies against SARS-CoV-2 spike proteins with a qualitative chemiluminescent ELISA (spike-only assay). In a subsample of participants (n=82) at round 2, a second assay was performed that measured IgGs reactive to SARS-CoV-2 nucleocapsid protein (nucleocapsid-containing assay). Round 1 biospecimen collections occurred prior to vaccination in all participants. Vaccination status at round 2 was determined via self-report.\n\nSettingThe Minneapolis/St. Paul, Minnesota metropolitan area.\n\nParticipantsHCW age 18-80 years.\n\nExposuresRound 1 recent SARS-CoV-2 infection assessed via a spike-only assay and participant self-report.\n\nOutcomesRound 2 SARS-CoV-2 infection assessed via the nucleocapsid-containing assay. Area under the curve (AUC) was computed to determine the discriminatory ability of round 2 IgG reactivity to nucleocapsid for identification of recent infection determined during round 1\n\nResultsParticipants had a mean age of 40 (range=23-66) years, 83% were female, 46% reported vaccination prior to the round 2 testing. Round 1 seroprevalence was 9.5%. Among those not recently infected, when comparing vaccinated vs. unvaccinated individuals, elevated levels of spike 1 (p<0.001) and spike 2 (p=0.01) were observed while nucleocapsid levels were not statistically significantly different (p=0.90). Among all participants, nucleocapsid response predicted recent infection with an AUC(95%CI) of 0.93(0.88,0.99). Among individuals vaccinated >10 days prior to antibody testing, the specificity of the nucleocapsid-containing assay was 92% and while the specificity of the spike-only assay was 0%.\n\nConclusions and RelevanceAn IgG assay identifying reactivity to nucleocapsid protein is an accurate predictor of natural infection among vaccinated individuals while a spike-only assay performed poorly. In the era of SARS-CoV-2 vaccination, seroprevalence studies monitoring natural infection will require assays that do not rely on spike-protein response alone.",
     "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Marcelo S Conzentino Sr.",
-        "author_inst": "UFPR"
+        "author_name": "Ryan T Demmer",
+        "author_inst": "Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN; Department of Epidemiology, Mailman School of "
       },
       {
-        "author_name": "Tatiele P.C. Santos Sr.",
-        "author_inst": "UFPR"
+        "author_name": "Brett Baumgartner",
+        "author_inst": "Quansys Biosciences, Logan, UT"
       },
       {
-        "author_name": "Khaled Selim",
-        "author_inst": "Tubingen University"
+        "author_name": "Talia D Wiggen",
+        "author_inst": "Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Berenike Wagner",
-        "author_inst": "Tubingen University"
+        "author_name": "Angela K Ulrich",
+        "author_inst": "Center for Infectious Disease Research and Policy, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Janette T Alford",
-        "author_inst": "Tubingen University"
+        "author_name": "Ali J Strickland",
+        "author_inst": "Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Nelli Deobald",
-        "author_inst": "Tubingen University"
+        "author_name": "Brianna M Naumchik",
+        "author_inst": "Medical School, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Nigella M Paula",
-        "author_inst": "UFPR"
+        "author_name": "Bruno Bohn",
+        "author_inst": "Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Fabiane G.M Rego Sr.",
-        "author_inst": "UFPR"
+        "author_name": "Sara Walsh",
+        "author_inst": "NORC at the University of Chicago, Health Sciences, Chicago, IL"
       },
       {
-        "author_name": "Dalila L Zanette",
-        "author_inst": "Fiocruz"
+        "author_name": "Stephen Smith",
+        "author_inst": "NORC at the University of Chicago, Health Sciences, Chicago, IL"
       },
       {
-        "author_name": "Mateus N Aoki",
-        "author_inst": "Fiocruz"
+        "author_name": "Susan Kline",
+        "author_inst": "Division of Infectious Diseases and International Medicine, Medical School, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Jeanine M Nardin",
-        "author_inst": "Hospital Erasto Gaerthener"
+        "author_name": "Steve D Stovitz",
+        "author_inst": "Department of Family Medicine and Community Health, Medical School, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Maria C.C Huergo",
-        "author_inst": "Prefeitura Municipal de Guaratuba"
+        "author_name": "Stephanie Yendell",
+        "author_inst": "Minnesota Department of Health, St. Paul, MN"
       },
       {
-        "author_name": "Rodrigo A Reis",
-        "author_inst": "UFPR"
+        "author_name": "Tim Beebe",
+        "author_inst": "Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN"
       },
       {
-        "author_name": "Luciano Huergo Sr.",
-        "author_inst": "UFPR"
+        "author_name": "Craig Hedberg",
+        "author_inst": "Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, MN"
       }
     ],
     "version": "1",
@@ -766216,51 +769875,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.13.21255384",
-    "rel_title": "Outcomes of COVID-19 infection in patients treated with Clozapine.",
+    "rel_doi": "10.1101/2021.04.13.21255413",
+    "rel_title": "The impact of population mobility on COVID-19 incidence and socioeconomic disparities at the sub-city level in 314 Latin American cities",
     "rel_date": "2021-04-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255384",
-    "rel_abs": "BackgroundClozapine, an antipsychotic, is associated with increased susceptibility to infection with COVID-19, compared to other antipsychotics.\n\nAimsTo investigate associations between clozapine treatment and increased risk of adverse outcomes of COVID-19, namely COVID-related hospitalisation and intensive care treatment, and death, among patients taking antipsychotics with schizophrenia-spectrum disorders.\n\nMethodUsing data from South London and Maudsley NHS Foundation Trust (SLAM) clinical records, via the Clinical Record Interactive Search system, we identified 157 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders, were taking antipsychotics at the time of the COVID-19 pandemic in the UK, and had a laboratory-confirmed COVID-19 infection. The following health outcomes were measured: COVID-related hospitalisation, COVID-related intensive care treatment death. We tested associations between clozapine treatment and each outcome using logistic regression models, adjusting for gender, age, ethnicity, neighbourhood deprivation, obesity, smoking status, diabetes, asthma, bronchitis and hypertension using propensity scores.\n\nResultsIn the 157 individuals who developed COVID while on antipsychotics, there were 44 COVID-related hospitalisations, 13 COVID-related intensive care treatments and 13 deaths of any cause during the follow-up period. In the unadjusted analysis, there was no significant association between clozapine and any of the outcomes and there remained no associations following adjusting for the confounding variables.\n\nConclusionsIn our sample of patients with COVID-19 and schizophrenia-spectrum disorders, we found no evidence that clozapine treatment puts patients at increased risk of hospitalisation, intensive care treatment or death, compared to any other antipsychotic treatment. However, further research should be considered in larger samples to confirm this.\n\nConflict of interestRDH has received research funding from Roche, Pfizer, Janssen, and Lundbeck. DFF has received research funding from Janssen and Lundbeck. JHM has received research funding from Lundbeck. JTT has received research funding from Bristol-Meyers-Squibb. RS declares research support in the last 36 months from Janssen, GSK and Takeda.\n\nEthics statementThe research was conducted under ethical approval reference 18/SC/0372 from Oxfordshire Research Ethics Committee C.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255413",
+    "rel_abs": "BackgroundLittle is known about the impact of changes in mobility at the sub-city level on subsequent COVID-19 incidence or the contribution of mobility to socioeconomic disparities in COVID-19 incidence.\n\nMethodsWe compiled aggregated mobile phone location data, COVID-19 confirmed cases, and features of the urban and social environments to analyze linkages between population mobility, COVID-19 incidence, and educational attainment at the sub-city level among cities with >100,000 inhabitants in Argentina, Brazil, Colombia, Guatemala, and Mexico from March to August 2020. We used mixed effects negative binomial regression to examine longitudinal associations between changes in weekly mobility (lags 1-6 weeks) and subsequent COVID-19 incidence at the sub-city level, adjusting for urban environmental factors.\n\nFindingsAmong 1,031 sub-cities representing 314 cities in five Latin American countries, 10% higher weekly mobility was associated with 8.5% (95% CI 7.4% to 9.5%) higher weekly COVID-19 incidence the following week. This association gradually declined as the lag between mobility and COVID-19 incidence increased and was not different from the null at a six-week lag. We found evidence that suggests differences in mobility reductions are a driver of socioeconomic disparities in COVID-19 incidence.\n\nInterpretationLower population movement within a sub-city is associated with lower risk of subsequent COVID-19 incidence among residents of that sub-city. Implementing policies that reduce population mobility at the sub-city level may be an impactful COVID-19 mitigation strategy that takes equity into consideration and reduces economic and social disruption at the city or regional level.\n\nFundingWellcome Trust",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Risha Govind",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK."
+        "author_name": "Josiah L Kephart",
+        "author_inst": "Dornsife School of Public Health, Drexel University, USA"
       },
       {
-        "author_name": "Daniela Fonseca de Freitas",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK."
+        "author_name": "Xavier Delclos-Alio",
+        "author_inst": "Institute of Urban and Regional Development, University of California, Berkeley, USA"
       },
       {
-        "author_name": "Megan Pritchard",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK."
+        "author_name": "Usama Bilal",
+        "author_inst": "Dornsife School of Public Health, Drexel University, USA"
       },
       {
-        "author_name": "Mizanur Khondoker",
-        "author_inst": "Faculty of Medicine and Health Sciences, Norwich Medical School, University of East Anglia, Norwich, UK."
+        "author_name": "Olga L Sarmiento",
+        "author_inst": "School of Medicine, Universidad de Los Andes, Colombia"
       },
       {
-        "author_name": "James T Teo",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK."
+        "author_name": "Tonatiuh Barrientos-Gutierrez",
+        "author_inst": "Center for Population Health Research, National Institute of Public Health, Mexico"
       },
       {
-        "author_name": "Robert Stewart",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK."
+        "author_name": "Manuel Ramirez-Zea",
+        "author_inst": "INCAP Research Center for the Prevention of Chronic Diseases, Institute of Nutrition of Central America and Panama, Guatemala"
       },
       {
-        "author_name": "Richard D. Hayes",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK."
+        "author_name": "D. Alex Quistberg",
+        "author_inst": "Dornsife School of Public Health, Drexel University, USA"
       },
       {
-        "author_name": "James H. MacCabe",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK."
+        "author_name": "Daniel A Rodriguez",
+        "author_inst": "Department of City and Regional Planning and Institute for Transportation Studies, University of California, Berkeley, USA"
+      },
+      {
+        "author_name": "Ana V Diez Roux",
+        "author_inst": "Dornsife School of Public Health, Drexel University, USA"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.04.12.21255329",
@@ -767974,127 +771637,31 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2021.04.13.21255139",
-    "rel_title": "Strong anti-viral responses in pediatric COVID-19 patients in South Brazil",
+    "rel_doi": "10.1101/2021.04.10.21254878",
+    "rel_title": "Preparations of Dutch emergency departments for the COVID-19 pandemic: a questionnaire-based study",
     "rel_date": "2021-04-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255139",
-    "rel_abs": "Epidemiological evidence that COVID-19 manifests as a milder disease in children compared to adults has been reported by numerous studies, but the mechanisms underlying this phenomenon have not been characterized. It is still unclear how frequently children get infected, and/or generate immune responses to SARS-CoV-2. We have performed immune profiling of pediatric and adult COVID-19 patients in Brazil, producing over 38 thousand data points, asking if cellular or humoral immune responses could help explain milder disease in children. In this study, pediatric COVID-19 patients presented high viral titers. Though their non-specific immune profile was dominated by naive, non-activated lymphocytes, their dendritic cells expressed high levels of HLA-DR and were low in CX3CR1, indicating competence to generate immune responses that are not targeted to inflamed tissue. Finally, children formed strong specific antibody and T cell responses for viral structural proteins. Childrens T cell responses differed from adults in that their CD8+ TNF+ T cell responses were low for S peptide but significantly higher against N and M peptide pools. Altogether, our data support a scenario in which SARS-CoV-2 infected children may contribute to transmission, though generating strong and differential responses to the virus that might associate with protection in pediatric COVID-19 presentation.",
-    "rel_num_authors": 27,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.10.21254878",
+    "rel_abs": "BackgroundThe onset of the COVID-19 pandemic was characterized by rapidly increasing patient volumes, which necessitated a swift emergency department (ED) overhaul. Challenges mainly concerned surge capacity, frontline staff protection and the segregation of patients with suspected COVID-19. To date, only few studies have assessed nation-wide ED preparedness for the COVID-19 pandemic. This study aimed to form an overview of preparations that were taken in Dutch EDs during the initial phase of this public health crisis.\n\nMethodsThis study was designed as a nation-wide, cross-sectional, questionnaire-based study among Dutch hospital organizations with [&ge;]1 ED. The questionnaire was conducted between the first and the second wave of the COVID-19 pandemic in the Netherlands and contained close-ended and open-ended questions on changes in ED infrastructure, ED workforce adaptions and the role of emergency physicians (EPs) in the hospitals crisis organization.\n\nResultsOverall response rate was 79.5%. All EDs had made preparations in anticipation of a possible COVID-19 surge. Treatment capacity was expanded in 69.7% of EDs, with a median increase of 49% (IQR 32.5-72.7%). COVID-19 suspected patients were segregated from non-COVID-19 patients in 86.4% of EDs. Non-COVID-19 patients were more often assessed at alternative locations than patients with suspected COVID-19 infection. In 81.8% of EDs the workforce was expanded, which mainly concerned expansion of nursing staff. A formal role of EPs in the hospitals crisis organization was reported by 93.9% of EP staffed hospital organizations.\n\nConclusionAll Dutch EDs made preparations for COVID-19 in a short time span and with many uncertainties. Preparations predominantly concerned expansion of treatment capacity and segregation of COVID-19 ED care. EPs had a prominent role, both in direct patient COVID-19 ED care and in the hospitals crisis organizations. Although it is vital for EDs to be able to dynamically adapt to community needs, variability of pandemic ED preparedness was high.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Tiago Fazolo",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
+        "author_name": "Rory D O' Connor",
+        "author_inst": "Department of Emergency Medicine, Jeroen Bosch Hospital, Henri Dunantstraat 1, 5223 GZ 's-Hertogenbosch, The Netherlands"
       },
       {
-        "author_name": "Karina Lima",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
+        "author_name": "Dennis G Barten",
+        "author_inst": "Department of Emergency Medicine, VieCuri Medical Center, Tegelseweg 210, 5912 BL Venlo, The Netherlands"
       },
       {
-        "author_name": "Julia C. Fontoura",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Priscila Oliveira de Souza",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Gabriel Hilario",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Renata Zorzetto",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Luiz Rodrigues Jr.",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Veridiane Maria Pscheidt",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Jayme Ferreira Neto",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Alisson F. Haubert",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Izza Gambin",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Aline C. Oliveira",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Raissa S. Mello",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Matheus Gutierrez",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
-      },
-      {
-        "author_name": "Rodrigo Benedetti Gassen",
-        "author_inst": "Center for Transplantation Sciences, Department of Surgery, Massachusetts"
-      },
-      {
-        "author_name": "Ivaine Tais Sauthier Sartor",
-        "author_inst": "Social responsibility - PROADI-SUS, Hospital Moinhos de Vento, Porto Alegre, Brazil"
-      },
-      {
-        "author_name": "Gabriela Oliveira Zavaglia",
-        "author_inst": "Social responsibility - PROADI-SUS, Hospital Moinhos de Vento, Porto Alegre, Brazil"
-      },
-      {
-        "author_name": "Ingrid Rodrigues Fernandes",
-        "author_inst": "Social responsibility - PROADI-SUS, Hospital Moinhos de Vento, Porto Alegre, Brazil"
-      },
-      {
-        "author_name": "Fernanda Hammes Varela",
-        "author_inst": "Social responsibility - PROADI-SUS, Hospital Moinhos de Vento, Porto Alegre, Brazil"
-      },
-      {
-        "author_name": "M\u00e1rcia Polese-Bonatto",
-        "author_inst": "Social responsibility - PROADI-SUS, Hospital Moinhos de Vento, Porto Alegre, Brazil"
-      },
-      {
-        "author_name": "Thiago J. Borges",
-        "author_inst": "Center for Transplantation Sciences, Department of Surgery, Massachusetts"
-      },
-      {
-        "author_name": "Sidia Maria Callegari-Jacques",
-        "author_inst": "Departamento de Estat\u00edstica, Universidade Federal do Rio Grande do Sul"
-      },
-      {
-        "author_name": "Marcela Santos Correa da Costa",
-        "author_inst": "Coordena\u00e7\u00e3o-Geral do Programa Nacional de Imuniza\u00e7\u00f5es - Departamento de Imuniza\u00e7\u00f5es e Doen\u00e7as Transmiss\u00edveis - Secretaria de Vigil\u00e2ncia em Sa\u00fade - Minist\u00e9rio da"
-      },
-      {
-        "author_name": "Jaqueline de Araujo Schwartz",
-        "author_inst": "Coordena\u00e7\u00e3o-Geral do Programa Nacional de Imuniza\u00e7\u00f5es - Departamento de Imuniza\u00e7\u00f5es e Doen\u00e7as Transmiss\u00edveis - Secretaria de Vigil\u00e2ncia em Sa\u00fade - Minist\u00e9rio da"
-      },
-      {
-        "author_name": "Marcelo Comerlato Scotta",
-        "author_inst": "Social responsibility - PROADI-SUS, Hospital Moinhos de Vento, Porto Alegre, Brazil"
-      },
-      {
-        "author_name": "Renato T. Stein",
-        "author_inst": "Social responsibility - PROADI-SUS, Hospital Moinhos de Vento, Porto Alegre, Brazil"
-      },
-      {
-        "author_name": "Cristina Bonorino",
-        "author_inst": "Departamento de Ci\u00eancias B\u00e1sicas da Sa\u00fade, Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre - UFCSPA. Porto Alegre RS Brazil"
+        "author_name": "Gideon HP Latten",
+        "author_inst": "Department of Emergency Medicine, Zuyderland Medical Center, Henri Dunantstraat 5, 6419 PC Heerlen, The Netherlands"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "emergency medicine"
   },
   {
     "rel_doi": "10.1101/2021.04.13.21254841",
@@ -769760,55 +773327,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.08.21255118",
-    "rel_title": "The association between loneliness during the COVID-19 pandemic and psychological distress",
+    "rel_doi": "10.1101/2021.04.09.21255215",
+    "rel_title": "Impacts of COVID-19 on sick leave",
     "rel_date": "2021-04-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255118",
-    "rel_abs": "The purpose of this study was to examine the association between loneliness and psychological distress during the COVID-19 pandemic in Japan. We conducted a cross-sectional, online study from 22 to 26 December 2020. A total of 27,036 participants, all employed at the time of the survey, were included in the analysis. Participants were asked if they felt loneliness in a single-item question. The Kessler 6 (K6) was used to assess psychological distress defined as K6 scores of 5 or higher, and 13 or higher. The odds ratios (ORs) of psychological distress associated with loneliness were estimated using a multilevel logistic model nested in the prefecture of residence, with adjustment for age, sex, marital status, equivalent income, educational level, smoking, alcohol consumption, job type, number of workplace employees, and cumulative incidence rate of COVID-19 in the prefecture. Communication with friends, acquaintances, and family was strongly associated with psychological distress, so we adjusted for these factors and eating meals alone. Results showed a significant association between loneliness and psychological distress (OR = 36.62, 95%CI = 32.95-40.69). Lack of friends to talk to, lack of acquaintances to ask for help, and lack of people to communicate with through social networking sites were all strongly associated with psychological distress, as were family time and solitary eating. Even after adjusting for these factors, loneliness was still strongly associated with psychological distress (OR = 29.36, 95%CI = 26.44-32.98). The association between loneliness during the COVID-19 pandemic and psychological distress indicates the need for intervention.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.09.21255215",
+    "rel_abs": "AimTo explore sick leave after COVID-19, by comparing doctor-certified sick leave for up to 6 months after testing for SARS-CoV-2 across employees who tested positive and negative.\n\nMethodsIn all persons (20-70 year of age) with an employment contract, who were tested for the SARS-CoV-2 in Norway from March 1st to November 1st 2020 (N=740 182 with mean [SD] age 39 [13] years, 44% men), we used a difference-in-difference design to contrast doctor-certified sick leave before and after testing, across employees with negative test and positive test by age and sex groups.\n\nResultsSick leave for those testing positive (N=11 414) remained elevated for up to 2 months after testing when compared to those testing negative (N= 728 768), for men and women aged 20-44 and for men aged 45-70 years (relative increase in sick-leave [~]344-415%, (Ball strata=0.079, 95% CI=0.076, 0.082). The increase in sick leave was prolonged for women aged 45-70 years only, persisting for up to 4 months after testing positive (relative increase = 35%, B=0.010, 95% CI=0.004-0.035).\n\nConclusionSick leave following COVID-19 is elevated for up to two to four months after initial infection, thereafter not elevated compared with employees who tested negative for COVID-19. Women aged 45-70 years tend to have a larger impact of COVID-19 on their work ability than men and younger women.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Yusuke Konno",
-        "author_inst": "University of Occupational and Environmental Health, Japan"
-      },
-      {
-        "author_name": "Masako Nagata",
-        "author_inst": "Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Jap"
-      },
-      {
-        "author_name": "Ayako Hino",
-        "author_inst": "Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan"
-      },
-      {
-        "author_name": "Seiichiro Tateishi",
-        "author_inst": "Department of Occupational Medicine, School of Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan"
-      },
-      {
-        "author_name": "Mayumi Tsuji",
-        "author_inst": "Department of Environmental Health, School of Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan"
-      },
-      {
-        "author_name": "Akira Ogami",
-        "author_inst": "Department of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japa"
+        "author_name": "Katrine Damgaard Skyrud",
+        "author_inst": "Norwegian Institute of Public Health"
       },
       {
-        "author_name": "Reiji Yoshimura",
-        "author_inst": "Department of Psychiatry, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan"
+        "author_name": "Kjetil Elias Telle",
+        "author_inst": "Norwegian Institute of Public Health"
       },
       {
-        "author_name": "Shinya Matsuda",
-        "author_inst": "Department of Preventive Medicine and Community Health, School of Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan"
+        "author_name": "Kjersti Helene Hernaes",
+        "author_inst": "Norwegian Institute of Public Health"
       },
       {
-        "author_name": "Yoshihisa Fujino",
-        "author_inst": "University of Occupational and Environmental Health, Japan"
+        "author_name": "Karin Magnusson",
+        "author_inst": "Norwegian Institute of Public Health"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "occupational and environmental health"
   },
   {
     "rel_doi": "10.1101/2021.04.09.21255047",
@@ -771586,107 +775133,75 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2021.04.13.439641",
-    "rel_title": "Spike Protein Targeting \"Nano-Glue\" that Captures and Promotes SARS-CoV-2 Elimination",
+    "rel_doi": "10.1101/2021.04.14.439793",
+    "rel_title": "Neuropilin-1 Mediates SARS-CoV-2 Infection in Bone Marrow-derived Macrophages",
     "rel_date": "2021-04-14",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.13.439641",
-    "rel_abs": "The global emergency caused by the SARS-CoV-2 pandemics can only be solved with adequate preventive and therapeutic strategies, both currently missing. The electropositive Receptor Binding Domain (RBD) of SARS-CoV-2 spike protein with abundant {beta}-sheet structure serves as target for COVID-19 therapeutic drug design. Here, we discovered that ultrathin 2D CuInP2S6 (CIPS) nanosheets as a new agent against SARS-CoV-2 infection, which also able to promote viral host elimination. CIPS exhibits extremely high and selective binding capacity with the RBD of SARS-CoV-2 spike protein, with consequent inhibition of virus entry and infection in ACE2-bearing cells and human airway epithelial organoids. CIPS displays nano-viscous properties in selectively binding with spike protein (KD < 1 pM) with negligible toxicity in vitro and in vivo. Further, the CIPS-bound SARS-CoV-2 was quickly phagocytosed and eliminated by macrophages, suggesting CIPS could be successfully used to capture and facilitate the virus host elimination with possibility of triggering anti-viral immunization. Thus, we propose CIPS as a promising nanodrug for future safe and effective anti-SARS-CoV-2 therapy, as well as for use as disinfection agent and surface coating material to constrain the SARS-CoV-2 spreading.",
-    "rel_num_authors": 22,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.14.439793",
+    "rel_abs": "SARS-CoV-2 infection in human can cause medical complications across various tissues and organs. Despite of the advances to understanding the pathogenesis of SARS-CoV-2, its tissue tropism and interactions with host cells have not been fully understood. Existing clinical data have suggested possible SARS-CoV-2 infection in human skeleton system. In the present study, we found that authentic SARS-CoV-2 could efficiently infect human and mouse bone marrow-derived macrophages (BMMs) and alter the expression of macrophage chemotaxis and osteoclast-related genes. Importantly, in a mouse SARS-CoV-2 infection model that was enabled by the intranasal adenoviral (AdV) delivery of human angiotensin converting enzyme 2 (hACE2), SARS-CoV-2 was found to be present in femoral BMMs as determined by in situ immunofluorescence analysis. Using single-cell RNA sequencing (scRNA-Seq), we characterized SARS-CoV-2 infection in BMMs. Importantly, SARS-CoV-2 entry on BMMs appeared to be dependent on the expression of neuropilin-1 (NRP1) rather than the widely recognized receptor ACE2. It was also noted that unlike brain macrophages which displayed aging-dependent NRP1 expression, BMMs from neonatal and aged mice had constant NRP1 expression, making BMMs constantly vulnerable target cells for SARS-CoV-2. Furthermore, it was found that the abolished SARS-CoV-2 entry in BMM-derived osteoclasts was associated with the loss of NRP1 expression during BMM-to-osteoclast differentiation. Collectively, our study has suggested that NRP1 can mediate SARS-CoV-2 infection in BMMs, which precautions the potential impact of SARS-CoV-2 infection on human skeleton system.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Guofang Zhang",
-        "author_inst": "Laboratory of Immunology and Nanomedicine, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
+        "author_name": "Gao Junjie",
+        "author_inst": "Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Shanghai Sixth People Hospital, Shanghai, 200233, China"
       },
       {
-        "author_name": "Yalin Cong",
-        "author_inst": "University of Chinese Academy of Science"
+        "author_name": "Mei Hong",
+        "author_inst": "Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, 201210, China"
       },
       {
-        "author_name": "Guoli Cao",
-        "author_inst": "Laboratory of Immunology and Nanomedicine, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Liang Li",
-        "author_inst": "Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Peng Yu",
-        "author_inst": "School of Materials Science and Engineering, Sun Yat-sen University"
-      },
-      {
-        "author_name": "Qingle Song",
-        "author_inst": "Laboratory of Immunology and Nanomedicine, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Ke Liu",
-        "author_inst": "Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Jing Qu",
-        "author_inst": "Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Jing Wang",
-        "author_inst": "State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University"
-      },
-      {
-        "author_name": "Wei Xu",
-        "author_inst": "CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety & CAS Center for Excellence in Nanoscience, Institute of High Energy Physics and Natio"
-      },
-      {
-        "author_name": "Shumin Liao",
-        "author_inst": "Department of Otolaryngology, The Seventh Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Sun Jing",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Yunping Fan",
-        "author_inst": "Department of Otolaryngology, The Seventh Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Li Hao",
+        "author_inst": "Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Shanghai Sixth People Hospital, Shanghai, 200233, China"
       },
       {
-        "author_name": "Yufeng Li",
-        "author_inst": "CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety & CAS Center for Excellence in Nanoscience, Institute of High Energy Physics and Natio"
+        "author_name": "Huang Yuege",
+        "author_inst": "Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, 201210, China"
       },
       {
-        "author_name": "Guocheng Wang",
-        "author_inst": "Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
+        "author_name": "Tang Yanhong",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Lijing Fang",
-        "author_inst": "Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
+        "author_name": "Duan Linwei",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Yanzhong Chang",
-        "author_inst": "College of Life Science, Hebei Normal University"
+        "author_name": "Liu Delin",
+        "author_inst": "Centre for Orthopaedic Research, School of Surgery, The University of Western Australia, Nedlands, Western Australia, 6009, Australia"
       },
       {
-        "author_name": "Yuliang Zhao",
-        "author_inst": "Research Unit of Nanoscience and Technology, Chinese Academy of Medical Sciences"
+        "author_name": "Wang Qiyang",
+        "author_inst": "Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Shanghai Sixth People Hospital, Shanghai, 200233, China"
       },
       {
-        "author_name": "Diana Boraschi",
-        "author_inst": "The Institute of Biochemistry and Cell Biology, National Research Council"
+        "author_name": "Gao Youshui",
+        "author_inst": "Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Shanghai Sixth People Hospital, Shanghai, 200233, China"
       },
       {
-        "author_name": "Hongchang Li",
-        "author_inst": "Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences"
+        "author_name": "Song Ke",
+        "author_inst": "Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, 201210, China"
       },
       {
-        "author_name": "Chunying Chen",
-        "author_inst": "CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety & CAS Center for Excellence in Nanoscience, Institute of High Energy Physics and Natio"
+        "author_name": "Zhao Jincun",
+        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
       },
       {
-        "author_name": "Liming Wang",
-        "author_inst": "CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety & CAS Center for Excellence in Nanoscience, Institute of High Energy Physics and Natio"
+        "author_name": "Zhang Changqing",
+        "author_inst": "Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Shanghai Sixth People Hospital, Shanghai, 200233, China"
       },
       {
-        "author_name": "Yang Li",
-        "author_inst": "Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"
+        "author_name": "Liu Jia",
+        "author_inst": "Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, 201210, China"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.04.13.439709",
@@ -773216,33 +776731,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.11.21253563",
-    "rel_title": "Impact of COVID -19 on Depression and Anxiety among Healthcare Professionals in Abu Dhabi",
+    "rel_doi": "10.1101/2021.04.09.21255179",
+    "rel_title": "SARS-CoV-2 UK, South African and Brazilian Variants in Karachi- Pakistan",
     "rel_date": "2021-04-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.11.21253563",
-    "rel_abs": "COVID-19 have affected Healthcare workers is many ways. One of the important areas is the psychological impact. The aim of this study is to examine the effects of the COVID-19 outbreak on the mental health of healthcare Professionals (HCP). A cross-sectional study was conducted between April 11th, and July 23rd, 2020, to assess depression and anxiety of healthcare workers, during the COVID-19 pandemic. An online, self-administered, anonymous questionnaire evaluated 1,268 HCP. More than half of the participants reported symptoms of anxiety (51.5%). Mild anxiety was reported in 28.8% of participating HCP, and 12.68 % of the participants registered moderate anxiety scores, while 9.95 % reported severe anxiety. Depression symptoms were revealed in 38.3 % of participating providers. Among all participates, 4.3 % and 2.7 % reported moderately severe and severe depression, accordingly, while 22.5%, and 8.8 % of the participating health care providers documented mild and moderate depression. The high prevalence of anxiety and depression recorded among HCP during the pandemic suggests that mental health intervention and support are necessary to ensure the psychological well-being of HCP.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.09.21255179",
+    "rel_abs": "COVID-19 pandemic has been evolving in Pakistan since the UK, South African and Brazilian variants have started surfacing which are known for increase transmissibility and can also be responsible for escape from immune responses. The gold standard to detect these variants of concern is sequencing, however routine genomic surveillance in resource limited countries like Pakistan is not always readily available. With the emergence of variants of concern and a dearth of facilities for genomic scrutiny leaves policy makers and health authorities an inconsistent and twisted image to make decisions. The inadvertent detection of B.1.1.7 by target failure because of a key deletion in spike {Delta}69-70 in the UK by commercially available COVID-19 PCR assay helps to understand target failures as an alternative approach to detect variants. It was ascertained further that a deletion in the ORF1a gene (ORF1a {Delta}3675-3677) found common in B.1.1.7, B.135 and P.1 variants of concern. The Real Time Quantitative PCR (RT-qPCR) assay for detection of emergence and spread of SARS-CoV-2 variants, by these target failures is used here. The positive samples archived in respective labs were divided in two groups used in the present study. Group I constitutes 261 positive samples out of 16964 (1.53%) collected from August till September 2020. Group II include 3501 positive samples out of 46041 (7.60%) from November 2020 till January 2021. In positive samples of group I, no variant of concern was found. A staggering difference in results was noted in group II where positivity ratio increased exponentially and the variants of concern started appearing in significant numbers (53.64% overall). This is indicative that the third wave in Pakistan is due to the importation of SARS-CoV-2 variants. This calls for measures to increase surveillance by RT-qPCR which would help authorities in decision making.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Amal Alzarooni",
-        "author_inst": "Ambulatory health care,Abu Dhabi Health Services Company, UAE"
+        "author_name": "Adnan Khan",
+        "author_inst": "Karachi Institute of Radiotherapy and Nuclear Medicine (KIRAN)"
+      },
+      {
+        "author_name": "Muhammad Hanif",
+        "author_inst": "1) Karachi Institute of Radiotherapy and Nuclear Medicine (KIRAN), Karachi and 2) Advanced Laboratories, Karachi"
       },
       {
-        "author_name": "Aljazia Alghfeli",
-        "author_inst": "Ambulatory health care, Abu Dhabi Health Services Company, AE"
+        "author_name": "Sarosh Syed",
+        "author_inst": "Advanced Laboratories, Karachi"
       },
       {
-        "author_name": "Hamda Alremeithi",
-        "author_inst": "Ambulatory health care,Abu Dhabi Health Services Company  , UAE"
+        "author_name": "Akhtar Ahmed",
+        "author_inst": "Karachi Institute of Radiotherapy and Nuclear Medicine (KIRAN), Karachi"
       },
       {
-        "author_name": "Roqayah Al Madhaani,",
-        "author_inst": "Ambulatory Healthcare Services,Abu Dhabi Health Services Company, UAE"
+        "author_name": "Saqib Ghazali",
+        "author_inst": "Karachi Institute of Radiotherapy and Nuclear Medicine (KIRAN), Karachi"
       },
       {
-        "author_name": "Latifa Al Ketbi,",
-        "author_inst": "Ambulatory Healthcare Services, Abu Dhabi Health Services Company, UAE"
+        "author_name": "Rafiq Khanani",
+        "author_inst": "1) Advanced Laboratories, Karachi 2) Citilab Diagnostic Center, Karachi and 3) Global Research and Reference Labs, Karachi"
       }
     ],
     "version": "1",
@@ -775194,63 +778713,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.09.21255161",
-    "rel_title": "The PUPPY Study - Protocol for a Longitudinal Mixed Methods Study Exploring Problems Coordinating and Accessing Primary Care for Attached and Unattached Patients Exacerbated During the COVID-19 Pandemic Year",
+    "rel_doi": "10.1101/2021.04.08.21255046",
+    "rel_title": "COVID-19 and mortality risk in patients with psychiatric disorders",
     "rel_date": "2021-04-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.09.21255161",
-    "rel_abs": "BackgroundThe COVID-19 pandemic significantly disrupted primary care in Canada, with many walk-in clinics and family practices initially closing or being perceived as inaccessible, pharmacies remaining open with restrictions on patient interactions, rapid uptake of virtual care, and reduced referrals for lab tests, diagnostics, and specialist care. The PUPPY Study (Problems Coordinating and Accessing Primary Care for Attached and Unattached Patients Exacerbated During the COVID-19 Pandemic Year) seeks to understand the impact of COVID-19 across the quadruple aim of primary care, with particular focus on the impacts on patients without attachment to a regular provider and those with chronic health conditions.\n\nObjectiveThe PUPPY Study objective is to understand the impact of COVID-19 across the quadruple aim of primary care.\n\nMethodsThe PUPPY study builds on an existing research program exploring patients access and attachment to primary care, pivoted to adapt to the emerging COVID-19 context. We will undertake a longitudinal mixed methods study to understand critical gaps in primary care access and coordination, comparing data pre- and post-pandemic in three Canadian provinces (Quebec, Ontario, and Nova Scotia). Multiple data sources will be used including: a policy review; qualitative interviews with primary care policymakers, providers (i.e., family physicians, nurse practitioners, and pharmacists), and patients (N=120); and medication prescribing and healthcare billings. The findings will inform the strengthening of primary care during and beyond the COVID-19 pandemic.\n\nResultsFunding was provided by the Canadian Institutes of Health Research COVID-19 Rapid Funding Opportunity Grant. Ethical approval to conduct this study was granted in Ontario (Queens Health Sciences & Affiliated Teaching Hospitals Research Ethics Board, file number 6028052; Western University Health Sciences Research Ethics Board, project 116591; University of Toronto Health Sciences Research Ethics Board, protocol number 40335), Quebec (Centre integre universitaire de sante et de services sociaux de lEstrie, project number 2020-3446) and Nova Scotia (Nova Scotia Health Research Ethics Board, file number 1024979).\n\nConclusionsThis is the first study of its kind exploring the impacts of COVID-19 on primary care systems, with particular focus on the issues of patients attachment and access to primary care. Through a multi-stakeholder, cross-jurisdictional approach, the PUPPY Study will generate findings and implications for future policy and practice.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.08.21255046",
+    "rel_abs": "COVID-19 has already caused the deaths of over 2.5 million people worldwide. Patients with certain medical conditions and severe psychiatric disorders are at increased risk of dying from it. However, such people have a reduced life expectancy anyway, raising the question whether COVID-19 incurs a specific risk for such patients for dying, over and above the risk of dying from other causes.\n\nWe analysed the UK Biobank data of half a million middle-aged participants from the UK. From the start of 2020 up to 24th January 2021, 894 participants had died from COVID-19 and another 4,562 had died from other causes. We demonstrate that the risk of dying from COVID-19 among patients with mental health problems, especially those with dementia, schizophrenia, or bipolar disorder, is increased compared to the risk of dying from other causes. This increase among patients with severe psychiatric disorders cannot be explained solely by the higher rate of diabetes or cardiovascular disorders.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Emily Gard Marshall",
-        "author_inst": "Dalhousie University"
-      },
-      {
-        "author_name": "Mylaine Breton",
-        "author_inst": "Universite de Sherbrooke"
-      },
-      {
-        "author_name": "Benoit Cossette",
-        "author_inst": "Universite de Sherbrooke"
-      },
-      {
-        "author_name": "Jennifer Isenor",
-        "author_inst": "Dalhousie University"
-      },
-      {
-        "author_name": "Maria Mathews",
-        "author_inst": "Western University"
-      },
-      {
-        "author_name": "Caitlyn Ayn",
-        "author_inst": "Dalhousie University"
-      },
-      {
-        "author_name": "Melanie Ann Smithman",
-        "author_inst": "Universite de Sherbrooke"
-      },
-      {
-        "author_name": "David Stock",
-        "author_inst": "Dalhousie University"
-      },
-      {
-        "author_name": "Eliot Frymire",
-        "author_inst": "Queen's University"
-      },
-      {
-        "author_name": "Lynn Edwards",
-        "author_inst": "Nova Scotia Health"
+        "author_name": "George Kirov",
+        "author_inst": "Cardiff University"
       },
       {
-        "author_name": "Michael Green",
-        "author_inst": "Queen's University"
+        "author_name": "Emily Baker",
+        "author_inst": "Cardiff University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "primary care research"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2021.04.07.21255079",
@@ -777008,51 +780491,127 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.09.439260",
-    "rel_title": "Nosocomial Pseudomonas aeruginosaregulates alginate biosynthesis and Type VI secretion system during adaptive and convergent evolution for coinfection in critically ill COVID-19 patients",
+    "rel_doi": "10.1101/2021.04.10.439275",
+    "rel_title": "CoVac501, a self-adjuvanting peptide vaccine conjugated with TLR7 agonists, against SARS-CoV-2 induces protective immunity",
     "rel_date": "2021-04-11",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.09.439260",
-    "rel_abs": "COVID-19 pandemic has caused millions of death globally and caused huge impact on the health of infected patients. Shift in the lung microbial ecology upon such viral infection often worsens the disease and increases host susceptibility to secondary infections. Recent studies have indicated that bacterial coinfection is an unignorable factor contributing to the aggravation of COVID-19 and posing great challenge to clinical treatments. However, there is still a lack of in-depth investigation on the coinfecting bacteria in COVID-19 patients for better treatment of bacterial coinfection. With the knowledge that Pseudomonas aeruginosa is one of the top coinfecting pathogens, we analyzed the adaptation and convergent evolution of nosocomial P. aeruginosa isolated from two critical COVID-19 patients in this study. We sequenced and compared the genomes and transcriptomes of P. aeruginosa isolates longitudinally and parallelly for its evolutionary traits. P. aeruginosa overexpressed alginate and attenuated Type VI secretion system (T6SS) during coinfection for excessive biofilm formation and suppressed virulence. Results of bacterial competition assay and macrophage cytotoxicity test indicated that P. aeruginosa reduced its virulence towards both prokaryotic competitors and eukaryotic host through inhibiting its T6SS during evolution. P. aeuginosa T6SS is thus one of the reasons for its advantage to cause coinfection in COVID-19 patients while the attenuation of T6SS could cause a shift in the microecological composition in the lung. Our study will contribute to the development of therapeutic measures and the discovery of novel drug target to eliminate P. aeruginosa coinfection in COVID-19 patient.",
-    "rel_num_authors": 8,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.10.439275",
+    "rel_abs": "Safe, economical and effective vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed to achieve adequate herd immunity and halt the pandemic. We have constructed a novel SARS-CoV-2 vaccine, CoVac501, which is a self-adjuvanting peptide vaccine conjugated with Toll-like receptor 7 (TLR7) agonists. The vaccine contains two immunodominant peptides screened from receptor-binding domain (RBD) and is fully chemically synthesized. And the vaccine has optimized nanoemulsion formulation, outstanding stability and safety. In non-human primates (NHPs), CoVac501 elicited high and persistent titers of RBD-specific and protective neutralizing antibodies (NAbs), which were also effective to RBD mutations. CoVac501 was found to elicit the increase of memory T cells, antigen-specific CD8+ T cell responses and Th1-biased CD4+ T cell immune responses in NHPs. More importantly, the sera from the immunized NHPs can prevent infection of live SARS-CoV-2 in vitro.\n\nOne-Sentence SummaryA novel SARS-CoV-2 vaccine we developed, CoVac501, which is a fully chemically synthesized and self-adjuvanting peptides conjugated with TLR7 agonists, can induce high-efficient humoral and cellular immune responses against SARS-CoV-2.",
+    "rel_num_authors": 27,
     "rel_authors": [
       {
-        "author_name": "Zhao Cai",
-        "author_inst": "School of Medicine, Southern University of Science and Technology"
+        "author_name": "Yiru Long",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
       },
       {
-        "author_name": "Xiangke Duan",
-        "author_inst": "School of Medicine, Southern University of Science and Technology"
+        "author_name": "Jianhua Sun",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
       },
       {
-        "author_name": "Han Zhang",
-        "author_inst": "School of Medicine, Southern University of Science and Technology"
+        "author_name": "Tingting Liu",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China."
       },
       {
-        "author_name": "Shuhong Han",
-        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, 518055, China"
+        "author_name": "Feng Tang",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
       },
       {
-        "author_name": "Kaiwei Yu",
-        "author_inst": "School of Medicine, Southern University of Science and Technology"
+        "author_name": "Xinxin Zhang",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
       },
       {
-        "author_name": "Yingdan Zhang",
-        "author_inst": "School of Medicine, Southern University of Science and Technology"
+        "author_name": "Qiuping Qin",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China."
       },
       {
-        "author_name": "Yang Liu",
-        "author_inst": "Medical Research Center, Southern University of Science and Technology Hospital"
+        "author_name": "Yunqiu Miao",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
       },
       {
-        "author_name": "Liang Yang",
-        "author_inst": "School of Medicine, Southern University of Science and Technology"
+        "author_name": "Xiaoyan Pan",
+        "author_inst": "Wuhan institute of virology, Chinese academy of sciences"
+      },
+      {
+        "author_name": "Qi An",
+        "author_inst": "Shanghai King-Cell Biotechnology Co., Ltd., No. 1136 Langong Road, Jinshan District, Shanghai"
+      },
+      {
+        "author_name": "Mian Qin",
+        "author_inst": "Zhongshan Institute for Drug Discovery, Institutes of Drug Discovery and Development, Chinese Academy of Sciences, Zhongshan, 528400, China."
+      },
+      {
+        "author_name": "Xiankun Tong",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China."
+      },
+      {
+        "author_name": "Xionghua Peng",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China."
+      },
+      {
+        "author_name": "Pan Yu",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China."
+      },
+      {
+        "author_name": "Peng Zhu",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China."
+      },
+      {
+        "author_name": "Weiliang Zhu",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
+      },
+      {
+        "author_name": "Yachun Zhang",
+        "author_inst": "Shanghai King-Cell Biotechnology Co., Ltd., No. 1136 Langong Road, Jinshan District, Shanghai"
+      },
+      {
+        "author_name": "Leike Zhang",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Gengfu Xiao",
+        "author_inst": "Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Jianping Zuo",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
+      },
+      {
+        "author_name": "Wei Tang",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
+      },
+      {
+        "author_name": "Ji Zhou",
+        "author_inst": "School of Pharmaceutical Sciences, Shenzhen University Health Science Center, Shenzhen University, Shenzhen, 518060, China;  International Cancer Center, Nation"
+      },
+      {
+        "author_name": "Zhijian Xu",
+        "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Yong Gan",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
+      },
+      {
+        "author_name": "Jin Ren",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
+      },
+      {
+        "author_name": "Wei Huang",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
+      },
+      {
+        "author_name": "Guangyi Jin",
+        "author_inst": "School of Pharmaceutical Sciences, Shenzhen University Health Science Center, Shenzhen University, Shenzhen, 518060, China; International Cancer Center, Nation-"
+      },
+      {
+        "author_name": "Likun Gong",
+        "author_inst": "State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; University of Chinese Academy"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.04.10.439161",
@@ -778710,145 +782269,81 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2021.04.05.21254834",
-    "rel_title": "Performance of Repeat BinaxNOW SARS-CoV-2 Antigen Testing in a Community Setting, Wisconsin, November-December 2020",
+    "rel_doi": "10.1101/2021.04.04.21254881",
+    "rel_title": "Neutralization of SARS-CoV-2 variants by convalescent and vaccinated serum",
     "rel_date": "2021-04-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21254834",
-    "rel_abs": "Repeating the BinaxNOW antigen test for SARS-CoV-2 by two groups of readers within 30 minutes resulted in high concordance (98.9%) in 2,110 encounters. BinaxNOW test sensitivity was 77.2% (258/334) compared to real-time reverse transcription-polymerase chain reaction. Repeating antigen testing on the same day did not significantly improve test sensitivity while specificity remained high.",
-    "rel_num_authors": 32,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.04.21254881",
+    "rel_abs": "We tested human sera from large, demographically balanced cohorts of BNT162b2 vaccine recipients (n=51) and COVID-19 patients (n=44) for neutralizing antibodies against SARS-CoV-2 variants B.1.1.7 and B.1.351. Although the effect is more pronounced in the vaccine cohort, both B.1.1.7 and B.1.351 show significantly reduced levels of neutralization by vaccinated and convalescent sera. Age is negatively correlated with neutralization in vaccinee, and levels of variant-specific RBD antibodies are proportional to neutralizing activities.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Melisa M. Shah",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Phillip P. Salvatore",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Laura Ford",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Emiko Kamitani",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Melissa J. Whaley",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Kaitlin Mitchell",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Dustin W. Currie",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Clint N. Morgan",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Hannah E. Segaloff",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Shirley Lecher",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Tarah Somers",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Miriam E. Van Dyke",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "John Paul Bigouette",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Augustina Delaney",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Juliana DaSilva",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Michelle O'Hegarty",
-        "author_inst": "Centers for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Lauren Boyle-Estheimer",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Timothy A. Bates",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Fatima Abdirizak",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Hans C Leier",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Sandor E. Karpathy",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Zoe L Lyski",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Jennifer Meece",
-        "author_inst": "Marshfield Clinic Research Institute"
+        "author_name": "Savannah K McBride",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Lynn Ivanic",
-        "author_inst": "Marshfield Clinic Research Institute"
+        "author_name": "Felicity J Coulter",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Kimberly Goffard",
-        "author_inst": "Winnebago County Health Department"
+        "author_name": "Jules B Weinstein",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Doug Gieryn",
-        "author_inst": "Winnebago County Health Department"
+        "author_name": "James R Goodman",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Alana Sterkel",
-        "author_inst": "Wisconsin State Laboratory of Hygiene"
+        "author_name": "Zhengchun Lu",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Allen Bateman",
-        "author_inst": "Wisconsin State Laboratory of Hygiene"
+        "author_name": "Sarah A. R. Siegel",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Juliana Kahrs",
-        "author_inst": "University of Wisconsin-Oshkosh"
+        "author_name": "Peter Sullivan",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Kimberly Langolf",
-        "author_inst": "University of Wisconsin-Oshkosh"
+        "author_name": "Matt Strnad",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Tara Zochert",
-        "author_inst": "University of Wisconsin-Oshkosh"
+        "author_name": "Amanda E Brunton",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Nancy W. Knight",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "David X Lee",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Christopher H. Hsu",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Marcel E Curlin",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Hannah L. Kirking",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "William B Messer",
+        "author_inst": "Oregon Health & Science University"
       },
       {
-        "author_name": "Jacqueline E. Tate",
-        "author_inst": "Centers for Disease Control and Prevention"
+        "author_name": "Fikadu G Tafesse",
+        "author_inst": "Oregon Health & Science University"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -780340,203 +783835,103 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.06.438709",
-    "rel_title": "Antibodies to the SARS-CoV-2 receptor-binding domain that maximize breadth and resistance to viral escape",
+    "rel_doi": "10.1101/2021.04.07.438806",
+    "rel_title": "Identifying SARS-CoV-2 Antiviral Compounds by Screening for Small Molecule Inhibitors of nsp5 Main Protease",
     "rel_date": "2021-04-08",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.06.438709",
-    "rel_abs": "An ideal anti-SARS-CoV-2 antibody would resist viral escape1-3, have activity against diverse SARS-related coronaviruses4-7, and be highly protective through viral neutralization8-11 and effector functions12,13. Understanding how these properties relate to each other and vary across epitopes would aid development of antibody therapeutics and guide vaccine design. Here, we comprehensively characterize escape, breadth, and potency across a panel of SARS-CoV-2 antibodies targeting the receptor-binding domain (RBD), including S3094, the parental antibody of the late-stage clinical antibody VIR-7831. We observe a tradeoff between SARS-CoV-2 in vitro neutralization potency and breadth of binding across SARS-related coronaviruses. Nevertheless, we identify several neutralizing antibodies with exceptional breadth and resistance to escape, including a new antibody (S2H97) that binds with high affinity to all SARS-related coronavirus clades via a unique RBD epitope centered on residue E516. S2H97 and other escape-resistant antibodies have high binding affinity and target functionally constrained RBD residues. We find that antibodies targeting the ACE2 receptor binding motif (RBM) typically have poor breadth and are readily escaped by mutations despite high neutralization potency, but we identify one potent RBM antibody (S2E12) with breadth across sarbecoviruses closely related to SARS-CoV-2 and with a high barrier to viral escape. These data highlight functional diversity among antibodies targeting the RBD and identify epitopes and features to prioritize for antibody and vaccine development against the current and potential future pandemics.",
-    "rel_num_authors": 46,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.07.438806",
+    "rel_abs": "The coronavirus 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread around the world with unprecedented health and socio-economic effects for the global population. While different vaccines are now being made available, very few antiviral drugs have been approved. The main viral protease (nsp5) of SARS-CoV-2 provides an excellent target for antivirals, due to its essential and conserved function in the viral replication cycle. We have expressed, purified and developed assays for nsp5 protease activity. We screened the nsp5 protease against a custom chemical library of over 5,000 characterised pharmaceuticals. We identified calpain inhibitor I and three different peptidyl fluoromethylketones (FMK) as inhibitors of nsp5 activity in vitro, with IC50 values in the low micromolar range. By altering the sequence of our peptidomimetic FMK inhibitors to better mimic the substrate sequence of nsp5, we generated an inhibitor with a subnanomolar IC50. Calpain inhibitor I inhibited viral infection in monkey-derived Vero E6 cells, with an EC50 in the low micromolar range. The most potent and commercially available peptidyl-FMK compound inhibited viral growth in Vero E6 cells to some extent, while our custom peptidyl FMK inhibitor offered a marked antiviral improvement.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Tyler N Starr",
-        "author_inst": "Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA"
-      },
-      {
-        "author_name": "Nadine Czudnochowski",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Fabrizia Zatta",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
-      },
-      {
-        "author_name": "Young-Jun Park",
-        "author_inst": "Department of Biochemistry, University of Washington, Seattle, WA 98195, USA"
-      },
-      {
-        "author_name": "Zhuoming Liu",
-        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA"
-      },
-      {
-        "author_name": "Amin Addetia",
-        "author_inst": "Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA"
-      },
-      {
-        "author_name": "Dora Pinto",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
-      },
-      {
-        "author_name": "Martina Beltramello",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
-      },
-      {
-        "author_name": "Patrick Hernandez",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Allison J Greaney",
-        "author_inst": "Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98"
-      },
-      {
-        "author_name": "Roberta Marzi",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
-      },
-      {
-        "author_name": "William G Glass",
-        "author_inst": "Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"
-      },
-      {
-        "author_name": "Ivy Zhang",
-        "author_inst": "Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Tri-Institutional PhD Pro"
-      },
-      {
-        "author_name": "Adam S Dingens",
-        "author_inst": "Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA"
-      },
-      {
-        "author_name": "John E Bowen",
-        "author_inst": "Department of Biochemistry, University of Washington, Seattle, WA 98195, USA"
-      },
-      {
-        "author_name": "Jason A Wojcechowskyj",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Anna De Marco",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
-      },
-      {
-        "author_name": "Laura E Rosen",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Jiayi Zhou",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Martin Montiel-Ruiz",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Hannah Kaiser",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Heather Tucker",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Michael P. Housley",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Julia Di Iulio",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
-      },
-      {
-        "author_name": "Gloria Lombardo",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
-      },
-      {
-        "author_name": "Maria Agostini",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "Clovis Basier",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Nicole Sprugasci",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
+        "author_name": "Rupert Beale",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Katja Culap",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
+        "author_name": "Ganka Bineva-Todd",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Stefano Jaconi",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
+        "author_name": "Berta Canal",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Marcel Meury",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "Joseph F Curran",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Exequiel Dellota",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "Tom D Deegan",
+        "author_inst": "The University of Dundee"
       },
       {
-        "author_name": "Elisabetta Cameroni",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
+        "author_name": "John FX Diffley",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Tristan I Croll",
-        "author_inst": "Cambridge Institute for Medical Research, Department of Haematology, University of Cambridge, Cambridge, CB2 0XY, UK"
+        "author_name": "Ryo Fujisawa",
+        "author_inst": "The University of Dundee"
       },
       {
-        "author_name": "Jay C Nix",
-        "author_inst": "Molecular Biology Consortium, Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA"
+        "author_name": "Michael Howell",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Colin Havenar-Daughton",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "Dhira Joshi",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Amalio Telenti",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "Karim Labib",
+        "author_inst": "The University of Dundee"
       },
       {
-        "author_name": "Florian A Lempp",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "Chew Theng Lim",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Matteo Samuele Pizzuto",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
+        "author_name": "Jennifer Milligan",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "John D Chodera",
-        "author_inst": "Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"
+        "author_name": "Hema Nagaraj",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Christy M Hebner",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "George Papageorgiou",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Sean PJ Whelan",
-        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA"
+        "author_name": "Christelle Soudy",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Herbert W Virgin",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA; Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO 63110, USA; D"
+        "author_name": "Kang Wei Tan",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "David Veesler",
-        "author_inst": "Department of Biochemistry, University of Washington, Seattle, WA 98195, USA"
+        "author_name": "Rachel Ulferts",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Davide Corti",
-        "author_inst": "Humabs BioMed SA, a subsidiary of Vir Biotechnology, 6500 Bellinzona, Switzerland"
+        "author_name": "Florian Weissmann",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Jesse D Bloom",
-        "author_inst": "Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Department of Genome Sciences, University of Washington, Seattle, WA 98"
+        "author_name": "Mary Wu",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Gyorgy Snell",
-        "author_inst": "Vir Biotechnology, San Francisco, CA 94158, USA"
+        "author_name": "Theresa U Zeisner",
+        "author_inst": "The Francis Crick Institute"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "microbiology"
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2021.04.07.438807",
@@ -782814,79 +786209,51 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.01.21254798",
-    "rel_title": "Female-male differences in COVID vaccine adverse events have precedence in seasonal flu shots: a potential link to sex-associated baseline gene expression patterns",
+    "rel_doi": "10.1101/2021.04.05.21254897",
+    "rel_title": "No Evidence of Infectious SARS-CoV-2 in Human Milk: Analysis of a Cohort of 110 Lactating Women",
     "rel_date": "2021-04-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254798",
-    "rel_abs": "Nearly 150 million doses of FDA-authorized COVID vaccines have been administered in the United States. Sex-based differences of adverse events remain poorly understood, mandating the need for real-world investigation from Electronic Health Records (EHRs) and broader epidemiological data sets. Based on an augmented curation of EHR clinical notes of 31,064 COVID-vaccinated individuals (19,321 females and 11,743 males) in the Mayo Clinic, we find that nausea and vomiting were documented significantly more frequently in females than males after both vaccine doses (nausea: RRDose 1 = 1.67, pDose 1 <0.001, RRDose 2 = 2.2, pDose 1 < 0.001; vomiting: RRDose 1 = 1.58, pDose 1 < 0.001, RRDose 2 = 1.88, pDose 1 = 3.4x10-2). Conversely, fever, fatigue, and lymphadenopathy were more common in males after the first dose vaccination (fever RR = 0.62; p = 8.65x10-3; fatigue RR = 0.86, p = 2.89x10-2; lymphadenopathy RR = 0.61, p = 3.45x10-3). Analysis of the Vaccine Adverse Events Reporting System (VAERS) database further confirms that nausea comprises a larger fraction of total reports among females than males (RR: 1.58; p<0.001), while fever comprises a larger fraction of total reports among males than females (RR: 0.84; p<0.001). Importantly, increased reporting of nausea and fever among females and males, respectively, is also observed for prior influenza vaccines in the VAERS database, establishing that these differences are not unique to the recently developed COVID-19 vaccines. Investigating the mechanistic basis underlying these clinical findings, an analysis of bulk RNA-sequencing data from 12,158 human blood samples (8626 female, 3532 male) reveals 85 genes that are not only significantly different in their gene expression between females and males at baseline, but also have established literature-based associations to COVID-19 as well as the vaccine-related adverse events of clinical consequence. The NLRP3 inflammasome and the NR3C1 glucocorticoid receptor emerge as particularly promising baseline links to sex-associated vaccine adverse events, warranting targeted investigation of these signaling pathways and associated cell types. From a public health standpoint, our clinical findings shall aid in educating patients on the sex-associated risks they should expect for COVID-19 vaccines and also promote better clinical management of vaccine-associated adverse events.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21254897",
+    "rel_abs": "BackgroundSARS-CoV-2 infections of infants and toddlers are usually mild but can result in life-threatening disease. SARS-CoV-2 RNA been detected in the breast milk of lactating women, but the potential role of breastfeeding in transmission to infants has remained uncertain.\n\nMethodsBreast milk specimens were examined for the presence of the virus by RT-PCR and/or culture. Specimens that contained viral RNA (vRNA) were examined for the presence of subgenomic coronavirus RNA (sgRNA), a putative marker of infectivity. Culture methods were used to determine the thermal stability of SARS-CoV-2 in human milk.\n\nResultsBreast milk samples from 110 women (65 confirmed with a SARS-CoV-2 diagnostic test, 36 with symptoms but without tests, and 9 with symptoms but a negative SARS-CoV-2 diagnostic test) were tested by RT-PCR (285 samples) and/or viral culture (160 samples). Although vRNA of SARS-CoV-2 was detected in the milk of 7 of 110 (6%) women with either a confirmed infection or symptomatic illness, and in 6 of 65 (9%) of women with a positive SARS-CoV-2 diagnostic test, virus was not detected in any culture. None of the 7 milk specimens with detectable vRNA contained sgRNA. Notably, when artificially added to human milk in control experiments, infectious SARS-CoV-2 could be cultured despite several freeze-thaw cycles, as occurs in the storage and usage of human milk.\n\nConclusionsSARS-CoV-2 RNA can be found infrequently in the breastmilk of women with recent infection, but we found no evidence that breastmilk contains infectious virus or that breastfeeding represents a risk factor for transmission of infection to infants.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSSARS-CoV-2 RNA has been detected in a small number of human milk samples collected from recently infected women. The role of breastfeeding in transmission of the virus to infants has remained uncertain due to the small number of specimens analyzed in any study published thus far.\n\nFindingsIn a total study group of 110 women, SARS-CoV-2 RNA was detected in milk from 6 of 65 women (9.2%) with recent confirmed infection. Neither infectious virus nor subgenomic RNA (a marker of virus infectivity) were detected in any of the samples.\n\nMeaningWe found no evidence that infectious SARS-CoV-2 is present milk from recently infected women, even if SARS-CoV-2 PCR tests are positive, providing reassurance of the safety of breastfeeding.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "AJ Venkatakrishnan",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Praveen Kumar-M",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Eli Silvert",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Enrique Garcia-Rivera",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Mariola Szenk",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Rohit Suratekar",
-        "author_inst": "nference Labs"
-      },
-      {
-        "author_name": "Patrick Lenehan",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Emily Lindemer",
-        "author_inst": "nference"
+        "author_name": "Paul Krogstad",
+        "author_inst": "David Geffen School of Medicine at UCLA"
       },
       {
-        "author_name": "John C OHoro",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Deisy Contreras",
+        "author_inst": "David Geffen School of Medicine at UCLA"
       },
       {
-        "author_name": "Amy W Williams",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Hwee Ng",
+        "author_inst": "David Geffen School of Medicine at UCLA"
       },
       {
-        "author_name": "Andrew D Badley",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Nicole Tobin",
+        "author_inst": "David Geffen School of Medicine at UCLA"
       },
       {
-        "author_name": "Abinash Virk",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Christina Chambers",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "Melanie D Swift",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Kerri Bertrand",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Gregory J Gores",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Lars Bode",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Venky Soundararajan",
-        "author_inst": "nference"
+        "author_name": "Grace Aldrovandi",
+        "author_inst": "David Geffen School of Medicine at UCLA"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2021.04.03.21254639",
@@ -784620,53 +787987,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.04.02.21254809",
-    "rel_title": "Risk factors for severity on admission and the disease progression during hospitalization in a large cohort of COVID-19 patients in Japan",
+    "rel_doi": "10.1101/2021.04.01.21254755",
+    "rel_title": "Rapid screening for variants of concern in routine SARS-CoV-2 PCR diagnostics",
     "rel_date": "2021-04-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.02.21254809",
-    "rel_abs": "ObjectivesTo investigate the risk factors contributing to severity on admission. Additionally, risk factors on worst severity and fatality were studied. Moreover, factors were compared based on three points: early severity, worst severity, and fatality.\n\nDesignA observational cohort study utilizing data entered in a Japan nationwide COVID-19 inpatient registry, COVIREGI-JP.\n\nSettingAs of August 31, 2020, 7,546 cases from 780 facilities have been registered. Participating facilities cover a wide range of hospitals where COVID-19 patients are admitted in Japan.\n\nParticipantsParticipants who had a positive test result on any applicable SARS-CoV-2 diagnostic tests, and were admitted to participating healthcare facilities. A total of 3,829 cases were identified from January 16 to May 31, 2020, of which 3,376 cases were included in this study.\n\nPrimary and secondary outcoe measuresPrimary outcome was severe or non-severe on admission, determined by the requirement of mechanical ventilation or oxygen therapy, SpO2, or respiratory rate. Secondary outcome was the worst severity during hospitalization, judged by the requirement of oxygen and/or IMV/ECMO.\n\nResultsRisk factors for severity on admission were older age, male, cardiovascular disease, chronic respiratory disease, diabetes, obesity, and hypertension. Cerebrovascular disease, liver disease, renal disease or dialysis, solid tumor, and hyperlipidemia did not influence severity on admission; however it influenced worst severity. Fatality rates for obesity, hypertension, and hyperlipidemia were relatively lower.\n\nConclusionsThis study segregated the comorbidities driving severity and death. It is possible that risk factors for severity on admission, worst severity, and fatality are not consistent and may be propelled by different factors. Specifically, while hypertension, hyperlipidemia, and obesity had major effect on worst severity, their impact was mild on fatality in the Japanese population. Some studies contradict our results; therefore, detailed analyses, considering in-hospital treatments, are needed for validation.\n\nTrial registrationUMIN000039873. https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000045453\n\nStrengths and limitations of this studyO_LIIn this article, we studied the disease progression of COVID-19, by comparing the risk factors on three points: early severity, worst severity, and fatality.\nC_LIO_LIOur results are useful from a public health perspective, as we provide risk factors for predicting the severity on admission and disease progression from patients background factors.\nC_LIO_LIThis study pointed out the possibility that risk factors of the severity on admission, worst severity, and fatality are not consistent and may be propelled by different factors.\nC_LIO_LIOur data were collected from hundreds of healthcare facilities; thus data accuracy may be questionable.\nC_LIO_LIAlso, treatment type, dosage, duration, and combination varied immensely across the facilities and we did not consider treatments prior to and during hospitalization in the analysis.\nC_LI",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254755",
+    "rel_abs": "The emerging spread of variants of concern (VOC) of SARS-CoV-2 has been noted in several countries worldwide during last months. VOCs associated with increased transmissibility and morality. Sequencing is the gold standard for investigation of variants, however it is expensive and time-consuming. S-dropout routine monitoring in combination with VOC screening by RT-PCR is a useful tool for VOC surveillance.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Mari Terada",
-        "author_inst": "National Center for Global Health and Medicine"
-      },
-      {
-        "author_name": "Hiroshi Ohtsu",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Paul Naaber",
+        "author_inst": "SYNLAB Estonia"
       },
       {
-        "author_name": "Sho Saito",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Andrio Lahesaare",
+        "author_inst": "SYNLAB Estonia"
       },
       {
-        "author_name": "Kayoko Hayakawa",
-        "author_inst": "National Center for Global Health and Medicine"
-      },
-      {
-        "author_name": "Shinya Tsuzuki",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Laura Truu",
+        "author_inst": "SYNLAB Estonia"
       },
       {
-        "author_name": "Yusuke Asai",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Andres Soojarv",
+        "author_inst": "SYNLAB Estonia"
       },
       {
-        "author_name": "Nobuaki Matsunaga",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Ainika Adamson",
+        "author_inst": "SYNLAB Estonia"
       },
       {
-        "author_name": "Satoshi Kutsuna",
-        "author_inst": "National Centre for Global Health and Medicine"
+        "author_name": "Kaido Beljaev",
+        "author_inst": "SYNLAB Estonia"
       },
       {
-        "author_name": "Wataru Sugiura",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Rainar Aamisepp",
+        "author_inst": "SYNLAB Estonia"
       },
       {
-        "author_name": "Norio Ohmagari",
-        "author_inst": "National Center for Global Health and Medicine"
+        "author_name": "Kaspar Ratnik",
+        "author_inst": "SYNLAB Estonia"
       }
     ],
     "version": "1",
@@ -786398,31 +789757,39 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.04.05.438465",
-    "rel_title": "The Up state of the SARS-COV-2 Spike homotrimer favors an increased virulence for new variants",
+    "rel_doi": "10.1101/2021.04.05.438500",
+    "rel_title": "An Autoantigen-ome from HS-Sultan B-Lymphoblasts Offers a Molecular Map for Investigating Autoimmune Sequelae of COVID-19",
     "rel_date": "2021-04-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.05.438465",
-    "rel_abs": "The COVID-19 pandemic has spread widely worldwide. However, as soon as the vaccines were released - the only scientifically verified and efficient therapeutic option thus far - a few mutations combined into variants of SARS-CoV-2 that are more transmissible and virulent emerged raising doubts about their efficiency. Therefore, this work aims to explain possible molecular mechanisms responsible for the increased transmissibility and the increased rate of hospitalizations related to the new variants. A combination of theoretical methods was employed. Constant-pH Monte Carlo simulations were carried out to quantify the stability of several spike trimeric structures at different conformational states and the free energy of interactions between the receptor binding domain (RBD) and Angiotensin Converting Enzyme 2 (ACE2) for the most worrying variants. Electrostatic epitopes were mapped using the PROCEEDpKa method. These analyses showed that the increased virulence is more likely to be due to the improved stability to the S trimer in the opened state (the one in which the virus can interact with the cellular receptor ACE2) than due to alterations in the complexation RBD-ACE2, once the increased observed in the free energy values is small. Conversely, the South African variant (B.1.351), when compared with the wild type SARS-CoV-2, is much more stable in the opened state (either with one or two RBDs in the up position) than in the closed state (with the three RBDs in the down position). Such results contribute to the understanding of the natural history of disease and also to indicate possible strategies to both develop new therapeutic molecules and to adjust the vaccine doses for a higher production of B cells antibodies.\n\nGraphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.05.438500",
+    "rel_abs": "To understand how COVID-19 may induce autoimmune diseases, we have been compiling an atlas of COVID-autoantigens (autoAgs). Using dermatan sulfate (DS) affinity enrichment of autoantigenic proteins extracted from HS-Sultan lymphoblasts, we identified 362 DS-affinity proteins, of which at least 201 (56%) are confirmed autoAgs. Comparison with available multi-omic COVID data shows that 315 (87%) of the 362 proteins are affected in SARS-CoV-2 infection via altered expression, interaction with viral components, or modification by phosphorylation or ubiquitination, at least 186 (59%) of which are known autoAgs. These proteins are associated with gene expression, mRNA processing, mRNA splicing, translation, protein folding, vesicles, and chromosome organization. Numerous nuclear autoAgs were identified, including both classical ANAs and ENAs of systemic autoimmune diseases and unique autoAgs involved in the DNA replication fork, mitotic cell cycle, or telomerase maintenance. We also identified many uncommon autoAgs involved in nucleic acid and peptide biosynthesis and nucleocytoplasmic transport, such as aminoacyl-tRNA synthetases. In addition, this study found autoAgs that potentially interact with multiple SARS-CoV-2 Nsp and Orf components, including CCT/TriC chaperonin, insulin degrading enzyme, platelet-activating factor acetylhydrolase, and the ezrin-moesin-radixin family. Furthermore, B-cell-specific IgM-associated ER complex (including MBZ1, BiP, heat shock proteins, and protein disulfide-isomerases) is enriched by DS-affinity and up-regulated in B-cells of COVID-19 patients, and a similar IgH-associated ER complex was also identified in autoreactive pre-B1 cells in our previous study, which suggests a role of autoreactive B1 cells in COVID-19 that merits further investigation. In summary, this study demonstrates that virally infected cells are characterized by alterations of proteins with propensity to become autoAgs, thereby providing a possible explanation for infection-induced autoimmunity. The COVID autoantigen-ome provides a valuable molecular resource and map for investigation of COVID-related autoimmune sequelae and considerations for vaccine design.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Carolina Correa Giron",
-        "author_inst": "Universidade Federal do Triangulo Mineiro"
+        "author_name": "Julia Y. Wang",
+        "author_inst": "Curandis"
       },
       {
-        "author_name": "Aatto Laaksonen",
-        "author_inst": "Stockholm University"
+        "author_name": "Wei Zhang",
+        "author_inst": "Guizhou Medical University"
       },
       {
-        "author_name": "Fernando Luis Barroso da Silva",
-        "author_inst": "University of Sao Paulo"
+        "author_name": "Victor B. Roehrl",
+        "author_inst": "Curandis"
+      },
+      {
+        "author_name": "Michael W. Roehrl",
+        "author_inst": "Curandis"
+      },
+      {
+        "author_name": "Michael H. Roehrl",
+        "author_inst": "Memorial Sloan Kettering Cancer Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.03.30.21254604",
@@ -788268,67 +791635,31 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.06.438634",
-    "rel_title": "Plasma microbiome in COVID-19 subjects: an indicator of gut barrier defects and dysbiosis",
+    "rel_doi": "10.1101/2021.04.05.438537",
+    "rel_title": "High-Potency Polypeptide-based Interference for Coronavirus Spike Glycoproteins",
     "rel_date": "2021-04-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.06.438634",
-    "rel_abs": "The gut is a well-established route of infection and target for viral damage by SARS-CoV-2. This is supported by the clinical observation that about half of COVID-19 patients exhibit gastrointestinal (GI) symptoms. We asked whether the analysis of plasma could provide insight into gut barrier dysfunction in patients with COVID-19 infection. Plasma samples of COVID-19 patients (n=30) and healthy control (n=16) were collected during hospitalization. Plasma microbiome was analyzed using 16S rRNA sequencing, metatranscriptomic analysis, and gut permeability markers including FABP-2, PGN and LPS in both patient cohorts. Almost 65% (9 out 14) COVID-19 patients showed abnormal presence of gut microbes in their bloodstream. Plasma samples contained predominately Proteobacteria, Firmicutes, and Actinobacteria. The abundance of gram-negative bacteria (Acinetobacter, Nitrospirillum, Cupriavidus, Pseudomonas, Aquabacterium, Burkholderia, Caballeronia, Parabhurkholderia, Bravibacterium, and Sphingomonas) was higher than the gram-positive bacteria (Staphylococcus and Lactobacillus) in COVID-19 subjects. The levels of plasma gut permeability markers FABP2 (1282{+/-}199.6 vs 838.1{+/-}91.33; p=0.0757), PGN (34.64{+/-}3.178 vs 17.53{+/-}2.12; p<0.0001), and LPS (405.5{+/-}48.37 vs 249.6{+/-}17.06; p=0.0049) were higher in COVID-19 patients compared to healthy subjects. These findings support that the intestine may represent a source for bacteremia and may contribute to worsening COVID-19 outcomes. Therapies targeting the gut and prevention of gut barrier defects may represent a strategy to improve outcomes in COVID-19 patients.",
-    "rel_num_authors": 12,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.05.438537",
+    "rel_abs": "Specific manipulation of proteins post-translationally remains difficult. Here we report results of a general approach that uses a partial sequence of a protein to efficiently modulate the expression level of the native protein. When applied to coronavirus, human immunodeficiency virus, Ebolavirus, respiratory syncytial virus and influenza virus, polypeptides containing highly conserved regions of the viral glycoproteins potently diminished expression of the respective native proteins. In the cases of coronavirus and influenza virus where multiple strains were tested, the polypeptides were equally effective against glycoproteins of other coronavirus and influenza strains with sequence identity as low as 27%, underscoring their high insensitivity to mutations. Thus, this method provides a platform for developing high-efficacy broad-spectrum anti-viral inhibitors, as well as a new way to alter expression of essentially any systems post-translationally.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Ram Prasad",
-        "author_inst": "University of Alabama at Birmingham"
-      },
-      {
-        "author_name": "Michael John Patton",
-        "author_inst": "University of Alabama at Birmingham"
-      },
-      {
-        "author_name": "Jason L Floyd",
-        "author_inst": "University of Alabama at Birmingham"
-      },
-      {
-        "author_name": "Cristiano P Vieira",
-        "author_inst": "Univeristy of Alabama at Birmingham"
-      },
-      {
-        "author_name": "Seth D. Fortmann",
-        "author_inst": "University of Alabama at Birmingham"
-      },
-      {
-        "author_name": "Mariana DuPont",
-        "author_inst": "University of Alabama at Birmingham"
-      },
-      {
-        "author_name": "Angie Harbour",
-        "author_inst": "University of Alabama at Birmingham"
-      },
-      {
-        "author_name": "Jeremy R Chen See",
-        "author_inst": "WrightLabs LLC"
-      },
-      {
-        "author_name": "Justin Wright",
-        "author_inst": "Wright Labs LLC"
-      },
-      {
-        "author_name": "Regina Lamendella",
-        "author_inst": "Juniata College"
+        "author_name": "Jianpeng Ma",
+        "author_inst": "Baylor College of Medicine"
       },
       {
-        "author_name": "Bruce R. Stevens",
-        "author_inst": "University of Florida College of Medicine"
+        "author_name": "Adam Campos Acevedo",
+        "author_inst": "Baylor College of Medicine"
       },
       {
-        "author_name": "Maria B. Grant",
-        "author_inst": "University of Alabama- Birmingham"
+        "author_name": "Qinghua Wang",
+        "author_inst": "Baylor College of Medicine"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2021.04.06.438630",
@@ -790290,119 +793621,23 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.04.02.438288",
-    "rel_title": "An emerging SARS-CoV-2 mutant evading cellular immunity and increasing viral infectivity",
+    "rel_doi": "10.1101/2021.04.04.438420",
+    "rel_title": "Rational Selection of PCR Primer/Probe Design Sites for SARS-CoV-2",
     "rel_date": "2021-04-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.438288",
-    "rel_abs": "During the current SARS-CoV-2 pandemic that is devastating the modern societies worldwide, many variants that naturally acquire multiple mutations have emerged. Emerging mutations can affect viral properties such as infectivity and immune resistance. Although the sensitivity of naturally occurring SARS-CoV-2 variants to humoral immunity has recently been investigated, that to human leukocyte antigen (HLA)-restricted cellular immunity remains unaddressed. Here we demonstrate that two recently emerging mutants in the receptor binding domain of the SARS-CoV-2 spike protein, L452R (in B.1.427/429) and Y453F (in B.1.298), can escape from the HLA-24-restricted cellular immunity. These mutations reinforce the affinity to viral receptor ACE2, and notably, the L452R mutation increases protein stability, viral infectivity, and potentially promotes viral replication. Our data suggest that the HLA-restricted cellular immunity potentially affects the evolution of viral phenotypes, and the escape from cellular immunity can be a further threat of the SARS-CoV-2 pandemic.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC=\"FIGDIR/small/438288v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (45K):\norg.highwire.dtl.DTLVardef@153428forg.highwire.dtl.DTLVardef@136ca5aorg.highwire.dtl.DTLVardef@1ee490org.highwire.dtl.DTLVardef@2fe478_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
-    "rel_num_authors": 25,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.04.438420",
+    "rel_abs": "Various reports of decreased analytical sensitivities of real-time PCR-based detection of Coronavirus Disease 2019 (COVID-19) have been associated with occurrence of mutations in the target area of primer/probe binding. Knowledge about propensities of different genes to undergo mutation can inform researchers to select optimal genes to target for the qPCR design. We analyzed supplementary data from over 45 thousand SARS-CoV-2 genomes provided by Mercatelli et al to calculate the unique and prevalent mutations in different genes of SARS-CoV-2. We found that non-structural proteins in the ORF1ab region were more conserved compared to structural genes. Further factors which need to be relied upon for proper selection of genes for qPCR design are discussed.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Chihiro Motozono",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Mako Toyoda",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Jiri Zahradnik",
-        "author_inst": "Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Terumasa Ikeda",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Akatsuki Saito",
-        "author_inst": "University of Miyazaki"
-      },
-      {
-        "author_name": "Toong Seng Tan",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Isaac Ngare",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Hesham Nasser",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Izumi Kimura",
-        "author_inst": "The University of Tokyo"
-      },
-      {
-        "author_name": "Keiya Uriu",
-        "author_inst": "The University of Tokyo"
-      },
-      {
-        "author_name": "Yusuke Kosugi",
-        "author_inst": "The University of Tokyo"
-      },
-      {
-        "author_name": "Shiho Torii",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Akiko Yonekawa",
-        "author_inst": "Kyushu University"
-      },
-      {
-        "author_name": "Nobuyuki Shimono",
-        "author_inst": "Kyushu University"
-      },
-      {
-        "author_name": "Yoji Nagasaki",
-        "author_inst": "Kyushu Medical Center"
-      },
-      {
-        "author_name": "Rumi Minami",
-        "author_inst": "Kyushu Medical Center"
-      },
-      {
-        "author_name": "Takashi Toya",
-        "author_inst": "Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital"
-      },
-      {
-        "author_name": "Noritaka Sekiya",
-        "author_inst": "Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital"
-      },
-      {
-        "author_name": "Takasuke Fukuhara",
-        "author_inst": "Hokkaido University"
-      },
-      {
-        "author_name": "Yoshiharu Matsuura",
-        "author_inst": "Osaka University"
-      },
-      {
-        "author_name": "Gideon Schreiber",
-        "author_inst": "Weizmann Institute of Science"
-      },
-      {
-        "author_name": "- The Genotype to Phenotype Japan (G2P-Japan) consortium",
-        "author_inst": "-"
-      },
-      {
-        "author_name": "So Nakagawa",
-        "author_inst": "Tokai University School of Medicine"
-      },
-      {
-        "author_name": "Takamasa Ueno",
-        "author_inst": "Kumamoto University"
-      },
-      {
-        "author_name": "Kei Sato",
-        "author_inst": "Institute of Medical Science, The University of Tokyo"
+        "author_name": "Divya RSJB Rana",
+        "author_inst": "The Leprosy Mission Nepal"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2021.03.29.21254343",
@@ -792232,25 +795467,49 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.04.02.438155",
-    "rel_title": "An immunoinformatics approach to study the epitopes contributed by Nsp13 of SARS-CoV-2",
+    "rel_doi": "10.1101/2021.04.02.438204",
+    "rel_title": "Discovery and in-vitro evaluation of potent SARS-CoV-2 entry inhibitors",
     "rel_date": "2021-04-02",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.438155",
-    "rel_abs": "The on-going coronavirus disease-19 (COVID-19) pandemic caused by SARS-CoV-2 has infected hundreds of millions of people and killed more than two million people worldwide. Currently, there are no effective drugs available for treating SARS-CoV-2 infections; however, vaccines are now being administered worldwide to control this virus. In this study, we have studied SARS-CoV-2 helicase, Nsp13, which is critical for viral replication. We compared the Nsp13 sequences reported from India with the first reported sequence from Wuhan province, China to identify and characterize the mutations occurring in this protein. To correlate the functional impact of these mutations, we characterised the most prominent B cell and T cell epitopes contributed by Nsp13. Our data revealed twenty-one epitopes, which exhibited high antigenicity, stability and interactions with MHC class-I and class-II molecules. Subsequently, the physiochemical properties of these epitopes were also analysed. Furthermore, several of these Nsp13 epitopes harbour mutations, which were further characterised by secondary structure and per-residue disorderness, stability and dynamicity predictions. Altogether, we report the candidate epitopes of Nsp13 that may help the scientific community to understand the evolution of SARS-CoV-2 variants and their probable implications.",
-    "rel_num_authors": 2,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.438204",
+    "rel_abs": "SARS-CoV-2 infection initiates with the attachment of spike protein to the ACE2 receptor. While vaccines have been developed, no SARS-CoV-2 specific small molecule inhibitors have been approved. Herein, utilizing the crystal structure of the ACE2/Spike receptor binding domain (S-RBD) complex in computer-aided drug design (CADD) approach, we docked [~]8 million compounds within the pockets residing at S-RBD/ACE2 interface. Five best hits depending on the docking score, were selected and tested for their in vitro efficacy to block SARS-CoV-2 replication. Of these, two compounds (MU-UNMC-1 and MU-UNMC-2) blocked SARS-CoV-2 replication at sub-micromolar IC50 in human bronchial epithelial cells (UNCN1T) and Vero cells. Furthermore, MU-UNMC-2 was highly potent in blocking the virus entry by using pseudoviral particles expressing SARS-CoV-2 spike. Finally, we found that MU-UNMC-2 is highly synergistic with remdesivir (RDV), suggesting that minimal amounts are needed when used in combination with RDV, and has the potential to develop as a potential entry inhibitor for COVID-19.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Sushant Kumar",
-        "author_inst": "Patna University"
+        "author_name": "Arpan Acharya",
+        "author_inst": "University of Nebraska Medical Center"
       },
       {
-        "author_name": "Gajendra Kumar Azad",
-        "author_inst": "Patna University"
+        "author_name": "Kabita Pandey",
+        "author_inst": "University of Nebraska Medical Center"
+      },
+      {
+        "author_name": "Michellie Thurman",
+        "author_inst": "University of Nebraska Medical Center"
+      },
+      {
+        "author_name": "Elizabeth Klug",
+        "author_inst": "University of Nebraska Medical Center"
+      },
+      {
+        "author_name": "Jay Trivedi",
+        "author_inst": "University of Nebraska Medical Center"
+      },
+      {
+        "author_name": "Christian L Lorson",
+        "author_inst": "University of Missouri, Columbia"
+      },
+      {
+        "author_name": "Kamlendra Singh",
+        "author_inst": "University of Missouri"
+      },
+      {
+        "author_name": "Siddappa N Byrareddy",
+        "author_inst": "University of Nebraska Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
     "category": "molecular biology"
   },
@@ -794362,83 +797621,59 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.03.28.21254496",
-    "rel_title": "SARS-CoV-2 infections in children and adolescents with rheumatic musculoskeletal diseases: data from the National Pediatric Rheumatology Database in Germany",
+    "rel_doi": "10.1101/2021.03.29.21254538",
+    "rel_title": "Half year longitudinal seroprevalence of SARS-CoV-2-antibodies and rule compliance in German hospital employees",
     "rel_date": "2021-03-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.28.21254496",
-    "rel_abs": "ObjectivesDue to their underlying disease as well as therapeutic immunosuppression, children and adolescents with rheumatic and musculoskeletal diseases (RMD) may be at higher risk for a severe course or worse outcome of COVID-19, and SARS-CoV2 infection may trigger a flare of the RMD. To address these issues, a specific SARS-CoV-2 questionnaire was implemented in the National Pediatric Rheumatology Database (NPRD) in Germany.\n\nMethodsDemographic, clinical and treatment data from juvenile patients with RMD as well as data about SARS-CoV-2 infection like test date and method, clinical characteristics, disease course, outcome and impact on the disease activity of the RMD documented on this questionnaire were analyzed.\n\nResultsFrom April 17th, 2020, to February 14th, 2021, data were collected from 79 patients (53% female) with RMD with median age of 14 years, diagnosed with juvenile idiopathic arthritis (57%), autoinflammatory (23%) and connective tissue disease (8%). Sixty-one patients (77%) received disease-modifying antirheumatic drugs (DMARDs), 43% biologic DMARDs, and 9% systemic glucocorticoids. Sixty patients (76%) developed symptoms of COVID-19. Disease severity was mild and outcome was good in the majority of patients. Two patients were hospitalized, one of whom required intensive care and died of cardiorespiratory failure. In 84% of SARS-CoV-2-positive patients, no relevant increase in disease activity of the RMD was observed.\n\nConclusionsIn our cohort, COVID-19 in juvenile patients with RMD under various medications was mild with good outcome in the majority of cases. SARS-CoV-2 infection does not appear to have a relevant impact on disease activity of the underlying condition.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.29.21254538",
+    "rel_abs": "IntroductionCOVID-19, caused by SARS-CoV-2, is an occupational health risk especially for healthcare employees. This study was designed to determine the longitudinal seroprevalence of specific immunglobolin-G (IgG)-antibodies in employees in a hospital setting.\n\nMethodsAll employees including healthcare and non-healthcare workers in a secondary care hospital were invited to participate in this single-center study. After an initial screening, a 6 months follow-up was done which included serological examination for SARS-CoV-2-IgG-antibodies and a questionnaire for self-reported symptoms, self-perception and thoughts about the local and national hygiene and pandemic plans.\n\nResultsThe seroprevalence of SARS-CoV-2-IgG-antibodies was 0.74% among 406 hospital employees (95% confidence interval) (0.75% in healthcare workers, 0.72% in non-healthcare workers), initially recruited in April 2020, in their follow-up blood specimen in October 2020.\n\nIn this study, 30.54% of the participants reported using the official German corona mobile application and the majority were content with the local and national rules in relation to Coronavirus restrictions.\n\nDiscussionAt the 6 months follow-up, the 0.74% seroprevalence was below the reported seroprevalence of 1.35% in the general German population. The prevalence in healthcare workers in direct patient care compared with those without direct patient contact did not differ significantly.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Claudia Sengler",
-        "author_inst": "German Rheumatism Research Center, Epidemiology Unit, Berlin, Germany"
-      },
-      {
-        "author_name": "Sascha Eulert",
-        "author_inst": "German Rheumatism Research Center, Epidemiology Unit, Berlin, Germany"
-      },
-      {
-        "author_name": "Martina Niewerth",
-        "author_inst": "German Rheumatism Research Center, Epidemiology Unit, Berlin, Germany"
-      },
-      {
-        "author_name": "Kirsten Minden",
-        "author_inst": "German Rheumatism Research Center, Epidemiology Unit, Berlin, Germany"
-      },
-      {
-        "author_name": "Gerd Horneff",
-        "author_inst": "Asklepios Klinik St. Augustin, Allgemeine Kinder- und Jugendmedizin, Sankt Augustin, Germany"
-      },
-      {
-        "author_name": "Jasmin B Kuemmerle-Deschner",
-        "author_inst": "Tuebingen University Hospital, Department of Pediatric and Adolescent Medicine, Tuebingen, Germany"
-      },
-      {
-        "author_name": "Caroline Siemer",
-        "author_inst": "Deutsches Zentrum fuer Kinder- und Jugendrheumatologie, Garmisch-Partenkirchen, Germany"
+        "author_name": "Jonas Herzberg",
+        "author_inst": "Department of Surgery, Krankenhaus Reinbek St. Adolf-Stift, Reinbek, Germany"
       },
       {
-        "author_name": "Rainer Berendes",
-        "author_inst": "Kinderkrankenhaus St. Marien, Landshut, Germany"
+        "author_name": "Tanja Vollmer",
+        "author_inst": "Institute for Laboratory and Transfusion Medicine, Heart and Diabetes Centre NRW, Bad Oeynhausen, Ruhr University Bochum, Bochum, Germany"
       },
       {
-        "author_name": "Hermann Girschick",
-        "author_inst": "Krankenhaus im Friedrichshain, Klinik fuer Kinder- und Jugendmedizin, Berlin, Germany"
+        "author_name": "Bastian Fischer",
+        "author_inst": "Institute for Laboratory and Transfusion Medicine, Heart and Diabetes Centre NRW, Bad Oeynhausen, Ruhr University Bochum, Bochum, Germany"
       },
       {
-        "author_name": "Regina Huehn",
-        "author_inst": "Universitaetsklinikum Halle (Saale), Klinik fuer Kinder- und Jugendmedizin, Haale (Saale), Germany"
+        "author_name": "Heiko Becher",
+        "author_inst": "University Medical Center Hamburg-Eppendorf, Hamburg, Germany"
       },
       {
-        "author_name": "Michael Borte",
-        "author_inst": "Klinikum St. Georg, Klinik fuer Kinder- und Jugendmedizin, Leipzig, Germany"
+        "author_name": "Ann-Kristin Becker",
+        "author_inst": "Asklepios Klinik Harburg, Hamburg, Germany"
       },
       {
-        "author_name": "Anton Hospach",
-        "author_inst": "Olgahospital and Women`s Clinic, Paediatrie 2 - Allgemeine und spezielle Paediatrie, Stuttgart, Germany"
+        "author_name": "Hany Sahly",
+        "author_inst": "Labor Lademannbogen MVZ Hamburg, Hamburg, Germany"
       },
       {
-        "author_name": "Wolfgang Emminger",
-        "author_inst": "Universitaetskinderklinik Wien, Wien, Austria"
+        "author_name": "Human Honarpisheh",
+        "author_inst": "Department of Surgery, Krankenhaus Reinbek St. Adolf-Stift, Reinbek, Germany"
       },
       {
-        "author_name": "Jakob Peter Armann",
-        "author_inst": "University Hospital and Medical Faculty Carl Gustav Carus, Technische Uni"
+        "author_name": "Salman Yousuf Guraya",
+        "author_inst": "Clinical Sciences Department, College of Medicine, University of Sharjah"
       },
       {
-        "author_name": "Ariane Klein",
-        "author_inst": "Asklepios Klinik St. Augustin, Allgemeine Kinder- und Jugendmedizin, Sankt Augustin, Germany"
+        "author_name": "Tim Strate",
+        "author_inst": "Department of Surgery, Krankenhaus Reinbek St. Adolf-Stift, Reinbek, Germany"
       },
       {
-        "author_name": "Tilmann Kallinich",
-        "author_inst": "Charite - Universitaetsmedizin Berlin, Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Berlin, Germany"
+        "author_name": "Cornelius Knabbe",
+        "author_inst": "Institute for Laboratory and Transfusion Medicine, Heart and Diabetes Centre NRW, Bad Oeynhausen, Ruhr University Bochum, Bochum, Germany"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "rheumatology"
+    "category": "occupational and environmental health"
   },
   {
     "rel_doi": "10.1101/2021.03.29.21254529",
@@ -795912,77 +799147,25 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.03.29.21254590",
-    "rel_title": "Use of portable air cleaners to reduce aerosol transmission on a hospital COVID-19 ward",
+    "rel_doi": "10.1101/2021.03.29.21254509",
+    "rel_title": "Genetic associations with severe COVID-19",
     "rel_date": "2021-03-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.29.21254590",
-    "rel_abs": "ObjectiveTo study the airflow, transmission and clearance of aerosols in the clinical spaces of a hospital ward that had been used to care for patients with COVID-19, and to examine the impact of portable air cleaners on aerosol clearance.\n\nDesignObservational study\n\nSettingA single ward of a tertiary public hospital in Melbourne Australia\n\nInterventionGlycerine-based aerosol was used as a surrogate for respiratory aerosols. The transmission of aerosols from a single patient room into corridors and a nurses station in the ward was measured. The rate of clearance of aerosols was measured over time from the patient room, nurses station and ward corridors with and without air cleaners (also called portable HEPA filters).\n\nResultsAerosols rapidly travelled from the patient room into other parts of the ward. Air cleaners were effective in increasing the clearance of aerosols from the air in clinical spaces and reducing their spread to other areas. With two small domestic air cleaners in a single patient room of a hospital ward, 99% of aerosols could be cleared within 5.5 minutes.\n\nConclusionAir cleaners may be useful in clinical spaces to help reduce the risk of healthcare acquired acquisition of respiratory viruses that are transmitted via aerosols. They are easy to deploy and are likely to be cost effective in a variety of healthcare settings",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.29.21254509",
+    "rel_abs": "Identification of host genetic factors that predispose individuals to severe COVID-19 is important, not only for understanding the disease and guiding the development of treatments, but also for risk prediction when combined to form a polygenic risk score (PRS). Using population controls, Pairo-Castineira et al. identified 12 SNPs (a panel of 8 SNPs and a panel of 6 SNPs, with two SNPs in both panels) associated with severe COVID-19. Using controls with asymptomatic or mild COVID-19, we were able to replicate the association with severe COVID-19 for only three of their SNPs and found marginal evidence for an association for one other. When combined as an 8-SNP PRS and a 6-SNP PRS, we found no evidence of association with severe COVID-19. The difference in our results and the results of Pairo-Castineira et al. might be the choice of controls: population controls vs controls with asymptomatic or mild COVID-19.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Kirsty Lee Buising",
-        "author_inst": "Royal Melbourne Hospital"
-      },
-      {
-        "author_name": "Robyn Schofield",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Louis Irving",
-        "author_inst": "Royal Melbourne Hospital"
-      },
-      {
-        "author_name": "Melita Keywood",
-        "author_inst": "Commonwealth Scientific and Industrial Research Organisation"
-      },
-      {
-        "author_name": "Ashley Stevens",
-        "author_inst": "Royal Melbourne Hospital"
-      },
-      {
-        "author_name": "Nick Keogh",
-        "author_inst": "Royal Melbourne Hospital"
-      },
-      {
-        "author_name": "Grant Skidmore",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Imogen Wadlow",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Kevin Kevin",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Behzad Rismanchi",
-        "author_inst": "University of Melbourne"
-      },
-      {
-        "author_name": "Amanda Wheeler",
-        "author_inst": "Australian Catholic University"
-      },
-      {
-        "author_name": "Ruhi Humphries",
-        "author_inst": "Commonwealth Scientific and Industrial research Organization"
-      },
-      {
-        "author_name": "Marion Kainer",
-        "author_inst": "Western Health"
-      },
-      {
-        "author_name": "Forbes McGain",
-        "author_inst": "Western Health"
+        "author_name": "Nicholas M Murphy",
+        "author_inst": "Genetic Technologies Limited"
       },
       {
-        "author_name": "Jason Monty",
-        "author_inst": "University of Melbourne"
+        "author_name": "Gillian S Dite",
+        "author_inst": "Genetic Technologies Ltd."
       },
       {
-        "author_name": "Caroline Marshall",
-        "author_inst": "The University of Melbourne"
+        "author_name": "Richard Allman",
+        "author_inst": "Genetic technologies Limited"
       }
     ],
     "version": "1",
@@ -797790,37 +800973,25 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.03.27.21254480",
-    "rel_title": "Assessing the impact of widespread respirator use in curtailing COVID-19 transmission in the United States",
+    "rel_doi": "10.1101/2021.03.26.21254429",
+    "rel_title": "Forecasting the Spreading Trajectory of the COVID-19 Pandemic",
     "rel_date": "2021-03-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.27.21254480",
-    "rel_abs": "Dynamic models are used to assess the impact of three types of face masks-cloth masks, surgical/procedure masks and respirators-in controlling the COVID-19 pandemic in the United States. We showed that the pandemic would have failed to establish in the US if a nationwide mask mandate, based on using respirators with moderately-high compliance, had been implemented during the first two months of the pandemic. The other mask types would fail to prevent the pandemic from becoming established. When mask usage compliance is low to moderate, respirators are far more effective in reducing disease burden. Using data from the third wave, we showed that the epidemic could be eliminated in the US if at least 40% of the population consistently wore respirators in public. Surgical masks can also lead to elimination, but requires compliance of at least 55%. Daily COVID-19 mortality could be eliminated in the US by June or July 2021 if 95% of the population opted for either respirators or surgical masks from the beginning of the third wave. We showed that the prospect of effective control or elimination of the pandemic using mask-based strategy is greatly enhanced if combined with other nonpharmaceutical interventions (NPIs) that significantly reduce the baseline community transmission. By slightly modifying the model to include the effect of a vaccine against COVID-19 and waning vaccine-derived and natural immunity, this study shows that the waning of such immunity could trigger multiple new waves of the pandemic in the US. The number, severity and duration of the projected waves depend on the quality of mask type used and the level of increase in the baseline levels of other NPIs used in the community during the onset of the third wave of the pandemic in the US. Specifically, no severe fourth or subsequent wave of the pandemic will be recorded in the US if surgical masks or respirators are used, particularly if the mask-use strategy is combined with an increase in the baseline levels of other NPIs. This study further emphasizes the role of human behavior towards masking on COVID-19 burden, and highlights the urgent need to maintain a healthy stockpile of highly-effective respiratory protection, particularly respirators, to be made available to the general public in times of future outbreaks or pandemics of respiratory diseases that inflict severe public health and socio-economic burden on the population.\n\nAuthor summaryWe developed and used dynamic models to assess the role of highly-effective face coverings on the control and mitigation of the COVID-19 pandemic in the US. The study indicates that implementing and sustaining mask mandates is useful in containing diseases like COVID-19. Additionally, the study suggests that prioritizing the use of respirators is more effective in combating the disease than using other mask types. Specifically, the COVID-19 pandemic would have been prevented from being established in the US if four in every five Americans started wearing respirators during the first two months of the pandemic. The study further shows that COVID-19 can be eliminated in the US if a universal masking strategy that emphasizes respirators, requiring only 23% compliance, is combined with other nonpharmaceutical interventions that can reduce community transmission by 20%. Furthermore, the daily COVID-19 death rate can be completely suppressed by June 2021 if 95% of the population consistently use respirators. The elimination will extend to January 2022 if cloth masks were adopted instead. We conclude that stockpiling and distributing highly-efficient face coverings, notably respirators, will be vital in effectively curtailing future epidemics and pandemics of respiratory diseases.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254429",
+    "rel_abs": "Predictively forecasting future developments for the spread of the COVID-19 pandemic is extremely challenging. A recently published logistic mathematic model has achieved good predictions for infections weeks ahead. In this short communication, we summarize the Logistic spread model, which describes the dynamics of the pandemic evolution and the impacts of people social behavior in fighting against the pandemic. The new pandemic model has two parameters (i.e., transmission rate {gamma} and social distancing d) to be calibrated to the data from the pandemic regions in the early stage of the outbreak while the social distancing is put in place. The model is capable to make early predictions about the spreading trajectory in the communities of any size (countries, states, counties and cities) including the total infections, the date of peak daily infections and the date of the infections reaching a plateau if the testing is sufficient. The results are in good agreement with data and have important applications for ongoing outbreaks and similar infectious disease pandemics in the future.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Calistus N Ngonghala",
-        "author_inst": "University of Florida"
-      },
-      {
-        "author_name": "James R Knitter",
-        "author_inst": "The University of Arizona, College of Medicine, Tucson"
-      },
-      {
-        "author_name": "Lucas Marinacci",
-        "author_inst": "Massachusetts General Hospital"
-      },
-      {
-        "author_name": "Matthew H Bonds",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Baolian Cheng",
+        "author_inst": "Los Alamos National Laboratory"
       },
       {
-        "author_name": "Abba B Gumel",
-        "author_inst": "Arizona State University"
+        "author_name": "Yi-Ming Wang",
+        "author_inst": "LANL Retiree"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -799588,67 +802759,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.26.21254427",
-    "rel_title": "Assessment of serological assays for identifying high titer convalescent plasma",
+    "rel_doi": "10.1101/2021.03.27.21254471",
+    "rel_title": "Estimation of SARS-CoV-2 antibody prevalence through integration of serology and incidence data",
     "rel_date": "2021-03-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254427",
-    "rel_abs": "The COVID-19 pandemic has been accompanied by the largest mobilization of therapeutic convalescent plasma (CCP) in over a century. Initial identification of high titer units was based on dose-response data using the Ortho VITROS IgG assay. The proliferation of SARS-CoV-2 serological assays and non-uniform application has led to uncertainty about their interrelationships. The purpose of this study was to establish correlations and analogous cutoffs between commercially available serological tests (Ortho, Abbott, Roche), a spike ELISA, and a virus neutralization assay using convalescent plasma from a cohort of 79 donors from April 2020. Relationships relative to FDA-approved cutoffs under the CCP EUA were identified by linear regression and receiver operator characteristic curves. Relative to the Ortho VITROS assay, the r2 of the Abbott, Roche, the anti-Spike ELISA and the neutralizing assay were 0.58, 0.5, 0.82, and 0.44, respectively. The best correlative index for establishing high-titer units was 3.82 S/C for the Abbott, 10.89 COI for the Roche, 1:1,202 for the anti-Spike ELISA, and 1:200 by the neutralization assay. The overall agreement using derived cutoffs compared to the CCP EUA Ortho VITROS cutoff of 9.5 was 92.4% for Abbott, 84.8% for Roche, 87.3% for the anti-S ELISA and 78.5% for the neutralization assay. Assays based on antibodies against the nucleoprotein (Roche, Abbott) and neutralizing antibody tests were positively associated with the Ortho assay, although their ability to distinguish FDA high-titer specimens was imperfect. The resulting relationships help reconcile results from the large body of serological data generated during the COVID-19 pandemic.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.27.21254471",
+    "rel_abs": "Serology tests for SARS-CoV-2 provide a paradigm for estimating the number of individuals who have had infection in the past (including cases that are not detected by routine testing, which has varied over the course of the pandemic and between jurisdictions). Classical statistical approaches to such estimation do not incorporate case counts over time, and may be inaccurate due to uncertainty about the sensitivity and specificity of the serology test. In this work, we provide a joint Bayesian model for case counts and serological data, integrating uncertainty through priors on the sensitivity and specificity. We also model the Phases of the pandemic with exponential growth and decay. This model improves upon maximum likelihood estimates by conditioning on more data, and by taking into account the epidemiological trajectory. We apply our model to the greater Vancouver area, British Columbia, Canada with data acquired during Phase 1 of the pandemic.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Christopher W. Farnsworth",
-        "author_inst": "Washington University in St. Louis"
-      },
-      {
-        "author_name": "Brett Case",
-        "author_inst": "Washington University in St. Louis"
-      },
-      {
-        "author_name": "Karl Hock",
-        "author_inst": "Washington University in St. Louis"
-      },
-      {
-        "author_name": "Rita E Chen",
-        "author_inst": "Washington University School of Medicine"
-      },
-      {
-        "author_name": "Jane O'Halloran",
-        "author_inst": "Washington University in St. Louis School of Medicine"
-      },
-      {
-        "author_name": "Rachel Presti",
-        "author_inst": "Wash U"
-      },
-      {
-        "author_name": "Charles William Goss",
-        "author_inst": "Washington University in St. Louis School of Medicine"
-      },
-      {
-        "author_name": "Adriana M Rauseo",
-        "author_inst": "Washington University in St. Louis School of Medicine"
+        "author_name": "Liangliang Wang",
+        "author_inst": "Simon Fraser University"
       },
       {
-        "author_name": "Ali Ellebedy",
-        "author_inst": "Washington University School of Medicine"
+        "author_name": "Joosung Min",
+        "author_inst": "Simon Fraser University"
       },
       {
-        "author_name": "Elitza S Theel",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Renny Doig",
+        "author_inst": "Simon Fraser University"
       },
       {
-        "author_name": "Michael Diamond",
-        "author_inst": "Washington University School of Medicine"
+        "author_name": "Lloyd T Elliott",
+        "author_inst": "Simon Fraser University"
       },
       {
-        "author_name": "Jeffrey P Henderson",
-        "author_inst": "Washington University School of Medicine"
+        "author_name": "Caroline Colijn",
+        "author_inst": "Simon Fraser University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.03.27.21254453",
@@ -801502,117 +804645,105 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.17.21253847",
-    "rel_title": "Femtomolar SARS-CoV-2 Antigen Detection Using the Microbubbling Digital Assay with Smartphone Readout Enables Antigen Burden Quantitation and Dynamics Tracking",
+    "rel_doi": "10.1101/2021.03.21.21254061",
+    "rel_title": "Quantitative SARS-CoV-2 anti-spike responses to Pfizer-BioNTech and Oxford-AstraZeneca vaccines by previous infection status",
     "rel_date": "2021-03-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.17.21253847",
-    "rel_abs": "BackgroundLittle is known about the dynamics of SARS-CoV-2 antigen burden in respiratory samples in different patient populations at different stages of infection. Current rapid antigen tests cannot quantitate and track antigen dynamics with high sensitivity and specificity in respiratory samples.\n\nMethodsWe developed and validated an ultra-sensitive SARS-CoV-2 antigen assay with smartphone readout using the Microbubbling Digital Assay previously developed by our group, which is a platform that enables highly sensitive detection and quantitation of protein biomarkers. A computer vision-based algorithm was developed for microbubble smartphone image recognition and quantitation. A machine learning-based classifier was developed to classify the smartphone images based on detected microbubbles. Using this assay, we tracked antigen dynamics in serial swab samples from COVID patients hospitalized in ICU and immunocompromised COVID patients.\n\nResultsThe limit of detection (LOD) of the Microbubbling SARS-CoV-2 Antigen Assay was 0.5 pg/mL (10.6 fM) recombinant nucleocapsid (N) antigen or 4000 copies/mL inactivated SARS-CoV-2 virus in nasopharyngeal (NP) swabs, comparable to many rRT-PCR methods. The assay had high analytical specificity towards SARS-CoV-2. Compared to EUA-approved rRT-PCR methods, the Microbubbling Antigen Assay demonstrated a positive percent agreement (PPA) of 97% (95% confidence interval (CI), 92-99%) in symptomatic individuals within 7 days of symptom onset and positive SARS-CoV-2 nucleic acid results, and a negative percent agreement (NPA) of 97% (95% CI, 94-100%) in symptomatic and asymptomatic individuals with negative nucleic acid results. Antigen positivity rate in NP swabs gradually decreased as days-after-symptom-onset increased, despite persistent nucleic acid positivity of the same samples. The computer vision and machine learning-based automatic microbubble image classifier could accurately identify positives and negatives, based on microbubble counts and sizes. Total microbubble volume, a potential marker of antigen burden, correlated inversely with Ct values and days-after-symptom-onset. Antigen was detected for longer periods of time in immunocompromised patients with hematologic malignancies, compared to immunocompetent individuals. Simultaneous detectable antigens and nucleic acids may indicate the presence of replicating viruses in patients with persistent infections.\n\nConclusionsThe Microbubbling SARS-CoV-2 Antigen Assay enables sensitive and specific detection of acute infections, and quantitation and tracking of antigen dynamics in different patient populations at various stages of infection. With smartphone compatibility and automated image processing, the assay is well-positioned to be adapted for point-of-care diagnosis and to explore the clinical implications of antigen dynamics in future studies.",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.21.21254061",
+    "rel_abs": "ObjectivesWe investigate determinants of SARS-CoV-2 anti-spike IgG responses in healthcare workers (HCWs) following one or two doses of Pfizer-BioNTech or Oxford-AstraZeneca vaccines.\n\nMethodsHCWs participating in regular SARS-CoV-2 PCR and antibody testing were invited for serological testing prior to first and second vaccination, and 4 weeks post-vaccination if receiving a 12-week dosing interval. Quantitative post-vaccination anti-spike antibody responses were measured using the Abbott SARS-CoV-2 IgG II Quant assay (detection threshold: [&ge;]50 AU/ml). We used multivariable logistic regression to identify predictors of seropositivity and generalised additive models to track antibody responses over time.\n\nResultsVaccine uptake was 80%, but less in lower-paid roles and Black, south Asian and minority ethnic groups. 3570/3610(98.9%) HCWs were seropositive >14 days post-first vaccination and prior to second vaccination, 2706/2720(99.5%) after Pfizer-BioNTech and 864/890(97.1%) following Oxford-AstraZeneca vaccines. Previously infected and younger HCWs were more likely to test seropositive post-first vaccination, with no evidence of differences by sex or ethnicity. All 470 HCWs tested >14 days after second vaccine were seropositive. Quantitative antibody responses were higher after previous infection: median(IQR) >21 days post-first Pfizer-BioNTech 14,604(7644-22,291) AU/ml vs. 1028(564-1985) AU/ml without prior infection (p<0.001). Oxford-AstraZeneca vaccine recipients had lower readings post-first dose compared to Pfizer-BioNTech, with and without previous infection, 10,095(5354-17,096) and 435(203-962) AU/ml respectively (both p<0.001 vs. Pfizer-BioNTech). Antibody responses post-second vaccination were similar to those after prior infection and one vaccine dose.\n\nConclusionsVaccination leads to detectable anti-spike antibodies in nearly all adult HCWs. Whether differences in response impact vaccine efficacy needs further study.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Hui Chen",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Zhao Li",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Sheng Feng",
-        "author_inst": "University of Pennsylvania"
-      },
-      {
-        "author_name": "Anni Wang",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "David W Eyre",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Melissa Richard-Greenblatt",
-        "author_inst": "Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania"
+        "author_name": "Sheila F Lumley",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Emily Hutson",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Jia Wei",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Stefen Andrianus",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Stuart Cox",
+        "author_inst": "Oxford University Hospitals"
       },
       {
-        "author_name": "Laurel Glaser",
-        "author_inst": "Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania"
+        "author_name": "Tim James",
+        "author_inst": "Oxford University Hospitals"
       },
       {
-        "author_name": "Kyle G Rodino",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Anita Justice",
+        "author_inst": "Oxford University Hospitals"
       },
       {
-        "author_name": "Jianing Qian",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Gerald Jesuthasan",
+        "author_inst": "Oxford University Hospitals"
       },
       {
-        "author_name": "Dinesh Jayaraman",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Alison Howarth",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Ronald Collman",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Stephanie B Hatch",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Abigail L Glascock",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Brian D Marsden",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Frederic Bushman",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "E Yvonne Jones",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Jae Seung Lee",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "David I Stuart",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sara Cherry",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Daniel Ebner",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Alejandra Fausto",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Sarah Hoosdally",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Susan R Weiss",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Derrick Crook",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Hyun Koo",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Tim EA Peto",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Patricia M Corby",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Timothy M Walker",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Una ODoherty",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Nicole EA Stoesser",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Alfred L Garfall",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Philippa C Matthews",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Dan T Vogl",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Koen B Pouwels",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Edward A Stadtmauer",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "A Sarah Walker",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Ping Wang",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Katie Jeffery",
+        "author_inst": "Oxford University Hospitals"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -803488,69 +806619,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.23.21254169",
-    "rel_title": "COVID-19 antibody seroprevalence in Duhok, Kurdistan Region, Iraq: A population-based study",
+    "rel_doi": "10.1101/2021.03.23.21253460",
+    "rel_title": "Serological profiles of pan-coronavirus-specific responses in COVID-19 patients using a multiplexed electro-chemiluminescence-based testing platform",
     "rel_date": "2021-03-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21254169",
-    "rel_abs": "ObjectiveThis population-based study aimed to evaluate the seroprevalence of antibodies to SARS-CoV-2 in Duhok City, Kurdistan Region of Iraq.\n\nMethodsWe analyzed the national COVID-19 database that contains data regarding COVID-19 testing, management, and clinical outcomes in Duhok. For this study, different subdistricts within each district of Duhok were considered distinct clusters. Blood samples were collected from and questionnaires were administered to eligible and consenting participants who were members of different families from the subdistricts. Immunoassays were conducted to detect antibodies against SARS-CoV-2, and the associations between certain variables were investigated.\n\nResultsThe average number cases of COVID-19 before November 2020 was 23141 {+/-} 4364, which was significantly higher than the average number of cases between November 2020 and February 2021 (3737 {+/-} 2634; P = 0.001). A total of 743 individuals agreed to participate and were enrolled in the study. Among the participants, 465/743 (62.58%) were found to have antibodies against severe acute respiratory syndrome coronavirus 2. Among the participants with antibodies, 262/465 (56.34%) denied having any history of COVID-19-related symptoms. The most common symptom was fever (81.77%), followed by myalgia (81.28%). We found that antibody levels increased steadily with age (Pearson correlation coefficient = 0.117; P = 0.012). A significant association was found between antibody levels and the presence of symptoms (P = 0.023; odds ratio = 1.0023; 95% confidence interval = 1.0002-1.0061).\n\nConclusionsA significant reduction in the number of COVID-19 cases was observed. This might be due to the high prevalence of SARS-CoV-2 antibodies in Duhok. However, infection-prevention measures should be followed as it remains unclear whether acquired immunity is protective against reinfection. It expected that the infection rates during the next wave will not be as high as the first wave due to the high infection rate in the society.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21253460",
+    "rel_abs": "Serological assessment of SARS-CoV-2 specific responses are an essential tool for determining the prevalence of past SARS-CoV-2 infections in the population especially when testing occurs after symptoms have developed and limited contact tracing is in place. The goal of our study was to test a new 10-plex electro-chemiluminescence-based assay to measure IgM and IgG responses to the spike proteins from multiple human coronaviruses including SARS-CoV-2, assess the epitope specificity of the SARS-CoV-2 antibody response against full-length spike protein, receptor-binding domain and N-terminal domain of the spike protein, and the nucleocapsid protein. We carried out the assay on samples collected from three sample groups: subjects diagnosed with COVID-19 from the U.S. Army hospital at Camp Humphreys in Pyeongtaek, South Korea; healthcare administrators from the same hospital but with no reported diagnosis of COVID-19; and pre-pandemic samples. We found that the new CoV-specific multiplex assay was highly sensitive allowing plasma samples to be diluted 1:30,000 with a robust signal. The reactivity of IgG responses to SARS-CoV-2 nucleocapsid protein and IgM responses to SARS-CoV-2 spike protein could distinguish COVID-19 samples from non-COVID-19 and pre-pandemic samples. The data from the three sample groups also revealed a unique pattern of cross-reactivity between SARS-CoV-2 and SARS-CoV-1, MERS-CoV, and seasonal coronaviruses HKU1 and OC43. Our findings show that the CoV-2 IgM response is highly specific while the CoV-2 IgG response is more cross-reactive across a range of human CoVs and also showed that IgM and IgG responses show distinct patterns of epitope specificity. In summary, this multiplex assay was able to distinguish samples by COVID-19 status and characterize distinct trends in terms of cross-reactivity and fine-specificity in antibody responses, underscoring its potential value in diagnostic or serosurveillance efforts.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Nawfal R Hussein",
-        "author_inst": "Department of Biomolecular Sciences, College of Medicine, University of Zakho"
+        "author_name": "Sidhartha Chaudhury",
+        "author_inst": "WRAIR"
+      },
+      {
+        "author_name": "Jack N Hutter",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Amer Balatay",
-        "author_inst": "Department of pharmacology and clinical pharmacy, College of pharmacy, University of Duhok, Kurdistan Region, Iraq"
+        "author_name": "Jessica S Bolton",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Ibrahim A Naqid",
-        "author_inst": "Department of Biomedical Sciences, College of Medicine, University of Zakho, Kurdistan Region, Iraq"
+        "author_name": "Shilpa Hakre",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Shakir A Jamal",
-        "author_inst": "Department of Biomedical Sciences, College of Medicine, University of Zakho, Kurdistan Region, Iraq"
+        "author_name": "Evelyn Mose",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Narin A Rasheed",
-        "author_inst": "Akre Technical Institute, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq"
+        "author_name": "Amy I Wooten",
+        "author_inst": "Bryan D Allgood Army Community Hospital, Camp Humphrey"
       },
       {
-        "author_name": "Alind N Ahmed",
-        "author_inst": "Azadi Teaching Hospital, Duhok, Kurdistan Region of Iraq"
+        "author_name": "William D O'Connell",
+        "author_inst": "Bryan D Allgood Army Community Hospital, Camp Humphrey"
       },
       {
-        "author_name": "Reving S Salih",
-        "author_inst": "Azadi Teaching Hospital, Duhok, Kurdistan Region of Iraq"
+        "author_name": "Joseph Hudak",
+        "author_inst": "Bryan D Allgood Army Community Hospital, Camp Humphrey"
       },
       {
-        "author_name": "Ahmed S Mahdi",
-        "author_inst": "Childhood Friends Hospital of Amedi, Kurdistan Region of Iraq"
+        "author_name": "Shelly J Krebs",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Sabeeha A Mansour",
-        "author_inst": "Azadi Teaching Hospital, Duhok, Kurdistan Region of Iraq"
+        "author_name": "Janice Darden",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Shaveen Mahdi",
-        "author_inst": "Duhok Maternity Hospital, Duhok, Kurdistan Region of Iraq"
+        "author_name": "Jason A Regules",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Nashwan Ibrahim",
-        "author_inst": "Department of Surgery, College of Medicine, University of Duhok, Kurdistan Region, Iraq"
+        "author_name": "Clinton K Murray",
+        "author_inst": "Bryan D Allgood Army Community Hospital, Camp Humphrey"
       },
       {
-        "author_name": "Dildar H Musa",
-        "author_inst": "Department of Surgery, College of Medicine, University of Duhok, Kurdistan Region, Iraq"
+        "author_name": "Kevin Mojarrad",
+        "author_inst": "WRAIR"
+      },
+      {
+        "author_name": "Sheila A Peel",
+        "author_inst": "WRAIR"
       },
       {
-        "author_name": "Zana SM Saleem",
-        "author_inst": "Department of Medicine, College of Medicine, University of Duhok, Duhok, Kurdistan Region of Iraq"
+        "author_name": "Elke S Bergmann-Leitner",
+        "author_inst": "WRAIR"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -805022,55 +808161,35 @@
     "category": "medical education"
   },
   {
-    "rel_doi": "10.1101/2021.03.23.21254207",
-    "rel_title": "Association between the physical work environment and work functioning impairment while working from home under the COVID-19 pandemic in Japanese workers",
+    "rel_doi": "10.1101/2021.03.25.21254314",
+    "rel_title": "Automatic identification of risk factors for SARS-CoV-2 positivity and severe clinical outcomes of COVID-19 using Data Mining and Natural Language Processing",
     "rel_date": "2021-03-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21254207",
-    "rel_abs": "ObjectiveThis study examined the relationship between the physical work environment and work functioning impairment while working from home in the context of rapid changes associated with the COVID-19 pandemic.\n\nMethodsThis cross-sectional study of internet monitors was conducted between December 22 and 26, 2020. Of a total of 33,302 participants, 5,760 who worked from home at least 1 day a month, excluding those who met the exclusion criteria, were included in the analysis. A binary subjective assessment of the physical work environment while working from home was used as an exposure factor. We examined 9 items related to the physical work environment, including level of illuminance and use of suitable desks and chairs, traditionally recommended for health and safety management when working at a desk. The number of non-conformities to 7 items was also used as an exposure factor. The presence of severe work functioning impairment was measured using the Work Functioning impairment Scale (WFun), a self-reported outcome measure of the degree of work functioning impairment. Odds ratios of severe work functioning impairment were estimated using mixed-effects logistic regression analysis with the prefecture of residence as a random effect.\n\nResultsMultivariate analysis showed that the odds ratio of severe work functioning impairment was significantly higher among those who indicated \"No\" to all recommended items except for \"I work at a desk/chair for office use.\" The highest odds ratio of work functioning impairment was associated with a \"No\" response to \"There is enough light to do my work\" (aOR: 2.02, 95%CI: 1.73-2.35, p<0.01). Our results also suggest the presence of a dose-response relationship between the number of non-conformities to recommendations for work environments while working from home and work functioning impairment.\n\nConclusionsOur findings suggest that it is important for both companies and individual workers to create a work environment that prevents negative health outcomes and improves productivity while working from home.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.25.21254314",
+    "rel_abs": "ObjectivesSeveral risk factors have been identified for severe clinical outcomes of COVID-19 caused by SARS-CoV-2. Some can be found in structured data of patients Electronic Health Records. Others are included as unstructured free-text, and thus cannot be easily detected automatically. We propose an automated real-time detection of risk factors using a combination of data mining and Natural Language Processing (NLP).\n\nMaterial and methodsPatients were categorized as negative or positive for SARS-CoV-2, and according to disease severity (severe or non-severe COVID-19). Comorbidities were identified in the unstructured free-text using NLP. Further risk factors were taken from the structured data.\n\nResults6250 patients were analysed (5664 negative and 586 positive; 461 non-severe and 125 severe). Using NLP, comorbidities, i.e. cardiovascular and pulmonary conditions, diabetes, dementia and cancer, were automatically detected (error rate [&le;]2%). Old age, male sex, higher BMI, arterial hypertension, chronic heart failure, coronary heart disease, COPD, diabetes, insulin only treatment of diabetic patients, reduced kidney and liver function were risk factors for severe COVID-19. Interestingly, the proportion of diabetic patients using metformin but not insulin was significantly higher in the non-severe COVID-19 cohort (p<0.05).\n\nDiscussion and conclusionOur findings were in line with previously reported risk factors for severe COVID-19. NLP in combination with other data mining approaches appears to be a suitable tool for the automated real-time detection of risk factors, which can be a time saving support for risk assessment and triage, especially in patients with long medical histories and multiple comorbidities.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Makoto Okawara",
-        "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
-      },
-      {
-        "author_name": "Tomohiro Ishimaru",
-        "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
-      },
-      {
-        "author_name": "Seiichiro Tateishi",
-        "author_inst": "Department of Occupational Medicine, School of Medicine, University of Occupational and Environmental Health, Japan"
-      },
-      {
-        "author_name": "Ayako Hino",
-        "author_inst": "Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
-      },
-      {
-        "author_name": "Mayumi Tsuji",
-        "author_inst": "Department of Environmental Health, School of Medicine, University of Occupational and Environmental Health, Japan"
-      },
-      {
-        "author_name": "Kazunori Ikegami",
-        "author_inst": "Department of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
+        "author_name": "Verena Schoening",
+        "author_inst": "University Hospital Bern"
       },
       {
-        "author_name": "Masako Nagata",
-        "author_inst": "Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Jap"
+        "author_name": "Evangelia Liakoni",
+        "author_inst": "University Hospital Bern"
       },
       {
-        "author_name": "Shinya Matsuda",
-        "author_inst": "Department of Preventive Medicine and Community Health, School of Medicine, University of Occupational and Environmental Health, Japan"
+        "author_name": "Juergen Drewe",
+        "author_inst": "University Hospital Basel"
       },
       {
-        "author_name": "Yoshihisa Fujino",
-        "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan"
+        "author_name": "Felix Hammann",
+        "author_inst": "University Hospital Bern"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2021.03.25.21254375",
@@ -806536,31 +809655,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.24.21254046",
-    "rel_title": "Sudden rise in COVID-19 case fatality among young and middle-aged adults in the south of Brazil after identification of the novel B.1.1.28.1 (P.1) SARS-CoV-2 strain: analysis of data from the state of Parana",
+    "rel_doi": "10.1101/2021.03.24.21254254",
+    "rel_title": "Dental mitigation strategies to reduce aerosolization of SARS-CoV-2",
     "rel_date": "2021-03-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.24.21254046",
-    "rel_abs": "Brazil is currently suffering a deadly surge of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, which has been attributed to the spread of a new strain known as P.1 (B.1.1.28.1). In this investigation, we analyzed coronavirus disease 2019 (COVID-19) public health data from Parana, the largest state in southern half of Brazil, between September 1, 2020 and March 17, 2021, to evaluate recent trends in case fatality rates in different age groups. A total of 553,518 cases of SARS-CoV-2, 8,853 currently registered as fatal, were finally included in our analysis. All age groups showed either decline or stabilization of the case fatality rates (CFRs) between September 2020 and January 2021. In February 2021, an increase in CFR for almost all age groups could be instead observed. All groups above 20 years of age showed statistically significant increases in CFR when diagnosed in February 2021 as opposed to January 2021. Patients aged 20-29 years experienced a tripling of their CFR, from 0.04% to 0.13%, while those aged 30-39, 40-49, 50-59 experienced approximate CFR doubling. Individuals between 20 and 29 years of age whose diagnosis was made in February 2021 had an over 3-fold higher risk of death compared to those diagnosed in January 2021 (Risk Ratio (RR): 3.15 [95%CI: 1.52-6.53], p<0.01), while those aged 30-39, 40-49, 50-59 years experienced 93% (1.93 [95%CI:1.31-2.85], p<0.01), 110% (RR: 2.10 [95%CI:1.62-2.72], p<0.01), and 80% (RR: 1.80 [95%CI:1.50-2.16], p<0.01) increases in risk of death, respectively. Notably, the observed CFR increase coincided with the second consecutive month of declining number of diagnosed SARS-CoV-2 cases. Taken together, these preliminary findings suggest significant increases in CFR in young and middle-aged adults after identification of a novel SARS-CoV-2 strain circulating in Brazil, and this should raise public health alarms, including the need for more aggressive local and regional public health interventions and faster vaccination.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.24.21254254",
+    "rel_abs": "Limiting infection transmission is central to the safety of all in dentistry, particularly during the current SARS-CoV-2 pandemic. Aerosol-generating procedures (AGPs) are crucial to the practise of dentistry; it is imperative to understand the inherent risks of viral dispersion associated with AGPs and the efficacy of available mitigation strategies.\n\nIn a dental surgery setting, crown preparation and root canal access procedures were performed with an air turbine or electric speed-controlled hand-piece, with mitigation via rubber dam or high-volume aspiration and a no mitigation control. A phantom head was used with a 1.5 mL flow of artificial saliva infected with {Phi}6 bacteriophage (a surrogate virus for SARS-CoV-2) at [~]108 plaque forming units mL-1, reflecting the upper limits of reported salivary SARS-CoV-2 levels. Bioaerosol dispersal was measured using agar settle plates lawned with the bacteriophages host, Pseudomonas syringae. Viral air concentrations were assessed using MicroBio MB2 air sampling, and particle quantities using Kanomax 3889 GEO particle counters.\n\nCompared to an air turbine, the electric hand-piece reduced settled bioaerosols by 99.72%, 100.00% and 100.00% for no mitigation, aspiration and rubber dam, respectively. Bacteriophage concentrations in the air were reduced by 99.98%, 100.00% and 100.00%, with the same mitigation strategies. Use of the electric hand-piece with high-volume aspiration, resulted in no detectable bacteriophage, both on settle plates and in air samples taken 6-10-minutes post-procedure.\n\nTo our knowledge, this study is the first to report the aerosolization of active virus as a marker for risk determination in the dental setting. Whilst this model represents a worst-case scenario for possible SARS-CoV-2 dispersal, these data showed that the use of electric hand-pieces can vastly reduce the risk of viral aerosolization, and therefore remove the need for clinic fallow time. Furthermore, our findings indicate that the use of particle analysis alone cannot provide sufficient insight to understand bioaerosol infection risk.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Maria Helena Santos de Oliveira",
-        "author_inst": "Federal University of Parana"
+        "author_name": "Jon J Vernon",
+        "author_inst": "University of Leeds"
       },
       {
-        "author_name": "Giuseppe Lippi",
-        "author_inst": "University of Verona"
+        "author_name": "Emma V.I. Black",
+        "author_inst": "University of Leeds"
       },
       {
-        "author_name": "Brandon Michael Henry",
-        "author_inst": "Cincinnati Children's Hospital Medical Center"
+        "author_name": "Thomas Dennis",
+        "author_inst": "Leeds Dental Institute, Leeds Teaching Hospitals Trust"
+      },
+      {
+        "author_name": "Deirdre A Devine",
+        "author_inst": "University of Leeds"
+      },
+      {
+        "author_name": "Louise Fletcher",
+        "author_inst": "University of Leeds"
+      },
+      {
+        "author_name": "David J Wood",
+        "author_inst": "University of Leeds"
+      },
+      {
+        "author_name": "Brian R Nattress",
+        "author_inst": "University of Leeds"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "dentistry and oral medicine"
   },
   {
     "rel_doi": "10.1101/2021.03.26.21254327",
@@ -808637,59 +811772,87 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.03.25.436930",
-    "rel_title": "Genomic surveillance and phylodynamic analyses reveal emergence of novel mutation and co-mutation patterns within SARS-CoV2 variants prevalent in India",
+    "rel_doi": "10.1101/2021.03.25.437046",
+    "rel_title": "Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring",
     "rel_date": "2021-03-25",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.25.436930",
-    "rel_abs": "Emergence of distinct viral clades has been observed in SARS-CoV2 variants across the world and India. Identification of the genomic diversity and the phylodynamic profiles of the prevalent strains of the country are critical to understand the evolution and spread of the variants. We performed whole-genome sequencing of 54 SARS-CoV2 strains collected from COVID-19 patients in Kolkata, West Bengal during August to October 2020. Phylogeographic and phylodynamic analyses were performed using these 54 and other sequences from India and abroad available in GISAID database. Spatio-temporal evolutionary dynamics of the pathogen across various regions and states of India over three different time periods in the year 2020 were analyzed. We estimated the clade dynamics of the Indian strains and compared the clade specific mutations and the co-mutation patterns across states and union territories of India over the time course. We observed that GR, GH and G (GISAID) or 20B and 20A (Nextstrain) clades were the prevalent clades in India during middle and later half of the year 2020. However, frequent mutations and co-mutations observed within the major clades across time periods do not show much overlap, indicating emergence of newer mutations in the viral population prevailing in the country. Further, we explored the possible association of specific mutations and co-mutations with the infection outcomes manifested within the Indian patients.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.25.437046",
+    "rel_abs": "The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Nupur Biswas",
-        "author_inst": "CSIR-IICB"
+        "author_name": "Wolfgang Maier",
+        "author_inst": "University of Freiburg"
       },
       {
-        "author_name": "Priyanka Mallick",
-        "author_inst": "CSIR-IICB"
+        "author_name": "Simon Bray",
+        "author_inst": "University of Freiburg"
       },
       {
-        "author_name": "Sujay Krishna Maity",
-        "author_inst": "CSIR-IICB"
+        "author_name": "Marius van den Beek",
+        "author_inst": "Penn State University"
       },
       {
-        "author_name": "Debaleena Bhowmik",
-        "author_inst": "CSIR-IICB"
+        "author_name": "Dave Bouvier",
+        "author_inst": "Penn State University"
       },
       {
-        "author_name": "Arpita Ghosh Mitra",
-        "author_inst": "MEDICA Superspeciality Hospital, Kolkata, West Bengal, India"
+        "author_name": "Nathaniel Coraor",
+        "author_inst": "Penn State University"
       },
       {
-        "author_name": "Soumen Saha",
-        "author_inst": "MEDICA Superspeciality Hospital, Kolkata, West Bengal, India"
+        "author_name": "Milad Miladi",
+        "author_inst": "University of Freiburg"
       },
       {
-        "author_name": "Aviral Roy",
-        "author_inst": "MEDICA Superspeciality Hospital, Kolkata, West Bengal, India"
+        "author_name": "Babita Singh",
+        "author_inst": "Centre for Genomic Regulation"
       },
       {
-        "author_name": "Partha Chakrabarti",
-        "author_inst": "CSIR-Indian Institute of Chemical Biology"
+        "author_name": "Jordi Rambla De Argila",
+        "author_inst": "Centre for Genomic Regulation"
       },
       {
-        "author_name": "Sandip Paul",
-        "author_inst": "CSIR-IICB"
+        "author_name": "Dannon Baker",
+        "author_inst": "Johns Hopkins University"
       },
       {
-        "author_name": "Saikat Chakrabarti",
-        "author_inst": "CSIR-Indian Institute of Chemical Biology"
+        "author_name": "Nathan Roach",
+        "author_inst": "GalaxyWorks, LLC"
+      },
+      {
+        "author_name": "Simon Gladman",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Frederik Coppens",
+        "author_inst": "Ghent University"
+      },
+      {
+        "author_name": "Darren Martin",
+        "author_inst": "University of Cape Town"
+      },
+      {
+        "author_name": "Andrew Lonie",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Bjorn Gruning",
+        "author_inst": "University of Freiburg"
+      },
+      {
+        "author_name": "Sergei Kosakovsky Pond",
+        "author_inst": "Temple University"
+      },
+      {
+        "author_name": "Anton Nekrutenko",
+        "author_inst": "Penn State University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "genomics"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.03.25.437060",
@@ -810275,27 +813438,83 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.22.21254134",
-    "rel_title": "Relationship between COVID-19 pandemic and ecological, economic, and social characteristics",
+    "rel_doi": "10.1101/2021.03.20.21253892",
+    "rel_title": "Intention of Healthcare Workers to Receive COVID-19 Vaccine: A Cross-Sectional Survey in 10 Countries in Eastern Mediterranean Region",
     "rel_date": "2021-03-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254134",
-    "rel_abs": "COVID-19 pandemic had huge impacts on the global world, with both a negative impact on society and economy, but a positive one on nature. But this universal effect resulted in different infection rates from country to country. We analyzed the relationship between the pandemic and ecological, economic, and social characteristics. All of these data were collected in 140 countries at 6 time points. Correlations were studied using univariate and multivariate regression models.\n\nThe world was interpreted as a single global ecosystem consisting of ecosystem units representing countries. We first studied 140 countries around the world together, and infection rates were related to per capita GDP, Ecological Footprint, median age, urban population, and Biological Capacity, globally. We then ranked 140 countries by infection rate and created 4 equal groups, each with 35 countries. In the first group, the infection rate was very high and was related to the Ecological Footprint (consumption) and GDP per capita (production). This group is dominated by developed countries and their ecological characteristics have proven to be particularly significant. In groups 2, 3, and 4, infection rates were high, moderate, and low, and were primarily associated with median age and urban population.\n\nIn the scientific discussion, we have interpreted why infection is high in developed countries. Sustainable ecosystems are balanced, unlike the ecosystems of developed countries. According to science, the resilience and health of both natural ecosystems and humans are closely linked to the world of microbial communities. Our results suggest that both the economy and society need to be in harmony with nature, creating sustainable ecosystems in developed countries as well.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.20.21253892",
+    "rel_abs": "BackgroundWillingness of healthcare workers to be vaccinated is an important factor to be consider for successful COVID-19 vaccination programme. Our study aimed to understand the willingness of health workers to receive COVID-19 vaccine and associated concerns across 10 countries in the Eastern Mediterranean Region (EMRO).\n\nMethodA cross-sectional study was conducted in January 2021 among healthcare workers using an online survey. A total of 2806 health workers (Physicians, Nurses and Pharmacists) completed and returned the informed consent along with the questionnaire electronically. Data were analyzed using IBM SPSS software package version 20.0. S\n\nResultsMore than half of the respondents (58.0%) were willing to receive COVID-19 vaccine, even if the vaccination is not mandatory for them. On the other hand, 25.7% of respondents were not willing to undertake COVID-19 vaccination while 16.3 % answered undecided. The top three reasons for not intending to be vaccinated were unreliability of COVID-19 vaccine clinical trials (62.0%), fear of the side effects of the vaccine (45.3%), and that COVID-19 vaccine will not give immunity for a long period of time (23.1%).\n\nConclusionOverall, our study revealed suboptimal acceptance of COVID-19 vaccine among our respondents in the EMRO region. Significant refusal of COVID-19 vaccine among healthcare professionals can reverse hard-won progress in building public trust in COVID-19 vaccination program. Our findings suggest the need to develop tailored strategies to address concerns identified in the study in order to ensure optimal vaccine acceptance among healthcare workers in the EMRO.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Attila Muranyi",
-        "author_inst": "Institute for Soil Science and Agricultural Chemistry, Hungarian Academy of Sciences"
+        "author_name": "Yasir Ahmed Mohammed Elhadi",
+        "author_inst": "Department of Health Administration and Behavioral Sciences, High Institute of Public Health. Alexandria University, Alexandria, Egypt"
+      },
+      {
+        "author_name": "Azza Mehanna",
+        "author_inst": "Department of Health Administration and Behavioral Sciences, High Institute of Public Health. Alexandria University, Alexandria, Egypt"
+      },
+      {
+        "author_name": "Yusuff Adebayo Adebisi",
+        "author_inst": "University of Ibadan, Ibadan, Nigeria"
+      },
+      {
+        "author_name": "Haider M El Saeh",
+        "author_inst": "Faculty of Medicine"
+      },
+      {
+        "author_name": "Saddam Abdulhakeem Alnahari",
+        "author_inst": "Department of Health Administration and Behavioral Sciences, High Institute of Public Health. Alexandria University, Alexandria, Egypt"
+      },
+      {
+        "author_name": "Omar Hassan Alenezi",
+        "author_inst": "Public Health Administration, Kuwait Ministry of Health, Kuwait"
       },
       {
-        "author_name": "Balint Varga",
-        "author_inst": "Department of Computer Science, Institute of Mathematics, Eotvos Lorand University, Budapest, Hungary"
+        "author_name": "Diala El Chbib",
+        "author_inst": "Lebanese University, Faculty of Medical Sciences, Beirut, Lebanon"
+      },
+      {
+        "author_name": "Zahraa Yahya",
+        "author_inst": "Department of Food Health and Nutrition, College of Food Science, Al-Qasim Green University, Babylon, Iraq."
+      },
+      {
+        "author_name": "Eiman Ahmed",
+        "author_inst": "School of Global Public Health, New York University, New York, United States"
+      },
+      {
+        "author_name": "Shoaib Ahmad",
+        "author_inst": "Punjab Medical College, Faisalabad, Pakistan"
+      },
+      {
+        "author_name": "Saad Uakkas",
+        "author_inst": "Faculty of medicine, University Mohammed V, Rabat, Morocco"
+      },
+      {
+        "author_name": "Majdi Mohammed Sabahelzain",
+        "author_inst": "Department of Public Health, School of Health Sciences, Ahfad University for Women, Sudan"
+      },
+      {
+        "author_name": "Bushra Ahmed Alyamani",
+        "author_inst": "Department of Health Administration and Behavioral Sciences, High Institute of Public Health. Alexandria University, Alexandria, Egypt"
+      },
+      {
+        "author_name": "Arash Nemat",
+        "author_inst": "Department of Microbiology, Kabul University of Medical Sciences, Kabul, Afghanistan"
+      },
+      {
+        "author_name": "Don Eliseo Lucero-Prisno III",
+        "author_inst": "Department of Global health and Development, London School of Hygiene and Tropical Medicine, London, UK"
+      },
+      {
+        "author_name": "Ashraf Zaghloul",
+        "author_inst": "Department of Health Administration and Behavioral Sciences, High Institute of Public Health. Alexandria University, Alexandria, Egypt"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.03.15.21253313",
@@ -811851,103 +815070,43 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.14.21253532",
-    "rel_title": "Epicardial adipose tissue thickness is associated with increased severity and mortality related to SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2021.03.16.21253652",
+    "rel_title": "Within-Day Variability of SARS-CoV-2 RNA in Municipal Wastewater Influent During Periods of Varying COVID-19 Prevalence and Positivity",
     "rel_date": "2021-03-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.14.21253532",
-    "rel_abs": "BACKGROUNDIncreased adiposity and visceral obesity have been linked to adverse COVID-19 outcomes. The amount of epicardial adipose tissue (EAT) may have relevant implications given its proximity to the heart and lungs. Here, we explored the role of EAT in increasing the risk for COVID-19 adverse outcomes.\n\nMETHODSWe included 748 patients with COVID-19 attending a reference center in Mexico City. EAT thickness, sub-thoracic and extra-pericardial fat were measured using thoracic CT scans. We explored the association of each thoracic adipose tissue compartment with COVID-19 mortality and severe COVID-19 (defined as mortality and need for invasive mechanical ventilation), according to the presence or absence of obesity. Mediation analyses evaluated the role of EAT in facilitating the effect of age, body mass index and cardiac troponin levels with COVID-19 outcomes.\n\nRESULTSEAT thickness was associated with increased risk of COVID-19 mortality (HR 1.18, 95%CI 1.01-1.39) independent of age, gender, comorbid conditions and BMI. Increased EAT was associated with lower SpO2 and PaFi index and higher levels of cardiac troponins, D-dimer, fibrinogen, C-reactive protein, and 4C severity score, independent of obesity. EAT mediated 13.1% (95%CI 3.67-28.0%) and 5.1% (95%CI 0.19-14.0%) of the effect of age and 19.4% (95%CI 4.67-63.0%) and 12.8% (95%CI 0.03-46.0%) of the effect of BMI on requirement for intubation and mortality, respectively. EAT also mediated the effect of increased cardiac troponins on myocardial infarction during COVID-19.\n\nCONCLUSIONEAT is an independent risk factor for severe COVID-19 and mortality independent of obesity. EAT partly mediates the effect of age and BMI and increased cardiac troponins on adverse COVID-19 outcomes.",
-    "rel_num_authors": 21,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253652",
+    "rel_abs": "Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is being used to monitor Coronavirus Disease 2019 (COVID-19) trends in communities; however, within-day variation in primary influent concentrations of SARS-CoV-2 RNA remain largely uncharacterized. In the current study, grab sampling of primary influent was performed every 2 hours over two different 24-hour periods at two wastewater treatment plants (WWTPs) in northern Indiana, USA. In primary influent, uncorrected, recovery-corrected, and pepper mild mottle virus (PMMoV)-normalized SARS-CoV-2 RNA concentrations demonstrated ordinal agreement with increasing clinical COVID-19 positivity, but not COVID-19 cases. Primary influent SARS-CoV-2 RNA concentrations exhibited greater variation than PMMoV RNA concentrations as expected for lower shedding prevalence. The bovine respiratory syncytial virus (BRSV) process control recovery efficiency was low (mean: 0.91%) and highly variable (coefficient of variation: 51% - 206%) over the four sampling events with significant differences between the two WWTPs (p <0.0001). The process control recovery was similar to the independently assessed SARS-CoV-2 RNA recovery efficiency, which was also significantly different between the two WWTPs (p <0.0001). Recovery-corrected SARS-CoV-2 RNA concentrations better reflected within-day changes in primary influent flow rate and fecal content, as indicated by PMMoV concentrations. These observations highlight the importance of assessing the process recovery efficiency, which is highly variable, using an appropriate process control. Despite large variations, both recovery-corrected and PMMoV-normalized SARS-CoV-2 RNA concentrations in primary influent demonstrate potential for monitoring COVID-19 positivity trends in WWTPs serving peri-urban and rural areas.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Roopa Mehta",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Omar Yaxmehen Bello-Chavolla",
-        "author_inst": "Instituto Nacional de Geriatria"
-      },
-      {
-        "author_name": "Leonardo Mancillas-Adame",
-        "author_inst": "Facultad de Medicina, Universidad Autonoma de Nuevo Leon"
-      },
-      {
-        "author_name": "Marcela Rodr\u00edguez-Flores",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Natalia Ram\u00edrez-Pedraza",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Bethsabel Rodr\u00edguez-Encinas",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Carolina Isabel P\u00e9rez-Carri\u00f3n",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Mar\u00eda Isabel Jasso-\u00c1vila",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Jorge Valladares-Garcia",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Pablo Esteban Vanegas-Cedillo",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Diana Hern\u00e1ndez-Ju\u00e1rez",
-        "author_inst": "dianaheez@hotmail.com"
-      },
-      {
-        "author_name": "Arsenio Vargas-V\u00e1zquez",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Neftali Eduardo Antonio-Villa",
-        "author_inst": "Instituto Nacional de Geriatria"
-      },
-      {
-        "author_name": "Monica Chapa-Ibarguengoitia",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Paloma Almeda-Vald\t\u00e9s",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
-      },
-      {
-        "author_name": "Daniel Elias-Lopez",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
+        "author_name": "Aaron Bivins",
+        "author_inst": "Ohio State University"
       },
       {
-        "author_name": "Arturo Galindo-Fraga",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
+        "author_name": "Devin North",
+        "author_inst": "University of Notre Dame"
       },
       {
-        "author_name": "Alfonso Gulias-Herrero",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
+        "author_name": "Zhenyu Wu",
+        "author_inst": "University of Notre Dame"
       },
       {
-        "author_name": "Alfredo Ponce de Leon",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
+        "author_name": "Marlee Shaffer",
+        "author_inst": "University of Notre Dame"
       },
       {
-        "author_name": "Jose Sifuentes-Osornio",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
+        "author_name": "Warish Ahmed",
+        "author_inst": "CSIRO"
       },
       {
-        "author_name": "Carlos A. Aguilar-Salinas",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
+        "author_name": "Kyle James Bibby",
+        "author_inst": "University of Notre Dame"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "endocrinology"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.03.17.21253626",
@@ -813877,25 +817036,29 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.03.21.21254047",
-    "rel_title": "Factors influencing COVID-19 vaccination uptake in an elderly sample in Poland",
+    "rel_doi": "10.1101/2021.03.21.21254068",
+    "rel_title": "Determinants of COVID-19 outcomes: A systematic review.",
     "rel_date": "2021-03-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.21.21254047",
-    "rel_abs": "BackgroundsThis research represents an investigation into potential predictors for the uptake of the COVID-19 vaccination in Poland, following the instigation of policies to encourage the over-seventies to be vaccinated.\n\nMethodsIndividuals participated in cross-sectional structured interviews. 1427 respondents were questioned for determining vaccination uptake, revealing attitudes regarding vaccination, where information was sourced from, health status and behavior, demographics and socio-economic profiles.\n\nResultsSelected predictors for acceptance of the vaccination were: being talked through the importance of the vaccination and potential side-effects by a medical professional; sharing living space with others; having a high ranking occupation; suffering from chronic illnesses; being able to access medical services by driving or walking rather than using public transport or relying on others. Those who opted not to be vaccinated most frequently justify their decision by saying that they were concerned about the efficacy of the vaccine or that they were worried about side-effects.\n\nConclusionsIt appears that the current nationwide campaign has successfully raised awareness regarding the vaccine, but this research indicates that a more information-based campaign, focusing on evidence of the vaccines efficacy and the non-serious nature of all side-effects, could lead to improved uptake of the COVID-19 vaccine.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.21.21254068",
+    "rel_abs": "BackgroundThe current pandemic, COVID-19, caused by a novel coronavirus SARS-CoV-2, has claimed over a million lives worldwide in a year, warranting the need for more research into the wider determinants of COVID-19 outcomes to support evidence-based policies.\n\nObjectiveThis study aimed to investigate what factors determined the mortality and length of hospitalisation in individuals with COVID-19.\n\nData SourceThis is a systematic review with data from four electronic databases: Scopus, Google Scholar, CINAHL and Web of Science.\n\nEligibility CriteriaStudies were included in this review if they explored determinants of COVID-19 mortality or length of hospitalisation, were written in the English Language, and had available full-text.\n\nStudy appraisal and data synthesisThe authors assessed the quality of the included studies with the Newcastle{square}Ottawa Scale and the Agency for Healthcare Research and Quality checklist, depending on their study design. Risk of bias in the included studies was assessed with risk of bias assessment tool for non-randomised studies. A narrative synthesis of the evidence was carried out. The review methods were informed by the Joana Briggs Institute guideline for systematic reviews.\n\nResultsThe review included 22 studies from nine countries, with participants totalling 239,830. The included studies quality was moderate to high. The identified determinants were categorised into demographic, biological, socioeconomic and lifestyle risk factors, based on the Dahlgren and Whitehead determinant of health model. Increasing age (ORs 1.04-20.6, 95%CIs 1.01-22.68) was the common demographic determinant of COVID-19 mortality while living with diabetes (ORs 0.50-3.2, 95%CIs -0.2-0.74) was one of the most common biological determinants of COVID-19 length of hospitalisation.\n\nReview limitationMeta-analysis was not conducted because of included studies heterogeneity.\n\nConclusionCOVID-19 outcomes are predicted by multiple determinants, with increasing age and living with diabetes being the most common risk factors. Population-level policies that prioritise interventions for the elderly population and the people living with diabetes may help mitigate the outbreaks impact.\n\nPROSPERO registration numberCRD42021237063.\n\nStrength and limitations of this reviewO_LIThis is the first systematic review synthesising the evidence on determinants of COVID-19 LOS outcome.\nC_LIO_LIIt is also the first review to provide a comprehensive investigation of contextual determinants of COVID-19 outcomes, based on the determinants of health model; thus, presenting with crucial gaps in the literature on the determinants of COVID-19 outcomes that require urgent attention.\nC_LIO_LIThe review was restricted in conducting meta-analysis due to included studies heterogeneity.\nC_LIO_LIThe review focused on only papers published in the English Language; hence, other relevant papers written on other languages could have been omitted.\nC_LI",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Marta Malesza",
-        "author_inst": "University of Economics and Human Sciences in Warsaw"
+        "author_name": "Shirley Crankson",
+        "author_inst": "Brunel University London"
       },
       {
-        "author_name": "Magdalena Bozym",
-        "author_inst": "Military Academy Hospital, Warsaw, Poland"
+        "author_name": "Subhash Pokhrel",
+        "author_inst": "Brunel University London"
+      },
+      {
+        "author_name": "Nana Kwame Anokye",
+        "author_inst": "Brunel University London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -815971,37 +819134,21 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2021.03.19.21253425",
-    "rel_title": "COVID 19 Vaccine Perceptions in the New York State Intellectual and Developmental Disabilities Community",
+    "rel_doi": "10.1101/2021.03.21.21254048",
+    "rel_title": "Factors informing healthcare workers' willingness to work during the COVID-19 pandemic",
     "rel_date": "2021-03-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253425",
-    "rel_abs": "BackgroundPeople with intellectual and developmental disabilities (IDD) are at disproportionate risk for severe COVID-19 outcomes, particularly those living in congregate care settings. Yet, there is limited data on vaccine perceptions in the disability community.\n\nObjectiveTo explore COVID-19 vaccine perceptions in individuals with IDD, their family members, and those who work with them, to inform a statewide vaccine information and messaging project.\n\nMethodsA national survey, adapted for the IDD community, was distributed to a convenience sample of IDD organizations throughout New York State, in five languages. Constructs included vaccine intention, reasons for vaccine hesitancy, and trusted sources of vaccine information. Zip code data were used to map respondent location and vaccine preferences.\n\nResultsOf n= 825 respondents, approximately 75% intended to or had received the vaccine, across roles (i.e., people with disabilities, family members, direct care workers) and racial/ethnic groups. Greater vaccine hesitancy was reported in younger individuals and those making decisions on behalf of a person with IDD. Concerns included side effects and the swiftness of vaccine development. Black and Hispanic participants had heightened concerns about being an \"experiment\" for the vaccine. Trusted sources of information included healthcare providers and family members. Respondents who intended/got the vaccine were distributed throughout the state.\n\nConclusionsVaccine preferences in this New York State disability community sample align with national data. Identified concerns suggest the need for community education that addresses misperceptions. Age and race differences in perspectives highlight the need for tailored education, delivered by trusted messengers.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.21.21254048",
+    "rel_abs": "ObjectiveThe COVID-19 pandemic represents a substantial challenge to healthcare workers. Exploring the determinants of their willingness to work is crucial to ensuring hospital function during the outbreak. Hence, this study examines the factors affecting the motivation and hesitation of health workers in the face of the COVID-19 pandemic in Poland.\n\nStudy DesignAn online, anonymous survey was carried out among Polish healthcare workers during the COVID-19 pandemic.\n\nMethodThe respondents were asked about their demographic characteristics, stress-related factors, and their self-reported motivation and hesitation to work. The responses were gathered during September-December 2020.\n\nResults912 valid responses were obtained. Of these, 22.8% (N = 208) respondents reported being strongly motivated to work while 37.8% (N = 345) expressed strong hesitation. The participants demographic characteristics and their responses to the stress-related questions were assigned to four categories depending on the odds ratios of motivation and hesitation. While some factors were linked to enhanced motivation and reduced hesitation, others solely affected either motivation or hesitation, and yet others had a positive impact on both.\n\nConclusionOverall, the study indicates that in order to increase hospital workers motivation and decrease their hesitation, they must be made to feel protected by both their hospitals and local and national authorities.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Suzannah Iadarola",
-        "author_inst": "University of Rochester Medical Center, Director, Strong Center for Developmental Disabilities"
-      },
-      {
-        "author_name": "Joanne Siegel",
-        "author_inst": "Einstein College of Medicine-Montefiore Medical Center"
-      },
-      {
-        "author_name": "Qi Gao",
-        "author_inst": "Einstein College of Medicine"
-      },
-      {
-        "author_name": "Kathleen McGrath",
-        "author_inst": "Einstein College of Medicine"
-      },
-      {
-        "author_name": "Karen Bonuck",
-        "author_inst": "Einstein College of Medicine"
+        "author_name": "Marta Malesza",
+        "author_inst": "University of Economics and Human Sciences in Warsaw"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -817977,27 +821124,211 @@
     "category": "oncology"
   },
   {
-    "rel_doi": "10.1101/2021.03.19.21253962",
-    "rel_title": "The effects of physical distancing and lockdown to restrain SARS-CoV-2 outbreak in the Italian Municipality of Cogne",
+    "rel_doi": "10.1101/2021.03.18.21253881",
+    "rel_title": "A Prospective Study of Long-Term Outcomes Among Hospitalized COVID-19 Patients with and without Neurological Complications",
     "rel_date": "2021-03-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253962",
-    "rel_abs": "The outbreak of SARS-CoV-2 started in Wuhan, China, and is now a pandemic. An understanding of the prevalence and contagiousness of the disease, and of whether the strategies used to contain it to date have been successful, is important for understanding future containment strategies. One strategy for controlling the spread of SARS-CoV-2 is to adopt strong social distancing policies. The Municipality of Cogne (I), adopted strict lockdown rules from March 4, 2020 up to May 18, 2020. This first wave of the pandemic impressed by the extremely low impact of the SARS-CoV-2 on the locals, compared to the number accused on all the Italian territory. Starting from October 2020 up to the end of December, when the second wave hit Italy and Cogne territory, heavier effects were observed. In order to cast light on the effectiveness of the adopted strategy 74,5% of the local population underwent to a blood screening to detect IgM and IgG antibodies and after six months all the people tested positive were again investigated to establish the longitudinal changes in antibodies level. Moreover, within the context of this survey a rare and interesting case of secondary infection has been identified and here presented.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253881",
+    "rel_abs": "BackgroundLittle is known regarding long-term outcomes of patients hospitalized with COVID-19.\n\nMethodsWe conducted a prospective study of 6-month outcomes of hospitalized COVID-19 patients. Patients with new neurological complications during hospitalization who survived were propensity score-matched to COVID-19 survivors without neurological complications hospitalized during the same period. The primary 6-month outcome was multivariable ordinal analysis of the modified Rankin Scale(mRS) comparing patients with or without neurological complications. Secondary outcomes included: activities of daily living (ADLs;Barthel Index), telephone Montreal Cognitive Assessment and Neuro-QoL batteries for anxiety, depression, fatigue and sleep.\n\nResultsOf 606 COVID-19 patients with neurological complications, 395 survived hospitalization and were matched to 395 controls; N=196 neurological patients and N=186 controls completed follow-up. Overall, 346/382 (91%) patients had at least one abnormal outcome: 56% had limited ADLs, 50% impaired cognition, 47% could not return to work and 62% scored worse than average on [&ge;]1 Neuro-QoL scale (worse anxiety 46%, sleep 38%, fatigue 36%, and depression 25%). In multivariable analysis, patients with neurological complications had worse 6-month mRS (median 4 vs. 3 among controls, adjusted OR 2.03, 95%CI 1.22-3.40, P=0.01), worse ADLs (aOR 0.38, 95%CI 0.29-0.74, P=0.01) and were less likely to return to work than controls (41% versus 64%, P=0.04). Cognitive and Neuro-QOL metrics were similar between groups.\n\nConclusionsAbnormalities in functional outcomes, ADLs, anxiety, depression and sleep occurred in over 90% of patients 6-months after hospitalization for COVID-19. In multivariable analysis, patients with neurological complications during index hospitalization had significantly worse 6-month functional outcomes than those without.",
+    "rel_num_authors": 48,
     "rel_authors": [
       {
-        "author_name": "Gianpiero Gervino",
-        "author_inst": "University of Torino"
+        "author_name": "Jennifer A. Frontera",
+        "author_inst": "NYU Grossman School of Medicine"
+      },
+      {
+        "author_name": "Dixon Yang",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Ariane Lewis",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Palak Patel",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Chaitanya Medicherla",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Vito Arena",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Taolin Fang",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Andres Andino",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Thomas Snyder",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Maya Madhavan",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Daniel Gratch",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Benjamin Fuchs",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Alexa Dessy",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Melanie Canizares",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Ruben Jauregui",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Betsy Thomas",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Kristie Bauman",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Anlys Olivera",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Dhristie Bhagat",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Michael Sonson",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "George Park",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Rebecca Stainman",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Brian Sunwoo",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Daniel Talmasov",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Michael Tamimi",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Yingrong Zhu",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Jonathan Rosenthal",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Levi Dygert",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Milan Rustic",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Haruki Ishii",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Eduard Valdes",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Mirza Omari",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Lindsey Gurin",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Joshua Huang",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Barry M Czseiler",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "D. Ethan Kahn",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Ting Zhou",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Jessica Lin",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Aaron Lord",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Kara Melmed",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Sharon Meropol",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Andrea Troxel",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Eva Petkova",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Thomas Wisniewski",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Laura Balcer",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Chris Morrison",
+        "author_inst": "NYU Langone Hospitals"
+      },
+      {
+        "author_name": "Shadi Yaghi",
+        "author_inst": "NYU Langone Hospitals"
       },
       {
-        "author_name": "Fabio Truc",
-        "author_inst": "University of Torino"
+        "author_name": "Steven Galetta",
+        "author_inst": "NYU Langone Hospitals"
       }
     ],
     "version": "1",
-    "license": "cc0_ng",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.03.18.21253907",
@@ -820323,41 +823654,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.03.19.21253974",
-    "rel_title": "Data-driven estimate of SARS-CoV-2 herd immunity threshold in populations with individual contact pattern variations",
+    "rel_doi": "10.1101/2021.03.18.21253931",
+    "rel_title": "A convergence based assessment of relative differences in age-stratified susceptibility and infectiousness for SARS-CoV-2 variants of B.1.1.7 lineage",
     "rel_date": "2021-03-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253974",
-    "rel_abs": "The development of efficacious vaccines has made it possible to envision mass vaccination programs aimed at suppressing SARS-CoV-2 transmission around the world. Here we use a data-driven age-structured multilayer representation of the population of 34 countries to estimate the disease induced immunity threshold, accounting for the contact variability across individuals. We show that the herd immunization threshold of random (un-prioritized) mass vaccination programs is generally larger than the disease induced immunity threshold. We use the model to test two additional vaccine prioritization strategies, transmission-focused and age-based, in which individuals are inoculated either according to their behavior (number of contacts) or infection fatality risk, respectively. Our results show that in the case of a sterilizing vaccine the behavioral strategy achieves herd-immunity at a coverage comparable to the disease-induced immunity threshold, but it appears to have inferior performance in averting deaths than the risk vaccination strategy. The presented results have potential use in defining the effects that the heterogeneity of social mixing and contact patterns has on herd immunity levels and the deployment of vaccine prioritization strategies.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253931",
+    "rel_abs": "We propose (a) a method for aggregating and processing age-stratified subregional time series data for positive tests of infection given partial sampling for variant-of-concern biomarkers, and (b) a simple model-based theoretical framework for interpreting these processed data, to assess whether observed heterogeneity in age-specific relative differences can be explained by environmental effects alone.\n\nWe then apply this strategy to public-domain subregional time series data with S-gene target failure (SGTF) sampling as a proxy for B.1.1.7 lineage, from weeks 45 to 50 of 2020 from England. For the time period in question, we observe convergence toward a 1.27 (95% CI 1.17-1.38) times higher ratio of SGTF to non-SGTF infection for 0-9-year-olds than for the total population, and a 1.16 (95% CI 1.09-1.23) times higher ratio for 10-19-year-olds. These are roughly comparable to previous findings, but this time we find high-significance evidence for adequate compatibility with our proposed modelling framework criteria to conclude that these relative elevations for 0-19-year-olds are very unlikely to be explained by environmental effects alone. We also find possible indications that 0-19-year-olds might experience a higher relative increase in infectiousness than susceptibility for B.1.1.7.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Dan Lu",
-        "author_inst": "University of Zaragoza"
-      },
-      {
-        "author_name": "Alberto Aleta",
-        "author_inst": "ISI Foundation"
-      },
-      {
-        "author_name": "Marco Ajelli",
-        "author_inst": "Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington"
-      },
-      {
-        "author_name": "Romualdo Pastor-Satorras",
-        "author_inst": "Universitat Politecnica de Catalunya"
-      },
-      {
-        "author_name": "Alessandro Vespignani",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Yamir Moreno",
-        "author_inst": "University of Zaragoza"
+        "author_name": "Sarah Dean Rasmussen",
+        "author_inst": "University of Cambridge"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -821885,55 +825196,91 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.03.16.21253731",
-    "rel_title": "The Spike-specific IgA in milk commonly-elicited after SARS-Cov-2 infection is concurrent with a robust secretory antibody response, exhibits neutralization potency strongly correlated with IgA binding, and is highly durable over time",
+    "rel_doi": "10.1101/2021.03.17.21252673",
+    "rel_title": "Detecting SARS-CoV-2 lineages and mutational load in municipal wastewater; a use-case in the metropolitan area of Thessaloniki, Greece",
     "rel_date": "2021-03-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253731",
-    "rel_abs": "Approximately 10% of infants will experience COVID-19 illness requiring advanced care (1). A potential mechanism to protect this population could be provided by passive immunity through the milk of a previously infected mother. We and others have reported on the presence of SARS-CoV-2-specific antibodies in human milk (2-5). We now report the prevalence of SARS-CoV-2 IgA in the milk of 75 COVID-19-recovered participants, and find that 88% of samples are positive for Spike-specific IgA. In a subset of these samples, 95% exhibited robust IgA activity as determined by endpoint binding titer, with 50% considered high-titer. These IgA positive specimens were also positive for Spike-specific antibodies bearing the secretory component. Levels of IgA antibodies and antibodies bearing secretory component were shown to be strongly positively correlated. The secretory IgA response was dominant among the milk samples tested compared to the IgG response, which was present in 75% of samples and found to be of high-titer in only 13% of cases. Our IgA durability analysis using 28 paired samples, obtained 4-6 weeks and 4-10 months after infection, found that all samples exhibited persistently significant Spike-specific IgA, with 43% of donors exhibiting increasing IgA titers over time. Finally, COVID-19 and pre-pandemic control milk samples were tested for the presence of neutralizing antibodies; 6 of 8 COVID-19 samples exhibited neutralization of Spike-pseudotyped VSV (IC50 range, 2.39 - 89.4ug/mL) compared to 1 of 8 controls. IgA binding and neutralization capacities were found to be strongly positively correlated. These data are highly relevant to public health, not only in terms of the protective capacity of these antibodies for breastfed infants, but also for the potential use of such antibodies as a COVID-19 therapeutic, given that secretory IgA is highly stable not only in milk and the infant mouth and gut, but in all mucosa including the gastrointestinal tract, upper airway, and lungs (6).",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.17.21252673",
+    "rel_abs": "The SARS-CoV-2 pandemic represents an unprecedented global crisis necessitating novel approaches for, amongst others, early detection of emerging variants relating to the evolution and spread of the virus. Recently, the detection of SARS-CoV-2 RNA in wastewater has emerged as a useful tool to monitor the prevalence of the virus in the community. Here, we propose a novel methodology, called lineagespot, for the detection of SARS-CoV-2 lineages in wastewater samples using next-generation sequencing. Our proposed method was tested and evaluated using NGS data produced by the sequencing of three wastewater samples from the municipality of Thessaloniki, Greece, covering three distinct time periods. The results showed a clear identification of trends in the presence of SARS-CoV-2 mutations in sewage data, and allowed for a robust inference between the variants evident through our approach and the variants observed in patients from the same area time periods. Lineagespot is an open-source tool, implemented in R, and is freely available on GitHub.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Alisa Fox",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Nikolaos Pechlivanis",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas / Dept of Genetics, Development and Molecular Biology, School of Biology, Aristotle U"
       },
       {
-        "author_name": "Jessica Marino",
-        "author_inst": "University of California, Merced"
+        "author_name": "Maria Tsagiopoulou",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas"
       },
       {
-        "author_name": "Fatima Amanat",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Maria Christina Maniou",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas"
       },
       {
-        "author_name": "Kasopefoluwa Y. Oguntuyo",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Anastasis Togkousidis",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas"
       },
       {
-        "author_name": "Jennifer Hahn-Holbrook",
-        "author_inst": "University of California, Merced"
+        "author_name": "Evangelia Mouchtaropoulou",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas"
       },
       {
-        "author_name": "Benhur Lee",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Taxiarchis Chassalevris",
+        "author_inst": "School of Veterinary Medicine, Aristotle University of Thessaloniki"
       },
       {
-        "author_name": "Florian Krammer",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Serafeim Chaintoutis",
+        "author_inst": "School of Veterinary Medicine, Aristotle University of Thessaloniki"
       },
       {
-        "author_name": "Susan Zolla-Pazner",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Chrysostomos Dovas",
+        "author_inst": "School of Veterinary Medicine, Aristotle University of Thessaloniki"
       },
       {
-        "author_name": "Rebecca L Powell",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Maria Petala",
+        "author_inst": "Dept. of Civil Engineering, Aristotle University of Thessaloniki"
+      },
+      {
+        "author_name": "Margaritis Kostoglou",
+        "author_inst": "Dept. of Chemistry, Aristotle University of Thessaloniki"
+      },
+      {
+        "author_name": "Thodoris Karapantsios",
+        "author_inst": "Dept. of Chemistry, Aristotle University of Thessaloniki"
+      },
+      {
+        "author_name": "Stamatia Laidou",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas / Dept of Genetics, Development and Molecular Biology, School of Biology, Aristotle U"
+      },
+      {
+        "author_name": "Elisavet Vlachonikola",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas / Dept of Genetics, Development and Molecular Biology, School of Biology, Aristotle U"
+      },
+      {
+        "author_name": "Anastasia Chatzidimitriou",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas"
+      },
+      {
+        "author_name": "Agis Papadopoulos",
+        "author_inst": "EYATH S.A., Thessaloniki Water Supply and Sewerage Company S.A."
+      },
+      {
+        "author_name": "Nikolaos Papaioannou",
+        "author_inst": "School of Veterinary Medicine, Aristotle University of Thessaloniki"
+      },
+      {
+        "author_name": "Anagnostis Argiriou",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas"
+      },
+      {
+        "author_name": "Fotis Psomopoulos",
+        "author_inst": "Institute of Applied Biosciences, Centre of Research and Technology Hellas"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.03.16.21253759",
@@ -823799,99 +827146,71 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.13.21253527",
-    "rel_title": "PD-1highCXCR5-CD4+ Peripheral Helper T (Tph) cells Promote Tissue-Homing Plasmablasts in COVID-19",
+    "rel_doi": "10.1101/2021.03.15.21253619",
+    "rel_title": "COVID-19 with early neurological and cardiac thromboembolic phenomena--timeline of incidence and clinical features",
     "rel_date": "2021-03-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.13.21253527",
-    "rel_abs": "A dysregulated immune response against coronavirus-2 (SARS-CoV-2) plays a critical role in the outcome of patients with coronavirus disease 2019 (COVID-19). A significant increase in circulating plasmablasts is characteristic of COVID-19 though the underlying mechanisms and its prognostic implications are not known. Here, we demonstrate that in the acute phase of COVID-19, activated PD-1highCXCR5-CD4+ T cells, peripheral helper T cells, (Tph) are significantly increased and promote inflammatory tissue-homing plasmablasts in patients with stable but not severe COVID-19. Analysis of scRNA-seq data revealed that plasmablasts in stable patients express higher levels of tissue-homing receptors including CXCR3. The increased Tph cells exhibited \"B cell help\" signatures similar to that of circulating T follicular helper (cTfh) cells and promoted B cell differentiation in vitro. Compared with cTfh cells, Tph cells produced more IFN{gamma}, inducing tissue-homing chemokine receptors on plasmablasts. Finally, expansion of activated Tph cells was correlated with the frequency of CXCR3+ plasmablasts in the acute phase of patients with stable disease. Our results demonstrate a novel role for Tph cells in acute viral immunity by inducing ectopic, antibody secreting plasmablasts.",
-    "rel_num_authors": 20,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253619",
+    "rel_abs": "BackgroundAt our tertiary care public hospital, we saw COVID-19 presenting with thromboembolic phenomena, indicating a possible early thrombo-inflammatory pathology.\n\nObjectivesWe documented patients with cardiac and neurological thromboembolic phenomena as a primary presentation of COVID-19, and compared a subset of COVID associated strokes against COVID-19 patients without thrombotic manifestations.\n\nMethodsWe included all COVID-Stroke and COVID-ACS (COVID-19, with ischemic arterial stroke/Acute Coronary Syndrome presenting prior to/simultaneous with/within 72 hours of systemic/respiratory COVID manifestations) admitted from April to November 2020. In the nested case control analysis, we used unpaired T-test and chi-square test to study differences between COVID-Strokes (case group) and non-thrombotic COVID controls.\n\nResults and ConclusionsWe noted 68 strokes and 122 ACS associated with COVID-19. ACS peaked in May-June, while stroke admissions peaked later in September-October, possibly because severe strokes may have expired at home during the lockdown.\n\nIn the case-control analysis, cases (n=43; 12F:31M; mean age 51.5 years) had significantly higher D-Dimer values than controls (n=50; 9F:41M; mean age 51.6 years). Mortality was significantly higher in cases (51.2% vs. 26.0%; p = 0.018). We noted 7.5 times higher mortality in cases versus controls even among patients needing minimal oxygen support. Imaging in 37 patients showed both anterior and posterior circulation territories affected in seven, with almost half of Carotid territory strokes being large hemispherical strokes. Additionally, CT/MRI angiography in 28 strokes showed large vessel occlusions in 19 patients. Death in cases thus probably occurred before progression to intense respiratory support, due to severe central nervous system insult.\n\nBinary logistic regression analysis showed respiratory support intensity to be the sole independent predictor of mortality among cases. Respiratory distress could have been due to COVID-19 lung infection or aspiration pneumonia resulting from obtunded sensorium. In controls, mortality was predicted by increasing age, female sex, and respiratory support intensity.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Hiromitsu Asashima",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "Subhasis Mohanty",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "Michela Comi",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "William E Ruff",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "Kenneth B Hoehn",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "Patrick Wong",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "Inessa Cohen",
-        "author_inst": "Yale School of Medicine"
-      },
-      {
-        "author_name": "Sarah Coffey",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Uma Sundar",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Khadir Raddassi",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Sanah Merchant",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Omkar Chaudhary",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Meera Shah",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Avraham Unterman",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Amita Mukhopadhyay",
+        "author_inst": "Dr Chandramma Dayananda Sagar Institute of Medical Education and Research, Kanakapura 562112, Ramanagara District, Karnataka, India"
       },
       {
-        "author_name": "Brinda Emu",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Shaonak Kolte",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Steven H Kleinstein",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Pramod Darole",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Ruth R Montgomery",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Sharvari Mahajan",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Akiko Iwasaki",
-        "author_inst": "Yale University School of Medicine"
+        "author_name": "Ashank Bansal",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Charles S Dela Cruz",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Satish Gosavi",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Naftali Kaminski",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Dnaneshwar Asole",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Albert C Shaw",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Niteen Karnik",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "David A Hafler",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Ajay Mahajan",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       },
       {
-        "author_name": "Tomokazu S Sumida",
-        "author_inst": "Yale School of Medicine"
+        "author_name": "Anagha Joshi",
+        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "cardiovascular medicine"
   },
   {
     "rel_doi": "10.1101/2021.03.16.21253534",
@@ -825573,29 +828892,29 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.03.16.435705",
-    "rel_title": "Identification of ACE2 mutations that modulate SARS-CoV-2 spike binding across multiple mammalian species",
+    "rel_doi": "10.1101/2021.03.16.434488",
+    "rel_title": "SARS-CoV-2 Spike receptor-binding domain with a G485R mutation in complex with human ACE2",
     "rel_date": "2021-03-17",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.16.435705",
-    "rel_abs": "Understanding how SARS-CoV-2 interacts with different mammalian angiotensin-converting enzyme II (ACE2) cell entry receptors elucidates determinants of virus transmission and facilitates development of vaccines for humans and animals. Yeast display-based directed evolution identified conserved ACE2 mutations that increase spike binding across multiple species. Gln42Leu increased ACE2-spike binding for human and four of four other mammalian ACE2s; Leu79Ile had a effect for human and three of three mammalian ACE2s. These residues are highly represented, 83% for Gln42 and 56% for Leu79, among mammalian ACE2s. The above findings can be important in protecting humans and animals from existing and future SARS-CoV-2 variants.",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.16.434488",
+    "rel_abs": "Since SARS-CoV-2 emerged in 2019, genomic sequencing has identified mutations in the viral RNA including in the receptor-binding domain of the Spike protein. Structural characterisation of the Spike carrying point mutations aids in our understanding of how these mutations impact binding of the protein to its human receptor, ACE2, and to therapeutic antibodies. The Spike G485R mutation has been observed in multiple isolates of the virus and mutation of the adjacent residue E484 to lysine is known to contribute to antigenic escape. Here, we have crystallised the SARS-CoV-2 Spike receptor-binding domain with a G485R mutation in complex with human ACE2. The crystal structure shows that while the G485 residue does not have a direct interaction with ACE2, its mutation to arginine affects the structure of the loop made by residues 480-488 in the receptor-binding motif, disrupting the interactions of neighbouring residues with ACE2 and with potential implications for antigenic escape from vaccines, antibodies and other biologics directed against SARS-CoV-2 Spike.",
     "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Pete Heinzelman",
-        "author_inst": "UW-Madison"
+        "author_name": "Claire Marie Weekley",
+        "author_inst": "Bio21 Institute and Department of Biochemistry and Pharmacology, The University of Melbourne 3010 Victoria, Australia"
       },
       {
-        "author_name": "Jonathan Greenhalgh",
-        "author_inst": "University of Wisconsin--Madison"
+        "author_name": "Damian Francis John Purcell",
+        "author_inst": "Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, The University of Melbourne 3010 Victoria, Australia"
       },
       {
-        "author_name": "Philip A Romero",
-        "author_inst": "UW-Madison"
+        "author_name": "Michael W Parker",
+        "author_inst": "Bio21 Institute and Department of Biochemistry and Pharmacology, The University of Melbourne 3010 Victoria, Australia and St. Vincents Institute of Medical Rese"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "new results",
     "category": "biochemistry"
   },
@@ -827799,29 +831118,73 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.03.11.21253404",
-    "rel_title": "COVID-19 Underreporting and its Impact on Vaccination Strategies",
+    "rel_doi": "10.1101/2021.03.12.21253000",
+    "rel_title": "Novel highly divergent SARS-CoV-2 lineage with the Spike substitutions L249S and E484K",
     "rel_date": "2021-03-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253404",
-    "rel_abs": "We present a novel methodology for the stable rate estimation of hospitalization and death related to the Corona Virus Disease 2019 (COVID-19) using publicly available reports from various distinct communities. These rates are then used to estimate underreported infections on the corresponding areas by making use of reported daily hospitalizations and deaths. The impact of underreporting infections on vaccination strategies is estimated under different disease-transmission scenarios using a Susceptible-Exposed-Infective-Removed-like (SEIR) epidemiological model.\n\nOne sentence SummaryUsing a novel methodology, we estimate COVID-19 underreporting from public data, quantifying its impact on vaccination.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253000",
+    "rel_abs": "COVID-19 pandemics has led to genetic diversification of SARS-CoV-2 and the appearance of variants with potential impact in transmissibility and viral escape from acquired immunity. We report a new lineage containing ten distinctive amino acid changes across the genome. Further studies are required for monitoring its epidemiologic impact.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Vinicius V. L. Albani",
-        "author_inst": "Universidade Federal de Santa Catarina"
+        "author_name": "Katherine Laiton-Donato",
+        "author_inst": "Instituto Nacional de Salud"
       },
       {
-        "author_name": "Jennifer Loria",
-        "author_inst": "Instituto Nacional de Matematica Pura e Aplicada and Universidad de Costa Rica"
+        "author_name": "Jose A. Usme-Ciro",
+        "author_inst": "Universidad Cooperativa de Colombia"
       },
       {
-        "author_name": "Eduardo Massad",
-        "author_inst": "Fundacao Getulio Vargas"
+        "author_name": "Carlos Franco-Munoz",
+        "author_inst": "Instituto Nacional de Salud"
       },
       {
-        "author_name": "Jorge P. Zubelli",
-        "author_inst": "Khalifa University"
+        "author_name": "Diego A. Alvarez-Diaz",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Hector Alejandro Ruiz-Moreno",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Jhonnatan Reales-Gonzalez",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Diego Andres Prada",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Sheryll Corchuelo",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Maria T Herrera-Sepulveda",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Julian Naizaque",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Gerardo Santamaria",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Magdalena Wiesner",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Diana Marcela Walteros",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Martha Lucia Ospina Martinez",
+        "author_inst": "Instituto Nacional de Salud"
+      },
+      {
+        "author_name": "Marcela Marcela Mercado-Reyes",
+        "author_inst": "Instituto Nacional de Salud"
       }
     ],
     "version": "1",
@@ -830089,67 +833452,219 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.12.21253484",
-    "rel_title": "Limits of lockdown: characterising essential contacts during strict physical distancing",
+    "rel_doi": "10.1101/2021.03.12.21253493",
+    "rel_title": "Seroprevalence of Antibodies to SARS-CoV-2 among Health Care Workers in Kenya",
     "rel_date": "2021-03-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253484",
-    "rel_abs": "COVID-19 has exposed health inequalities within countries and globally. The fundamental determining factor behind an individuals risk of infection is the number of social contacts they make. In many countries, physical distancing measures have been implemented to control transmission of SARS-CoV-2, reducing social contacts to a minimum. Characterising unavoidable social contacts is key for understanding the inequalities behind differential risks and planning vaccination programmes. We utilised an existing English longitudinal birth cohort, which is broadly representative of the wider population (n=6807), to explore social contact patterns and behaviours when strict physical distancing measures were in place during the UKs first lockdown in March-May 2020. Essential workers, specifically those in healthcare, had 4.5 times as many contacts as non-essential workers [incident rate ratio = 4.42 (CI95%: 3.88-5.04)], whilst essential workers in other sectors, mainly teaching and the police force had three times as many contacts [IRR = 2.84 (2.58-3.13)]. The number of individuals in a household, which is conflated by number of children, increases essential social contacts by 40%. Self-isolation effectively reduces numbers of contacts outside of the home, but not entirely. Together, these findings will aid the interpretation of epidemiological data and impact the design of effective SARS-CoV-2 control strategies, such as vaccination, testing and contact tracing.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.12.21253493",
+    "rel_abs": "BackgroundFew studies have assessed the seroprevalence of antibodies against SARS-CoV-2 among Health Care Workers (HCWs) in Africa. We report findings from a survey among HCWs in three counties in Kenya.\n\nMethodsWe recruited 684 HCWs from Kilifi (rural), Busia (rural) and Nairobi (urban) counties. The serosurvey was conducted between 30th July 2020 and 4th December 2020. We tested for IgG antibodies to SARS-CoV-2 spike protein using ELISA. Assay sensitivity and specificity were 93% (95% CI 88-96%) and 99% (95% CI 98-99.5%), respectively. We adjusted prevalence estimates using Bayesian modeling to account for assay performance.\n\nResultsCrude overall seroprevalence was 19.7% (135/684). After adjustment for assay performance seroprevalence was 20.8% (95% CI 17.5-24.4%). Seroprevalence varied significantly (p<0.001) by site: 43.8% (CI 35.8-52.2%) in Nairobi, 12.6% (CI 8.8-17.1%) in Busia and 11.5% (CI 7.2-17.6%) in Kilifi. In a multivariable model controlling for age, sex and site, professional cadre was not associated with differences in seroprevalence.\n\nConclusionThese initial data demonstrate a high seroprevalence of antibodies to SARS-CoV-2 among HCWs in Kenya. There was significant variation in seroprevalence by region, but not by cadre.",
+    "rel_num_authors": 50,
     "rel_authors": [
       {
-        "author_name": "Amy C Thomas",
-        "author_inst": "University of Bristol"
+        "author_name": "Anthony O. Etyang",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Leon Danon",
-        "author_inst": "University of Bristol"
+        "author_name": "Ruth Lucinde",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Hannah Christensen",
-        "author_inst": "University of Bristol"
+        "author_name": "Henry Karanja",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Kate Northstone",
-        "author_inst": "University of Bristol"
+        "author_name": "Catherine Kalu",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Daniel Smith",
-        "author_inst": "University of Bristol"
+        "author_name": "Daisy Mugo",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Emily J Nixon",
-        "author_inst": "University of Bristol"
+        "author_name": "James Nyagwange",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Adam Trickey",
-        "author_inst": "University of Bristol"
+        "author_name": "John Gitonga",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Gibran Hemani",
-        "author_inst": "University of Bristol"
+        "author_name": "James Tuju",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Sarah Sauchelli",
-        "author_inst": "NIHR Bristol Biomedical Research Centre, University of Bristol"
+        "author_name": "Perpetual Wanjiku",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Adam Finn",
-        "author_inst": "University of Bristol"
+        "author_name": "Angela Karani",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Nicholas J Timpson",
-        "author_inst": "University of Bristol"
+        "author_name": "Shadrack Mutua",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Ellen Brooks-Pollock",
-        "author_inst": "University of Bristol"
+        "author_name": "Hosea Maroko",
+        "author_inst": "KEMRI Center for Infectious and Parasitic Diseases Control Research"
+      },
+      {
+        "author_name": "Eddy Nzomo",
+        "author_inst": "Kilifi County Hospital"
+      },
+      {
+        "author_name": "Eric Maitha",
+        "author_inst": "Department of Health, Kilifi County"
+      },
+      {
+        "author_name": "Evanson Kamuri",
+        "author_inst": "Kenyatta National Hospital"
+      },
+      {
+        "author_name": "Thuranira Kaugiria",
+        "author_inst": "Kenyatta National Hospital"
+      },
+      {
+        "author_name": "Justus Weru",
+        "author_inst": "Kenyatta National Hospital"
+      },
+      {
+        "author_name": "Lucy B. Ochola",
+        "author_inst": "Institute of Primate Research"
+      },
+      {
+        "author_name": "Nelson Kilimo",
+        "author_inst": "Alupe Sub-County Hospital"
+      },
+      {
+        "author_name": "Sande Charo",
+        "author_inst": "Kocholia sub-County Hospital"
+      },
+      {
+        "author_name": "Namdala Emukule",
+        "author_inst": "Busia County Referral Hospital"
+      },
+      {
+        "author_name": "Wycliffe Moracha",
+        "author_inst": "Department of Health, Busia County"
+      },
+      {
+        "author_name": "David Mukabi",
+        "author_inst": "Department of Health, Busia County"
+      },
+      {
+        "author_name": "Rosemary Okuku",
+        "author_inst": "Department of Health, Busia County"
+      },
+      {
+        "author_name": "Monicah Ogutu",
+        "author_inst": "Department of Health, Busia County"
+      },
+      {
+        "author_name": "Barrack Angujo",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Mark Otiende",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Christian Bottomley",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Edward Otieno",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Leonard Ndwiga",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Amek Nyaguara",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Shirine Voller",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Charles Agoti",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "David James Nokes",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Lynette Isabella Ochola-Oyier",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Rashid Aman",
+        "author_inst": "Ministry of Health, Government of Kenya"
+      },
+      {
+        "author_name": "Patrick Amoth",
+        "author_inst": "Ministry of Health, Government of Kenya"
+      },
+      {
+        "author_name": "Mercy Mwangangi",
+        "author_inst": "Ministry of Health, Government of Kenya"
+      },
+      {
+        "author_name": "Kadondi Kasera",
+        "author_inst": "Ministry of Health, Government of Kenya"
+      },
+      {
+        "author_name": "Wangari Nganga",
+        "author_inst": "Ministry of Health, Government of Kenya"
+      },
+      {
+        "author_name": "Ifedayo Adetifa",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Wangeci Kagucia",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Katherine Gallagher",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Sophie Uyoga",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Benjamin Tsofa",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Edwine Barasa",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Philip Bejon",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "J. Anthony G. Scott",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "Ambrose Agweyu",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
+      },
+      {
+        "author_name": "George Warimwe",
+        "author_inst": "KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.03.12.21253015",
@@ -831939,57 +835454,105 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.10.21253260",
-    "rel_title": "Analytical and clinical performances of a SARS-CoV-2 S-RBD IgG assay: comparison with neutralization titers",
+    "rel_doi": "10.1101/2021.03.10.21252711",
+    "rel_title": "An In-House ELISA for SARS-CoV-2 RBD uncovers elevatedimmune response at higher altitudes",
     "rel_date": "2021-03-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253260",
-    "rel_abs": "BackgroundSARS-CoV-2 serology presents an important role in understanding the virus epidemiology, in vaccine prioritization strategies and in convalescent plasma therapy. Immunoassays performances have to be accurately evaluated and correlated with neutralizing antibodies to be used as a surrogate measure of neutralizing activity. We investigate the analytical and clinical performance of a SARS-CoV-2 RBD IgG assay, automated on a high throughput platform, and the correlation of the antibodies (Ab) levels with the plaque reduction neutralization (PRNT50) Ab titers.\n\nMethodsA series of 546 samples were evaluated by SARS-CoV-2 RBD IgG assay (Snibe diagnostics), including 171 negative and 168 positive SARS-CoV-2 subjects and a further group of 207 subjects of the COVID-19 family clusters follow-up cohort.\n\nResultsAssay precision was acceptable at low and medium levels; linearity was excellent in all the measurement range. Considering specimens collected after 14 days post symptoms onset, overall sensitivity and specificity were 99.0% and 92.5%, respectively. A total of 281 leftover samples results of the PRNT50 test were available. An elevated correlation was obtained between the SARS-CoV-2 RBD IgG assay and the PRNT50 titer at univariate (rho = 0.689) and multivariate (rho = 0.712) analyses.\n\nConclusionsSARS-CoV-2 S-RBD IgG assay achieves elevated analytical and clinical performances, and a strong correlation with sera neutralization activity.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21252711",
+    "rel_abs": "The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) first reported in Wuhan has caused a global pandemic with dramatic health and socioeconomic consequences. The Coronavirus Disease 2019 (COVID-19) associated represents a challenge for health systems that had to quickly respond developing new diagnostic and therapeutic strategies. In the present work, we developed an \"In House\" ELISA with high sensitivity (92.2 %), specificity (100%) and precision (93.9%), with an area under the ROC curve (AUC) of 0.991, rendering the assay as an excellent serological test to correctly discriminate between SARS-COv-2 infected and non-infected individuals and study population seroprevalence. Among 758 patients evaluated for SARS-CoV-2 diagnosis in the province of Tucuman, Argentina, we found a Pearson correlation coefficient of 0.5048 between antibodies elicited against the RBD and the nucleocapsid (N) antigen. Additionally, 33.6% of individuals diagnosed with COVID-19 displayed mild levels of RBD-IgG antibodies, while 19% of the patients showed high antibody titers. Interestingly, patients with SARS-COV-2 infection over 60 years old elicited significantly higher levels of IgG antibodies against RBD compared to younger ones, while no difference was found between women and men. Surprisingly, individuals from a high altitude village displayed statistically significant higher and longer lasting anti-RBD antibodies compared to those from a city at a lower altitude, suggesting that a hypobaric hypoxia-adapted mechanism may act as a protective factor for COVID-19. To our knowledge, this is the first report correlating altitude with increased humoral immune response against SARS-Cov-2 infection.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Andrea Padoan",
-        "author_inst": "university of padova"
+        "author_name": "Rodrigo Tomas Grau",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Francesco Bonfante",
-        "author_inst": "Istituto Zooprofilattico sperimentale delle venezie, legnaro, italy"
+        "author_name": "Diego Ploper",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Chiara Cosma",
-        "author_inst": "Department of Laboratory medicine, University-hospital of padova, italy"
+        "author_name": "Cesar Luis Avila",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Costanza Di Chiara",
-        "author_inst": "Department of women's and children's health, university of padova"
+        "author_name": "Esteban Vera Pingitore",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Laura Sciacovelli",
-        "author_inst": "Department of Laboratory Medicine, University-Hospital of Padova"
+        "author_name": "Carolina Maldonado",
+        "author_inst": "Centro de Referencia para Lactobacilos. CERELA, CONICET. Tucuman, Argentina."
       },
       {
-        "author_name": "Matteo Pagliari",
-        "author_inst": "Istituto zooprofilattico sperimentale delle venezie, legnaro, italy"
+        "author_name": "Silvina Chaves",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Alessio Bortolami",
-        "author_inst": "Istituto zooprofilattico sperimentale delle venezie, legnaro, italy"
+        "author_name": "Sergio Benjamin Socias",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Paola Costenaro",
-        "author_inst": "Department for Women's and Children's Health, University of Padova, Italy"
+        "author_name": "Agustin Stagnetto",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Giulia Musso",
-        "author_inst": "Department of Laboratory Medicine, University-Hospital of Padova, Italy"
+        "author_name": "Silvia Navarro",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Daniela Basso",
-        "author_inst": "University of Padova"
+        "author_name": "Rossana Chahla",
+        "author_inst": "Hospital Nestor Kirchner, Laboratorio de Salud Publica, Sistema Provincial de Salud. LSP (SiProSa). Tucuman, Argentina."
       },
       {
-        "author_name": "Mario Plebani",
-        "author_inst": "University of Padova"
+        "author_name": "Monica Aguilar",
+        "author_inst": "Hospital Nestor Kirchner, Laboratorio de Salud Publica, Sistema Provincial de Salud. LSP (SiProSa). Tucuman, Argentina."
+      },
+      {
+        "author_name": "Conrado Llapur",
+        "author_inst": "Direccion de Investigacion en Salud. Ministerio de Salud Publica, Tucuman, Argentina"
+      },
+      {
+        "author_name": "Patricia Aznar",
+        "author_inst": "Hospital Nestor Kirchner, Laboratorio de Salud Publica, Sistema Provincial de Salud. LSP (SiProSa). Tucuman, Argentina."
+      },
+      {
+        "author_name": "Malena Alcorta",
+        "author_inst": "Hospital Nestor Kirchner, Laboratorio de Salud Publica, Sistema Provincial de Salud. LSP (SiProSa). Tucuman, Argentina."
+      },
+      {
+        "author_name": "Dardo Costas",
+        "author_inst": "Hospital Nestor Kirchner, Laboratorio de Salud Publica, Sistema Provincial de Salud. LSP (SiProSa). Tucuman, Argentina."
+      },
+      {
+        "author_name": "Isolina Flores",
+        "author_inst": "Hospital Nestor Kirchner, Laboratorio de Salud Publica, Sistema Provincial de Salud. LSP (SiProSa). Tucuman, Argentina."
+      },
+      {
+        "author_name": "Gabriela Apfelbaum",
+        "author_inst": "Facultad de Medicina. Universidad Nacional de Tucuman. Tucuman, Argentina"
+      },
+      {
+        "author_name": "Dar Heinze",
+        "author_inst": "EDITAR  Section of Gastroenterology, Department of Medicine, Center for Regenerative Medicine (CReM), Boston University School of Medicine, Boston, MA, USA."
+      },
+      {
+        "author_name": "Raul Mostoslavsky",
+        "author_inst": "The Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA."
+      },
+      {
+        "author_name": "Gustavo Mostoslavsky",
+        "author_inst": "Section of Gastroenterology, Department of Medicine, Center for Regenerative Medicine (CReM), Boston University School of Medicine, Boston, MA, USA"
+      },
+      {
+        "author_name": "Gabriela Perdigon",
+        "author_inst": "Centro de Referencia para Lactobacilos. CERELA. CONICET. Tucuman, Argentina."
+      },
+      {
+        "author_name": "Silvia Cazorla",
+        "author_inst": "Centro de Referencia para Lactobacilos. CERELA. CONICET. Tucuman, Argentina."
+      },
+      {
+        "author_name": "Rosana Chehin",
+        "author_inst": "Instituto de Medicina Molecular y Celular Aplicada - IMMCA (CONICET-UNT-SiProSa). Tucuman, Argentina."
       }
     ],
     "version": "1",
@@ -833717,27 +837280,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.10.21253322",
-    "rel_title": "A Dynamical Map to Describe Covid-19 Epidemics",
+    "rel_doi": "10.1101/2021.03.10.21253259",
+    "rel_title": "Evaluation of Measles Surveillance System amidst Covid 19 pandemic in Asutifi North District, Ahafo Region, Ghana.",
     "rel_date": "2021-03-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253322",
-    "rel_abs": "Nonlinear dynamics perspective is an interesting approach to describe COVID-19 epidemics, providing information to support strategic decisions. This paper proposes a dynamical map to describe COVID-19 epidemics based on the classical susceptible-exposed-infected-recovered (SEIR) differential model, incorporating vaccinated population. On this basis, the novel map represents COVID-19 discrete-time dynamics by adopting three populations: infected, cumulative infected and vaccinated. The map promotes a dynamical description based on algebraic equations with a reduced number of variables and, due to its simplicity, it is easier to perform parameter adjustments. In addition, the map description allows analytical calculations of useful information to evaluate the epidemic scenario, being important to support strategic decisions. In this regard, it should be pointed out the estimation of the number death cases, infectious rate and the herd immunization point. Numerical simulations show the model capability to describe COVID-19 dynamics, capturing the main features of the epidemic evolution. Reported data from Germany, Italy and Brazil are of concern showing the map ability to describe different scenario patterns that include multi-wave and plateaus behaviors. The effect of vaccination is analyzed considering different campaign strategies, showing its importance to control the epidemics.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.10.21253259",
+    "rel_abs": "BackgroundMeasles is a disease of public health importance earmarked for elimination by all WHO Regions. Globally, more than 140 000 people died from Measles in 2018 affecting mostly children under 5 years, despite the availability of safe and effective vaccine.\n\nMethodsA descriptive cross-sectional survey was conducted. Disease surveillance focal persons were interviewed using semi-structured questionnaire on the system operations and use of Measles case definitions. Measles case-based investigation forms from 2015 - 2020 were reviewed for its timeliness and data quality. CDC updated guidelines for surveillance system evaluation was used to assess its usefulness and attributes. Data was analyzed for frequencies and proportions and results presented in tables and graphs.\n\nResultsMeasles surveillance system was timely as 100% (69/69) of the suspected cases were reported on time. Also, the level of representativeness was good as all the 14 health facilities in the District were participating in the Measles Surveillance system. Majority 73.1 (44/60) of the case-based investigation forms filled were incomplete with some columns wrongly filled.\n\nConclusionDespite the outbreak of Covid - 19 with most districts battling with how to contain the virus, measles surveillance system was still meeting its objectives of early detection and prompt reporting but with poor data quality.",
     "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Eduardo Villela M. dos Reis",
-        "author_inst": "Universidade Federal do Rio de Janeiro"
+        "author_name": "Stephen Owusu Sekyere",
+        "author_inst": "University of Health and Allied Sciences"
       },
       {
-        "author_name": "Marcelo A. Savi",
-        "author_inst": "Universidade Federal do Rio de Janeiro"
+        "author_name": "Salaam Laar Dam-Park",
+        "author_inst": "Ghana Health Service"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.03.10.21253317",
@@ -835247,77 +838810,161 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.11.21253367",
-    "rel_title": "SARS-CoV-2 specific immune-signature in direct contacts of COVID-19 cases protect them from contracting disease: A Retrospective Study",
+    "rel_doi": "10.1101/2021.03.09.21253218",
+    "rel_title": "An observational cohort study on the incidence of SARS-CoV-2 infection and B.1.1.7 variant infection in healthcare workers by antibody and vaccination status",
     "rel_date": "2021-03-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253367",
-    "rel_abs": "The response to SARS-CoV-2 is largely impacted by the level of exposure and the status of immunity. The nature of protection shown by direct contacts of COVID-19 positive patients is quite intriguing to note. We aimed to study the immune differences reinforcing contact individuals in circumventing the disease. Our observation showed direct contacts of PCR positive patients developed elevated neutralizing antibody titres and cytokine levels. On the other hand, single cell data revealed differential usage of V(D)J genes and unique BCR clonotypes imparting protective immune signatures.\n\nTopicsserologic tests, immunoglobulin a, immunoglobulin g, immunoglobulin m, antibody titre; cytokine levels; virus neutralization; V(D)J sequencing; BCR clonotypes",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21253218",
+    "rel_abs": "BackgroundNatural and vaccine-induced immunity will play a key role in controlling the SARS-CoV-2 pandemic. SARS-CoV-2 variants have the potential to evade natural and vaccine-induced immunity.\n\nMethodsIn a longitudinal cohort study of healthcare workers (HCWs) in Oxfordshire, UK, we investigated the protection from symptomatic and asymptomatic PCR-confirmed SARS-CoV-2 infection conferred by vaccination (Pfizer-BioNTech BNT162b2, Oxford-AstraZeneca ChAdOx1 nCOV-19) and prior infection (determined using anti-spike antibody status), using Poisson regression adjusted for age, sex, temporal changes in incidence and role. We estimated protection conferred after one versus two vaccinations and from infections with the B.1.1.7 variant identified using whole genome sequencing.\n\nResults13,109 HCWs participated; 8285 received the Pfizer-BioNTech vaccine (1407 two doses) and 2738 the Oxford-AstraZeneca vaccine (49 two doses). Compared to unvaccinated seronegative HCWs, natural immunity and two vaccination doses provided similar protection against symptomatic infection: no HCW vaccinated twice had symptomatic infection, and incidence was 98% lower in seropositive HCWs (adjusted incidence rate ratio 0.02 [95%CI <0.01-0.18]). Two vaccine doses or seropositivity reduced the incidence of any PCR-positive result with or without symptoms by 90% (0.10 [0.02-0.38]) and 85% (0.15 [0.08-0.26]) respectively. Single-dose vaccination reduced the incidence of symptomatic infection by 67% (0.33 [0.21-0.52]) and any PCR-positive result by 64% (0.36 [0.26-0.50]). There was no evidence of differences in immunity induced by natural infection and vaccination for infections with S-gene target failure and B.1.1.7.\n\nConclusionNatural infection resulting in detectable anti-spike antibodies and two vaccine doses both provide robust protection against SARS-CoV-2 infection, including against the B.1.1.7 variant.\n\nSummaryNatural infection resulting in detectable anti-spike antibodies and two vaccine doses both provided [&ge;] 85% protection against symptomatic and asymptomatic SARS-CoV-2 infection in healthcare workers, including against the B.1.1.7 variant. Single dose vaccination reduced symptomatic infection by 67%.",
+    "rel_num_authors": 36,
     "rel_authors": [
       {
-        "author_name": "Sunil K. Raghav",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Sheila F Lumley",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Kaushik Sen",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Gillian Rodger",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Arup Ghosh",
-        "author_inst": "Institute of Life Sciences"
+        "author_name": "Bede Constantinides",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sudeshna Datta",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Nicholas Sanderson",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Abdul Ahad",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Kevin K Chau",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Atimukta Jha",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Teresa L Street",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sanchari Chatterjee",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Alison Howarth",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sandhya Suranjika",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Stephanie B Hatch",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Soumya Sengupta",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Brian D Marsden",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Gargee Bhattacharya",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Stuart Cox",
+        "author_inst": "Oxford University Hospitals"
       },
       {
-        "author_name": "Omprakash Shriwas",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Tim James",
+        "author_inst": "Oxford University Hospitals"
       },
       {
-        "author_name": "Kiran Avula",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Fiona Warren",
+        "author_inst": "Oxford University Hospitals"
       },
       {
-        "author_name": "Jayasingh Kshatri",
-        "author_inst": "ICMR-Regional Medical Research Center"
+        "author_name": "Liam J Peck",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Punit Prasad",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Thomas G Ritter",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Ajay K. Parida",
-        "author_inst": "Institute of Life Sciences, Bhubaneswar"
+        "author_name": "Zoe de Toledo",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Laura Warren",
+        "author_inst": "Oxford University Hospitals"
+      },
+      {
+        "author_name": "David Axten",
+        "author_inst": "Oxford University Hospitals"
+      },
+      {
+        "author_name": "Richard J Cornall",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "E Yvonne Jones",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "David I Stuart",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Gavin Screaton",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Daniel Ebner",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Sarah Hoosdally",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Meera Chand",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "- Oxford University Hospitals Staff Testing Group",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Derrick Crook",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Christopher P Conlon",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Koen B Pouwels",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "A Sarah Walker",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Tim EA Peto",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Susan Hopkins",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Timothy M Walker",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Nicole EA Stoesser",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Philippa C Matthews",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Katie Jeffery",
+        "author_inst": "Oxford University Hospitals"
+      },
+      {
+        "author_name": "David W Eyre",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -836816,91 +840463,59 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.03.11.434841",
-    "rel_title": "Antibody responses to SARS-CoV-2 mRNA vaccines are detectable in saliva",
+    "rel_doi": "10.1101/2021.03.11.434937",
+    "rel_title": "SARS-CoV-2 comprehensive receptor profiling: mechanistic insight to drive new therapeutic strategies",
     "rel_date": "2021-03-11",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.11.434841",
-    "rel_abs": "Vaccines are critical for curtailing the COVID-19 pandemic (1, 2). In the USA, two highly protective mRNA vaccines are available: BNT162b2 from Pfizer/BioNTech and mRNA-1273 from Moderna (3, 4). These vaccines induce antibodies to the SARS-CoV-2 S-protein, including neutralizing antibodies (NAbs) predominantly directed against the Receptor Binding Domain (RBD) (1-4). Serum NAbs are induced at modest levels within [~]1 week of the first dose, but their titers are strongly boosted by a second dose at 3 (BNT162b2) or 4 weeks (mRNA-1273) (3, 4). SARS-CoV-2 is most commonly transmitted nasally or orally and infects cells in the mucosae of the respiratory and to some extent also the gastrointestinal tract (5). Although serum NAbs may be a correlate of protection against COVID-19, mucosal antibodies might directly prevent or limit virus acquisition by the nasal, oral and conjunctival routes (5). Whether the mRNA vaccines induce mucosal immunity has not been studied. Here, we report that antibodies to the S-protein and its RBD are present in saliva samples from mRNA-vaccinated healthcare workers (HCW). Within 1-2 weeks after their second dose, 37/37 and 8/8 recipients of the Pfizer and Moderna vaccines, respectively, had S-protein IgG antibodies in their saliva, while IgA was detected in a substantial proportion. These observations may be relevant to vaccine-mediated protection from SARS-CoV-2 infection and disease.",
-    "rel_num_authors": 18,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.11.434937",
+    "rel_abs": "Here we describe a hypothesis free approach to screen for interactions of SARS-CoV-2 spike (S) protein with human cell surface receptors. We used a library screening approach to detect binding interactions across one of the largest known panels of membrane-bound and soluble receptors, comprising 5845 targets, expressed recombinantly in human cells. We were able confirm and replicate SARS-CoV-2 binding to ACE2 and other putative coreceptors such as CD209 and CLEC4M. More significantly, we identified interactions with a number of novel SARS-CoV-2 S binding proteins. Three of these novel receptors, NID1, CNTN1 and APOA4 were specific to SARS-CoV-2, and not SARS-COV, with APOA4 binding the S-protein with equal affinity as ACE2. With this knowledge we may further understand the disease pathogenesis of COVID-19 patients and how infection by SARS-CoV-2 may lead to differences in pathology in specific organs or indeed the virulence observed in different ethnicities. Importantly we illustrate a methodology which can be used for rapid, unbiassed identification of cell surface receptors, to support drug screening and drug repurposing approaches for this and future pandemics.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Thomas J. Ketas",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Devidas Chaturbhuj",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Victor Cruz Portillo",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Erik Francomano",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Encouse Golden",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Sharanya Chandrasekhar",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Gargi Debnath",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Randy Diaz Tapia",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Anila Yasmeen",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Sarah MV Brockbank",
+        "author_inst": "Medicines Discovery Catapult"
       },
       {
-        "author_name": "Wilhem Leconet",
-        "author_inst": "Genmab"
+        "author_name": "Raquel Faba-Rodriguez",
+        "author_inst": "Peak Proteins Limited"
       },
       {
-        "author_name": "Zhen Zhao",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Lyn Rosenbrier Ribeiro",
+        "author_inst": "Medicines Discovery Catapult"
       },
       {
-        "author_name": "Philip J.M. Brouwer",
-        "author_inst": "Amsterdam University Medical Center"
+        "author_name": "Catherine Geh",
+        "author_inst": "Peak Proteins Limited"
       },
       {
-        "author_name": "Melissa M. Cushing",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Helen Thomas",
+        "author_inst": "Retrogenix Ltd"
       },
       {
-        "author_name": "Rogier Sanders",
-        "author_inst": "Amsterdam University Medical Center"
+        "author_name": "Jenni Delight",
+        "author_inst": "Retrogenix Ltd"
       },
       {
-        "author_name": "Albert Cupo",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Lucy Coverley",
+        "author_inst": "Retrogenix Ltd"
       },
       {
-        "author_name": "Per Johan Klasse",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "W Mark Abbott",
+        "author_inst": "Peak Proteins Limited"
       },
       {
-        "author_name": "Silvia C. Formenti",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Jo Soden",
+        "author_inst": "Retrogenix Ltd"
       },
       {
-        "author_name": "John P. Moore",
-        "author_inst": "Weill Cornell Medicine"
+        "author_name": "Jim Freeth",
+        "author_inst": "Retrogenix Ltd"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc0_ng",
     "type": "new results",
-    "category": "microbiology"
+    "category": "cell biology"
   },
   {
     "rel_doi": "10.1101/2021.03.11.434764",
@@ -838801,35 +842416,75 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.03.09.21252764",
-    "rel_title": "A High Rate of COVID-19 Vaccine Hesitancy Among Arabs: Results of a Large-scale Survey",
+    "rel_doi": "10.1101/2021.03.08.21253141",
+    "rel_title": "COVID-19 is associated with multiple sclerosis exacerbations that are prevented by disease modifying therapies",
     "rel_date": "2021-03-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21252764",
-    "rel_abs": "In this study, we present the results of the first large-scale multinational study (36,220 participants) that measures vaccine hesitancy among Arab-speaking subjects. Our analysis shows a significant rate of vaccine hesitancy among Arabs in and outside the Arab region (83% and 81%, respectively). The most cited reasons for hesitancy are concerns about side effects and distrust in healthcare policies, vaccine expedited production, published studies and vaccine producing companies. We also found that female participants, participants 30-59 year-old, those with no chronic diseases, those with lower-level of academic education, and those who do not know the type of vaccine authorized in their countries are more hesitant to receive COVID-19 vaccination. On the other hand, participants who regularly receive the influenza vaccine, health care workers, and those from countries with higher rates of COVID-19 infections showed more vaccination willingness. Interactive representation of our results is posted on our project website at https://mainapp.shinyapps.io/CVHAA.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21253141",
+    "rel_abs": "BackgroundInfections can trigger exacerbations of multiple sclerosis (MS). The effects of the coronavirus disease 2019 (COVID-19) on MS are not known. The aim of this study was to understand the impact of COVID-19 on new and pre-existing symptoms of MS.\n\nMethodsThe COVID-19 and MS study is an ongoing community-based, prospective cohort study conducted as part of the United Kingdom MS Register. People with MS and COVID-19 were invited by email to complete a questionnaire about their MS symptoms during the infection. An MS exacerbation was defined as developing new MS symptoms and/or worsening of pre-existing MS symptoms.\n\nResultsFifty-seven percent (230/404) of participants had an MS exacerbation during their infection; 82 developed new MS symptoms, 207 experienced worsened pre-existing MS symptoms, and 59 reported both. Disease modifying therapies (DMTs) reduced the likelihood of developing new MS symptoms during the infection (OR 0.556, 95%CI 0.316-0.978). Participants with a higher pre-COVID-19 webEDSS (web-based Expanded Disability Status Scale) score (OR 1.251, 95%CI 1.060-1.478) and longer MS duration (OR 1.042, 95%CI 1.009-1.076) were more likely to experience worsening of their pre-existing MS symptoms during the infection.\n\nConclusionCOVID-19 infection was associated with exacerbation of MS. DMTs reduced the chance of developing new MS symptoms during the infection.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Eyad A. Qunaibi",
-        "author_inst": "Department of Pharmaceutical Sciences, Jerash Private University, Jerash, Jordan"
+        "author_name": "Afagh Garjani",
+        "author_inst": "University of Nottingham"
+      },
+      {
+        "author_name": "Rodden M Middleton",
+        "author_inst": "Swansea University Medical School"
       },
       {
-        "author_name": "Mohamed Helmy",
-        "author_inst": "Agency for Science, Research and Technology"
+        "author_name": "Rachael Hunter",
+        "author_inst": "Swansea University"
       },
       {
-        "author_name": "Iman Basheti",
-        "author_inst": "Department of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, Amman, Jordan"
+        "author_name": "Katherine A Tuite-Dalton",
+        "author_inst": "Swansea University Medical School"
       },
       {
-        "author_name": "Iyad Sultan",
-        "author_inst": "King Hussein Cancer Center"
+        "author_name": "Alasdair Coles",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Ruth Dobson",
+        "author_inst": "Queen Mary University London"
+      },
+      {
+        "author_name": "Martin Duddy",
+        "author_inst": "Newcastle upon Tyne Hospitals NHS Trust"
+      },
+      {
+        "author_name": "Stella Hughes",
+        "author_inst": "Belfast Health and Social Care Trust"
+      },
+      {
+        "author_name": "Owen R Pearson",
+        "author_inst": "Swansea Bay University Health Board"
+      },
+      {
+        "author_name": "David Rog",
+        "author_inst": "Salford Royal NHS Foundation Trust"
+      },
+      {
+        "author_name": "Emma C Tallantyre",
+        "author_inst": "Cardiff University"
+      },
+      {
+        "author_name": "Roshan das Nair",
+        "author_inst": "University of Nottingham"
+      },
+      {
+        "author_name": "Richard Nicholas",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Nikos Evangelou",
+        "author_inst": "University of Nottingham"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "neurology"
   },
   {
     "rel_doi": "10.1101/2021.03.09.21253183",
@@ -841219,115 +844874,55 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.08.21252839",
-    "rel_title": "Transmission of SARS-CoV-2 by children attending school. Interim report on an observational, longitudinal sampling study of infected children, contacts, and the environment",
+    "rel_doi": "10.1101/2021.03.08.21252200",
+    "rel_title": "Vaccine effectiveness after 1st and 2nd dose of the BNT162b2 mRNA Covid-19 Vaccine in long-term care facility residents and healthcare workers - a Danish cohort study",
     "rel_date": "2021-03-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21252839",
-    "rel_abs": "BackgroundAssessing transmission of SARS-CoV-2 by children in schools is of critical importance to inform public health action. We assessed frequency of acquisition of SARS-CoV-2 by contacts of children with COVID-19 in schools and households, as well as the amount of virus shed into the air and onto fomites in both settings.\n\nMethodsCases of COVID-19 in children in London schools were identified via notification. Weekly sampling for 3-4 weeks and PCR testing for SARS-CoV-2 of immediate classroom contacts (the \"bubble\"), non-bubble school contacts, and household contacts was undertaken supported by genome sequencing, along with surface and air sampling in the school and home environment.\n\nResultsWithin schools, secondary transmission was not detected in 28 individual bubble contacts, representing 10 distinct bubble classes. Across 8 non-bubble classes, 3/62 pupils tested positive- all three were asymptomatic and tested positive in one setting on the same day, unrelated to the original index case. In contrast, the secondary attack rate in naive household contacts was 14.3% (5/35) rising to 19.1% (9/47) when considering all household contacts. Environmental contamination with SARS-CoV-2 was rare in schools, regardless of school type; fomite SARS-CoV-2 RNA was identified in 4/189 (2.1%) samples in bubble classrooms, 2/127 (1.6%) samples in non-bubble classrooms, and 5/130 (3.8%) samples in washrooms. This contrasted with fomites in households, where SARS-CoV-2 RNA was identified in 60/248 (24.2%) bedroom samples, 66/241 (27.4%) communal room samples, and 21/188 (11.2%) bathroom samples. Air sampling identified SARS-CoV-2 RNA in just 1/68 (1.5%) of school air samples, compared with 21/85 (24.7%) of air samples taken in homes.\n\nSummaryThe low levels of environmental contamination in schools are consistent with low transmission frequency and adequate levels of cleaning and ventilation in schools during the period of study. Secondary transmission in schools was rare. The high frequency of secondary transmission in households associated with evident viral shedding throughout the home suggests a need to improve advice to households with infection in children in order to prevent onward community spread by sibling and adult contacts. The data highlight that transmission from children is very likely to occur when precautions are reduced.",
-    "rel_num_authors": 24,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21252200",
+    "rel_abs": "BackgroundAt the end of 2020, Denmark launched an immunization program against SARS-CoV-2. The Danish health authorities prioritized persons currently living in long-term care facilities (LTCF residents) and frontline healthcare workers (HCW) as the first receivers of vaccination. Here we present preliminary population based vaccine effectiveness (VE) estimates in these two target groups.\n\nMethodsThe study was designed as a retrospective registry- and population-based observational cohort study including all LTCF residents and all HWC. The outcome was a polymerase chain reaction confirmed SARS-CoV-2, and VE was estimated for different periods following first and second dose. We used Poisson and Cox regressions to estimate respectively crude and calendar time-adjusted VE for the BNT162b2 mRNA Covid-19 Vaccine from Pfizer/BioNTech with 95% confidence intervals (CI) for vaccinated versus unvaccinated.\n\nResultsA total of 39,040 LTCF residents (median age at first dose; 84 years, Interquartile range (IQR): 77-90) and 331,039 HCW (median age at first dose; 47 years, IQR: 36-57) were included. Among LTCF residents, 95.2% and 86.0% received first and second dose from 27 December 2020 until 18 February 2021, for HWC the proportion was 27.8% and 24.4%. During a median follow-up of 53 days, there were 488 and 5,663 confirmed SARS-CoV-2 cases in the unvaccinated groups, whereas there were 57 and 52 in LTCF residents and HCW within the first 7 days after the second dose and 27 and 10 cases beyond seven days of second dose. No protective effect was observed for LTCF residents after first dose. In HCW, VE was 17% (95% CI; 4-28) in the > 14 days after first dose (before second dose). Furthermore, the VE in LTCF residents at day 0-7 of second dose was 52% (95% CI; 27-69) and 46% (95% CI; 28-59) in HCW. Beyond seven days of second dose, VE increased to 64% (95% CI; 14-84) and 90% (95% CI; 82-95) in the two groups, respectively.\n\nConclusionThe results were promising regarding the VE both within and beyond seven days of second vaccination with the BNT162b2 mRNA Covid-19 Vaccine currently used in many countries to help mitigate the global SARS-CoV-2 pandemic.\n\nImpact of the researchSo far, observational studies of the real-word effectiveness of the mRNA Vaccine BNT162b2 has been limited to the period after the administration of the first dose. This is the first report to date to present vaccine effectiveness (VE) estimates after the second BNT162b2 mRNA Covid-19 Vaccine. We estimated a VE of 52% and 46% in LTCF residents and HCW within seven days, which increased to 64% and 90% in the two groups respectively beyond seven days of immunization. These findings supports maintaining a two-dose schedule of the BNT162b2 mRNA Covid-19 Vaccine.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Rebecca Cordery",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Lucy Reeves",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Jie Zhou",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Aileen G. Rowan",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Patricia Watber",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Carolina Rosadas",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Michael Andrew Crone",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Marko Storch",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Paul Freemont",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Lucy Mosscrop",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Alice Cowley",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Gina Zelent",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Kate Bisset",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Holly LeBlond",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Sadie Regmi",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Christian Buckingham",
-        "author_inst": "Imperial College London"
+        "author_name": "Ida Rask Moustsen-Helms",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Ramlah Junaideen",
-        "author_inst": "Imperial College London"
+        "author_name": "Hanne-Dorthe Emborg",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Nadia Abdulla",
-        "author_inst": "Imperial College London"
+        "author_name": "Jens Nielsen",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Joseph Eliahoo",
-        "author_inst": "Imperial College London"
+        "author_name": "Katrine Finderup Nielsen",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Miranda Mindlin",
-        "author_inst": "Public Health England"
+        "author_name": "Tyra Grove Krause",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Theresa Lamagni",
-        "author_inst": "Public Health England"
+        "author_name": "Kaare Molbak",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Wendy Barclay",
-        "author_inst": "Imperial College London"
+        "author_name": "Karina Lauenborg Moeller",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Graham P Taylor",
-        "author_inst": "Imperial College London"
+        "author_name": "Ann-Sofie Nicole Berthelsen",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Shiranee Sriskandan",
-        "author_inst": "Imperial College London"
+        "author_name": "Palle Valentiner-Branth",
+        "author_inst": "Staten Serum Institut"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.03.02.21252722",
@@ -843717,31 +847312,71 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.03.06.434059",
-    "rel_title": "Structural Analysis of Spike Protein Mutations in an Emergent SARS-CoV-2 Variant from the Philippines",
+    "rel_doi": "10.1101/2021.03.08.434390",
+    "rel_title": "Identification of novel bat coronaviruses sheds light on the evolutionary origins of SARS-CoV-2 and related viruses",
     "rel_date": "2021-03-08",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.06.434059",
-    "rel_abs": "A SARS-CoV-2 lineage designated as P.3 with multiple signature mutations in the Spike protein region was recently reported with cases from the Central Visayas Region of the Philippines. Whole genome sequencing revealed that the 33 samples under this lineage all contain the E484K, N501Y, and P681H Spike mutations previously found in variants of concern (VOC) such as the B.1.351, the P.1 and B.1.1.7 variants first reported in South Africa, Brazil, and the United Kingdom, respectively. The possible implications of the mutations found in the Spike protein of P.3 were analyzed for their potential effects on structure, stability, and molecular surface character. The analysis suggests that these mutations could significantly impact the possible interactions of the Spike protein with the ACE2 receptor and neutralizing antibodies, and warrants further clinical investigation. Some of the mutations affecting the N and C terminal domains may have effects on Spike monomer and trimer stability. This report provides insights on relevant targets for the design of future diagnostics, therapeutics and vaccines against the evolving SARS-CoV-2 variants in the Philippines.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.08.434390",
+    "rel_abs": "Although a variety of SARS-CoV-2 related coronaviruses have been identified, the evolutionary origins of this virus remain elusive. We describe a meta-transcriptomic study of 411 samples collected from 23 bat species in a small (~1100 hectare) region in Yunnan province, China, from May 2019 to November 2020. We identified coronavirus contigs in 40 of 100 sequencing libraries, including seven representing SARS-CoV-2-like contigs. From these data we obtained 24 full-length coronavirus genomes, including four novel SARS-CoV-2 related and three SARS-CoV related genomes. Of these viruses, RpYN06 exhibited 94.5% sequence identity to SARS-CoV-2 across the whole genome and was the closest relative of SARS-CoV-2 in the ORF1ab, ORF7a, ORF8, N, and ORF10 genes. The other three SARS-CoV-2 related coronaviruses were nearly identical in sequence and clustered closely with a virus previously identified in pangolins from Guangxi, China, although with a genetically distinct spike gene sequence. We also identified 17 alphacoronavirus genomes, including those closely related to swine acute diarrhea syndrome virus and porcine epidemic diarrhea virus. Ecological modeling predicted the co-existence of up to 23 Rhinolophus bat species in Southeast Asia and southern China, with the largest contiguous hotspots extending from South Lao and Vietnam to southern China. Our study highlights both the remarkable diversity of bat viruses at the local scale and that relatives of SARS-CoV-2 and SARS-CoV circulate in wildlife species in a broad geographic region of Southeast Asia and southern China. These data will help guide surveillance efforts to determine the origins of SARS-CoV-2 and other pathogenic coronaviruses.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Neil Andrew David Bascos",
-        "author_inst": "University of the Philippines Diliman"
+        "author_name": "Hong Zhou",
+        "author_inst": "Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of"
       },
       {
-        "author_name": "Denise Mirano-Bascos",
-        "author_inst": "University of the Philippines Diliman"
+        "author_name": "Jingkai Ji",
+        "author_inst": "Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of"
       },
       {
-        "author_name": "Cynthia Palmes Saloma",
-        "author_inst": "University of the Philippines"
+        "author_name": "Xing Chen",
+        "author_inst": "Landscape Ecology Group, Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences,Menglun, Mengla, Yunnan 66630"
+      },
+      {
+        "author_name": "Yuhai Bi",
+        "author_inst": "CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, CAS Center for Influenza Research and Early-warning (CASCIRE), CAS-TWAS"
+      },
+      {
+        "author_name": "Juan Li",
+        "author_inst": "Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of"
+      },
+      {
+        "author_name": "Tao Hu",
+        "author_inst": "Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of"
+      },
+      {
+        "author_name": "Hao Song",
+        "author_inst": "Research Network of Immunity and Health (RNIH), Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China"
+      },
+      {
+        "author_name": "Yanhua Chen",
+        "author_inst": "Landscape Ecology Group, Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences,Menglun, Mengla, Yunnan 66630"
+      },
+      {
+        "author_name": "Mingxue Cui",
+        "author_inst": "Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of"
+      },
+      {
+        "author_name": "Yanyan Zhang",
+        "author_inst": "Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of"
+      },
+      {
+        "author_name": "Alice C. Hughes",
+        "author_inst": "Landscape Ecology Group, Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences,Menglun, Mengla, Yunnan 66630"
+      },
+      {
+        "author_name": "Edward C. Holmes",
+        "author_inst": "Marie Bashir Institute for Infectious Diseases and Biosecurity, School of Life and Environmental Sciences and School of Medical Sciences, The University of Sydn"
+      },
+      {
+        "author_name": "Weifeng Shi",
+        "author_inst": "Key Laboratory of Etiology and Epidemiology of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "biophysics"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.03.08.434363",
@@ -845235,61 +848870,161 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.04.21252658",
-    "rel_title": "SARS-CoV-2-specific T Cell Memory is Sustained in COVID-19 Convalescents for 8 Months with Successful Development of Stem Cell-like Memory T Cells",
+    "rel_doi": "10.1101/2021.03.04.21252528",
+    "rel_title": "Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England",
     "rel_date": "2021-03-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.04.21252658",
-    "rel_abs": "Memory T cells contribute to rapid viral clearance during re-infection, but the longevity and differentiation of SARS-CoV-2-specific memory T cells remain unclear. We conducted direct ex vivo assays to evaluate SARS-CoV-2-specific CD4+ and CD8+ T cell responses in COVID-19 convalescents up to 254 days post-symptom onset (DPSO). Here, we report that memory T cell responses were maintained during the study period. In particular, we observed sustained polyfunctionality and proliferation capacity of SARS-CoV-2-specific T cells. Among SARS-CoV-2-specific CD4+ and CD8+ T cells detected by activation-induced markers, the proportion of stem cell-like memory T (TSCM) cells increased, peaking at approximately 120 DPSO. Development of TSCM cells was confirmed by SARS-CoV-2-specific MHC-I multimer staining. Considering the self-renewal capacity and multipotency of TSCM cells, our data suggest that SARS-CoV-2-specific T cells are long-lasting after recovery from COVID-19. The current study provides insight for establishing an effective vaccination program and epidemiological measurement.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.04.21252528",
+    "rel_abs": "The B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (HR: 1.67 (95% CI: 1.34 - 2.09; P<.0001). Absolute risk of death by 28-days increased with age and comorbidities. VOC has potential to spread faster with higher mortality than the pandemic to date.",
+    "rel_num_authors": 36,
     "rel_authors": [
       {
-        "author_name": "Jae Hyung Jung",
-        "author_inst": "Korea Advanced Institute of Science and Technology"
+        "author_name": "Daniel J Grint",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
       },
       {
-        "author_name": "Min-Seok Rha",
-        "author_inst": "Korea Advanced Institute of Science and Technology"
+        "author_name": "Kevin Wing",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
       },
       {
-        "author_name": "Moa Sa",
-        "author_inst": "Korea Advanced Institute of Science and Technology"
+        "author_name": "Elizabeth Williamson",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
       },
       {
-        "author_name": "Hee Kyoung Choi",
-        "author_inst": "Korea University College of Medicine, Ansan Hospital"
+        "author_name": "Helen I McDonald",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
       },
       {
-        "author_name": "Ji Hoon Jeon",
-        "author_inst": "Korea University College of Medicine, Ansan Hospital"
+        "author_name": "Krishnan Bhaskaran",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
       },
       {
-        "author_name": "Hyeri Seok",
-        "author_inst": "Korea University College of Medicine, Ansan Hospital"
+        "author_name": "David Evans",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
       },
       {
-        "author_name": "Dae Won Park",
-        "author_inst": "Korea University College of Medicine, Ansan Hospital"
+        "author_name": "Stephen JW Evans",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
       },
       {
-        "author_name": "Su-Hyung Park",
-        "author_inst": "Korea Advanced Institute of Science and Technology"
+        "author_name": "Alex J Walker",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
       },
       {
-        "author_name": "Hye Won Jeong",
-        "author_inst": "Chungbuk National University College of Medicine"
+        "author_name": "George Hickman",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
       },
       {
-        "author_name": "Won Suk Choi",
-        "author_inst": "Korea University College of Medicine, Ansan Hospital"
+        "author_name": "Emily Nightingale",
+        "author_inst": "Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, UK"
       },
       {
-        "author_name": "Eui-Cheol Shin",
-        "author_inst": "Korea Advanced Institute of Science and Technology"
+        "author_name": "Anna Schultze",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Christopher T Rentsch",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Chris Bates",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK"
+      },
+      {
+        "author_name": "Jonathan Cockburn",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK"
+      },
+      {
+        "author_name": "Helen J Curtis",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Caroline E Morton",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Sebastian Bacon",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Simon Davy",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Angel YS Wong",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Amir Mehrkar",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Laurie Tomlinson",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Ian J Douglas",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Rohini Mathur",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Paula Blomquist",
+        "author_inst": "COVID-19 Outbreak Surveillance Team, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Brian MacKenna",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Peter Ingelsby",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Richard Croker",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "John Parry",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK"
+      },
+      {
+        "author_name": "Frank Hester",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK"
+      },
+      {
+        "author_name": "Sam Harper",
+        "author_inst": "TPP, TPP House, 129 Low Lane, Horsforth, Leeds, UK"
+      },
+      {
+        "author_name": "Nicolas J DeVito",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Will Hulme",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "John Tazare",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Ben Goldacre",
+        "author_inst": "The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, UK"
+      },
+      {
+        "author_name": "Liam Smeeth",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
+      },
+      {
+        "author_name": "Rosalind M Eggo",
+        "author_inst": "Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, UK"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -847069,23 +850804,51 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2021.03.06.21253058",
-    "rel_title": "Low Dose Regimens of BNT162b2 mRNA Vaccine Exceed SARS-Cov-2 Correlate of Protection Estimates for Symptomatic Infection, in those 19-55 Years of Age",
+    "rel_doi": "10.1101/2021.03.06.21252964",
+    "rel_title": "Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data",
     "rel_date": "2021-03-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.06.21253058",
-    "rel_abs": "BackgroundAn exact correlate of protection (CoP) is not yet known for symptomatic COVID-19. However, it is still possible to show a new vaccine regimen exceeds an unknown CoP, provided the regimen shows an equivalent or greater immunological response in all measured indicators relative to the immunological response elicited by a clinically proven vaccine regimen. The principle of comparing immunogenicity between regimens is what the FDA, EMA, and Access Consortium use to authorize modifications to the vaccines for VOC, without requiring clinical efficacy studies before implementation. It is logical to apply the same principle to modifying vaccine doses if the data is available to do so. A two dose 30ug regimen of BNT162b2 has strong clinical evidence of efficacy, as does a single dose 30 ug regimen. The immunological markers for these regimens have been profiled in detail in Phase 1 and 2 trial data.\n\nMethodsThe immunological profile (including binding antibodies, viral neutralization, cytokine profiles, and CD4 and 8 expansion) of the 2 dose 30ug BNT162b2 vaccine is examined, referred to as a highly conservative CoP estimate. The single dose 30 ug BNT162b2 immunological profile is also examined, a tenable CoP estimate. Data from the phase 1 and 2 trials are examined to see if alternate regimens meet or exceed the level of each immune marker measured, relative to the regimens listed above that have proven clinical efficacy.\n\nResultsFor adults aged 19-55, a 2 dose 10ug BNT162b2 regimen elicits a comparable response to the standard 30 ug dose for each immune indicator, with viral neutralization nearly an order of magnitude greater than the tenable CoP estimate. Similarly, a single dose 10ug BNT 162b2 regimen or a two dose 1ug BNT 162b2 regimen equals or exceeds the immunogenicity of a single 30 ug dose.\n\nConclusionIf it is reasonable for the FDA, EMA, and Access Consortium to approve vaccine modifications without a clinical trial based on immunogenicity data, three alternate low dose regimens were identified that meet the requirements of having comparable immunogenicity relative to a protocol that has proven clinical efficacy. Immediate implementation of these lower dose regimens should be considered as they have major implications in alleviating vaccine supply, as well as improving vaccine side effect profile, and lowering total cost of vaccination.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.06.21252964",
+    "rel_abs": "BackgroundSchools have been closed in England since the 4th of January 2021 as part of the national restrictions to curb transmission of SARS-CoV-2. The UK Government plans to reopen schools on the 8th of March. Although there is evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings are not clear.\n\nMethodsWe measured social contacts when schools were both open or closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number.\n\nResultsOur results suggest that reopening all schools could increase R from an assumed baseline of 0.8 to between 1.0 and 1.5, or to between 0.9 and 1.2 reopening primary or secondary schools alone.\n\nConclusionOur results suggest that reopening schools is likely to halt the fall in cases observed in recent months and risks returning to rising infections, but these estimates rely heavily on the current estimates or reproduction number and the current validity of the susceptibility and infectiousness profiles we use.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Graham Jurgens",
-        "author_inst": "Unaffiliated"
+        "author_name": "James D Munday",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Christopher I Jarvis",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Amy Gimma",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Kerry LM Wong",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Kevin van Zandvoort",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "- CMMID COVID-19 Working Group",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Sebastian Funk",
+        "author_inst": "London School of Hygiene & Tropical Medicine"
+      },
+      {
+        "author_name": "W. John Edmunds",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.03.07.21252972",
@@ -849147,59 +852910,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.03.02.21252766",
-    "rel_title": "Self-reported symptoms, self-reported viral testing result and seroprevalence of SARS CoV-2 among a community sample in Essex County New Jersey: A brief report.",
+    "rel_doi": "10.1101/2021.03.03.21252809",
+    "rel_title": "Sharing positive changes made during COVID-19 national lockdown: a multi-method co-production study",
     "rel_date": "2021-03-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252766",
-    "rel_abs": "BackgroundSARS-CoV-2, the virus that causes COVID-19, has rapidly spread globally beginning in late 2019. Early areas impacted by this pandemic in the US include Essex County, New Jersey. Beyond understanding the prevalence of active infections and deaths, it is important to understand the true burden of infection in the community, as indicated by seroprevalence of antibodies directed to the virus. Understanding the spectrum of disease is key to the effectiveness of primary prevention and control measures and the design of interventions against transmission of infection.\n\nMethodsWe utilized venue-based-sampling (VBS), implemented by a community partner, to sample members of the community in Essex County. In VBS the venues are randomized as a proxy for randomizing the attendees of the venues. We asked standard demographic questions, questions about symptoms and PCR testing and previous antibody testing. Participants provide a blood sample collected by finger stick with the Neoteryx Mitra Collection device. Samples were tested using a novel ELISA based approached developed by our team.\n\nResultsFrom September 15, 2020 to December 22, 2020, we conducted 92 randomly selected sampling events where we approached 1349 individuals for screening. Of these, 924 consented and had complete data for analysis. Only 6.5% of the sample reported any COVID-19 like symptoms while 45.9% had sought out a COVID-19 test. In total 13 (1.4%) participants received a positive SARS-CoV-2 PCR test result. While 33 participants (2.6%) sought a SARS-CoV-2 antibody test, only 0.5% of the sample reported a positive antibody result. Testing in this study identified 83 (9.0%) participants positive for SARS-CoV-2 antibodies.\n\nConclusionWe recruited a large sample of the population of Essex County, New Jersey using VBS, electronic surveys, novel sample collection and lab methods. Our findings suggest that the burden of SARS-Cov-2 is slightly more than six times than that suggested by PCR testing. This burden is higher than most estimates obtained through studies of remnant blood samples from hospitals (4.2%), samples from staff at a public-school system (2.9%), and residents of a California county recruited with targeted Facebook ads (1.5%). (9-11) Moreover, with only 6.5% of the sample reporting any COVID-19-like symptoms, our finding suggests that the number of asymptomatic persons may be close to 1.5 times greater than anyone reporting symptoms.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.03.21252809",
+    "rel_abs": "ObjectiveA multi-method co-production study was designed to share psychosocial insights into the adoption of positive changes made during COVID-19 national lockdown in Scotland. We examined: i) the psychosocial patterning of positive changes, ii) the psychosocial processes by which positive change was realised, and worked with partner organizations to share our insights.\n\nMethodsA sequential multi-method design included an online survey (n=2445) assessing positive changes in sleep and physical activity patterns, socio-demographics, mood, social support, coping, and resilience, with multivariate logistic regression analysis. We also employed interviews with a purposive diverse sub-sample of people self-reporting high levels of positive change (n=48) and used thematic analysis. Finally, partnership work translated insights into positive change-sharing targeted resources.\n\nResultsThe survey identified positive change was significantly patterned by age, gender and vulnerability to COVID-19. Higher positive reframing and higher active coping were associated with higher levels of cross-domain positive change. Higher symptoms of depression, planning, and self-distraction were associated with less cross-domain positive change. Thematic analysis showed the centrality of perceptions of time, opportunities to self-reflect and engage with the natural world, access support in diverse ways, actively build routine and purposefully build self-efficacy and a sense of control were key to initiating positive change. Our partner organizations focused on the rapid co-production of a series of online resources that shared study insights.\n\nConclusionsOur study, based around a salutogenic ethos and the constraints of COVID-19, sought to identify and share insights into achieving positive changes at a time of international crisis.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Henry F Raymond",
-        "author_inst": "School of Public Health, Rutgers University"
-      },
-      {
-        "author_name": "Pratik Datta",
-        "author_inst": "Public Health Research Institute, New Jersey Medical School, Rutgers University, Newark NJ"
+        "author_name": "Lynn Williams",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Rahul Ukey",
-        "author_inst": "Public Health Research Institute, New Jersey Medical School, Rutgers University, Newark NJ"
+        "author_name": "Bradley MacDonald",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Peng Wang",
-        "author_inst": "School of Public Health, Rutgers University, Piscataway, NJ"
+        "author_name": "Lesley Rollins",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Richard J Martino",
-        "author_inst": "School of Public Health, Rutgers University, Piscataway, NJ"
+        "author_name": "Xanne Janssen",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Kristen D Krause",
-        "author_inst": "School of Public Health, Rutgers University, Piscataway, NJ"
+        "author_name": "Leanne Fleming",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Corey Rosmarin-DeStefano",
-        "author_inst": "North Jersey Community Research Initiative, Newark, NJ"
+        "author_name": "Madeleine Grealy",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Abraham Pinter",
-        "author_inst": "Public Health Research Institute, New Jersey Medical School, Rutgers University, Newark NJ"
+        "author_name": "Alison Kirk",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Perry N Halkitis",
-        "author_inst": "School of Public Health, Rutgers University, Piscataway, NJ"
+        "author_name": "David Young",
+        "author_inst": "University of Strathclyde"
       },
       {
-        "author_name": "Maria L Gennaro",
-        "author_inst": "Public Health Research Institute, New Jersey Medical School, Rutgers University, Newark NJ"
+        "author_name": "Paul Flowers",
+        "author_inst": "University of Strathclyde"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.03.02.21252777",
@@ -850885,75 +854644,27 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.03.05.434152",
-    "rel_title": "Scalable, Micro-Neutralization Assay for Qualitative Assessment of SARS-CoV-2 (COVID 19) Virus-Neutralizing Antibodies in Human Clinical Samples",
+    "rel_doi": "10.1101/2021.03.05.434119",
+    "rel_title": "SARS-CoV-2-host chimeric RNA-sequencing reads do not necessarily signify virus integration into the host DNA",
     "rel_date": "2021-03-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.05.434152",
-    "rel_abs": "As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic was expanding, it was clear that effective testing for the presence of neutralizing antibodies in the blood of convalescent patients would be critical for development of plasma-based therapeutic approaches. To address the need for a high-quality neutralization assay against SARS-CoV-2, a previously established fluorescence reduction neutralization assay (FRNA) against Middle East respiratory syndrome coronavirus (MERS-CoV) was modified and optimized. The SARS-CoV-2 FRNA provides a quantitative assessment of a large number of infected cells through use of a high-content imaging system. Because of this approach, and the fact that it does not involve subjective interpretation, this assay is more efficient and more accurate than other neutralization assays. In addition, the ability to set robust acceptance criteria for individual plates and specific test wells provided further rigor to this assay. Such agile adaptability avails use with multiple virus variants. By February 2021, the SARS-CoV-2 FRNA had been used to screen over 5,000 samples, including acute and convalescent plasma or serum samples and therapeutic antibody treatments, for SARS-CoV-2 neutralizing titers.",
-    "rel_num_authors": 14,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.05.434119",
+    "rel_abs": "The human genome bears evidence of extensive invasion by retroviruses and other retroelements, as well as by diverse RNA and DNA viruses. High frequency of somatic integration of the RNA virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into the DNA of infected cells was recently suggested, partly based on the detection of chimeric RNA-sequencing (RNA-seq) reads between SARS-CoV-2 RNA and RNA transcribed from human host DNA. Here, we examined the possible origin of human-SARS-CoV-2 chimeric reads in RNA-seq libraries and provide alternative explanations for their origin. Chimeric reads were frequently detected also between SARS-CoV-2 RNA and RNA transcribed from mitochondrial DNA or episomal adenoviral DNA present in transfected cell lines, which was unlikely the result of SARS-CoV-2 integration. Furthermore, chimeric reads between SARS-CoV-2 RNA and RNA transcribed from nuclear DNA was highly enriched for host exonic, than intronic or intergenic sequences and often involved the same, highly expressed host genes. These findings suggest that human-SARS-CoV-2 chimeric reads found in RNA-seq data may arise during library preparation and do not necessarily signify SARS-CoV-2 reverse transcription, integration in to host DNA and further transcription.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Michael R Holbrook",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Richard S Bennett",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Elena N Postnikova",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Janie Liang",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Robin Gross",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Dawn Gerhardt",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Shalamar Georgia-Clark",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Yingyun Cai",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Shuiqinq Yu",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Lindsay Marron",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Greg Kocher",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Steven Mazur",
-        "author_inst": "NIAID IRF-Frederick"
-      },
-      {
-        "author_name": "Saurabh Dixit",
-        "author_inst": "NIAID IRF-Frederick"
+        "author_name": "Anastasiya Kazachenka",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Vladimir V Lukin",
-        "author_inst": "Kearney"
+        "author_name": "George Kassiotis",
+        "author_inst": "The Francis Crick Institute"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.03.03.433675",
@@ -852843,193 +856554,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.03.02.21252420",
-    "rel_title": "Delayed rise of oral fluid antibodies, elevated BMI, and absence of early fever correlate with longer time to SARS-CoV-2 RNA clearance in an longitudinally sampled cohort of COVID-19 outpatients",
+    "rel_doi": "10.1101/2021.03.01.21252243",
+    "rel_title": "On the Environmental Determinants of COVID-19 Seasonality",
     "rel_date": "2021-03-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252420",
-    "rel_abs": "BackgroundSustained molecular detection of SARS-CoV-2 RNA in the upper respiratory tract (URT) in mild to moderate COVID-19 is common. We sought to identify host and immune determinants of prolonged SARS-CoV-2 RNA detection.\n\nMethodsNinety-five outpatients self-collected mid-turbinate nasal, oropharyngeal (OP), and gingival crevicular fluid (oral fluid) samples at home and in a research clinic a median of 6 times over 1-3 months. Samples were tested for viral RNA, virus culture, and SARS-CoV-2 and other human coronavirus antibodies, and associations were estimated using Cox proportional hazards models.\n\nResultsViral RNA clearance, as measured by SARS-CoV-2 RT-PCR, in 507 URT samples occurred a median (IQR) 33.5 (17-63.5) days post-symptom onset. Sixteen nasal-OP samples collected 2-11 days post-symptom onset were virus culture positive out of 183 RT-PCR positive samples tested. All participants but one with positive virus culture were negative for concomitant oral fluid anti-SARS-CoV-2 antibodies. The mean time to first antibody detection in oral fluid was 8-13 days post-symptom onset. A longer time to first detection of oral fluid anti-SARS-CoV-2 S antibodies (aHR 0.96, 95% CI 0.92-0.99, p=0.020) and BMI [&ge;] 25kg/m2 (aHR 0.37, 95% CI 0.18-0.78, p=0.009) were independently associated with a longer time to SARS-CoV-2 viral RNA clearance. Fever as one of first three COVID-19 symptoms correlated with shorter time to viral RNA clearance (aHR 2.06, 95% CI 1.02-4.18, p=0.044).\n\nConclusionsWe demonstrate that delayed rise of oral fluid SARS-CoV-2-specific antibodies, elevated BMI, and absence of early fever are independently associated with delayed URT viral RNA clearance.",
-    "rel_num_authors": 44,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.01.21252243",
+    "rel_abs": "Viral respiratory diseases (VRDs), such as influenza and COVID-19, are thought to spread faster over winter than during summer. It has been previously argued that cold and dry conditions were more conducive to the transmission of VRD than warm and humid climates, although this relationship appears restricted to temperate regions, and the causal relationship is not well understood. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19 has emerged as a serious global public health problem after the first COVID-19 reports in Wuhan, China, in late 2019. It is still unclear whether this novel respiratory disease will ultimately prove to be a seasonal endemic disease. Here, we suggest that Air Drying Capacity (ADC; an atmospheric state-variable known to control the fate/evolution of the virus-laden droplets) and ultraviolet radiation (UV) are probable environmental determinants in shaping the transmission of COVID-19 at the seasonal time scale. These variables, unlike temperature and humidity, provide a physically-based framework consistent with the apparent seasonal variability in COVID-19 prevalence across a broad range of climates (e.g., Germany and India). Since this disease is known to be influenced by the compounding effect of social, biological, and environmental determinants, this study does not claim that these environmental determinants exclusively shape the seasonality of COVID-19. However, we argue that ADC and UV play a significant role in COVID-19 dynamics at the seasonal scale. These findings could help guide the development of a sound adaptation strategy against the pandemic over the coming seasons.\n\nPlain Language SummaryThere is growing scientific interest in the potential seasonality of COVID-19 and its links to climate variables. This study aims to determine whether four environmental variables, namely temperature, humidity, Air Drying Capacity (ADC), and ultraviolet radiation (UV), are probable environmental determinants for the observed seasonal dynamics of COVID-19 prevalence, based on extensive country-level data spanning the first year of the pandemic. Although the influence of socio-economic factors may be dominant, we here suggest that ADC and UV are key environmental determinants of COVID-19 and can potentially affect the transmission and seasonality of the disease across a wide range of climates.\n\nKey PointsO_LIThe seasonality of COVID-19 appears to follow seasonality of some environmental variables.\nC_LIO_LISeasonality of air drying capacity and ultraviolet radiation consistently match seasonality of COVID-19, across climatic zones.\nC_LIO_LISeasonality of air humidity and temperature, match seasonality of COVID-19 in temperate climates, but not in tropical monsoon climates.\nC_LI",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Annukka A. R. Antar",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Tong Yu",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Nora Pisnic",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Medicine"
-      },
-      {
-        "author_name": "Razvan Azamfirei",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Jeffrey A Tornheim",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Diane M. Brown",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Kate Kruczynski",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Justin P. Hardick",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Thelio Sewell",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Minyoung Jang",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Taylor Church",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Samantha N. Walch",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Carolyn Reuland",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Vismaya S. Bachu",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Kirsten Littlefield",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Han-Sol Park",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Rebecca L. Ursin",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Abhinaya Ganesan",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Oyinkansola Kusemiju",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Brittany Barnaba",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Curtisha Charles",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Michelle Prizzi",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Jaylynn R. Johnstone",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Christine Payton",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Weiwei Dai",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Joelle Fuchs",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Guido Massaccesi",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Derek T. Armstrong",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Jennifer L. Townsend",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Sara C. Keller",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Zoe O Demko",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Chen Hu",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Mei-Cheng Wang",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Lauren M. Sauer",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Heba H. Mostafa",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Jeanne C. Keruly",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Shruti H. Mehta",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Sabra L. Klein",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Andrea L. Cox",
-        "author_inst": "The Johns Hopkins University School of Medicine"
-      },
-      {
-        "author_name": "Andrew Pekosz",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Christopher D. Heaney",
-        "author_inst": "The Johns Hopkins University Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "David L. Thomas",
-        "author_inst": "The Johns Hopkins University School of Medicine"
+        "author_name": "Yeon-Woo Choi",
+        "author_inst": "Massachusetts Institute of Technology"
       },
       {
-        "author_name": "Paul W. Blair",
-        "author_inst": "The Johns Hopkins University School of Medicine"
+        "author_name": "Alexandre Tuel",
+        "author_inst": "Massachusetts Institute of Technology"
       },
       {
-        "author_name": "Yukari C. Manabe",
-        "author_inst": "The Johns Hopkins University School of Medicine"
+        "author_name": "Elfatih A. B. Eltahir",
+        "author_inst": "Massachusetts Institute of Technology"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -855217,37 +858764,41 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.23.21252328",
-    "rel_title": "SARS-CoV-2 antibodies detected in human breast milk post-vaccination",
+    "rel_doi": "10.1101/2021.02.26.21252555",
+    "rel_title": "Introductions and evolutions of SARS-CoV-2 strains in Japan",
     "rel_date": "2021-03-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252328",
-    "rel_abs": "ImportanceThe SARS-CoV-2 pandemic has infected over a hundred million people worldwide, with almost 2.5 million deaths at the date of this publication. In the United States, Pfizer-BioNTech and Moderna vaccines were first administered to the public starting in December 2020, and no lactating women were included in the initial trials of safety/efficacy. Research on SARS-CoV-2 vaccination in lactating women and the potential transmission of passive immunity to the infant through breast milk is needed to guide patients, clinicians and policy makers during the worldwide effort to curb the spread of this virus.\n\nObjectiveTo determine whether SARS-CoV-2 specific immunoglobins are found in breast milk post-vaccination, and to characterize the time course and types of immunoglobulins present.\n\nDesignProspective cohort study\n\nSettingProvidence Portland Medical Center, Oregon, USA\n\nParticipantsSix lactating women who planned to receive both doses of the Pfizer-BioNTech or Moderna vaccine between December 2020 and January 2021. Breast milk samples were collected pre-vaccination and at 11 additional timepoints, with last sample at 14 days post 2nd dose of vaccine.\n\nExposureTwo doses of Pfizer-BioNTech or Moderna SARS-CoV-2 vaccine.\n\nMain Outcome(s) and Measure(s)Levels of SARS-CoV-2 specific IgA and IgG immunoglobulins in breast milk.\n\nResultsIn this cohort of 6 lactating women who received 2 doses of SARS-CoV-2 vaccine, we observed significantly elevated levels of SARS-CoV-2 specific IgG and IgA antibodies in breast milk beginning at Day 7 after the initial vaccine dose, with an IgG-dominant response.\n\nConclusions and RelevanceWe are the first to show that maternal vaccination results in SARS-CoV-2 specific immunoglobulins in breast milk that may be protective for infants.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.26.21252555",
+    "rel_abs": "COVID-19 caused by SARS-CoV-2 was first identified in Japan on January 15th, 2020, soon after the pandemic originated in Wuhan, China. Subsequently, Japan experienced three distinct waves of the outbreak in the span of a year and has been attributed to new exogenous strains and evolving existing strains. Japan engaged very early on in tracking different COVID-19 sub-strains and have sequenced approximately 5% of all confirmed cases. While Japan has enforced stringent airport surveillance on cross-border travelers and returnees, some carriers appear to have advanced through the quarantine stations undetected. In this study, 17112 genomes sampled in Japan were analyzed to understand the strains, heterogeneity and temporal evolution of different SARS-CoV-2 strains. We identified 11 discrete strains with a substantial number of cases with most strains possessing the spike (S) D614G and nucleocapsid (N) 203_204delinsKR mutations. Besides these variants, ORF1ab P3371S, A4815V, S1361P, and N P151L were also detected in nearly half the samples constituting the most common strain in Japan. 115 distinct strains have been introduced into Japan and 12 of them were introduced after strict quarantine policy was implemented. In particular, the B.1.1.7 strain, that emerged in the United Kingdom (UK) in September 2020, has been circulating in Japan since late 2020 after eluding cross-border quarantine stations. Similarly, the B.1.351 strain dubbed the South African variant, P.1 Brazilian strain and R.1 strain with the spike E484K mutation have been detected in Japan. At least four exogenous B.1.1.7 sub-strains have been independently introduced in Japan as of late January 2021, and these strains carry mutations that give selective advantage including N501Y, H69_V70del, and E484K that confer increased transmissibility, reduced efficacy to vaccines and possible increased virulence. It is imperative that the quarantine policy be revised, cross-border surveillance reinforced, and new public health measures implemented to mitigate further transmission of this deadly disease and to identify strains that may engender resistance to vaccines.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Jill K Baird",
-        "author_inst": "Legacy Medical Group, Portland OR USA"
+        "author_name": "Reitaro Tokumasu",
+        "author_inst": "IBM Research - Tokyo"
+      },
+      {
+        "author_name": "Dilhan Weeraratne",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Shawn M Jensen",
-        "author_inst": "Earle A. Chiles Research Institute, Providence Cancer Institute, Providence Portland Medical Center, Portland, OR, USA"
+        "author_name": "Jane Snowdon",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Walter J Urba",
-        "author_inst": "Earle A. Chiles Research Institute, Providence Cancer Institute, Providence Portland Medical Center, Portland, OR, USA"
+        "author_name": "Laxmi Parida",
+        "author_inst": "IBM TJ Watson Research Center"
       },
       {
-        "author_name": "Bernard A Fox",
-        "author_inst": "Earle A. Chiles Research Institute, Providence Cancer Institute, Providence Portland Medical Center, Portland, OR, USA"
+        "author_name": "Michiharu Kudo",
+        "author_inst": "IBM Research - Tokyo"
       },
       {
-        "author_name": "Jason R Baird",
-        "author_inst": "Earle A. Chiles Research Institute, Providence Cancer Institute, Providence Portland Medical Center, Portland, OR, USA"
+        "author_name": "Takahiko Koyama",
+        "author_inst": "IBM TJ Watson Research Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -857219,31 +860770,27 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.03.01.21252598",
-    "rel_title": "Investigation of ventilation conditions associated with CO2 concentration changes in ultrasonographic exam room from the perspective of COVID-19 infection control",
+    "rel_doi": "10.1101/2021.03.01.21252330",
+    "rel_title": "Does Telemedicine Reduce health disparities? Longitudinal Evidence during the COVID-19 Pandemic in the US",
     "rel_date": "2021-03-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.01.21252598",
-    "rel_abs": "ObjectivesVentilation is an important factor in preventing COVID-19 infection. To clarify the state of ventilation in ultrasonic exam rooms, as an index of ventilation rate, the carbon dioxide (CO2) concentration in our exam rooms was measured.\n\nMethodsWe measured the CO2 concentration in each exam room before the examination and 0-15 minutes after end of the exam.\n\nThe subjects were 70 cases (abdomen: 24, breast: 16, neck: 16, and musculoskeletal: 14). In infant cases, one parent accompanied the patient during the examination.\n\nResultsThe highest CO2 concentration was 2261 ppm, observed after the breast examination. In all cases, the CO2 concentration in the exam room was highest immediately after the examination or two minutes after. Almost all cases had recovered to within 120% of the pre-examination CO2 concentrations within 15 minutes after the examination. The average CO2 concentration after ultrasonography was significantly higher for breast examinations than others.\n\nConclusionsEven in a hospital with modern ventilation equipment, the CO2 concentration in the ultrasound room was high after the exam and it takes 15 minutes to recover to the pre-exam state. Care must be taken to ensure adequate ventilation in ultrasonographic facilities.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.01.21252330",
+    "rel_abs": "ObjectiveThe COVID-19 pandemic could be a significant health issue for the elderly population and those with pre-excising chronic condition. In response to the pandemic health care services have increased the use of telehealth medicine. The propose of this study is to examine factors associated with access to telemedicine before and after COVID-19 based on sociodemographic factors and type of chronic disease.\n\nMethodWe have used data from the Research and Development Survey (RANDS) at two different time points Data collection for the first wave occurred between June 9, 2020 and July 6, 2020 (n= 6786), second wave was between August 3, 2020 and August 20, 2020 (n=5972). Three questions have been asked from the participant: 1) did the provider offer telemedicine before the pandemic? 2) does the provider offer telemedicine during the pandemic? And 3) have the participants schedule telemedicine appointments?\n\nResultIn both waves, 62 % of the participants reported providers did not have telemedicine services prior to the COVID-19 pandemic. However, we found a 22% increase in offering telemedicine in six first month of the COVID-19 pandemic. The finding shows almost no change in providing telemedicine between June and August. The data indicates just a 0.5% and 0.1% increase in accessing telemedicine, and scheduling in August than June, respectively. Patients older than 65 had higher access to telemedicine and had higher scheduling frequencies than other age groups, while they had the lowest access prior to the COVID-19. Blacks had the highest access to telemedicine services than other races (40%). Additionally, females, higher education, and living in metropolitan areas were associated with higher access and scheduling during the pandemic. There was a variation of access and scheduling in different chronic diseases, however, providers offered more remote services for those who diagnosed by diabetes.\n\nConclusionThe aim of telemedicine is to reduce disparities in healthcare access. The findings of this study show telemedicine has reduced racial disparities and provided greater accessibility for older groups. However, spatial and educational disparities are still noticeable. Research is necessary to examine how healthcare must address the socioeconomic heterogeneity in telemedicine by avoiding further disparities.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Roka Namoto Matsubayashi",
-        "author_inst": "National Hospital Organization Kyushu Medical Center"
-      },
-      {
-        "author_name": "Shino Harada",
-        "author_inst": "National Hospital Organization Kyushu Medical Center"
+        "author_name": "Ali Roghani",
+        "author_inst": "University of Utah"
       },
       {
-        "author_name": "Mitsuhiro Tominaga",
-        "author_inst": "National Hospital Organization Kyushu Medical Center"
+        "author_name": "Samin Panahi",
+        "author_inst": "University of Utah"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "category": "health systems and quality improvement"
   },
   {
     "rel_doi": "10.1101/2021.03.02.21252362",
@@ -858937,129 +862484,85 @@
     "category": "pharmacology and toxicology"
   },
   {
-    "rel_doi": "10.1101/2021.03.01.433314",
-    "rel_title": "Reduced antibody cross-reactivity following infection with B.1.1.7 than with parental SARS-CoV-2 strains",
+    "rel_doi": "10.1101/2021.02.27.433180",
+    "rel_title": "Negligible impact of SARS-CoV-2 variants on CD4+ and CD8+ T cell reactivity in COVID-19 exposed donors and vaccinees.",
     "rel_date": "2021-03-01",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.01.433314",
-    "rel_abs": "We examined the immunogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant B.1.1.7 that arose in the United Kingdom and spread globally. Antibodies elicited by B.1.1.7 infection exhibited significantly reduced recognition and neutralisation of parental strains or of the South Africa B.1.351 variant, than of the infecting variant. The drop in cross-reactivity was more pronounced following B.1.1.7 than parental strain infection, indicating asymmetric heterotypic immunity induced by SARS-CoV-2 variants.",
-    "rel_num_authors": 29,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.27.433180",
+    "rel_abs": "The emergence of SARS-CoV-2 variants highlighted the need to better understand adaptive immune responses to this virus. It is important to address whether also CD4+ and CD8+ T cell responses are affected, because of the role they play in disease resolution and modulation of COVID-19 disease severity. Here we performed a comprehensive analysis of SARS-CoV-2-specific CD4+ and CD8+ T cell responses from COVID-19 convalescent subjects recognizing the ancestral strain, compared to variant lineages B.1.1.7, B.1.351, P.1, and CAL.20C as well as recipients of the Moderna (mRNA-1273) or Pfizer/BioNTech (BNT162b2) COVID-19 vaccines. Similarly, we demonstrate that the sequences of the vast majority of SARS-CoV-2 T cell epitopes are not affected by the mutations found in the variants analyzed. Overall, the results demonstrate that CD4+ and CD8+ T cell responses in convalescent COVID-19 subjects or COVID-19 mRNA vaccinees are not substantially affected by mutations found in the SARS-CoV-2 variants.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Nikhil Faulkner",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Kevin Ng",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Mary Wu",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Ruth Harvey",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Saira Hussain",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Maria Greco",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "William Bolland",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Scott Warchal",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Marios Margaritis",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Stavroula Paraskevopoulou",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Judith Heaney",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Hannah Rickman",
-        "author_inst": "UCL"
+        "author_name": "Alison Tarke",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Catherine Houlihan",
-        "author_inst": "UCL"
+        "author_name": "John Sidney",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Moria Spyer",
-        "author_inst": "UCL"
+        "author_name": "Nils Methot",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Daniel Frampton",
-        "author_inst": "UCL"
+        "author_name": "Yun Zhang",
+        "author_inst": "J. Craig Venter Institute"
       },
       {
-        "author_name": "Matthew Byott",
-        "author_inst": "UCL"
+        "author_name": "Jennifer M Dan",
+        "author_inst": "La Jolla Institute for Immunology"
       },
       {
-        "author_name": "Tulio de Oliveira",
-        "author_inst": "University of KwaZulu-Natal,SA"
+        "author_name": "Benjamin Goodwin",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Alex Sigal",
-        "author_inst": "University of KwaZulu-Natal,SA"
+        "author_name": "Paul Rubiro",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Svend Kjaer",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Aaron Sutherland",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Charles Swanton",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Ricardo da Silva Antunes",
+        "author_inst": "La Jolla Institute for Immunology"
       },
       {
-        "author_name": "Sonia Gandhi",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "April Fraizer",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Rupert Beale",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Stephen A. Rawlings",
+        "author_inst": "University of California San Diego (UCSD)"
       },
       {
-        "author_name": "Steve Gamblin",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Davey M. Smith",
+        "author_inst": "University of California San Diego (UCSD)"
       },
       {
-        "author_name": "John Mccauley",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Bjoern Peters",
+        "author_inst": "La Jolla Institute for Immunology"
       },
       {
-        "author_name": "Rodney Daniels",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Richard H. Scheuermann",
+        "author_inst": "J. Craig Venter Institute"
       },
       {
-        "author_name": "Michael Howell",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Daniela Weiskopf",
+        "author_inst": "La Jolla Institute for Immunology"
       },
       {
-        "author_name": "David Bauer",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Shane Crotty",
+        "author_inst": "La Jolla Institute for immunology"
       },
       {
-        "author_name": "Eleni Nastouli",
-        "author_inst": "UCL"
+        "author_name": "Alba Grifoni",
+        "author_inst": "La Jolla Institute for Immunology"
       },
       {
-        "author_name": "George Kassiotis",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Alessandro Sette",
+        "author_inst": "La Jolla Institute for immunology"
       }
     ],
     "version": "1",
@@ -860555,51 +864058,35 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.02.25.21252451",
-    "rel_title": "Muscle Strength Explains the Protective Effect of Physical Activity against COVID-19 Hospitalization among Adults aged 50 Years and Older",
+    "rel_doi": "10.1101/2021.02.26.21252552",
+    "rel_title": "The Charitable Feeding System helps Food Insecure Participants maintain Fruit and Vegetable intake during COVID-19.",
     "rel_date": "2021-03-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.25.21252451",
-    "rel_abs": "ObjectivesPhysical activity has been proposed as a protective factor for COVID-19 hospitalization. However, the mechanisms underlying this association are unclear. Here, we examined the association between physical activity and COVID-19 hospitalization and whether this relationship was explained by other risk factors for severe COVID-19.\n\nMethodWe used data from adults aged 50 years and older from the Survey of Health, Ageing and Retirement in Europe. The outcome was self-reported hospitalization due to COVID-19 measured before August 2020. The main exposure was usual physical activity, self-reported between 2004 and 2017. Data were analyzed using logistic regression models.\n\nResultsAmong the 3139 participants included in the study (69.3 {+/-} 8.5 years, 1763 women), 266 were tested positive for COVID-19 and 66 were hospitalized. Results showed that individuals who engaged in physical activity more than once a week had lower odds of COVID-19 hospitalization than individuals who hardly ever or never engaged in physical activity (odds ratios = 0.41, 95% confidence interval = 0.22-0.74, p = .004). This association between physical activity and COVID-19 hospitalization was explained by muscle strength, but not by other risk factors.\n\nConclusionThese findings suggest that, after 50 years of age, engaging in physical activity more than once a week is associated with lower odds of COVID-19 hospitalization. The protective effect of physical activity on COVID-19 hospitalization is explained by muscle strength.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.26.21252552",
+    "rel_abs": "Charitable food services, including food banks and pantries, support individual and households food access, potentially maintaining food security and diet quality during emergencies. During the COVID-19 pandemic, the use of food banks and pantries has increased in the US. Here we examine perceptions of the charitable food system and its relationship to food security and dietary quality, specifically fruit and vegetable (FV) intake during the first six months of the COVID-19 pandemic, using a statewide representative survey (n=600) of residents of Vermont. We find that demand for charitable food services increased by 68%. The utilization of food pantries was more common among food insecure households and households with children. Among food insecure respondents, those who used the charitable food system were less likely to reduce their FV intake during the pandemic than those who did not use the charitable food system. Further, we find significant interactions between food pantry use and food insecure households, suggesting that, for food, insecure households, utilizing a food pantry since the onset of the COVID-19 pandemic was associated with higher fruit consumption. These results indicate that these services may support food access and diet quality for at-risk populations during emergencies.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Silvio Maltagliati",
-        "author_inst": "Universite Grenoble Alpes"
-      },
-      {
-        "author_name": "Stefan Sieber",
-        "author_inst": "University of Geneva"
-      },
-      {
-        "author_name": "Philippe Sarrazin",
-        "author_inst": "Universite Grenoble Alpes"
-      },
-      {
-        "author_name": "Stephane Cullati",
-        "author_inst": "University of Fribourg"
-      },
-      {
-        "author_name": "Aina Chalabaev",
-        "author_inst": "Universite Grenoble Alpes"
+        "author_name": "Farryl MW Bertmann",
+        "author_inst": "University of Vermont"
       },
       {
-        "author_name": "Gregoire P Millet",
-        "author_inst": "University of Lausanne"
+        "author_name": "Katherine Rogomentich",
+        "author_inst": "University of Vermont"
       },
       {
-        "author_name": "Matthieu P Boisgontier",
-        "author_inst": "University of Ottawa"
+        "author_name": "Emily H Belarmino",
+        "author_inst": "University of Vermont"
       },
       {
-        "author_name": "Boris Cheval",
-        "author_inst": "University of Geneva"
+        "author_name": "Meredith T. Niles",
+        "author_inst": "University of Vermont"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "sports medicine"
+    "category": "nutrition"
   },
   {
     "rel_doi": "10.1101/2021.02.27.21252569",
@@ -862057,125 +865544,81 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.23.21252319",
-    "rel_title": "Control of COVID-19 transmission on an urban university campus during a second wave of the pandemic",
+    "rel_doi": "10.1101/2021.02.23.21252299",
+    "rel_title": "The Public Health Impact of Delaying a Second Dose of the BNT162b2 or mRNA-1273 COVID-19 Vaccine",
     "rel_date": "2021-02-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252319",
-    "rel_abs": "ImportanceThe COVID-19 pandemic had a wide-ranging impact on educational institutions across the United States. Given potential financial challenges and adverse psychosocial effects of campus closure, as done in the spring of 2020 in response to the first wave, many institutions of higher education developed strategies to allow campuses to reopen and operate in the fall despite the ongoing threat of COVID-19. Many however opted to have limited campus re-opening in order to minimize potential risk of spread of SARS-CoV-2.\n\nObjectiveTo analyze how Boston University (BU) fully reopened its campus in the fall of 2020 and controlled COVID-19 transmission despite worsening transmission in the city of Boston.\n\nDesignMulti-faceted intervention case study.\n\nSettingLarge urban university campus.\n\nInterventionsThe BU response included a high-throughput SARS-CoV-2 PCR testing facility with capacity to delivery results in less than 24 hours; routine asymptomatic screening for COVID-19; daily health attestations; compliance monitoring and feedback; robust contact tracing, quarantine and isolation in on campus facilities; face mask use; enhanced hand hygiene; social distancing recommendations; de-densification of classrooms and public places; and enhancement of all building air systems.\n\nMain Outcomes and MeasuresBetween August and December 2020, BU conducted >500,000 COVID-19 tests and identified 719 individuals with COVID-19: 627 (87.2%) students, 11 (1.5%) faculty, and 212 (25.5%) staff. Overall, about 1.8% of the BU community tested positive. Infections among faculty and staff were mostly acquired off campus, while undergraduate infections were more likely acquired in non-classroom campus settings. Of 837 close contacts traced, 86 (10.3%) tested positive for COVID-19. BU contact tracers identified a source of transmission for 51.5% of cases with 55.7% identifying a source outside of BU. Among infected faculty and staff with a known source of infection, the majority reported a transmission source outside of BU (100% for faculty and 79.8% for staff).\n\nConclusions and RelevanceBU was successful in containing COVID-19 transmission on campus while minimizing off campus acquisition of COVID-19 from the greater Boston area. A coordinated strategy of testing, contact tracing, isolation and quarantine, with robust management and oversight, can control COVID-19 transmission, even in an urban university setting.",
-    "rel_num_authors": 27,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252299",
+    "rel_abs": "ObjectivesTo estimate population health outcomes under delayedsecond dose versus standard schedule SARS-CoV-2 mRNA vaccination.\n\nDesignAgent-based modeling on a simulated population of 100,000 based on a real-world US county. The simulation runs were replicated 10 times. To test the robustness of these findings, simulations were performed under different estimates for single-dose efficacy and vaccine administration rates, and under the possibility that a vaccine prevents only symptoms but not asymptomatic spread.\n\nSettingpopulation level simulation.\n\nParticipants100,000 agents are included in the simulation, with a representative distribution of demographics and occupations. Networks of contacts are established to simulate potentially infectious interactions though occupation, household, and random interactions\n\nInterventionswe simulate standard Covid-19 vaccination, versus delayed-second-dose vaccination prioritizing first dose. Sensitivity analyses include first-dose vaccine efficacy of 70%, 80% and 90% after day 12 post-vaccination; vaccination rate of 0.1%, 0.3%, and 1% of population per day; assuming the vaccine prevents only symptoms but not asymptomatic spread; and an alternative vaccination strategy that implements delayed-second-dose only for those under 65 years of age.\n\nMain outcome measurescumulative Covid-19 mortality over 180 days, cumulative infections and hospitalizations.\n\nResultsOver all simulation replications, the median cumulative mortality per 100,000 for standard versus delayed second dose was 226 vs 179; 233 vs 207; and 235 vs 236; for 90%, 80% and 70% first-dose efficacy, respectively. The delayed-second-dose strategy was optimal for vaccine efficacies at or above 80%, and vaccination rates at or below 0.3% population per day, both under sterilizing and non-sterilizing vaccine assumptions, resulting in absolute cumulative mortality reductions between 26 and 47 per 100,000. The delayed-second-dose for those under 65 performed consistently well under all vaccination rates tested.\n\nConclusionsA delayed-second-dose vaccination strategy, at least for those under 65, could result in reduced cumulative mortality under certain conditions.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Davidson H Hamer",
-        "author_inst": "Boston University School of Public Health"
-      },
-      {
-        "author_name": "Laura White",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Helen E Jenkins",
-        "author_inst": "Boston University School of Public Health"
-      },
-      {
-        "author_name": "christopher J gill",
-        "author_inst": "boston university school of public health"
-      },
-      {
-        "author_name": "Hannah N. Landsberg",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Catherine Klapperich",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Katia Bulekova",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Judy Platt",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Linette Decarie",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Wayne Gilmore",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Megan Pilkington",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Trevor L. McDowell",
-        "author_inst": "Boston University"
+        "author_name": "Santiago Romero-Brufau",
+        "author_inst": "Mayo Clinic, Harvard T. H. Chan School of Public Health"
       },
       {
-        "author_name": "Mark A. Fari",
-        "author_inst": "Boston University"
+        "author_name": "Ayush Chopra",
+        "author_inst": "Massachusetts Institute of Technology"
       },
       {
-        "author_name": "Douglas M. Densmore",
-        "author_inst": "Boston University"
+        "author_name": "Alex J Ryu",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Lena Landaverde",
-        "author_inst": "Boston University"
+        "author_name": "Esma Gel",
+        "author_inst": "Arizona State University"
       },
       {
-        "author_name": "Wenrui Li",
-        "author_inst": "Boston University"
+        "author_name": "Ramesh Raskar",
+        "author_inst": "Massachusetts Institute of Technology"
       },
       {
-        "author_name": "Tom Rose",
-        "author_inst": "Boston University"
+        "author_name": "Walter Kremers",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Stephen P. Burgay",
-        "author_inst": "Boston University"
+        "author_name": "Karen Anderson",
+        "author_inst": "Mayo Clinic, Arizona State University"
       },
       {
-        "author_name": "Candice Miller",
-        "author_inst": "Boston University"
+        "author_name": "Jayakumar Subramanian",
+        "author_inst": "Adobe Systems"
       },
       {
-        "author_name": "Lynn Doucette-Stamm",
-        "author_inst": "Boston University"
+        "author_name": "Balaji Krishnamurthy",
+        "author_inst": "Adobe Systems"
       },
       {
-        "author_name": "Kelly Lockard",
-        "author_inst": "Boston University"
+        "author_name": "Abhishek Singh",
+        "author_inst": "Massachusetts Institute of Technology"
       },
       {
-        "author_name": "Kenneth Elmore",
-        "author_inst": "Boston University"
+        "author_name": "Kalyan Pasupathy",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Tracy Schroeder",
-        "author_inst": "Boston University"
+        "author_name": "Yue Dong",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Ann M. Zaia",
-        "author_inst": "Boston University"
+        "author_name": "John C O'Horo",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Eric D. Kolaczyk",
-        "author_inst": "Boston University"
+        "author_name": "Walter R Wilson",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Gloria Waters",
-        "author_inst": "Boston University"
+        "author_name": "Oscar Mitchell",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "Robert A. Brown",
-        "author_inst": "Boston University"
+        "author_name": "Thomas C Kingsley",
+        "author_inst": "Mayo Clinic"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -864227,51 +867670,35 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.02.23.21252294",
-    "rel_title": "Evaluation of COVID-19 as a risk factor for maternal-fetal and neonatal complications: protocol of a systematic review and meta-analysis of cohort and case-control studies.",
+    "rel_doi": "10.1101/2021.02.23.21251915",
+    "rel_title": "Clinical evaluation of the molecular-based BD SARS-CoV-2/Flu for the BD MAX\u2122 System",
     "rel_date": "2021-02-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252294",
-    "rel_abs": "BackgroundCOVID-19 in pregnant women has been suggested to impair maternal-fetal and neonatal outcomes. We then designed the present systematic review with meta-analysis to evaluate the repercussion of such disease over maternal fetal and neonatal mortality, need for intensive care, way of delivery, premature delivery, birth weight, Apgar score, presence of intrauterine growth restriction (IGR), and presence of amniotic fluid change.\n\nMethodsWe will conduct a computerized search through MEDLINE/PubMed, LILACS/BIREME, Web of science, Biorxiv, Medrxiv, and Embase on July 23, 2020. We will include cohort and case-control studies fully reported comparing pregnant women with COVID-19 with those not affected by the disease for maternal fetal and neonatal mortality, need for intensive care, way of delivery, premature delivery occurrence, birth weight, Apgar scores, presence of intrauterine growth restriction, and presence of amniotic fluid change. Three doubles of reviewers will perform in duplicate and independently all steps on screening, risk of bias judgments, and data extraction with ability to discuss disagreements with supervising authors. Pooled effects will be estimated by both fixed and random-effects models and presented according to qualitative and quantitative heterogeneity assessment. Sensitivity analyses will be performed as well as a priori subgroup, meta-regression and multiple meta-regression analyses. Well also evaluate the risk of selective publication by assessing funnel plot asymmetry and the quality of the evidence by the application of the GRADE recommendations.\n\nDiscussionThis systematic review with meta-analysis aims to assess the repercussion of COVID-19 in pregnant women over maternal-fetal and neonatal outcomes and to help clinicians and health systems improve such population outcomes throughout the current pandemic.\n\nSystematic review registrationThis review protocol was also submitted to PROSPERO registration on February 9, 2021.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21251915",
+    "rel_abs": "Efficient and accurate assays for the differential diagnosis of COVID-19 and/or influenza (flu) could facilitate optimal treatment for both diseases. Diagnostic performance related to SARS-CoV-2 and Flu A/B detection was characterized for the BD SARS-CoV-2/Flu for BD MAX System (\"MAX SARS-CoV-2/Flu\") multiplex assay in comparison with BD BioGx SARS-CoV-2 Reagents for BD MAX System (\"BioGx SARS-CoV-2\") and the Cepheid Xpert(R) Xpress Flu/RSV (\"Xpert Flu\"). Two hundred and thirty-five nasopharyngeal specimens were obtained from external vendors. MAX SARS-CoV-2/Flu had positive percent agreement (PPA) and negative percent agreement (NPA) values for SARS-CoV-2 and Flu A/B that met FDA-EUA acceptance criteria of >95%.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Priscila Bezerra",
-        "author_inst": "Instituto de Medicina Integral professor Fernando Figueira"
+        "author_name": "Sonia Paradis",
+        "author_inst": "BD"
       },
       {
-        "author_name": "Fernanda Gabriella de Siqueira Barros Nogueira Sr.",
-        "author_inst": "Instituto de Medicina Integral Prof. Fernando Figueira (IMIP)"
-      },
-      {
-        "author_name": "Alan Chaves dos Santos",
-        "author_inst": "Instituto de medicina integral professor Fernando Figueira"
-      },
-      {
-        "author_name": "Anna Katharina Souza Lima",
-        "author_inst": "Universidade Federal de Pernambuco"
-      },
-      {
-        "author_name": "David Emanuel Ribeiro",
-        "author_inst": "Universidade Federal de Pernambuco"
-      },
-      {
-        "author_name": "Elias Almeida Silva Barbosa",
-        "author_inst": "Universidade Federal de Pernambuco"
+        "author_name": "Elizabeth Lockamy",
+        "author_inst": "BD"
       },
       {
-        "author_name": "Suellen Casado dos Santos",
-        "author_inst": "Universidade Federal de Pernambuco"
+        "author_name": "Charles K Cooper",
+        "author_inst": "BD"
       },
       {
-        "author_name": "Clistenes Cristian de Carvalho",
-        "author_inst": "Instituto de Medicina Integral Professor Fernando Figueira"
+        "author_name": "Stephen Young",
+        "author_inst": "TriCore Reference Laboratories"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "obstetrics and gynecology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.02.23.21252309",
@@ -866253,29 +869680,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.22.21252254",
-    "rel_title": "Associations Between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States",
+    "rel_doi": "10.1101/2021.02.23.21252230",
+    "rel_title": "Prior COVID-19 Infection and Antibody Response to Single Versus Double Dose mRNA SARS-CoV-2 Vaccination",
     "rel_date": "2021-02-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252254",
-    "rel_abs": "We utilize functional data analysis techniques to investigate patterns of COVID-19 positivity and mortality in the US and their associations with Google search trends for COVID-19 related symptoms. Specifically, we represent state-level time series data for COVID-19 and Google search trends for symptoms as smoothed functional curves. Given these functional data, we explore the modes of variation in the data using functional principal component analysis (FPCA). We also apply functional clustering analysis to identify patterns of COVID-19 confirmed case and death trajectories across the US. Moreover, we quantify the associations between Google COVID-19 search trends for symptoms and COVID-19 confirmed case and death trajectories using dynamic correlation. Finally, we examine the dynamics of correlations for the top nine Google search trends of symptoms commonly associated with COVID-19 confirmed case and death trajectories. Our results reveal and characterize distinct patterns for COVID-19 spread and mortality across the US. The dynamics of these correlations suggest the feasibility of using Google queries to forecast COVID-19 cases and mortality for up to three weeks in advance. Our results and analysis framework set the stage for the development of predictive models for forecasting COVID-19 confirmed cases and deaths using historical data and Google search trends for nine symptoms associated with both outcomes.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.23.21252230",
+    "rel_abs": "The double dose regimen for mRNA vaccines against SARS-CoV-2 presents both a hope and a challenge for global efforts to curb the COVID-19 pandemic. With supply chain logistics impacting the rollout of population-scale vaccination programs, increasing attention has turned to the potential efficacy of single versus double dose vaccine administration for select individuals. To this end, we examined response to Pfizer-BioNTech mRNA vaccine in a large cohort of healthcare workers including those with versus without prior COVID-19 infection. For all participants, we quantified circulating levels of SARS-CoV-2 anti-spike (S) protein IgG at baseline prior to vaccine, after vaccine dose 1, and after vaccine dose 2. We observed that the anti-S IgG antibody response following a single vaccine dose in persons who had recovered from confirmed prior COVID-19 infection was similar to the antibody response following two doses of vaccine in persons without prior infection (P[&ge;]0.58). Patterns were similar for the post-vaccine symptoms experienced by infection recovered persons following their first dose compared to the symptoms experienced by infection naive persons following their second dose (P=0.66). These results support the premise that a single dose of mRNA vaccine could provoke in COVID-19 recovered individuals a level of immunity that is comparable to that seen in infection naive persons following a double dose regimen. Additional studies are needed to validate our findings, which could allow for public health programs to expand the reach of population wide vaccination efforts.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Mostafa Abbas",
-        "author_inst": "Geisinger"
+        "author_name": "Joseph E. Ebinger",
+        "author_inst": "Cedars-Sinai Medical Center"
       },
       {
-        "author_name": "Thomas B. Morland",
-        "author_inst": "Geisinger"
+        "author_name": "Justyna Fert-Bober",
+        "author_inst": "Cedars-Sinai Medical Center"
       },
       {
-        "author_name": "Eric S. Hall",
-        "author_inst": "Geisinger"
+        "author_name": "Ignat Printsev",
+        "author_inst": "Cedars-Sinai Medical Center"
       },
       {
-        "author_name": "Yasser El-Manzalawy",
-        "author_inst": "Geisinger"
+        "author_name": "Min Wu",
+        "author_inst": "Cedars-Sinai Medical Center"
+      },
+      {
+        "author_name": "Nancy Sun",
+        "author_inst": "Cedars-Sinai Medical Center"
+      },
+      {
+        "author_name": "Jane C. Figueiredo",
+        "author_inst": "Cedars-Sinai Medical Center"
+      },
+      {
+        "author_name": "Jennifer Van Eyk",
+        "author_inst": "Cedars-Sinai Medical Center"
+      },
+      {
+        "author_name": "Jonathan Braun",
+        "author_inst": "Cedars-Sinai Medical Center"
+      },
+      {
+        "author_name": "Susan Cheng",
+        "author_inst": "Cedars-Sinai Medical Center"
+      },
+      {
+        "author_name": "Kimia Sobhani",
+        "author_inst": "Cedars-Sinai Medical Center"
       }
     ],
     "version": "1",
@@ -868151,39 +871602,71 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.02.19.21252073",
-    "rel_title": "Health-related quality of life of adult COVID-19 patients following one-month illness experience since diagnosis: findings of a cross-sectional study in Bangladesh",
+    "rel_doi": "10.1101/2021.02.20.21251855",
+    "rel_title": "Transmission of SARS-CoV-2 Considering Shared Chairs in Outpatient Dialysis: A Real-World Case-Control Study",
     "rel_date": "2021-02-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.19.21252073",
-    "rel_abs": "BackgroundThe pandemic coronavirus disease 2019 (COVID-19) stances an incredible impact on the quality of life of the patients. The disease not only denigrates the physical health of the patients but also affects their mental health. This cross-sectional study aimed to assess the health-related quality of life (HRQOL) of patients.\n\nMethodsThe study was conducted at the National Institute of Preventive and Social Medicine (NIPSOM), Dhaka, Bangladesh during the period from June to November 2020. The study enrolled 1204 adult (>18 years) COVID-19 patients diagnosed by real-time reverse transcriptase-polymerase chain reaction (RT-PCR) assay and completed the one-month duration of illness. The patients were interviewed with the CDC HRQOL-14 questionnaire to assess their HRQOL. Data were collected by telephone-interview and reviewing medical records using a semi-structured questionnaire and checklist respectively. Informed consent was obtained from each patient before data collection.\n\nResultsThe majority of the COVID-19 patients were males (72.3%), urban residents (50.2%), and diverse service holders (49.6%). More than one-third (35.5%) of patients had comorbidity including hypertension (55.6%), diabetes mellitus (55.6%), ischaemic heart disease (16.4%), chronic lung (12.4%), kidney (2.8%), and liver (4.2%) diseases. The mean{+/-}SD duration of physical illness was 9.83({+/-}7.09) days, and it was 7.97({+/-}8.12) days for mental illness. During the one-month disease course, the general health condition was excellent/very good/good in 70.1% of the patients while it was fair/poor in 29.8% of the patients. Older age, sex, and marital status were significantly associated with at least one dimension of HRQOL. Patients having symptoms of COVID-19 and comorbidity had significantly poorer HRQOL.\n\nConclusionCOVID-19 pretenses a significant impact on the HRQOL of the patients including physical and mental illness during the clinical course. Our findings suggest more pragmatic preventive, promotive, and curative measures considering illness experiences of the COVID-19 patients to restore their quality of life.\n\nHighlightsSince COVID-19 was identified first in china in 2019, it has been transmitted globally and caused a significant impact on human health. A few studies have been carried out on HRQOL of COVID-19 patients and struggled with an accurate estimation of the severity of their physical and mental illness. Most of the studies recognized the poor quality of life of COVID-19 patients after the one-month disease course. Our study provides new insights on the HRQOL of the COVID-19 patients using the CDC HRQOL-14 questionnaire. We measured the HRQOL following one-month illness experience of the patients using three modules: the healthy days core; the activity limitations; and the healthy days symptoms. The study adds information regarding general health conditions including both the physical and mental health of COVID-19 patients. The study also complements information regarding the activity limitations of the patients. The study findings could contribute to designing an efficient clinical algorithm to alleviate the illness sufferings of the COVID-19 patients using a more pragmatic approach. The study conserves decisive policy implications to concoct effective interventions for improving the HRQOL of COVID-19 patients in the country and elsewhere in other countries world-wide.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.20.21251855",
+    "rel_abs": "BackgroundSARS-CoV-2 is primarily transmitted through aerosolized droplets; however, the virus can remain transiently viable on surfaces.\n\nObjectiveWe examined transmission within hemodialysis facilities, with a specific focus on the possibility of indirect patient-to-patient transmission through shared dialysis chairs.\n\nDesignWe used real-world data from hemodialysis patients treated between February 1st and June 8th, 2020 to perform a case-control study matching each SARS-CoV-2 positive patient (case) to a non-SARS-CoV-2 patient (control) in the same dialysis shift and traced back 14 days to capture possible exposure from chairs sat in by SARS-CoV-2 patients. Cases and controls were matched on age, sex, race, facility, shift date, and treatment count.\n\nSetting2,600 hemodialysis facilities in the United States.\n\nPatientsAdult (age [&ge;]18 years) hemodialysis patients.\n\nMeasurementsConditional logistic regression models tested whether chair exposure after a positive patient conferred a higher risk of SARS-CoV-2 infection to the immediate subsequent patient.\n\nResultsAmong 170,234 hemodialysis patients, 4,782 (2.8%) tested positive for SARS-CoV-2 (mean age 64 years, 44% female). Most facilities (68.5%) had 0 to 1 positive SARS-CoV-2 patient. We matched 2,379 SARS-CoV-2 positive cases to 2,379 non-SARS-CoV-2 controls; 1.30% (95%CI 0.90%, 1.87%) of cases and 1.39% (95%CI 0.97%, 1.97%) of controls were exposed to a chair previously sat in by a shedding SARS-CoV-2 patient. Transmission risk among cases was not significantly different from controls (OR=0.94; 95%CI 0.57 to 1.54; p=0.80). Results remained consistent in adjusted and sensitivity analyses.\n\nLimitationAnalysis used real-world data that could contain errors and only considered vertical transmission associated with shared use of dialysis chairs by symptomatic patients.\n\nConclusionsThe risk of indirect patient-to-patient transmission of SARS-CoV-2 infection from dialysis chairs appears to be low.\n\nPrimary Funding SourceFresenius Medical Care North America; National Institute of Diabetes and Digestive and Kidney Diseases (R01DK130067)",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Md. Ziaul Islam",
-        "author_inst": "National Institute of Preventive and Social Medicine (NIPSOM)"
+        "author_name": "Ravi Thadhani",
+        "author_inst": "Partners HealthCare"
       },
       {
-        "author_name": "Baizid Khoorshid Riaz",
-        "author_inst": "National Institute of Preventive and Social Medicine"
+        "author_name": "Joanna Willetts",
+        "author_inst": "Fresenius Medical Care, Global Medical Office"
       },
       {
-        "author_name": "Syeda Sumaiya Efa",
-        "author_inst": "Diabetic Association of Bangladesh"
+        "author_name": "Catherine Wang",
+        "author_inst": "University of California-Santa Barbara"
       },
       {
-        "author_name": "Sharmin Farjana",
-        "author_inst": "Shaheed Suhrawardy Medical College Hospital"
+        "author_name": "John W Larkin",
+        "author_inst": "Fresenius Medical Car, Global Medical Office"
+      },
+      {
+        "author_name": "Hanjie Zhang",
+        "author_inst": "Renal Research Institute"
+      },
+      {
+        "author_name": "Lemuel Rivera Fuentes",
+        "author_inst": "Renal Research Institute"
+      },
+      {
+        "author_name": "Len Usvyat",
+        "author_inst": "Fresenius Medical Care, Global Medical Office"
       },
       {
-        "author_name": "Fahad Mahmood",
-        "author_inst": "National Institute of Preventive and Social Medicine"
+        "author_name": "Kathleen Belmonte",
+        "author_inst": "Fresenius Kidney Care"
+      },
+      {
+        "author_name": "Yuedong Wang",
+        "author_inst": "University of California-Santa Barbara"
+      },
+      {
+        "author_name": "Robert Kossmann",
+        "author_inst": "Fresenius Medical Care North America"
+      },
+      {
+        "author_name": "Jeffrey Hymes",
+        "author_inst": "Fresenius Medical Care, Global Medical Office"
+      },
+      {
+        "author_name": "Peter Kotanko",
+        "author_inst": "Renal Research Institute"
+      },
+      {
+        "author_name": "Franklin W Maddux",
+        "author_inst": "Fresenius Medical Care AG & Co. KGaA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "nephrology"
   },
   {
     "rel_doi": "10.1101/2021.02.19.21252101",
@@ -870065,17 +873548,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.02.19.21252106",
-    "rel_title": "Impact of environmental temperature on Covid-19 spread: Model and analysis of measurements recorded during the second pandemic in Cyprus",
+    "rel_doi": "10.1101/2021.02.22.21252208",
+    "rel_title": "Vaccination efforts in Brazil: scenarios and perspectives under a mathematical modeling approach",
     "rel_date": "2021-02-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.19.21252106",
-    "rel_abs": "The paper investigates the effect of the environmental temperature on the spread of COVID-19. We study the daily numbers of the cases infected and deaths caused by Covid-19 during the second wave of the pandemic within 2020, and how they were affected by the daily average-high temperature for the districts of the Republic of Cyprus. Among the findings of the paper, we show that (i) the average ratio of the PCR to rapid positive tests is [~]2.57{+/-}0.25, as expected from the tests responses, indicating that PCR overestimates positivity by [~]2.5 times; (ii) the average age of deaths caused by Covid-19 increases with rate about a year of age per week; (iii) the probability of a person infected by Covid-19 to develop severe symptoms leading to death is strongly depended on the persons age, while the probability of having a death on the age of [~]67 or younger is less than 1/1000; (iv) the number of infected cases and deaths declined dramatically when the environmental temperature reaches and/or climbs above the critical temperature of TC=30.1{+/-}2.4 C0; (v) the observed negative correlation between the exponential growth rate of the infected cases and the environmental temperature can be described within the framework of chemical kinetics, with at least two competing reactions, the connection of the coronavirus towards the receptor and the dissolution of the coronavirus; the estimated activation energy difference corresponding to the competing chemical reactions, 0.212{+/-}0.25 eV, matches the known experimental value; and (vi) the infected cases will decline to zero, when the environmental temperature climbs above the critical temperature within the summery days of 2021, which is expected for the Republic of Cyprus by the 16th of May, 2021.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252208",
+    "rel_abs": "An agent-based model is proposed to access the impact of vaccination strategies to halt the COVID-19 spread. The model is parameterized using data from Sao Paulo State, Brazil. It was considered the two vaccines that are already approved for emergency use in Brazil, the CoronaVac vaccine developed by the Chinese bio-pharmaceutical company Sinovac and the Oxford-AstraZeneca vaccine (ChadOx1) developed by Oxford University and the British laboratory AstraZeneca. Both of them are two-dose schemes, but the efficacy and the interval between doses are different. We found that even in the worst scenario, in which the vaccine does not prevent infection either severe symptoms, the number of deaths decreases from 122 to 99 for CoronaVac application and to 80 for ChadOx1 administration. The same patterns have been seen in hospitalizations. Nevertheless, we show that when a low risk perception occurs, the reduction values decrease between 2% to 4%. Moreover, the increase of disease prevalence also jeopardizes immunization, showing the importance of the mitigation measures maintenance. On the other hand, doubling the vaccination rate would be able to significantly decrease the disease outcomes, reducing deaths by up to 74.4%. In conclusion, vaccination, along with non-pharmaceutical measures, is key to the control of COVID-19 in Brazil.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "George Livadiotis",
-        "author_inst": "Southwest Research Institute"
+        "author_name": "Thomas Nogueira Vilches",
+        "author_inst": "IMECC-UNICAMP"
+      },
+      {
+        "author_name": "Felipe Alves Rubio",
+        "author_inst": "University of Campinas"
+      },
+      {
+        "author_name": "Rafael Forti Perroni",
+        "author_inst": "UNESP"
+      },
+      {
+        "author_name": "Gabriel Berg de Almeida",
+        "author_inst": "Faculdade de Medicina de Botucatu"
+      },
+      {
+        "author_name": "Claudia Pio Ferreira",
+        "author_inst": "Institute of Bioscience - UNESP"
+      },
+      {
+        "author_name": "Carlos Magno Castelo Branco Fortaleza",
+        "author_inst": "Botucatu Medical School, S\u00e3o Paulo State University (UNESP)"
       }
     ],
     "version": "1",
@@ -871871,145 +875374,69 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2021.02.20.432046",
-    "rel_title": "Reduced binding and neutralization of infection- and vaccine-induced antibodies to the B.1.351 (South African) SARS-CoV-2 variant",
+    "rel_doi": "10.1101/2021.02.20.432110",
+    "rel_title": "A novel glucocorticoid and androgen receptor modulator reduces viral entry and innate immune inflammatory responses in the Syrian Hamster model of SARS-CoV-2",
     "rel_date": "2021-02-22",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.20.432046",
-    "rel_abs": "The emergence of SARS-CoV-2 variants with mutations in the spike protein is raising concerns about the efficacy of infection- or vaccine-induced antibodies to neutralize these variants. We compared antibody binding and live virus neutralization of sera from naturally infected and spike mRNA vaccinated individuals against a circulating SARS-CoV-2 B.1 variant and the emerging B.1.351 variant. In acutely-infected (5-19 days post-symptom onset), convalescent COVID-19 individuals (through 8 months post-symptom onset) and mRNA-1273 vaccinated individuals (day 14 post-second dose), we observed an average 4.3-fold reduction in antibody titers to the B.1.351-derived receptor binding domain of the spike protein and an average 3.5-fold reduction in neutralizing antibody titers to the SARS-CoV-2 B.1.351 variant as compared to the B.1 variant (spike D614G). However, most acute and convalescent sera from infected and all vaccinated individuals neutralize the SARS-CoV-2 B.1.351 variant, suggesting that protective immunity is retained against COVID-19.",
-    "rel_num_authors": 33,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.20.432110",
+    "rel_abs": "Since its initial discovery in late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of COVID19, has spread worldwide and despite significant research efforts, treatment options remain limited. Replication of SARS-CoV-2 in lung is associated with marked infiltration of macrophages and activation of innate immune inflammatory responses triggered, in part, by heightened production of interleukin-6 (IL-6) that recruits lymphocytes to the site of infection that amplify tissue injury. Antagonists of the glucocorticoid and androgen receptors have shown promise in experimental models of COVID19 and in clinical studies, because cell surface proteins required for viral entry, angiotensin converting enzyme 2 (ACE2) and the transmembrane serine protease 2 (TMPRSS2), are transcriptionally regulated by these receptors. We therefore postulated that the glucocorticoid (GR) and androgen receptor (AR) antagonist, PT150, would reduce infectivity of SARS-CoV-2 and prevent inflammatory lung injury in the Syrian golden hamster model of COVID19. Animals were infected intranasally with 2.5 x 104 TCID50/ml equivalents of SARS-CoV-2 (strain 2019-nCoV/USA-WA1/ 2020) and PT150 was administered by oral gavage at 30 and 100 mg/Kg/day for a total of 7 days. Animals were then examined at days 3, 5 and 7 post-infection (DPI) for lung histopathology, viral load and production of proteins regulating the initiation and progression of SARS-CoV-2 infection. Results of these studies indicated that oral administration of PT150 decreased replication of SARS-CoV-2 in lung, as well as expression of ACE2 and TMPRSS2 protein. Hypercellularity and inflammatory cell infiltration driven by macrophage responses were dramatically decreased in PT150-treated animals, as was tissue damage and expression of IL-6. Molecular modeling suggested that PT150 binds to the co-activator interface of the ligand binding domain of both AR and GR and thereby acts as an allosteric modulator and transcriptional repressor of these receptors. Phylogenetic analysis of AR and GR across multiple species permissive to SARS-CoV-2 infection revealed a high degree of sequence identity maintained across species, including human, suggesting that the mechanism of action and therapeutic efficacy observed in Syrian hamsters would likely be predictive of positive outcomes in patients. PT150 is therefore a strong candidate for further clinical development for the treatment of COVID19 across variants of SARS-CoV-2.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Venkata Viswanadh Edara",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Carson Norwood",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Katharine Floyd",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Lilin Lai",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Meredith E Davis-Gardner",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "William H Hudson",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Grace Mantus",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Lindsay E Nyhoff",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Max W Adelman",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Rebecca Fineman",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Shivan Patel",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Rebecca Byram",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Dumingu Nipuni Gomes",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Garett Michael",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Hayatu Abdullahi",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Nour Beydoun",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Bernadine Panganiban",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Nina McNair",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Kieffer Hellmeister",
-        "author_inst": "Emory University"
-      },
-      {
-        "author_name": "Jamila Pitts",
-        "author_inst": "Emory University"
+        "author_name": "Savannah M. Rocha",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Joy Winters",
-        "author_inst": "Emory University"
+        "author_name": "Anna C. Fagre",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Jennifer Kleinhenz",
-        "author_inst": "Emory University"
+        "author_name": "Amanda S. Latham",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Jacob Usher",
-        "author_inst": "Emory University"
+        "author_name": "Katriana A. Popichak",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Anne Piantadosi",
-        "author_inst": "Emory University"
+        "author_name": "Casey P. McDermott",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Jesse J Waggoner",
-        "author_inst": "Emory University"
+        "author_name": "Clinton C. Dawson",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Ahmed Babiker",
-        "author_inst": "Emory University"
+        "author_name": "Juliette Lewis",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "David S Stephens",
-        "author_inst": "Emory University"
+        "author_name": "Phillip Reigan",
+        "author_inst": "University of Colorado Denver Anschutz Medical Campus"
       },
       {
-        "author_name": "Evan J Anderson",
-        "author_inst": "Emory University"
+        "author_name": "Tawfik A. Aboellail",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Srilatha Edupuganti",
-        "author_inst": "Emory University"
+        "author_name": "Rebekah C. Kading",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Nadine Rouphael",
-        "author_inst": "Emory University"
+        "author_name": "Tony Schountz",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Rafi Ahmed",
-        "author_inst": "Emory University"
+        "author_name": "Neil D. Theise",
+        "author_inst": "New York University-Grossman School of Medicine"
       },
       {
-        "author_name": "Jens Wrammert",
-        "author_inst": "Emory University"
+        "author_name": "Richard A. Slayden",
+        "author_inst": "Colorado State University"
       },
       {
-        "author_name": "Mehul S Suthar",
-        "author_inst": "Emory University"
+        "author_name": "Ronald B. Tjalkens",
+        "author_inst": "Colorado State University"
       }
     ],
     "version": "1",
@@ -873589,79 +877016,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.16.21251838",
-    "rel_title": "Profile of SARS-CoV-2-specific CD4 T cell response: Relationship with disease severity and impact of HIV-1 and active Mycobacterium tuberculosis co-infection",
+    "rel_doi": "10.1101/2021.02.18.21251939",
+    "rel_title": "Applicability of Neighborhood and Building Scale Wastewater-Based Genomic Epidemiology to Track the SARS-CoV-2 Pandemic and other Pathogens.",
     "rel_date": "2021-02-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.16.21251838",
-    "rel_abs": "T cells are involved in control of COVID-19, but limited knowledge is available on the relationship between antigen-specific T cell response and disease severity. Here, we assessed the magnitude, function and phenotype of SARS-CoV-2-specific CD4 T cells in 95 hospitalized COVID-19 patients (38 of them being HIV-1 and/or tuberculosis (TB) co-infected) and 38 non-COVID-19 patients, using flow cytometry. We showed that SARS-CoV-2-specific CD4 T cell attributes, rather than magnitude, associates with disease severity, with severe disease being characterized by poor polyfunctional potential, reduced proliferation capacity and enhanced HLA-DR expression. Moreover, HIV-1 and TB co-infection skewed the SARS-CoV-2 T cell response. HIV-1 mediated CD4 T cell depletion associated with suboptimal T cell and humoral immune responses to SARS-CoV-2; and a decrease in the polyfunctional capacity of SARS-CoV-2-specific CD4 T cells was observed in COVID-19 patients with active TB. Our results also revealed that COVID-19 patients displayed reduced frequency of Mtb-specific CD4 T cells, with possible implications for TB disease progression. There results corroborate the important role of SARS-CoV-2-specific T cells in COVID-19 pathogenesis and support the concept of altered T cell functions in patients with severe disease.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.18.21251939",
+    "rel_abs": "The benefits of wastewater-based epidemiology (WBE) for tracking the viral load of SARS-CoV-2, the causative agent of COVID-19, have become apparent since the start of the pandemic. However, most sampling occurs at the wastewater treatment plant influent and therefore can only monitor SARS-CoV-2 concentration and spread within the entire catchment, which can encompass multiple municipalities. Furthermore, most WBE only quantifies the virus, and therefore miss crucial information that can be gained by sequencing SARS-CoV-2. Here we demonstrate feasibility of sampling at the neighborhood or building complex level using a mix of quantitative polymerase chain reaction (qPCR) and targeted sequencing to provide a more refined understanding of the local dynamics of SARS-CoV-2 strains. When coupled with the higher-level treatment plant samples, this creates an opportunity for health officials to monitor the spread of the virus at different spatial and temporal scales to inform policy decisions.\n\nHere we demonstrate the feasibility of tracking SARS-CoV-2 at the neighborhood, hospital, and nursing home level with the ability to detect one COVID-19 positive out of 60 nursing home residents. The viral load obtained was correlative with the number of COVID-19 patients being treated in the hospital. Sequencing of the samples over time demonstrated that nonsynonymous mutations fluctuate in the viral population, and wastewater-based sequencing could be an efficient approach to monitor for vaccine or convalescent plasma escape mutants, as well as mutations that could reduce the efficacy of diagnostics. Furthermore, while SARS-CoV-2 was detected by untargeted RNA sequencing, qPCR and targeted whole genome amplicon sequencing were more reliable methods for tracking the pandemic. From our sequencing data, clades and shifts in mutation profiles within the community were traceable and could be used to determine if vaccine or diagnostics need to be adapted to ensure continued efficacy.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC=\"FIGDIR/small/21251939v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@110f217org.highwire.dtl.DTLVardef@185d3f0org.highwire.dtl.DTLVardef@11d3a8corg.highwire.dtl.DTLVardef@1eef33d_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LINeighborhood or building level wastewater analysis accurately detects SARS-CoV-2\nC_LIO_LISARS-CoV-2 was detected in wastewater from one infected person out of 60 residents\nC_LIO_LITotal RNAseq did not accurately detect SARS-CoV-2 in wastewater samples.\nC_LIO_LITargeted whole genome sequencing of wastewater samples identified Spike mutations.\nC_LI",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Catherine Riou",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Elsa du Bruyn",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Cari Stek",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Remy Daroowala",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Rene T Goliath",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Fatima Abrahams",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Qonita Said-Hartley",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Brian W Allowed",
-        "author_inst": "Stellenbosch University and Tygerberg Hospital"
-      },
-      {
-        "author_name": "Marvin Hsiao",
-        "author_inst": "University of Cape Town"
-      },
-      {
-        "author_name": "Katalin A Wilkinson",
-        "author_inst": "University of Cape Town and The Francis Crick Institute"
-      },
-      {
-        "author_name": "Cecilia S Lindestam Arlehamn",
-        "author_inst": "La Jolla Institute for Immunology"
-      },
-      {
-        "author_name": "Alessandro Sette",
-        "author_inst": "University of California San Diego"
-      },
-      {
-        "author_name": "Sean Wasserman",
-        "author_inst": "University of Cape Town"
+        "author_name": "Rachel R Spurbeck",
+        "author_inst": "Battelle Memorial Institute"
       },
       {
-        "author_name": "Robert J Wilkinson",
-        "author_inst": "University of Cape Town, Imperial College London and The Francis Crick Institute"
+        "author_name": "Lindsay A Catlin",
+        "author_inst": "Battelle Memorial Institute"
       },
       {
-        "author_name": "- the HIATUS consortium",
-        "author_inst": "-"
+        "author_name": "Angela T Minard-Smith",
+        "author_inst": "Battelle Memorial Institutes"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.02.18.21252000",
@@ -875015,57 +878394,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.16.21251625",
-    "rel_title": "Healthcare-associated COVID-19 in England: a national data linkage study",
+    "rel_doi": "10.1101/2021.02.16.21251844",
+    "rel_title": "An exploratory study on the correlation of population SARS-CoV-2 cycle threshold values to local disease dynamics",
     "rel_date": "2021-02-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.16.21251625",
-    "rel_abs": "ObjectivesNosocomial transmission was an important aspect of SARS-CoV-1 and MERS-CoV outbreaks. Healthcare-associated SARS-CoV-2 infection has been reported in single and multi-site hospital-based studies in England, but not nationally.\n\nMethodsAdmission records for all hospitals in England were linked to SARS-CoV-2 national test data for the period 01/03/2020 to 31/08/2020. Case definitions were: community-onset community-acquired (CO.CA), first positive test (FPT) <14 days pre-admission, up to day 2 of admission; hospital-onset indeterminate healthcare-associated (HO.iHA), FPT on day 3-7; hospital-onset probable healthcare-associated (HO.pHA), FPT on day 8-14; hospital-onset definite healthcare-associated (HO.HA), FPT from day 15 of admission until discharge; community-onset possible healthcare-associated (CO.pHA), FPT [&le;]14 days post-discharge.\n\nResultsOne-third (34.4%, 100,859/293,204) of all laboratory-confirmed COVID-19 cases were linked to a hospital record. HO.pHA and HO.HA cases represented 5.3% (15,564/293,204) of all laboratory-confirmed cases and 15.4% (15,564/100,859) of laboratory-confirmed cases among hospital patients. CO.CA and CO.pHA cases represented 86.5% (253,582/293,204) and 5.1% (14,913/293,204) of all laboratory-confirmed cases, respectively.\n\nConclusionsUp to 1 in 6 SARS-CoV-2 infections among hospitalised patients with COVID-19 in England during the first 6 months of the pandemic could be attributed to nosocomial transmission, but these represent less than 1% of the estimated 3 million COVID-19 cases in this period.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.16.21251844",
+    "rel_abs": "IntroductionDespite limitations on the use of cycle threshold (CT) values for individual patient care, population distributions of CT values may be useful indicators of local outbreaks.\n\nMethodsSpecimens from the greater El Paso area were processed in the Dascena COVID-19 Laboratory. Daily median CT value, daily transmission rate R(t), daily count of COVID-19 hospitalizations, daily change in percent positivity, and rolling averages of these features were plotted over time. Two-way scatterplots and linear regression evaluated possible associations between daily median CT and outbreak measures. Cross-correlation plots determined whether a time delay existed between changes in the daily median CT value and measure of community disease dynamics.\n\nResultsDaily median CT was negatively correlated with the daily R(t), the daily COVID-19 hospitalization count (with a time delay), and the daily change in percent positivity among testing samples. Despite visual trends suggesting time delays in the plots for median CT and outbreak measures, a statistically significant delay was only detected between changes in median CT and COVID-19 hospitalization count.\n\nConclusionsThis study adds to the literature by analyzing samples collected from an entire geographical area, and contextualizing the results with other research investigating population CT values.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Alex Bhattacharya",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Simon M Collin",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "James Stimson",
-        "author_inst": "Public Health England"
+        "author_name": "Chak Foon Tso",
+        "author_inst": "Dascena, Inc"
       },
       {
-        "author_name": "Simon Thelwall",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Olisaeloka Nsonwu",
-        "author_inst": "Public Health England"
+        "author_name": "Anurag Garikipati",
+        "author_inst": "Dascena, Inc"
       },
       {
-        "author_name": "Sarah Gerver",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Julie Robotham",
-        "author_inst": "Public Health England"
-      },
-      {
-        "author_name": "Mark Wilcox",
-        "author_inst": "University of Leeds"
+        "author_name": "Abigail Green-Saxena",
+        "author_inst": "Dascena, Inc"
       },
       {
-        "author_name": "Susan Hopkins",
-        "author_inst": "Public Health England"
+        "author_name": "Qingqing Mao",
+        "author_inst": "Dascena, Inc"
       },
       {
-        "author_name": "Russell Hope",
-        "author_inst": "Public Health England"
+        "author_name": "Ritankar Das",
+        "author_inst": "Dascena, Inc"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -876673,53 +880032,89 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.17.21251758",
-    "rel_title": "Prediction of Mortality in hospitalized COVID-19 patients in a statewide health network",
+    "rel_doi": "10.1101/2021.02.16.21251849",
+    "rel_title": "Convalescent plasma for preventing critical illness in COVID-19: A phase 2 trial and immune profile",
     "rel_date": "2021-02-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.17.21251758",
-    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSImportanceC_ST_ABSA predictive model to automatically identify the earliest determinants of both hospital discharge and mortality in hospitalized COVID-19 patients could be of great assistance to caregivers if the predictive information is generated and made available in the immediate hours following admission.\n\nObjectiveTo identify the most important predictors of hospital discharge and mortality from measurements at admission for hospitalized COVID-19 patients.\n\nDesignObservational cohort study.\n\nSettingElectronic records from hospitalized patients.\n\nParticipantsPatients admitted between March 3rd and August 24th with COVID-19 in Johns Hopkins Health System hospitals.\n\nExposures216 phenotypic variables collected within 48 hours of admission.\n\nMain OutcomesWe used age-stratified (<60 and >=60 years) random survival forests with competing risks to identify the most important predictors of death and discharge. Fine-Gray competing risk regression (FGR) models were then constructed based on the most important RSF-derived covariates.\n\nResultsOf 2212 patients, 1913 were discharged (age 57{+/-}19, time-to-discharge 9{+/-}11 days) while 279 died (age 75{+/-}14, time to death 14{+/-}15 days). Patients >= 60 years were nearly 10 times as likely to die within 60 days of admission as those <60. As the pandemic evolved, the rate of hospital discharge increased in both older and younger patients. Incident death and hospital discharge were accurately predicted by measures of respiratory distress, inflammation, infection, renal function, red cell turn over and cardiac stress. FGR models for each of hospital discharge and mortality as outcomes based on these variables performed well in the older (AUC 0.80-0.85 at 60-days) and younger populations (AUC >0.90 at 60-days).\n\nConclusions and RelevanceWe identified markers collected within 2 days of admission that predict hospital discharge and mortality in COVID-19 patients and provide prediction models that may be used to guide patient care. Our proposed model suggests that hospital discharge and mortality can be forecasted with high accuracy based on 8-10 variables at this stage of the COVID-19 pandemic. Our findings also point to several specific pathways that could be the focus of future investigations directed at reducing mortality and expediting hospital discharge among COVID-19 patients. Probability of hospital discharge increased over the course of the pandemic.\n\nKO_SCPLOWEYC_SCPLOW PO_SCPLOWOINTSC_SCPLOWO_ST_ABSQuestionC_ST_ABSCan we predict the likelihood of hospital discharge as well as mortality from data obtained in the first 48 hours from admission in hospitalized COVID-19 patients?\n\nFindingsModels based on extensive phenotyping mined directly from electronic medical records followed by variable selection, accounted for the competing events of hospital death versus discharge, predicted both death and discharge with area under the receiver operating characteristic curves of >0.80.\n\nMeaningHospital discharge and mortality can be forecasted with high accuracy based on just 8-10 variables, and the probability of hospital discharge increased over the course of the pandemic.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.16.21251849",
+    "rel_abs": "RationaleThe COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an unprecedented event requiring rapid adaptation to changing clinical circumstances. Convalescent immune plasma (CIP) is a promising treatment that can be mobilized rapidly in a pandemic setting.\n\nObjectivesWe tested whether administration of SARS-CoV-2 CIP at hospital admission could reduce the rate of ICU transfer or 28 day mortality.\n\nMethodsIn a single-arm phase II study, patients >18 years-old with respiratory symptoms documented with COVID-19 infection who were admitted to a non-ICU bed were administered two units of CIP within 72 hours of admission. Detection of respiratory tract SARS-CoV-2 by polymerase chain reaction and circulating anti-SARS-CoV-2 antibody titers were measured before and at time points after CIP transfusion.\n\nMeasurements and Main ResultsTwenty-nine patients were transfused CIP and forty-eight contemporaneous controls were identified with comparable baseline characteristics. Levels of anti-SARS-CoV-2 IgG, IgM, and IgA anti-spike, anti-receptor-binding domain, and anti-nucleocapsid significantly increased from baseline to post-transfusion for all proteins tested. In patients transfused with CIP, the rate of ICU transfer was 13.8% compared to 27.1% for controls with a hazard ratio 0.506 (95% CI 0.165-1.554), and 28-day mortality was 6.9% compared to 10.4% for controls, hazard ratio 0.640 (95% CI 0.124-3.298).\n\nConclusionsTransfusion of high-titer CIP to patients early after admission with COVID-19 respiratory disease was associated with reduced ICU transfer and 28-day mortality but was not statistically significant. Follow up randomized trials may inform the use of CIP for COVID-19 or future coronavirus pandemics.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Bharath Ambale Venkatesh",
-        "author_inst": "Johns Hopkins University"
+        "author_name": "Jeffrey Michael Sturek",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Thiago Quinaglia",
-        "author_inst": "Johns Hopkins Hospital"
+        "author_name": "Tania A Thomas",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Mahsima Shabani",
-        "author_inst": "Johns Hopkins Hospital"
+        "author_name": "James D Gorham",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Jaclyn Sesso",
-        "author_inst": "Johns Hopkins Hospital"
+        "author_name": "Chelsea A Sheppard",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Karan Kapoor",
-        "author_inst": "Johns Hopkins Hospital"
+        "author_name": "Allison E Raymond",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Matthew Matheson",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Kristen Petros De Guex",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Colin O Wu",
-        "author_inst": "National Institutes of Health"
+        "author_name": "William B Harrington",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Christopher Cox",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Andrew J Barros",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Joao A Lima",
-        "author_inst": "Johns Hopkins Hospital"
+        "author_name": "Gregory R Madden",
+        "author_inst": "University of Virginia School of Medicine"
+      },
+      {
+        "author_name": "Yosra M Alkabab",
+        "author_inst": "University of Virginia School of Medicine"
+      },
+      {
+        "author_name": "David Lu",
+        "author_inst": "Cornell University"
+      },
+      {
+        "author_name": "Qin Liu",
+        "author_inst": "The Wistar Institute"
+      },
+      {
+        "author_name": "Melinda D Poulter",
+        "author_inst": "University of Virginia School of Medicine"
+      },
+      {
+        "author_name": "Amy J Mathers",
+        "author_inst": "University of Virginia School of Medicine"
+      },
+      {
+        "author_name": "Archana Thakur",
+        "author_inst": "University of Virginia School of Medicine"
+      },
+      {
+        "author_name": "Ewa M Kubicka",
+        "author_inst": "University of Virginia School of Medicine"
+      },
+      {
+        "author_name": "Lawrence G Lum",
+        "author_inst": "University of Virginia School of Medicine"
+      },
+      {
+        "author_name": "Scott K Heysell",
+        "author_inst": "University of Virginia School of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -878367,121 +881762,29 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.02.15.21249420",
-    "rel_title": "COVID-19 Associated Stroke--A Single Centre Experience",
+    "rel_doi": "10.1101/2021.02.13.21251670",
+    "rel_title": "Excess Mortality in Suicide caused by COVID-19 in Japan",
     "rel_date": "2021-02-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21249420",
-    "rel_abs": "Background and PurposeVarious neurological complications have been reported in association with COVID-19. We report our experience of COVID-19 with stroke at a single center over a period of eight months spanning 1 March to 31 October 2020.\n\nMethodsWe recruited all patients admitted to Internal Medicine with an acute stroke, who also tested positive for COVID-19 on RTPCR. We included all stroke cases in our analysis for prediction of in-hospital mortality, and separately analyzed arterial infarcts for vascular territory of ischemic strokes.\n\nResultsThere were 62 stroke cases among 3923 COVID-19 admissions (incidence 1.6%). Data was available for 58 patients {mean age 52.6 years; age range 17-91; F/M=20/38; 24% (14/58) aged [&le;]40; 51% (30/58) hypertensive; 36% (21/58) diabetic; 41% (24/58) with O2 saturation <95% at admission; 32/58 (55.17 %) in-hospital mortality}. Among 58 strokes, there were 44 arterial infarcts, seven bleeds, three arterial infarcts with associated cerebral venous sinus thrombosis, two combined infarct and bleed, and two of indeterminate type. Among the total 49 infarcts, Carotid territory was the commonest affected (36/49; 73.5%), followed by vertebrobasilar (7/49; 14.3%) and both (6/49; 12.2%). Concordant arterial block was seen in 61% (19 of 31 infarcts with angiography done).  Early stroke (within 48 hours of respiratory symptoms) was seen in 82.7% (48/58) patients. Patients with poor saturation at admission were older (58 vs 49 years) and had more comorbidities and higher mortality (79% vs 38%). Mortality was similar in young strokes and older patients, although the latter required more intense respiratory support. Logistic regression analysis showed that low GCS and requirement for increasing intensity of respiratory support predicted in-hospital mortality.\n\nConclusionsWe had a 1.6% incidence of COVID-19 related stroke of which the majority were carotid territory infarcts. In-hospital mortality was 55.17%, predicted by low GCS at admission.",
-    "rel_num_authors": 26,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.13.21251670",
+    "rel_abs": "BackgroundCountermeasures against COVID-19 outbreak such as lockdown and voluntary restrictions against going out adversely affect human stress and economic activity. Particularly, this stress might lead to suicide.\n\nObjectWe examined excess mortality attributable to suicide caused by COVID-19. Method: We applied the NIID model to suicide deaths from October 2009 through September, 2021 for the whole of Japan by gender. Effects of the great earthquake that struck in eastern Japan on March 11, 2011 were incorporated into the estimation model. Results: Significant excess mortality in suicide was found between July, 2020 and July, 2021 for both genders. However, in August and September, 2021, excess mortality in suicide was detected only in female. It was greater among females than among males. In total, 2950 excess cases of mortality were identified.\n\nDiscussion and ConclusionExcess mortality during the four months was more than two times greater than the number of COVID-19 deaths confirmed by PCR testing. Countermeasures against COVID-19 should be chosen carefully in light of suicide effects.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Uma Sundar",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Niteen Karnik",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Amita Mukhopadhyay",
-        "author_inst": "Dr Chandramma Dayananda Sagar Institute of Medical Education and Research, Kanakapura 562112, Ramanagara District, Karnataka, India"
-      },
-      {
-        "author_name": "Pramod Darole",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Shaonak Kolte",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Ashank Bansal",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Yojana Gokhale",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Dnaneshwar Asole",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Anagha Joshi",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Sangeeta Pednekar",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Swati Chavan",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Trupti Trivedi",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Namita Padwal",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Lalana Kalekar",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Charulata Londhe",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Rupal Padhiyar",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Dharmendra Pandey",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Dhirendra Yadav",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Sonal Honrao",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Prerana Bhavsar",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Priyanshu Shah",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Satish Gosavi",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Aniket Wadal",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
-      },
-      {
-        "author_name": "Awesh Shingare",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
+        "author_name": "Junko Kurita",
+        "author_inst": "Tokiwa University, Ibaraki, Japan"
       },
       {
-        "author_name": "Mayuri Trivedi",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
+        "author_name": "Tamie Sugawara",
+        "author_inst": "Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Shinjuku, Tokyo, Japan"
       },
       {
-        "author_name": "Gauri Pathak Oak",
-        "author_inst": "Lokmanya Tilak Municipal Medical College and General Hospital (LTMMC&GH), Sion, Mumbai 400022, Maharashtra, India"
+        "author_name": "Yasushi Ohkusa",
+        "author_inst": "Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Shinjuku, Tokyo, Japan"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -880237,105 +883540,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.02.15.21251781",
-    "rel_title": "Epidemiological dynamics of the incidence of COVID-19 in children and the relationship with the opening of schools in Catalonia (Spain)",
+    "rel_doi": "10.1101/2021.02.15.21251788",
+    "rel_title": "COVID-19 European Regional Tracker",
     "rel_date": "2021-02-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251781",
-    "rel_abs": "Here we analyse the epidemiological trend of the incidence of COVID-19 in children in Catalonia (Spain) during the first 20 weeks of the 2020-2021 school year. This study demonstrates that while schools were open the incidence rate among children remained significantly lower than in general population, despite a greater diagnostic effort in children. These results suggest that schools have not played a significant role in the SARS-CoV-2 dissemination in Catalonia.",
-    "rel_num_authors": 22,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251788",
+    "rel_abs": "This Tracker presents data on daily COVID-19 cases at the sub-national level for 26 European countries from January 2020 till present. Country-level data sources are identified and processed to form a homogenized panel at the NUTS 3 or NUTS 2 level, the two lowest standardized administrative units of Europe. The strengths and weaknesses of each country dataset are discussed in detail. The raw data, spatial layers, the code, and the final homogenized files are provided in an online repository for replication. The data highlights the spatial distribution of cases both within and across countries that can be utilized for a disaggregated analysis on the impacts of the pandemic. The Tracker is updated monthly to expand its coverage.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Aida Perramon",
-        "author_inst": "Universitat Pompeu Fabra, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Antoni Soriano-Arandes",
-        "author_inst": "Pediatric Infectious Diseases and Immunodeficiencies Unit, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "David Pino",
-        "author_inst": "Department of Physics, Universitat Politecnica de Catalunya (UPC BarcelonaTech), Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Uxue Lazcano",
-        "author_inst": "Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS), Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Cristina Andres",
-        "author_inst": "Respiratory Viruses Unit, Department of Microbiology, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Marti Catala",
-        "author_inst": "Comparative Medicine and Bioimage Centre of Catalonia (CMCiB), Fundacio Institut d'Investigacio en Ciencies de la Salut Germans Trias i Pujol (IGTP), Badalona, "
-      },
-      {
-        "author_name": "Anna Gatell",
-        "author_inst": "Equip Pediatria Territorial Alt Penedes-Garraf, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Mireia Carulla",
-        "author_inst": "ABS Pla d'Urgell (Mollerussa), Lleida, Catalonia, Spain"
-      },
-      {
-        "author_name": "Dolors Canadell",
-        "author_inst": "CAP Barbera del Valles, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Gemma Ricos",
-        "author_inst": "CAP Drassanes, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Maria Teresa Riera-Bosch",
-        "author_inst": "EAP Vic Nord, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Silvia Burgaya",
-        "author_inst": "EAP Manlleu, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Olga Salvado",
-        "author_inst": "CAP Llibertat Reus, Tarragona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Javier Cantero",
-        "author_inst": "Corporacio del Maresme i la Selva, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Monica Vila",
-        "author_inst": "EAP Horta, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Miriam Poblet",
-        "author_inst": "Equip Territorial Pediatric Sabadell Nord, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Almudena Sanchez",
-        "author_inst": "CAP Les Hortes, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Anna Maria Ristol",
-        "author_inst": "CAP Can Serra Hospitalet de Llobregat, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Pepe Serrano",
-        "author_inst": "Equip Pediatria Territorial Alt Penedes-Garraf, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Andres Anton",
-        "author_inst": "Respiratory Viruses Unit, Department of Microbiology, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Clara Prats",
-        "author_inst": "Department of Physics, Universitat Politecnica de Catalunya (UPC BarcelonaTech), Barcelona, Catalonia, Spain"
-      },
-      {
-        "author_name": "Pere Soler-Palacin",
-        "author_inst": "Pediatric Infectious Diseases and Immunodeficiencies Unit, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain"
+        "author_name": "Asjad Naqvi",
+        "author_inst": "International Institute for Applied Systems Analysis (IIASA)"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -882126,135 +885345,71 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.02.15.431291",
-    "rel_title": "Favourable antibody responses to human coronaviruses in children and adolescents with autoimmune rheumatic diseases",
+    "rel_doi": "10.1101/2021.02.15.430863",
+    "rel_title": "Live attenuated SARS-CoV-2 vaccine candidate: Protective immunity without serious lung lesions in Syrian hamsters",
     "rel_date": "2021-02-16",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.15.431291",
-    "rel_abs": "Differences in humoral immunity to coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), between children and adults remain unexplained and the impact of underlying immune dysfunction or suppression unknown. Here, we examined the antibody immune competence of children and adolescents with prevalent inflammatory rheumatic diseases, juvenile idiopathic arthritis (JIA), juvenile dermatomyositis (JDM) and juvenile systemic lupus erythematosus (JSLE), against the seasonal human coronavirus (HCoV)-OC43 that frequently infects this age group. Despite immune dysfunction and immunosuppressive treatment, JIA, JDM and JSLE patients mounted comparable or stronger responses than healthier peers, dominated by IgG antibodies to HCoV-OC43 spike, and harboured IgG antibodies that cross-reacted with SARS-CoV-2 spike. In contrast, responses to HCoV-OC43 and SARS-CoV-2 nucleoproteins exhibited delayed age-dependent class-switching and were not elevated in JIA, JDM and JSLE patients, arguing against increased exposure. Consequently, autoimmune rheumatic diseases and their treatment were associated with a favourable ratio of spike to nucleoprotein antibodies.",
-    "rel_num_authors": 29,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.15.430863",
+    "rel_abs": "Live attenuated vaccines are generally highly effective. Here, we aimed to develop one against SARS-CoV-2, based on the identification of three types of temperature-sensitive (TS) strains with mutations in nonstructural proteins (nsp), impaired proliferation at 37-39{degrees}C, and the capacity to induce protective immunity in Syrian hamsters. To develop a live-attenuated vaccine, we generated a virus that combined all these TS-associated mutations (rTS-all), which showed a robust TS phenotype in vitro and high attenuation in vivo. The vaccine induced an effective cross-reactive immune response and protected hamsters against homologous or heterologous viral challenges. Importantly, rTS-all rarely reverted to the wild-type phenotype. By combining these mutations with an Omicron spike protein to construct a recombinant virus, protection against the Omicron strain was obtained. We show that immediate and effective live-attenuated vaccine candidates against SARS-CoV-2 variants may be developed using rTS-all as a backbone to incorporate the spike protein of the variants.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Claire Deakin",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Georgina Cornish",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Kevin Ng",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Nikhil Faulkner",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "William Bolland",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Veera Panova",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Joshua Hope",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Annachiara Rosa",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Ruth Harvey",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Saira Hussain",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Chris Earl",
-        "author_inst": "The Francis Crick Institute"
-      },
-      {
-        "author_name": "Bethany Jebson",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Merry Wilkinson",
-        "author_inst": "UCL"
+        "author_name": "Akiho Yoshida",
+        "author_inst": "Virus vaccine group, BIKEN Innovative Vaccine Research Alliance Laboratories, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, S"
       },
       {
-        "author_name": "Lucy Marshall",
-        "author_inst": "UCL"
+        "author_name": "Shinya Okamura",
+        "author_inst": "Virus vaccine group, BIKEN Innovative Vaccine Research Alliance Laboratories, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, S"
       },
       {
-        "author_name": "Lizzy Rosser",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Ania Radziszewska",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Hannah Peckham",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Judith Heaney",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Hannah Rickman",
-        "author_inst": "UCL"
+        "author_name": "Shiho Torii",
+        "author_inst": "Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka, Japan"
       },
       {
-        "author_name": "Stavroula Paraskevopoulou",
-        "author_inst": "UCL"
+        "author_name": "Sayuri Komatsu",
+        "author_inst": "Virus Vaccine Group, BIKEN Innovative Vaccine Research Alliance Laboratories, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, S"
       },
       {
-        "author_name": "Catherine Houlihan",
-        "author_inst": "UCL"
+        "author_name": "Paola Miyazato",
+        "author_inst": "Virus vaccine group, BIKEN Innovative Vaccine Research Alliance Laboratories, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, S"
       },
       {
-        "author_name": "Moria Spyer",
-        "author_inst": "UCL"
+        "author_name": "Shiori Ueno",
+        "author_inst": "Department of Infectious Diseases and Host Defense, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan"
       },
       {
-        "author_name": "Steve Gamblin",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Hidehiko Suzuki",
+        "author_inst": "Virus vaccine group, BIKEN Innovative Vaccine Research Alliance Laboratories, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, S"
       },
       {
-        "author_name": "John Mccauley",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Wataru Kamitani",
+        "author_inst": "Department of Infectious Diseases and Host Defense, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan"
       },
       {
-        "author_name": "Eleni Nastouli",
-        "author_inst": "UCL"
+        "author_name": "Chikako Ono",
+        "author_inst": "Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka, Japan"
       },
       {
-        "author_name": "Peter Cherepanov",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Yoshiharu Matsuura",
+        "author_inst": "Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka, Japan"
       },
       {
-        "author_name": "Coziana Ciurtin",
-        "author_inst": "UCL"
+        "author_name": "Shiro Takekawa",
+        "author_inst": "The Research Foundation for Microbial Diseases of Osaka University, Suita, Osaka, Japan"
       },
       {
-        "author_name": "Lucy Wedderburn",
-        "author_inst": "UCL"
+        "author_name": "Koichi Yamanishi",
+        "author_inst": "The Research Foundation for Microbial Diseases of Osaka University, Suita, Osaka, Japan"
       },
       {
-        "author_name": "George Kassiotis",
-        "author_inst": "The Francis Crick Institute"
+        "author_name": "Hirotaka Ebina",
+        "author_inst": "Virus vaccine group, BIKEN Innovative Vaccine Research Alliance Laboratories, Research institute for Microbial Diseases, Osaka University, Suita, Osaka, Japan."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.02.16.431305",
@@ -883835,31 +886990,35 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2021.02.12.431032",
-    "rel_title": "Pulsed broad-spectrum UV light effectively inactivates SARS-CoV-2 on multiple surfaces",
+    "rel_doi": "10.1101/2021.02.12.431026",
+    "rel_title": "Jumper Enables Discontinuous Transcript Assembly in Coronaviruses",
     "rel_date": "2021-02-15",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.12.431032",
-    "rel_abs": "The ongoing SARS-CoV-2 pandemic has resulted in an increased need for technologies capable of efficiently disinfecting public spaces as well as personal protective equipment. UV light disinfection is a well-established method for inactivating respiratory viruses. Here, we have determined that broad-spectrum, pulsed UV light is effective at inactivating SARS-CoV-2 on multiple surfaces. For hard, non-porous surfaces we observed that SARS-CoV-2 was inactivated to undetectable levels on plastic and glass with a UV dose of 34.9 mJ/cm2 and stainless steel with a dose of 52.5 mJ/cm2. We also observed that broad-spectrum, pulsed UV light is effective at reducing SARS-CoV-2 on N95 respirator material to undetectable levels with a dose of 103 mJ/cm2. We included UV dosimeter cards that provide a colorimetric readout of UV dose and demonstrated their utility as a means to confirm desired levels of exposure were reached. Together, the results present here demonstrate that broad-spectrum, pulsed UV light is an effective technology for the inactivation of SARS-CoV-2 on multiple surfaces.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.12.431026",
+    "rel_abs": "Genes in SARS-CoV-2 and, more generally, in viruses in the order of Nidovirales are expressed by a process of discontinuous transcription mediated by the viral RNA-dependent RNA polymerase. This process is distinct from alternative splicing in eukaryotes, rendering current transcript assembly methods unsuitable to Nidovirales sequencing samples. Here, we introduce the DO_SCPLOWISCONTINUOUSC_SCPLOW TO_SCPLOWRANSCRIPTC_SCPLOW AO_SCPLOWSSEMBLYC_SCPLOW problem of finding transcripts [Formula] and their abundances c given an alignment [Formula] under a maximum likelihood model that accounts for varying transcript lengths. Underpinning our approach is the concept of a segment graph, a directed acyclic graph that, distinct from the splice graph used to characterize alternative splicing, has a unique Hamiltonian path. We provide a compact characterization of solutions as subsets of non-overlapping edges in this graph, enabling the formulation of an efficient mixed integer linear program. We show using simulations that our method, JO_SCPLOWUMPERC_SCPLOW, drastically outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1 and SARS-CoV-2 samples, we find that JO_SCPLOWUMPERC_SCPLOW not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are well supported by direct evidence from long-read data, presence in multiple, independent samples or a conserved core sequence. JO_SCPLOWUMPERC_SCPLOW enables detailed analyses of Nidovirales transcriptomes.\n\nCode availabilitySoftware is available at https://github.com/elkebir-group/Jumper",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Alexander S Jureka",
-        "author_inst": "Georgia State University"
+        "author_name": "Palash Sashittal",
+        "author_inst": "University of Illinois, Urbana-Champaign"
       },
       {
-        "author_name": "Caroline G Williams",
-        "author_inst": "Georgia State University"
+        "author_name": "Chuanyi Zhang",
+        "author_inst": "University of Illinois at Urbana-Champaign"
       },
       {
-        "author_name": "Christopher F Basler",
-        "author_inst": "Georgia State University"
+        "author_name": "Jian Peng",
+        "author_inst": "University of Illinois at Urbana-Champaign"
+      },
+      {
+        "author_name": "Mohammed El-Kebir",
+        "author_inst": "UIUC"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc",
     "type": "new results",
-    "category": "microbiology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.02.11.430757",
@@ -885381,83 +888540,31 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.02.10.21251478",
-    "rel_title": "CATALYST trial protocol: A multicentre, open-label, phase II, multi-arm trial for an early and accelerated evaluation of the potential treatments for COVID-19 in hospitalised adults",
+    "rel_doi": "10.1101/2021.02.11.21251581",
+    "rel_title": "A genetically-informed study disentangling the relationships between tobacco smoking, cannabis use, alcohol consumption, substance use disorders and respiratory infections, including COVID-19",
     "rel_date": "2021-02-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251478",
-    "rel_abs": "IntroductionSevere SARS-CoV-2 infection is associated with a dysregulated immune response. Inflammatory monocytes and macrophages are crucial, promoting injurious, pro-inflammatory sequelae. Immunomodulation is, therefore, an attractive therapeutic strategy and we sought to test licensed and novel candidate drugs.\n\nMethods and analysisThe CATALYST trial is a multi-arm, open-label, multi-centre, phase II platform trial designed to identify candidate novel treatments to improve outcomes of patients hospitalised with COVID-19 compared with usual care. Treatments with evidence of biomarker improvements will be put forward for larger-scale testing by current national phase III platform trials. Hospitalised patients >16 years with a clinical picture strongly suggestive of SARS-CoV-2 pneumonia (confirmed by chest X-ray or CT scan, with or without a positive reverse transcription polymerase chain reaction (RT-PCR) assay) and a C-Reactive Protein (CRP) [&ge;]40 mg/L are eligible. The primary outcome measure is CRP, measured serially from admission to day 14, hospital discharge or death. Secondary outcomes include the WHO Clinical Progression Improvement Scale as a principal efficacy assessment.\n\nEthics and disseminationThe protocol was approved by the East Midlands - Nottingham 2 Research Ethics Committee (20/EM/0115) and given Urgent Public Health status; initial approval was received on 05-May-2020, current protocol version (v6.0) approval on 12-Oct-2020. The MHRA also approved all protocol versions. The results of this trial will be disseminated through national and international presentations and peer-reviewed publications.\n\nTrial registration numberEudraCT Number: 2020-001684-89\n\nISRCTN Number: 40580903\n\nStrengths and limitations of this trialO_LICATALYST will provide a rapid readout on the safety and proof-of-concept of candidate novel treatments\nC_LIO_LICATALYST will enable phase III trial resources to be focussed and allocated for agents with a high likelihood of success\nC_LIO_LICATALYST uses Bayesian multi-level models to allow for nesting of repeated measures data, with factors for each individual patient and treatment arm, and allowing for non-linear responses\nC_LIO_LICATALYST is not designed to provide a definitive signal on clinical outcomes\nC_LI",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.11.21251581",
+    "rel_abs": "BackgroundObservational studies suggest smoking, cannabis use, alcohol consumption, cannabis use, and substance use disorders (SUDs) may play a role in the susceptibility for respiratory infections and disease, including coronavirus 2019 (COVID-2019). However, causal inference is challenging due to comorbid substance use.\n\nMethodsUsing genome-wide association study data of European ancestry (data from >1.7 million individuals), we performed single-variable and multivariable Mendelian randomization to evaluate relationships between smoking, cannabis use, alcohol consumption, SUDs, and respiratory infections.\n\nResultsGenetically predicted lifetime smoking was found to be associated with increased risk for hospitalized COVID-19 (odds ratio (OR)=4.039, 95% CI 2.335-6.985, P-value=5.93x10-7) and very severe hospitalized COVID-19 (OR=3.091, 95% CI, 1.883-5.092, P-value=8.40x10-6). Genetically predicted lifetime smoking was also associated with increased risk pneumoniae (OR=1.589, 95% CI, 1.214-2.078, P-value=7.33x10-4), lower respiratory infections (OR=2.303, 95% CI, 1.713-3.097, P-value=3.40x10-8), and several others. Genetically predicted cannabis use disorder (CUD) was associated with increased bronchitis risk (OR=1.078, 95% CI, 1.020-1.128, P-value=0.007).\n\nConclusionsWe provide strong genetic evidence showing smoking increases the risk for respiratory infections and diseases even after accounting for other substance use and abuse. Additionally, we provide find CUD may increase the risk for bronchitis, which taken together, may guide future research SUDs and respiratory outcomes.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Tonny Veenith",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Benjamin A Fisher",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Daniel Slade",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Anna Rowe",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Rowena Sharpe",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "David R Thickett",
-        "author_inst": "University of Birmingham"
+        "author_name": "DANIEL B Rosoff",
+        "author_inst": "NIAAA/NIH Oxford-Cambridge Scholars Program"
       },
       {
-        "author_name": "Tony Whitehouse",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Matthew Rowland",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "James Scriven",
-        "author_inst": "University Hospitals Birmingham NHS Trust"
+        "author_name": "Joyce Yoo",
+        "author_inst": "Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA"
       },
       {
-        "author_name": "Dhruv Parekh",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Sarah J Bowden",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Joshua S Savage",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Duncan Richards",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Julian Bion",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Pamela Kearns",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Simon Gates",
-        "author_inst": "University of Birmingham"
+        "author_name": "Falk W Lohoff",
+        "author_inst": "Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "intensive care and critical care medicine"
+    "category": "addiction medicine"
   },
   {
     "rel_doi": "10.1101/2021.02.11.21251585",
@@ -887171,228 +890278,28 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.10.21251247",
-    "rel_title": "Safety and efficacy of the ChAdOx1 nCoV-19 (AZD1222) Covid-19 vaccine against the B.1.351 variant in South Africa",
+    "rel_doi": "10.1101/2021.02.10.21251392",
+    "rel_title": "COVID-19 and Influenza: Vaccination Before and During the Pandemic among the Lebanese Adult Population",
     "rel_date": "2021-02-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251247",
-    "rel_num_authors": 53,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251392",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Shabir Ahmed Madhi",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Vicky Lynne Baillie",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Clare Louise Cutland",
-        "author_inst": "Wits- Alive: African Leadership in Vaccinology Expertise, University of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Merryn Voysey",
-        "author_inst": "Oxford Vaccine Group, Department of Paediatrics, University of Oxford, UK"
-      },
-      {
-        "author_name": "Anthonet L Koen",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Lee Fairlie",
-        "author_inst": "Wits Reproductive Health and HIV Institute, Faculty of Health Sciences, University of the Witwatersrand, Johanesburg, South Africa"
-      },
-      {
-        "author_name": "Sherman D Padayachee",
-        "author_inst": "Setshaba Research Centre, Tshwane, South Africa"
-      },
-      {
-        "author_name": "Keertan Dheda",
-        "author_inst": "Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute University of Cape Town, South Africa"
-      },
-      {
-        "author_name": "Shaun L Barnabas",
-        "author_inst": "Family Centre for Research with Ubuntu, Department of Paediatrics, University of Stellenbosch, Cape Town, South Africa"
-      },
-      {
-        "author_name": "Qasim Ebrahim Bhorat",
-        "author_inst": "Soweto Clinical Trials Centre"
-      },
-      {
-        "author_name": "Carmen Briner",
-        "author_inst": "Perinatal HIV Research Unit, Faculty of Health Science, University of the Witwatersrand, South Africa"
-      },
-      {
-        "author_name": "Gaurav Kwatra",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Khatija Ahmed",
-        "author_inst": "Setshaba Research Centre, Tshwane, South Africa"
-      },
-      {
-        "author_name": "Parvinder Aley",
-        "author_inst": "Oxford Vaccine Group, Department of Paediatrics, University of Oxford, UK"
-      },
-      {
-        "author_name": "Sutika Bhikha",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Jinal N Bhiman",
-        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa."
-      },
-      {
-        "author_name": "As'ad Ebrahim Bhorat",
-        "author_inst": "Soweto Clinical Trials Centre, Soweto, South Africa"
-      },
-      {
-        "author_name": "Jeanine du plessis",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Aliasgar Esmail",
-        "author_inst": "Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute University of Cape Town, South Africa"
-      },
-      {
-        "author_name": "Marisa Groenewald",
-        "author_inst": "Family Centre for Research with Ubuntu, Department of Paediatrics, University of Stellenbosch, Cape Town, South Africa"
-      },
-      {
-        "author_name": "Elizea Horne",
-        "author_inst": "Wits Reproductive Health and HIV Institute, Faculty of Health Sciences, University of the Witwatersrand, Johanesburg, South Africa"
-      },
-      {
-        "author_name": "Shi-Hsia Hwa",
-        "author_inst": "Africa Health Research Institute, Durban 4001, South Africa."
-      },
-      {
-        "author_name": "Aylin Jose",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Teresa Lambe",
-        "author_inst": "Jenner Institute, Nuffield Department of Medicine, University of Oxford, UK"
-      },
-      {
-        "author_name": "Matt Laubscher",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Mookho Malahleha",
-        "author_inst": "Setshaba Research Centre, Tshwane, South Africa"
-      },
-      {
-        "author_name": "Masebole Masenya",
-        "author_inst": "Wits Reproductive Health and HIV Institute, Faculty of Health Sciences, University of the Witwatersrand, Johanesburg, South Africa"
-      },
-      {
-        "author_name": "Mduduzi Masilela",
-        "author_inst": "Setshaba Research Centre, Tshwane, South Africa"
-      },
-      {
-        "author_name": "Shakeel McKenzie",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Kgaogelo Molapo",
-        "author_inst": "Setshaba Research Centre, Tshwane, South Africa"
-      },
-      {
-        "author_name": "Andrew Moultrie",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Suzette Oelofse",
-        "author_inst": "Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute University of Cape Town, South Africa"
-      },
-      {
-        "author_name": "Faeezah Patel",
-        "author_inst": "Wits Reproductive Health and HIV Institute, Faculty of Health Sciences, University of the Witwatersrand, Johanesburg, South Africa"
-      },
-      {
-        "author_name": "Sureshnee Pillay",
-        "author_inst": "KwaZulu-Natal Research and Innovation Sequencing Platform (KRISP), University of KwaZulu-Natal, Durban South Africa"
-      },
-      {
-        "author_name": "Sarah Rhead",
-        "author_inst": "Oxford Vaccine Group, Department of Paediatrics, University of Oxford, UK"
-      },
-      {
-        "author_name": "Hylton Rodel",
-        "author_inst": "Africa Health Research Institute, Durban 4001, South Africa."
-      },
-      {
-        "author_name": "Lindie Rossouw",
-        "author_inst": "Family Centre for Research with Ubuntu, Department of Paediatrics, University of Stellenbosch, Cape Town, South Africa"
-      },
-      {
-        "author_name": "Carol Taoushanis",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Houryiah Tegally",
-        "author_inst": "KwaZulu-Natal Research and Innovation Sequencing Platform (KRISP), University of KwaZulu-Natal, Durban South Africa"
-      },
-      {
-        "author_name": "Asha Thombrayil",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
-      },
-      {
-        "author_name": "Samuel van Eck",
-        "author_inst": "Wits Reproductive Health and HIV Institute, Faculty of Health Sciences, University of the Witwatersrand, Johanesburg, South Africa"
-      },
-      {
-        "author_name": "Constantinos Wibmer",
-        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa."
-      },
-      {
-        "author_name": "Nicholas M Durham",
-        "author_inst": "Astra Zeneca Biopharmaceuticals, Cambridge, UK"
-      },
-      {
-        "author_name": "Elizabeth J Kelly",
-        "author_inst": "Astra Zeneca Biopharmaceuticals, Cambridge, UK"
-      },
-      {
-        "author_name": "Tonya Villafana",
-        "author_inst": "Astra Zeneca Biopharmaceuticals, Cambridge, UK"
-      },
-      {
-        "author_name": "Sarah Gilbert",
-        "author_inst": "Jenner Institute, Nuffield Department of Medicine, University of Oxford, UK"
-      },
-      {
-        "author_name": "Andrew J Pollard",
-        "author_inst": "Oxford Vaccine Group, Department of Paediatrics, University of Oxford, UK"
-      },
-      {
-        "author_name": "Tulio de Oliveira",
-        "author_inst": "KwaZulu-Natal Research and Innovation Sequencing Platform (KRISP), University of KwaZulu-Natal, Durban South Africa"
-      },
-      {
-        "author_name": "Penny L Moore",
-        "author_inst": "National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa."
-      },
-      {
-        "author_name": "Alex Sigal",
-        "author_inst": "Africa Health Research Institute, Durban 4001, South Africa."
-      },
-      {
-        "author_name": "Alane Izu",
-        "author_inst": "Wits-VIDA - Vaccines and infectious diseases analytical research unit, Universtiy of the Witwatersrand, Johannesburg, South Africa"
+        "author_name": "Anthony Elia",
+        "author_inst": "Lebanese American University"
       },
       {
-        "author_name": "- Network for Genomic Surveillance in South Africa (NGS-SA)",
-        "author_inst": ""
+        "author_name": "Nedal Taha",
+        "author_inst": "Lebanese American University"
       },
       {
-        "author_name": "- Wits VIDA COVID vaccine trial group",
-        "author_inst": ""
+        "author_name": "Sima T Tokajian",
+        "author_inst": "Lebanese American University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -889181,51 +892088,151 @@
     "category": "cardiovascular medicine"
   },
   {
-    "rel_doi": "10.1101/2021.02.08.21250309",
-    "rel_title": "Hospitalizations for emergency-sensitive conditions in Germany during the Covid-19 pandemic - Insights from the German-wide Helios hospital network",
+    "rel_doi": "10.1101/2021.02.10.430668",
+    "rel_title": "Data-driven analysis of COVID-19 reveals specific severity patterns distinct from the temporal immune response",
     "rel_date": "2021-02-11",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21250309",
-    "rel_abs": "BackgroundWhile there are numerous reports that describe emergency care during the early Covid-19 pandemic, there is scarcity of data for later stages. This study analyzes hospitalization rates for 37 emergency-sensitive conditions in the largest German-wide hospital network during different pandemic phases.\n\nMethodsUsing claims data of 80 hospitals, consecutive cases between January 1 and November 17, 2020 were analyzed and compared to a corresponding period in 2019. Incidence-rate ratios (IRR) comparing the both periods were calculated using Poisson regression to model the number of hospitalizations per day.\n\nResultsThere was a hospitalization deficit between March 12 and June 13, 2020 (coinciding with the 1st pandemic wave) with 32,807 hospitalizations as opposed to 39,379 in 2019 (IRR 0.83, 95% CI 0.82 - 0.85, P<0.01). During the following period (June 14 to November 17, 2020, including the start of 2nd wave), hospitalizations were reduced from 63,799 in 2019 to 59,910 in 2020, but this reduction was not that pronounced (IRR 0.94, 95% CI 0.93 - 0.95, P<0.01). There was an increase in hospitalizations for acute myocardial infarction, aortic aneurism/dissection and pulmonary embolism after the 1st wave during which hospitalizations had been reduced for those conditions. In contrast, hospitalizations for sepsis, pneumonia, obstructive pulmonary disease, and intracranial injuries were reduced during the entire pandemic.\n\nConclusionsThere was an overall reduction of hospitalizations for emergency-sensitive conditions in Germany during the Covid-19 pandemic with heterogeneous effects on different disease categories. The increase of hospitalizations for acute myocardial infarction, aortic aneurism/dissection and pulmonary embolism is an alarming signal that requires attention and further studies.\n\nKEY MESSAGESO_ST_ABSWhat is already known on this subjectC_ST_ABSO_LIThere has been a reduction in emergency room visits and hospital admissions for several emergent medical and surgical conditions during the early Covid-19 pandemic (1st wave).\nC_LI\n\nWhat this study addsO_LIUsing claims data of 80 German-wide Helios hospitals, we found an overall reduction of hospitalizations for emergency-sensitive conditions in Germany during the Covid-19 pandemic until mid November 2020 with heterogeneous effects on different disease categories. While hospitalizations for sepsis, pneumonia, obstructive pulmonary disease, and intracranial injuries were reduced during the entire pandemic. There was an alarming increase of hospitalizations for acute myocardial infarction, aortic aneurism/dissection and pulmonary embolism after the 1st wave.\nC_LI",
-    "rel_num_authors": 8,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.10.430668",
+    "rel_abs": "Key immune signatures of SARS-CoV-2 infection may associate with either adverse immune reactions (severity) or simply an ongoing anti-viral response (temporality); how immune signatures contribute to severe manifestations and/or temporal progression of disease and whether longer disease duration correlates with severity remain unknown. Patient blood was comprehensively immunophenotyped via mass cytometry and multiplex cytokine arrays, leading to the identification of 327 basic subsets that were further stratified into more than 5000 immunotypes and correlated with 28 plasma cytokines. Low-density neutrophil abundance was closely correlated with hepatocyte growth factor levels, which in turn correlated with disease severity. Deep analysis also revealed additional players, namely conventional type 2 dendritic cells, natural killer T cells, plasmablasts and CD16+ monocytes, that can influence COVID-19 severity independent of temporal progression. Herein, we provide interactive network analysis and data visualization tools to facilitate data mining and hypothesis generation for elucidating COVID-19 pathogenesis.",
+    "rel_num_authors": 33,
     "rel_authors": [
       {
-        "author_name": "ANDREAS BOLLMANN",
-        "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute"
+        "author_name": "Jackwee Lim",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
       },
       {
-        "author_name": "Sven Hohenstein",
-        "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute"
+        "author_name": "Guillaume Carissimo",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
       },
       {
-        "author_name": "Vincent Pellissier",
-        "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute"
+        "author_name": "Yi-Hao Chan",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
       },
       {
-        "author_name": "Sebastian Koenig",
-        "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute"
+        "author_name": "Siew-Wai Fong",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
       },
       {
-        "author_name": "Laura Ueberham",
-        "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute"
+        "author_name": "Wendy WL Lee",
+        "author_inst": "Singapore Immunology Network"
       },
       {
-        "author_name": "Gerhard Hindricks",
-        "author_inst": "Heart Center Leipzig at University of Leipzig and Leipzig Heart Institute"
+        "author_name": "Seow-Yen Tan",
+        "author_inst": "Changi General Hospital"
       },
       {
-        "author_name": "Andreas Meier-Hellmann",
-        "author_inst": "Helios Hospitals"
+        "author_name": "David C Lye",
+        "author_inst": "National Centre for Infectious Diseases, Singapore"
       },
       {
-        "author_name": "Ralf Kuhlen",
-        "author_inst": "Helios Health"
+        "author_name": "Barnaby E Young",
+        "author_inst": "National Centre for Infectious Diseases, Singapore"
+      },
+      {
+        "author_name": "Laurent Renia",
+        "author_inst": "Agency for Science, Technology and Research (A*STAR)"
+      },
+      {
+        "author_name": "Lisa Fong-Poh NG",
+        "author_inst": "Singapore Immunology Network, Agency for Science, Technology and Research, Singapore."
+      },
+      {
+        "author_name": "Olaf Rotzschke",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Kia Joo Puan",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Liang Wei Wang",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Karen Wei Weng Teng",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Chiew Yee Loh",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Kim Peng Tan",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Chek Meng Poh",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
+      },
+      {
+        "author_name": "Cheryl Yi-Pin Lee",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
+      },
+      {
+        "author_name": "Nicholas Kim-Wah Yeo",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
+      },
+      {
+        "author_name": "Rhonda Sin-Ling Chee",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
+      },
+      {
+        "author_name": "Siti Naqiah Amrun",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
+      },
+      {
+        "author_name": "Zi Wei Chang",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
+      },
+      {
+        "author_name": "Matthew Zirui Tay",
+        "author_inst": "Agency for Science, Technology and Research (A*STAR)"
+      },
+      {
+        "author_name": "Anthony Torres-Ruesta",
+        "author_inst": "Agency for Science, Technology and Research, Singapore"
+      },
+      {
+        "author_name": "Norman Leo Fernandez",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Wilson How",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Anand K. Andiappan",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Kaibo Duan",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
+      },
+      {
+        "author_name": "Gabriel Yan",
+        "author_inst": "National University Hospital"
+      },
+      {
+        "author_name": "Shirin Kalimuddin",
+        "author_inst": "Singapore General Hospital"
+      },
+      {
+        "author_name": "Yee-Sin Leo",
+        "author_inst": "National Centre for Infectious Diseases"
+      },
+      {
+        "author_name": "Sean W. X. Ong",
+        "author_inst": "National Centre for Infectious Diseases"
+      },
+      {
+        "author_name": "Bernett Lee",
+        "author_inst": "Singapore Immunology Network (A*STAR)"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "emergency medicine"
+    "license": "cc_by",
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.02.11.430787",
@@ -891395,57 +894402,49 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.02.07.21251311",
-    "rel_title": "Poor antigen-specific responses to the second BNT162b2 mRNA vaccine dose in SARS-CoV-2-experienced individuals",
+    "rel_doi": "10.1101/2021.02.07.21251309",
+    "rel_title": "The effect of respiratory activity, ventilatory therapy and facemasks on total aerosol emissions",
     "rel_date": "2021-02-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.07.21251311",
-    "rel_abs": "The use of COVID-19 vaccines will play the major role in helping to end the pandemic that has killed millions worldwide. COVID-19 vaccines have resulted in robust humoral responses and protective efficacy in human trials, but efficacy trials excluded individuals with a prior diagnosis of COVID-19. As a result, little is known about how immune responses induced by mRNA vaccines differ in individuals who recovered from COVID-19. Here, we evaluated longitudinal immune responses to two-dose BNT162b2 mRNA vaccination in 15 adults who recovered from COVID-19, compared to 21 adults who did not have prior COVID-19 diagnosis. Consistent with prior studies of mRNA vaccines, we observed robust cytotoxic CD8+ T cell responses in both cohorts following the second dose. Furthermore, SARS-CoV-2-naive individuals had progressive increases in humoral and antigen-specific antibody-secreting cell (ASC) responses following each dose of vaccine, whereas SARS-CoV-2-experienced individuals demonstrated strong humoral and antigen-specific ASC responses to the first dose but muted responses to the second dose of the vaccine at the time points studied. Together, these data highlight the relevance of immunological history for understanding vaccine immune responses and may have significant implications for personalizing mRNA vaccination regimens used to prevent COVID-19, including booster shots.\n\nOne Sentence SummaryPrior history of COVID-19 affects adaptive immune responses to mRNA vaccination.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.07.21251309",
+    "rel_abs": "Background Exhaled respirable aerosols (<5 m diameter) present a high risk of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission. Many guidelines recommend using aerosol precautions during \"aerosol generating procedures\" (AGPs) and droplet (>5 m) precautions at other times. However, there is emerging evidence that respiratory activities such as cough and not AGPs are the important source of aerosols. Methods We used a novel chamber with an optical particle counter sampling at 100 L/min to count and size-fractionate all exhaled particles (0.5-25 m). We compared emissions from ten healthy subjects during respiratory \"activities\" (quiet breathing, talking, shouting, forced expiratory maneuvers, exercise and coughing) with respiratory \"therapies\" designated as AGPs: high flow nasal oxygen (HFNO) and single or dual circuit non-invasive positive pressure ventilation, NIPPV-S and NIPPV-D, respectively. Activities were repeated wearing facemasks. Results Compared to quiet breathing, respiratory activities increased particle counts between 34.6-fold (95% confidence interval [CI], 15.2 to 79.1) during talking, to 370.8-fold (95% CI, 162.3 to 847.1) during coughing (p<0.001). During quiet breathing, HFNO at 60 L/min increased counts 2.3-fold (95% CI, 1.2 to 4.4) (p=0.03) and NIPPV-S and NIPPV-D at 25/10 cm H2O increased counts by 2.6-fold (95% CI, 1.7 to 4.1) and 7.8-fold (95% CI, 4.4 to 13.6) respectively (p<0.001). During activities, respiratory therapies and facemasks reduced emissions compared to activities alone. Conclusion Talking, exertional breathing and coughing generate substantially more aerosols than the respiratory therapies HFNO and NIPPV which can reduce total emissions. The risk of aerosol exposure is underappreciated and warrants widespread targeted interventions.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Marie Ines Samanovic-Golden",
-        "author_inst": "NYU School of Medicine"
-      },
-      {
-        "author_name": "Amber R Cornelius",
-        "author_inst": "NYU School of Medicine"
-      },
-      {
-        "author_name": "Sophie L Gray-Gaillard",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Nicholas Wilson",
+        "author_inst": "Prince of Wales Hospital"
       },
       {
-        "author_name": "Joseph Richard Allen",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Guy Marks",
+        "author_inst": "University of New South Wales, Sydney, Australia"
       },
       {
-        "author_name": "Trishala Karmacharya",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Andrew Eckhardt",
+        "author_inst": "Department of Intensive Care Medicine, Prince of Wales Hospital, Sydney, Australia"
       },
       {
-        "author_name": "Jimmy P Wilson",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Alyssa Clarke",
+        "author_inst": "Department of Intensive Care, Royal Prince Alfred Hospital, Camperdown, NSW, Australia"
       },
       {
-        "author_name": "Sara Wesley Hyman",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Francis Young",
+        "author_inst": "Department of Intensive Care Medicine, Prince of Wales Hospital, Sydney, Australia"
       },
       {
-        "author_name": "Michael Tuen",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Frances Garden",
+        "author_inst": "South Western Sydney Clinical School, University of New South Wales, Sydney, Australia"
       },
       {
-        "author_name": "Sergei B Koralov",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Warren Stewart",
+        "author_inst": "Department of Intensive Care Medicine, Prince of Wales Hospital, Sydney, Australia"
       },
       {
-        "author_name": "Mark J Mulligan",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Tim Cook",
+        "author_inst": "Department of Anaesthesia and Intensive Care Medicine, Royal United Hospital NHS Trust, Bath, UK"
       },
       {
-        "author_name": "Ramin Sedaghat Herati",
-        "author_inst": "NYU School of Medicine"
+        "author_name": "Euan Tovey",
+        "author_inst": "Woolcock Institute of Medical Research, University of Sydney, Glebe, NSW, Australia"
       }
     ],
     "version": "1",
@@ -893013,65 +896012,69 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.04.21251131",
-    "rel_title": "Using Machine Learning to Predict Mortality for COVID-19 Patients on Day Zero in the ICU",
+    "rel_doi": "10.1101/2021.02.04.21251170",
+    "rel_title": "Symptoms of COVID-19 infection and magnitude of antibody response in a large community-based study",
     "rel_date": "2021-02-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251131",
-    "rel_abs": "RationaleGiven the expanding number of COVID-19 cases and the potential for upcoming waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.\n\nObjectivesEarly prediction of mortality using machine learning based on typical laboratory results and clinical data registered on the day of ICU admission.\n\nMethodsWe studied retrospectively 263 COVID-19 ICU patients. To find parameters with the highest predictive values, Kolmogorov-Smirnov and Pearson chi-squared tests were used. Logistic regression and random forest (RF) algorithms were utilized to build classification models. The impact of each marker on the RF model predictions was studied by implementing the local interpretable model-agnostic explanation technique (LIME-SP).\n\nResultsAmong 66 documented parameters, 15 factors with the highest predictive values were identified as follows: gender, age, blood urea nitrogen (BUN), creatinine, international normalized ratio (INR), albumin, mean corpuscular volume, white blood cell count, segmented neutrophil count, lymphocyte count, red cell distribution width (RDW), and mean cell hemoglobin along with a history of neurological, cardiovascular, and respiratory disorders. Our RF model can predict patients outcomes with a sensitivity of 70% and a specificity of 75%.\n\nConclusionsThe most decisive variables in our model were increased levels of BUN, lowered albumin levels, increased creatinine, INR, and RDW along with gender and age. Complete blood count parameters were also crucial for some patients. Considering the importance of early triage decisions, this model can be a useful tool in COVID-19 ICU decision-making.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251170",
+    "rel_abs": "BackgroundThe majority of COVID-19 cases are asymptomatic, or minimally symptomatic with management in the home. Little is known about the frequency of specific symptoms in the general population, and how symptoms predict the magnitude of antibody response to SARS-CoV-2 infection.\n\nMethodsWe quantified IgG antibodies against the SARS-CoV-2 receptor binding domain (RBD) in home-collected dried blood spot samples from 3,365 adults participating in a community-based seroprevalence study in the city of Chicago, USA, collected between June 24 and November 11, 2020.\n\nResults17.8% of the sample was seropositive for SARS-CoV-2. A cluster of symptoms (loss of sense of smell or taste, fever, shortness of breath, muscle or body aches, cough, fatigue, diarrhea, headache) was associated with stronger anti-RBD IgG responses among the seropositives. 39.2% of infections were asymptomatic, and 2 or fewer symptoms were reported for 66.7% of infections. Total number of symptoms was positively but weakly associated with IgG response: Median anti-RBD IgG was 0.95 ug/mL for individuals with 3 or more symptoms, in comparison with 0.61 ug/mL for asymptomatic infections.\n\nConclusionWe document high rates of asymptomatic and mild infection in a large community-based cohort, and relatively low levels of anti-SARS-CoV-2 IgG antibody in the general population of previously exposed individuals.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Elham Jamshidi",
-        "author_inst": "Division of Pulmonary Medicine, Department of Medicine, Lausanne University Hospital (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland."
+        "author_name": "Thomas W McDade",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Amirhossein Asgary",
-        "author_inst": "Department of Biotechnology, College of Sciences, University of Tehran, Tehran, Iran."
+        "author_name": "Joshua Schrock",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Nader Tavakoli",
-        "author_inst": "Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran."
+        "author_name": "Richard D'Aquila",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Alireza Zali",
-        "author_inst": "Functional Neurosurgery Research Center, Shohada Tajrish Comprehensive Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehra"
+        "author_name": "Brian Mustanski",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Hadi Esmaily",
-        "author_inst": "Department of Clinical Pharmacy, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran."
+        "author_name": "Nanette Benbow",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Seyed Hamid Jamaldini",
-        "author_inst": "Department of Genetic, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran"
+        "author_name": "Lauren Vaught",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Amir Daaee",
-        "author_inst": "School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran"
+        "author_name": "Nina Reiser",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Amirhesam Babajani",
-        "author_inst": "Department of Pharmacology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran"
+        "author_name": "Matt Velez",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Mohammad Ali Sendani Kashi",
-        "author_inst": "Master of Business Administration (MBA)-University of Tehran, Tehran, Iran."
+        "author_name": "Ryan Hsieh",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Masoud Jamshidi",
-        "author_inst": "Department of Exercise Physiology, Tehran University, Iran."
+        "author_name": "Daniel Ryan",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Sahand Rahi",
-        "author_inst": "Laboratory of the Physics of Biological Systems, Institute of Physics, Ecole polytechnique federale de Lausanne (EPFL), Lausanne, Switzerland"
+        "author_name": "Rana Saber",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Nahal Mansouri",
-        "author_inst": "Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Ecole polytechnique federale de Lausanne (EPFL), Lausanne, Switzerland"
+        "author_name": "ELIZABETH MCNALLY",
+        "author_inst": "Northwestern University Feinberg School of Medicine"
+      },
+      {
+        "author_name": "Alexis R. Demonbreun",
+        "author_inst": "Northwestern University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -894987,55 +897990,31 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.02.06.21251099",
-    "rel_title": "COVID-19 increases age- and sex-controlled 21-day fatality rates for patients with melanoma, hematologic malignancies, uterine cancer, or kidney cancer",
+    "rel_doi": "10.1101/2021.02.05.21251085",
+    "rel_title": "Molecular Mechanism of Parosmia",
     "rel_date": "2021-02-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.06.21251099",
-    "rel_abs": "IntroductionPrior research has reported an increased risk of fatality for cancer patients, but most studies investigated the risk by comparing cancer patients to non-cancer patients among COVID-19 infections. Only a few studies have compared the impact of a COVID-19 infection to non-infection with matched cancer patients and types.\n\nMethods & MaterialsWe conducted survival analyses of 4,606 cancer patients with COVID-19 test results from March 16 to October 11, 2020 in UK Biobank and estimated the overall hazard ratio of fatality with and without COVID-19 infection. We also examined the hazard ratios of thirteen specific cancer types with at least 100 patients.\n\nResultsCOVID-19 resulted in an overall hazard ratio of 7.76 (95% CI: [5.78, 10.40], p<10-10) by studying the survival rate of 4,606 cancer patients for 21-days after the tests. The hazard ratio was shown to vary among cancer type, with over a 10-fold increase in fatality rate (false discovery rate[&le;]0.02) for melanoma, hematologic malignancies, uterine cancer, and kidney cancer using a stratified analysis on each of the cancer types. Although COVID-19 imposed a higher risk for localized cancers compared to distant metastasis ones, those of distant metastasis yielded higher fatality rates due to their multiplicative effects.\n\nConclusionThe results highlight the importance of timely care for localized and hematological cancer patients and the necessity to vaccinate uninfected patients as soon as possible, particularly for the cancer types influenced most by COVID-19.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.05.21251085",
+    "rel_abs": "The molecular stimuli that trigger a parosmic response have been identified. Parosmia is a debilitating disease in which familiar smells become distorted and unpleasant. Often a result of post infectious smell loss, incidences are increasing as the number of COVID-19 cases escalates worldwide. Little is understood of its pathophysiology, but the prevailing hypothesis for the underlying mechanism is a mis-wiring of olfactory sensory neurons. We identified 15 different molecular triggers in coffee using GC-Olfactometry as a relatively rapid screening tool for assessment of both quantitative olfactory loss and parosmia. This provides evidence for peripheral causation, but places constraints on the mis-wiring theory.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Haiquan Li",
-        "author_inst": "Department of Biosystems Engineering, University of Arizona"
-      },
-      {
-        "author_name": "Edwin Alexander Baldwin",
-        "author_inst": "Department of Biosystems Engineering, University of Arizona"
-      },
-      {
-        "author_name": "Xiang Zhang",
-        "author_inst": "Department of Biosystems Engineering, University of Arizona"
-      },
-      {
-        "author_name": "Colleen Kenost",
-        "author_inst": "Department of Biomedical Informatics, University of Utah"
-      },
-      {
-        "author_name": "Wenting Luo",
-        "author_inst": "Statistics and Data Science GIDP, Biosystems Analytics & Technology Program, University of Arizona"
-      },
-      {
-        "author_name": "Elizabeth A Calhoun",
-        "author_inst": "Department of Population Health, University of Kansas Medical Center"
-      },
-      {
-        "author_name": "Lingling An",
-        "author_inst": "Department of Biosystems Engineering, University of Arizona"
+        "author_name": "Jane K Parker",
+        "author_inst": "University of Reading"
       },
       {
-        "author_name": "Charles L Bennett",
-        "author_inst": "Department of Clinical Pharmacy and Outcomes Sciences, University of South Carolina"
+        "author_name": "Christine E Kelly",
+        "author_inst": "AbScent"
       },
       {
-        "author_name": "Yves A Lussier",
-        "author_inst": "Department of Biomedical Informatics, University of Utah"
+        "author_name": "Simon B Gane",
+        "author_inst": "Royal National Ear, Nose and Throat and Eastman Dental Hospitals"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "oncology"
+    "category": "otolaryngology"
   },
   {
     "rel_doi": "10.1101/2021.02.06.21251271",
@@ -896805,39 +899784,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.02.04.21251111",
-    "rel_title": "SARS-CoV-2 Worldwide Replication Drives Rapid Rise and Selection of Mutations across the Viral Genome: A Time-Course StudyPotential Challenge for Vaccines and Therapies",
+    "rel_doi": "10.1101/2021.02.04.21250932",
+    "rel_title": "The systemic inflammatory response and clinicopathological characteristics in patients admitted to hospital with COVID-19 infection: Comparison of 2 consecutive cohorts",
     "rel_date": "2021-02-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251111",
-    "rel_abs": "Scientists and the public were alarmed at the first large viral variant of SARS-CoV2 reported in December 2020. We have followed the time course of emerging viral mutants and variants during the SARS-CoV-2 pandemic in ten countries on four continents. We examined complete SARS-CoV-2 nucleotide sequences in GISAID, (Global Initiative of Sharing All Influenza Data) with sampling dates extending until January 20, 2021. These sequences originated from ten different countries: United Kingdom, South Africa, Brazil, USA, India, Russia, France, Spain, Germany, and China. Among the novel mutations, some previously reported mutations waned and some of them increased in prevalence over time. VUI2012/01 (B.1.1.7) and 501Y.V2 (B.1.351), the so-called UK and South Africa variants, respectively, and two variants from Brazil, 484K.V2, now called P.1 and P.2, increased in prevalence. Despite lockdowns, worldwide active replication in genetically and socio-economically diverse populations facilitated selection of new mutations. The data on mutant and variant SARS-CoV-2 strains provided here comprise a global resource for easy access to the myriad mutations and variants detected to date globally. Rapidly evolving new variant and mutant strains might give rise to escape variants, capable of limiting the efficacy of vaccines, therapies, and diagnostic tests.\n\nSignificance and New Aspects of Study - SynopsisO_LIWe examine the time course of emerging mutations in the SARS-CoV-2 genome that have rapidly been selected in the worlds populations through the beginning of 2021. A study of the prevalence of viral mutations in the GISAID database in ten different countries - United Kingdom, South Africa, Brazil, US, India, Russia, France, Spain, Germany, and China - revealed widespread mutations along the genome.\nC_LIO_LIWe previously identified about 10 hotspot mutations in the SARS-CoV-2 genome that became prevalent in many of the countries studied1. Since the beginning of February, many new mutations arose in the ten countries (and worldwide). The preponderance of variants and mutations correlated with the increased spread of Covid-19.\nC_LIO_LIThere was a temporal progression from about 10 predominant mutants shared by several countries up to the end of May 2020, followed by a consistent and rapid increase in the number of new mutations between June and December along with the emergence of variants of concern, first reported in December 2020.\nC_LIO_LIWe examine the relative frequencies of mutations, along with variants of interest, in 10 countries up until January 20, 2021. Investigations on the pathogenic properties of individual SARS-CoV-2 mutations will be urgently needed to understand the kaleidoscopic patterns of worldwide Covid-19 outbreaks and symptoms. Monitoring the frequency and speed of mutant selection have direct relevance to diagnostic testing, vaccines and therapeutics.\nC_LIO_LIAs an explanation for efficient viral mutagenesis, we hypothesize that the viral spike protein - as documented - facilitates viral entry via the cells ACE receptor2. This in turn interacts with the APOBEC polypeptide, an m-RNA editing function. The actually observed frequent C to U (T) transitions and other base exchanges are thus effected. Hence, as one of the earliest steps upon viral entry, active mutagenesis commences, since SARS-CoV-2 exploits one of the cells defenses against viral infections.\nC_LI",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21250932",
+    "rel_abs": "BackgroundIn order to manage the COVID-19 systemic inflammatory response, it is important to identify clinicopathological characteristics across multiple cohorts.\n\nMethodsElectronic patient records for 2 consecutive cohorts of patients admitted to two urban teaching hospitals with COVID-19 during two 7-week periods of the COVID-19 pandemic in Glasgow, U.K. (cohort 1: 17th March 2020 - 1st May 2020) and (cohort 2: 18th May 2020 - 6th July 2020) were examined for routine clinical, laboratory and clinical outcome data.\n\nResultsCompared with cohort 1, cohort 2 were older (p<0.001), more likely to be female (p<0.05) and have less independent living circumstances (p<0.001). More patients in cohort 2 were PCR positive, CXR negative (both p<0.001) and had low serum albumin concentrations (p<0.001). 30-day mortality was similar between both cohorts (23% and 22%). Over the 2 cohorts, age [&ge;]70 (p<0.001), male gender (p<0.05), hypertension (p<0.01), heart failure (p<0.05), cognitive impairment (p<0.001), frailty (p<0.001), COPD (p<0.05), delirium (p<0.001), elevated perioperative Glasgow Prognostic Score (p[&le;]0.001), elevated neutrophil-lymphocyte ratio (p<0.001), low haematocrit (p<0.01), elevated urea (p<0.001), creatinine (p<0.001), glucose (p<0.05) and lactate (p<0.01); and the 4C score were associated with 30-day mortality. When compared with the 4C score, greater frailty (OR 10.2, 95% C.I. 3.4 - 30.6, p<0.01) and low albumin (OR 5.6, 95% C.I. 2.0 - 15.6, p<0.01) were strongly independently associated with 30-day mortality.\n\nConclusionIn addition to the 4C mortality score, frailty score and a low albumin were strongly independently associated with 30-day mortality in two consecutive cohorts of patients admitted to hospital with COVID-19.\n\nArticle summaryO_LIIn two consecutive cohorts of patients with COVID-19 infection admitted to two urban teaching hospitals in Glasgow, UK, there were variations in a number of clinicopathological characteristics despite similar mortality (23 and 22%).\nC_LIO_LIIn these two cohorts, in a multivariate analysis that included the 4C mortality score, clinical frailty score >3, low serum albumin concentration (<35 g/L), high neutrophil-lymphocyte ratio ([&ge;]5), and abnormal serum sodium concentration (<133/>145 mmol/L) remained independently associated with 30-day mortality.\nC_LI",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Stefanie Weber",
-        "author_inst": "University of Cologne/Erlangen University"
-      },
-      {
-        "author_name": "Christina C.M. Ramirez",
-        "author_inst": "UCLA School of Public Health, Los Angeles"
-      },
-      {
-        "author_name": "Barbara Weiser",
-        "author_inst": "University of California, Davis,"
+        "author_name": "Donogh Maguire",
+        "author_inst": "Glasgow Royal Infirmary"
       },
       {
-        "author_name": "Harold Burger",
-        "author_inst": "University of California, Davis"
-      },
-      {
-        "author_name": "Walter Doerfler",
-        "author_inst": "Friedrich-Alexander University Erlangen"
+        "author_name": "Donald McMillan",
+        "author_inst": "Academic Unit of Surgery, University of Glasgow, Glasgow Royal Infirmary"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "emergency medicine"
   },
   {
     "rel_doi": "10.1101/2021.02.04.21251126",
@@ -898655,55 +901622,111 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2021.02.02.21251043",
-    "rel_title": "COVID-19 infection and subsequent thromboembolism: A self-controlled case series analysis of a population cohort",
+    "rel_doi": "10.1101/2021.02.03.21251011",
+    "rel_title": "GPS-estimated foot traffic data and venue selection for COVID-19 serosurveillance studies",
     "rel_date": "2021-02-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21251043",
-    "rel_abs": "ObjectiveAn unexpectedly large number of people infected with Covid-19 had experienced a thrombotic event. This study aims to assess the associations between Covid-19 infection and thromboembolism including myocardial infarction (MI), ischaemic stroke, deep-vein thrombosis (DVT), and pulmonary embolism (PE).\n\nPatients and MethodsA self-controlled case-series study was conducted covering the whole of Scotlands general population. The study population comprised individuals with confirmed (positive test) Covid-19 and at least one thromboembolic event between March 2018 and October 2020. Their incidence rates during the risk interval (5 days before to 56 days after the positive test) and the control interval (the remaining periods) were compared intra-personally.\n\nResultsAcross Scotland, 1,449 individuals tested positive for Covid-19 and experienced a thromboembolic event. The risk of thromboembolism was significantly elevated over the whole risk period but highest in the 7 days following the positive test (IRR 12.01, 95% CI 9.91-14.56) in all included individuals. The association was also present in individuals not originally hospitalised for Covid-19 (IRR 4.07, 95% CI 2.83-5.85). Risk of MI, stroke, PE and DVT were all significantly higher in the week following a positive test. The risk of PE and DVT was particularly high and remained significantly elevated even 56 days following the test.\n\nConclusionConfirmed Covid-19 infection was associated with early elevations in risk with MI, ischaemic stroke, and substantially stronger and prolonged elevations with DVT and PE both in hospital and community settings. Clinicians should consider thromboembolism, especially PE, among people with Covid-19 in the community.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.03.21251011",
+    "rel_abs": "The initial phase of the COVID-19 pandemic in the US was marked by limited diagnostic testing, resulting in the need for seroprevalence studies to estimate cumulative incidence and define epidemic dynamics. In lieu of systematic representational surveillance, venue-based sampling was often used to rapidly estimate a communitys seroprevalence. However, biases and uncertainty due to site selection and use of convenience samples are poorly understood. Using data from a SARS-CoV-2 serosurveillance study we performed in Somerville, Massachusetts, we found that the uncertainty in seroprevalence estimates depends on how well sampling intensity matches the known or expected geographic distribution of seropositive individuals in the study area. We use GPS-estimated foot traffic to measure and account for these sources of bias. Our results demonstrated that study-site selection informed by mobility patterns can markedly improve seroprevalence estimates. Such data should be used in the design and interpretation of venue-based serosurveillance studies.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Frederick Ho",
-        "author_inst": "University of Glasgow"
+        "author_name": "Tyler S Brown",
+        "author_inst": "Harvard T.H. Chan School of Public Health, Massachusetts General Hospital"
       },
       {
-        "author_name": "Kenneth Man",
-        "author_inst": "UCL"
+        "author_name": "Pablo Martinez de Salazar Munoz",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "Mark Toshner",
-        "author_inst": "University of Cambridge"
+        "author_name": "Abhishek Bhatia",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "Colin Church",
-        "author_inst": "NHS Greater Glasgow and Clyde"
+        "author_name": "Bridget Bunda",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Carlos Celis-Morales",
-        "author_inst": "University of Glasgow"
+        "author_name": "Ellen K Williams",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Ian Wong",
-        "author_inst": "UCL"
+        "author_name": "David Bor",
+        "author_inst": "Cambridge Health Alliance"
       },
       {
-        "author_name": "Colin Berry",
-        "author_inst": "University of Glasgow"
+        "author_name": "James S Miller",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Naveed Sattar",
-        "author_inst": "University of Glasgow"
+        "author_name": "Amir Mohareb",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Jill Pell",
-        "author_inst": "University of Glasgow"
+        "author_name": "Julia Thierauf",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Wenxin Yang",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Julian Villalba",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Vivek Naranbai",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Wilfredo Garcia Beltran",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Tyler E Miller",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Doug Kress",
+        "author_inst": "City of Somerville Board of Health"
+      },
+      {
+        "author_name": "Kristen Stelljes",
+        "author_inst": "City of Somerville SomerStat"
+      },
+      {
+        "author_name": "Keith Johnson",
+        "author_inst": "City of Somerville SomerStat"
+      },
+      {
+        "author_name": "Daniel B Larremore",
+        "author_inst": "University of Colorado Boulder"
+      },
+      {
+        "author_name": "Jochen Lennerz",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "A. John Iafrate",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Satchit Balsari",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
+      },
+      {
+        "author_name": "Caroline O Buckee",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
+      },
+      {
+        "author_name": "Yonatan H Grad",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "cardiovascular medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2021.02.02.21251028",
@@ -901449,39 +904472,35 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2021.02.03.429646",
-    "rel_title": "Extensive recombination-driven coronavirus diversification expands the pool of potential pandemic pathogens",
+    "rel_doi": "10.1101/2021.02.04.429819",
+    "rel_title": "Codon arrangement modulates MHC-I peptides presentation: implications for a SARS-CoV-2 peptide-based vaccine",
     "rel_date": "2021-02-04",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429646",
-    "rel_abs": "The ongoing SARS-CoV-2 pandemic is the third zoonotic coronavirus identified in the last twenty years. Enzootic and epizootic coronaviruses of diverse lineages also pose a significant threat to livestock, as most recently observed for virulent strains of porcine epidemic diarrhea virus (PEDV) and swine acute diarrhea-associated coronavirus (SADS-CoV). Unique to RNA viruses, coronaviruses encode a proofreading exonuclease (ExoN) that lowers point mutation rates to increase the viability of large RNA virus genomes, which comes with the cost of limiting virus adaptation via point mutation. This limitation can be overcome by high rates of recombination that facilitate rapid increases in genetic diversification. To compare dynamics of recombination between related sequences, we developed an open-source computational workflow (IDPlot) to measure nucleotide identity, locate recombination breakpoints, and infer phylogenetic relationships. We analyzed recombination dynamics among three groups of coronaviruses with noteworthy impacts on human health and agriculture: SARSr-CoV, Betacoronavirus-1, and SADSr-CoV. We found that all three groups undergo recombination with highly diverged viruses from sparsely sampled or undescribed lineages, which can disrupt the inference of phylogenetic relationships. In most cases, no parental origin of recombinant regions could be found in genetic databases, suggesting that much coronavirus diversity remains unknown. These patterns of recombination expand the genetic pool that may contribute to future zoonotic events. Our results also illustrate the limitations of current sampling approaches for anticipating zoonotic threats to human and animal health.",
-    "rel_num_authors": 5,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.04.429819",
+    "rel_abs": "Among various vaccination strategies, peptide-based vaccines appear as excellent candidates because they are cheap to produce, are highly stable and harbor low toxicity. However, predicting which MHC-I Associated Peptide (MAP) will ultimately reach cell surface remains challenging, due to high false discovery rates. Previously, we demonstrated that synonymous codon arrangement (usage and placement) is predictive of, and modulates MAP presentation. Here, we apply CAMAP (Codon Arrangement MAP Predictor), the artificial neural network we used to unveil the role of codon arrangement in MAP presentation, to predict SARS-CoV MAPs. We report that experimentally identified SARS-CoV-1 and SARS-CoV-2 MAPs are associated with significantly higher CAMAP scores. Based on CAMAP scores and binding affinity, we identified 48 non-overlapping MAP candidates for a peptide-based vaccine, ensuring coverage for a high proportion of HLA haplotypes in the US population (>78%) and SARS-CoV-2 strains (detected in >98% of SARS-CoV-2 strains present in the GISAID database). Finally, we built an interactive web portal (https://www.epitopes.world) where researchers can freely explore CAMAP predictions for SARS-CoV-1/2 viruses. Collectively, we present an analysis framework that can be generalizable to empower the rapid identification of virus-specific MAPs, including in the context of an emergent virus, to help accelerate target identification for peptide-based vaccine designs that could be critical in safely attaining group immunity in the context of a global pandemic.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Stephen A. Goldstein",
-        "author_inst": "University of Utah"
+        "author_name": "Tariq Daouda",
+        "author_inst": "Broad Institute of MIT and Harvard; Center for Cancer Research, Massachusetts General Hospital; Department of Medicine, Harvard Medical School;  Center for Immu"
       },
       {
-        "author_name": "Joe Brown",
-        "author_inst": "University of Utah"
+        "author_name": "Maude Dumont-Lagac\u00e9",
+        "author_inst": "Institute for Research in Immunology and Cancer; Universit\u00e9 de Montr\u00e9al"
       },
       {
-        "author_name": "Brent S Pedersen",
-        "author_inst": "University of Utah"
+        "author_name": "Albert Feghaly",
+        "author_inst": "Institute for Research in Immunology and Cancer; Universit\u00e9 de Montr\u00e9al"
       },
       {
-        "author_name": "Aaron R. Quinlan",
-        "author_inst": "University of Utah"
-      },
-      {
-        "author_name": "Nels C. Elde",
-        "author_inst": "University of Utah"
+        "author_name": "Alexandra-Chloe Villani",
+        "author_inst": "Broad Institute of MIT and Harvard; Center for Cancer Research, Massachusetts General Hospital; Department of Medicine, Harvard Medical School;  Center for Immu"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "evolutionary biology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.02.04.429711",
@@ -903331,123 +906350,103 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.02.02.21250825",
-    "rel_title": "Evaluation of Depression, Anxiety and Sleep Quality in the Brazilian Population During Social Isolation Due to the New Coronavirus (SARS-CoV-2) pandemic: the DEGAS-CoV Study",
+    "rel_doi": "10.1101/2021.02.01.21250943",
+    "rel_title": "Seroprevalence of SARS-CoV-2 during pregnancy and associated outcomes: results from an ongoing prospective cohort study, New York City",
     "rel_date": "2021-02-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21250825",
-    "rel_abs": "IntroductionThe new coronavirus infection (COVID-19) has caused distress and repercussions in mental and physical health of individuals. Depression, anxiety and worsening of sleep quality have been reported in several recent articles that surveyed populations all over the globe. Our work meant to access, through a cross-sectional study, these disorders in the Brazilian population, through the application of an online questionnaire conducted on the second trimester of 2020.\n\nMaterials and MethodsWe applied an online questionnaire, filled with questions regarding social, economic, financial, educational and health status, as well as questions from the Hospital Anxiety and Depression Scale (HAD), and from the Pittsburgh Sleep Quality Index (PSQI).\n\nResultsWe collected 2,695 valid answers, from April 24th to May 31st, 2020. Age ranged from 18 to 79 years, mean of 31.3. Women were 76.3%, men 23.7%. Symptoms of Anxiety were found in 56.5%, of depression in 46.1%, and of bad sleep in 49.2%. Some groups were more prone than others to one or more of those conditions, such as: younger people, women, mestizos, Northeasterners, people with lesser years of education, of lower income or whose income dropped significantly during the pandemic, caregivers, students, sedentary or people practicing less physical activity, people who followed more hours of news of COVID-19 and those less engaged in social and instrumental activities.\n\nConclusionanxiety, depression and bad sleep quality were significantly high in our survey. Mental and sleep health is heterogeneously affected among individuals, depending on social, economic, financial, educational and health status.\n\nO_TEXTBOXHIGHLIGHTS\n\n- An online survey (DEGAS-CoV) was conducted between April 30th and May 31st, 2020, with people living in Brazil, aged 18 or more. The study obtained 2,695 valid answers.\n- Rates of possible anxiety, possible depression and bad sleep quality were 56.5%, 46.1% and 49.2%, respectively. Rates are similar to another Brazilian survey, with 45,161 participants, conducted in a similar time window.\n- Were more prone to mental and/or sleep conditions: younger participants, women, mestizos, unemployed, students, people with less years of education, people with lower income or with considerable drops of income during the virus outbreak, caregivers, people who followed more news of COVID-19, people less engaged in social and instrumental activities, smokers, sedentary or those who practiced less physical activity, and people who had symptoms suspected (confirmed or not) of SARS-CoV-2 infection.\n- Alcohol drinkers were slightly less likely to be possibly depressed. That finding needs more clarification and may be due to confounders.\n\n\nC_TEXTBOX",
-    "rel_num_authors": 26,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250943",
+    "rel_abs": "BackgroundIn May-July 2020 in the New York City area, up to 16% of pregnant women had reportedly been infected with SARS-CoV-2. Prior studies found associations between SARS-CoV-2 infection during pregnancy and certain adverse outcomes (e.g., preterm birth, cesarean delivery). These studies relied on reverse transcription polymerase chain reaction (RT-PCR) testing to establish SARS-CoV-2 infection. This led to overrepresentation of symptomatic or acutely ill cases in scientific studies.\n\nObjectiveTo expand our understanding of the effects of SARS-CoV-2 infection during pregnancy on pregnancy outcomes, regardless of symptomatology and stage of infection, by using serological tests to measure IgG antibody levels.\n\nStudy DesignThe Generation C Study is an ongoing prospective cohort study conducted at the Mount Sinai Health System. All pregnant women receiving obstetrical care at the Mount Sinai Hospital and Mount Sinai West Hospital from April 20, 2020 onwards are eligible for participation. For the current analysis, we included participants who had given birth to a liveborn singleton infant on or before August 15, 2020. Blood was drawn as part of routine clinical care; for each woman, we tested the latest sample available to establish seropositivity using a SARS-CoV-2 serologic enzyme-linked immunosorbent assay. Additionally, RT-PCR testing was performed on a nasopharyngeal swab taken during labor and delivery. Pregnancy outcomes of interest (i.e., gestational age at delivery, birth weight, mode of delivery, Apgar score, ICU/NICU admission, and neonatal hospital length of stay) and covariates were extracted from electronic medical records. Among all Generation C participants who had given birth by August 15, 2020 (n=708), we established the SARS-CoV-2 seroprevalence. Excluding women who tested RT-PCR positive at delivery, we conducted crude and adjusted linear and logistic regression models to compare antibody positive women without RT-PCR positivity at delivery with antibody negative women without RT-PCR positivity at delivery. We stratified analyses by race/ethnicity to examine potential effect modification.\n\nResultsThe SARS-CoV-2 seroprevalence based on IgG measurement was 16.4% (n=116, 95% CI 13.7-19.3). Twelve women (1.7%) were SARS-CoV-2 RT-PCR positive at delivery (11 of these women were seropositive). Seropositive women were generally younger, more often Black or Hispanic, and more often had public insurance and higher pre-pregnancy BMI compared with seronegative women. SARS-CoV-2 seropositivity without RT-PCR positivity at delivery was associated with decreased odds of caesarean delivery (aOR 0.48, 95%CI 0.27; 0.84) compared with seronegative women without RT-PCR positivity at delivery. Stratified by race/ethnicity, the association between seropositivity and decreased odds of caesarean delivery remained for non-Hispanic Black/African-American and Hispanic women, but not for non-Hispanic White women. No other pregnancy outcomes differed by seropositivity, overall or stratified by race/ethnicity.\n\nConclusionSeropositivity for SARS-CoV-2 without RT-PCR positivity at delivery, suggesting that infection occurred earlier during pregnancy, was not associated with selected adverse maternal or neonatal outcomes among live births in a cohort sample of women from New York City. While non-Hispanic Black and Latina women in our cohort had a higher rate of SARS-CoV-2 seropositivity compared with non-Hispanic White women, we found no increase in adverse maternal or neonatal outcomes among these groups due to infection.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Paulo Afonso Mei",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
-      },
-      {
-        "author_name": "Amanda Sasse",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
-      },
-      {
-        "author_name": "Ana Lara Navarrete Fernandez",
-        "author_inst": "Pontificia Universidade Catolica de Goias"
-      },
-      {
-        "author_name": "Barbara Neiva Perri",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
-      },
-      {
-        "author_name": "Breno Alexander Bispo",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
-      },
-      {
-        "author_name": "Giselly Brito Santana",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Nina M Molenaar",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Gabriela Sakita Munhos",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Anna-Sophie Rommel",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Giovanni Giuliani Verghetti",
-        "author_inst": "Universidade Sao Leopoldo Mandic Araras"
+        "author_name": "Lotje de Witte",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Guilherme Barbosa de Almeida Oliveira Martins",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Siobhan Dolan",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Jennifer Pereira da Rocha",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Whitney Lieb",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Jessyca Rosa Lopes Mendonca",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Erona Ibroci",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Julia Patel Lebl",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Sophie Ohrn",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Valdemiro Da Rolt Jr",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Jezelle Lynch",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Lais Grabner Ruivo",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Christina Capuano",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Laura Loeb",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Daniel Stadlbauer",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Marielly Isepon",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Florian Krammer",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Marina Joseane Pachecco",
-        "author_inst": "Universidade Sao Leopoldo Mandic Araras"
+        "author_name": "Lauren Zapata",
+        "author_inst": "Centers for Disease Control"
       },
       {
-        "author_name": "Cintia Zonta Baptista",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Rachel Brody",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Fabio Soares Nespoli",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Rhoda Sperling",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Paloma Ricciardi de Castro",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Omara Afzal",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Paola Ricciardi de Castro",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Roy Missall",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Rafaela Dotta Brustolin",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Amy Balbierz",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Taysa Maria Pimentel Goncalves Gomes Silva",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Teresa Janevic",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Victoria Gomes Andreata",
-        "author_inst": "Universidade Sao Leopoldo Mandic"
+        "author_name": "Joanne Stone",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Amilton Santos Jr",
-        "author_inst": "Universidade Estadual de Campinas"
+        "author_name": "Elizabeth Howell",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "Tania Marchiori de Oliveira Cardoso",
-        "author_inst": "Universidade Estadual de Campinas"
+        "author_name": "Veerle Bergink",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "neurology"
+    "category": "obstetrics and gynecology"
   },
   {
     "rel_doi": "10.1101/2021.02.01.21250952",
@@ -905249,31 +908248,51 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.02.02.429431",
-    "rel_title": "Potential global impact of the N501Y mutation on MHC-II presentation and immune escape",
+    "rel_doi": "10.1101/2021.02.03.429355",
+    "rel_title": "Impact of the B.1.1.7 variant on neutralizing monoclonal antibodies recognizing diverse epitopes on SARS-CoV-2 Spike",
     "rel_date": "2021-02-03",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.02.429431",
-    "rel_abs": "The B.1.1.7 SARS-CoV-2 variant, characterized by the N501Y mutation, is rapidly emerging, raising concerns about its effectiveness on natural as well as vaccine-induced adaptive viral immunity at the population level. Since CD4 T cell responses are of critical importance to the antibody response, we examined the global effects of N501Y mutation on MHC-II presentation compared to the N501 wildtype and found poorer presentation across the majority of MHC-II alleles. This suggests that the N501Y mutation may not only diminish binding of antibodies to the RBD but also interfere with their production by weakening the cooperation between T and B cells, facilitating immune escape.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429355",
+    "rel_abs": "The interaction of the SARS-CoV-2 Spike receptor binding domain (RBD) with the ACE2 receptor on host cells is essential for viral entry. RBD is the dominant target for neutralizing antibodies and several neutralizing epitopes on RBD have been molecularly characterized. Analysis of circulating SARS-CoV-2 variants has revealed mutations arising in the RBD, the N-terminal domain (NTD) and S2 subunits of Spike. To fully understand how these mutations affect the antigenicity of Spike, we have isolated and characterized neutralizing antibodies targeting epitopes beyond the already identified RBD epitopes. Using recombinant Spike as a sorting bait, we isolated >100 Spike-reactive monoclonal antibodies from SARS-CoV-2 infected individuals. ~45% showed neutralizing activity of which ~20% were NTD-specific. None of the S2-specific antibodies showed neutralizing activity. Competition ELISA revealed that NTD-specific mAbs formed two distinct groups: the first group was highly potent against infectious virus, whereas the second was less potent and displayed glycan-dependant neutralization activity. Importantly, mutations present in B.1.1.7 Spike frequently conferred resistance to neutralization by the NTD-specific neutralizing antibodies. This work demonstrates that neutralizing antibodies targeting subdominant epitopes need to be considered when investigating antigenic drift in emerging variants.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Andrea Castro",
-        "author_inst": "University of California San Diego"
+        "author_name": "Luke Muir",
+        "author_inst": "UCL"
       },
       {
-        "author_name": "Hannah Carter",
-        "author_inst": "University of California, San Diego"
+        "author_name": "Weng M Ng",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Maurizio Zanetti",
-        "author_inst": "University of California, San Diego"
+        "author_name": "Helen M. E. Duyvesteyn",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Yuguang Zhao",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Thomas A. Bowden",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Annachiara Rosa",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Peter Cherepanov",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Laura E McCoy",
+        "author_inst": "UCL"
       }
     ],
     "version": "1",
-    "license": "",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2021.02.03.429164",
@@ -907143,53 +910162,77 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.01.31.429023",
-    "rel_title": "Mn2+ coordinates Cap-0-RNA to align substrates for efficient 2'-O-methyl transfer by SARS-CoV-2 nsp16",
+    "rel_doi": "10.1101/2021.01.31.429001",
+    "rel_title": "Identification of anti-severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) oxysterol derivatives in vitro",
     "rel_date": "2021-02-01",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.31.429023",
-    "rel_abs": "Capping viral messenger RNAs is essential for efficient translation and prevents their detection by host innate immune responses. For SARS-CoV-2, RNA capping includes 2'-O-methylation of the first ribonucleotide by methyltransferase nsp16 in complex with activator nsp10. The reaction requires substrates, a short RNA and SAM, and is catalyzed by divalent cations, with preference for Mn2+. Crystal structures of nsp16-nsp10 with capped RNAs revealed a critical role of metal ions in stabilizing interactions between ribonucleotides and nsp16, resulting in precise alignment of the substrates for methyl transfer. An aspartate residue that is highly conserved among coronaviruses alters the backbone conformation of the capped RNA in the binding groove. This aspartate is absent in mammalian methyltransferases and is a promising site for designing coronavirus-specific inhibitors.",
-    "rel_num_authors": 9,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.31.429001",
+    "rel_abs": "Development of effective antiviral drugs targeting the severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) are urgently needed to combat the coronavirus disease 2019 (COVID-19). Oxysterols, defined as oxidized derivatives of cholesterol, include endogenous (naturally occurring) cholesterol metabolites as well as semi-synthetic oxysterol derivatives. We have previously studied the use of semi-synthetic oxysterol derivatives as drug candidates for inhibition of cancer, fibrosis, and bone regeneration. In this study, we have screened a panel of naturally occurring and semi-synthetic oxysterol derivatives for anti-SARS-CoV-2 activity, using a cell culture infection assay. We show that the natural oxysterols, 7-ketocholesterol, 22(R)-hydroxycholesterol, 24(S)-hydroxycholesterol, and 27-hydroxycholesterol, substantially inhibited SARS-CoV-2 propagation in cultured cells. Among semi-synthetic oxysterols, Oxy186 displayed antiviral activity comparable to natural oxysterols. In addition, related oxysterol analogues Oxy210 and Oxy232 displayed more robust anti-SARS-CoV-2 activities, reducing viral replication more than 90% at 10 M and 99% at 15 M, respectively. When orally administered in mice, peak plasma concentrations of Oxy210 fall into a therapeutically relevant range (19 M), based on the dose-dependent curve for antiviral activity in our cell culture infection assay. Mechanistic studies suggest that Oxy210 reduced replication of SARS-CoV-2 with disrupting the formation of double membrane vesicles (DMVs), intracellular membrane compartments associated with viral replication. Oxy210 also inhibited the replication of hepatitis C virus, another RNA virus whose replication is associated with DMVs, but not the replication of the DMV-independent hepatitis D virus. Our study warrants further evaluation of Oxy210 and Oxy232 as a safe and reliable oral medication, which could help protect vulnerable populations with increased risk developing COVID-19.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "George Minasov",
-        "author_inst": "Northwestern University, Feinberg School of Medicine"
+        "author_name": "Hirofumi Ohashi",
+        "author_inst": "National Institute for Infectious Diseases"
       },
       {
-        "author_name": "Monica Rosas-Lemus",
-        "author_inst": "Northwestern University, Feinberg School of Medicine"
+        "author_name": "Feng Wang",
+        "author_inst": "MAX BioPharma, Inc."
       },
       {
-        "author_name": "Ludmilla Shuvalova",
-        "author_inst": "Northwestern University, Feinberg School of Medicine"
+        "author_name": "Frank Stappenbeck",
+        "author_inst": "MAX BioPharma, Inc."
       },
       {
-        "author_name": "Nicole L. Inniss",
-        "author_inst": "Northwestern University, Feinberg School of Medicine"
+        "author_name": "Kana Tsuchimoto",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Joseph S. Brunzelle",
-        "author_inst": "Northwestern Synchrotron Research Center"
+        "author_name": "Chisa Kobayashi",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Courtney M. Daczkowski",
-        "author_inst": "Purdue University"
+        "author_name": "Wakana Saso",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Paul Hoover",
-        "author_inst": "Northwestern University, Feinberg School of Medicine"
+        "author_name": "Michiyo Kataoka",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Andrew D Mesecar",
-        "author_inst": "Purdue University"
+        "author_name": "Kouji Kuramochi",
+        "author_inst": "Tokyo University of Science"
       },
       {
-        "author_name": "Karla J Satchell",
-        "author_inst": "Northwestern University Feinberg School of Medicine"
+        "author_name": "Masamichi Muramatsu",
+        "author_inst": "National Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Tadaki Suzuki",
+        "author_inst": "National Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Camille Sureau",
+        "author_inst": "Institut National de la Transfusion Sanguine (INTS)"
+      },
+      {
+        "author_name": "Makoto Takeda",
+        "author_inst": "National Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Takaji Wakita",
+        "author_inst": "National Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Farhad Parhami",
+        "author_inst": "MAX BioPharma, Inc."
+      },
+      {
+        "author_name": "Koichi Watashi",
+        "author_inst": "National Institute of Infectious Diseases"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "",
     "type": "new results",
     "category": "microbiology"
   },
@@ -908857,65 +911900,89 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.29.21250407",
-    "rel_title": "12-lead Electrocardiogram in Hospitalized COVID 19 Patients",
+    "rel_doi": "10.1101/2021.01.28.21250129",
+    "rel_title": "Application of a 27-protein candidate cardiovascular surrogate endpoint to track risk ascendancy and resolution in COVID-19.",
     "rel_date": "2021-02-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.21250407",
-    "rel_abs": "COVID-19 pandemic resulted in considerable morbidity and mortality. We analyzed 345 Electrocardiograms of 100 COVID-19 patients admitted to our tertiary care center in Detroit, during the initial month of Covid-19. Findings were correlated with mortality, cardiac injury and inflammatory markers. Our cohort included 61% males and 77% African Americans. The median age and BMI were 66 years (57-74) and 31 kg/m2 (26.1-39), respectively. We observed atrial arrhythmias in 29% of the patients (17% new onset), First degree heart block in 12%, ST-T segment changes in 17%, S1Q3T3 pattern in 19%, premature ventricular complexes in 23%, premature atrial complexes in 13%, Q waves in 27%, T wave inversion in 42% of the cases. While presence of premature atrial complexes or left atrial abnormality correlated with mortality (P = 0.02 & 0.03, respectively), other findings did not show significant correlation in this small cohort of patients.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250129",
+    "rel_abs": "BackgroundThere is an urgent need for tools allowing the early prognosis and subsequent monitoring of individuals with heterogeneous COVID-19 disease trajectories. Pre-existing cardiovascular (CV) disease is a leading risk factor for COVID-19 susceptibility and poor outcomes, and cardiac involvement is prevalent in COVID-19 patients both during the acute phase as well as in convalescence. The utility of traditional CV risk biomarkers in mild COVID-19 disease or across disease course is poorly understood. We sought to determine if a previously validated 27-protein predictor of CV outcomes served a purpose in COVID-19.\n\nMethodsThe 27-protein test of residual CV (RCV) risk was applied without modification to n=860 plasma samples from hospitalized and non-hospitalized SARS-CoV-2 infected individuals at disease presentation from three independent cohorts to predict COVID-19 severity and mortality. The same test was applied to an additional n=991 longitudinal samples to assess sensitivity to change in CV risk throughout the course of infection into convalescence.\n\nResultsIn each independent cohort, RCV predictions were significantly related to maximal subsequent COVID-19 severity and to mortality. At the baseline blood draw, the mean protein-predicted likelihood of an event in subjects who died during the study period ranged from 88-99% while it ranged from 8-36% in subjects who were not admitted to hospital. Additionally, the test outperformed existing risk predictors based on commonly used laboratory chemistry values or presence of comorbidities. Application of the RCV test to sequential samples showed dramatic increases in risk during the first few days of infection followed by risk reduction in the survivors; a period of catastrophically high cardiovascular risk (above 50%) typically lasted 8-12 days and had not resolved to normal levels in most people within that timescale.\n\nConclusionsThe finding that a 27-protein candidate CV surrogate endpoint developed in multi-morbid patients prior to the pandemic is both prognostic and acutely sensitive to the adverse effects of COVID-19 suggests that this disease activates the same biologic risk-related mechanisms. The test may be useful for monitoring recovery and drug response.",
+    "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Mohamed Shokr",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Clare Paterson",
+        "author_inst": "SomaLogic Inc. Boulder, CO, USA"
       },
       {
-        "author_name": "Omar Chehab",
-        "author_inst": "Department of Internal Medicine, Wayne State University, Detroit, MI, USA"
+        "author_name": "Yolanda Hagar",
+        "author_inst": "SomaLogic Inc. Boulder, CO, USA"
       },
       {
-        "author_name": "Mustafa Ajam",
-        "author_inst": "Department of Pulmonary and Critical Care Medicine, Oregon Health & Science University, Portland, OR, USA"
+        "author_name": "Michael A Hinterberg",
+        "author_inst": "SomaLogic Inc. Boulder, CO, USA"
       },
       {
-        "author_name": "Manmohan Singh",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Alexander W Charney",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA"
       },
       {
-        "author_name": "Said Ashraf",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Diane M Del Valle",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA"
       },
       {
-        "author_name": "John Dawdy",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Michael R Filbin",
+        "author_inst": "Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA"
       },
       {
-        "author_name": "Mohit Pahuja",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Sacha Gnjatic",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA"
       },
       {
-        "author_name": "Vivek Reddy",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Jason D Goldman",
+        "author_inst": "Swedish Center for Research and Innovation, Swedish Medical Center, Seattle, WA, USA"
       },
       {
-        "author_name": "Ahmed Subahi",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Nir Hacohen",
+        "author_inst": "Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA"
       },
       {
-        "author_name": "M. Chadi Alraies",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "James R Heath",
+        "author_inst": "Institute for Systems Biology, Seattle, WA, USA"
       },
       {
-        "author_name": "Luis Afonso",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Rainer Hillenbrand",
+        "author_inst": "Novartis Institutes for BioMedical Research, Basel, Switzerland"
       },
       {
-        "author_name": "Randy Lieberman",
-        "author_inst": "Department of Cardiology, Wayne State University, Detroit, MI, USA"
+        "author_name": "Lori L Jennings",
+        "author_inst": "Novartis Institutes for BioMedical Research, Cambridge, MA, USA"
+      },
+      {
+        "author_name": "Seunghee Kim-Schulze",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA"
+      },
+      {
+        "author_name": "Andrew T Magis",
+        "author_inst": "Institute for Systems Biology, Seattle, WA, USA"
+      },
+      {
+        "author_name": "Miriam Merad",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA"
+      },
+      {
+        "author_name": "Konstantinos Mouskas",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA"
+      },
+      {
+        "author_name": "Nicole W Simons",
+        "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY, USA"
+      },
+      {
+        "author_name": "Stephen A Williams",
+        "author_inst": "SomaLogic Inc. Boulder, CO, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "cardiovascular medicine"
   },
@@ -910507,21 +913574,61 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.01.29.21250793",
-    "rel_title": "COVID-19 spread and Weather in U.S. states: a cross-correlative study on summer-autumn 2020.",
+    "rel_doi": "10.1101/2021.01.30.21250830",
+    "rel_title": "Estimated SARS-CoV-2 Seroprevalence in Healthy Children and Those with Chronic Illnesses in The Washington Metropolitan Area as of October 2020",
     "rel_date": "2021-02-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.21250793",
-    "rel_abs": "An effect of weather on sars-cov-2 transmission is regularly proposed as a putative cause of unexplained fluctuations of covid-19 new cases, but clear data supporting this hypothesis remains to be presented. Here I measured longitudinal time-series correlations between outdoor temperature, humidity and covid-19 reproduction number (Rt) in the 50 U.S. states (+DC). In order to mitigate the confounding influence of varying social restriction measures, the analysis spans a 5-month period during summer and autumn 2020 when restrictions were comparatively lower and more stable. I used a cross-covariance approach to account for a variable delay between infection and case report. For a delay near 11 days, most U.S. states exhibited a negative correlation between outdoor temperature and Rt, as well as between absolute humidity and Rt (mean r = -0.35). In 21 states, the correlation was strong (r < -0.5). Individual state data are presented, and associations between cold and/or dry weather episodes and short-term new case surges are proposed. After identifying potential confounding factors, I discuss 3 possible causal mechanisms that could explain a correlation between outdoor weather and indoor disease transmission: behavioral adaptations to cold weather, respiratory tract temperature, and the importing of outdoor absolute humidity to indoor spaces.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.30.21250830",
+    "rel_abs": "The estimated SARS-CoV-2 seroprevalence in children was found to be 9.46% for the Washington Metropolitan area. Hispanic/Latinx individuals were found to have higher odds of seropositivity. While chronic medical conditions were not associated with having antibodies, previous fever and body aches were predictive symptoms.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Emmanuel de Margerie",
-        "author_inst": "CNRS"
+        "author_name": "Burak Bahar",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Joelle N Simpson",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Cara Biddle",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Andrew Campbell",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Jeffrey S Dome",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Roberta L DeBiasi",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Catriona Mowbray",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Stefanie Marguilies",
+        "author_inst": "Children's National Hospital"
+      },
+      {
+        "author_name": "Adrienne Sherman",
+        "author_inst": "DC Department of Health"
+      },
+      {
+        "author_name": "Jacqueline Reuben",
+        "author_inst": "DC Department of Health"
+      },
+      {
+        "author_name": "Meghan Delaney",
+        "author_inst": "Children's National Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -912285,67 +915392,55 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.01.28.21250700",
-    "rel_title": "Surveillance-to-Diagnostic Testing Program for Asymptomatic SARS-CoV-2 Infections on a Large, Urban Campus - Georgia Institute of Technology, Fall 2020",
-    "rel_date": "2021-01-31",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250700",
-    "rel_abs": "A SARS-CoV-2 testing program combining pooled saliva sample surveillance leading to diagnosis and intervention surveyed over 112,000 samples from 18,029 students, staff and faculty, as part of integrative efforts to mitigate transmission at the Georgia Institute of Technology in Fall 2020. Cumulatively, 1,508 individuals were confirmed diagnostically. The surveillance strategy, including focused intensification of testing given case clusters, was effective in disrupting transmission following rapid case increases upon entry in August 2020, and again in November 2020. Owing to broad adoption by the campus community, the program protected higher risk staff while allowing some normalization of research activities.",
-    "rel_num_authors": 12,
+    "rel_doi": "10.1101/2021.01.29.428890",
+    "rel_title": "Recombinant production of a functional SARS-CoV-2 spike receptor binding domain in the green algae Chlamydomonas reinhardtii",
+    "rel_date": "2021-01-30",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.29.428890",
+    "rel_abs": "Recombinant production of viral proteins can be used to produce vaccine antigens or reagents to identify antibodies in patient serum. Minimally, these proteins must be correctly folded and have appropriate post-translation modifications. Here we report the production of the SARS-CoV-2 spike protein Receptor Binding Domain (RBD) in the green algae Chlamydomonas. RBD fused to a fluorescent reporter protein accumulates as an intact protein when targeted for ER-Golgi retention or secreted from the cell, while a chloroplast localized version is truncated, lacking the amino terminus. The ER-retained RBD fusion protein was able to bind the human ACE2 receptor, the host target of SARS-CoV-2, and was specifically out-competed by mammalian cell-produced recombinant RBD, suggesting that the algae produced proteins are sufficiently post-translationally modified to act as authentic SARS-CoV-2 antigens. Because algae can be grown at large scale very inexpensively, this recombinant protein may be a low cost alternative to other expression platforms.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Greg C Gibson",
-        "author_inst": "Georgia Tech"
-      },
-      {
-        "author_name": "Joshua S Weitz",
-        "author_inst": "Georgia Institute of Technology"
-      },
-      {
-        "author_name": "Michael P. Shannon",
-        "author_inst": "Georgia Tech Research Institute"
-      },
-      {
-        "author_name": "Benjamin Holton",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Anthony J Berndt",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Anton Bryksin",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Tressa N Smalley",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Brian Liu",
-        "author_inst": "Georgia Tech Research Institute"
+        "author_name": "Bijie Ren",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Sandra Bramblett",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Amr Badary",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Julianne Williamson",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Ashley Sproles",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Michael Farrell",
-        "author_inst": "Georgia Tech Research Institute"
+        "author_name": "Francis Fields",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Alexander Ortiz",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Yasin Torres-Tiji",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Chaouki T. Abdallah",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Vanessa Heredia",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Andr\u00e9s Garc\u00eda",
-        "author_inst": "Georgia Institute of Technology"
+        "author_name": "Stephen P Mayfield",
+        "author_inst": "University of California, San Diego"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "synthetic biology"
   },
   {
     "rel_doi": "10.1101/2021.01.30.428921",
@@ -914107,65 +917202,33 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.26.21250349",
-    "rel_title": "HLA-A*11:01:01:01, HLA*C*12:02:02:01-HLA-B*52:01:02:02, age and sex are associated with severity of Japanese COVID-19 with respiratory failure",
+    "rel_doi": "10.1101/2021.01.27.21250048",
+    "rel_title": "A Rapid and Low-Cost protocol for the detection of B.1.1.7 lineage of SARS-CoV-2 by using SYBR Green-Based RT-qPCR",
     "rel_date": "2021-01-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.26.21250349",
-    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 2019 (COVID-19) was announced as an outbreak by the World Health Organization (WHO) in January 2020 and as a pandemic in March 2020. The majority of infected individuals have experienced no or only mild symptoms, ranging from fully asymptomatic cases to mild pneumonic disease. However, a minority of infected individuals develop severe respiratory symptoms. The objective of this study was to identify susceptible HLA alleles and clinical markers for the early identification of severe COVID-19 among hospitalized COVID-19 patients. A total of 137 patients with mild COVID-19 (mCOVID-19) and 53 patients with severe COVID-19 (sCOVID-19) were recruited from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan for the period of February-August 2020. High-resolution sequencing-based typing for eight HLA genes was performed using next-generation sequencing. In the HLA association studies, HLA-A*11:01:01:01 [Pc = 0.013, OR = 2.26 (1.27-3.91)] and HLA-C*12:02:02:01-HLA-B*52:01:01:02 [Pc = 0.020, OR = 2.25 (1.24-3.92)] were found to be significantly associated with the severity of COVID-19. After multivariate analysis controlling for other confounding factors and comorbidities, HLA-A*11:01:01:01 [P = 3.34E-03, OR = 3.41 (1.50-7.73)], age at diagnosis [P = 1.29E-02, OR = 1.04 (1.01-1.07)] and sex at birth [P = 8.88E-03, OR = 2.92 (1.31-6.54)] remained significant. Early identification of potential sCOVID-19 could help clinicians prioritize medical utility and significantly decrease mortality from COVID-19.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.27.21250048",
+    "rel_abs": "BackgroundThe new SARS-CoV-2 variant VUI (202012/01), identified recently in the United Kingdom (UK), exhibits a higher transmissibility rate compared to other variants, and a reproductive number 0.4 higher. In the UK, scientists were able to identify the increase of this new variant through the rise of false negative results for the spike (S) target using a three-target RT-PCR assay (TaqPath kit).\n\nMethodsTo control and study the current coronavirus pandemic, it is important to develop a rapid and low-cost molecular test to identify the aforementioned variant. In this work, we designed primer sets specific to SARS-CoV-2 variant VUI (202012/01) to be used by SYBR Green-based RT-PCR. These primers were specifically designed to confirm the deletion mutations {Delta}69/{Delta}70 in the spike and the {Delta}106/{Delta}107/{Delta}108 in the NSP6 gene. We studied 20 samples from positive patients, 16 samples displayed an S-negative profile (negative for S target and positive for N and ORF1ab targets) and four samples with S, N and ORF1ab positive profile.\n\nResultsOur results emphasized that all S-negative samples harbored the mutations {Delta}69/{Delta}70 and {Delta}106/{Delta}107/{Delta}108. This protocol could be used as a second test to confirm the diagnosis in patients who were already positive to COVID-19 but showed false negative results for S-gene.\n\nConclusionsThis technique may allow to identify patients carrying the VUI (202012/01) variant or a closely related variant, in case of shortage in sequencing.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Seik-Soon Khor",
-        "author_inst": "Genome Medical Science Project, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
-      },
-      {
-        "author_name": "Yosuke Omae",
-        "author_inst": "Genome Medical Science Project, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
-      },
-      {
-        "author_name": "Nao Nishida",
-        "author_inst": "Genome Medical Sciences Project, National Center for Global Health and Medicine, 1-7-1 Kohnodai, Ichikawa, Chiba 272-8516, Japan"
-      },
-      {
-        "author_name": "Masaya Sugiyama",
-        "author_inst": "Genome Medical Sciences Project, National Center for Global Health and Medicine, 1-7-1 Kohnodai, Ichikawa, Chiba 272-8516, Japan"
-      },
-      {
-        "author_name": "Noriko Kinoshita",
-        "author_inst": "Disease Control and Prevention Center, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
-      },
-      {
-        "author_name": "Tetsuya Suzuki",
-        "author_inst": "Disease Control and Prevention Center, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
-      },
-      {
-        "author_name": "Michiyo Suzuki",
-        "author_inst": "Disease Control and Prevention Center, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
-      },
-      {
-        "author_name": "Satoshi Suzuki",
-        "author_inst": "Biobank, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
+        "author_name": "Fadi Abdel-Sater",
+        "author_inst": "Laboratory of Molecular Biology and Cancer Immunology (Covid 19 Unit), FACULTY OF SCIENCE I, Lebanese University, HADATH, Beirut, LB 1003"
       },
       {
-        "author_name": "Shinyu Izumi",
-        "author_inst": "Department of Respiratory Medicine, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
+        "author_name": "Mahmoud Younes",
+        "author_inst": "Research Department, Beirut Cardiac institute, Old airport road, Beirut, Lebanon"
       },
       {
-        "author_name": "Masayuki Hojo",
-        "author_inst": "Department of Respiratory Medicine, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
+        "author_name": "Hassan Nassar",
+        "author_inst": "Bahman Hospital, Beirut, Lebanon"
       },
       {
-        "author_name": "Norio Ohmagari",
-        "author_inst": "Disease Control and Prevention Center, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
-      },
-      {
-        "author_name": "Masashi Mizokami",
-        "author_inst": "Genome Medical Sciences Project, National Center for Global Health and Medicine, 1-7-1 Kohnodai, Ichikawa, Chiba 272-8516, Japan"
+        "author_name": "Paul Nguewa",
+        "author_inst": "University of Navarra, ISTUN Instituto de Salud Tropical, Department of Microbiology and Parasitology. IdiSNA (Navarra Institute for Health Research). c/ Irunla"
       },
       {
-        "author_name": "Katsushi Tokunaga",
-        "author_inst": "Genome Medical Science Project, National Center for Global Health and Medicine Hospital, 1-21-1 Toyama, Shinjuku-ku, Tokyo 162-8655, Japan"
+        "author_name": "Kassem Hamze",
+        "author_inst": "Laboratory of Molecular Biology and Cancer Immunology (Covid 19 Unit), FACULTY OF SCIENCE I, Lebanese University, HADATH, Beirut, LB 1003"
       }
     ],
     "version": "1",
@@ -915773,149 +918836,77 @@
     "category": "systems biology"
   },
   {
-    "rel_doi": "10.1101/2021.01.27.428516",
-    "rel_title": "SARS-CoV-2 variant B.1.1.7 is susceptible to neutralizing antibodies elicited by ancestral Spike vaccines",
+    "rel_doi": "10.1101/2021.01.27.428534",
+    "rel_title": "Unbiased interrogation of memory B cells from convalescent COVID-19 patients reveals a broad antiviral humoral response targeting SARS-CoV-2 antigens beyond the spike protein",
     "rel_date": "2021-01-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.27.428516",
-    "rel_abs": "The SARS-CoV-2 Spike glycoprotein mediates virus entry and is a major target for neutralizing antibodies. All current vaccines are based on the ancestral Spike with the goal of generating a protective neutralizing antibody response. Several novel SARS-CoV-2 variants with multiple Spike mutations have emerged, and their rapid spread and potential for immune escape have raised concerns. One of these variants, first identified in the United Kingdom, B.1.1.7 (also called VUI202012/01), contains eight Spike mutations with potential to impact antibody therapy, vaccine efficacy and risk of reinfection. Here we employed a lentivirus-based pseudovirus assay to show that variant B.1.1.7 remains sensitive to neutralization, albeit at moderately reduced levels (~2-fold), by serum samples from convalescent individuals and recipients of two different vaccines based on ancestral Spike: mRNA-1273 (Moderna), and protein nanoparticle NVX-CoV2373 (Novavax). Some monoclonal antibodies to the receptor binding domain (RBD) of Spike were less effective against the variant while others were largely unaffected. These findings indicate that B.1.1.7 is not a neutralization escape variant that would be a major concern for current vaccines, or for an increased risk of reinfection.",
-    "rel_num_authors": 33,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.27.428534",
+    "rel_abs": "Patients who recover from SARS-CoV-2 infections produce antibodies and antigen-specific T cells against multiple viral proteins. Here, an unbiased interrogation of the anti-viral memory B cell repertoire of convalescent patients has been performed by generating large, stable hybridoma libraries and screening thousands of monoclonal antibodies to identify specific, high-affinity immunoglobulins (Igs) directed at distinct viral components. As expected, a significant number of antibodies were directed at the Spike (S) protein, a majority of which recognized the full-length protein. These full-length Spike specific antibodies included a group of somatically hypermutated IgMs. Further, all but one of the six COVID-19 convalescent patients produced class-switched antibodies to a soluble form of the receptor-binding domain (RBD) of S protein. Functional properties of anti-Spike antibodies were confirmed in a pseudovirus neutralization assay. Importantly, more than half of all of the antibodies generated were directed at non-S viral proteins, including structural nucleocapsid (N) and membrane (M) proteins, as well as auxiliary open reading frame-encoded (ORF) proteins. The antibodies were generally characterized as having variable levels of somatic hypermutations (SHM) in all Ig classes and sub-types, and a diversity of VL and VH gene usage. These findings demonstrated that an unbiased, function-based approach towards interrogating the COVID-19 patient memory B cell response may have distinct advantages relative to genomics-based approaches when identifying highly effective anti-viral antibodies directed at SARS-CoV-2.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Haili Tang",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "Charlene McDana",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "Xiaoying Shen",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "Kshitij Wagh",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Haili Tang",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "Will Fischer",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Charlene McDana",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "James Theiler",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Kshitij Wagh",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Hyejin Yoon",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Will Fischer",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Dapeng Li",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "James Theiler",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Barton F Haynes",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "Hyejin Yoon",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "S. Gnanakaran",
-        "author_inst": "Los Alamos National Laboratory"
-      },
-      {
-        "author_name": "Dapeng Li",
-        "author_inst": "Duke University"
-      },
-      {
-        "author_name": "Nicholas W Hengartner",
-        "author_inst": "Los Alamos Nationa Lab"
-      },
-      {
-        "author_name": "Barton F Haynes",
-        "author_inst": "Duke University"
+        "author_name": "Jillian M DiMuzio",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Rolando Pajon",
-        "author_inst": "Moderna Inc"
+        "author_name": "Baron C Heimbach",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "S. Gnanakaran",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Raymond J Howanski",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Gale Smith",
-        "author_inst": "Novavax, Inc."
+        "author_name": "John P Dowling",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Nicholas W Hengartner",
-        "author_inst": "Los Alamos Nationa Lab"
+        "author_name": "Nirja B Patel",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Filip Dubovsky",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Noeleya Henriquez",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Rolando Pajon",
-        "author_inst": "Moderna Inc"
+        "author_name": "Chris Nicolescu",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Gregory M Glenn",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Mitchell Nath",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Gale Smith",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Antonio Polley",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Bette Korber",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Jamie L Bingaman",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Filip Dubovsky",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Todd Smith",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "David Montefiori",
-        "author_inst": "Duke University"
+        "author_name": "Benjamin C Harman",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Gregory M Glenn",
-        "author_inst": "Novavax, Inc."
+        "author_name": "Matthew K Robinson",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "Bette Korber",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Michael J Morin",
+        "author_inst": "Immunome, Inc."
       },
       {
-        "author_name": "David Montefiori",
-        "author_inst": "Duke University"
+        "author_name": "Pavel A Nikitin",
+        "author_inst": "Immunome, Inc."
       }
     ],
     "version": "1",
-    "license": "",
+    "license": "cc_by_nd",
     "type": "new results",
     "category": "immunology"
   },
@@ -917623,39 +920614,67 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.01.26.428208",
-    "rel_title": "Do examinations prepare students for higher education? A lesson from the Covid-19 lockdown.",
-    "rel_date": "2021-01-27",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.26.428208",
-    "rel_abs": "The COVID-19 pandemic caused severe disruption to education in the UK in 2020, with most of the school teaching moving online and national school examinations being cancelled. This was particularly disruptive for those taking end of school examinations in preparation for higher education. Biological science courses require students to absorb a lot of new vocabulary and concepts, with examinations traditionally focusing on content recall rather than reasoning. Students who had entered university in September 2019 were compared with those arriving in September 2020 with respect to their knowledge of bioscience vocabulary and understanding of key concepts. Results showed no significant difference between those who had gone through the examination process in 2019 relative to those who had not, in 2020. This suggests the cramming of information for examinations has no detectable effect on the knowledge and understanding of biology that students take with them to university.",
-    "rel_num_authors": 5,
+    "rel_doi": "10.1101/2021.01.21.21250249",
+    "rel_title": "Evaluation of six commercial SARS-CoV-2 Enzyme-Linked Immunosorbent assays for clinical testing and serosurveillance.",
+    "rel_date": "2021-01-26",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21250249",
+    "rel_abs": "BackgroundSerological testing for SARS-CoV-2 complements nucleic acid tests for patient diagnosis and enables monitoring of population susceptibility to inform the COVID-19 pandemic response. As we move into the era of vaccines, the detection of neutralising antibody will become increasingly important. Many serological tests have been developed under emergency use authorization, but their reliability remains unclear.\n\nMethodsWe evaluated the performance of six commercially-available Enzyme-linked Immunosorbent Assays (ELISAs), including a surrogate virus neutralization test, for detection of SARS-CoV-2 immunoglobulins (IgA, IgM, IgG), total or neutralising antibodies and a subset of results were compared to microneutralisation.\n\nResultsFor sera collected > 14 days post-symptom onset the Wantai total Ab performed best with highest sensitivity 100% (95% confidence interval: 94.6-100) followed by 93.1% for Euroimmun NCP-IgG,93.1% for GenScript Surrogate Virus Neutralization Test, 90.3% for Euroimmun S1-IgG, 88.9% for Euroimmun S1-IgA and 83.3% for Wantai IgM. Specificity for the best performing assay was 99.5% and for the lowest 97.1%.\n\nConclusionWantai ELISA, detecting total immunoglobulins against SARS-CoV-2 receptor binding domain, had the best performance. Antibody target, timing and longevity of the immune response, and the objectives of testing should be considered in test choice. ELISAs should be used within a confirmatory testing algorithm to ensure reliable results. ELISAs provide high quality results, with flexibility for test numbers without the need for manufacturer specific analyzers.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Harriet L Jones",
-        "author_inst": "University of East Anglia"
+        "author_name": "Suellen R Nicholson",
+        "author_inst": "The Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Aust"
       },
       {
-        "author_name": "Valentina Zini",
-        "author_inst": "University of East Anglia"
+        "author_name": "Theo Karapanagiotidis",
+        "author_inst": "The Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Aust"
       },
       {
-        "author_name": "Jon R Green",
-        "author_inst": "University of Birmingham"
+        "author_name": "Arseniy Khvorov",
+        "author_inst": "WHO Collaborating Centre for Reference and Research on Influenza at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia"
       },
       {
-        "author_name": "John R Prendergast",
-        "author_inst": "JRP Information Services"
+        "author_name": "Celia Douros",
+        "author_inst": "The Victorian Infectious Diseases Reference Laboratory, The Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Aust"
       },
       {
-        "author_name": "Jon Scott",
-        "author_inst": "University of Leicester"
+        "author_name": "Francesca Mordant",
+        "author_inst": "Department of Microbiology and Immunology, The University of Melbourne, WHO Collaborating Centre for Reference and Research on Influenza at The Peter Doherty In"
+      },
+      {
+        "author_name": "Katherine Bond",
+        "author_inst": "Department of Microbiology, Royal Melbourne Hospital, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for "
+      },
+      {
+        "author_name": "Deborah A Williamson",
+        "author_inst": "Department of Microbiology, Royal Melbourne Hospital, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for "
+      },
+      {
+        "author_name": "Damian Francis John Purcell",
+        "author_inst": "Peter Doherty Institute for Infection and Immunity"
+      },
+      {
+        "author_name": "Sharon Lewin",
+        "author_inst": "The Peter Doherty Institute for Infection and Immunity, Victorian Infectious Diseases Service, Royal Melbourne Hospital, Department of Infectious Diseases, Alfr"
+      },
+      {
+        "author_name": "Sheena Sullivan",
+        "author_inst": "WHO Collaborating Centre for Reference and Research on Influenza at The Peter Doherty Institute  for Infection and Immunity, Melbourne, Australia"
+      },
+      {
+        "author_name": "Kanta Subbarao",
+        "author_inst": "Department of Microbiology and Immunology, WHO Collaborating Centre for Reference and Research on Influenza The University of Melbourne at The Peter Doherty  In"
+      },
+      {
+        "author_name": "Mike Catton",
+        "author_inst": "Victorian Infectious Diseases Reference Laboratory at the Peter Doherty Institute for Infection and Immunity, Melbourne"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "scientific communication and education"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2021.01.21.21249203",
@@ -919337,73 +922356,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.25.21250082",
-    "rel_title": "SARS-CoV-2 RNA screening in routine pathology specimens",
+    "rel_doi": "10.1101/2021.01.21.21249906",
+    "rel_title": "Genomic Epidemiology of SARS-CoV-2 in Esteio, Rio Grande do Sul, Brazil",
     "rel_date": "2021-01-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.21250082",
-    "rel_abs": "Virus detection methods are important to cope with the SARS-CoV-2 pandemics. Apart from the lung, SARS-CoV-2 was detected in multiple organs in severe cases. Less is known on organ tropism in patients developing mild or no symptoms, and some of such patients might be missed in symptom-indicated swab testing.\n\nHere we tested and validated several approaches and selected the most reliable RT-PCR protocol for the detection of SARS-CoV-2 RNA in patients routine diagnostic formalin-fixed and paraffin-embedded (FFPE) specimens available in pathology, to assess a) organ tropism in samples from COVID-19-positive patients, b) unrecognized cases in selected tissues from negative or not-tested patients during a pandemic peak, and c) retrospectively, pre-pandemic lung samples.\n\nWe identified SARS-CoV-2 RNA in four samples from confirmed COVID-19 patients, in two gastric biopsies, one colon resection, and one pleural effusion specimen, while all other specimens, particularly from patients with mild COVID-19 disease course, were negative. In the pandemic peak cohort, we identified one previously unrecognized COVID-19 case in tonsillectomy samples. All pre-pandemic lung samples were negative.\n\nIn conclusion, SARS-CoV-2 RNA detection in FFPE pathology specimens can potentially improve surveillance of COVID-19, allow retrospective studies, and advance our understanding of SARS-CoV-2 organ tropism and effects.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21249906",
+    "rel_abs": "Brazil is the third country most affected by Covid-19 pandemic. In spite of this, viral evolution in municipality resolution is poorly understood in Brazil and it is crucial to understand the epidemiology of viral spread. We identified four main circulating lineages in Esteio (Southern Brazil) and their relationship with global, national and regional lineages using phylogenetics and phylodynamics inferences from 21 SARS-CoV-2 genome sequences. We provided a comprehensive view of viral mutations from a time- and age-representative sampling from May to October 2020, in Esteio (RS, Brazil), highlighting two frequent mutations in Spike glycoprotein (D614G and V1176F), an emergent mutation (E484K) in Spike Receptor Binding Domain (RBD) characteristic of the South African lineage B.1.351, and the adjacent replacement of 2 amino acids in Nucleocapsid phosphoprotein (R203K and G204R). A significant viral diversity was evidenced with the identification of 80 different SNPs. The E484K replacement was found in two genomes (9.5%) from samples obtained in mid-October, which is to our best knowledge the earliest description of E484K harboring SARS-CoV-2 in South Brazil. This mutation identified in a small municipality from the RS state demonstrates that it was probably widely distributed in the Brazilian territory, but went unnoticed so far by the lack of genomic surveillance in Brazil. The introduction of E484K mutants shows temporal correlation with later increases in new cases in our state. Importantly, since it has been associated with immune evasion and enhanced interaction with hACE-2, lineages containing this substitution must be the subject of intense surveillance. Our date demonstrates multiple introductions of the most prevalent lineages (B.1.1.33 and B.1.1.248) and the major role of community transmission in viral spreading and the establishment of Brazilian lineages. This represents an important contribution to the epidemiology of SARS-CoV-2.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Saskia E von Stillfried",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Vinicius Bonetti Franceschi",
+        "author_inst": "Universidade Federal do Rio Grande do Sul"
       },
       {
-        "author_name": "Sophia Villwock",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Gabriel Dickin Caldana",
+        "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre"
       },
       {
-        "author_name": "Roman D Buelow",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Amanda de Menezes Mayer",
+        "author_inst": "Universidade Federal do Rio Grande do Sul"
       },
       {
-        "author_name": "Sonja Djudjaj",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Gabriela Bettella Cybis",
+        "author_inst": "Universidade Federal do Rio Grande do Sul"
       },
       {
-        "author_name": "Eva M Buhl",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Carla Andretta Moreira Neves",
+        "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre"
       },
       {
-        "author_name": "Angela Maurer",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Patricia Aline Grohs Ferrareze",
+        "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre"
       },
       {
-        "author_name": "Nadina Ortiz-Bruechle",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Meriane Demoliner",
+        "author_inst": "Universidade Feevale"
       },
       {
-        "author_name": "Peter Celec",
-        "author_inst": "Institute of Virology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia; Institute of Pathophysiology, Faculty of Medicine, Comenius"
+        "author_name": "Paula Rodrigues de Almeida",
+        "author_inst": "Universidade Feevale"
       },
       {
-        "author_name": "Barbara M Klinkhammer",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Juliana Schons Gularte",
+        "author_inst": "Universidade Feevale"
       },
       {
-        "author_name": "Dickson WL Wong",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Alana Witt Hansen",
+        "author_inst": "Universidade Feevale"
       },
       {
-        "author_name": "Claudio Cacchi",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Matheus Nunes Weber",
+        "author_inst": "Universidade Feevale"
       },
       {
-        "author_name": "Till Braunschweig",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Juliane Deise Fleck",
+        "author_inst": "Universidade Feevale"
       },
       {
-        "author_name": "Ruth Knuechel",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Ricardo Ariel Zimerman",
+        "author_inst": "Irmandade Santa Casa de Misericordia de Porto Alegre"
       },
       {
-        "author_name": "Edgar Dahl",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany"
+        "author_name": "Livia Kmetzsch",
+        "author_inst": "Universidade Federal do Rio Grande do Sul"
       },
       {
-        "author_name": "Peter Boor",
-        "author_inst": "Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany and Departments of Nephrology and Immunology, RWTH Aachen University Hospital, Aachen, "
+        "author_name": "Fernando Rosado Spilki",
+        "author_inst": "Universidade Feevale"
+      },
+      {
+        "author_name": "Claudia Elizabeth Thompson",
+        "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre"
       }
     ],
     "version": "1",
@@ -921259,33 +924282,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.26.21250507",
-    "rel_title": "Estimation of the SARS-CoV-2 infection fatality rate in Germany",
+    "rel_doi": "10.1101/2021.01.25.21250505",
+    "rel_title": "Community structured model for vaccine strategies to control COVID19 spread: a mathematical study",
     "rel_date": "2021-01-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.26.21250507",
-    "rel_abs": "Assessing the infection fatality rate (IFR) of SARS-CoV-2 is one of the most controversial issues during the pandemic. Due to asymptomatic or mild courses of COVID-19, many infections remain undetected. Reported case fatality rates - COVID-19-associated deaths divided by number of detected infections - are therefore poor estimates of the IFR. Endogenous changes of the population at risk of a SARS-CoV-2 infection, changing test practices and an improved understanding of the pathogenesis of COVID-19 further exacerbate the estimation of the IFR. Here, we propose a strategy to estimate the IFR of SARS-CoV-2 in Germany that combines official data on reported cases and fatalities supplied by the Robert Koch Institute (RKI) with data from seroepidemiological studies in two infection hotspots, the Austrian town Ischgl and the German municipality Gangelt, respectively. For this purpose, we use the law of total probability to derive an approximate formula for the IFR that is based on a set of assumptions regarding data quality and test specificity and sensitivity. The resulting estimate of the IFR in Germany of 0.83% (95% CI: [0.69%; 0.98%]) that is based on a combination of the RKI and Ischgl data is notably higher than the IFR estimate reported in the Gangelt study (0.36% [0.29%; 0.45%]). It is closer to the consolidated estimate based on a meta-analysis (0.68% [0.53%; 0.82%]), where the difference can be explained by Germanys disadvantageous age structure. As a result of virus mutations, vaccination strategies, and improved therapy, a re-estimation of the IFR will eventually be mandated; the proposed method is able to account for such developments.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.21250505",
+    "rel_abs": "Efforts to mitigate the COVID-19 pandemic have relied heavily on non-pharmaceutical interventions (NPIs), including physical distancing, hand hygiene, and mask-wearing. However, an effective vaccine is essential to containing the spread of the virus. The first doses were distributed at the end of 2020, but the efficacy, period of immunity it will provide, and percentage of coverage still remain unclear. We developed a compartment model to examine different vaccine strategies for controlling the spread of COVID-19. Our framework accounts for testing rates, test-turnaround times, and vaccination waning immunity. Using reported case data from the city of Toronto, Canada between Mar-Dec, 2020 we defined epidemic phases of infection using contact rates, which depend on individuals duration of time spent within the household, workplace/school, or community settings, as well as the probability of transmission upon contact. We investigated the impact of vaccine distribution by comparing different permutations of waning immunity, vaccine coverage and efficacy throughout various stages of NPIs relaxation in terms of cases, deaths, and household transmission, as measured using the basic reproduction number (R0). We observed that widespread vaccine coverage substantially reduced the number of cases and deaths. In order for NPIs to be relaxed 8 months after vaccine distribution, infection spread can be kept under control with either 60% vaccine coverage, no waning immunity, and 70% efficacy, or with 60% coverage with a 12-month waning immunity and 90% vaccine efficacy. Widespread virus resurgence can result when the immunity wanes under 3 months and/or when NPIs are relaxed in concomitance with vaccine distribution. In addition to vaccination, our analysis of R0 showed that the basic reproduction number is reduced by decreasing the tests turnaround time and transmission in the household. While we found that household transmission can decrease following the introduction of a vaccine, public health efforts to reduce test turnaround times remain important for virus containment. Our findings suggest that vaccinating two-thirds of the population with a vaccine that is at least 70% effective may be sufficient for controlling COVID-19 spread, as long as NPIs are not immediately relaxed.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Thomas Dimpfl",
-        "author_inst": "University of T\u00fcbingen, Department of Statistics and Econometrics"
+        "author_name": "Elena Aruffo",
+        "author_inst": "York University"
+      },
+      {
+        "author_name": "Pei Yuan",
+        "author_inst": "York University"
       },
       {
-        "author_name": "Jantje S\u00f6nksen",
-        "author_inst": "University of T\u00fcbingen, Department of Statistics and Econometrics"
+        "author_name": "Yi Tan",
+        "author_inst": "York University"
       },
       {
-        "author_name": "Ingo Bechmann",
-        "author_inst": "University of Leipzig, Institute of Anatomy"
+        "author_name": "Evgenia Gatov",
+        "author_inst": "Toronto Public Health"
       },
       {
-        "author_name": "Joachim Grammig",
-        "author_inst": "University of T\u00fcbingen, Department of Statistics and Econometrics"
+        "author_name": "Effie Gournis",
+        "author_inst": "Toronto Public Health"
+      },
+      {
+        "author_name": "Sarah Collier",
+        "author_inst": "Toronto Public Health"
+      },
+      {
+        "author_name": "Nick Ogden",
+        "author_inst": "Public Health Agency of Canada"
+      },
+      {
+        "author_name": "Jacques B\u00e9lair",
+        "author_inst": "Universit\u00e9 de Montr\u00e9al"
+      },
+      {
+        "author_name": "Huaiping Zhu",
+        "author_inst": "York University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -922957,61 +926000,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.21.21249176",
-    "rel_title": "Distinct Autoimmune Antibody Signatures Between Hospitalized Acute COVID-19 Patients, SARS-CoV-2 Convalescent Individuals, and Unexposed Pre-Pandemic Controls",
+    "rel_doi": "10.1101/2021.01.22.21249716",
+    "rel_title": "An interactive COVID-19 virus Mutation Tracker (CovMT) with a particular focus on critical mutations in the Receptor Binding Domain (RBD) region of the Spike protein",
     "rel_date": "2021-01-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21249176",
-    "rel_abs": "Increasing evidence suggests that autoimmunity may play a role in the pathophysiology of SARS-CoV-2 infection during both the acute and  long COVID phases of disease. However, an assessment of autoimmune antibodies in convalescent SARS-CoV-2 patients has not yet been reported.\n\nMethodologyWe compared the levels of 18 different IgG autoantibodies (AABs) between four groups: (1) unexposed pre-pandemic subjects from the general population (n = 29); (2) individuals hospitalized with acute moderate-severe COVID-19 (n = 20); (3) convalescent SARS-COV-2-infected subjects with asymptomatic to mild viral symptoms during the acute phase with samples obtained between 1.8 and 7.3 months after infection (n = 9); and (4) unexposed pre-pandemic subjects with systemic lupus erythematous (SLE) (n = 6). Total IgG and IgA levels were also measured from subjects in groups 1-3 to assess non-specific pan-B cell activation.\n\nResultsAs expected, in multivariate analysis, AABs were detected at much higher odds in SLE subjects (5 of 6, 83%) compared to non-SLE pre-pandemic controls (11 of 29, 38%) [odds ratio (OR) 19.4,95% CI, 2.0 - 557.0, p = 0.03]. AAB detection (percentage of subjects with one or more autoantibodies) was higher in SARS-CoV-2 infected convalescent subjects (7 of 9, 78%) [OR 17.4, 95% CI, 2.0 - 287.4, p = 0.02] and subjects with acute COVID-19 (12 of 20, 60%) compared with non-SLE pre-pandemic controls, but was not statistically significant among the latter [OR 1.8,95% CI, 0.6 - 8.1, p = 0.23]. Within the convalescent subject group, AABs were detected in 5/5 with reported persistent symptoms and 2/4 without continued symptoms (p = 0.17). The multivariate computational algorithm Partial Least Squares Determinant Analysis (PLSDA) was used to determine if distinct AAB signatures distinguish subject groups 1-3. Of the 18 autoantibodies measured, anti-Beta 2-Glycoprotein, anti-Proteinase 3-ANCA, anti-Mi-2 and anti-PM/Scl-100 defined the convalescent group; anti-Proteinase 3-ANCA, anti-Mi-2, anti-Jo-1 and anti-RNP/SM defined acute COVID-19 subjects; and anti-Proteinase 3-ANCA, anti-Mi-2, anti-Jo-1, anti-Beta 2-Glycoprotein distinguished unexposed controls. The AABs defining SARS-COV-2 infected from pre-pandemic subjects are widely associated with myopathies, vasculitis, and antiphospholipid syndromes, conditions with some similarities to COVID-19. Compared to pre-pandemic non-SLE controls, subjects with acute COVID-19 had higher total IgG concentration (p-value=0.006) but convalescent subjects did not (p-value=0.08); no differences in total IgA levels were found between groups.\n\nConclusionsOur findings support existing studies suggesting induction of immune responses to self-epitopes during acute, severe COVID-19 with evidence of general B cell hyperactivation. Also, the preponderance of AAB positivity among convalescent individuals up to seven months after infection indicates potential initiation or proliferation, and then persistence of self-reactive immunity without severe initial disease. These results underscore the importance of further investigation of autoimmunity during SARS-CoV-2 infection and its role in the onset and persistence of post-acute sequelae of COVID-19.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21249716",
+    "rel_abs": "Almost one year has passed since the appearance of SARS-CoV-2, causing the COVID-19 pandemic. The number of confirmed SARS-Cov-2 cases worldwide has now reached [~]92 million, with 2 million reported deaths (https://covid19.who.int). Nearly 400,000 SARS-Cov-2 genomes were sequenced from COVID-19 samples and added to public resources such as GISAID (https://gisaid.org). With the vaccines becoming available or entering trials (https://covid19.trackvaccines.org), it is vital to keep track of mutations in the genome of SARS-CoV-2, especially in the Spike proteins Receptor Binding Domain (RBD) region, which could have a potential impact on disease severity and treatment strategies.1-3 In the wake of a recent increase in cases with a potentially more infective RBD mutation (N501Y) in the United Kingdom, countries worldwide are concerned about the spread of this or similar variants. Impressive sampling and timely increase in sequencing efforts related to COVID-19 in the United Kingdom (UK) helped detect and monitor the spread of the new N501Y variant. Similar sequencing efforts are needed in other countries for timely tracking of this or different variants. To track geographic sequencing efforts and mutations, with a particular focus on RBD region of the Spike protein, we present our daily updated COVID-19 virus Mutation Tracker system, see https://www.cbrc.kaust.edu.sa/covmt.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Nahid Bhadelia",
-        "author_inst": "Department of Medicine, Boston University School of Medicine and National Emerging Infectious Diseases Laboratories (NEIDL), Boston University"
-      },
-      {
-        "author_name": "Anna Belkina",
-        "author_inst": "Flow Cytometry Core Facility and Department of Pathology and Laboratory Medicine, Boston University School of Medicine"
-      },
-      {
-        "author_name": "Alex Olson",
-        "author_inst": "Department of Medicine, Boston University School of Medicine"
-      },
-      {
-        "author_name": "Thomas Winter",
-        "author_inst": "Research Occupational Health Program, Boston University"
-      },
-      {
-        "author_name": "Patricia Urick",
-        "author_inst": "Research Occupational Health Program, Boston University"
+        "author_name": "Intikhab Alam",
+        "author_inst": "Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, Saudi Arabia."
       },
       {
-        "author_name": "Nina Lin",
-        "author_inst": "Department of Medicine, Boston University School of Medicine"
+        "author_name": "Aleksandar Radovanovic",
+        "author_inst": "Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, Saudi Arabia."
       },
       {
-        "author_name": "Ian Rifkin",
-        "author_inst": "Renal Section, Department of Medicine, Boston University School of Medicine and Renal Section, Department of Medicine, VA Boston Healthcare System"
+        "author_name": "Roberto Incitti",
+        "author_inst": "Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, Saudi Arabia."
       },
       {
-        "author_name": "Yachana Kataria",
-        "author_inst": "Department of Pathology and Laboratory Medicine, Boston University School of Medicine"
+        "author_name": "Allan Kamau",
+        "author_inst": "Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, Saudi Arabia."
       },
       {
-        "author_name": "Rachel Yuen",
-        "author_inst": "Department of Microbiology; Boston University School of Medicine"
+        "author_name": "Muhammed Alarawi",
+        "author_inst": "Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, Saudi Arabia."
       },
       {
-        "author_name": "Manish Sagar",
-        "author_inst": "Department of Medicine, Boston University School of Medicine"
+        "author_name": "Esam I. Azhar",
+        "author_inst": "Special Infectious Agent Unit (SIAU), King Fahd Medical Research Center (KFMRC), and Medical Laboratory Technology Department, Faculty of Applied Medical Scienc"
       },
       {
-        "author_name": "Jennifer Cappione",
-        "author_inst": "Department of Microbiology; Boston University School of Medicine"
+        "author_name": "Takashi Gojobori",
+        "author_inst": "Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, Saudi Arabia."
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -924947,131 +927974,23 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2021.01.25.428136",
-    "rel_title": "mRNA-1273 efficacy in a severe COVID-19 model: attenuated activation of pulmonary immune cells after challenge",
+    "rel_doi": "10.1101/2021.01.25.428122",
+    "rel_title": "Profiling transcription factor sub-networks in type I interferon signaling and in response to SARS-CoV-2 infection",
     "rel_date": "2021-01-25",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.25.428136",
-    "rel_abs": "The mRNA-1273 vaccine was recently determined to be effective against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from interim Phase 3 results. Human studies, however, cannot provide the controlled response to infection and complex immunological insight that are only possible with preclinical studies. Hamsters are the only model that reliably exhibit more severe SARS-CoV-2 disease similar to hospitalized patients, making them pertinent for vaccine evaluation. We demonstrate that prime or prime-boost administration of mRNA-1273 in hamsters elicited robust neutralizing antibodies, ameliorated weight loss, suppressed SARS-CoV-2 replication in the airways, and better protected against disease at the highest prime-boost dose. Unlike in mice and non-human primates, mRNA-1273- mediated immunity was non-sterilizing and coincided with an anamnestic response. Single-cell RNA sequencing of lung tissue permitted high resolution analysis which is not possible in vaccinated humans. mRNA-1273 prevented inflammatory cell infiltration and the reduction of lymphocyte proportions, but enabled antiviral responses conducive to lung homeostasis. Surprisingly, infection triggered transcriptome programs in some types of immune cells from vaccinated hamsters that were shared, albeit attenuated, with mock-vaccinated hamsters. Our results support the use of mRNA-1273 in a two-dose schedule and provides insight into the potential responses within the lungs of vaccinated humans who are exposed to SARS-CoV-2.",
-    "rel_num_authors": 28,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.25.428122",
+    "rel_abs": "Type I interferons (IFN /{beta}) play a central role in innate immunity to respiratory viruses, including coronaviruses. Genetic defects in type I interferon signaling were reported in a significant proportion of critically ill COVID-19 patients. Extensive studies on interferon-induced intracellular signal transduction pathways led to the elucidation of the Jak-Stat pathway. Furthermore, advances in gene expression profiling by microarrays have revealed that type I interferon rapidly induced multiple transcription factor mRNA levels. In this study, transcription factor profiling in the transcriptome was used to gain novel insights into the role of inducible transcription factors in response to type I interferon signaling in immune cells and in lung epithelial cells after SARS-CoV-2 infection. Modeling the interferon-inducible transcription factor mRNA data in terms of distinct sub-networks based on biological functions such as antiviral response, immune modulation, and cell growth revealed enrichment of specific transcription factors in mouse and human immune cells. The evolutionarily conserved core type I interferon gene expression consists of the inducible transcriptional factor mRNA of the antiviral response sub-network and enriched in granulocytes. Analysis of the type I interferon-inducible transcription factor sub-networks as distinct protein-protein interaction pathways revealed insights into the role of critical hubs in signaling. Interrogation of multiple microarray datasets revealed that SARS-CoV-2 induced high levels of IFN-beta and interferon-inducible transcription factor mRNA in human lung epithelial cells. Transcription factor mRNA of the three major sub-networks regulating antiviral, immune modulation, and cell growth were differentially regulated in human lung epithelial cell lines after SARS-CoV-2 infection and in the tissue samples of COVID-19 patients. A subset of type I interferon-inducible transcription factors and inflammatory mediators were specifically enriched in the lungs and neutrophils of COVID-19 patients. The emerging complex picture of type I IFN transcriptional regulation consists of a rapid transcriptional switch mediated by the Jak-Stat cascade and a graded output of the inducible transcription factor activation that enables temporal regulation of gene expression.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Michelle Meyer",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Yuan Wang",
-        "author_inst": "Princeton University"
-      },
-      {
-        "author_name": "Darin Edwards",
-        "author_inst": "Moderna Inc"
-      },
-      {
-        "author_name": "Gregory R Smith",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Aliza B Rubenstein",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Palaniappan Ramanathan",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Chad E Mire",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Colette Pietzsch",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Xi Chen",
-        "author_inst": "Flatiron Institute, Simons Foundation"
-      },
-      {
-        "author_name": "Yongchao Ge",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Wan Sze Cheng",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Carole Henry",
-        "author_inst": "Moderna Inc"
-      },
-      {
-        "author_name": "Angela Woods",
-        "author_inst": "Moderna Inc"
-      },
-      {
-        "author_name": "LingZhi Ma",
-        "author_inst": "Moderna Inc"
-      },
-      {
-        "author_name": "Guillaume B. E. Stewart-Jones",
-        "author_inst": "Moderna Inc"
-      },
-      {
-        "author_name": "Kevin W Bock",
-        "author_inst": "National Institute of Health"
-      },
-      {
-        "author_name": "Minai Mahnaz",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Bianca M Nagata",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Sivakumar Periasamy",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Pei-Yong Shi",
-        "author_inst": "University of Texas Medical Branch"
-      },
-      {
-        "author_name": "Barney S Graham",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Ian N Moore",
-        "author_inst": "National Institutes of Health"
-      },
-      {
-        "author_name": "Irene Ramos",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Olga G. Troyanskaya",
-        "author_inst": "Princeton University"
-      },
-      {
-        "author_name": "Elena Zaslavsky",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Andrea Carfi",
-        "author_inst": "Moderna Inc"
-      },
-      {
-        "author_name": "Stuart C Sealfon",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Alexander Bukreyev",
-        "author_inst": "University of Texas Medical Branch at Galveston"
+        "author_name": "Ramana Chilakamarti",
+        "author_inst": "Dartmouth-Hitchcock Medical Center, Dartmouth Med School, Lebanon, New Hampshire"
       }
     ],
     "version": "1",
-    "license": "",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.01.25.428097",
@@ -926557,39 +929476,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.22.21250289",
-    "rel_title": "Development and validation of a predictive model for critical illness in adult patients requiring hospitalization for COVID-19",
+    "rel_doi": "10.1101/2021.01.21.21250261",
+    "rel_title": "Using body temperature and variables commonly available in the EHR to predict acute infection: A proof-of-concept study showing improved pretest probability estimates for acute COVID-19 infection among discharged emergency department patients",
     "rel_date": "2021-01-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250289",
-    "rel_abs": "BackgroundIdentifying factors that can predict severe disease in patients needing hospitalization for COVID-19 is crucial for early recognition of patients at greatest risk.\n\nObjective1) Identify factors predicting intensive care unit (ICU) transfer and (2) develop a simple calculator for clinicians managing patients hospitalized with COVID-19.\n\nMethodsA total of 2,685 patients with laboratory-confirmed COVID-19 admitted to a large metropolitan health system in Georgia, USA between March and July 2020 were included in the study. Seventy-five percent of patients were included in the training dataset (admitted March 1 to July 10). Through multivariable logistic regression, we developed a prediction model (probability score) for ICU transfer. Then, we validated the model by estimating its performance accuracy (area under the curve [AUC]) using data from the remaining 25% of patients (admitted July 11 to July 31).\n\nResultsWe included 2,014 and 671 patients in the training and validation datasets, respectively. Diabetes mellitus, coronary artery disease, chronic kidney disease, serum C-reactive protein, and serum lactate dehydrogenase were identified as significant risk factors for ICU transfer, and a prediction model was developed. The AUC was 0.752 for the training dataset and 0.769 for the validation dataset. We developed a free, web-based calculator to facilitate use of the prediction model (https://icucovid19.shinyapps.io/ICUCOVID19/).\n\nConclusionOur validated, simple, and accessible prediction model and web-based calculator for ICU transfer may be useful in assisting healthcare providers in identifying hospitalized patients with COVID-19, who are at high risk for clinical deterioration.\n\nTriage of such patients for early aggressive treatment can impact clinical outcomes for this potentially deadly disease.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.21.21250261",
+    "rel_abs": "ObjectivesObtaining body temperature is a quick and easy method to screen for acute infection such as COVID-19. Currently, the predictive value of body temperature for acute infection is inhibited by failure to account for other readily available variables that affect temperature values. In this proof-of-concept study, we sought to improve COVID-19 pretest probability estimation by incorporating covariates known to be associated with body temperature, including patient age, sex, comorbidities, month, time of day.\n\nMethodsFor patients discharged from an academic hospital emergency department after testing for COVID-19 in March and April of 2020, we abstracted clinical data. We reviewed physician documentation to retrospectively generate estimates of pretest probability for COVID-19. Using patients COVID-19 PCR test results as a gold standard, we compared AUCs of logistic regression models predicting COVID-19 positivity that used: 1) body temperature alone; 2) body temperature and pretest probability; 3) body temperature, pretest probability, and body temperature-relevant covariates. Calibration plots and bootstrap validation were used to assess predictive performance for model #3.\n\nResultsData from 117 patients were included. The models AUCs were: 1) 0.69 2) 0.72, and 3) 0.76, respectively. The absolute difference in AUC was 0.029 (95%CI -0.057 to 0.114, p=0.25) between model 2 and 1 and 0.038 (95%CI -0.021 to 0.097, p=0.10) between model 3 and 2.\n\nConclusionsBy incorporating covariates known to affect body temperature, we demonstrated improved pretest probability estimates of acute COVID-19 infection. Future work should be undertaken to further develop and validate our model in a larger, multi-institutional sample.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Neha Paranjape",
-        "author_inst": "Wellstar Medical Group"
+        "author_name": "Carl T Berdahl",
+        "author_inst": "Cedars-Sinai Medical Center; Departments of Medicine and Emergency Medicine: Los Angeles, CA, US"
       },
       {
-        "author_name": "Lauren Staples",
-        "author_inst": "Kennesaw State University"
+        "author_name": "An T Nguyen",
+        "author_inst": "Cedars-Sinai Medical Center; Department of Physical Medicine and Rehabilitation: Los Angeles, CA, US"
       },
       {
-        "author_name": "Christina Stradwick",
-        "author_inst": "Kennesaw State University"
+        "author_name": "Marcio A Diniz",
+        "author_inst": "Cedars-Sinai Health System; Biostatistics and Bionformatics Research Center: Los Angeles, CA, US"
       },
       {
-        "author_name": "Herman Ray",
-        "author_inst": "Kennesaw State University"
+        "author_name": "Andrew J Henreid",
+        "author_inst": "Cedars-Sinai Medical Center; Department of Medicine: Los Angeles, CA, US"
       },
       {
-        "author_name": "Ian Saldanha",
-        "author_inst": "Brown University"
+        "author_name": "Teryl K Nuckols",
+        "author_inst": "Cedars-Sinai Medical Center; Department of Medicine: Los Angeles, CA, US"
+      },
+      {
+        "author_name": "Christopher P Libby",
+        "author_inst": "Cedars-Sinai Medical Center; EIS: Los Angeles, CA, US"
+      },
+      {
+        "author_name": "Joshua M Pevnick",
+        "author_inst": "Cedars-Sinai Medical Center; Department of General Internal Medicine: Los Angeles, CA, US"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "intensive care and critical care medicine"
+    "category": "emergency medicine"
   },
   {
     "rel_doi": "10.1101/2021.01.21.21250264",
@@ -928227,21 +931154,33 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2021.01.15.21249893",
-    "rel_title": "COVID-19 propagation by diffusion - a two-dimensional approach for Germany",
+    "rel_doi": "10.1101/2021.01.15.20249089",
+    "rel_title": "Physician Perceptions of Catching COVID-19",
     "rel_date": "2021-01-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249893",
-    "rel_abs": "Diffusion comes anytime and everywhere. If there is a gradient or a potential difference of a quantity a diffusion process happens and this ends if an equilibrium is reached only. The concentration of a species maybe such quantity, or the voltage. An electric currant will be driven by a voltage difference for example.\n\nIn this COVID-19 pandemic one observes both regions with low incidence and other ones with high incidence. The local different people density could be a reason for that. In populous areas like big cities or congested urban areas higher COVID-19 incidences could be observed than in rural regions.\n\nThe aim of this paper consists in the application of a diffusion concept to describe one possible issue of the the COVID-19 propagation.\n\nThis will be discussed for the German situation based on the quite different incidence data for the different federal states of Germany.\n\nWith this ansatz some phenomenoms of the actual development of the pandemic could be confirmed. The model gives a possibility to investigate certain scenarios like border-crossings or local spreading events and their influence on the COVID-19 propagation as well.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.20249089",
+    "rel_abs": "BackgroundRisk perception, influenced and biased by multiple factors, can affect behavior.\n\nObjectiveTo assess the variability of physician perceptions of catching COVID-19.\n\nDesignCross sectional, random stratified sample of physicians registered with Sermo, a global networking platform open to verified and licensed physicians.\n\nMain outcome measuresThe survey asked: \"What is your likelihood of catching COVID-19 in the next three months?\" The physicians were asked to give their best estimate as an exact percentage.\n\nResultsThe survey was completed by 1004 physicians (40 countries, 67 specialties, 49% frontline [e.g. ER, infectious disease, internal medicine]) with a mean (SD) age of 49.14 (12) years. Mean (SD) self-risk estimate was 32.3% {+/-} 26% with a range from 0% to 100% (Figure 1a). Risk estimates were higher in younger (<50 years) doctors and in non-US doctors versus their older and US counterparts (p<0.05 for all) (Figure 1b). Risk estimates were higher among front line versus non-frontline doctors (p<0.05). Risk estimates were higher for women than men (p<0.05) among respondents (60%) reporting gender.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/20249089v2_fig1A.gif\" ALT=\"Figure 1A\">\nView larger version (17K):\norg.highwire.dtl.DTLVardef@7dd844org.highwire.dtl.DTLVardef@17241org.highwire.dtl.DTLVardef@f43cb2org.highwire.dtl.DTLVardef@bcd7f1_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFigure 1A.C_FLOATNO Distribution of risk prediction for overall sample (N=1004). Upper panel is a line box whisker and bottom panel shows the frequency distribution.\n\nC_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC=\"FIGDIR/small/20249089v2_fig1B.gif\" ALT=\"Figure 1B\">\nView larger version (21K):\norg.highwire.dtl.DTLVardef@51be7org.highwire.dtl.DTLVardef@16ae5fcorg.highwire.dtl.DTLVardef@12118a2org.highwire.dtl.DTLVardef@1d848c6_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFigure1B.C_FLOATNO Mean (SD) risk estimates by age, frontline status, and geographic region.\n\nC_FIG ConclusionsTo our knowledge, this is the first global study to document physician risk perceptions for catching COVID-19 and how it is impacted by age, gender, practice specialty and geography. Accurate calibration of risk perception is vital since both over- and underestimation of risk could impact physician behavior and have implications for public health.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Guenter K.F. Baerwolff",
-        "author_inst": "Technical University Berlin"
+        "author_name": "P. Murali Doraiswamy",
+        "author_inst": "Duke University School of Medicine"
+      },
+      {
+        "author_name": "Mohan Chilukuri",
+        "author_inst": "University of North Carolina School of Medicine"
+      },
+      {
+        "author_name": "Dan Ariely",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Alexandra Rose Linares",
+        "author_inst": "Duke University School of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -929621,25 +932560,29 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.01.18.21250012",
-    "rel_title": "Studying the course of Covid-19 by a recursive delay approach",
+    "rel_doi": "10.1101/2021.01.18.21249998",
+    "rel_title": "The Association between Early Country-level Testing Capacity and Later COVID-19 Mortality Outcomes",
     "rel_date": "2021-01-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21250012",
-    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWIn an earlier paper we proposed a recursive model for epidemics; in the present paper we generalize this model to include the asymptomatic or unrecorded symptomatic people, which we call dark people (dark sector). We call this the SEPARd-model. A delay differential equation version of the model is added; it allows a better comparison to other models. We carry this out by a comparison with the classical SIR model and indicate why we believe that the SEPARd model may work better for Covid-19 than other approaches.\n\nIn the second part of the paper we explain how to deal with the data provided by the JHU, in particular we explain how to derive central model parameters from the data. Other parameters, like the size of the dark sector, are less accessible and have to be estimated more roughly, at best by results of representative serological studies which are accessible, however, only for a few countries. We start our country studies with Switzerland where such data are available. Then we apply the model to a collection of other countries, three European ones (Germany, France, Sweden), the three most stricken countries from three other continents (USA, Brazil, India). Finally we show that even the aggregated world data can be well represented by our approach.\n\nAt the end of the paper we discuss the use of the model. Perhaps the most striking application is that it allows a quantitative analysis of the influence of the time until people are sent to quarantine or hospital. This suggests that imposing means to shorten this time is a powerful tool to flatten the curves.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21249998",
+    "rel_abs": "BackgroundThe COVID-19 pandemic has overrun hospital systems while exacerbating economic hardship and food insecurity on a global scale. In an effort to understand how early action to find and control the virus is associated with cumulative outcomes, we explored how country-level testing capacity affects later COVID-19 mortality.\n\nMethodsWe used the Our World in Data database to explore testing and mortality records in 27 countries from December 31, 2019 to September 30, 2020; we applied ordinary-least squares regression with clustering on country to determine the association between early COVID-19 testing capacity (cumulative tests per case) and later COVID-19 mortality (time to specified mortality thresholds), adjusting for country-level confounders, including median age, GDP, hospital bed capacity, population density, and non-pharmaceutical interventions.\n\nResultsHigher early testing implementation, as indicated by more cumulative tests per case when mortality was still low, was associated with longer accrual time for higher per capita deaths. For instance, a higher cumulative number of tests administered per case at the time of 6 deaths per million persons was positively predictive of a longer time to reach 15 deaths per million, after adjustment for all confounders ({beta}=0.659; P=0.001).\n\nConclusionsCountries that developed stronger COVID-19 testing capacity at early timepoints, as measured by tests administered per case identified, experienced a slower increase of deaths per capita. Thus, this study operationalizes the value of testing and provides empirical evidence that stronger testing capacity at early timepoints is associated with reduced mortality and better pandemic control.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Erhard Scholz",
-        "author_inst": "University of Wuppertal"
+        "author_name": "Sneha Kannoth",
+        "author_inst": "Columbia University, Mailman School of Public Health"
       },
       {
-        "author_name": "Matthias Kreck",
-        "author_inst": "University of Bonn"
+        "author_name": "Sasikiran Kandula",
+        "author_inst": "Columbia University, Mailman School of Public Health"
+      },
+      {
+        "author_name": "Jeffrey Shaman",
+        "author_inst": "Columbia University, Mailman School of Public Health"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -931543,39 +934486,75 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2021.01.19.426622",
-    "rel_title": "Evaluation of the effects of SARS-CoV-2 genetic mutations on diagnostic RT-PCR assays",
+    "rel_doi": "10.1101/2021.01.20.427105",
+    "rel_title": "Use Of Canine Olfactory Detection For COVID-19 Testing Study On U.A.E. Trained Detection Dog Sensitivity",
     "rel_date": "2021-01-20",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.426622",
-    "rel_abs": "Several mutant strains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging. Mismatch(es) in primer/probe binding regions would decrease the detection sensitivity of the PCR test, thereby affecting the results of clinical testing. In this study, we conducted an in silico survey on SARS-CoV-2 sequence variability within the binding regions of primer/probe published by the Japan National Institute of Infectious Diseases (NIID) and Centers for Disease Control and Prevention (CDC). In silico analysis revealed the presence of mutations in the primer/probe binding regions. We performed RT-PCR assays using synthetic RNAs containing the mutations and showed that some mutations significantly decreased the detection sensitivity of the RT-PCR assays.\n\nOur results highlight the importance of genomic monitoring of SARS-CoV-2 and evaluating the effects of mismatches on PCR testing sensitivity.",
-    "rel_num_authors": 5,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.20.427105",
+    "rel_abs": "This study aimed to evaluate the sensitivity of 21 dogs belonging to different United Arab Emirates (UAE) Ministry of Interior (MOI), trained for COVID-19 olfactory detection.\n\nThe study involved 17 explosives detection dogs, two cadaver detection dogs and two dogs with no previous detection training. Training lasted two weeks before starting the validation protocol. Sequential five and seven-cone line-ups were used with axillary sweat samples from symptomatic COVID-19 individuals (SARS-CoV-2 PCR positive) and from asymptomatic COVID-19 negative individuals (SARS-CoV-2 PCR negative). A total of 1368 trials were performed during validation, including 151 positive and 110 negative samples. Each line-up had one positive sample and at least one negative sample. The dog had to mark the positive sample, randomly positioned behind one of the cones. The dog, handler and data recorder were blinded to the positive sample location.\n\nThe calculated overall sensitivities were between 71% and 79% for three dogs, between83% and 87% for three other dogs, and equal to or higher than 90% for the remaining 15 dogs (more than two thirds of the 21 dogs).\n\nAfter calculating the overall sensitivity for each dog using all line-ups, \"matched\" sensitivities were calculated only including line-ups containing COVID-19 positive and negative samples strictly comparable on confounding factors such as diabetes, anosmia, asthma, fever, body pain, diarrhoea, sex, hospital, method of sweat collection and sampling duration. Most of the time, the sensitivities increased after matching.\n\nPandemic conditions in the U.A.E., associated with the desire to use dogs as an efficient mass-pretesting tool has already led to the operational deployment of the study dogs.\n\nFuture studies will focus on comparatives fields-test results including the impact of the main COVID-19 comorbidities and other respiratory tract infections.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Takeru Nakabayashi",
-        "author_inst": "H.U. Group Research Institute G.K."
+        "author_name": "Dana H Al Marzooqi",
+        "author_inst": "Ministry of Interior. International affairs bureau. UAE"
       },
       {
-        "author_name": "Yuki Kawasaki",
-        "author_inst": "H.U. Group Research Institute G.K."
+        "author_name": "Clothilde Lecoq-Julien",
+        "author_inst": "Ecole Nationale Veterinaire Alfort. France"
       },
       {
-        "author_name": "Koichiro Murashima",
-        "author_inst": "H.U. Group Research Institute G.K."
+        "author_name": "Hamad K Al Hammadi",
+        "author_inst": "Ministry of Interior. International affairs bureau. UAE"
       },
       {
-        "author_name": "Kazuya Omi",
-        "author_inst": "H.U. Group Research Institute G.K."
+        "author_name": "Guillaume Alvergnat",
+        "author_inst": "Ministry of Interior. International affairs bureau. UAE"
+      },
+      {
+        "author_name": "Kalthoom M Al Blooshi",
+        "author_inst": "Ministry of Health and Prevention. Director of hospitals dept. UAE"
+      },
+      {
+        "author_name": "Salah K Al Mazrooei",
+        "author_inst": "General Dept of Protective Security and Emergency. Director Dubai K9 Unit. UAE"
+      },
+      {
+        "author_name": "Mohammed S Alhmoudi",
+        "author_inst": "Ministry of Interior of the U.A.E. International Affairs Bureau"
+      },
+      {
+        "author_name": "Faisal M Al Ahbabi",
+        "author_inst": "Infectious Diseases Programs. Abu Dhabi Health Center. UAE"
+      },
+      {
+        "author_name": "Yasser S Mohammed",
+        "author_inst": "Dubai Health Authority. UAE"
+      },
+      {
+        "author_name": "Nasser M Al Falasi",
+        "author_inst": "General Dept of Protective Security and Emergency. Dubai K9 Unit. UAE"
+      },
+      {
+        "author_name": "Noor M Almheiri",
+        "author_inst": "Head of Medical Services Unit Hospital Dpt. Ministry of Health and Prevention. UAE"
+      },
+      {
+        "author_name": "Sumaya M Al Blooshi",
+        "author_inst": "Director of Nursing Department, Hospital Sector, Ministry of Health and Prevention. UAE"
+      },
+      {
+        "author_name": "Quentin Muzzin",
+        "author_inst": "Ecole Nationale Veterinaire Alfort. France"
       },
       {
-        "author_name": "Satoshi Yuhara",
-        "author_inst": "H.U. Group Research Institute G.K."
+        "author_name": "Loic Desquilbet",
+        "author_inst": "Ecole Nationale Veterinaire Alfort. France"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "molecular biology"
+    "category": "animal behavior and cognition"
   },
   {
     "rel_doi": "10.1101/2021.01.20.427368",
@@ -933329,63 +936308,59 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2021.01.19.427282",
-    "rel_title": "SARS-CoV-2 infection of circulating immune cells is not responsible for virus dissemination in severe COVID-19 patients",
+    "rel_doi": "10.1101/2021.01.19.427250",
+    "rel_title": "COVID-19 Knowledge, Attitudes, and Practices of United Arab Emirates Medical and Health Sciences Students: A Cross Sectional Study",
     "rel_date": "2021-01-19",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.427282",
-    "rel_abs": "In late 2019 a novel coronavirus (SARS-CoV-2) emerged, and has since caused a global pandemic. Understanding the pathogenesis of COVID-19 disease is necessary to inform development of therapeutics, and management of infected patients. Using scRNAseq of blood drawn from SARS-CoV-2 patients, we asked whether SARS-CoV-2 may exploit immune cells as a  Trojan Horse to disseminate and access multiple organ systems. Our data suggests that circulating cells are not actively infected with SARS-CoV-2, and do not appear to be a source of viral dissemination.",
-    "rel_num_authors": 11,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.19.427250",
+    "rel_abs": "COVID-19 pandemic is the largest unprecedented viral pandemic of the 21st century. We aimed to study the COVID-19 knowledge, attitudes, and practices (KAP) among medical and health sciences students in the United Arab Emirates (UAE). We performed a cross-sectional study between 2nd June and 19th August 2020. The survey was developed using online Survey Monkey. The link was distributed via UAE University to all students and via WhatsApp(C) groups. The self-administered questionnaire was conducted in English and comprised of two parts: socio-demographic characteristics and KAP towards COVID-19. A total of 712 responses to the questionnaire were collected. 90% (n=695) were under-graduate, while 10% (n=81) were post-graduate students. Majority (87%, n=647) stated that they obtained COVID-19 information from multiple reliable sources. They were highly knowledgeable about COVID-19 pandemic but 76% (n=539) did not recognize its routes of transmission. 63% (n=431) were worried of getting COVID-19, while 92% (n=633)) were worried that a family member could get infected with the virus. 97% (n=655) took precautions when accepting home deliveries, 94% (n=637) had been washing their hands more frequently, and 95% (n=643) had been wearing face masks. In conclusion, participants showed high levels of knowledge and awareness about COVID-19. They were worried about getting infected themselves or their family members, and had good practices against COVID-19.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Nicole L Rosin",
-        "author_inst": "University of Calgary"
+        "author_name": "Noura Baniyas",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Arzina Jaffer",
-        "author_inst": "University of Calgary"
+        "author_name": "Mohamud  M Sheek-Hussein",
+        "author_inst": "UAE University: United Arab Emirates University"
       },
       {
-        "author_name": "Sarthak Sinha",
-        "author_inst": "University of Calgary"
+        "author_name": "Nouf Al Kaabi",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Rory P Mulloy",
-        "author_inst": "University of Calgary"
+        "author_name": "Maitha Al Shamsi",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Carolyn Robinson",
-        "author_inst": "University of Calgary"
+        "author_name": "Maitha  M Al Neyadi",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Elodie Labit",
-        "author_inst": "University of Calgary"
+        "author_name": "Rauda Al Khoori",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Luiz G Almeida",
-        "author_inst": "University of Calgary"
-      },
-      {
-        "author_name": "Antoine Dufour",
-        "author_inst": "University of Calgary"
+        "author_name": "Suad Ajab",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Jennifer A Corcoran",
-        "author_inst": "University of Calgary"
+        "author_name": "Muhammad Abid",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Bryan Yipp",
-        "author_inst": "University of Calgary"
+        "author_name": "Michael Grivna",
+        "author_inst": "College of Medicine"
       },
       {
-        "author_name": "Jeff Biernaskie",
-        "author_inst": "University of Calgary"
+        "author_name": "Fikri  M Abu Zidan",
+        "author_inst": "UAE University: United Arab Emirates University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "new results",
-    "category": "immunology"
+    "category": "scientific communication and education"
   },
   {
     "rel_doi": "10.1101/2021.01.16.21249632",
@@ -935826,43 +938801,59 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.01.14.21249637",
-    "rel_title": "SARS-CoV-2 infection control implementation based on sources of infection showing directions for three age groups in Japan",
+    "rel_doi": "10.1101/2021.01.15.21249863",
+    "rel_title": "How to best test suspected cases of COVID-19: an analysis of the diagnostic performance of RT-PCR and alternative molecular methods for the detection of SARS-CoV-2",
     "rel_date": "2021-01-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.14.21249637",
-    "rel_abs": "BackgroundSome aspects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in children and adults remain unclear. This report describes different SARS-CoV-2 transmission patterns by age group in Japan.\n\nMethods and findingsThis retrospective observational case series study analyzed transmission patterns of real-time polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 infections found by local health authorities and commercial laboratories during January 14 through July 31, 2020 in Japan. After ascertaining the infection source for every symptomatic case as clusters at households, daycare facilities, schools, hospitals and workplaces etc., their associated transmission patterns were analyzed. Identified cases were divided into three groups: underage, < 20; adults, 20-59; and elderly people 60 years old and older. The reproductive number (R)s of respective transmission directions found for the respective age groups were compared.\n\nOf 26,986 total cases, 23,746 unknown cases were found, leaving 3,240 ascertained sources of infection (12.0%) comprising 125 (3.9%) underage, 2350 (72.5%) adult, and 765 (23.6%) elderly people. The respective Rs of underage infection sources directed to underage, adult, and elderly people were estimated respectively as 0.0415 (95% CI, 0.0138-0.0691), 1.11 (95% CI, 0.9171-1.3226), and 0.2811 (95% CI, 0.2074-0.3687). The respective Rs of adult infection source directed to underage, adult, and elderly people were estimated respectively as 0.0140 (95% CI, 0.0120-0.0162), 0.5392 (95% CI, 0.5236-0.5550), and 0.1135 (95% CI, 0.1074-0.1197). The respective Rs of elderly infection source directed to underage, adult, and elderly people were estimated as 0.065 (95% CI, 0.0039-0.0091), 0.3264 (95% CI, 0.3059-0.3474), and 0.3991 (95% CI, 0.3757-0.4229).\n\nConclusionsThe main sources of SARS-CoV-2 infection were adults and elderly people. The R of underage people directed to adults was greater than 1 because of close familial contact but they were unlikely to become carriers transmitting SARS-CoV-2 because they accounted for a minority for transmissions. Apparently, SARS-CoV-2 was transmitted among adults and elderly people, suggesting that infection control of SARS-CoV-2 should be managed specifically by generation.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249863",
+    "rel_abs": "As COVID-19 testing is rolled out increasingly widely, the use of a range of alternative testing methods will be beneficial in ensuring testing systems are resilient and adaptable to different clinical and public health scenarios. Here, we compare and discuss the diagnostic performance of a range of different molecular assays designed to detect the presence of SARS-CoV-2 infection in people with suspected COVID-19. Using findings from a systematic review of 103 studies, we categorised COVID-19 molecular assays into 12 different test classes, covering point-of-care tests, various alternative RT-PCR protocols, and alternative methods such as isothermal amplification. We carried out meta-analyses to estimate the diagnostic accuracy and clinical utility of each test class. We also estimated the positive and negative predictive values of all diagnostic test classes across a range of prevalence rates. Using previously validated RT-PCR assays as a reference standard, 11 out of 12 classes showed a summary sensitivity estimate of at least 92% and a specificity estimate of at least 99%. Several diagnostic test classes were estimated to have positive predictive values of 100% throughout the investigated prevalence spectrum, whilst estimated negative predictive values were more variable and sensitive to disease prevalence. We also report the results of clinical utility models that can be used to determine the information gained from a positive and negative test result in each class, and whether each test is more suitable for confirmation or exclusion of disease. Our analysis suggests that several tests exist that are suitable alternatives to standard RT-PCR and we discuss scenarios in which these could be most beneficial, such as where time to test result is critical or, where resources are constrained. However, we also highlight methodological concerns with the design and conduct of many included studies, and also the existence of likely publication bias for some test classes. Our results should be interpreted with these shortcomings in mind. Furthermore, our conclusions on test performance are limited to their use in symptomatic populations: we did not identify sufficient suitable data to allow analysis of testing in asymptomatic populations.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Atsuko Hata",
-        "author_inst": "Kitano hospital, The Tazuke Kofukai Medical Research Institute"
+        "author_name": "Adrian Mironas",
+        "author_inst": "Health Technology Wales"
       },
       {
-        "author_name": "Junko Kurita",
-        "author_inst": "Tokiwa University, Ibaraki, Japan"
+        "author_name": "David Jarrom",
+        "author_inst": "Health Technology Wales"
       },
       {
-        "author_name": "Eri Muso",
-        "author_inst": "Kyoto Kacho University"
+        "author_name": "Evan Campbell",
+        "author_inst": "Healthcare Improvement Scotland"
       },
       {
-        "author_name": "Toshiro Katayama",
-        "author_inst": "Morinomiya University of Medical Sciences"
+        "author_name": "Jennifer Washington",
+        "author_inst": "Health Technology Wales"
       },
       {
-        "author_name": "Takahide Hata",
-        "author_inst": "Kitano hospital, The Tazuke Kofukai Medical Research Institute"
+        "author_name": "Sabine Ettinger",
+        "author_inst": "HTA Austria - Austrian Institute for Health Technology Assessment GmbH"
       },
       {
-        "author_name": "Yasushi Ohkusa",
-        "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan"
+        "author_name": "Ingrid Wilbacher",
+        "author_inst": "Federation of Social Insurances"
+      },
+      {
+        "author_name": "Gottfried Endel",
+        "author_inst": "Federation of Social Insurances"
+      },
+      {
+        "author_name": "Hrvoje Vrazic",
+        "author_inst": "Federation of Social Insurances"
+      },
+      {
+        "author_name": "Susan Myles",
+        "author_inst": "Health Technology Wales"
+      },
+      {
+        "author_name": "Matthew Prettyjohns",
+        "author_inst": "Health Technology Wales"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2021.01.15.21249868",
@@ -937740,41 +940731,81 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.12.21249603",
-    "rel_title": "Isolation of SARS-CoV-2 from the air in a car driven by a COVID patient with mild illness",
+    "rel_doi": "10.1101/2021.01.10.20248871",
+    "rel_title": "Emergence of multiple SARS-CoV-2 mutations in an immunocompromised host",
     "rel_date": "2021-01-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.12.21249603",
-    "rel_abs": "We used a Sioutas personal cascade impactor sampler (PCIS) to screen for SARS-CoV-2 in a car driven by a COVID-19 patient. SARS-CoV-2 was detectable at all PCIS stages by PCR and was cultured from the section of the sampler collecting particles in the 0.25 to 0.50 {square}m size range.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.10.20248871",
+    "rel_abs": "Prolonged shedding of infectious SARS-CoV-2 has recently been reported in a number of immunosuppressed individuals with COVID-19. Here, we describe the detection of high levels of replication-competent SARS-CoV-2 in specimens taken from the respiratory tract of a B-cell depleted patient up to 154 days after initial COVID-19 diagnosis concomitant with the development of high mutation rate. In this patient, a total of 11 nonsynonymous mutations were detected in addition to the Y144 deletion in the spike protein of SARS-CoV-2.\n\nVirus evolution studies revealed a dramatic diversification in viral population coinciding with treatment with convalescent plasma and clinical respiratory deterioration. Our findings highlight the urgent need for continuous real-time surveillance of genetic changes of SARS-CoV-2 adaptation alongside immunological investigations in patients with severely compromised humoral responses who may shed infectious virus over prolonged periods of time.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "John A Lednicky",
-        "author_inst": "University of Florida"
+        "author_name": "Elham Khatamzas",
+        "author_inst": "Department of Medicine III, LMU Hospital Munich, Germany"
       },
       {
-        "author_name": "Michael Lauzardo",
-        "author_inst": "University of Florida"
+        "author_name": "Alexandra Rehn",
+        "author_inst": "Bundeswehr, Institute of Microbiology, Munich, Germany and German Center for Infection Research (DZIF), Partner Site Munich, Germany"
       },
       {
-        "author_name": "Md. Mabubul Alam",
-        "author_inst": "Univesrity of Florida"
+        "author_name": "Maximilian Muenchhoff",
+        "author_inst": "Max von Pettenkofer Institute and Gene Center, Virology, Faculty of Medicine, LMU Munich, Germany and COVID-19 Registry of the LMU Munich (CORKUM), University H"
       },
       {
-        "author_name": "Maha Elbadry",
-        "author_inst": "Univesrity of Florida"
+        "author_name": "Johannes Hellmuth",
+        "author_inst": "Department of Medicine III, LMU Hospital Munich, Germany; COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU, Munich, Germany"
       },
       {
-        "author_name": "Caroline Stephenson",
-        "author_inst": "Univesrity of Florida"
+        "author_name": "Erik Gaitzsch",
+        "author_inst": "Department of Medicine III, LMU Hospital Munich, Germany"
       },
       {
-        "author_name": "Julia C. Gibson",
-        "author_inst": "University of Florida"
+        "author_name": "Tobias Weiglein",
+        "author_inst": "Department of Medicine III, LMU Hospital Munich, Germany"
       },
       {
-        "author_name": "John Glenn Morris Jr.",
-        "author_inst": "University of Florida"
+        "author_name": "Enrico Georgi",
+        "author_inst": "Bundeswehr, Institute of Microbiology, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany"
+      },
+      {
+        "author_name": "Clemens Scherer",
+        "author_inst": "COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, LMU, Munich, Germany; Department of Medicine I, LMU Hospital Munich, Germany"
+      },
+      {
+        "author_name": "Stephanie Stecher",
+        "author_inst": "Department of Medicine II, LMU Hospital Munich, Germany"
+      },
+      {
+        "author_name": "Oliver Weigert",
+        "author_inst": "Department of Medicine III, LMU Hospital Munich, Germany; German Cancer Consortium (DKTK), Munich, Germany; German Cancer Research Center (DKFZ), Heidelberg, Ge"
+      },
+      {
+        "author_name": "Philipp Girl",
+        "author_inst": "Bundeswehr, Institute of Microbiology, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany"
+      },
+      {
+        "author_name": "Sabine Zange",
+        "author_inst": "German Center for Infection Research (DZIF), Partner Site Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany"
+      },
+      {
+        "author_name": "Oliver T. Keppler",
+        "author_inst": "Max von Pettenkofer Institute and Gene Center, Virology, Faculty of Medicine, LMU Munich, Germany; German Center for Infection Research (DZIF), Partner Site Mun"
+      },
+      {
+        "author_name": "Joachim Stemmler",
+        "author_inst": "Department of Medicine III, LMU Hospital Munich, Germany"
+      },
+      {
+        "author_name": "Michael Bergwelt-Baildon",
+        "author_inst": "Department of Medicine III, LMU Hospital Munich, Germany; German Cancer Consortium (DKTK), Munich, Germany; German Cancer Research Center (DKFZ), Heidelberg, Ge"
+      },
+      {
+        "author_name": "Roman Woelfel",
+        "author_inst": "Bundeswehr, Institute of Microbiology, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany"
+      },
+      {
+        "author_name": "Markus Antwerpen",
+        "author_inst": "Bundeswehr, Institute of Microbiology, Munich, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany"
       }
     ],
     "version": "1",
@@ -939682,83 +942713,151 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.12.20248588",
-    "rel_title": "Bacterial superinfection pneumonia in SARS-CoV-2 respiratory failure",
+    "rel_doi": "10.1101/2021.01.14.21249831",
+    "rel_title": "Increased peripheral blood neutrophil activation phenotypes and NETosis in critically ill COVID-19 patients",
     "rel_date": "2021-01-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.12.20248588",
-    "rel_abs": "BackgroundSevere community-acquired pneumonia secondary to SARS-CoV-2 is a leading cause of death. Current guidelines recommend patients with SARS-CoV-2 pneumonia receive empirical antibiotic therapy for suspected bacterial superinfection, but little evidence supports these recommendations.\n\nMethodsWe obtained bronchoscopic bronchoalveolar lavage (BAL) samples from patients with SARS-CoV-2 pneumonia requiring mechanical ventilation. We analyzed BAL samples with multiplex PCR and quantitative culture to determine the prevalence of superinfecting pathogens at the time of intubation and identify episodes of ventilator-associated pneumonia (VAP) over the course of mechanical ventilation. We compared antibiotic use with guideline-recommended care.\n\nResultsThe 179 ventilated patients with severe SARS-CoV-2 pneumonia discharged from our hospital by June 30, 2020 were analyzed. 162 (90.5%) patients had at least one BAL procedure; 133 (74.3%) within 48 hours after intubation and 112 (62.6%) had at least one subsequent BAL during their hospitalization. A superinfecting pathogen was identified within 48 hours of intubation in 28/133 (21%) patients, most commonly methicillin-sensitive Staphylococcus aureus or Streptococcus species (21/28, 75%). BAL-based treatment reduced antibiotic use compared with guideline-recommended care. 72 patients (44.4%) developed at least one VAP episode. Only 15/72 (20.8%) of initial VAPs were attributable to multidrug-resistant pathogens. The incidence rate of VAP was 45.2/1000 ventilator days.\n\nConclusionsWith use of sensitive diagnostic tools, bacterial superinfection at the time of intubation is infrequent in patients with severe SARS-CoV-2 pneumonia. Treatment based on current guidelines would result in substantial antibiotic overuse. The incidence rate of VAP in ventilated patients with SARS-CoV-2 pneumonia are higher than historically reported.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.14.21249831",
+    "rel_abs": "BackgroundIncreased inflammation is a hallmark of COVID-19, with pulmonary and systemic inflammation identified in multiple cohorts of patients. Definitive cellular and molecular pathways driving severe forms of this disease remain uncertain. Neutrophils, the most numerous leukocytes in blood circulation, can contribute to immunopathology in infections, inflammatory diseases and acute respiratory distress syndrome (ARDS), a primary cause of morbidity and mortality in COVID-19. Changes in multiple neutrophil functions and circulating cytokine levels over time during COVID-19 may help define disease severity and guide care and decision making.\n\nMethodsBlood was obtained serially from critically ill COVID-19 patients for 11 days. Neutrophil oxidative burst, neutrophil extracellular trap formation (NETosis), phagocytosis and cytokine levels were assessed ex vivo. Lung tissue was obtained immediately post-mortem for immunostaining.\n\nResultsElevations in neutrophil-associated cytokines IL-8 and IL-6, and general inflammatory cytokines IP-10, GM-CSF, IL-1b, IL-10 and TNF, were identified in COVID-19 plasma both at the first measurement and at multiple timepoints across hospitalization (p < 0.0001). Neutrophils had exaggerated oxidative burst (p < 0.0001), NETosis (p < 0.0001) and phagocytosis (p < 0.0001) relative to controls. Increased NETosis correlated with both leukocytosis and neutrophilia. Neutrophils and NETs were identified within airways and alveoli in the lung parenchyma of 40% of SARS-CoV-2 infected lungs. While elevations in IL-8 and ANC correlated to COVID-19 disease severity, plasma IL-8 levels alone correlated with death.\n\nConclusionsCirculating neutrophils in COVID-19 exhibit an activated phenotype with increased oxidative burst, NETosis and phagocytosis. Readily accessible and dynamic, plasma IL-8 and circulating neutrophil function may be potential COVID-19 disease biomarkers.",
+    "rel_num_authors": 33,
     "rel_authors": [
       {
-        "author_name": "Chiagozie O. Pickens",
-        "author_inst": "Division of Pulmonary and Critical Care, Department of Medicine, Northwestern University Feinberg School of Medicine"
+        "author_name": "Jorge A. Masso-Silva PhD",
+        "author_inst": "VA San Diego Healthcare System"
       },
       {
-        "author_name": "Catherine A. Gao",
-        "author_inst": "Northwestern"
+        "author_name": "Alexander Moshensky BS",
+        "author_inst": "VA San Diego Healthcare System"
       },
       {
-        "author_name": "Michael J. Cuttica",
-        "author_inst": "Division of Pulmonary and Critical Care, Department of Medicine, Northwestern University Feinberg School of Medicine"
+        "author_name": "Michael T. Y. Lam MD PhD",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "Sean B. Smith",
-        "author_inst": "Division of Pulmonary and Critical Care, Department of Medicine, Northwestern University Feinberg School of Medicine"
+        "author_name": "Mazen Odish MD",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "Lorenzo Pesce",
-        "author_inst": "Department of Pharmacology, Northwestern University Department of Pharmacology School of Medicine"
+        "author_name": "Arjun Patel MBBS",
+        "author_inst": "VA San Diego Healthcare System"
       },
       {
-        "author_name": "Rogan Grant",
-        "author_inst": "Northwestern University Feinberg School of Medicine"
+        "author_name": "Le Xu PhD",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "Mengjia Kang",
-        "author_inst": "Northwestern University Feinberg School of Medicine"
+        "author_name": "Emily Hansen MS",
+        "author_inst": "Rady Childrens Hospital"
       },
       {
-        "author_name": "Luisa Morales-Nebreda",
-        "author_inst": "Division of Pulmonary and Critical Care, Department of Medicine, Northwestern University Feinberg School of Medicine"
+        "author_name": "Samantha Trescott BS",
+        "author_inst": "Rady Childrens Hospital"
       },
       {
-        "author_name": "Avni A. Bavishi",
-        "author_inst": "Northwestern University Feinberg School of Medicine"
+        "author_name": "Celina Nguyen BS",
+        "author_inst": "Rady Childrens Hospital"
       },
       {
-        "author_name": "Jason Arnold",
-        "author_inst": "Northwestern University Feinberg School of Medicine"
+        "author_name": "Roy Kim BS",
+        "author_inst": "Rady Childrens Hospital"
       },
       {
-        "author_name": "Anna Pawlowski",
-        "author_inst": "Clinical Translational Sciences Institute, Northwestern University Feinberg School of Medicine"
+        "author_name": "Katherine Perofsky MD",
+        "author_inst": "Rady Childrens Hospital"
       },
       {
-        "author_name": "Chao Qi",
-        "author_inst": "Department of Pathology, Northwestern University Feinberg School of Medicine"
+        "author_name": "Samantha Perera N/A",
+        "author_inst": "VA San Diego Healthcare System"
       },
       {
-        "author_name": "GR Scott Budinger",
-        "author_inst": "Division of Pulmonary and Critical Care, Department of Medicine, Northwestern University Feinberg School of Medicine"
+        "author_name": "Lauren Ma BS",
+        "author_inst": "VA San Diego Healthcare System"
       },
       {
-        "author_name": "Benjamin D. Singer",
-        "author_inst": "Division of Pulmonary and Critical Care, Department of Medicine, Northwestern University Feinberg School of Medicine"
+        "author_name": "Josephine Pham N/A",
+        "author_inst": "VA San Diego Healthcare System"
       },
       {
-        "author_name": "Richard G. Wunderink",
-        "author_inst": "Division of Pulmonary and Critical Care, Department of Medicine, Northwestern University Feinberg School of Medicine"
+        "author_name": "Mark Rolfsen MD",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "- NU COVID Investigators",
-        "author_inst": ""
+        "author_name": "Jarod Olay MS",
+        "author_inst": "VA San Diego Healthcare System"
+      },
+      {
+        "author_name": "John Shin BS",
+        "author_inst": "VA San Diego Healthcare System"
+      },
+      {
+        "author_name": "Jennifer M. Dan MD PhD",
+        "author_inst": "La Jolla Institute of Allergy and Immunology"
+      },
+      {
+        "author_name": "Robert Abbott PhD",
+        "author_inst": "La Jolla Institute of Allergy and Immunology"
+      },
+      {
+        "author_name": "Sydney Ramirez MD PhD",
+        "author_inst": "La Jolla Institute of Allergy and Immunology"
+      },
+      {
+        "author_name": "Thomas H. Alexander MD MHSc",
+        "author_inst": "Scripps Clinic"
+      },
+      {
+        "author_name": "Grace Y. Lin MD",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Ana Lucia Fuentes MD",
+        "author_inst": "VA San Diego Healthcare System"
+      },
+      {
+        "author_name": "Ira N. Advani BS",
+        "author_inst": "VA San Diego Healthcare System"
+      },
+      {
+        "author_name": "Deepti Gunge BS",
+        "author_inst": "VA San Diego Healthcare System"
+      },
+      {
+        "author_name": "Victor Pretorius MBChB MD",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Atul Malhotra MD",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Xin Sun PhD",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Jason Duran MD PhD",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Shane Crotty PhD",
+        "author_inst": "La Jolla Institute of Allergy and Immunology"
+      },
+      {
+        "author_name": "Nicole G. Coufal MD PhD",
+        "author_inst": "Rady Childrens Hospital"
+      },
+      {
+        "author_name": "Angela Meier MD PhD",
+        "author_inst": "VA San Diego Healthcare System"
+      },
+      {
+        "author_name": "Laura E. Crotty Alexander MD",
+        "author_inst": "VA San Diego Healthcare System"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "intensive care and critical care medicine"
+    "category": "allergy and immunology"
   },
   {
     "rel_doi": "10.1101/2021.01.13.21249429",
@@ -941528,65 +944627,141 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.01.11.21249630",
-    "rel_title": "Determining the optimal COVID-19 policy response using agent-based modelling linked to health and cost modelling: Case study for Victoria, Australia",
+    "rel_doi": "10.1101/2021.01.11.21249564",
+    "rel_title": "The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions",
     "rel_date": "2021-01-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.11.21249630",
-    "rel_abs": "ImportanceDetermining the best policy on social restrictions and lockdowns for the COVID-19 pandemic is challenging.\n\nObjectiveTo determine the optimal policy response ranging from aggressive and moderate elimination, tight suppression (aiming for 1 to 5 cases per million per day) and loose suppression (5 to 25 cases per million per day).\n\nDesignTwo simulation models in series: an agent-based model to estimate daily SARS-CoV-2 infection rates and time in four stages of social restrictions; a proportional multistate lifetable model to estimate long-run health impacts (health adjusted life years (HALYs) arising from SARS-CoV-2) and costs (health systems, and health system plus GDP).\n\nThe net monetary benefit (NMB) of each policy option at varying willingness to pay (WTP) per HALY was calculated: NMB = HALYs x WTP - cost. The optimal policy response was that with the highest NMB.\n\nSetting and participantsThe State of Victoria, Australia, using simulation modeling of all residents.\n\nMain Outcome and MeasuresSARS-CoV-2 infection rates, time under various stages of restrictions, HALYs, health expenditure and GDP losses.\n\nResultsAggressive elimination resulted in the highest percentage of days with the lowest level of restrictions (median 31.7%, 90% simulation interval 6.6% to 64.4%). However, days in hard lockdown were similar across all four strategies (medians 27.5% to 36.1%).\n\nHALY losses (compared to a no-COVID-19 scenario) were similar for aggressive elimination (286, 219 to 389) and moderate elimination (314, 228 to 413), and nearly eight and 40-times higher for tight and loose suppression. The median GDP loss was least for moderate elimination ($US41.7 billion, $29.0 to $63.6 billion), but there was substantial overlap in simulation intervals between the four strategies.\n\nFrom a health system perspective aggressive elimination was optimal in 64% of simulations above a willingness to pay of $15,000 per HALY, followed by moderate elimination in 35% of simulations.\n\nModerate elimination was optimal from a partial societal perspective in half the simulations followed by aggressive elimination in a quarter.\n\nShortening the pandemic duration to 6 months saw loose suppression become preferable under a partial societal perspective.\n\nConclusions and RelevanceElimination strategies were preferable over a 1-year pandemic duration.\n\nFundingAnonymous philanthropic donation to the University of Melbourne.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSTo determine the optimal of four policy responses to COVID-19 in the State of Victoria, Australia (aggressive and moderate elimination, tight suppression (aiming for 1 to 5 cases per million per day) and loose suppression (5 to 25 cases per million per day), based on estimated future health loss and costs from both a health system and partial societal perspective.\n\nFindingsFrom a health system perspective aggressive elimination was optimal in 64% of simulations above a willingness to pay of $15,000 per HALY, followed by moderate elimination in 35% of simulations. Moderate elimination was optimal from a partial societal perspective (i.e., including GDP losses) in half the simulations followed by aggressive elimination in a quarter.\n\nMeaningWhilst there is considerable uncertainty in outcomes for all the four policy options, the two elimination options are usually optimal from both a health system and a partial societal (health expenditure plus GDP cost) perspective.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.11.21249564",
+    "rel_abs": "We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Among control measures implemented, only national lockdown brought the reproduction number below 1 consistently; introduced one week earlier it could have reduced first wave deaths from 36,700 to 15,700 (95%CrI: 8,900-26,800). Improved clinical care reduced the infection fatality ratio from 1.25% (95%CrI: 1.18%-1.33%) to 0.77% (95%CrI: 0.71%-0.84%). The infection fatality ratio was higher in the elderly residing in care homes (35.9%, 95%CrI: 29.1%-43.4%) than those residing in the community (10.4%, 95%CrI: 9.1%-11.5%). England is still far from herd immunity, with regional cumulative infection incidence to 1st December 2020 between 4.8% (95%CrI: 4.4%-5.1%) and 15.4% (95%CrI: 14.9%-15.9%) of the population.\n\nOne-sentence summaryWe fit a mathematical model of SARS-CoV-2 transmission to surveillance data from England, to estimate transmissibility, severity, and the impact of interventions",
+    "rel_num_authors": 31,
     "rel_authors": [
       {
-        "author_name": "Professor Tony Blakely",
-        "author_inst": "University of Melbourne"
+        "author_name": "Edward S. Knock",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Dr Jason Thompson",
-        "author_inst": "University of Melbourne"
+        "author_name": "Lilith K. Whittles",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Dr Laxman Bablani",
-        "author_inst": "University of Melbourne"
+        "author_name": "John A. Lees",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Patrick Andersen",
-        "author_inst": "University of Melbourne"
+        "author_name": "Pablo N. Perez-Guzman",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Dr Driss Ait Ouakrim",
-        "author_inst": "University of Melbourne"
+        "author_name": "Robert Verity",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Dr Natalie Carvalho",
-        "author_inst": "University of Melbourne"
+        "author_name": "Richard G. FitzJohn",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Patrick Abraham",
-        "author_inst": "University of Melbourne"
+        "author_name": "Katy AM. Gaythorpe",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Marie-Anne Boujaoude",
-        "author_inst": "University of Melbourne"
+        "author_name": "Natsuko Imai",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Ameera Katar",
-        "author_inst": "University of Melbourne"
+        "author_name": "Wes Hinsley",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Edifofon Akpan",
-        "author_inst": "University of Melbourne"
+        "author_name": "Lucy C. Okell",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Nick Wilson",
-        "author_inst": "University of Otago, Wellington"
+        "author_name": "Alicia Rosello",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Professor Mark Stevenson",
-        "author_inst": "University of Melbourne"
+        "author_name": "Nikolas Kantas",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Caroline E. Walters",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Sangeeta Bhatia",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Oliver J. Watson",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Charles Whittaker",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Lorenzo Cattarino",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Adhiratha Boonyasiri",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Bimandra A. Djaafara",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Keith Fraser",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Han Fu",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Haowei Wang",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Xiaoyue Xi",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Christl A. Donnelly",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Elita Jauneikaite",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Daniel J. Laydon",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Peter J. White",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Azra C. Ghani",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Neil M. Ferguson",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Anne Cori",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "Marc Baguelin",
+        "author_inst": "Imperial College London"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -943150,31 +946325,31 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2021.01.09.21249489",
-    "rel_title": "Impact of COVID-19 pandemic on use of Pediatric Emergency Health Services in a Tertiary Care Pediatric Hospital in North India",
+    "rel_doi": "10.1101/2021.01.06.20249030",
+    "rel_title": "Convergence of Comorbidity and COVID-19 Infection to Fatality: An Investigation Based on Concurrent Health Status Evaluation among the Elderly Population in Kerala",
     "rel_date": "2021-01-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.09.21249489",
-    "rel_abs": "ObjectiveTo compare Pediatric Emergency attendance pre-COVID 19 to that during COVID 19 pandemic and to study changes in patient profiles attending Pediatric Emergency Department during COVID 19 pandemic.\n\nMethodsWe conducted a retrospective cross-sectional observational study and collected data from Medical Record Section during the COVID-19 pandemic from January to June 2020 and compared it with data from 2019 in similar months. Data collected was analyzed to find out the impact of COVID - 19 on use of pediatric emergency health services with respect to patient attendance, age and clinical profile before and during COVID-19 in a tertiary care hospital in New Delhi.\n\nResultsWe observed a 43% decline in PED visits which increased to 75% during the period of lock-down (p value = 0.005). There was a significant decrease in children of age group 1-5 years attending PED. Mortality rate during lockdown had gone up by nearly 3times than the average monthly mortality.\n\nConclusionsWhile children might not have been directly affected by the COVID-19 pandemic, but the fear of COVID 19 and measures taken to control the pandemic has affected the health seeking behavior of patients to an extent that indirectly caused more damage than anticipated.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.20249030",
+    "rel_abs": "ObjectiveTo investigate the impact of age, comorbidity, and vaccination in the fatality of older COVID-19 patients in the state of Kerala, India, based on their comorbidity and vaccination status.\n\nMethodsIt is a cross sectional study adopting a mixed method approach conducted among the older population in Kerala. To study the health profile, 405 older people were surveyed, and 102 people were interviewed in-depth at their households, between June to November 2020. The results of the study were triangulated with elderly COVID-19 fatality data, available from the citizen-science dashboards of the research team and Department of Health, Kerala. Vaccination data was retrieved from cowin.gov.in to study its impact. The data was analysed using the IBM SPSS version 22.0.\n\nResultsAge is a predictor of COVID-19 fatality. Diabetes, hypertension, heart diseases, CKD and COPD are the significant predictors of elderly COVID-19 fatality. The current comorbidity profile of the total older population matches with the comorbidities of the COVID-19 elderly death cases. Vaccination has impacted COVID-19 mortality after vaccinating 65 percent (first dose) of the elderly.\n\nConclusionsAge and comorbidities can predict potential fatality among older COVID-19 patients. Timely and accurate health data and better knowledge of high-risk factors such as comorbidity can easily guide the healthcare system and authorities to efficient prevention and treatment methodologies. Knowledge on prevailing NCDs can drive early preparedness before it converges with an epidemic like the present zoonotic disease. Priority must be given for elderly vaccination to bring down the mortality rates.",
     "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Ravitanaya Sodani",
-        "author_inst": "Lady Hardinge Medical College, New Delhi, India"
+        "author_name": "Sindhu Joseph",
+        "author_inst": "Govinda Pai Memorial Government College"
       },
       {
-        "author_name": "Shalu Gupta",
-        "author_inst": "Lady Hardinge Medical College & Kalawati Saran Children's Hospital, New Delhi, India"
+        "author_name": "Jijo Pulickiyil Ulahannan",
+        "author_inst": "Government College Kasaragod"
       },
       {
-        "author_name": "Virendra Kumar",
-        "author_inst": "Lady Hardinge Medical College & Kalawati Saran Children's Hospital, New Delhi, India"
+        "author_name": "Parvathy AJ",
+        "author_inst": "Vellore Institute of Technology"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pediatrics"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2021.01.10.20249079",
@@ -944856,21 +948031,105 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2021.01.10.21249548",
-    "rel_title": "Atmospheric PM2.5 before and after Lockdown in relation to COVID-19 Evolution and daily Viral Counts: Could Viral Natural Selection have occurred due to changes in the Airborne Pollutant PM2.5 acting as a Vector for SARS-CoV-2?",
+    "rel_doi": "10.1101/2021.01.10.21249151",
+    "rel_title": "Robotic RNA extraction for SARS-CoV-2 surveillance using saliva samples",
     "rel_date": "2021-01-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.10.21249548",
-    "rel_abs": "BackgroundGenes coding for SARS-CoV-2 have been detected on the microscopic airborne pollutant particulate matter, which has been suggested as a vector for COVID-19 transmission. Lockdown in China has been shown to be associated with significant reduction in pollution including the particulate matter component which coincided with the appearance of a viral mutant (Clade G) which steadily displaced the original Clade D after lockdown. The reason why Clade G developed a fitness advantage is as yet unknown. This paper examines the possible role of airborne particulate matter PM2.5 as selective pressure determining viral Clade predominance and further shedding light on the mode of SARS-CoV-2 transmission.\n\nMethodsThe average levels of PM2.5 of a number of cities were obtained from the Air Quality Index (AQI), a real-time assessment of atmospheric pollution. The daily average PM2.5 levels were assessed between January 23rd and April 29th 2020 determined by the timeline when viral counts in Beijing and other cities were available. Daily viral counts of Clades D and G were available starting from the 12th February as determined by the scientific literature published in August 2020. The cities chosen were Beijing, Sheffield, Nottingham, Sydney and Cambridge because of their substantially elevated viral counts compared to other cities. Cities as opposed to vaster areas/nations were chosen as PM2.5 levels vary across regions and countries.\n\nResultsFor the time period assessed, the Beijing PM2.5 pattern initiated with highly elevated mean PM2.5 levels of 155.8{micro}g/m3 (SD+/-73.6) during high viral counts, followed by 82.1{micro}g/m3 (SD+/-44.9) (p<0.04) when the viral counts decreased. In all the other cities assessed, the pattern differed whereby the PM2.5 levels increased significantly over the preceding baseline contemporaneously with the viral count rise. The changes in these cities PM2.5 levels were on average 31.5{micro}g/m3 before viral counts rose and 56.35{micro}g/m3 contemporaneous with viral count rise. The average levels of PM2.5 in these cities started to decrease one week after lockdown to 46{micro}g/m3 when measured over 2 weeks post-lockdown.\n\nAs regards the viral counts from data retrieved from Beijing, the latter part of the bell-shaped curve and a subsequent smaller curve of the viral count was available for evaluation. The average viral count for Clade D in Beijing was 11.1(SD+/-13.5) followed by a mean viral count for Clade G was 13.8(SD+/-9.2). Conversely in all the other cities besides Beijing, the viral counts averaged 45.8 for Clade D and 161 for Clade G. The variation in viral counts between cities suggests the strong possibility of variation in the availability of sampling between cities.\n\nThe newer variant, Clade G demonstrated viral counts initially appearing in mid-February in Beijing to later displace Clade D as the dominant viral Clade. The appearance of Clade G coincided with the decreasing gradient of PM2.5 levels. A number of significant correlations were obtained between PM2.5 levels and the viral count in all the cities reviewed.\n\nConclusionCOVID-19 viral counts appear to increase concomitant with increasing PM2.5 levels. Viral counts of both Clades correlated differentially with PM2.5 levels in all the cities assessed. The significantly highly elevated PM2.5 levels in Beijing resulted in correlating mainly with Clade D, however Clade G began to appear with decreasing PM2.5 levels, suggesting the beginnings for the initial SARS-CoV-2 Clade evolution. Clade G, the newer variant was able to flourish at lower levels of PM2.5 than Clade D. Clade G may possibly have utilized other sources of particulate matter as a viral vector, such as that derived from tobacco smoking, whereby 66% of Chinese males are smokers and 70% of the Chinese non-smoking population are exposed to 2nd hand smoking.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.10.21249151",
+    "rel_abs": "Saliva is an attractive specimen type for asymptomatic surveillance of COVID-19 in large populations due to its ease of collection and its demonstrated utility for detecting RNA from SARS-CoV-2. Multiple saliva-based viral detection protocols use a direct-to-RT-qPCR approach that eliminates nucleic acid extraction but can reduce viral RNA detection sensitivity. To improve test sensitivity while maintaining speed, we developed a robotic nucleic acid extraction method for detecting SARS-CoV-2 RNA in saliva samples with high throughput. Using this assay, the Free Asymptomatic Saliva Testing (IGI-FAST) research study on the UC Berkeley campus conducted 11,971 tests on supervised self-collected saliva samples and identified rare positive specimens containing SARS-CoV-2 RNA during a time of low infection prevalence. In an attempt to increase testing capacity, we further adapted our robotic extraction assay to process pooled saliva samples. We also benchmarked our assay against the gold standard, nasopharyngeal swab specimens. Finally, we designed and validated a RT-qPCR test suitable for saliva self-collection. These results establish a robotic extraction-based procedure for rapid PCR-based saliva testing that is suitable for samples from both symptomatic and asymptomatic individuals.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Yves Muscat Baron",
-        "author_inst": "Medical School, University of Malta."
+        "author_name": "Jennifer R. Hamilton",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Elizabeth C. Stahl",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Connor A. Tsuchida",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Enrique Lin-Shiao",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "C. Kimberly Tsui",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Kathleen Pestal",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Holly K. Gildea",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Lea B. Witkowsky",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Erica A. Moehle",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Shana L. McDevitt",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Matthew McElroy",
+        "author_inst": "Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Amanda Keller",
+        "author_inst": "Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Iman Sylvain",
+        "author_inst": "Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Ariana Hirsh",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Alison Ciling",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Alexander J. Ehrenberg",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "- IGI SARS-CoV-2 consortium",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Bradley R. Ringeisen",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Garth Huberty",
+        "author_inst": "Washington Hospital Healthcare System Clinical Laboratory, Fremont, CA USA"
+      },
+      {
+        "author_name": "Fyodor D. Urnov",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Petros Giannikopoulos",
+        "author_inst": "Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA"
+      },
+      {
+        "author_name": "Jennifer A. Doudna",
+        "author_inst": "University of California, Berkeley, Berkeley, CA, USA. Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA. Howard Hughes Medic"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -947078,95 +950337,63 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.08.20249041",
-    "rel_title": "The incremental value of computed tomography of COVID-19 pneumonia in predicting ICU admission",
+    "rel_doi": "10.1101/2021.01.06.21249325",
+    "rel_title": "Pregnancy and neonatal outcomes of COVID-19, co-reporting of common outcomes from the PAN-COVID and AAP SONPM registry",
     "rel_date": "2021-01-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.20249041",
-    "rel_abs": "RationaleTriage is crucial for patients management and estimation of the required Intensive Care Unit (ICU) beds is fundamental for Health Systems during the COVID-19 pandemic.\n\nObjectiveTo assess whether chest Computed Tomography (CT) of COVID-19 pneumonia has an incremental role in predicting patients admission to ICU.\n\nMethodsWe performed volumetric and texture analysis of the areas of the affected lung in CT of 115 outpatients with COVID-19 infection presenting to the Emergency Room with dyspnea and unresponsive hypoxyemia. Admission blood laboratory including lymphocyte count, serum lactate dehydrogenase, D-dimer and C-Reactive Protein and the ratio between the arterial partial pressure of oxygen and inspired oxygen were collected. By calculating the areas under the receiver-operating characteristic curves (AUC), we compared the performance of blood laboratory-arterial gas analyses features alone and combined with the CT features in two hybrid models (Hybrid radiological and Hybrid radiomics)for predicting ICU admission. Following a machine learning approach, 63 patients were allocated to the training and 52 to the validation set.\n\nMeasurements and Main ResultsTwenty-nine (25%) of patients were admitted to ICU. The Hybrid radiological model comprising the lung %consolidation performed significantly (p=0.04) better in predicting ICU admission in the validation (AUC=0.82; 95%Confidence Interval 0.68-0.95) set than the blood laboratory-arterial gas analyses features alone (AUC=0.71; 95%Confidence Interval 0.56-0.86). A risk calculator for ICU admission was derived and is available at:https://github.com/cgplab/covidapp\n\nConclusionsThe volume of the consolidated lung in CT of patients with COVID-19 pneumonia has a mild but significant incremental value in predicting ICU admission.",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.21249325",
+    "rel_abs": "BackgroundFew large, cohort studies report data on individuals maternal, fetal, perinatal, and neonatal outcomes associated with SARS-CoV-2 infection in pregnancy. We report outcomes from a collaboration formed early during the pandemic between the investigators of two registries, the UK and global Pregnancy and Neonatal outcomes in COVID-19 (PAN-COVID) study and the US American Academy of Pediatrics Section on Neonatal Perinatal Medicine (AAP SONPM) National Perinatal COVID-19 Registry.\n\nMethodsPAN-COVID (suspected or confirmed SARS-CoV-2 infection at any stage in pregnancy) and the AAP SONPM registry (positive maternal testing for SARS-CoV-2 from 14 days before delivery to 3 days after delivery) studies collected data on maternal, fetal, perinatal and neonatal outcomes. PAN-COVID results are presented as all inclusions and those with confirmed SARS-CoV-2 infection only.\n\nResultsWe report 4004 women in pregnancy affected by suspected or confirmed SARS-CoV-2 infection (1606 from PAN-COVID and 2398 from the AAP SONPM) from January 1st 2020 to July 25th 2020 (PAN-COVID) and August 8th (AAP SONPM). For obstetric outcomes in PAN-COVID and AAP SONPM, respectively, maternal death occurred in 0.5% and 0.17%, early neonatal death in 0.2% and 0.3%, and stillbirth in 0.50% and 0.65% of women. Delivery was pre-term (<37 weeks gestation) in 12% of all women in PAN-COVID, in 16.2% of those women with confirmed infection in PAN-COVID and 16.2% of women in AAP SONPM. Very preterm delivery (< 27 weeks gestation) occurred in 0.6% in PAN-COVID and 0.7% in AAP SONPM.\n\nNeonatal SARS-CoV-2 infection was reported in 0.8% of PAN-COVID all inclusions, 2.0% in PAN-COVID confirmed infections and 1.8% in the AAP SONPM study; the proportions of babies tested were 9.5%, 20.7% and 87.2% respectively.\n\nThe proportion of SGA babies was 8.2% in PAN-COVID all inclusions, 9.7% in PAN-COVID confirmed infection and 9.6% in AAP SONPM. Gestational age adjusted mean z-scores were -0.03 for PAN-COVID and -0.18 for AAP SONPM.\n\nConclusionsThe findings from the UK and US SARS-CoV-2 in pregnancy registries were remarkably concordant. Pre-term delivery affected a higher proportion of women in pregnancy than expected from historical and contemporaneous national data. The proportions of women affected by stillbirth, small for gestational age infants and early neonatal death were comparable to historical and contemporaneous UK and US data. Although maternal death was uncommon, the proportion was higher than expected from UK and US population data, likely explained by under-ascertainment of women affected by milder and asymptomatic infection in pregnancy. The data presented support strong guidance for enhanced precautions to prevent SARS-COV-2 infection in pregnancy, particularly in the context of increased risks of preterm delivery and maternal mortality, and for priority vaccination of women planning pregnancy.\n\nWhat is known about SARS-COV-2 infection in pregnancy and neonates?Cohort, population surveillance studies and living systematic reviews have included limited numbers of women in pregnancy affected by COVID-19 and report that most women and infants had good outcomes.\n\nWhat this study addsPreterm deliveries occurred in a high proportion of women participating in these two registries in comparison to contemporaneous and historical national data in the UK and US. The majority of preterm deliveries occurred late preterm (between 32+0 and 36+6 weeks gestation).\n\nSARS-COV-2 infection in pregnancy did not appear to be associated with a clinically significant effect on the rate of stillbirth, fetal growth, or neonatal outcomes.\n\nAlthough maternal death was uncommon, the proportion was higher than expected from UK and US population data, likely explained by under-ascertainment of women affected by milder and asymptomatic infection in pregnancy.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Maurizio Bartolucci",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Matteo Benelli",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Margherita Betti",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Sara Bicchi",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Luca Fedeli",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Federico Giannelli",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Donatella Aquilini",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Alessio Baldini",
-        "author_inst": "Azienda USL Toscana Centro"
-      },
-      {
-        "author_name": "Guglielmo Consales",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Edward Mullins",
+        "author_inst": "Imperial College"
       },
       {
-        "author_name": "Massimo Edoardo Di Natale",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Mark Hudak",
+        "author_inst": "University of Florida, AAP SONPM"
       },
       {
-        "author_name": "Pamela Lotti",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Jay Banerjee",
+        "author_inst": "Imperial College Healthcare NHS Trust"
       },
       {
-        "author_name": "Letizia Vannucchi",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Trace Getzlaff",
+        "author_inst": "University of Florida"
       },
       {
-        "author_name": "Michele Trezzi",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Julia Townson",
+        "author_inst": "Cardiff University"
       },
       {
-        "author_name": "Lorenzo Nicola Mazzoni",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Kimberly Barnette",
+        "author_inst": "University of Florida Jacksonville Physicians Inc."
       },
       {
-        "author_name": "Sandro Santini",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Rebecca Playle",
+        "author_inst": "Cardiff University"
       },
       {
-        "author_name": "Roberto Carpi",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "Tom Bourne",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Daniela Matarrese",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "- PAN-COVID-investigators",
+        "author_inst": "-"
       },
       {
-        "author_name": "Luca Bernardi",
-        "author_inst": "Azienda USL Toscana Centro"
+        "author_name": "- National Perinatal COVID-19 Registry Study Group",
+        "author_inst": "-"
       },
       {
-        "author_name": "Mario Mascalchi",
-        "author_inst": "University of Florence"
+        "author_name": "Christoph Lees",
+        "author_inst": "Imperial College London"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "radiology and imaging"
+    "category": "obstetrics and gynecology"
   },
   {
     "rel_doi": "10.1101/2021.01.04.20237578",
@@ -948948,55 +952175,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2021.01.07.21249381",
-    "rel_title": "Comparing the age and sex trajectories of SARS-CoV-2 morbidity with other respiratory pathogens points to potential immune mechanisms.",
+    "rel_doi": "10.1101/2021.01.07.21249392",
+    "rel_title": "Predicting severity of Covid-19 using standard laboratory parameters",
     "rel_date": "2021-01-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.07.21249381",
-    "rel_abs": "Comparing age and sex differences in SARS-CoV-2 hospitalization and mortality with influenza and other health outcomes opens the way to generating hypotheses as to the underlying mechanisms, building on the extraordinary advances in immunology and physiology that have occurred over the last year. Notable departures in health outcomes starting around puberty suggest that burdens associated with influenza and other causes are reduced relative to the two emergent coronaviruses over much of adult life. Two possible hypotheses could explain this: protective adaptive immunity for influenza and other infections, or greater sensitivity to immunosenescence in the coronaviruses. Comparison of sex differences suggest an important role for adaptive immunity; but immunosenescence might also be relevant, if males experience faster immunosenescence. Involvement of the renin-angiotensin-system in SARS-CoV-2 infection might drive high sensitivity to disruptions of homeostasis. Overall, these results highlight the long tail of vulnerability in the age profile relevant to the emergent coronaviruses, which more transmissible variants have the potential to uncover at the younger end of the scale, and aging populations will expose at the other end of the scale.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.07.21249392",
+    "rel_abs": "BackgroundMore than 1.6 million people have already deceased due to a COVID-19 infection making it a major public health concern. A prediction of severe courses can enhance treatment quality and thus lower fatality and morbidity rates. The use of laboratory parameters has recently been established for a prediction. However, laboratory parameters have rarely been used in combination to predict severe outcomes.\n\nMethodWe used a retrospective case-control design to analyze risk factors derived from laboratory parameters. Patients treated for COVID-19 at an hospital in Krefeld, Germany, from March to May 2020 were included (n =42). Patients were classified into two categories based on their outcome (Mild course vs. treatment in intensive care unit). Laboratory parameters were compared across severity categories using non-parametric statistic. Identified laboratory parameters were used in a logistic regression model. The model was replicated using a) clinical standardized parameters b) aggregated factors derived from a factor analysis.\n\nResultsPatients in intensive care unit showed elevated ALT, CRP and LDH levels, a higher leukocyte and neutrophile count, a higher neutrophile ratio and a lowered lymphocyte ratio. We were able to classify 95.1% of all cases correctly (96.6% of mild and 91.7% of severe cases, p<.001).\n\nConclusionA number of routinely collected laboratory parameters is associated with a severe outcome of COVID-19. The combination of these parameters provides a powerful tool in predicting severity and can enhance treatment effectiveness.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "C. Jessica E. Metcalf",
-        "author_inst": "Princeton University"
-      },
-      {
-        "author_name": "Juliette Paireau",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Megan ODriscoll",
-        "author_inst": "Department of Genetics, Cambridge University"
+        "author_name": "Thimo Buchmueller",
+        "author_inst": "Alexianer Krefeld GmbH"
       },
       {
-        "author_name": "Mathilde Pivette",
-        "author_inst": "Sante publique France, French national public health agency, Saint Maurice, France"
+        "author_name": "Ingmar Groening",
+        "author_inst": "Alexianer Krefeld GmbH"
       },
       {
-        "author_name": "Bruno Hubert",
-        "author_inst": "Sante publique France, French national public health agency, Saint Maurice, France"
-      },
-      {
-        "author_name": "Isabelle Pontais",
-        "author_inst": "Sante publique France, French national public health agency, Saint Maurice, France"
-      },
-      {
-        "author_name": "Derek Cummings",
-        "author_inst": "Department of Biology, University of Florida, Gainesville, USA"
-      },
-      {
-        "author_name": "Simon Cauchemez",
-        "author_inst": "Institut Pasteur, Paris"
-      },
-      {
-        "author_name": "Henrik Salje",
-        "author_inst": "Department of Biology, University of Florida, Gainesville, USA"
+        "author_name": "Ralf Ihl",
+        "author_inst": "Alexianer Krefeld GmbH"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "intensive care and critical care medicine"
   },
   {
     "rel_doi": "10.1101/2021.01.07.21249419",
@@ -950361,109 +953564,33 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2021.01.05.21249247",
-    "rel_title": "SARS-CoV-2 seroprevalence in the urban population of Qatar: An analysis of antibody testing on a sample of 112,941 individuals",
+    "rel_doi": "10.1101/2021.01.04.21249235",
+    "rel_title": "Machine Learning Forecast of Growth in COVID-19 Confirmed Infection Cases with Non-Pharmaceutical Interventions and Cultural Dimensions: Algorithm Development and Validation",
     "rel_date": "2021-01-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.05.21249247",
-    "rel_abs": "BackgroundQatar has experienced a large SARS-CoV-2 epidemic. Our first objective was to assess the proportion of the urban population that has been infected with SARS-CoV-2, by measuring the prevalence of detectable antibodies. Our second objective was to identify predictors for infection and for having higher antibody titers.\n\nMethodsResidual blood specimens from individuals receiving routine and other clinical care between May 12-September 9, 2020 were tested for anti-SARS-CoV-2 antibodies. Associations with seropositivity and higher antibody titers were identified through regression analyses. Probability weights were applied in deriving the epidemiological measures.\n\nResultsWe tested 112,941 individuals ([~]10% of Qatars urban population), of whom 51.6% were men and 66.0% were 20-49 years of age. Seropositivity was 13.3% (95% CI: 13.1-13.6%) and was significantly associated with sex, age, nationality, clinical-care type, and testing date. The proportion with higher antibody titers varied by age, nationality, clinical-care type, and testing date. There was a strong correlation between higher antibody titers and seroprevalence in each nationality, with a Pearson correlation coefficient of 0.85 (95% CI: 0.47-0.96), suggesting that higher antibody titers may indicate repeated exposure to the virus. The percentage of antibody-positive persons with prior PCR-confirmed diagnosis was 47.1% (95% CI: 46.1-48.2%), severity rate was 3.9% (95% CI: 3.7-4.2%), criticality rate was 1.3% (95% CI: 1.1-1.4%), and fatality rate was 0.3% (95% CI: 0.2-0.3%).\n\nConclusionsFewer than two in every 10 individuals in Qatars urban population had detectable antibodies against SARS-CoV-2 between May 12-September 9, 2020, suggesting that this population is still far from the herd immunity threshold and at risk from a subsequent epidemic wave.",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.04.21249235",
+    "rel_abs": "BackgroundNational governments have implemented non-pharmaceutical interventions to control and mitigate against the COVID-19 pandemic. A deep understanding of these interventions is required.\n\nObjectiveWe investigate the prediction of future daily national Confirmed Infection Growths - the percentage change in total cumulative cases across 14 days - using metrics representative of non-pharmaceutical interventions and cultural dimensions of each country.\n\nMethodsWe combine the OxCGRT dataset, Hofstedes cultural dimensions, and COVID-19 daily reported infection case numbers to train and evaluate five non-time series machine learning models in predicting Confirmed Infection Growth. We use three validation methods - in-distribution, out-of-distribution, and country-based cross-validation - for evaluation, each applicable to a different use case of the models.\n\nResultsOur results demonstrate high R2 values between the labels and predictions for the in-distribution, out-of-distribution, and country-based cross-validation methods (0.959, 0.513, and 0.574 respectively) using random forest and AdaBoost regression. While these models may be used to predict the Confirmed Infection Growth, the differing accuracies obtained from the three tasks suggest a strong influence of the use case.\n\nConclusionsThis work provides new considerations in using machine learning techniques with non-pharmaceutical interventions and cultural dimensions data for predicting the national growth of confirmed infections of COVID-19.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Peter V. Coyle",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Hiam Chemaitelly",
-        "author_inst": "Weill Cornell Medicine-Qatar, Doha, Qatar"
-      },
-      {
-        "author_name": "Mohamed Ali Ben Hadj Kacem",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Naema Hassan Abdulla Al Molawi",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Reham Awni El Kahlout",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Imtiaz Gilliani",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Nourah Younes",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Zaina Al Kanaani",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Abdullatif Al Khal",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Einas Al Kuwari",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Adeel A Butt",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Andrew Jeremijenko",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Anvar Hassan Kaleeckal",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Ali Nizar Latif",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Riyazuddin Mohammad Shaik",
-        "author_inst": "Hamad Medical Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Hanan F. Abdul Rahim",
-        "author_inst": "Qatar University, Doha, Qatar"
-      },
-      {
-        "author_name": "Gheyath K. Nasrallah",
-        "author_inst": "Qatar University, Doha, Qatar"
-      },
-      {
-        "author_name": "Hadi M. Yassine",
-        "author_inst": "Qatar University, Doha, Qatar"
-      },
-      {
-        "author_name": "Mohamed G. Al Kuwari",
-        "author_inst": "Primary Health Care Corporation, Doha, Qatar"
-      },
-      {
-        "author_name": "Hamad Eid Al Romaihi",
-        "author_inst": "Ministry of Public Health, Doha, Qatar"
+        "author_name": "Arnold YS Yeung",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Mohamed H. Al-Thani",
-        "author_inst": "Ministry of Public Health, Doha, Qatar"
+        "author_name": "Francois Roewer-Despres",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Roberto Bertollini",
-        "author_inst": "Ministry of Public Health, Doha, Qatar"
+        "author_name": "Laura Rosella",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Laith J Abu-Raddad",
-        "author_inst": "Weill Cornell Medicine-Qatar, Doha, Qatar"
+        "author_name": "Frank Rudzicz",
+        "author_inst": "University of Toronto"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -952207,31 +955334,31 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2021.01.06.425543",
-    "rel_title": "Heterogeneity versus the COVID-19 Pandemic",
+    "rel_doi": "10.1101/2021.01.06.425544",
+    "rel_title": "Complex Systems Analysis Informs on the Spread of COVID-19",
     "rel_date": "2021-01-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.06.425543",
-    "rel_abs": "In this paper, heterogeneity is formally defined, and its properties are explored. We define and distinguish observable versus non-observable heterogeneity. It is proposed that heterogeneity among the vulnerable is a significant factor in the contagion impact of COVID-19, as demonstrated with incidence rates on a Diamond Princess Cruise ship in February 2020. Given the nature of the disease, its heterogeneity and human social norms, pre-voyage and post-voyage quick testing procedures may become the new standard for cruise ship passengers and crew. The technological advances in testing available today would facilitate more humanistic treatment as compared to more archaic quarantine and isolation practices for all onboard ship. With quick testing, identification of those infected and thus not allowed to embark on a cruise or quarantining those disembarking and other mitigation strategies, the popular cruise adventure could be available safely again. Whatever the procedures implemented, the methodological purpose of this study should add valuable insight in the modeling of disease and specifically, the COVID-19 virus.",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.06.425544",
+    "rel_abs": "The non-linear progression of new infection numbers in a pandemic poses challenges to the evaluation of its management. The tools of complex systems research may aid in attaining information that would be difficult to extract with other means. To study the COVID-19 pandemic, we utilize the reported new cases per day for the globe, nine countries and six US states through October 2020. Fourier and univariate wavelet analyses inform on periodicity and extent of change. Evaluating time-lagged data sets of various lag lengths, we find that the autocorrelation function, average mutual information and box counting dimension represent good quantitative readouts for the progression of new infections. Bivariate wavelet analysis and return plots give indications of containment versus exacerbation. Homogeneity or heterogeneity in the population response, uptick versus suppression, and worsening or improving trends are discernible, in part by plotting various time lags in three dimensions. The analysis of epidemic or pandemic progression with the techniques available for observed (noisy) complex data can aid decision making in the public health response.",
     "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Ramalingam Shanmugam",
-        "author_inst": "Texas State University"
+        "author_name": "Xia Wang",
+        "author_inst": "University of Cincinnati"
       },
       {
-        "author_name": "Gerald Ledlow",
-        "author_inst": "University of Texas Health Science Center at Tyler: The University of Texas Health Science Center at Tyler"
+        "author_name": "Dorcas Washington",
+        "author_inst": "University of Cincinnati"
       },
       {
-        "author_name": "Karan  P. Singh",
-        "author_inst": "University of Texas Health Science Center Tyler"
+        "author_name": "Georg F. Weber",
+        "author_inst": "College of Pharmacy, University of Cincinnati Medical Center, 3225 Eden Avenue, Cincinnati, OH 45267-0004, USA"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "new results",
-    "category": "scientific communication and education"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2021.01.06.425542",
@@ -953445,59 +956572,103 @@
     "category": "radiology and imaging"
   },
   {
-    "rel_doi": "10.1101/2021.01.04.21249195",
-    "rel_title": "The incidence, characteristics and outcomes of pregnant women hospitalized with symptomatic and asymptomatic SARS-CoV-2 infection in the UK from March to September 2020: a national cohort study using the UK Obstetric Surveillance System (UKOSS)",
+    "rel_doi": "10.1101/2021.01.04.425336",
+    "rel_title": "SARS-CoV-2 susceptibility of cell lines and substrates commonly used in diagnosis and isolation of influenza and other viruses",
     "rel_date": "2021-01-05",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.04.21249195",
-    "rel_abs": "BackgroundEvidence on risk factors, incidence and impact of SARS-CoV-2 infection in pregnant mothers and their babies has rapidly expanded but there is a lack of population level data to inform accurate incidence rates and unbiased descriptions of characteristics and outcomes. The primary aim of this study was to describe the incidence, characteristics and outcomes of hospitalized pregnant women with symptomatic and asymptomatic SARS-CoV-2 in the UK compared to pregnant women without SARS-CoV-2 in order to inform future clinical guidance and management.\n\nMethods and FindingsWe conducted a national, prospective cohort study of all hospitalized pregnant women with confirmed SARS-CoV-2 from 1st March 2020 to 31st August 2020 using the UK Obstetric Surveillance System (UKOSS) across all 194 hospitals in the UK with a consultant-led maternity unit. Incidence was estimated using the latest national maternity data. Overall, 1148 hospitalized women had confirmed SARS-CoV-2 in pregnancy, 63% of which were symptomatic. Therefore, the estimated incidence of hospitalization with symptomatic SARS-CoV-2 was 2.0 per 1000 maternities (95% CI 1.9-2.2) and for asymptomatic SARS-CoV-2 was 1.2 per 1000 maternities (95% CI 1.1-1.4). Compared to pregnant women without SARS-CoV-2, women hospitalized with symptomatic SARS-CoV-2 were more likely to be overweight or obese (adjusted OR 1.86, 95% CI 1.39-2.48 and aOR 2.07, 95% CI 1.53-2.29 respectively), to be of Black, Asian or Other minority ethnic group (aOR 6.24, 95% CI 3.93-9.90, aOR 4.36, 95% CI 3.19-5.95 and aOR 12.95, 95% CI 4.93-34.01 respectively), and to have a relevant medical comorbidity (aOR 1.83, 95% CI 1.32-2.54). Compared to pregnant women without SARS-CoV-2, hospitalized pregnant women with symptomatic SARS-CoV-2 were more likely to be admitted to intensive care (aOR 57.67, 95% CI 7.80-426.70) but the absolute risk of poor outcomes was low. Cesarean births and neonatal unit admission were increased regardless of symptom status (symptomatic aOR 2.60, 95% CI 1.97-3.42 and aOR 3.08, 95% CI 1.99-4.77 respectively; asymptomatic aOR 2.02, 95% CI 1.52-2.70 and aOR 1.84, 95% 1.12-3.03 respectively). Iatrogenic preterm births were more common in women with symptomatic SARS-CoV-2 (aOR 11.43, 95% CI 5.07-25.75). The risks of stillbirth or neonatal death were not significantly increased, regardless of symptom status but numbers were small. The limitations of this study include the restriction to women hospitalized with SARS-CoV-2, who may by nature of their admission have been at greater risk of adverse outcome.\n\nConclusionsWe have identified factors that increase the risk of symptomatic and asymptomatic SARS-CoV-2 in pregnancy. The increased risks of cesarean and iatrogenic preterm birth provide clear evidence of the indirect impact of SARS-CoV-2 on mothers and maternity care in high income settings. Clinicians can be reassured that the majority of women do not experience severe complications of SARS-CoV-2 in pregnancy and women with mild disease can be discharged to continue their pregnancy safely.",
-    "rel_num_authors": 10,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.04.425336",
+    "rel_abs": "Coinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other viruses is inevitable as the COVID-19 pandemic continues. This study aimed to evaluate cell lines commonly used in virus diagnosis and isolation for their susceptibility to SARS-CoV-2. While multiple kidney cell lines from monkeys were susceptible and permissive to SARS-CoV-2, many cell types derived from human, dog, mink, cat, mouse, or chicken were not. Analysis of MDCK cells, which are most commonly used for surveillance and study of influenza viruses, demonstrated that they were insusceptible to SARS-CoV-2 and that the cellular barrier to productive infection was due to low expression level of the angiotensin converting enzyme 2 (ACE2) receptor and lower receptor affinity to SARS-CoV-2 spike, which could be overcome by over-expression of canine ACE2 in trans. Moreover, SARS-CoV-2 cell tropism did not appear to be affected by a D614G mutation in the spike protein.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Nicola Vousden",
-        "author_inst": "University of Oxford"
+        "author_name": "Li Wang",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
       },
       {
-        "author_name": "Kathryn Bunch",
-        "author_inst": "University of Oxford"
+        "author_name": "Xiaoyu Fan",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
       },
       {
-        "author_name": "Edward Morris",
-        "author_inst": "Royal College of Obstetricians and Gynaecologists"
+        "author_name": "Gaston Bonenfant",
+        "author_inst": "Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA"
       },
       {
-        "author_name": "Nigel Simpson",
-        "author_inst": "University of Leeds"
+        "author_name": "Dan Cui",
+        "author_inst": "Battelle Memorial Institute, Atlanta, Georgia, USA"
       },
       {
-        "author_name": "Christopher Gale",
-        "author_inst": "Imperial College London"
+        "author_name": "Jaber Hossain",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
       },
       {
-        "author_name": "Patrick O'Brien",
-        "author_inst": "University College London"
+        "author_name": "Nannan Jiang",
+        "author_inst": "Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA"
       },
       {
-        "author_name": "Maria Quigley",
-        "author_inst": "University of Oxford"
+        "author_name": "Gloria Larson",
+        "author_inst": "Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA"
       },
       {
-        "author_name": "Peter Brocklehurst",
-        "author_inst": "University College London"
+        "author_name": "Michael Currier",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
       },
       {
-        "author_name": "Jennifer J Kurinczuk",
-        "author_inst": "University of Oxford"
+        "author_name": "Jimma Liddell",
+        "author_inst": "Battelle Memorial Institute, Atlanta, Georgia, USA"
       },
       {
-        "author_name": "Marian Knight",
-        "author_inst": "University of Oxford"
+        "author_name": "Malania Wilson",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Azaibi Tamin",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Jennifer Harcourt",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Jessica Ciomperlik-Patton",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Hong Pang",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Naomi Dybdahl-Sissoko",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Ray Campagnoli",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Pei-Yong Shi",
+        "author_inst": "University of Texas Medical Branch, Galveston, Texas, USA"
+      },
+      {
+        "author_name": "John R Barnes",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Natalie J. Thornburg",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "David E Wentworth",
+        "author_inst": "Centers for Disease Control and Prevention, Atlanta, Georgia, USA"
+      },
+      {
+        "author_name": "Bin Zhou",
+        "author_inst": "Centers for Disease Control and Prevention"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "obstetrics and gynecology"
+    "license": "cc0",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2021.01.05.425331",
@@ -955063,85 +958234,33 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.30.20248890",
-    "rel_title": "Detection of SARS-CoV-2 in the air from hospitals and closed rooms occupied by COVID-19 patients",
+    "rel_doi": "10.1101/2020.12.23.20248803",
+    "rel_title": "Clinical diagnosis of COVID-19: a prompt, feasible, and sensitive diagnostic tool for COVID-19 based on a 1,757-patient cohort (The AndroCoV Clinical Scoring for COVID-19 diagnosis).",
     "rel_date": "2021-01-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.30.20248890",
-    "rel_abs": "To understand air transmission characteristics of SARS-CoV-2 and risks for health care personnel and visitors to hospitals, we analyzed air samples collected from various enclosures in hospitals at Hyderabad and Mohali and performed closed room experiments with COVID-19 positive individuals. We collected 64 air samples from COVID and non-COVID areas of various hospitals and 17 samples from closed rooms occupied by COVID patients. 4 samples from COVID care areas were positive for SARS-CoV-2 with no obvious predilection towards ICU/non-ICU areas in the hospital samples. In the closed room experiments, where one or more COVID-19 patients spent a short duration of time, one sample - collected immediately after the departure of three symptomatic patients from the room - was positive. Our results indicate that the chance of picking up SARS-CoV-2 in the air is directly related to a number of COVID positive cases in the room, their symptomatic status, and the duration of exposure and that the demarcation of hospital areas into COVID and non-COVID areas is a successful strategy to prevent cross infections. In neutral environmental conditions, the virus does not seem to spread farther away from the patients, especially if they are asymptomatic, giving an objective evidence for the effectiveness of physical distancing in curbing the spread of the epidemic.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248803",
+    "rel_abs": "ImportanceIn the COVID-19 pandemic, a limiting barrier for more successful approaches to COVID-19 is the lack of appropriate timing for its diagnosis, during the viral replication stage, when antiviral approaches could demonstrate efficacy, precluding progression to severe stages. Three major reasons that hamper the diagnosis earlier in the disease are the unspecific and mild symptoms in the first stage, the cost- and time-limitations of the rtPCR-SARS-CoV-2, and the insufficient sensitivity of this test as desired for screening purposes during the pandemic. More sensitive and earlier methods of COVID-19 detection should be considered as key for breakthrough changes in the disease course and response to specific therapeutic strategies. Our objective was to propose a clinical scoring for the diagnosis of COVID-19 (The AndroCoV Clinical Scoring for COVID-19 Diagnosis) that has been validated in a large population sample, aiming to encourage the management of patients with high pre-clinical likelihood of presenting COVID-19, at least during the pandemics, independent of a rtPCR-SARS-COV-2 test.\n\nMaterials and methodsThis is a compounded retrospective and prospective analysis of clinical data prospectively collected from the Pre-AndroCoV and AndroCov Trials that resulted in a clinical scoring for COVID-19 diagnosis based on likelihood of presenting COVID-19 according to the number of symptoms, presence of anosmia, and known positive household contact, in a variety of combinations of scoring criteria, aiming to the detect scorings that provided the highest pre-test probability and accuracy. Sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and accuracy were calculated for subjects screened in two different periods and altogether, for females, males, and both, in a total of nine different scenarios, for combinations between one, two, or three or more symptoms, or presence of anosmia in subjects without known positive household contacts, and no symptoms, one, two, or three or more symptoms, or presence of anosmia or ageusia in subjects with known positive household contacts.\n\nResults1,757 patients were screened for COVID-19. Among the multiple combinations, requiring two or more symptoms with or without anosmia or ageusia for subjects without known contact and one or more symptoms with or without anosmia or ageusia with known positive contacts presented the highest accuracy (80.4%), and higher pretest probability and accuracy than virtually all rtPCR-SARS-CoV-2 commercially available kit tests.\n\nConclusionThe AndroCoV Clinical Scoring for COVID-19 Diagnosis was demonstrated to be a feasible, quick, inexpensive and sensitive diagnostic tool for clinical diagnosis of COVID-19. A clinical diagnosis of COVID-19 should avoid delays and missed diagnosis, and reduce costs, and should therefore be recommended as a first-line option for COVID-19 diagnosis for public health policies, at least while SARS-CoV-2 is the prevailing circulating virus.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSIs a clinical diagnosis of COVID-19 sensitive, accurate, and feasible?\n\nFindingsThe present analysis of a 1,757-subject cohort of the AndroCoV trials demonstrated that clinical scoring for COVID-19 diagnosis can deliver a more sensitive and prompter diagnosis than the current gold-standard diagnostic method, rtPCR-SARS-CoV-2, with an accuracy above 80%.\n\nMeaningA clinical diagnosis of COVID-19 avoids missed diagnosis due to insufficient sensitivity or incorrect timing of the performance of rtPCR-SARS-CoV-2, reduces costs, avoid delays on specific managements, and allows the testing of potentially effective antiviral therapeutic approaches that should work if administered in the early stage of COVID-19",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Shivranjani Moharir",
-        "author_inst": "CSIR- Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India"
-      },
-      {
-        "author_name": "Sharat Sharath Chandra",
-        "author_inst": "CSIR- Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India"
-      },
-      {
-        "author_name": "Arushi Goel",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
-      },
-      {
-        "author_name": "Bhuwaneshwar Thakur",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
-      },
-      {
-        "author_name": "Gurpreet Singh Bhalla",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
-      },
-      {
-        "author_name": "Dinesh Kumar",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
-      },
-      {
-        "author_name": "Digvijay Singh Naruka",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
-      },
-      {
-        "author_name": "Ashwani Kumar",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
-      },
-      {
-        "author_name": "Amit Tuli",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
-      },
-      {
-        "author_name": "Swathi Suravaram",
-        "author_inst": "ESI Hospital and Medical College, Hyderabad, India"
-      },
-      {
-        "author_name": "Thrilok Chander Bingi",
-        "author_inst": "COVID-19 nodal centre, Hyderabad, India"
-      },
-      {
-        "author_name": "M Srinivas",
-        "author_inst": "ESI Hospital and Medical College, Hyderabad, India"
-      },
-      {
-        "author_name": "Rajarao Mesipogu",
-        "author_inst": "COVID-19 nodal centre, Hyderabad, India"
-      },
-      {
-        "author_name": "Krishna Reddy",
-        "author_inst": "Durgabai Deshmukh Hospital, Hyderabad, India"
+        "author_name": "Flavio A Cadegiani",
+        "author_inst": "Federal University of Sao Paulo"
       },
       {
-        "author_name": "Sanjeev Khosla",
-        "author_inst": "CSIR- Institute of Microbial Technology (CSIR-IMTech), Chandigarh, India"
+        "author_name": "John A McCoy",
+        "author_inst": "Applied Biology, Inc."
       },
       {
-        "author_name": "Karthik Bharadwaj Tallapaka",
-        "author_inst": "CSIR- Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India"
+        "author_name": "Carlos Gustavo Wambier",
+        "author_inst": "Warren Alpert Medical School of Brown University"
       },
       {
-        "author_name": "Rakesh K Mishra",
-        "author_inst": "CSIR- Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India"
+        "author_name": "Andy Goren",
+        "author_inst": "Applied Biology Inc."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -956417,53 +959536,29 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.12.31.20249088",
-    "rel_title": "Stages of COVID-19 pandemic and paths to herd immunity by vaccination: dynamical model comparing Austria, Luxembourg and Sweden",
+    "rel_doi": "10.1101/2020.12.30.20249066",
+    "rel_title": "Need of care in interpreting Google Trends-based COVID-19 infodemiological study results: potential risk of false-positivity",
     "rel_date": "2021-01-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.31.20249088",
-    "rel_abs": "BackgroundWorldwide more than 72 million people have been infected and 1.6 million died with SARS-CoV-2 by 15th December 2020. Non-pharmaceutical interventions which decrease social interaction have been implemented to reduce the spread of SARS-CoV-2 and to mitigate stress on healthcare systems and prevent deaths. The pandemic has been tackled with disparate strategies by distinct countries resulting in different epidemic dynamics. However, with vaccines now becoming available, the current urgent open question is how the interplay between vaccination strategies and social interaction will shape the pandemic in the next months.\n\nMethodsTo address this question, we developed an extended Susceptible-Exposed-Infectious-Removed (SEIR) model including social interaction, undetected cases and the progression of patients trough hospitals, intensive care units (ICUs) and death. We calibrated our model to data of Luxem-bourg, Austria and Sweden, until 15th December 2020. We incorporated the effect of vaccination to investigate under which conditions herd immunity would be achievable in 2021.\n\nResultsThe model reveals that Sweden has the highest fraction of undetected cases, Luxembourg displays the highest fraction of infected population, and all three countries are far from herd immunity as of December 2020. The model quantifies the level of social interactions, and allows to assess the level which would keep Reff (t) below 1. In December 2020, this level is around 1/3 of what it was before the pandemic for all the three countries. The model allows to estimate the vaccination rate needed for herd immunity and shows that 2700 vaccinations/day are needed in Luxembourg to reach it by mid of April and 45,000 for Austria and Sweden. The model estimates that vaccinating the whole countrys population within 1 year could lead to herd immunity by July in Luxembourg and by August in Austria and Sweden.\n\nConclusionThe model allows to shed light on the dynamics of the epidemics in different waves and countries. Our results emphasize that vaccination will help considerably but not immediately and therefore social measures will remain important for several months before they can be fully alleviated.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.30.20249066",
+    "rel_abs": "ObjectiveGoogle Trends (GT) is being used as an epidemiological tool to study coronavirus disease (COVID-19) by identifying keywords in search trends that are predictive for the COVID-19 epidemiological burden. However, many of the earlier GT-based studies include potential statistical fallacies by measuring the correlation between non-stationary time sequences without adjusting for multiple comparisons or the confounding of media coverage, leading to concerns about the increased risk of obtaining false-positive results. In this study, we aimed to apply statistically more favorable methods to validate the earlier GT-based COVID-19 study results.\n\nMethodsWe extracted the relative GT search volume for keywords associated with COVID-19 symptoms, and evaluated their Granger-causality to weekly COVID-19 positivity in eight English-speaking countries and Japan. In addition, the impact of media coverage on keywords with significant Granger-causality was further evaluated using Japanese regional data.\n\nResultsOur Granger causality-based approach largely decreased (by up to approximately one-third) the number of keywords identified as having a significant temporal relationship with the COVID-19 trend when compared to those identified by the Pearson correlation-based approach. \"Sense of smell\" and \"loss of smell\" were the most reliable GT keywords across all the evaluated countries; however, when adjusted with their media coverage, these keyword trends did not Granger-cause the COVID-19 positivity trends (in Japan).\n\nConclusionOur results suggest that some of the search keywords reported as candidate predictive measures in earlier GT-based COVID-19 studies may potentially be unreliable; therefore, caution is necessary when interpreting published GT-based study results.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Francoise Kemp",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
-      },
-      {
-        "author_name": "Daniele Proverbio",
-        "author_inst": "University of Luxembourg"
-      },
-      {
-        "author_name": "Atte Aalto",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
-      },
-      {
-        "author_name": "Laurent Mombaerts",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
-      },
-      {
-        "author_name": "Aymeric Fouquier d Herouel",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
-      },
-      {
-        "author_name": "Andreas Husch",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
-      },
-      {
-        "author_name": "Christophe Ley",
-        "author_inst": "University of Ghent"
+        "author_name": "Kenichiro Sato",
+        "author_inst": "University of Tokyo Hospital"
       },
       {
-        "author_name": "Jorge Goncalves",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
+        "author_name": "Tatsuo Mano",
+        "author_inst": "University of Tokyo Hospital"
       },
       {
-        "author_name": "Alexander Skupin",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
+        "author_name": "Atsushi Iwata",
+        "author_inst": "Tokyo Metropolitan Geriatric Medical Center Hospital"
       },
       {
-        "author_name": "Stefano Magni",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg"
+        "author_name": "Tatsushi Toda",
+        "author_inst": "University of Tokyo Hospital"
       }
     ],
     "version": "1",
@@ -957979,79 +961074,155 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.12.26.20248878",
-    "rel_title": "Direct detection of SARS-CoV-2 RNA using high-contrast pH-sensitive dyes",
+    "rel_doi": "10.1101/2020.12.31.424987",
+    "rel_title": "Paired heavy and light chain signatures contribute to potent SARS-CoV-2 neutralization in public antibody responses",
     "rel_date": "2021-01-03",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.26.20248878",
-    "rel_abs": "The worldwide COVID-19 pandemic has had devastating effects on health, healthcare infrastructure, social structure, and economics. One of the limiting factors in containing the spread of this virus has been the lack of widespread availability of fast, inexpensive, and reliable methods for testing of individuals. Frequent screening for infected and often asymptomatic people is a cornerstone of pandemic management plans. Here, we introduce two pH sensitive  LAMPshade dyes as novel readouts in an isothermal RT-LAMP amplification assay for SARS-CoV-2 RNA. The resulting JaneliaLAMP (jLAMP) assay is robust, simple, inexpensive, has low technical requirements and we describe its use and performance in direct testing of contrived and clinical samples without RNA extraction.",
-    "rel_num_authors": 15,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.31.424987",
+    "rel_abs": "Understanding protective mechanisms of antibody recognition can inform vaccine and therapeutic strategies against SARS-CoV-2. We discovered a new antibody, 910-30, that targets the SARS-CoV-2 ACE2 receptor binding site as a member of a public antibody response encoded by IGHV3-53/IGHV3-66 genes. We performed sequence and structural analyses to explore how antibody features correlate with SARS-CoV-2 neutralization. Cryo-EM structures of 910-30 bound to the SARS-CoV-2 spike trimer revealed its binding interactions and ability to disassemble spike. Despite heavy chain sequence similarity, biophysical analyses of IGHV3-53/3-66 antibodies highlighted the importance of native heavy:light pairings for ACE2 binding competition and for SARS-CoV-2 neutralization. We defined paired heavy:light sequence signatures and determined antibody precursor prevalence to be ~1 in 44,000 human B cells, consistent with public antibody identification in several convalescent COVID-19 patients. These data reveal key structural and functional neutralization features in the IGHV3-53/3-66 public antibody class to accelerate antibody-based medical interventions against SARS-CoV-2.\n\nHighlightsO_LIA molecular study of IGHV3-53/3-66 public antibody responses reveals critical heavy and light chain features for potent neutralization\nC_LIO_LICryo-EM analyses detail the structure of a novel public antibody class member, antibody 910-30, in complex with SARS-CoV-2 spike trimer\nC_LIO_LICryo-EM data reveal that 910-30 can both bind assembled trimer and can disassemble the SARS-CoV-2 spike\nC_LIO_LISequence-structure-function signatures defined for IGHV3-53/3-66 class antibodies including both heavy and light chains\nC_LIO_LIIGHV3-53/3-66 class precursors have a prevalence of 1:44,000 B cells in healthy human antibody repertoires\nC_LI",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Timothy A Brown",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Bailey B Banach",
+        "author_inst": "Bioengineering Graduate Program, University of Kansas, Lawrence, KS 66045, USA."
       },
       {
-        "author_name": "Katherine S. Schaefer",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Gabriele Cerutti",
+        "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Zuckerman Mind Brain Behavior Institute, Columbia University,"
       },
       {
-        "author_name": "Arthur Tsang",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Ahmed S Fahad",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
       },
       {
-        "author_name": "Hyun Ah Yi",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Chen-Hsiang Shen",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA."
       },
       {
-        "author_name": "Jonathan B. Grimm",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Matheus Oliveira de Souza",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
       },
       {
-        "author_name": "Andrew L. Lemire",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Phinikoula S Katsamba",
+        "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Zuckerman Mind Brain Behavior Institute, Columbia University,"
       },
       {
-        "author_name": "Fadi M. Jradi",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Yaroslav Tsybovsky",
+        "author_inst": "Electron Microscopy Laboratory, Cancer Research Technology Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederi"
       },
       {
-        "author_name": "Charles Kim",
-        "author_inst": "Sensei Biotherapeutics"
+        "author_name": "Pengfei Wang",
+        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA."
       },
       {
-        "author_name": "Kevin McGowan",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Manoj S Nair",
+        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA."
       },
       {
-        "author_name": "Kimberly Ritola",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Yaoxing Huang",
+        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA."
       },
       {
-        "author_name": "Derek T Armstrong",
-        "author_inst": "Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine"
+        "author_name": "Irene M Francino Urdaniz",
+        "author_inst": "Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, 80305, USA."
       },
       {
-        "author_name": "Heba H. Mostafa",
-        "author_inst": "Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine"
+        "author_name": "Paul J Steiner",
+        "author_inst": "Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, 80305, USA."
       },
       {
-        "author_name": "Wyatt Korff",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Matias Gutierrez-Gonzalez",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
       },
       {
-        "author_name": "Ronald D. Vale",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Lihong Liu",
+        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA."
+      },
+      {
+        "author_name": "Sheila N Lopez Acevedo",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
+      },
+      {
+        "author_name": "Alexandra Nazzari",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA."
       },
       {
-        "author_name": "Luke D Lavis",
-        "author_inst": "HHMI Janelia Research Campus"
+        "author_name": "Jacy R Wolfe",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
+      },
+      {
+        "author_name": "Yang Luo",
+        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA."
+      },
+      {
+        "author_name": "Adam S Olia",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA."
+      },
+      {
+        "author_name": "I-Ting Teng",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA."
+      },
+      {
+        "author_name": "Jian Yu",
+        "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Aaron Diamond AIDS Research Center, Columbia University Vagel"
+      },
+      {
+        "author_name": "Tongqing Zhou",
+        "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA."
+      },
+      {
+        "author_name": "Eswar R Reddem",
+        "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Zuckerman Mind Brain Behavior Institute, Columbia University,"
+      },
+      {
+        "author_name": "Jude Bimela",
+        "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Zuckerman Mind Brain Behavior Institute, Columbia University,"
+      },
+      {
+        "author_name": "Xiaoli Pan",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
+      },
+      {
+        "author_name": "Bharat Madan",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
+      },
+      {
+        "author_name": "Amy D Laflin",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
+      },
+      {
+        "author_name": "Rajani Nimrania",
+        "author_inst": "Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045, USA."
+      },
+      {
+        "author_name": "Kwon-Tung Yuen",
+        "author_inst": "State Key Laboratory for Emerging Infectious Diseases, Department of Microbiology, Carol Yu Centre for Infection, Li Ka Shing Faculty of Medicine, The Universit"
+      },
+      {
+        "author_name": "Timothy A Whitehead",
+        "author_inst": "Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, 80305, USA."
+      },
+      {
+        "author_name": "David D Ho",
+        "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, USA."
+      },
+      {
+        "author_name": "Peter D Kwong",
+        "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Vaccine Research Center, National Institute of Allergy and In"
+      },
+      {
+        "author_name": "Lawrence Shapiro",
+        "author_inst": "Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. Aaron Diamond AIDS Research Center, Columbia University Vagel"
+      },
+      {
+        "author_name": "Brandon J DeKosky",
+        "author_inst": "Bioengineering Graduate Program, University of Kansas, Lawrence, KS 66045, USA. Department of Pharmaceutical Chemistry, University of Kansas, Lawrence, KS 66045"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.12.31.424729",
@@ -959573,43 +962744,31 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.12.29.424728",
-    "rel_title": "In vitro Targeting of Transcription Factors to Control the Cytokine Release Syndrome in COVID-19",
+    "rel_doi": "10.1101/2020.12.30.424801",
+    "rel_title": "Pharmacophore-based peptide biologics neutralize SARS-CoV-2 S1 and deter S1-ACE2 interaction in vitro",
     "rel_date": "2020-12-30",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.29.424728",
-    "rel_abs": "Treatment of the cytokine release syndrome (CRS) has become an important part of rescuing hospitalized COVID-19 patients. Here, we systematically explored the transcriptional regulators of inflammatory cytokines involved in the COVID-19 CRS to identify candidate transcription factors (TFs) for therapeutic targeting using approved drugs. We integrated a resource of TF-cytokine gene interactions with single-cell RNA-seq expression data from bronchoalveolar lavage fluid cells of COVID-19 patients. We found 581 significantly correlated interactions, between 95 TFs and 16 cytokines upregulated in the COVID-19 patients, that may contribute to pathogenesis of the disease. Among these, we identified 19 TFs that are targets of FDA approved drugs. We investigated the potential therapeutic effect of 10 drugs and 25 drug combinations on inflammatory cytokine production in peripheral blood mononuclear cells, which revealed two drugs that inhibited cytokine production and numerous combinations that show synergistic efficacy in downregulating cytokine production. Further studies of these candidate repurposable drugs could lead to a therapeutic regimen to treat the CRS in COVID-19 patients.",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.30.424801",
+    "rel_abs": "Effective therapeutics and stable vaccine are the urgent need of the day to combat COVID-19 pandemic. SARS-CoV-2 spike protein has a pivotal role in cell-entry and host immune response, thus regarded as potential drug- and vaccine-target. As the virus utilizes the S1 domain of spike to initiate cell-attachment and S2 domain for membrane fusion, several attempts have been made to design viral-receptor and viral-fusion blockers. Here, by deploying interactive structure-based design and pharmacophore-based approaches, we designed short and stable peptide-biologics i.e. CoV-spike-neutralizing peptides (CSNPs) including CSNP1, CSNP2, CSNP3, CSNP4. We could demonstrate in cell culture experiments that CSNP2 binds to S1 at submicromolar concentration and abrogates the S1-hACE2 interaction. CSNP3, a modified and downsized form of CSNP2, could neither interfere with the S1-hACE2 interaction nor bind to S1. CSNP4 exhibited dose-dependent binding to both S1 and hACE2 and abolished the S1-hACE2 interaction in vitro. CSNP4 possibly enhance the mAb-based S1 neutralization by limiting the spontaneous movement of spike receptor-binding domain (RBD), whereas CSNP2 allowed RBD-mAb binding without any steric hindrance. Taken together, we suggest that CSNP2 and CSNP4 are potent and stable candidate peptides that can neutralize the SARS-CoV-2 spike and possibly pose the virus to host immune surveillance.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Clarissa S Santoso",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Zhaorong Li",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Jaice T Rottenberg",
-        "author_inst": "Boston University"
-      },
-      {
-        "author_name": "Xing Liu",
-        "author_inst": "Boston University"
+        "author_name": "Hyun Goo Woo",
+        "author_inst": "Ajou University"
       },
       {
-        "author_name": "Vivian X Shen",
-        "author_inst": "Boston University"
+        "author_name": "Masaud Shah",
+        "author_inst": "Dept. Physiology. Biomedical School, Ajou University"
       },
       {
-        "author_name": "Juan I Fuxman Bass",
-        "author_inst": "Boston University"
+        "author_name": "Sung Ung Moon",
+        "author_inst": "Ajou University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc",
     "type": "new results",
-    "category": "immunology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2020.12.29.424779",
@@ -961258,167 +964417,47 @@
     "category": "neuroscience"
   },
   {
-    "rel_doi": "10.1101/2020.12.28.424622",
-    "rel_title": "Landscapes and dynamic diversifications of B-cell receptor repertoires in COVID-19 patients",
+    "rel_doi": "10.1101/2020.12.29.424682",
+    "rel_title": "ACE2 peptide fragment interacts with several sites on the SARS-CoV-2 spike protein S1",
     "rel_date": "2020-12-29",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.28.424622",
-    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the pandemic of coronavirus disease 2019 (COVID-19). Great international efforts have been put into the development of prophylactic vaccines and neutralizing antibodies. However, the knowledge about the B cell immune response induced by the SARS-CoV-2 virus is still limited. Here, we report a comprehensive characterization of the dynamics of immunoglobin heavy chain (IGH) repertoire in COVID-19 patients. By using next-generation sequencing technology, we examined the temporal changes in the landscape of the patients immunological status, and found dramatic changes in the IGH within the patients immune system after the onset of COVID-19 symptoms. Although different patients have distinct immune responses to SARS-CoV-2 infection, by employing clonotype overlap, lineage expansion and clonotype network analyses, we observed a higher clonotype overlap and substantial lineage expansion of B cell clones during 2-3 weeks of illness, which is of great importance to B-cell immune responses. Meanwhile, for preferences of V gene usage during SARS-CoV-2 infection, IGHV3-74 and IGHV4-34 and IGHV4-39 in COVID-19 patients were more abundant than that of healthy controls. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic development as well as mechanistic research.",
-    "rel_num_authors": 37,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.29.424682",
+    "rel_abs": "The influence of the peptide QAKTFLDKFNHEAEDLFYQ on the kinetics of the SARS-CoV-2 spike protein S1 binding to angiotensin-converting enzyme 2(ACE2) was studied to model the interaction of the virus with its host cell. This peptide corresponds to the sequence 24-42 of the ACE2 1 domain, which is the binding site for the S1 protein. The on-rate and off-rate of S1-ACE2 complex formation were measured in the presence of various peptide concentrations using Bio-Layer Interferometry (BLI). The formation of the S1-ACE2 complex was inhibited when the S1 protein was preincubated with the peptide, however, no significant inhibitory effect was observed in the absence of preincubation. Dissociation kinetics revealed that the peptide remained bound to the S1-ACE2 complex and stabilized this complex. Computational mapping of the S1 protein surface for peptide binding revealed two additional sites, located at some distance from the receptor binding domain (RBD) of S1. These additional binding sites affect the interaction between the peptide, the S1 protein, and ACE2.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Haitao Xiang",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Yingze Zhao",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Xinyang Li",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Peipei Liu",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Longlong Wang",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Meiniang Wang",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Lei Tian",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Haixi Sun",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Wei Zhang",
-        "author_inst": "Department of Computer Science, City University of Hong Kong"
-      },
-      {
-        "author_name": "Ziqian Xu",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Beiwei Ye",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Xiaoju Yuan",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Pengyan Wang",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Ning Zhang",
-        "author_inst": "CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Yuhuan Gong",
-        "author_inst": "CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Chengrong Bian",
-        "author_inst": "5th Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases"
-      },
-      {
-        "author_name": "Zhaohai Wang",
-        "author_inst": "5th Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases"
-      },
-      {
-        "author_name": "Linxiang Yu",
-        "author_inst": "5th Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases"
-      },
-      {
-        "author_name": "Jin Yan",
-        "author_inst": "5th Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases"
-      },
-      {
-        "author_name": "Fanping Meng",
-        "author_inst": "5th Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases"
-      },
-      {
-        "author_name": "Changqing Bai",
-        "author_inst": "5th Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases"
-      },
-      {
-        "author_name": "Xiaoshan Wang",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Xiaopan Liu",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Kai Gao",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Liang Wu",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Longqi F. Liu",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Ying Gu",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Yuhai J. Bi",
-        "author_inst": "CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Yi Shi",
-        "author_inst": "CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Shaogeng Zhang",
-        "author_inst": "The Fifth Medical Center of PLA General Hospital, National Clinical Research Center for Infectious Diseases"
-      },
-      {
-        "author_name": "Chen Zhu",
-        "author_inst": "The Fifth Medical Center of PLA General Hospital, National Clinical Research Center for Infectious Diseases"
+        "author_name": "Aleksei Kuznetsov",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Xun Xu",
-        "author_inst": "BGI-Shenzhen"
+        "author_name": "Piret Arukuusk",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Guizhen Wu",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
+        "author_name": "Heleri H\u00e4rk",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "George Gao",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
+        "author_name": "Erkki Juronen",
+        "author_inst": "Icosagen AS, Tartu"
       },
       {
-        "author_name": "Naibo Yang",
-        "author_inst": "BGI-Shenzhen"
+        "author_name": "\u00dclo Langel",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "William Liu",
-        "author_inst": "National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention"
+        "author_name": "Mart Ustav",
+        "author_inst": "University of Tartu"
       },
       {
-        "author_name": "Penghui Yang",
-        "author_inst": "5th Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases"
+        "author_name": "Jaak J\u00e4rv",
+        "author_inst": "University of Tartu"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "immunology"
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2020.12.28.424630",
@@ -963115,81 +966154,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.23.20248444",
-    "rel_title": "Association between Use of Qingfei Paidu Tang and Mortality in Hospitalized Patients with COVID-19: A national retrospective registry study",
+    "rel_doi": "10.1101/2020.12.23.20248784",
+    "rel_title": "The importance of continued non-pharmaceutical interventions during the upcoming SARS-COV-2 vaccination campaign",
     "rel_date": "2020-12-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248444",
-    "rel_abs": "BackgroundQingfei Paidu Tang (QPT), a formula of traditional Chinese medicine, which was suggested to be able to ease symptoms in patients with Coronavirus Disease 2019 (COVID-19), has been recommended by clinical guidelines and widely used to treat COVID-19 in China. However, whether it decreases mortality remains unknown.\n\nPurposeWe aimed to explore the association between QPT use and in-hospital mortality among patients hospitalized for COVID-19.\n\nStudy designA retrospective study based on a real-world database was conducted.\n\nMethodsWe identified patients consecutively hospitalized with COVID-19 in 15 hospitals from a national retrospective registry in China, from January through May 2020. Data on patients characteristics, treatments, and outcomes were extracted from the electronic medical records. The association of QPT use with mortality was evaluated using Cox proportional hazards models based on propensity score analysis.\n\nResultsOf the 8939 patients included, 28.7% received QPT. The crude mortality was 1.2% (95% confidence interval [CI] 0.8% to 1.7%) among the patients receiving QPT and 4.8% (95% CI 4.3% to 5.3%) among those not receiving QPT. After adjustment for patient characteristics and concomitant treatments, QPT use was associated with a relative reduction of 50% in in-hospital mortality (hazard ratio, 0.50; 95% CI, 0.37 to 0.66 P <0.001). This association was consistent across subgroups by sex and age. Meanwhile, the incidence of acute liver injury (8.9% [95% CI, 7.8% to 10.1%]vs. 9.9% [95% CI, 9.2% to 10.7%]; odds ratio, 0.96 [95% CI, 0.81% to 1.14%], P =0.658) and acute kidney injury (1.6% [95% CI, 1.2% to 2.2%] vs. 3.0% [95% CI, 2.6% to 3.5%]; odds ratio, 0.85 [95% CI, 0.62 to 1.17], P =0.318) was comparable between patients receiving QPT and those not receiving QPT. The major study limitations included that the study was an observational study based on real-world data rather than a randomized control trial, and the quality of data could be affected by the accuracy and completeness of medical records.\n\nConclusionsQPT was associated with a substantially lower risk of in-hospital mortality, without extra risk of acute liver injury or acute kidney injury among patients hospitalized with COVID-19.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248784",
+    "rel_abs": "In this communication we assess the potential benefit of SARS-COV-2 pandemic vaccination in the US and show how continued use of non-pharmaceutical interventions (NPIs) will be crucial during implementation.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Lihua Zhang",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Xin Zheng",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Xueke Bai",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Qing Wang",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Bowang Chen",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Haibo Wang",
-        "author_inst": "Clinical Trial Unit, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou Province,PRC"
-      },
-      {
-        "author_name": "Jiapeng Lu",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Shuang Hu",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Xiaoyan Zhang",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
-      },
-      {
-        "author_name": "Haibo Zhang",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
+        "author_name": "Marta Galanti",
+        "author_inst": "Columbia University"
       },
       {
-        "author_name": "Jiamin Liu",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
+        "author_name": "Sen Pei",
+        "author_inst": "Columbia University"
       },
       {
-        "author_name": "Ying Shi",
-        "author_inst": "China Standard Medical Information Research Center, Shenzhen,PRC"
+        "author_name": "Teresa K Yamana",
+        "author_inst": "Columbia University"
       },
       {
-        "author_name": "Zhiye Zhou",
-        "author_inst": "China Standard Medical Information Research Center, Shenzhen,PRC"
+        "author_name": "Frederick J Angulo",
+        "author_inst": "Pfizer Vaccines"
       },
       {
-        "author_name": "Lanxia Gan",
-        "author_inst": "China Standard Medical Information Research Center, Shenzhen,PRC"
+        "author_name": "Apostolos Charos",
+        "author_inst": "Pfizer Vaccines"
       },
       {
-        "author_name": "Xi Li",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
+        "author_name": "David L Swerdlow",
+        "author_inst": "Pfizer Vaccines"
       },
       {
-        "author_name": "Jing Li",
-        "author_inst": "National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascula"
+        "author_name": "Jeffrey Shaman",
+        "author_inst": "Columbia University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -964849,75 +967852,63 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.12.23.424254",
-    "rel_title": "Cell-type apoptosis in lung during SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2020.12.23.424189",
+    "rel_title": "Berberine and obatoclax inhibit SARS-CoV-2 replication in primary human nasal epithelial cells in vitro",
     "rel_date": "2020-12-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.23.424254",
-    "rel_abs": "The SARS-CoV-2 pandemic has inspired renewed interest in understanding the fundamental pathology of acute respiratory distress syndrome (ARDS) following infection because fatal COVID-19 cases are commonly linked to respiratory failure due to ARDS. The pathologic alteration known as diffuse alveolar damage in endothelial and epithelial cells is a critical feature of acute lung injury in ARDS. However, the pathogenesis of ARDS following SRAS-CoV-2 infection remains largely unknown.\n\nIn the present study, we examined apoptosis in post-mortem lung sections from COVID-19 patients and lung tissues from a non-human primate model of SARS-CoV-2 infection, in a cell-type manner, including type 1 and 2 alveolar cells and vascular endothelial cells (ECs), macrophages, and T cells. Multiple-target immunofluorescence (IF) assays and western blotting suggest both intrinsic and extrinsic apoptotic pathways are activated during SARS-CoV-2 infection. Furthermore, we observed that SARS-CoV-2 fails to induce apoptosis in human bronchial epithelial cells (i.e., BEAS2B cells) and primary human umbilical vein endothelial cells (HUVECs), which are refractory to SARS-CoV-2 infection. However, infection of co-cultured Vero cells and HUVECs or Vero cells and BEAS2B cells with SARS-CoV-2 induced apoptosis in both Vero cells and HUVECs/BEAS2B cells, but did not alter the permissiveness of HUVECs or BEAS2B cells to the virus. Post-exposure treatment of the co-culture of Vero cells and HUVECs with an EPAC1-specific activator ameliorated apoptosis in HUVECs. These findings may help to delineate a novel insight into the pathogenesis of ARDS following SARS-CoV-2 infection.",
-    "rel_num_authors": 14,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.23.424189",
+    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged as a new human pathogen in late 2019 and has infected an estimated 10% of the global population in less than a year. There is a clear need for effective antiviral drugs to complement current preventive measures including vaccines. In this study, we demonstrate that berberine and obatoclax, two broad-spectrum antiviral compounds, are effective against multiple isolates of SARS-CoV-2. Berberine, a plant-derived alkaloid, inhibited SARS-CoV-2 at low micromolar concentrations and obatoclax, originally developed as an anti-apoptotic protein antagonist, was effective at sub-micromolar concentrations. Time-of-addition studies indicated that berberine acts on the late stage of the viral life cycle. In agreement, berberine mildly affected viral RNA synthesis, but strongly reduced infectious viral titers, leading to an increase in the particle-to-pfu ratio. In contrast, obatoclax acted at the early stage of the infection, in line with its activity to neutralize the acidic environment in endosomes. We assessed infection of primary human nasal epithelial cells cultured on an air-liquid interface and found that SARS-CoV-2 infection induced and repressed expression of a specific set of cytokines and chemokines. Moreover, both obatoclax and berberine inhibited SARS-CoV-2 replication in these primary target cells. We propose berberine and obatoclax as potential antiviral drugs against SARS-CoV-2 that could be considered for further efficacy testing.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Yakun Liu",
-        "author_inst": "University of Texas Medical Branch at Galveston"
-      },
-      {
-        "author_name": "Tania M. Garron",
-        "author_inst": "University of Texas Medical Branch at Galveston"
-      },
-      {
-        "author_name": "Qing Chang",
-        "author_inst": "University of Texas Medical Branch at Galveston"
-      },
-      {
-        "author_name": "Zhengchen Su",
-        "author_inst": "University of Texas Medical Branch at Galveston"
+        "author_name": "Finny S. Varghese",
+        "author_inst": "Department of Medical Microbiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Changcheng Zhou",
-        "author_inst": "University of Texas Medical Branch at Galveston"
+        "author_name": "Esther van Woudenbergh",
+        "author_inst": "Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment, Bilthoven, the Netherlands"
       },
       {
-        "author_name": "Eric C. Gong",
-        "author_inst": "University of Texas Medical Branch at Galveston"
+        "author_name": "Gijs J. Overheul",
+        "author_inst": "Department of Medical Microbiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Junying Zheng",
-        "author_inst": "The University of Texas Medical Branch"
+        "author_name": "Marc J. Eleveld",
+        "author_inst": "Section Paediatric Infectious Diseases, Laboratory of Medical Immunology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijm"
       },
       {
-        "author_name": "Whitney Yin",
-        "author_inst": "University of Texas Medical Branch, Galveston"
+        "author_name": "Lisa Kurver",
+        "author_inst": "Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Thomas Ksiazek",
-        "author_inst": "University of Texas Medical Branch at Galveston"
+        "author_name": "Niels van Heerbeek",
+        "author_inst": "Department of Otolaryngology, Head and Neck Surgery, Radboudumc, Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Trevor Brasel",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Arjan van Laarhoven",
+        "author_inst": "Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Yang Jin",
-        "author_inst": "Boston University Medical Campus"
+        "author_name": "Pascal Miesen",
+        "author_inst": "Department of Medical Microbiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands"
       },
       {
-        "author_name": "Paul Boor",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Gerco den Hartog",
+        "author_inst": "Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment, Bilthoven, The Netherlands"
       },
       {
-        "author_name": "Jason Edward Comer",
-        "author_inst": "UTMB"
+        "author_name": "Marien I. de Jonge",
+        "author_inst": "Section Paediatric Infectious Diseases, Laboratory of Medical Immunology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijm"
       },
       {
-        "author_name": "Bin Gong",
-        "author_inst": "University of Texas Medical Branch"
+        "author_name": "Ronald P. van Rij",
+        "author_inst": "Department of Medical Microbiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "pathology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.12.23.424199",
@@ -966587,25 +969578,25 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.12.23.20248790",
-    "rel_title": "A Systematic Review of the Incubation Period of SARS-CoV-2: The Effects of Age, Biological Sex, and Location on Incubation Period",
+    "rel_doi": "10.1101/2020.12.22.20248736",
+    "rel_title": "REAL-TIME MECHANISTIC BAYESIAN FORECASTS OF COVID-19 MORTALITY",
     "rel_date": "2020-12-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248790",
-    "rel_abs": "A systematic review of the incubation period of COVID-19 was compiled and analyzed from 21 quantitative studies. We investigated the incubation period of COVID-19 with regard to age, biological sex, location, and severity of the disease. Based on the data extracted, we report an overall mean and median incubation period for SARS-CoV-2 of 5.894 days and 5.598 days, respectively. The incubation period did not statistically vary for biological sex or age, but some studies suggest a longer incubation period in the young and elderly. Cases of COVID-19 in Wuhan and Hubei Province of China may have a shorter incubation period for COVID-19 but the shorter incubation period may be due to an increase in viral load. In studying coronavirus strains such as SARS and MERS, researchers have discovered an inverse relationship between incubation period length and virus severity. Taking into consideration that SARS-CoV-2 is part of the beta-coronavirus family, as well as the study mentioned above, we suggest that people who experience more severe disease due to SARS-CoV-2 may have a shorter incubation period.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.22.20248736",
+    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWThe COVID-19 pandemic emerged in late December 2019. In the first six months of the global outbreak, the US reported more cases and deaths than any other country in the world. Effective modeling of the course of the pandemic can help assist with public health resource planning, intervention efforts, and vaccine clinical trials. However, building applied forecasting models presents unique challenges during a pandemic. First, case data available to models in real-time represent a non-stationary fraction of the true case incidence due to changes in available diagnostic tests and test-seeking behavior. Second, interventions varied across time and geography leading to large changes in transmissibility over the course of the pandemic. We propose a mechanistic Bayesian model (MechBayes) that builds upon the classic compartmental susceptible-exposed-infected-recovered (SEIR) model to operationalize COVID-19 forecasting in real time. This framework includes non-parametric modeling of varying transmission rates, non-parametric modeling of case and death discrepancies due to testing and reporting issues, and a joint observation likelihood on new case counts and new deaths; it is implemented in a probabilistic programming language to automate the use of Bayesian reasoning for quantifying uncertainty in probabilistic forecasts. The model has been used to submit forecasts to the US Centers for Disease Control, through the COVID-19 Forecast Hub. We examine the performance relative to a baseline model as well as alternate models submitted to the Forecast Hub. Additionally, we include an ablation test of our extensions to the classic SEIR model. We demonstrate a significant gain in both point and probabilistic forecast scoring measures using MechBayes when compared to a baseline model and show that MechBayes ranks as one of the top 2 models out of 10 submitted to the COVID-19 Forecast Hub. Finally, we demonstrate that MechBayes performs significantly better than the classical SEIR model.",
     "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Caitlin Daley",
-        "author_inst": "Wheaton College"
+        "author_name": "Graham C Gibson",
+        "author_inst": "University of Massachusetts Amherst"
       },
       {
-        "author_name": "Megan Fydenkevez",
-        "author_inst": "Wheaton College"
+        "author_name": "Nicholas G Reich",
+        "author_inst": "University of Massachusetts Amherst"
       },
       {
-        "author_name": "Shari Ackerman-Morris",
-        "author_inst": "Wheaton College"
+        "author_name": "Daniel Sheldon",
+        "author_inst": "University of Massachusetts Amherst"
       }
     ],
     "version": "1",
@@ -968232,47 +971223,291 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.12.17.20248234",
-    "rel_title": "Airflow and air velocity measurements while playing wind instruments, with respect to risk assessment of a SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2020.12.21.20248608",
+    "rel_title": "Adaptive immunity to SARS-CoV-2 in cancer patients: The CAPTURE study",
     "rel_date": "2020-12-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.17.20248234",
-    "rel_abs": "Due to airborne transmission of infection with the coronavirus, the question arose as to how high the risk of spreading infectious particles can be while playing a wind instrument.\n\nTo contribute to this question and to help clarify the possible risks, we analyzed 14 wind instruments, first qualitative by making airflows visible while playing and second quantitative by measuring air velocities at three distances (1m, 1.5m and 2m) in direction of the instruments bell.\n\nMeasurements took place with wind instrumentalists of the Bamberg Symphony in their concert hall.\n\nOur findings highlight that while playing all wind instruments no airflow escaping from the instruments - from the bell with brass instruments, from the mouthpiece, keyholes and bell with woodwinds - was measured beyond a distance of 1.5m from the instruments bell, regardless of volume, pitch or what was played. With that, air velocity while playing corresponded to the usual value of hall-like rooms, of 0.1 m/s. For air-jet woodwinds, alto flute and piccolo, significant air movements were seen close to their mouthpieces, which escaped directly into the room without passing through the instrument and therefore generating directed air movements.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248608",
+    "rel_abs": "There is a pressing need to characterise the nature, extent and duration of immune response to SARS-CoV-2 in cancer patients and inform risk-reduction strategies and preserve cancer outcomes. CAPTURE is a prospective, longitudinal cohort study of cancer patients and healthcare workers (HCWs) integrating longitudinal immune profiling and clinical annotation. We evaluated 529 blood samples and 1051 oronasopharyngeal swabs from 144 cancer patients and 73 HCWs and correlated with >200 clinical variables. In patients with solid cancers and HCWs, S1-reactive and neutralising antibodies to SARS-CoV-2 were detectable five months post-infection. SARS-CoV-2-specific T-cell responses were detected, and CD4+ T-cell responses correlated with S1 antibody levels. Patients with haematological malignancies had impaired but partially compensated immune responses. Overall, cancer stage, disease status, and therapies did not correlate with immune responses. These findings have implications for understanding individual risks and potential effectiveness of SARS-CoV-2 vaccination in the cancer population.",
+    "rel_num_authors": 68,
     "rel_authors": [
       {
-        "author_name": "Claudia Spahn",
-        "author_inst": "Freiburg Institute for Musicians' Medicine"
+        "author_name": "Annika Fendler",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Anna Maria Hipp",
-        "author_inst": "Freiburg Institute for Musicians' Medicine"
+        "author_name": "Lewis Au",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Bernd Schubert",
-        "author_inst": "Tintschl BioEnergie und Stroemungstechnik AG"
+        "author_name": "Laura Amanda Boos",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
       },
       {
-        "author_name": "Marcus Rudolf Axt",
-        "author_inst": "Bamberg Symphony"
+        "author_name": "Fiona Byrne",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Markus Stratmann",
-        "author_inst": "Bamberg Symphony"
+        "author_name": "Scott Thomas Colville Shepherd",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Christian Schmoelder",
-        "author_inst": "Bamberg Symphony"
+        "author_name": "Ben Shum",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Bernhard Richter",
-        "author_inst": "Freiburg Institute for Musicians' Medicine"
+        "author_name": "Camille L Gerard",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Barry Ward",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Wenyi Xie",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Maddalena Cerrone",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Georgina H Cornish",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Martin Pule",
+        "author_inst": "Autolus Limited, The MediaWorks"
+      },
+      {
+        "author_name": "Leila Mekkaoui",
+        "author_inst": "Autolus Limited, The MediaWorks"
+      },
+      {
+        "author_name": "Kevin Ng",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Richard Stone",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Camilla Gomes",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Helen R Flynn",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Ana Agua-Doce",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Phillip Hobson",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Simon Caidan",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Mike Howell",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Robert Goldstone",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Mike Gavrielides",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Emma Nye",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Bram Snijders",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "James Macrae",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Jerome Nicod",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Adrian Hayday",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Firza Gronthoud",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Christina Messiou",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "David Cunningham",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Ian Chau",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Naureen Starling",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Nicholas Turner",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Jennifer Rusby",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Liam Welsh",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Nicholas van As",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Robin Jones",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Joanne Droney",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Susana Banerjee",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Kate Tatham",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Shaman Jhanji",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Olivia Curtis",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Kevin Harrington",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Shreerang Bhide",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Tim Slattery",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Yasir Khan",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Zayd Tippu",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Isla Leslie",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Spyridon Gennatas",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Alicia Okines",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Alison Reid",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Kate Young",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Andrew Furness",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Lisa Pickering",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Sonia Ghandi",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Steve Gamblin",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Charles Swanton",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Emma Nicholson",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Sacheen Kumar",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Nadia Yousaf",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Katalin Andrea Wilkinson",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Anthony Swerdlow",
+        "author_inst": "The Institute of Cancer Research"
+      },
+      {
+        "author_name": "Ruth Harvey",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "George Kassiotis",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "Robert Wilkinson",
+        "author_inst": "The Francis Crick Institute"
+      },
+      {
+        "author_name": "James Larkin",
+        "author_inst": "The Royal Marsden NHS Foundation Trust"
+      },
+      {
+        "author_name": "Samra Turajlic",
+        "author_inst": "The Francis Crick Institute"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "category": "oncology"
   },
   {
     "rel_doi": "10.1101/2020.12.22.20248392",
@@ -969974,21 +973209,45 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.12.21.20248627",
-    "rel_title": "COVID-19 pandemic dynamics in Ukraine after September 1, 2020",
+    "rel_doi": "10.1101/2020.12.22.20248622",
+    "rel_title": "Optimal strategies for combining vaccine prioritization and social distancing to reduce hospitalizations and mitigate COVID19 progression",
     "rel_date": "2020-12-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248627",
-    "rel_abs": "BackgroundThe threats of the COVID-19 pandemic require the mobilization of scientists, including mathematicians. To understand how the number of cases increases versus time, various models based on direct observations of a random number of new cases and differential equations can be used. Complex mathematical models contain many unknown parameters, the values of which must be determined using a limited number of observations of the disease over time. Even long-term monitoring of the epidemic may not provide reliable estimates of its parameters due to the constant change of testing conditions, isolation of infected and quarantine. Therefore, simpler approaches should also be used, for example, some smoothing of the dependence of the number of cases on time and the known SIR (susceptible-infected-removed) model. These approaches allowed to detect the waves of pandemic in different countries and regions and to make adequate predictions of the duration, hidden periods, reproduction numbers, and final sizes of its waves. In particular, seven waves of the COVID-19 pandemic in Ukraine were investigated.\n\nObjectiveWe will detect new epidemic waves in Ukraine that occurred after September 1, 2020 and estimate the epidemic characteristics with the use of generalized SIR model. Some predictions of the epidemic dynamics will be presented.\n\nMethodsIn this study we use the smoothing method for the dependence of the number of cases on time; the generalized SIR model for the dynamics of any epidemic wave, the exact solution of the linear differential equations and statistical approach developed before.\n\nResultsSeventh and eights epidemic waves in Ukraine were detected and the reasons of their appearance were discussed. The optimal values of the SIR model parameters were calculated. The prediction for the COVID-19 epidemic dynamics in Ukraine is not very optimistic: new cases will not stop appearing until June 2021. Only mass vaccination and social distancing can change this trend.\n\nConclusionsNew waves of COVID-19 pandemic can be detected, calculated and predicted with the use of rather simple mathematical simulations. The expected long duration of the pandemic forces us to be careful and in solidarity.The government and all Ukrainians must strictly adhere to quarantine measures in order to avoid fatal consequences.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.22.20248622",
+    "rel_abs": "Social distancing is an effective population-level mitigation strategy to prevent COVID19 propagation but it does not reduce the number of susceptible individuals and bears severe social consequences--a dire situation that can be overcome with the recently developed vaccines. Although a combination of these interventions should provide greater benefits than their isolated deployment, a mechanistic understanding of the interplay between them is missing. To tackle this challenge we developed an age-structured deterministic model in which vaccines are deployed during the pandemic to individuals who, in the eye of public health, are susceptible (do not show symptoms). The model allows for flexible and dynamic prioritization strategies with shifts between target groups. We find a strong interaction between social distancing and vaccination in their effect on the proportion of hospitalizations. In particular, prioritizing vaccines to elderly (60+) before adults (20-59) is more effective when social distancing is applied to adults or uniformly. In addition, the temporal reproductive number Rt is only affected by vaccines when deployed at sufficiently high rates and in tandem with social distancing. Finally, the same reduction in hospitalization can be achieved via different combination of strategies, giving decision makers flexibility in choosing public health policies. Our study provides insights into the factors that affect vaccination success and provides methodology to test different intervention strategies in a way that will align with ethical guidelines.\n\nAuthor summaryA major question in epidemiology is how to combine intervention methods in an optimal way. With the recent deployment of COVID19 vaccine, this question is now particularly relevant. Using a data-driven model in which vaccines are deployed during the pandemic and their prioritization can shift between target groups we show that there is a strong interplay between these interventions. For example, prioritizing vaccines to elderly--the common strategy worldwide--results in a larger reduction in hospitalizations when social distancing is applied to adults than to elderly. Importantly, reduction in hospitalizations can be achieved via multiple combination of intervention strategies, allowing for flexible public health policies.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Igor Nesteruk",
-        "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine"
+        "author_name": "Sharon Guerstein",
+        "author_inst": "Ben-Gurion University of the Negev"
+      },
+      {
+        "author_name": "Victoria Romeo-Aznar",
+        "author_inst": "University of Chicago"
+      },
+      {
+        "author_name": "Ma'ayan Dekel",
+        "author_inst": "Ben-Gurion University of the Negev"
+      },
+      {
+        "author_name": "Oren Miron",
+        "author_inst": "Ben-Gurion University of the Negev"
+      },
+      {
+        "author_name": "Nadav Davidovitch",
+        "author_inst": "Ben-Gurion University of the Negev"
+      },
+      {
+        "author_name": "Rami Puzis",
+        "author_inst": "Ben-Gurion University of the Negev"
+      },
+      {
+        "author_name": "Shai Pilosof",
+        "author_inst": "Ben Gurion University of the Negev"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -971284,21 +974543,133 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.20.20248587",
-    "rel_title": "Predicting intention to receive COVID-19 vaccine among the general population using the Health Belief Model and the Theory of Planned Behavior Model",
+    "rel_doi": "10.1101/2020.12.19.20248559",
+    "rel_title": "Changes in UK hospital mortality in the first wave of COVID-19: the ISARIC WHO Clinical Characterisation Protocol prospective multicentre observational cohort study",
     "rel_date": "2020-12-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.20.20248587",
-    "rel_abs": "BackgroundA novel coronavirus (COVID-19) was declared a global pandemic by the World Health Organization (WHO) in March, 2020. Until such time as a vaccine becomes available, it is important to identify the determining factors that influence the intention of the general public to accept a future COVID-19 vaccine. Consequently, we aim to explore behavioral-related factors predicting intention to receive COVID-19 vaccine among the general population using the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB) model.\n\nMethodsAn online survey was conducted among adults aged 18 years and older from May 24 to June 24, 2020. The survey included socio-demographic and health-related questions, questions related to the HBM and TPB dimensions, and intention to receive COVID-19 vaccine. Associations between questionnaire variables and COVID-19 vaccination intention were assessed by univariate and multivariate analyses.\n\nResultsEighty percent of 398 eligible respondents stated their willingness to receive COVID-19 vaccine. A unified model including HBM and TPB covariates as well as demographic and health-related factors, proved to be a powerful predictor of intention to receive COVID-19 vaccine, explaining 78% of the variance (adjusted R2 = 0.78). Men (OR=4.35, 95% CI 1.58-11.93), educated respondents (OR=3.54, 95% CI 1.44-8.67) and respondents who had received the seasonal influenza vaccine in the previous year (OR=3.31, 95% CI 1.22-9.00) stated higher intention to receive COVID-19 vaccine. Participants were more likely to be willing to get vaccinated if they reported higher levels of perceived benefits of COVID-19 vaccine (OR=4.49, 95% CI 2.79-7.22), of perceived severity of COVID-19 infection (OR=2.36, 95% CI 1.58-3.51) and of cues to action (OR=1.99, 95% CI 1.38-2.87), according to HBM, and if they reported higher levels of subjective norms (OR=3.04, 95% CI 2.15-4.30) and self-efficacy (OR=2.05, 95% CI 1.54-2.72) according to TPB. Although half of the respondents reported they had not received influenza vaccine last year, 40% of them intended to receive influenza vaccine in the coming winter and 66% of them intended to receive COVID-19 vaccine.\n\nConclusionsProviding data on the public perspective and predicting intention for COVID-19 vaccination using HBM and TPB is important for health policy makers and healthcare providers and can help better guide compliance as the COVID-19 vaccine becomes available to the public.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.19.20248559",
+    "rel_abs": "BackgroundMortality rates of UK patients hospitalised with COVID-19 appeared to fall during the first wave. We quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital.\n\nMethodsThe International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK recruited a prospective cohort admitted to 247 acute UK hospitals with COVID-19 in the first wave (March to August 2020). Outcome was hospital mortality within 28 days of admission. We performed a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and hospital mortality adjusting for confounders (demographics, comorbidity, illness severity) and quantifying potential mediators (respiratory support and steroids).\n\nFindingsUnadjusted hospital mortality fell from 32.3% (95%CI 31.8, 32.7) in March/April to 16.4% (95%CI 15.0, 17.8) in June/July 2020. Reductions were seen in all ages, ethnicities, both sexes, and in comorbid and non-comorbid patients. After adjustment, there was a 19% reduction in the odds of mortality per 4 week period (OR 0.81, 95%CI 0.79, 0.83). 15.2% of this reduction was explained by greater disease severity and comorbidity earlier in the epidemic. The use of respiratory support changed with greater use of non-invasive ventilation (NIV). 22.2% (OR 0.94, 95%CI 0.94, 0.96) of the reduction in mortality was mediated by changes in respiratory support.\n\nInterpretationThe fall in hospital mortality in COVID-19 patients during the first wave in the UK was partly accounted for by changes in case mix and illness severity. A significant reduction was associated with differences in respiratory support and critical care use, which may partly reflect improved clinical decision making. The remaining improvement in mortality is not explained by these factors, and may relate to community behaviour on inoculum dose and hospital capacity strain.\n\nFundingNIHR & MRC\n\nKey points / Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSRisk factors for mortality in patients hospitalised with COVID-19 have been established. However there is little literature regarding how mortality is changing over time, and potential explanations for why this might be. Understanding changes in mortality rates over time will help policy makers identify evolving risk, strategies to manage this and broader decisions about public health interventions.\n\nAdded value of this studyMortality in hospitalised patients at the beginning of the first wave was extremely high. Patients who were admitted to hospital in March and early April were significantly more unwell at presentation than patients who were admitted in later months. Mortality fell in all ages, ethnic groups, both sexes and in patients with and without comorbidity, over and above contributions from falling illness severity. After adjustment for these variables, a fifth of the fall in mortality was explained by changes in the use of respiratory support and steroid treatment, along with associated changes in clinical decision-making relating to supportive interventions. However, mortality was persistently high in patients who required invasive mechanical ventilation, and in those patients who received non-invasive ventilation outside of critical care.\n\nImplications of all the available evidenceThe observed reduction in hospital mortality was greater than expected based on the changes seen in both case mix and illness severity. Some of this fall can be explained by changes in respiratory care, including clinical learning. In addition, introduction of community policies including wearing of masks, social distancing, shielding of vulnerable patients and the UK lockdown potentially resulted in people being exposed to less virus.\n\nThe decrease in mortality varied depending on the level of respiratory support received. Patients receiving invasive mechanical ventilation have persistently high mortality rates, albeit with a changing case-mix, and further research should target this group.\n\nSevere COVID-19 disease has primarily affected older people in the UK. Many of these people, but not all have significant frailty. It is essential to ensure that patients and their families remain at the centre of decision-making, and we continue with an individualised approach to their treatment and care.",
+    "rel_num_authors": 29,
     "rel_authors": [
       {
-        "author_name": "Liora Shmueli",
-        "author_inst": "Bar-Ilan university"
+        "author_name": "Annemarie B Docherty",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Rachel H Mulholland",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Nazir I Lone",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Christopher P Cheyne",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Daniela De Angelis",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Karla Diaz-Ordaz",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Cara Donoghue",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Thomas M Drake",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Jake Dunning",
+        "author_inst": "Imperial College, London"
+      },
+      {
+        "author_name": "Sebastian Funk",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Marta Garcia-Finana",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Michelle Girvan",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Hayley E Hardwick",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Janet Harrison",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Antonia Ho",
+        "author_inst": "University of Glasgow"
+      },
+      {
+        "author_name": "David M Hughes",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Ruth H Keogh",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Peter D Kirwan",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Gary Leeming",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Jonathan S Nguyen-Van-Tam",
+        "author_inst": "University of Nottingham"
+      },
+      {
+        "author_name": "Riinu Pius",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Clark D Russell",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Rebecca Spencer",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Brian DM Tom",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Lance Turtle",
+        "author_inst": "University of Liverpool"
+      },
+      {
+        "author_name": "Peter JM Openshaw",
+        "author_inst": "Imperial College London"
+      },
+      {
+        "author_name": "J Kenneth Baillie",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Ewen M Harrison",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Malcolm G Semple",
+        "author_inst": "University of Liverpool"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -973542,83 +976913,43 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.12.22.423893",
-    "rel_title": "Transcriptional and epi-transcriptional dynamics of SARS-CoV-2 during cellular infection",
+    "rel_doi": "10.1101/2020.12.22.423920",
+    "rel_title": "Evolutionary tracking of SARS-CoV-2 genetic variants highlights intricate balance of stabilizing and destabilizing mutations",
     "rel_date": "2020-12-22",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.22.423893",
-    "rel_abs": "SARS-CoV-2 uses subgenomic (sg)RNA to produce viral proteins for replication and immune evasion. We applied long-read RNA and cDNA sequencing to in vitro human and primate infection models to study transcriptional dynamics. Transcription-regulating sequence (TRS)-dependent sgRNA was upregulated earlier in infection than TRS-independent sgRNA. An abundant class of TRS-independent sgRNA consisting of a portion of ORF1ab containing nsp1 joined to ORF10 and 3UTR was upregulated at 48 hours post infection in human cell lines. We identified double-junction sgRNA containing both TRS-dependent and independent junctions. We found multiple sites at which the SARS-CoV-2 genome is consistently more modified than sgRNA, and that sgRNA modifications are stable across transcript clusters, host cells and time since infection. Our work highlights the dynamic nature of the SARS-CoV-2 transcriptome during its replication cycle. Our results are available via an interactive web-app at http://coinlab.mdhs.unimelb.edu.au/.",
-    "rel_num_authors": 16,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.22.423920",
+    "rel_abs": "The currently ongoing COVID-19 pandemic caused by SARS-CoV-2 has accounted for millions of infections and deaths across the globe. Genome sequences of SARS-CoV-2 are being published daily in public databases and the availability of this genome datasets has allowed unprecedented access into the mutational patterns of SARS-CoV-2 evolution. We made use of the same genomic information for conducting phylogenetic analysis and identifying lineage-specific mutations. The catalogued lineage defining mutations were analysed for their stabilizing or destabilizing impact on viral proteins. We recorded persistence of D614G, S477N, A222V V1176F variants and a global expansion of the PANGOLIN variant B.1. In addition, a retention of Q57H (B.1.X), R203K/G204R (B.1.1.X), T85I (B.1.2-B.1.3), G15S+T428I (C.X) and I120F (D.X) variations was observed. Overall, we recorded a striking balance between stabilizing and destabilizing mutations, therefore well-maintained protein structures. With selection pressures in the form of newly developed vaccines and therapeutics to mount soon in coming months, the task of mapping of viral mutations and recording of their impact on key viral proteins would be crucial to pre-emptively catch any escape mechanism that SARS-CoV-2 may evolve for.\n\nSTUDY IMPORTANCEAs large numbers of the SARS CoV-2 genome sequences are shared in publicly accessible repositories, it enables scientists a detailed evolutionary analysis since its initial isolation in Wuhan, China. We investigated the evolutionarily associated mutational diversity overlaid on the major phylogenetic lineages circulating globally, using 513 representative genomes. We detailed phylogenetic persistence of key variants facilitating global expansion of the PANGOLIN variant B.1, including the recent, fast expanding, B.1.1.7 lineage. The stabilizing or destabilizing impact of the catalogued lineage defining mutations on viral proteins indicates their possible involvement in balancing the protein function and structure. A clear understanding of this mutational profile is of high clinical significance to catch any vaccine escape mechanism, as the same proteins make crucial components of vaccines recently approved and in development. In this direction, our study provides an imperative framework and baseline data upon which further analysis could be built as newer variants of SARS-CoV-2 continue to appear.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Jessie J.-Y. Chang",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
-      },
-      {
-        "author_name": "Daniel Rawlinson",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
-      },
-      {
-        "author_name": "Miranda E. Pitt",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
-      },
-      {
-        "author_name": "George Taiaroa",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
-      },
-      {
-        "author_name": "Josie Gleeson",
-        "author_inst": "Centre for Stem Cell Systems, Department of Anatomy and Neuroscience, The University of Melbourne"
-      },
-      {
-        "author_name": "Chenxi Zhou",
-        "author_inst": "Department of Clinical Pathology, University of Melbourne,"
-      },
-      {
-        "author_name": "Francesca L. Mordant",
-        "author_inst": "Department of Clinical Pathology, University of Melbourne,"
-      },
-      {
-        "author_name": "Ricardo De Paoli-Iseppi",
-        "author_inst": "Centre for Stem Cell Systems, Department of Anatomy and Neuroscience, The University of Melbourne"
-      },
-      {
-        "author_name": "Leon Caly",
-        "author_inst": "Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity"
-      },
-      {
-        "author_name": "Damian F. J. Purcell",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
-      },
-      {
-        "author_name": "Tim P. Stinear",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
+        "author_name": "Jobin John Jacob",
+        "author_inst": "Christian Medical College,Vellore"
       },
       {
-        "author_name": "Sarah L. Londrigan",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
+        "author_name": "Karthick Vasudevan",
+        "author_inst": "Christian Medical College, Vellore"
       },
       {
-        "author_name": "Michael B. Clark",
-        "author_inst": "Centre for Stem Cell Systems, Department of Anatomy and Neuroscience, The University of Melbourne"
+        "author_name": "Agila Kumari Pragasam",
+        "author_inst": "Christian Medical College, Vellore"
       },
       {
-        "author_name": "Deborah A. Williamson",
-        "author_inst": "Department of Microbiology and Immunology, University of Melbourne"
+        "author_name": "Karthik Gunasekaran",
+        "author_inst": "Christian Medical College, Vellore"
       },
       {
-        "author_name": "Kanta Subbarao",
-        "author_inst": "WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity"
+        "author_name": "Balaji Veeraraghavan",
+        "author_inst": "Christian Medical College, Vellore"
       },
       {
-        "author_name": "Lachlan J M Coin",
-        "author_inst": "Department of Microbiology and Immunology, The University of Melbourne"
+        "author_name": "Ankur Mutreja",
+        "author_inst": "University of Cambridge"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.12.21.423850",
@@ -975459,39 +978790,43 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.12.19.423597",
-    "rel_title": "A comprehensive transcriptome analysis reveals broader but weaker host response of SARS-CoV-2 than SARS-CoV",
+    "rel_doi": "10.1101/2020.12.18.20248455",
+    "rel_title": "The impact of the first UK Covid-19 lockdown on carers and people living with low prevalence dementia: results from the Rare Dementia Support survey",
     "rel_date": "2020-12-20",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.19.423597",
-    "rel_abs": "COVID-19, which has resulted a worldwide health crisis with more than 74.9 million confirmed cases worldwide by December 2020, is caused by a newly emerging coronavirus identified and named SARS-CoV-2 in February in Wuhan, China. Experiences in defeating SARS, which infested during 2002-2003, can be used in treating the new disease. However, comparative genomics and epidemiology studies have shown much difference between SARS-CoV and SARS-CoV-2, which underlies the different clinical features and therapies in between those two diseases. Further studies comparing transcriptomes infected by these two viruses to uncover the differences in host responses would be necessary. Here we conducted a comprehensive transcriptome analysis of SARS-CoV and SARS-CoV-2-infected human cell lines, including Caco-2, Calu-3, H1299. Clustering analysis and expression of ACE2 show that SARS-CoV-2 has broader but weaker infection, where the largest discrepancy occurs in the epithelial lung cancer cell, Calu-3. SARS-CoV-2 genes also show less tissue specificity than SARS-CoV genes. Furthermore, we detected more general but moderate immune responses in SARS-CoV-2 infected transcriptomes by comparing weighted gene co-expression networks and modules. Our results suggest a different immune therapy and treatment scheme for COVID-19 patients than the ones used on SARS patients. The wider but weaker permissiveness and host responses of virus infection may also imply a long-term existence of SARS-CoV-2 among human populations.",
-    "rel_num_authors": 5,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248455",
+    "rel_abs": "IntroductionThe public health measures imposed to contain Covid-19 during the first UK lockdown resulted in significant changes in the provision of community support and care for people with dementia. People with low prevalence and young-onset dementias often experience non-memory, behavioural or neuropsychiatric symptoms that require specialised support.\n\nObjectiveWe explored the impact of the first Covid-19 lockdown on people living with low prevalence and young-onset dementia and their carers in the UK.\n\nMethodAn online survey, including eleven questions about the impact of the lockdown on both the person with dementia and their family caregivers was conducted. Participants were people living with dementia and caregivers who are members of the UK national-reach organisation Rare Dementia Support.\n\nResults184 carers and 24 people with dementia completed the survey. People with dementia experienced worsening of cognitive symptoms (70%), ability to do things (62%) and well-being (57%) according to their carers. Carers also reported a reduction in the support received for caring (55%). 93% of carers of people living in care homes reported a reduction in their ability to provide care. 26% of carers reported changes in the medication of the person with dementia during the lockdown. 74% of people with dementia reported decreased ability to connect with people socially.\n\nConclusionsPeople with dementia experienced a worsening of dementia symptoms, removal of support and increased difficulty to connect with other people socially during the 1st wave of Covid-19. Carers encountered barriers to both receiving and providing support and a decline in their own mental health and well-being.\n\nKey pointsO_LI70 % of carers reported cognitive symptoms getting worse during the lockdown (e.g., the person with dementia being more disoriented and finding it more difficult to communicate).\nC_LIO_LI26 % of carers reported a change (initiation or increase) in medication in the person with dementia during the lockdown.\nC_LIO_LI79 % carers reported their own physical or mental health getting worse due to the lockdown. This increased to 93% when considering responses only from family carers of people living in care homes.\nC_LIO_LI93 % of family carers of people living in care homes found it harder to continue providing care and support for their relative due to Covid-19.\nC_LI",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Chi Sum Leung",
-        "author_inst": "AmazingX Academy"
+        "author_name": "Aida Suarez Gonzalez",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Songhong Xie",
-        "author_inst": "AmazingX Academy"
+        "author_name": "Emma Harding",
+        "author_inst": "UCL"
+      },
+      {
+        "author_name": "Nicola Zimmerman",
+        "author_inst": "UCL"
       },
       {
-        "author_name": "Jiali Feng",
-        "author_inst": "AmazingX Academy"
+        "author_name": "Zoe Hoare",
+        "author_inst": "UCL"
       },
       {
-        "author_name": "Dongjing Chen",
-        "author_inst": "AmazingX Academy"
+        "author_name": "Emilie Brotherhood",
+        "author_inst": "UCL"
       },
       {
-        "author_name": "Aimei Dai",
-        "author_inst": "School of Life Science, Sun Yat-sen University"
+        "author_name": "Sebastian J Crutch",
+        "author_inst": "UCL"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "neurology"
   },
   {
     "rel_doi": "10.1101/2020.12.18.20248319",
@@ -977445,47 +980780,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.18.20248434",
-    "rel_title": "Excess deaths among Latino people in California during the COVID-19 pandemic",
+    "rel_doi": "10.1101/2020.12.18.20248449",
+    "rel_title": "Coinfection with Respiratory Pathogens in COVID-19 in Korea",
     "rel_date": "2020-12-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248434",
-    "rel_abs": "BackgroundLatino people in the US are experiencing higher excess deaths during the COVID-19 pandemic than any other racial/ethnic group, but it is unclear which subgroups within this diverse population are most affected. Such information is necessary to target policies that prevent further excess mortality and reduce inequities.\n\nMethodsUsing death certificate data for January 1, 2016 through February 29, 2020 and time-series models, we estimated the expected weekly deaths among Latino people in California from March 1 through October 3, 2020. We quantified excess mortality as observed minus expected deaths and risk ratios (RR) as the ratio of observed to expected deaths. We considered subgroups defined by age, sex, place of birth, education, occupation, and combinations of these factors.\n\nFindingsDuring the first seven months of the pandemic, Latino deaths in California exceeded expected deaths by 10,316, a 31% increase. Excess death rates were greatest for individuals born in Mexico (RR 1.44; 95% PI, 1.41, 1.48) or Central America (RR 1.49; 95% PI, 1.37, 1.64), with less than a high school degree (RR 1.41; 95% PI, 1.35, 1.46), or in food-and-agriculture (RR 1.60; 95% PI, 1.48, 1.74) or manufacturing occupations (RR 1.59; 95% PI, 1.50, 1.69). Immigrant disadvantages in excess death were magnified among working-age Latinos in essential occupations.\n\nInterpretationThe pandemic has disproportionately impacted mortality among Latino immigrants and Latinos in unprotected essential jobs; Interventions to reduce these disparities should include early vaccination, workplace safety enforcement, and expanded access to medical care.\n\nFundingNational Institute on Aging; UCSF\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSSeveral articles have suggested all-cause excess mortality estimates are superior to official COVID-19 counts for assessing the impact of the pandemic on marginalized populations that lack access to testing and healthcare. We searched PubMed, Google scholar, and the medRxiv preprint database through December 22, 2020 for studies of (\"excess mortality\" or \"excess death\") AND (\"COVID-19\" or \"coronavirus\") set in the United States and we identified two empirical studies with estimates of excess mortality among Latinos during the pandemic. The study set in California (from our research team) found per capita excess mortality was highest among Black and Latino people. The national study found percent excess mortality was significantly higher among Latino people than any other racial/ethnic group. Neither study further disaggregated the diverse Latino population or provided subgroup estimates to clarify why excess pandemic mortality is so high in this population. In the U.S., official COVID-19 statistics are rarely disaggregated by place of birth, education, or occupation which has resulted in a lack of evidence of how these factors have impacted mortality during the pandemic. No study to date of excess mortality in the U.S. has provided estimates for immigrant or occupational subgroups.\n\nAdded value of this studyOur population-based observational study of all-cause mortality during the COVID-19 pandemic provides the first estimates of within-group heterogeneity among the Latino population in California - one of the populations hardest hit by COVID-19 in the U.S. We provide the first subgroup estimates by place of birth and occupational sector, in addition to combined estimates by foreign-birth and participation in an essential job and education. In doing so, we reveal that Latino immigrants in essential occupations have the highest risk of excess death during the pandemic among working-age Latinos. We highlight the heightened risk of excess mortality associated with food/agriculture and manufacturing occupational sectors, essential sectors in which workers may lack COVID-19 protections.\n\nImplications of all the available evidenceOur study revealed stark disparities in excess mortality during the COVID-19 pandemic among Latinos, pointing to the particularly high vulnerability of Latino immigrants and Latinos in essential jobs. These findings may offer insight into the disproportionate COVID-19 mortality experienced by immigrants or similarly marginalized groups in other contexts. Interventions to reduce these disparities should include policies enforcing occupational safety, especially for immigrant workers, early vaccination, and expanded access to medical care.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.18.20248449",
+    "rel_abs": "Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in upper and lower respiratory specimens and coinfection with other respiratory pathogens in patients with coronavirus disease 2019 (COVID-19) were investigated. From the study subjects (N = 258) retrospectively enrolled when confirmed as SARS-CoV-2 positive, nasopharyngeal (NPS), oropharyngeal swabs (OPS), and sputum specimens were restored for retesting SARS-CoV-2 and detecting respiratory pathogens. Majority of the study subjects (95.7%, N = 247) were confirmed as SARS-CoV-2 positive using NPS/OPS specimens, suggesting that the upper respiratory specimen is most valuable in detecting SARS-CoV-2. Coinfection rates in COVID-19 patients (N = 258) with respiratory pathogens were 9.7% (N = 25); 8.5% (N = 22) respiratory viruses and 1.2% (N = 3) Mycoplasma pneumoniae, an atypical bacterium. Of the respiratory virus coinfection cases (N = 22), 20 (90.9%) were co-infected with a single respiratory virus and 2 (0.8%) (metapneumovirus/adenovirus and rhinovirus/bocavirus 1/2/3/4) with two viruses. Respiratory viruses in single viral coinfection cases with SARS-CoV-2 were as follows: non-SARS-CoV-2 coronaviruses (229E, NL63, and OC43, N = 5, 1.9%), rhinovirus (N = 4, 1.6%), metapneumovirus (N = 3, 1.2%), influenza A (N = 3, 1.2%), respiratory syncytial virus A and B (N = 3, 1.2%), and adenovirus (N = 2, 0.8%). No mixed coinfections with respiratory viruses and M. pneumoniae were found. In conclusion, the diagnostic value of utilizing NPS/OPS specimen is excellent, and, as the first report in Korea, coinfection with respiratory pathogens were detected at a rate of 9.7% in patients with COVID-19.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Alicia R. Riley",
-        "author_inst": "Department of Epidemiology and Biostatistics, University of California, San Francisco"
+        "author_name": "Kyung Ho Roh",
+        "author_inst": "Seegene Medical Foundation"
       },
       {
-        "author_name": "Yea-Hung Chen",
-        "author_inst": "Institute for Global Health Sciences, University of California, San Francisco"
+        "author_name": "Yu Kyung Kim",
+        "author_inst": "Kyungpook National University Hospital"
       },
       {
-        "author_name": "Ellicott C. Matthay",
-        "author_inst": "Department of Epidemiology and Biostatistics, University of California, San Francisco"
+        "author_name": "Shin-Woo Kim",
+        "author_inst": "Kyungpook National University Hospital"
       },
       {
-        "author_name": "M. Maria Glymour",
-        "author_inst": "Department of Epidemiology and Biostatistics, University of California, San Francisco"
+        "author_name": "Eun-Rim Kang",
+        "author_inst": "Seegene Medical Foundation"
       },
       {
-        "author_name": "Jacqueline M. Torres",
-        "author_inst": "Department of Epidemiology and Biostatistics, University of California, San Francisco"
+        "author_name": "Yong-Jin Yang",
+        "author_inst": "Seegene Medical Foundation"
       },
       {
-        "author_name": "Alicia Fernandez",
-        "author_inst": "Department of Medicine, University of California, San Francisco"
+        "author_name": "Sun-Kyung Jung",
+        "author_inst": "Seegene Medical Foundation"
       },
       {
-        "author_name": "Kirsten Bibbins-Domingo",
-        "author_inst": "Department of Epidemiology and Biostatistics, University of California, San Francisco"
+        "author_name": "Sun-Hwa Lee",
+        "author_inst": "Seegene Medical Foundation"
+      },
+      {
+        "author_name": "Nackmoon Sung",
+        "author_inst": "Seegene Medical Foundation"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.12.17.20248362",
@@ -979379,21 +982718,77 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.12.17.20248382",
-    "rel_title": "Sub-national forecasts of COVID-19 vaccine acceptance across the UK: a large-scale cross-sectional spatial modelling study",
+    "rel_doi": "10.1101/2020.12.15.20247981",
+    "rel_title": "SIREN protocol: Impact of detectable anti-SARS-CoV-2 on the subsequent incidence of COVID-19 in 100,000 healthcare workers: do antibody positive healthcare workers have less reinfection than antibody negative healthcare workers?",
     "rel_date": "2020-12-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.17.20248382",
-    "rel_abs": "The rollout of COVID-19 vaccines has begun to at-risk populations around the world. It is currently unclear whether rejection of the vaccine will pose challenges for achieving herd/community immunity either through large-scale rejection or localised pockets. Here we predict uptake of the vaccine at unprecedented spatial resolution across the UK using a large-scale survey of over 17,000 individuals. Although the majority of the UK population would likely take the vaccine, there is substantial heterogeneity in uptake intent across the UK. Large urban areas, including London and North West England, females, Black or Black British ethnicities, and Polish-speakers are among the least accepting. This study helps identify areas and socio-demographic groups where vaccination levels may not reach those levels required for herd immunity. Identifying clusters of non-vaccinators is extremely important in the context of achieving herd immunity as vaccination \"cold-spots\" can amplify epidemic spread and disproportionately increase vaccination levels required for herd protection.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20247981",
+    "rel_abs": "BackgroundThe overall risk of reinfection in individuals who have previously had COVID-19 is unknown. To determine if prior SARS-CoV-2 infection (as determined by at least one positive commercial antibody test performed in a laboratory) in healthcare workers confers future immunity to reinfection, we are undertaking a large-scale prospective longitudinal cohort study of healthcare staff across the United Kingdom.\n\nMethodsPopulation and Setting: staff members of healthcare organisations working in hospitals in the UK\n\nAt recruitment, participants will have their serum tested for anti-SARS-CoV-2 at baseline and using these results will be initially allocated to either antibody positive or antibody negative cohorts. Participants will undergo antibody and viral RNA testing at 1-4 weekly intervals throughout the study period, and based on these results may move between cohorts. Any results from testing undertaken for other reasons (e.g. symptoms, contact tracing etc.) or prior to study entry will also be included. Individuals will complete enrolment and fortnightly questionnaires on exposures and symptoms. Follow-up will be for at least 12 months from study entry.\n\nOutcomeThe primary outcome of interest is a reinfection with SARS -CoV-2 during the study period. Secondary outcomes will include incidence and prevalence (both RNA and antibody) of SARS-CoV-2, viral genomics, viral culture, symptom history and antibody/neutralising antibody titres.\n\nConclusionThis large study will help us to understand the impact of the presence of antibodies on the risk of reinfection with SARS-CoV-2; the results will have substantial implications in terms of national and international policy, as well as for risk management of contacts of COVID-19 cases.\n\nTrial RegistrationIRAS ID 284460, HRA and Health and Care Research Wales approval granted 22 May 2020.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Alex de Figueiredo",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Sarah Wallace",
+        "author_inst": "Public Health England"
+      },
+      {
+        "author_name": "Victoria Hall",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Andre Charlett",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Peter D Kirwan",
+        "author_inst": "COVID-19 response, Public Health England, London, UK and MRC Biostatistics Unit, University of Cambridge, Cambridge, UK"
+      },
+      {
+        "author_name": "Michelle J Cole",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Madhumita Shrotri",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Sakib Rokadiya",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Blanche Oguti",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Amoolya Vusirikala",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Maria Zambon",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Tim Brooks",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Mary Ramsay",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Colin S Brown",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Meera A Chand",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
+      },
+      {
+        "author_name": "Susan Hopkins",
+        "author_inst": "COVID-19 response, Public Health England, London, UK"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -980921,43 +984316,39 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2020.12.17.423130",
-    "rel_title": "Suppression of miR-155 attenuates lung cytokine storm induced by SARS-CoV-2 infection in human ACE2-transgenic mice",
+    "rel_doi": "10.1101/2020.12.16.423166",
+    "rel_title": "Molecular diversity analysis of the spike glycoprotein (S) gene from Hong Kong - China",
     "rel_date": "2020-12-17",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.17.423130",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19) is a recent global pandemic. It is a deadly human viral disease, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a high rate of infection, morbidity and mortality. Therefore, there is a great urgency to develop new therapies to control, treat and prevent this disease. Endogenous microRNAs (miRNAs, miRs) of the viral host are key molecules in preventing viral entry and replication, and building an antiviral cellular defense. Here, we have analyzed the role of miR-155, one of the most powerful drivers of host antiviral responses including immune and inflammatory responses, in the pathogenicity of SARS-CoV-2 infection. Subsequently, we have analyzed the potency of anti-miR-155 therapy in a COVID-19 mouse model (mice transgenic for human angiotensin I-converting enzyme 2 receptor (tg-mice hACE2)). We report for the first time that miR-155 expression is elevated in COVID-19 patients. Further, our data indicate that the viral load as well as miR-155 levels are higher in male relative to female patients. Moreover, we find that the delivery of anti-miR-155 to SARS-CoV-2-infected tg-mice hACE2 effectively suppresses miR-155 expression, and leads to improved survival and clinical scores. Importantly, anti-miR-155-treated tg-mice hACE2 infected with SARS-CoV-2 not only exhibit reduced levels of pro-inflammatory cytokines, but also have increased anti-viral and anti-inflammatory cytokine responses in the lungs. Thus, our study suggests anti-miR-155 as a novel therapy for mitigating the lung cytokine storm induced by SARS-CoV-2 infection.",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.16.423166",
+    "rel_abs": "In this work, 37 haplotypes of spike glycoprotein of SARS-CoV-2 from Hong Kong, China, were used. All sequences were publicly available on the Platform of the National Center for Biotechnology Information (NCBI) and were analyzed for their Molecular Variance (AMOVA), haplotypic diversity, mismatch, demographic and spatial expansion, molecular diversity and time of evolutionary divergence. The results suggested that there was a low diversity among haplotypes, with very low numbers of transitions, transversions, indels-type mutations and with total absence of population expansion perceived in the neutrality tests. The estimators used in this study supported the uniformity among all the results found and confirm the evolutionary conservation of the gene, as well as its protein product, a fact that stimulates the use of therapies based on neutralizing antibodies, such as vaccines based on protein S.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Dharmendra Kumar Soni",
-        "author_inst": "Uniformed Services University of the Health Sciences"
-      },
-      {
-        "author_name": "Juan Cabrera-Luque",
-        "author_inst": "GeneDx"
+        "author_name": "Eduarda Doralice Alves Braz Da Silva",
+        "author_inst": "Laboratory of Population Genetics and Computational Evolutionary Biology - LaBECom, UNIVISA"
       },
       {
-        "author_name": "Swagata Kar",
-        "author_inst": "Bioqual Inc."
+        "author_name": "Dallynne Barbara Ramos Venancio",
+        "author_inst": "Laboratory of Population Genetics and Computational Evolutionary Biology - LaBECom, UNIVISA"
       },
       {
-        "author_name": "Chaitali Sen",
-        "author_inst": "Uniformed Services University of the Health Sciences"
+        "author_name": "Rosane Maria de Albuquerque",
+        "author_inst": "Laboratory of Population Genetics and Computational Evolutionary Biology - LaBECom, UNIVISA"
       },
       {
-        "author_name": "Joseph Devaney",
-        "author_inst": "GeneDx"
+        "author_name": "Robson da Silva Ramos",
+        "author_inst": "Laboratory of Population Genetics and Computational Evolutionary Biology - LaBECom, UNIVISA"
       },
       {
-        "author_name": "Roopa Biswas",
-        "author_inst": "Uniformed Services University of the Health Sciences"
+        "author_name": "Pierre Teodosio Felix Sr.",
+        "author_inst": "Laboratory of Population Genetics and Computational Evolutionary Biology - LaBECom, UNIVISA"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2020.12.15.422900",
@@ -982647,71 +986038,59 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.14.20248181",
-    "rel_title": "Predicting the need for escalation of care or death from repeated daily clinical observations and laboratory results in patients with SARS-CoV-2 during 2020: a retrospective population-based cohort study from the United Kingdom",
+    "rel_doi": "10.1101/2020.12.15.20248279",
+    "rel_title": "Shared genetic etiology between idiopathic pulmonary fibrosis and COVID-19 severity",
     "rel_date": "2020-12-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.14.20248181",
-    "rel_abs": "ObjectivesCurrently used prognostic tools for patients with SARS-CoV-2 infection are based on clinical and laboratory parameters measured at a single point in time, usually on admission. We aimed to determine how dynamic changes in clinical and laboratory parameters relate to SARS-CoV-2 prognosis.\n\nDesignretrospective, observational cohort study using routinely collected clinical data to model the dynamic change in prognosis of SARS-CoV-2.\n\nSettinga single, large hospital in England.\n\nParticipantsall patients with confirmed SARS-CoV-2 admitted to Nottingham University Hospitals (NUH) NHS Trust, UK from 1st February 2020 until 30th November 2020.\n\nMain outcome measuresIntensive Care Unit (ICU) admission, death and discharge from hospital.\n\nStatistical MethodsWe split patients into 1st (admissions until 30th June) and 2nd (admissions thereafter) waves. We incorporated all clinical observations, blood tests and other covariates from electronic patient records and follow up until death or 30 days from the point of hospital discharge. We modelled daily risk of admission to ICU or death with a time varying Cox proportional hazards model.\n\nResults2,964 patients with confirmed SARS-CoV-2 were included. Of 1,374 admitted during the 1st wave, 593 were eligible for ICU escalation, and 466 had near complete ascertainment of all covariates at admission. Our validation sample included 1,590 confirmed cases, of whom 958 were eligible for ICU admission. Our model had good discrimination of daily need for ICU admission or death (C statistic = 0.87 (IQR 0.85-0.90)) and predicted this daily prognosis better than previously published scores (NEWS2, ISCARIC 4C). In validation in the 2nd wave the score overestimated escalation (calibration slope 0.55), whilst retaining a linear relationship and good discrimination (C statistic = 0.88 (95% CI 0.81 -0.95)).\n\nConclusionsA bespoke SARS-CoV-2 escalation risk prediction score can predict need for clinical escalation better than a generic early warning score or a single estimation of risk at admission.\n\nWhat is already known on this topicSARS-CoV-2 is a recently emerged viral infection, which presents typically with flu like symptoms, can have severe sequelae and has caused a pandemic during 2020.\n\nA number of risk factors for poor outcomes including obesity, age and comorbidity have been recognized.\n\nRisk scores have been developed to stratify risk of poor outcome for patients with SARS-CoV-2 at admission, but these do not take account of dynamic changes in severity of disease on a daily basis.\n\nWhat this study addsWe have developed a dynamic risk score to predict escalation to ICU or death within the next 24 hours.\n\nOur score has good discrimination between those who will and not require ICU admission (or die) in both our derivation and validation cohorts.\n\nOur bespoke SARS-CoV-2 escalation risk prediction score can predict need for clinical escalation better than a generic early warning score or a single estimation of risk at admission.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.15.20248279",
+    "rel_abs": "BackgroundIdiopathic pulmonary fibrosis (IPF) is a complex lung disease, characterized by progressive lung scarring. Severe COVID-19 is associated with substantial pneumonitis and has a number of shared major risk factors with IPF. This study aimed to determine the genetic correlation between IPF and severe COVID-19 and assess a potential causal role of genetically increased risk of IPF on COVID-19 severity.\n\nMethodsWe performed a Mendelian randomisation (MR) study for IPF causality in COVID-19. Genetic variants associated with IPF susceptibility (P<5x10-8) in previous genome-wide association studies (GWAS) were used as instrumental variables (IVs). Effect estimates of those IVs on COVID-19 severity were gathered from the GWAS meta-analysis by the COVID-19 Host Genetics Initiative. The genetic correlation between IPF and COVID-19 severity was estimated with linkage disequilibrium (LD) score regression.\n\nFindingsWe detected a positive genetic correlation of IPF with COVID-19 severity (rg=0.31 [95% CI 0.04-0.57], P = 0.023). The MR estimates for severe COVID-19 did not reveal any genetic association (OR 1.05, [95% CI 0.92-1.20], P = 0.43). However, outlier analysis revealed that the IPF risk allele rs35705950 at MUC5B had a different effect compared with the other variants. When rs35705950 was excluded, MR results provided evidence that genetically increased risk of IPF has a causal effect on COVID-19 severity (OR 1.21, [95% CI 1.06-1.38], P = 4.24x10-3). Furthermore, the IPF risk-allele at MUC5B showed an apparent protective effect against COVID-19 hospitalization only in older adults (OR 0.86, [95% CI 0.73-1.00], P = 2.99x10-2).\n\nInterpretationThe strongest genetic determinant of IPF, rs35705950 at MUC5B, seems to confer protection against COVID-19, whereas the combined effect of all other IPF risk loci seem to confer risk of COVID-19 severity. The observed effect of rs35705950 could either be due to protective effects of mucin over-production on the airways or a consequence of selection bias due to a patient group that is heavily enriched for the rs35705950 T undertaking strict self-isolation. Due to the diverse impact of IPF causal variants on SARS-CoV-2 infection, further investigation is needed to address this apparent paradox between variance at MUC5B and other IPF genetic risk factors.\n\nFundingNovo Nordisk Foundation and Oak Foundation.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Colin J Crooks",
-        "author_inst": "University of Nottingham"
-      },
-      {
-        "author_name": "Joe West",
-        "author_inst": "University of Nottingham"
-      },
-      {
-        "author_name": "Andrew Fogarty",
-        "author_inst": "University of Nottingham"
-      },
-      {
-        "author_name": "Joanne R Morling",
-        "author_inst": "University of Nottingham"
+        "author_name": "Joao Fadista",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Matthew J Grainge",
-        "author_inst": "University of Nottingham"
+        "author_name": "Luke M. Kraven",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Sherif Gonem",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Juha Karjalainen",
+        "author_inst": "Institute for Molecular Medicine Finland (FIMM)"
       },
       {
-        "author_name": "Mark Simmonds",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Shea J. Andrews",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Andrea Race",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Frank Geller",
+        "author_inst": "Statens Serum Institut"
       },
       {
-        "author_name": "Irene Juurlink",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "- The COVID-19 Host Genetics Initiative",
+        "author_inst": "-"
       },
       {
-        "author_name": "Stephen Briggs",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "J Kenneth Baillie",
+        "author_inst": "Roslin Institute"
       },
       {
-        "author_name": "Simon Cruikshank",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Louise V. Wain",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Susan Hammond-Pears",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "R. Gisli Jenkins",
+        "author_inst": "University of Nottingham"
       },
       {
-        "author_name": "Timothy R Card",
-        "author_inst": "University of Nottingham"
+        "author_name": "Bjarke Feenstra",
+        "author_inst": "Statens Serum Institut"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "genetic and genomic medicine"
   },
   {
     "rel_doi": "10.1101/2020.12.15.20248214",
@@ -984325,31 +987704,155 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.12.14.422793",
-    "rel_title": "Genomic diversity analysis of SARS-CoV-2 genomes in Rwanda",
-    "rel_date": "2020-12-15",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.14.422793",
-    "rel_abs": "COVID-19 (Coronavirus disease 2019) is an emerging pneumonia-like respiratory disease of humans and is recently spreading across the globe.\n\nObjectiveTo analyze the genome sequence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) isolated from Rwanda with other viral strains from African countries.\n\nMethodsWe downloaded 75 genomes sequences of clinical SARS-CoV-2 from the GISAID (global initiative on sharing all influenza data) database and we comprehensively analyzed these SARS-CoV-2 genomes sequences alongside with Wuhan SARS-CoV-2 sequences as the reference strains.\n\nResultsWe analyzed 75 genomes sequences of SARS-CoV-2 isolated in different African countries including 10 samples of SARS-CoV-2 isolated in Rwanda between July and August 2020. The phylogenetic analysis of the genome sequence of SARS-CoV-2 revealed a strong identity with reference strains between 90-95%. We identified a missense mutation in four proteins including orf1ab polyprotein, NSP2, 2-O-ribose methyltransferase and orf1a polyprotein. The most common changes in the base are C > T. We also found that all clinically SARS-CoV-2 isolated from Rwanda had genomes belonging to clade G and lineage B.1.\n\nConclusionsTracking the genetic evolution of SARS-CoV-2 over time is important to understand viral evolution pathogenesis. These findings may help to implement public health measures in curbing COVID-19 in Rwanda.",
-    "rel_num_authors": 3,
+    "rel_doi": "10.1101/2020.12.10.20245944",
+    "rel_title": "Azithromycin in Hospitalised Patients with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial",
+    "rel_date": "2020-12-14",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20245944",
+    "rel_abs": "BackgroundAzithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatory actions. We evaluated the efficacy and safety of azithromycin in hospitalised patients with COVID-19.\n\nMethodsIn this randomised, controlled, open-label, adaptive platform trial, several possible treatments were compared with usual care in patients hospitalised with COVID-19 in the UK. Eligible and consenting patients were randomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once daily by mouth or intravenously for 10 days or until discharge (or one of the other treatment arms). Patients were twice as likely to be randomised to usual care as to any of the active treatment groups. The primary outcome was 28-day mortality. The trial is registered with ISRCTN (50189673) and clinicaltrials.gov (NCT04381936).\n\nFindingsBetween 7 April and 27 November 2020, 2582 patients were randomly allocated to receive azithromycin and 5182 patients to receive usual care alone. Overall, 496 (19%) patients allocated to azithromycin and 997 (19%) patients allocated to usual care died within 28 days (rate ratio 1{middle dot}00; 95% confidence interval [CI] 0{middle dot}90-1{middle dot}12; p=0{middle dot}99). Consistent results were seen in all pre-specified subgroups of patients. There was no difference in duration of hospitalisation (median 12 days vs. 13 days) or the proportion of patients discharged from hospital alive within 28 days (60% vs. 59%; rate ratio 1{middle dot}03; 95% CI 0{middle dot}97-1{middle dot}10; p=0{middle dot}29). Among those not on invasive mechanical ventilation at baseline, there was no difference in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (21% vs. 22%; risk ratio 0{middle dot}97; 95% CI 0{middle dot}89-1{middle dot}07; p=0{middle dot}54).\n\nInterpretationIn patients hospitalised with COVID-19, azithromycin did not provide any clinical benefit. Azithromycin use in patients hospitalised with COVID-19 should be restricted to patients where there is a clear antimicrobial indication.\n\nFundingUK Research and Innovation (Medical Research Council) and National Institute of Health Research (Grant ref: MC_PC_19056).",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Nzungize Lambert",
-        "author_inst": "Synthetic Biology Rwanda"
+        "author_name": "Peter W Horby",
+        "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Alistair Roddick",
+        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Enti Spata",
+        "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Natalie Staplin",
+        "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Jonathan R Emberson",
+        "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Guilherme Pessoa-Amorim",
+        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Leon Peto",
+        "author_inst": "Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Mark Campbell",
+        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Christopher Brightling",
+        "author_inst": "Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom"
+      },
+      {
+        "author_name": "Ben Prudon",
+        "author_inst": "Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom"
+      },
+      {
+        "author_name": "David Chadwick",
+        "author_inst": "Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom"
+      },
+      {
+        "author_name": "Andrew Ustianowski",
+        "author_inst": "North Manchester General Hospital & University of Manchester, Manchester, United Kingdom"
       },
       {
-        "author_name": "Ndishimye Pacifique",
-        "author_inst": "Rwanda Joint Task Force COVID-19, Rwanda Biomedical Center, Ministry of Health, Kigali, Rwanda."
+        "author_name": "Abdul Ashish",
+        "author_inst": "Wrightington Wigan and Leigh NHS Foundation Trust, Wigan, United Kingdom"
       },
       {
-        "author_name": "Fathiah Zakham",
-        "author_inst": "Laboratory of Virology, University of Helsinki, Helsinki 00014, Finland."
+        "author_name": "Stacy Todd",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom"
+      },
+      {
+        "author_name": "Bryan Yates",
+        "author_inst": "Northumbria Healthcare NHS Foundation Trust, North Tyneside, United Kingdom"
+      },
+      {
+        "author_name": "Robert Buttery",
+        "author_inst": "North West Anglia NHS Foundation Trust, Peterborough, United Kingdom"
+      },
+      {
+        "author_name": "Stephen Scott",
+        "author_inst": "The Countess of Chester Hospital NHS Foundation Trust, Chester, United Kingdom"
+      },
+      {
+        "author_name": "Diego Maseda",
+        "author_inst": "Mid Cheshire Hospitals NHS Foundation Trust, Crewe, United Kingdom"
+      },
+      {
+        "author_name": "J Kenneth Baillie",
+        "author_inst": "Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom"
+      },
+      {
+        "author_name": "Maya H Buch",
+        "author_inst": "Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom"
+      },
+      {
+        "author_name": "Lucy C Chappell",
+        "author_inst": "School of Life Sciences, King's College London, London, United Kingdom"
+      },
+      {
+        "author_name": "Jeremy N Day",
+        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Saul N Faust",
+        "author_inst": "NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, "
+      },
+      {
+        "author_name": "Thomas Jaki",
+        "author_inst": "Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; MRC Biostatistics Unit, University of Cambridge, Cambridge, United Ki"
+      },
+      {
+        "author_name": "Katie Jeffery",
+        "author_inst": "Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Edmund Juszczak",
+        "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom"
+      },
+      {
+        "author_name": "Wei Shen Lim",
+        "author_inst": "Respiratory Medicine Department, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom"
+      },
+      {
+        "author_name": "Alan Montgomery",
+        "author_inst": "School of Medicine, University of Nottingham, Nottingham, United Kingdom"
+      },
+      {
+        "author_name": "Andrew Mumford",
+        "author_inst": "School of Cellular and Molecular Medicine, University of Bristol, Bristol, United kingdom"
+      },
+      {
+        "author_name": "Kathryn Rowan",
+        "author_inst": "Intensive Care National Audit & Research Centre, London, United Kingdom"
+      },
+      {
+        "author_name": "Guy Thwaites",
+        "author_inst": "Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Marion Mafham",
+        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Richard Haynes",
+        "author_inst": "MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
+      },
+      {
+        "author_name": "Martin J Landray",
+        "author_inst": "Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc_by",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.12.12.20248070",
@@ -985955,45 +989458,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.14.20248160",
-    "rel_title": "Acceptability and feasibility of strategies to shield the vulnerable during the COVID-19 outbreak: a qualitative study in six Sudanese communities",
+    "rel_doi": "10.1101/2020.12.11.20247262",
+    "rel_title": "COVID-19 in persons affected by Hansen's disease in Brazil",
     "rel_date": "2020-12-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.14.20248160",
-    "rel_abs": "BackgroundShielding of high-risk groups from coronavirus disease (COVID-19), either within their households or safe communal structures, has been suggested as a realistic alternative to severe movement restrictions in response to the COVID-19 epidemic in low-income countries. To our knowledge, this concept has not been tested or evaluated in resource-poor settings. This study aimed to explore the acceptability and feasibility of strategies to shield persons at higher risk of severe COVID-19 outcomes, during the COVID-19 epidemic in six communities in Sudan.\n\nMethodsWe purposively sampled participants from six communities, illustrative of urban, rural and forcibly-displaced settings. In-depth telephone interviews were held with 59 members of households with one or more members at higher risk of severe COVID-19 outcomes. Follow-up interviews were held with 30 community members after movement restrictions were eased across the country. All interviews were audio-recorded, transcribed verbatim, and analysed using a two-stage deductive and inductive thematic analysis.\n\nResultsMost participants were aware that some people are at higher risk of severe COVID-19 outcomes but were unaware of the concept of shielding. Most participants found shielding acceptable and consistent with cultural inclinations to respect elders and protect the vulnerable. However, extra-household shielding arrangements were mostly seen as socially unacceptable. Participants reported feasibility concerns related to the social isolation of shielded persons and loss of income for shielding families. The acceptability and feasibility of shielding strategies were reduced after movement restrictions were eased, as participants reported lower perception of risk in their communities and increased pressure to comply with social commitments outside the house.\n\nConclusionShielding is generally acceptable in the study communities. Acceptability is influenced by feasibility, and by contextual changes in the epidemic and associated policy response. The promotion of shielding should capitalise on the cultural and moral sense of duty towards elders and vulnerable groups. Communities and households should be provided with practical guidance to implement feasible shielding options. Households must be socially, psychologically and financially supported to adopt and sustain shielding effectively.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.11.20247262",
+    "rel_abs": "BackgroundHansens disease (HD) is endemic in Brazil, a country with the third highest number of COVID-19 cases in the world and the second highest number of COVID-19 deaths. COVID-19 in persons affected by HD has not been described at population level in this country.\n\nMethodsWe collated numbers of COVID-19 cases and deaths among patients who were receiving routine treatment for HD at six centres across Brazil (Belem, Bauru, Brasilia, Vitoria, Petrolina, Palmas) between 1st March and 10th December 2020.\n\nResultsOf 1,333 HD patients receiving treatment, 70 (5.2%) reported having had COVID-19. Almost all patients (97% (1,296/1,333)) including all but one of the COVID-19 cases were receiving MDT comprising rifampicin (600mg once per month), dapsone (100mg daily), and clofazimine (50 mg daily plus 300 mg once per month). Four patients died, including a patient in their 30s on MDT who had a severe type 2 HD reaction (erythema nodosum leprosum) and who was taking clofazimine 100mg daily.\n\nConclusionsWe cannot determine from these preliminary data whether persons affected by Hansens disease have a higher or lower risk of COVID-19 and related mortality compared with the general population. We will continue to monitor the effects of COVID-19 in persons affected by and treated for HD and extend this to monitor SARS-CoV-2 vaccine effectiveness in this group of patients.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Nada Abdelmagid",
-        "author_inst": "London School of Hygiene and Tropical Medicine, (Department of Infectious Disease Epidemiology), London, (London), United Kingdom / Sudan COVID-19 Research Grou"
+        "author_name": "Patr\u00edcia Deps",
+        "author_inst": "Universidade Federal do Esp\u00edrito Santo"
       },
       {
-        "author_name": "Salma A.E. Ahmed",
-        "author_inst": "Independent public health researcher, Khartoum, (Khartoum), Sudan / Sudan COVID-19 Research Group"
+        "author_name": "Taynah Repsold",
+        "author_inst": "Universidade Federal do Esp\u00edrito Santo"
       },
       {
-        "author_name": "Nazik Nurelhuda",
-        "author_inst": "University of Khartoum, Faculty of Dentistry, Khartoum, (Khartoum), Sudan / Sudan COVID-19 Research Group"
+        "author_name": "Claudio Salgado",
+        "author_inst": "Universidade Federal do Par\u00e1"
       },
       {
-        "author_name": "Israa Zainalabdeen",
-        "author_inst": "Y-PEER Sudan, Khartoum, (Khartoum), Sudan / Sudan COVID-19 Research Group"
+        "author_name": "Raquel de Carvalho Bouth",
+        "author_inst": "Universidade Federal do Par\u00e1"
       },
       {
-        "author_name": "Aljaile Ahmed",
-        "author_inst": "Y-PEER Sudan, Khartoum, (Khartoum), Sudan / Sudan COVID-19 Research Group"
+        "author_name": "Selma Regina Penha Silva Cerqueira",
+        "author_inst": "Universidade de Bras\u00edlia"
       },
       {
-        "author_name": "Mahmoud Ali Fadlallah",
-        "author_inst": "Asian Institute of Technology, Bangkok, (Bangkok), Thailand / Public Health Institute (PHI), Khartoum, (Khartoum), Sudan / Sudan COVID-19 Research Group"
+        "author_name": "Marisa Simon Brezinscki",
+        "author_inst": "Hospital da Santa Casa de Miseric\u00f3rdia de Vit\u00f3ria"
       },
       {
-        "author_name": "Maysoon Dahab",
-        "author_inst": "London School of Hygiene and Tropical Medicine, (Department of Infectious Disease Epidemiology), London, (London), United Kingdom / Sudan COVID-19 Research Grou"
+        "author_name": "Rebeca Ruppert Galarda Baptista Peixoto",
+        "author_inst": "Hospital da Santa Casa de Miseric\u00f3rdia de Vit\u00f3ria"
+      },
+      {
+        "author_name": "Jaison Antonio Barreto",
+        "author_inst": "Instituto Lauro de Souza Lima"
+      },
+      {
+        "author_name": "Andrea Fonseca",
+        "author_inst": "Servi\u00e7o de Infectologia de Petrolina"
+      },
+      {
+        "author_name": "Marlene Peixoto",
+        "author_inst": "Secretaria Municipal de Sa\u00fade de Petrolina"
+      },
+      {
+        "author_name": "Seyna Ueno Mendes",
+        "author_inst": "Secretaria Municipal de Sa\u00fade de Palmas"
+      },
+      {
+        "author_name": "Rafael Pereira Rabelo Mendes",
+        "author_inst": "Secretaria Municipal de Sa\u00fade de Palmas"
+      },
+      {
+        "author_name": "Pedro Paulo dos Santos Oliveira",
+        "author_inst": "Secretaria Municipal de Sa\u00fade de Palmas"
+      },
+      {
+        "author_name": "Ciro Martins Gomes",
+        "author_inst": "Universidade de Bras\u00edlia"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -987668,51 +991199,35 @@
     "category": "rehabilitation medicine and physical therapy"
   },
   {
-    "rel_doi": "10.1101/2020.11.22.20235184",
-    "rel_title": "Neurological Disorders associated with COVID-19 Hospital Admissions : Experience of a Single Tertiary Healthcare Centre",
+    "rel_doi": "10.1101/2020.12.08.20246140",
+    "rel_title": "How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19",
     "rel_date": "2020-12-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.22.20235184",
-    "rel_abs": "BackgroundEarly reports have detailed a range of neurological symptoms in patients with the SARS-CoV-2 infection. However, there is a lack of detailed description and incidence of the neurological disorders amongst hospitalized COVID-19 patients. We describe a range of neurological disorders (other than non-specific neurological symptoms), including their clinical, radiological and laboratory findings, encountered in our cohort of COVID-19 patients admitted to a large tertiary institution.\n\nMethodsWe reviewed our prospectively collated database of all adult Neurology referrals, Neurology and Stroke admissions and Neurological multi-disciplinary team meetings for all hospitalized patients with suspected or proven COVID-19 from 17 March 2020 to 31 August 2020.\n\nResultsTwenty-nine of 1243 COVID-19 inpatients (2.3%) presented with COVID-19-related neurological disorders. The mean age was 68.9 +/- 13.5(SD) years, age range of 34-97 years, and there were 16 males. 22 patients had confirmed, 5 were probable and 2 had suspected COVID-19 infection according to the WHO case classification. Eight patients (27%) required critical care admission. Neurological symptoms at presentation included acute confusion and delirium, seizures, and new focal neurological deficits. Based on the pre-defined neurological phenotype, COVID-19 patients were grouped into four main categories. 16 patients had cerebrovascular events (13 with acute ischaemic stroke and 3 had haemorrhagic features), 7 patients were found to have inflammatory, non-inflammatory and autoimmune encephalopathy (including 2 with known Multiple Sclerosis), whilst disorders of movement and peripheral nervous system were diagnosed in 3 patients each.\n\nConclusionAlthough the exact prevalence and aetiology remain unclear, new onset of neurological disorders, in addition to anosmia, is non-sporadic during the acute COVID-19-infection. Longitudinal follow-up of these patients is required to determine the clinical and functional outcome, treatment response and long-term effects of the SARS-CoV-2 infection.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.08.20246140",
+    "rel_abs": "To combat the COVID-19 pandemic, many countries have adopted digital contact tracing apps. Various technologies exist to trace contacts that are potentially prone to different types of tracing errors. Here, we study the impact of different proximity detection ranges on the effectiveness and efficiency of digital contact tracing apps. Furthermore, we study a usage stop effect induced by a false positive quarantine. Our results reveal that policy makers should adjust digital contact tracing apps to the behavioral characteristics of a society. Based on this, the proximity detection range should at least cover the range of a disease spread, and be much wider in certain cases. The widely used Bluetooth Low Energy protocol may not necessarily be the most effective option in its current setting.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Permesh Singh Dhillon",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Robert Dineen",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Haley Morris",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Radu Tanasescu",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Esmaeil Nikfekr",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Konstantin D Pandl",
+        "author_inst": "Karlsruhe Institute of Technology"
       },
       {
-        "author_name": "Jonathan Evans",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Scott Thiebes",
+        "author_inst": "Karlsruhe Institute of Technology"
       },
       {
-        "author_name": "Cris S Constantinescu",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Manuel Schmidt-Kraepelin",
+        "author_inst": "Karlsruhe Institute of Technology"
       },
       {
-        "author_name": "Akram A Hosseini",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Ali Sunyaev",
+        "author_inst": "Karlsruhe Institute of Technology"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "neurology"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2020.12.08.20246132",
@@ -989522,125 +993037,29 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.12.10.20246884",
-    "rel_title": "SARS-CoV-2/COVID-19 hospitalised patients in Switzerland: a prospective cohort profile",
+    "rel_doi": "10.1101/2020.12.09.20246363",
+    "rel_title": "Risk of adverse outcomes with COVID-19 in the Republic of Ireland",
     "rel_date": "2020-12-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20246884",
-    "rel_abs": "BackgroundSARS-CoV-2/COVID-19, which emerged in China in late 2019, rapidly spread across the world causing several million victims in 213 countries. Switzerland was severely hit by the virus, with 43000 confirmed cases as of September 1st, 2020.\n\nAimIn cooperation with the Federal Office of Public Health, we set up a surveillance database in February 2020 to monitor hospitalised patients with COVID-19 in addition to their mandatory reporting system.\n\nMethodsPatients hospitalised for more than 24 hours with a positive PCR test, from 20 Swiss hospitals, are included. Data collection follows a custom Case Report Form based on WHO recommendations and adapted to local needs. Nosocomial infections were defined as infections for which the onset of symptoms started more than 5 days after the patients admission date.\n\nResultsAs of September 1st, 2020, 3645 patients were included. Most patients were male (2168 - 59.5%),and aged between 50 and 89 years (2778 - 76.2%), with a median age of 68 (IQR 54-79). Community infections dominated with 3249 (89.0%) reports. Comorbidities were frequently reported: hypertension (1481 - 61.7%), cardiovascular diseases (948 - 39.5%), and diabetes (660 - 27.5%) being the most frequent in adults; respiratory diseases and asthma (4 -21.1%), haematological and oncological diseases (3 - 15.8%) being the most frequent in children. Complications occurred in 2679 (73.4%) episodes, mostly for respiratory diseases (2470 - 93.2% in adults, 16 - 55.2% in children), renal (681 - 25.7%) and cardiac (631 - 23.8%) complication for adults. The second and third most frequent complications in children affected the digestive system and the liver (7 - 24.1%). A targeted treatment was given in 1299 (35.6%) episodes, mostly with hydroxychloroquine (989 - 76.1%). Intensive care units stays were reported in 578 (15.8%) episodes. 527 (14.5%) deaths were registered, all among adults.\n\nConclusionThe surveillance system has been successfully initiated and provides a very representative set of data for Switzerland. We therefore consider it to be a valuable addition to the existing mandatory reporting, providing more precise information on the epidemiology, risk factors, and clinical course of these cases.",
-    "rel_num_authors": 28,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.09.20246363",
+    "rel_abs": "AimsTo compare the risk of adverse outcomes (i.e. hospital/intensive care admission, death) in population sub-groups during two periods of the COVID-19 pandemic in the Republic of Ireland.\n\nMethodsWe analysed routinely-collected, publicly-available data on 67,900 people with laboratory confirmed COVID-19 infection between 29th Feb to 14th Nov 2020. This period encompassed two waves of infection and two corresponding national lockdowns. For two observational periods covering each wave (W1, W2), each ending 17-19 days before implementation of high-level national restrictions, we segmented the population based on age and underlying clinical conditions.\n\nResultsThe prevalence of laboratory confirmed COVID-19 was 1.4%. The risk of admission to hospital, admission to intensive care, and death was 7.2%, 0.9%, and 2.5%, respectively. Compared to younger confirmed cases, those aged [&ge;]65 y had increased risk of hospital admission (RR 5.61), ICU admission (RR 3.56), and death (RR 60.8). W2 was associated with more cases and fewer adverse events than W1. The risk of all adverse outcomes was reduced in W2 than in W1.\n\nConclusionsOngoing responses should consider the variation in risk of adverse outcomes between specific sub-groups. These findings indicate the need to sustain the prevention, identification and management of noncommunicable diseases to reduce the burden of COVID-19.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Amaury Thiabaud",
-        "author_inst": "Institut de Sant\u00e9 Globale, Facult\u00e9 de M\u00e9decine de l'Universit\u00e9 de Gen\u00e8ve, Geneva, Switzerland"
-      },
-      {
-        "author_name": "Anne Iten",
-        "author_inst": "Service de pr\u00e9vention et contr\u00f4le de l'infection, Direction m\u00e9dicale et qualit\u00e9, HUG, Geneva, Switzerland"
-      },
-      {
-        "author_name": "Carlo Balmelli",
-        "author_inst": "Infection Control Programme, EOC Hospitals, Ticino, Switzerland"
-      },
-      {
-        "author_name": "Laurence Senn",
-        "author_inst": "Service de m\u00e9decine pr\u00e9ventive hospitali\u00e8re, CHUV, Lausanne, Switzerland"
-      },
-      {
-        "author_name": "Nicolas Troillet",
-        "author_inst": "Service of Infectious Diseases, Central Institute, Valais Hospitals, Sion, Switzerland"
-      },
-      {
-        "author_name": "Andreas Widmer",
-        "author_inst": "Department of Infectious Diseases, University Hospital Basel, Basel, Switzerland"
-      },
-      {
-        "author_name": "Domenica Flury",
-        "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland"
-      },
-      {
-        "author_name": "Peter W. Schreiber",
-        "author_inst": "Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland"
-      },
-      {
-        "author_name": "Miriam V\u00e1zquez",
-        "author_inst": "Department of Infectious Diseases, Bern University Hospital (Inselspital), Bern, Switzerland"
-      },
-      {
-        "author_name": "Lauro Damonti",
-        "author_inst": "Department of Infectious Diseases, Bern University Hospital (Inselspital), Bern, Switzerland"
-      },
-      {
-        "author_name": "Michael Buettcher",
-        "author_inst": "Paediatric Infectious Diseases, Department of Paediatrics, Children's Hospital, Cantonal Hospital Lucerne, Switzerland"
-      },
-      {
-        "author_name": "Danielle Vuichard-Gysin",
-        "author_inst": "Department of Infectious Diseases, Thurgau Cantonal Hospital, Thurgau, Switzerland"
-      },
-      {
-        "author_name": "Christoph Kuhm",
-        "author_inst": "Department of Infectious Diseases, Thurgau Cantonal Hospital, Thurgau, Switzerland"
-      },
-      {
-        "author_name": "Alexia Cusini",
-        "author_inst": "Department of Infectious Diseases, Cantonal Hospital Graubuenden, Chur, Switzerland"
-      },
-      {
-        "author_name": "Thomas Riedel",
-        "author_inst": "Department of Pediatrics, Cantonal Hospital Graubuenden, Chur, Switzerland"
-      },
-      {
-        "author_name": "Yvonne Nussbaumer",
-        "author_inst": "Klinik f\u00fcr Innere Medizin, Kantonsspital Spit\u00e4ler Schaffhausen, Schaffhausen, Switzerland"
-      },
-      {
-        "author_name": "Roman Gaudenz",
-        "author_inst": "Innere Medizin und Infektiologie, Kantonsspital Nidwalden, Stans, Switzerland"
-      },
-      {
-        "author_name": "Ulrich Heininger",
-        "author_inst": "Infectious Diseases and Vaccinology, University of Basel Children's Hospital, Basel, Switzerland"
-      },
-      {
-        "author_name": "Christoph Berger",
-        "author_inst": "Division of Infectious Diseases, and Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland"
-      },
-      {
-        "author_name": "Franziska Zucol",
-        "author_inst": "Paediatric Infectious Diseases, Department of Paediatrics, Cantonal Hospital Winterthur, Winterthur, Switzerland"
-      },
-      {
-        "author_name": "Sara Bernhard-Stirnemann",
-        "author_inst": "Children's Hospital Aarau, Aarau, Switzerland"
-      },
-      {
-        "author_name": "Natascia Corti",
-        "author_inst": "Unit of General Internal Medicine, Hirslanden Clinic, Zurich, Switzerland"
-      },
-      {
-        "author_name": "Petra Zimmermann",
-        "author_inst": "Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland; and Department of Paediatrics, Fribourg Hospital HFR, Fribourg, Switzerland"
-      },
-      {
-        "author_name": "Anita Uka",
-        "author_inst": "Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland; and Department of Paediatrics, Fribourg Hospital HFR, Fribourg, Switzerland"
-      },
-      {
-        "author_name": "Anita Niederer-Loher",
-        "author_inst": "Children's Hospital of Eastern Switzerland, St. Gallen, Switzerland"
+        "author_name": "Mark Roe",
+        "author_inst": "University College Dublin"
       },
       {
-        "author_name": "C\u00e9line Gardiol",
-        "author_inst": "Swiss Federal Office of Public Health, Bern, Switzerland"
+        "author_name": "Patrick Wall",
+        "author_inst": "University College Dublin"
       },
       {
-        "author_name": "Maroussia Roelens",
-        "author_inst": "Institut de Sant\u00e9 Globale, Facult\u00e9 de M\u00e9decine de l'Universit\u00e9 de Gen\u00e8ve, Geneva, Switzerland"
+        "author_name": "Patrick Mallon",
+        "author_inst": "University College Dublin"
       },
       {
-        "author_name": "Olivia Keiser",
-        "author_inst": "Institut de Sant\u00e9 Globale, Facult\u00e9 de M\u00e9decine de l'Universit\u00e9 de Gen\u00e8ve, Geneva, Switzerland"
+        "author_name": "Mary Horgan",
+        "author_inst": "University College Cork"
       }
     ],
     "version": "1",
@@ -991316,35 +994735,63 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.10.20247361",
-    "rel_title": "COVID-19 prediction in South Africa: Understanding the unascertained cases -- the hidden part of the epidemiological iceberg",
+    "rel_doi": "10.1101/2020.12.10.20247247",
+    "rel_title": "Mathematical modelling projections versus the actual course of the COVID-19 epidemic following the nationwide lockdown in Kyrgyzstan",
     "rel_date": "2020-12-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20247361",
-    "rel_abs": "Understanding the impact of non-pharmaceutical interventions as well as acscounting for the unascertained cases remain critical challenges for epidemiological models for understanding the transmission dynamics of COVID-19 spread. In this paper, we propose a new epidemiological model (eSEIRD) that extends the widely used epidemiological models such as extended Susceptible-Infected-Removed model (eSIR) and SAPHIRE (initially developed and used for analyzing data from Wuhan). We fit these models to the daily ascertained infected (and removed) cases from March 15, 2020 to Dec 31, 2020 in South Africa that reported the largest number of confirmed COVID-19 cases and deaths from the WHO African region. Using the eSEIRD model, the COVID-19 transmission dynamics in South Africa was characterized by the estimated basic reproduction number (R0) starting at 3.22 (95%CrI: [3.19, 3.23]) then dropping below 2 following a mandatory lockdown implementation and subsequently increasing to 3.27 (95%CrI: [3.27, 3.27]) by the end of 2020. The initial decrease of effective reproduction number followed by an increase suggest the effectiveness of early interventions and the combined effect of relaxing strict interventions and emergence of a new coronavirus variant in South Africa. The low estimated ascertainment rate was found to vary from 1.65% to 9.17% across models and time periods. The overall infection fatality ratio (IFR) was estimated as 0.06% (95%CrI: [0.04%, 0.22%]) accounting for unascertained cases and deaths while the reported case fatality ratio was 2.88% (95% CrI: [2.45%, 6.01%]). The models predict that from December 31, 2020, to April 1, 2021, the predicted cumulative number of infected would reach roughly 70% of total population in South Africa. Besides providing insights on the COVID-19 dynamics in South Africa, we develop powerful forecasting tools that enable estimation of ascertainment rates and IFR while quantifying the effect of intervention measures on COVID-19 spread.\n\nAMS ClassificationPlace Classification here. Leave as is, if there is no classification",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20247247",
+    "rel_abs": "Kyrgyzstan was placed under a two-month, nationwide lockdown due to the COVID-19 epidemic, starting on March 25, 2020. Given the highly disruptive effects of the lockdown on the national economy and peoples lives, the government decided not to extend lockdown beyond the initially planned date of May 10, 2020. The strategy chosen by the government was close to the input parameters of our models baseline scenario,  full lockdown release, which we presented to policymakers in April 2020, along with various other hypothetical scenarios with managed lockdown release options. To explore whether our model could accurately predict the actual course of the epidemic following the release of lockdown, we compared the outputs of the baseline scenario, such as new cases, deaths, and demand for and occupancy of hospital beds, with actual official reports. Our analysis revealed that the model could accurately predict the timing of the epidemic peak, with a difference of just two weeks, although the magnitude of the peak was overestimated compared with the official statistics. However, it is important to note that the accuracy of the official reports remains debatable, so outputs relating to the size of the epidemic and related pressures on the health system will need to be updated if new evidence becomes available.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Xuelin Gu",
-        "author_inst": "Department of Biostatistics, University of Michigan"
+        "author_name": "Ainura Moldokmatova",
+        "author_inst": "Univeristy of Oxford"
       },
       {
-        "author_name": "Bhramar Mukherjee",
-        "author_inst": "Department of Biostatistics, University of Michigan; Department of Epidemiology, University of Michigan"
+        "author_name": "Aida Estebesova",
+        "author_inst": "USAID Mission in the Kyrgyz Republic"
+      },
+      {
+        "author_name": "Aizhan Dooronbekova",
+        "author_inst": "Public Fund Institution of Social Development in the Kyrgyz Republic"
+      },
+      {
+        "author_name": "Chynar Zhumalieva",
+        "author_inst": "Public Fund Institution of Social Development in the Kyrgyz Republic"
       },
       {
-        "author_name": "Sonali Das",
-        "author_inst": "Department of Business Management, University of Pretoria"
+        "author_name": "Aibek Mukambetov",
+        "author_inst": "Soros Foundation in the Kyrgyz Republic"
       },
       {
-        "author_name": "Jyotishka Datta",
-        "author_inst": "Department of Statistics, Virginia Polytechnic Institute and State University"
+        "author_name": "Talant Abdyldaev",
+        "author_inst": "Kyrgyz Medical Academy in the Kyrgyz Republic"
+      },
+      {
+        "author_name": "Aisuluu Kubatova",
+        "author_inst": "Public Fund Institution of Social Development in the Kyrgyz Republic"
+      },
+      {
+        "author_name": "Shamil Ibragimov",
+        "author_inst": "Soros Foundation in the Kyrgyz Republic"
+      },
+      {
+        "author_name": "Nurbolot Usenbaev",
+        "author_inst": "Ministry of Health of the Kyrgyz Republic"
+      },
+      {
+        "author_name": "Ainura Kutmanova",
+        "author_inst": "Ministry of Health of the Kyrgyz Republic"
+      },
+      {
+        "author_name": "Lisa J White",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.12.11.20246694",
@@ -993447,18 +996894,91 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.12.08.416677",
-    "rel_title": "Intranasal administration of SARS-CoV-2 neutralizing human antibody prevents infection in mice",
+    "rel_doi": "10.1101/2020.12.09.417741",
+    "rel_title": "Characterization of protease activity of Nsp3 from SARS-CoV-2 and its in vitro inhibition by nanobodies",
     "rel_date": "2020-12-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.08.416677",
-    "rel_abs": "Prevention of SARS-CoV-2 infection at the point of nasal entry is a novel strategy that has the potential to help contain the ongoing pandemic. Using our proprietary technologies, we have engineered a human antibody that recognizes SARS-CoV-2 S1 spike protein with an enhanced affinity for mucin to improve the antibodys retention in respiratory mucosa. The modified antibody, when administered into mouse nostrils, was shown to block infection in mice that were exposed to high titer SARS-CoV-2 pseudovirus 10 hours after the initial antibody treatment. Our data show that the protection against SARS-CoV-2 infection is effective in both nasal and lung areas 7 days after viral exposure. The modified antibody is stable in a nasal spray formulation and maintains its SARS-CoV-2 neutralizing activity. Nasal spray of the modified antibody can be developed as an affordable and effective prophylactic product to protect people from infection by exposure to SARS-CoV-2 virus in the air.\n\nOne-sentence summaryA Fc-modified human antibody prevents SARS-CoV-2 viral infection via nasal administration",
-    "rel_num_authors": 0,
-    "rel_authors": null,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.09.417741",
+    "rel_abs": "Of the 16 non-structural proteins (Nsps) encoded by SARS CoV-2, Nsp3 is the largest and plays important roles in the viral life cycle. Being a large, multidomain, transmembrane protein, Nsp3 has been the most challenging Nsp to characterize. Encoded within Nsp3 is the papain-like protease PLpro domain that cleaves not only the viral protein but also polyubiquitin and the ubiquitin-like modifier ISG15 from host cells. We here compare the interactors of PLpro and Nsp3 and find a largely overlapping interactome. Intriguingly, we find that near full length Nsp3 is a more active protease compared to the minimal catalytic domain of PLpro. Using a MALDI-TOF based assay, we screen 1971 approved clinical compounds and identify five compounds that inhibit PLpro with IC50s in the low micromolar range but showed cross reactivity with other human deubiquitinases and had no significant antiviral activity in cellular SARS-CoV-2 infection assays. We therefore looked for alternative methods to block PLpro activity and engineered competitive nanobodies that bind to PLpro at the substrate binding site with nanomolar affinity thus inhibiting the enzyme. Our work highlights the importance of studying Nsp3 and provides tools and valuable insights to investigate Nsp3 biology during the viral infection cycle.",
+    "rel_num_authors": 18,
+    "rel_authors": [
+      {
+        "author_name": "Lee Armstrong",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      },
+      {
+        "author_name": "Sven M Lange",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      },
+      {
+        "author_name": "Virginia de Cesare",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      },
+      {
+        "author_name": "Stephen P Matthews",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      },
+      {
+        "author_name": "Raja Sekar Nirujogi",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      },
+      {
+        "author_name": "Isobel Cole",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      },
+      {
+        "author_name": "Anthony Hope",
+        "author_inst": "Drug Discovery Unit, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, UK"
+      },
+      {
+        "author_name": "Fraser Cunningham",
+        "author_inst": "Drug Discovery Unit, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, UK"
+      },
+      {
+        "author_name": "Rachel Toth",
+        "author_inst": "MRC Reagents and Services, University of Dundee, Dundee DD1 5EH, Scotland, UK"
+      },
+      {
+        "author_name": "Rukmini Mukherjee",
+        "author_inst": "Institute of Biochemistry II, Faculty of Medicine, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.  Buchmann Institute for Molecular "
+      },
+      {
+        "author_name": "Denisa Bojkova",
+        "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Frankfurt am Main, Germany"
+      },
+      {
+        "author_name": "Franz Gruber",
+        "author_inst": "National Phenotypic Screening Centre, University of Dundee, Dundee DD1 5EH, Scotland, UK"
+      },
+      {
+        "author_name": "David Gray",
+        "author_inst": "Drug Discovery Unit, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, UK"
+      },
+      {
+        "author_name": "Paul G Wyatt",
+        "author_inst": "Drug Discovery Unit, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland, UK"
+      },
+      {
+        "author_name": "Jindrich Cinatl",
+        "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Frankfurt am Main, Germany"
+      },
+      {
+        "author_name": "Ivan Dikic",
+        "author_inst": "Institute of Biochemistry II, Faculty of Medicine, Goethe University, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany.  Buchmann Institute for Molecular "
+      },
+      {
+        "author_name": "Paul Davies",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      },
+      {
+        "author_name": "Yogesh Kulathu",
+        "author_inst": "MRC Protein Phosphorylation and Ubiquitylation Unit, Sir James Black Centre, Dow Street, School of Life Sciences, University of Dundee, Dundee DD1 5EH, Scotland"
+      }
+    ],
     "version": "1",
-    "license": "",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "bioengineering"
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2020.12.08.417022",
@@ -995147,47 +998667,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.06.20243691",
-    "rel_title": "What is the probability that this patient, who presents to a UK hospital, will be diagnosed with Covid-19? Prospective validation of the open-source CovidCalculatorUK resource.",
+    "rel_doi": "10.1101/2020.12.06.20244756",
+    "rel_title": "Comparing Decision Tree-Based Ensemble Machine Learning Models for COVID-19 Death Probability Profiling",
     "rel_date": "2020-12-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.06.20243691",
-    "rel_abs": "IntroductionThe novel coronavirus SARS-CoV2 and the associated disease, Covid-19, continue to pose a global health threat. The CovidCalculatorUK is an open-source online tool (covidcalculatoruk.org) that estimates the probability that an individual patient, who presents to a UK hospital, will later test positive for SARS-CoV2. The objective is to aid cohorting decisions and minimise nosocomial transmission of SARS-CoV2.\n\nMethodsThis n = 500 prospective, observational, multicentre, validation study compared the CovidCalculatorUKs estimated probability of Covid-19 with the first SARS-CoV2 oropharyngeal/nasopharyngeal swab result for individual patients admitted to hospital during the study period (01.04.20 - 18.05.20). A comparison with senior clinicians estimates of the probability of Covid-19 was also made.\n\nResultsPatients who were prospectively grouped, by the CovidCalculatorUK, into 0-30% estimated probability, 30-60% and 60-100% estimated probability went on to have first swab SARS-CoV2 positive results in: 15.7%, 30.5% and 61.9% of cases, respectively. CovidCalculatorUK performance demonstrated an area under the curve of 0.76 (95% CI 0.71 - 0.81) (p < 0.001). Senior clinician stratification of the estimated probability of Covid-19 performed similarly to the CovidCalculatorUK.\n\nConclusionThe CovidCalculatorUK provides a reasonably accurate estimate of the probability of an individual testing positive on their first SARS-CoV2 nasopharyngeal/oropharyngeal swab. The CovidCalculatorUK output performs similarly to a senior clinicians estimate. Further evolution of the calculator may improve performance.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.06.20244756",
+    "rel_abs": "We compare the performance of major decision tree-based ensemble machine learning models on the task of COVID-19 death probability prediction, conditional on three risk factors: age group, sex and underlying comorbidity or disease, using the US Centers for Disease Control and Prevention (CDC)s COVID-19 case surveillance dataset. To evaluate the impact of the three risk factors on COVID-19 death probability, we extract and analyze the conditional probability profile produced by the best performer. The results show the presence of an exponential rise in death probability from COVID-19 with the age group, with males exhibiting a higher exponential growth rate than females, an effect that is stronger when an underlying comorbidity or disease is present, which also acts as an accelerator of COVID-19 death probability rise for both male and female subjects. The results are discussed in connection to healthcare and epidemiological concerns and in the degree to which they reinforce findings coming from other studies on COVID-19.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "George A Chapman",
-        "author_inst": "Oxford University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Lewis Mundell",
-        "author_inst": "Lanarkshire NHS Trust"
-      },
-      {
-        "author_name": "Charlotte H Harrison",
-        "author_inst": "Oxford University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Tamsin Cargill",
-        "author_inst": "Oxford University Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Odhran Keating",
-        "author_inst": "Buckinghamshire Healthcare NHS Trust"
-      },
-      {
-        "author_name": "Mark Johnson",
-        "author_inst": "Buckinghamshire Healthcare NHS Trust"
+        "author_name": "Carlos Pedro Goncalves",
+        "author_inst": "Lusofona University of Humanities and Technologies"
       },
       {
-        "author_name": "Andrew Smith",
-        "author_inst": "Lanarkshire NHS Trust"
+        "author_name": "Jose Rouco",
+        "author_inst": "Lusofona University of Humanities and Technologies"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.12.07.20245506",
@@ -996684,31 +1000184,39 @@
     "category": "pediatrics"
   },
   {
-    "rel_doi": "10.1101/2020.12.05.20244426",
-    "rel_title": "Exploring drugs and vaccines associated with altered risks and severity of COVID-19: a UK Biobank cohort study of all ATC level-4 drug categories",
+    "rel_doi": "10.1101/2020.12.04.20244327",
+    "rel_title": "COVID-19 RELATED IMMUNIZATION DISRUPTIONS IN RAJASTHAN, INDIA: A RETROSPECTIVE OBSERVATIONAL STUDY",
     "rel_date": "2020-12-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.05.20244426",
-    "rel_abs": "BackgroundCOVID-19 is a major public health concern, yet its risk factors are not well-understood and effective therapies are lacking. It remains unclear how different drugs may increase or decrease the risks of infection and severity of disease.\n\nMethodsWe studied associations of prior use of all level-4 ATC drug categories (including vaccines) with COVID-19 diagnosis and outcome, based on a prospective cohort of UK Biobank(UKBB). Drug history was based on general practitioner(GP) records. Effects of prescribed medications/vaccinations on the risk of infection, severity of disease and mortality were investigated separately. Hospitalized and fatal cases were categorized as  severe infection. We also considered different study designs and conducted analyses within infected patients, tested subjects and the whole population respectively, and for 5 different time-windows of prescriptions. Missing data were accounted for by multiple imputation and inverse probability weighting was employed to reduce testing bias. Multivariable logistic regression was conducted which controls for main confounders.\n\nResultsWe placed a greater focus on protective associations here, as (residual) confounding by indication and comorbidities tends to bias towards harmful effects. Across all categories, statins showed the strongest and most consistent protective associations. Significant protective effects against severe infection were seen among infected subjects (OR for prescriptions within a 12-month window, same below: 0.50, 95% CI:0.42-0.60), tested subjects (OR=0.63, 0.54-0.73) or in the general population (OR=0.49, 0.42-0.57). A number of top-listed drugs with protective effects were also cardiovascular medications, such as angiotensin converting enzyme inhibitors, angiotensin receptor blockers, calcium channel blocker and beta-blockers. Some other drugs showing protective associations included biguanides (metformin), estrogens, thyroid hormones and proton pump inhibitors, among others.\n\nInterestingly, we also observed protective associations by numerous vaccines. The most consistent association was observed for influenza vaccines, which showed reduced odds of infection (OR= 0.73 for vaccination in past year, CI 0.65-0.83) when compared cases to general population controls or test-negative controls (OR=0.60, 0.53-0.68). Protective associations were also observed when severe or fatal infection was considered as the outcome. Pneumococcal, tetanus, typhoid and combined bacterial and viral vaccines (ATC code J07CA) were also associated with lower odds of infection/severity.\n\nFurther subgroup and interaction analyses revealed difference in protective effects in different clinical subgroups. For example, protective effects of flu and pneumococcal vaccines were weaker in obese individuals, while we observed stronger protective effects of statins in those with cardiometabolic disorders, such as diabetes, coronary artery disease, hypertension and obesity.\n\nConclusionsA number of drugs, including many for cardiometabolic disorders, may be associated with lower odds of infection/severity of infection. Several existing vaccines, especially flu vaccines, may be beneficial against COVID-19 as well. However, causal relationship cannot be established due to risk of confounding. While further studies are required to validate the findings, this work provides a useful reference for future meta-analyses, clinical trials or experimental studies.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.04.20244327",
+    "rel_abs": "IntroductionGovernments around the world suspended immunization outreach to control COVID-19 spread. Many have since resumed services with an emphasis on catch-up vaccinations to reach children with missed vaccinations. This paper evaluated immunization disruptions during Indias March-May 2020 lockdown and the extent to which subsequent catch-up efforts reversed them in Rajasthan, India.\n\nMethodsIn this retrospective observational study, we conducted phone surveys to collect immunization details for 2,144 children that turned one year old between January and October 2020. We used logistic regressions to compare differences in immunization timeliness and completed first-year immunization status among children that were due immunizations just before (unexposed), during (heavily exposed), and after (post-exposure) the lockdown.\n\nResultsRelative to unexposed children, heavily exposed children were significantly less likely to be immunized at or before 9 months (OR 0.550; 95%CI 0.367-0.824; p=0.004), but more likely to be immunized at 10-12 months (OR 1.761; 95%CI 1.196-2.591; p=0.004). They were also less likely to have completed their key first-year immunizations (OR 0.624; 95%CI 0.478-0.816; p=0.001) by the time of survey. In contrast, post-exposure children showed no difference in timeliness or completed first-year immunizations relative to unexposed children, and their immunization coverage was 6.9pp above heavily exposed children despite their younger age. Declines in immunization coverage were larger among children in households that were poorer, less educated, lower caste, and residing in COVID red zones, although subgroup comparisons were not statistically significant.\n\nConclusionDisruptions to immunization services resulted in children missing immunization during the lockdown, but catch-up efforts after it was eased ensured many children were reached at later ages. Nevertheless, catch-up was incomplete and children due their immunizations during the lockdown remained less likely to be fully immunized 4-5 months after it lifted, even as younger cohorts due immunizations in June or later returned to pre-lockdown schedules.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Yong XIANG",
-        "author_inst": "The Chinese University of Hong Kong"
+        "author_name": "Radhika Jain",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Kenneth Chi-Yin WONG",
-        "author_inst": "The Chinese University of Hong Kong"
+        "author_name": "Ambika Chopra",
+        "author_inst": "J-PAL South Asia at IFMR"
       },
       {
-        "author_name": "Hon-Cheong SO",
-        "author_inst": "Chinese University of Hong Kong"
+        "author_name": "Camille Falezan",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Mustufa Patel",
+        "author_inst": "J-PAL South Asia at IFMR"
+      },
+      {
+        "author_name": "Pascaline Dupas",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pharmacology and therapeutics"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.12.05.20244657",
@@ -998134,71 +1001642,55 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.12.06.413443",
-    "rel_title": "Efficient inhibition of SARS-CoV-2 strains by a novel ACE2-IgG4-Fc fusion protein with a stabilized hinge region",
+    "rel_doi": "10.1101/2020.12.06.412759",
+    "rel_title": "The new generation hDHODH inhibitor MEDS433 hinders the in vitro replication of SARS-CoV-2",
     "rel_date": "2020-12-07",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.06.413443",
-    "rel_abs": "The novel severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2) enters its host cells after binding to the angiotensin-converting enzyme 2 (ACE2) via its spike glycoprotein. This interaction is critical for virus entry and virus-host membrane fusion. Soluble ACE2 ectodomains bind and neutralize the virus but the short in vivo half-lives of soluble ACE2 limits its therapeutic use. Fusion of the fragment crystallizable (Fc) part of human immunoglobulin G (IgG) to the ACE2 ectodomain can prolong the in vivo half-life but bears the risk of unwanted Fc-receptor activation and antibody-dependent disease enhancement. Here, we describe optimized ACE2-Fc fusion constructs that avoid Fc-receptor binding by using IgG4-Fc as a fusion partner. The engineered ACE2-IgG4-Fc fusion proteins described herein exhibit promising pharmaceutical properties and a broad antiviral activity at single-digit nanomolar concentration. In addition, they allow to maintain the beneficial enzymatic activity of ACE2 and thus are very promising candidate antivirals broadly acting against coronaviruses.",
-    "rel_num_authors": 13,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.06.412759",
+    "rel_abs": "Identification and development of effective drugs active against SARS-CoV-2 are urgently needed. Here, we report on the anti-SARS-CoV-2 activity of MEDS433, a novel inhibitor of human dihydroorotate dehydrogenase (hDHODH), a key cellular enzyme of the de novo pyrimidines biosynthesis. MEDS433 inhibits in vitro virus replication in the low nanomolar range, and through a mechanism that stems from its ability to block hDHODH activity. MEDS433 thus represents an attractive candidate to develop novel anti-SARS-CoV-2 agents.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Hristo L Svilenov",
-        "author_inst": "Department of Chemistry, Technical University of Munich, Garching, Germany"
-      },
-      {
-        "author_name": "Julia Sacherl",
-        "author_inst": "Institute of Virology, Technical University of Munich / Helmholtz Zentrum Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Alwin Reiter",
-        "author_inst": "Formycon AG, Martinsried/Planegg, Germany"
-      },
-      {
-        "author_name": "Lisa Wolff",
-        "author_inst": "Institute of Virology, Technical University of Munich / Helmholtz Zentrum Munich, Munich, Germany"
-      },
-      {
-        "author_name": "Cho-Chin Chen",
-        "author_inst": "Institute of Virology, Technical University of Munich / Helmholtz Zentrum Munich, Munich, Germany / German Center for Infection Research, Munich partner site, M"
+        "author_name": "Arianna Calistri",
+        "author_inst": "University of Padova"
       },
       {
-        "author_name": "Marcel Stern",
-        "author_inst": "Max von Pettenkofer Institute & Gene Center, Virology, LMU Muenchen, Munich, Germany / German Center for Infection Research, Munich partner site, Munich, German"
+        "author_name": "Anna Luganini",
+        "author_inst": "University of Turin"
       },
       {
-        "author_name": "Frank-Peter Wachs",
-        "author_inst": "Formycon AG, Martinsried/Planegg, Germany"
+        "author_name": "Valeria Conciatori",
+        "author_inst": "University of Padua"
       },
       {
-        "author_name": "Nicole Simonavicius",
-        "author_inst": "Formycon AG, Martinsried/Planegg, Germany"
+        "author_name": "Claudia Del Vecchio",
+        "author_inst": "University of Padova"
       },
       {
-        "author_name": "Susanne Pippig",
-        "author_inst": "Formycon AG, Martinsried/Planegg, Germany"
+        "author_name": "Stefano Sainas",
+        "author_inst": "University of Turin"
       },
       {
-        "author_name": "Florian Wolschin",
-        "author_inst": "Formycon AG, Martinsried/Planegg, Germany"
+        "author_name": "Donatella Boschi",
+        "author_inst": "University of Turin"
       },
       {
-        "author_name": "Johannes Buchner",
-        "author_inst": "Department of Chemistry, Technical University of Munich, Garching, Germany"
+        "author_name": "Marco Lucio Lolli",
+        "author_inst": "Department of Sciences and Drug Technology"
       },
       {
-        "author_name": "Carsten Brockmeyer",
-        "author_inst": "Formycon AG, Martinsried/Planegg, Germany"
+        "author_name": "Giorgio Gribaudo",
+        "author_inst": "University of Turin"
       },
       {
-        "author_name": "Ulrike Protzer",
-        "author_inst": "Institute of Virology, Technical University of Munich / Helmholtz Zentrum Munich, Munich, Germany"
+        "author_name": "Cristina Parolin",
+        "author_inst": "University of Padova"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.12.07.414292",
@@ -1000020,68 +1003512,48 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.12.02.20242925",
-    "rel_title": "Mapping each pre-existing conditions association to short-term and long-term COVID-19 complications",
+    "rel_doi": "10.1101/2020.12.02.20242958",
+    "rel_title": "Longitudinal lab test analysis confirms pre-existing anemia as a severe risk factor for post-viral clearance hospitalization in COVID-19 patients",
     "rel_date": "2020-12-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.02.20242925",
-    "rel_abs": "Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage 1.1 million clinical notes from 1,903 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0-30 days, 31-60 days, and 61-90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (23% of 383 complications) followed by cardiac arrhythmia (12% of 383 complications). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia and anemia. Furthermore, novel associations between cancer (risk ratio: 3, p=0.02) or immunosuppression (risk ratio: 4.3, p=0.04) with early-onset heart failure have also been identified. Onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 24% of 45 patients, 61-90 days: 25% of 36 patients). Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.02.20242958",
+    "rel_abs": "BackgroundAs the number of new and recovering COVID-19 cases continues to rise, it has become evident that patients can experience symptoms and complications after viral clearance. Clinical biomarkers characterizing patients who are likely to experience these prolonged effects are unknown.\n\nMethodsWe conducted a retrospective study to compare longitudinal lab test measurements (hemoglobin, hematocrit, estimated glomerular filtration rate, serum creatinine, and blood urea nitrogen) in patients rehospitalized after PCR-confirmed SARS-CoV-2 clearance (n=104) versus patients not rehospitalized after viral clearance (n=278).\n\nFindingsCompared to patients who were not rehospitalized after PCR-confirmed viral clearance, those who were rehospitalized had lower median hemoglobin levels in the year prior to COVID-19 diagnosis (cohens D = -0.50; p=1.2x10-3) and during the active infection window (cohens D = -0.71; p=4.6x10-8). Patients hospitalized after viral clearance were also more likely to be diagnosed with moderate or severe anemia during the active infection window (OR = 2.18; p = 4.99x10-9).\n\nConclusionsThe occurrence of moderate or severe anemia in hospitalized COVID-19 patients is strongly associated with rehospitalization after viral clearance. Whether interventions to mitigate anemia can improve long term outcomes of COVID-19 patients should be further investigated.\n\nFundingThis study was funded by nference.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "AJ Venkatakrishnan",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Colin Pawlowski",
+        "author_name": "Patrick Lenehan",
         "author_inst": "nference"
       },
       {
-        "author_name": "David Zemmour",
+        "author_name": "Eshwan Ramudu",
         "author_inst": "nference"
       },
       {
-        "author_name": "Travis Hughes",
+        "author_name": "AJ Venkatakrishnan",
         "author_inst": "nference"
       },
-      {
-        "author_name": "Akash Anand",
-        "author_inst": "nference Labs"
-      },
       {
         "author_name": "Gabriela Berner",
         "author_inst": "nference"
       },
       {
-        "author_name": "Nikhil Kayal",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Arjun Puranik",
-        "author_inst": "nference"
-      },
-      {
-        "author_name": "Ian Conrad",
+        "author_name": "Reid McMurry",
         "author_inst": "nference"
       },
       {
-        "author_name": "Sairam Bade",
-        "author_inst": "nference Labs"
-      },
-      {
-        "author_name": "Rakesh Barve",
-        "author_inst": "nference Labs"
+        "author_name": "John O'Horo",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Purushottam Sinha",
-        "author_inst": "nference Labs"
+        "author_name": "Andrew D Badley",
+        "author_inst": "Mayo Clinic"
       },
       {
-        "author_name": "Jack O'Horo",
-        "author_inst": "Mayo Clinic"
+        "author_name": "William G Morice",
+        "author_inst": "Mayo Clinic Laboratories"
       },
       {
-        "author_name": "Andrew D Badley",
+        "author_name": "John Halamka",
         "author_inst": "Mayo Clinic"
       },
       {
@@ -1001694,35 +1005166,155 @@
     "category": "surgery"
   },
   {
-    "rel_doi": "10.1101/2020.12.03.20239681",
-    "rel_title": "Spatial risk factors for Pillar 1 COVID-19 case counts and mortality in rural eastern England, UK",
+    "rel_doi": "10.1101/2020.12.03.20243535",
+    "rel_title": "OpenSAFELY: impact of national guidance on switching from warfarin to direct oral anticoagulants (DOACs) in early phase of COVID-19 pandemic in England",
     "rel_date": "2020-12-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.03.20239681",
-    "rel_abs": "Understanding is still developing about risk factors for COVID-19 infection or mortality. This is especially true with respect to identifying spatial risk factors and therefore identifying which geographic areas have populations who are at greatest risk of acquiring severe disease. This is a secondary analysis of patient records in a confined area of eastern England, covering persons who tested positive for SARS-CoV-2 through end May 2020, including dates of death and residence area. For each residence area (local super output area), we obtained data on air quality, deprivation levels, care home bed capacity, age distribution, rurality, access to employment centres and population density. We considered these covariates as risk factors for excess cases and excess deaths in the 28 days after confirmation of positive covid status relative to the overall case load and death recorded for the study area as a whole. We used the conditional autoregressive Besag-York-Mollie model to investigate the spatial dependency of cases and deaths allowing for a Poisson error structure. Structural equation models were also applied to clarify relationships between predictors and outcomes. Excess case counts or excess deaths were both predicted by the percentage of population age 65 years, care home bed capacity and less rurality: older population and more urban areas saw excess cases. Greater deprivation did not correlate with excess case counts but was significantly linked to higher mortality rates after infection. Neither excess cases nor excess deaths were predicted by population density, travel time to local employment centres or air quality indicators. Only 66% of mortality could be explained by locally high case counts. The results show a clear link between greater deprivation and higher COVID-19 mortality that is separate from wider community prevalence and other spatial risk factors.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243535",
+    "rel_abs": "BackgroundEarly in the COVID-19 pandemic the NHS recommended that appropriate patients anticoagulated with warfarin should be switched to direct acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately co-prescribed two anticoagulants following a medication change, and associated monitoring.\n\nObjectiveTo describe which people were switched from warfarin to DOACs; identify potentially unsafe co-prescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic.\n\nMethodsWorking on behalf of NHS England we conducted a population cohort based study using routine clinical data from >17 million adults in England.\n\nResults20,000 of 164,000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in co-prescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. INR testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420).\n\nConclusionsIncreased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people co-prescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Julii S Brainard",
-        "author_inst": "university of east anglia"
+        "author_name": "Helen J Curtis",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Steve Rushton",
-        "author_inst": "Newcastle University"
+        "author_name": "Brian MacKenna",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Tim Winters",
-        "author_inst": "Norfolk County Council"
+        "author_name": "Alex J Walker",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Paul R Hunter",
-        "author_inst": "University of East Anglia"
+        "author_name": "Richard Croker",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Amir Mehrkar",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Caroline E Morton",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Seb Bacon",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "George Hickman",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Peter Inglesby",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Chris Bates",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "David Evans",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Tom Ward",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Jonathan Cockburn",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Simon Davy",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Krishnan Bhaskaran",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Anna Schultze",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Christopher T Rentsch",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Elizabeth Williamson",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "William Hulme",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Helen I McDonald",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Laurie Tomlinson",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Rohini Mathur",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Henry Drysdale",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Rosalind M Eggo",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Kevin Wing",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Angel Wong",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Harriet Forbes",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "John Parry",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Frank Hester",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Sam Harper",
+        "author_inst": "TPP"
+      },
+      {
+        "author_name": "Stephen JW Evans",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Ian J Douglas",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Liam Smeeth",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
+      },
+      {
+        "author_name": "Ben Goldacre",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "cardiovascular medicine"
   },
   {
     "rel_doi": "10.1101/2020.12.04.410340",
@@ -1003120,41 +1006712,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.12.01.20241885",
-    "rel_title": "Prediction of Covid-19 spreading and optimal coordination of counter-measures: From microscopic to macroscopic models to Pareto fronts",
+    "rel_doi": "10.1101/2020.12.01.20242289",
+    "rel_title": "The COVID-19 herd immunity threshold is not low: A re-analysis of European data from spring of 2020",
     "rel_date": "2020-12-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20241885",
-    "rel_abs": "The Covid-19 disease has caused a world-wide pandemic with more than 60 million positive cases and more than 1.4 million deaths by the end of November 2020. As long as effective medical treatment and vaccination are not available, non-pharmaceutical interventions such as social distancing, self-isolation and quarantine as well as far-reaching shutdowns of economic activity and public life are the only available strategies to prevent the virus from spreading. These interventions must meet conflicting requirements where some objectives, like the minimization of disease-related deaths or the impact on health systems, demand for stronger counter-measures, while others, such as social and economic costs, call for weaker counter-measures. Therefore, finding the optimal compromise of counter-measures requires the solution of a multi-objective optimization problem that is based on accurate prediction of future infection spreading for all combinations of counter-measures under consideration. We present a strategy for construction and solution of such a multi-objective optimization problem with real-world applicability. The strategy is based on a micro-model allowing for accurate prediction via a realistic combination of person-centric data-driven human mobility and behavior, stochastic infection models and disease progression models including micro-level inclusion of governmental intervention strategies. For this micro-model, a surrogate macro-model is constructed and validated that is much less computationally expensive and can therefore be used in the core of a numerical solver for the multi-objective optimization problem. The resulting set of optimal compromises between counter-measures (Pareto front) is discussed and its meaning for policy decisions is outlined.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20242289",
+    "rel_abs": "The recent publication of the Great Barrington Declaration (GBD), which calls for relaxing all public health interventions on young, healthy individuals, has brought the question of herd immunity to the forefront of COVID-19 policy discussions, and is partially based on unpublished research that suggests low herd immunity thresholds (HITs) of 10-20%. We re-evaluate these findings and correct a flawed assumption leading to COVID-19 HIT estimates of 60-80%. If policymakers were to adopt a herd immunity strategy, in which the virus is allowed to spread relatively unimpeded, we project that cumulative COVID-19 deaths would be five times higher than the initial estimates suggest. Our re-estimates of the COVID-19 HIT corroborate strong signals in the data and compelling arguments that most of the globe remains far from herd immunity, and suggest that abandoning community mitigation efforts would jeopardize the welfare of communities and integrity of healthcare systems.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Hanna Wulkow",
-        "author_inst": "Zuse Institute Berlin"
-      },
-      {
-        "author_name": "Tim Conrad",
-        "author_inst": "Zuse Institute Berlin and Freie Universitaet Berlin"
+        "author_name": "Spencer J Fox",
+        "author_inst": "The University of Texas at Austin"
       },
       {
-        "author_name": "Natasa Djurdjevac Conrad",
-        "author_inst": "Zuse Institute Berlin"
+        "author_name": "Pratyush Potu",
+        "author_inst": "The University of Texas at Austin"
       },
       {
-        "author_name": "Sebastian Alexander Mueller",
-        "author_inst": "TU Berlin"
+        "author_name": "Ravi Srinivasan",
+        "author_inst": "The University of Texas at Austin"
       },
       {
-        "author_name": "Kai Nagel",
-        "author_inst": "TU Berlin"
+        "author_name": "Michael Lachmann",
+        "author_inst": "The Santa Fe Institute"
       },
       {
-        "author_name": "Christof Schuette",
-        "author_inst": "FU Berlin"
+        "author_name": "Lauren Ancel Meyers",
+        "author_inst": "The University of Texas at Austin"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1004610,41 +1008198,37 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2020.12.01.20241570",
-    "rel_title": "The Acceleration Index as a Test-Controlled Reproduction Number: Application to COVID-19 in France",
+    "rel_doi": "10.1101/2020.11.30.20240986",
+    "rel_title": "A Net Benefit Approach for the Optimal Allocation of a COVID-19 Vaccine",
     "rel_date": "2020-12-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20241570",
-    "rel_abs": "We provide a novel way to correct the effective reproduction number for the time-varying amount of tests, using the acceleration index (Baunez et al., 2021) as a simple measure of viral spread dynamics. Not correcting results in the reproduction number being a biased estimate of viral acceleration and we provide a formal decomposition of the resulting bias, involving the useful notions of test and infectivity intensities. When applied to French data for the COVID-19 pandemic (May 13, 2020 - October 26, 2022), our decomposition shows that the reproduction number, when considered alone, characteristically underestimates the resurgence of the pandemic, compared to the acceleration index which accounts for the time-varying volume of tests. Because the acceleration index aggregates all relevant information and captures in real time the sizable time variation featured by viral circulation, it is a more parsimonious indicator to track the dynamics of an infectious disease outbreak in real time, compared to the equivalent alternative which would combine the reproduction number with the test and infectivity intensities.\n\nJEL Classification NumbersI18; H12",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20240986",
+    "rel_abs": "OBJECTIVEWe implement a model-based approach to identify the optimal allocation of a COVID-19 vaccine in the province of Alberta, Canada.\n\nMETHODSWe develop an epidemiologic model to evaluate allocation strategies defined by age and risk target groups, coverage, effectiveness, and cost of vaccine. The model simulates hypothetical immunization scenarios within a dynamic context, capturing concurrent public health strategies and population behaviour changes.\n\nRESULTSIn a scenario with 80% vaccine effectiveness, 40% population coverage, and prioritisation of those over the age of 60 at high-risk of poor outcomes, active cases are reduced by 17% and net monetary benefit increased by $263 million dollars, relative to no vaccine. Concurrent implementation of policies such as school closure and senior contact reductions have similar impacts on incremental net monetary benefit ($352 vs. 292 million, respectively) when there is no prioritisation given to any age or risk group. When older age groups are given priority, the relative benefit of school closures is much larger ($214 vs. 118 million). Results demonstrate that the rank ordering of different prioritisation options varies by prioritisation criteria, vaccine effectiveness and coverage, and concurrently implemented policies.\n\nCONCLUSIONSOur results have three implications: (i) optimal vaccine allocation will depend on the public health policies in place at the time of allocation and the impact of those policies on population behaviour; (ii) outcomes of vaccine allocation policies can be greatly supported with interventions targeting contact reduction in critical sub-populations; and (iii) identification of the optimal strategy depends on which outcomes are prioritised.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Christelle Baunez",
-        "author_inst": "Institut Neurosciences Timone"
-      },
-      {
-        "author_name": "Mickael Degoulet",
-        "author_inst": "Institut Neurosciences Timone"
+        "author_name": "Erin Kirwin",
+        "author_inst": "University of Manchester, Institute of Health Economics"
       },
       {
-        "author_name": "Stephane Luchini",
-        "author_inst": "Aix-Marseille School of Economics"
+        "author_name": "Ellen Rafferty",
+        "author_inst": "Institute of Health Economics"
       },
       {
-        "author_name": "Matteo Louis Pintus",
-        "author_inst": "AgroParisTech"
+        "author_name": "Kate Harback",
+        "author_inst": "Institute of Health Economics"
       },
       {
-        "author_name": "Patrick Pintus",
-        "author_inst": "Aix-Marseille University and CNRS"
+        "author_name": "Jeff Round",
+        "author_inst": "Institute of Health Economics, University of Alberta"
       },
       {
-        "author_name": "Miriam Teschl",
-        "author_inst": "Aix-Marseille School of Economics"
+        "author_name": "Christopher McCabe",
+        "author_inst": "Institute of Health Economics, University of Alberta"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "health economics"
   },
@@ -1006240,135 +1009824,35 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2020.12.01.405738",
-    "rel_title": "Guidelines for accurate genotyping of SARS-CoV-2 using amplicon-based sequencing of clinical samples",
+    "rel_doi": "10.1101/2020.11.30.405340",
+    "rel_title": "Role of Long-range Allosteric Communication in Determining the Stability and Disassembly of SARS-COV-2 in Complex with ACE2",
     "rel_date": "2020-12-01",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.01.405738",
-    "rel_abs": "BackgroundSARS-CoV-2 genotyping has been instrumental to monitor virus evolution and transmission during the pandemic. The reliability of the information extracted from the genotyping efforts depends on a number of aspects, including the quality of the input material, applied technology and potential laboratory-specific biases. These variables must be monitored to ensure genotype reliability. The current lack of guidelines for SARS-CoV-2 genotyping leads to inclusion of error-containing genome sequences in studies of viral spread and evolution.\n\nResultsWe used clinical samples and synthetic viral genomes to evaluate the impact of experimental factors, including viral load and sequencing depth, on correct sequence determination using an amplicon-based approach. We found that at least 1000 viral genomes are necessary to confidently detect variants in the genome at frequencies of 10% or higher. The broad applicability of our recommendations was validated in >200 clinical samples from six independent laboratories. The genotypes of clinical isolates with viral load above the recommended threshold cluster by sampling location and period. Our analysis also supports the rise in frequency of 20A.EU1 and 20A.EU2, two recently reported European strains whose dissemination was favoured by travelling during the summer 2020.\n\nConclusionsWe present much-needed recommendations for reliable determination of SARS-CoV-2 genome sequence and demonstrate their broad applicability in a large cohort of clinical samples.",
-    "rel_num_authors": 29,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.30.405340",
+    "rel_abs": "Severe acute respiratory syndrome (SARS) and novel coronavirus disease (COVID-19) are caused by two closely related beta-coronaviruses, SARS-CoV and SARS-CoV-2, respectively. The envelopes surrounding these viruses are decorated with spike proteins, whose receptor binding domains (RBDs) initiate invasion by binding to the human angiotensin-converting enzyme 2 (ACE2). Subtle changes at the interface with ACE2 seem to be responsible for the enhanced affinity for the receptor of the SARS-CoV-2 RBD compared to SARS-CoV RBD. Here, we use Elastic Network Models (ENMs) to study the response of the viral RBDs and ACE2 upon dissassembly of the complexes. We identify a dominant detachment mode, in which the RBD rotates away from the surface of ACE2, while the receptor undergoes a conformational transition which stretches the active-site cleft. Using the Structural Perturbation Method, we determine the network of residues, referred to as the Allostery Wiring Diagram (AWD), which drives the large-scale motion activated by the detachment of the complex. The AWD for SARS-CoV and SARS-CoV-2 are remarkably similar, showing a network that spans the interface of the complex and reaches the active site of ACE2, thus establishing an allosteric connection between RBD binding and receptor catalytic function. Informed in part by the AWD, we used Molecular Dynamics simulations to probe the effect of interfacial mutations in which SARS-CoV-2 residues are replaced by their SARS-CoV counterparts. We focused on a conserved glycine (G502 in SARS-CoV-2, G488 in SARS-CoV) because it belongs to a region that initiates the dissociation of the complex along the dominant detachment mode, and is prominent in the AWD. Molecular Dynamics simulations of SARS-CoV-2 wild-type and G502P mutant show that the affinity for the human receptor of the mutant is drastically diminished. Our results suggest that in addition to residues that are in direct contact with the interface those involved in long range allosteric communication are also a determinant of the stability of the RBD-ACE2 complex.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Slawomir Kubik",
-        "author_inst": "SOPHiA Genetics, Chemin des Mines 9, CH-1202 Geneva, Switzerland"
-      },
-      {
-        "author_name": "Ana Claudia Marques",
-        "author_inst": "SOPHiA Genetics, Rue du Centre 172, CH-1025 Saint Sulpice, Switzerland"
-      },
-      {
-        "author_name": "Xiaobin Xing",
-        "author_inst": "SOPHiA Genetics, Rue du Centre 172, CH-1025 Saint Sulpice, Switzerland"
-      },
-      {
-        "author_name": "Janine Silvery",
-        "author_inst": "LABCON-OWL GmbH, Siemensstrasse 40, D-32105 Bad Salzuflen, USt-IdNr. DE814960283, Germany"
-      },
-      {
-        "author_name": "Claire Bertelli",
-        "author_inst": "Genomics and Metagenomics Laboratory, Institute of Microbiology, Lausanne University Hospital and University of Lausanne, Bugnon 48, 1011 Lausanne, Switzerland"
-      },
-      {
-        "author_name": "Flavio De Maio",
-        "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCCS, Universita Cattolica del Sacro Cuore, L.go Agostino Gemelli 8, 00168 Roma, Italy"
-      },
-      {
-        "author_name": "Spyros Pournaras",
-        "author_inst": "Laboratory of Clinical Microbiology, Attikon University Hospital Medical School, National and Kapodistrian University of Athens, Athens, Rimini 1, Chaidari 124 "
-      },
-      {
-        "author_name": "Tom Burr",
-        "author_inst": "Source BioScience, Units 24/25, William James House, Cowley Road, Cambridge, CB4 0WU, United Kingdom"
-      },
-      {
-        "author_name": "Yannis Duffourd",
-        "author_inst": "Equipe GAD - Inserm U1231, CHU Francois Mitterrand; 21000 Dijon, France"
-      },
-      {
-        "author_name": "Helena Siemens",
-        "author_inst": "LABCON-OWL GmbH, Siemensstrasse 40, D-32105 Bad Salzuflen, USt-IdNr. DE814960283, Germany"
-      },
-      {
-        "author_name": "Chakib Alloui",
-        "author_inst": "Laboratoire de Virologie, CHU Avicenne, AP-HP, 93000 Bobigny, France"
-      },
-      {
-        "author_name": "Lin Song",
-        "author_inst": "SOPHiA Genetics, Rue du Centre 172, CH-1025 Saint Sulpice, Switzerland"
-      },
-      {
-        "author_name": "Yvan Wenger",
-        "author_inst": "SOPHiA Genetics, Chemin des Mines 9, CH-1202 Geneva, Switzerland"
-      },
-      {
-        "author_name": "Alexandra Saitta",
-        "author_inst": "SOPHiA Genetics, Chemin des Mines 9, CH-1202 Geneva, Switzerland"
-      },
-      {
-        "author_name": "Morgane Macheret",
-        "author_inst": "SOPHiA Genetics, Chemin des Mines 9, CH-1202 Geneva, Switzerland"
-      },
-      {
-        "author_name": "Ewan W Smith",
-        "author_inst": "SOPHiA Genetics, Chemin des Mines 9, CH-1202 Geneva, Switzerland"
-      },
-      {
-        "author_name": "Philippe Menu",
-        "author_inst": "SOPHiA Genetics, Rue du Centre 172, CH-1025 Saint Sulpice, Switzerland"
-      },
-      {
-        "author_name": "Marion Brayer",
-        "author_inst": "SOPHiA Genetics, Rue du Centre 172, CH-1025 Saint Sulpice, Switzerland"
-      },
-      {
-        "author_name": "Lars M Steinmetz",
-        "author_inst": "Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA"
-      },
-      {
-        "author_name": "Ali Si-Mohammed",
-        "author_inst": "Laboratoire de Virologie, CHU Francois Mitterrand; 2, rue Angelique Ducoudray, 2100 Dijon, France"
-      },
-      {
-        "author_name": "Josiane Chuisseu",
-        "author_inst": "Source BioScience, Units 24/25, William James House, Cowley Road, Cambridge, CB4 0WU, United Kingdom"
-      },
-      {
-        "author_name": "Richard Stevens",
-        "author_inst": "Source BioScience, Units 24/25, William James House, Cowley Road, Cambridge, CB4 0WU, United Kingdom"
-      },
-      {
-        "author_name": "Pantelis Constantoulakis",
-        "author_inst": "BioAnalytica Genotypos SA, 3-5 Ilision str, 115 28 Athens, Greece"
-      },
-      {
-        "author_name": "Michela Sali",
-        "author_inst": "Dipartimento di Scienze biotecnologiche di base, cliniche intensivologiche e perioperatorie - Sezione di Microbiologia, Universita Cattolica del Sacro Cuore, Ro"
-      },
-      {
-        "author_name": "Gilbert Greub",
-        "author_inst": "Genomics and Metagenomics Laboratory, Institute of Microbiology, Lausanne University Hospital and University of Lausanne, Bugnon 48, 1011 Lausanne, Switzerland"
-      },
-      {
-        "author_name": "Carsten Tiemann",
-        "author_inst": "LABCON-OWL GmbH, Siemensstrasse 40, D-32105 Bad Salzuflen, USt-IdNr. DE814960283, Germany"
+        "author_name": "Mauro Lorenzo Mugnai",
+        "author_inst": "The University of Texas at Austin"
       },
       {
-        "author_name": "Vicent Pelechano",
-        "author_inst": "SciLifeLab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 17165 Solna, Sweden"
+        "author_name": "Clark Templeton",
+        "author_inst": "The University of Texas at Austin"
       },
       {
-        "author_name": "Adrian Willig",
-        "author_inst": "SOPHiA Genetics, Chemin des Mines 9, CH-1202 Geneva, Switzerland"
+        "author_name": "Ron Elber",
+        "author_inst": "The University of Texas at Austin"
       },
       {
-        "author_name": "Zhenyu Xu",
-        "author_inst": "SOPHiA Genetics, Rue du Centre 172, CH-1025 Saint Sulpice, Switzerland"
+        "author_name": "Dave Thirumalai",
+        "author_inst": "University of Texas at Austin"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "genomics"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2020.11.30.405472",
@@ -1008382,43 +1011866,47 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.11.26.20239103",
-    "rel_title": "I'm alone but not lonely. U-shaped pattern of perceived loneliness during the COVID-19 pandemic in the UK and Greece",
+    "rel_doi": "10.1101/2020.11.25.20238741",
+    "rel_title": "I dont feel safe sitting in my own yard: Chicago resident experiences with urban rats during a COVID-19 stay-at-home order",
     "rel_date": "2020-11-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.26.20239103",
-    "rel_abs": "Many countries have adopted lengthy lockdown measures to mitigate the spreading of the COVID-19 virus. In this study, we train a RandomForest model using 10 variables quantifying individuals living environment, physical and mental health statuses to predict how long each of the UK participants (N=382) had been in lockdown. Self-perceived loneliness was found to be the most important variable predicting time in lockdown and, therefore, the aspect most influenced by the time the participant spent in lockdown. Subsequent statistical analysis showed a significant U-shaped curve for the levels of perceived loneliness (p<0.012), specifically decreasing during the 4th and 5th lockdown weeks. The same pattern was found on data from Greek citizens (N=129, p<0.041). These results suggest that lockdown measures may have affected how people evaluated their social support while in lockdown, leading to a decreased sense of loneliness. Implications of this study should be reflected on policies and countermeasures to current and future pandemics.\n\nState of relevanceThis study aims to inform policies for the current and/or future pandemics, particularly those involving lockdown restrictions. It highlights that self-perceived loneliness was the trait most affected by the time spent in lockdown: data show that the very first period of lockdown was characterised by a decrease in levels of perceived loneliness. The machine learning approach adopted and the statistical validation on two different Western European countries ensure that the uncovered pattern is substantial. This result highlights the dissociation between objective social support and perceived loneliness: initially, restrictions may have triggered better social behaviours among communities or increased the level of gratitude for the social support people have always received. The short duration of these desirable effects suggests that measures and campaigns promoting better social support strategies could be potentially effective, even in social isolation, to keep the levels of perceived loneliness low.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20238741",
+    "rel_abs": "BackgroundEncounters with rats in urban areas increase risk of human exposure to rat-associated zoonotic pathogens and act as a stressor associated with psychological distress. The frequency and nature of human-rat encounters may be altered by social distancing policies to mitigate the COVID-19 pandemic. For example, restaurant closures may reduce food availability for rats and promote rat activity in nearby residential areas, thus increasing public health risks during a period of public health crisis. In this study, we aimed to identify factors associated with increased perceived exposure to rats during a stay-at-home order, describe residents encounters with rats relevant to their health and well-being, and identify factors associated with increased use of rodent control.\n\nMethodsUrban residents in Chicago, a large city with growing concerns about rats and health disparities, completed an online questionnaire including fixed response and open-ended questions during the spring 2020 stay-at-home order. Analyses included ordinal multivariate regression, spatial analysis, and thematic analysis for open-ended responses.\n\nResultsOverall, 21% of respondents (n=835) reported an increase in rat sightings around their homes during the stay-at-home order and increased rat sightings was positively associated with proximity to restaurants, low-rise apartment buildings, and rat feces in the home (p[&le;]0.01). Many respondents described feeling unsafe using their patio or yard, and afraid of rats entering their home or spreading disease. Greater engagement with rodent control was associated with property ownership, information about rat control, and lower incomes (p[&le;]0.01).\n\nConclusionsMore frequent rat encounters may be an unanticipated public health concern during periods of social distancing, especially in restaurant-dense areas or in low-rise apartment buildings. Rat presence may also limit residents ability to enjoy nearby outdoor spaces, which otherwise might buffer stress experienced during a stay-at-home order. Proactive rat control may be needed to mitigate rat-associated health risks during future stay-at-home orders.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Alessandro Carollo",
-        "author_inst": "University of Trento"
+        "author_name": "Maureen H Murray",
+        "author_inst": "Lincoln Park Zoo"
       },
       {
-        "author_name": "Andrea Bizzego",
-        "author_inst": "University of Trento"
+        "author_name": "Kaylee A Byers",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Giulio Gabrieli",
-        "author_inst": "Nanyang Technological University"
+        "author_name": "Jacqueline Buckley",
+        "author_inst": "Lincoln Park Zoo"
       },
       {
-        "author_name": "Keri Ka-Yee Wong",
-        "author_inst": "Department of Psychology and Human Development, University College London, London, UK"
+        "author_name": "Seth B Magle",
+        "author_inst": "Lincoln Park Zoo"
       },
       {
-        "author_name": "Adrian Raine",
-        "author_inst": "Departments of Criminology, Psychiatry, and Psychology, University of Pennsylvania"
+        "author_name": "Dorothy Maffei",
+        "author_inst": "University of Illinois at Chicago"
       },
       {
-        "author_name": "Gianluca Esposito",
-        "author_inst": "Nanyang Technological University"
+        "author_name": "Preeya Waite",
+        "author_inst": "DePaul University"
+      },
+      {
+        "author_name": "Danielle German",
+        "author_inst": "Johns Hopkins University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.11.25.20238998",
@@ -1010044,17 +1013532,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.11.28.20240259",
-    "rel_title": "Threatening second wave of COVID-19 is imminent: A deep learning perspective",
+    "rel_doi": "10.1101/2020.11.27.20240036",
+    "rel_title": "Rapid disappearance of influenza following the implementation of COVID-19 mitigation measures in Hamilton, Ontario",
     "rel_date": "2020-11-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.28.20240259",
-    "rel_abs": "When the entire world is waiting restlessly for a safe and effective COVID-19 vaccine that could soon become a reality, numerous countries around the globe are grappling with unprecedented surges of new COVID-19 cases. As the number of new cases is skyrocketing, pandemic fatigue and public apathy towards different intervention strategies are posing new challenges to the government officials to combat the pandemic. Henceforth, it is indispensable for the government officials to understand the future dynamics of COVID-19 flawlessly in order to develop strategic preparedness and resilient response planning. In light of the above circumstances, probable future outbreak scenarios in Brazil, Russia and the United kingdom have been sketched in this study with the help of four deep learning models: long short term memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN) and multivariate convolutional neural network (MCNN). In our analysis, CNN algorithm has outperformed other deep learning models in terms of validation accuracy and forecasting consistency. It has been unearthed in our study that CNN can provide robust long term forecasting results in time series analysis due to its capability of essential features learning, distortion invariance and temporal dependence learning. However, the prediction accuracy of LSTM algorithm has been found to be poor as it tries to discover seasonality and periodic intervals from any time series dataset, which were absent in our studied countries. Our study has highlighted the promising validation of using convolutional neural networks instead of recurrent neural networks when it comes to forecasting with very few features and less amount of historical data.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.27.20240036",
+    "rel_abs": "BackgroundPublic health measures, such as social distancing and closure of schools and non-essential services, were rapidly implemented in Canada to interrupt the spread of the novel coronavirus disease 2019 (COVID-19).\n\nObjectiveWe sought to investigate the impact of mitigation measures during the spring wave of COVID-19 on the incidence of other laboratory-confirmed respiratory viruses in Hamilton, Ontario.\n\nMethodsAll nasopharyngeal swab specimens (n = 57,503) submitted for routine respiratory virus testing at a regional laboratory serving all acute-care hospitals in Hamilton, Ontario between January 2010 and June 2020 were reviewed. Testing for influenza A/B, respiratory syncytial virus, human metapneumovirus, parainfluenza I-III, adenovirus and rhinovirus/enterovirus was done routinely using a laboratory-developed polymerase chain reaction multiplex respiratory viral panel. A Bayesian linear regression model was used to determine the trend of positivity rates of all influenza samples for the first 26 weeks of each year from 2010 to 2019. The mean positivity rate of Bayesian inference was compared with the weekly reported positivity rate of influenza samples in 2020.\n\nResultsThe positivity rate of influenza in 2020 diminished sharply following the population-wide implementation of COVID-19 interventions. Weeks 12-26 reported 0% positivity for influenza, with the exception of 0.1% reported in week 13.\n\nConclusionsPublic health measures implemented during the COVID-19 pandemic were associated with a reduced incidence of other respiratory viruses and should be considered to mitigate severe seasonal influenza and other respiratory virus pandemics.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Khondoker Nazmoon Nabi",
-        "author_inst": "Bangladesh University of Engineering and Technology"
+        "author_name": "Kevin Zhang",
+        "author_inst": "University of Toronto"
+      },
+      {
+        "author_name": "Avika Misra",
+        "author_inst": "University of Ottawa"
+      },
+      {
+        "author_name": "Patrick J. Kim",
+        "author_inst": "McMaster University"
+      },
+      {
+        "author_name": "Seyed M. Moghadas",
+        "author_inst": "York University"
+      },
+      {
+        "author_name": "Joanne M. Langley",
+        "author_inst": "Dalhousie University"
+      },
+      {
+        "author_name": "Marek Smieja",
+        "author_inst": "McMaster University"
       }
     ],
     "version": "1",
@@ -1011510,59 +1015018,55 @@
     "category": "bioengineering"
   },
   {
-    "rel_doi": "10.1101/2020.11.30.20240721",
-    "rel_title": "Remote working in mental health services: a rapid umbrella review of pre-COVID-19 literature",
+    "rel_doi": "10.1101/2020.11.25.20234914",
+    "rel_title": "The efficacy and safety of hydroxychloroquine in COVID19 patients : a multicenter national retrospective cohort",
     "rel_date": "2020-11-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20240721",
-    "rel_abs": "BackgroundTele-mental health care has been rapidly adopted to maintain services during the pandemic, and there is now substantial interest in its future role. Service planning and policy making for recovery from the pandemic and beyond should draw not only on COVID-19 experiences, but also on the substantial research evidence accumulated prior to this.\n\nAimsto conduct an umbrella review of systematic reviews of research literature and evidence-based guidance on remote working in mental health, including both qualitative and quantitative literature.\n\nMethodThree databases were searched between January 2010 and August 2020 for systematic reviews meeting pre-defined criteria. Reviews retrieved were independently screened and those meeting inclusion criteria were synthesised and assessed for risk of bias. Narrative synthesis was used to report findings\n\nResultsNineteen systematic reviews met inclusion criteria. Fifteen examined clinical effectiveness, eight reported on aspects of tele-mental health implementation, ten reported on acceptability to service users and clinicians, two on cost-effectiveness and one on guidance. Most reviews were assessed as low quality. Findings suggested that video-based communication could be as effective and acceptable as face-face formats, at least in the short-term. Evidence was lacking on extent of digital exclusion and how it can be overcome, or on significant context such as children and young people and inpatient settings.\n\nConclusionsThis umbrella review suggests that tele-mental health has potential to be an effective and acceptable form of service delivery. However, we found limited evidence on impacts of large-scale implementation across catchment areas. Combining previous evidence and COVID-19 experiences may allow realistic planning for future tele-mental health implementation.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20234914",
+    "rel_abs": "BackgroundHydroxychloroquine is an antimalarial drug that received worldwide news and media attention in the treatment of COVID-19 patients. This drug was used based on its antimicrobial and antiviral properties despite lack of definite evidence of clinical efficacy. In this study, we aim to assess the efficacy and safety of using Hydroxychloroquine in treatment of COVID-19 patients who are admitted in acute care hospitals in Bahrain.\n\nMethodologyWe conducted retrospective cohort study on a random sample of admitted COVID19 patients between 24 February and 31 July 2020. The study was conducted in four acute care COVID19 hospitals in Bahrain. Data was extracted from the medical records. The primary endpoint was the requirement of non-invasive ventilation, intubation or death. Secondary endpoint was length of hospitalization for survivors. Three methods of analysis were used to control for confounding factors: logistic multivariate regression, propensity score adjusted regression and matched propensity score analysis.\n\nResultsA random sample of 1571 patients were included, 440 of which received HCQ (treatment group) and 1131 did not receive it (control group). Our results showed that HCQ did not have a significant effect on primary outcomes due to COVID-19 infection when compared to controls after adjusting for confounders (OR 1.43 95% CI 0.85 to 2.37, P value=0.17). Co-administration of azithromycin had no effect on primary outcomes (OR 2.7 95% CI 0.82 to 8.85 P value =0.10). HCQ was found to be associated with increased risk of hypoglycemia (OR 10.9 95% CI 1.72 - 69.49, P value =0.011) and diarrhea(OR 2.8, 95% CI 1.4-5.5, P value =0.003), but not QT prolongation(OR=1.92, 95% CI 0.95-3.9, P value =0.06) or cardiac arrhythmia.(OR=1.06, 95% CI 0.55-2.05, P value =0.85).\n\nConclusionOur results showed no significant beneficial effect of using hydroxychloroquine on the outcome of COVID-19 patients. Moreover, the risk of hypoglycemia due to hydroxychloroquine would possess a significant risk for out of hospital use.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Phoebe Barnett",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Lucy Goulding",
-        "author_inst": "King's College London"
+        "author_name": "Abdulkarim Abdulrahman",
+        "author_inst": "National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Mohammed Bin Khalifa Cardiac Centre, Bahrain"
       },
       {
-        "author_name": "Cecilia Casetta",
-        "author_inst": "King's College London"
+        "author_name": "Islam AlSayed",
+        "author_inst": "King Hamad University Hospital, Bahrain"
       },
       {
-        "author_name": "Harriet Jordan",
-        "author_inst": "King's College London"
+        "author_name": "Marwa AlMadhi",
+        "author_inst": "School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom"
       },
       {
-        "author_name": "Luke Sheridan Rains",
-        "author_inst": "University College London"
+        "author_name": "Jumana AlArayedh",
+        "author_inst": "Ministry of Health, Bahrain"
       },
       {
-        "author_name": "Thomas Steare",
-        "author_inst": "University College London"
+        "author_name": "Sara Jaafar Mohamed",
+        "author_inst": "King Hamad University Hospital, Bahrain"
       },
       {
-        "author_name": "Julie Williams",
-        "author_inst": "King's College London"
+        "author_name": "Aesha Khalid Sharif",
+        "author_inst": "Ministry of Health, Bahrain"
       },
       {
-        "author_name": "Lisa Wood",
-        "author_inst": "University College London"
+        "author_name": "Khadija Alansari",
+        "author_inst": "King Hamad University Hospital, Bahrain"
       },
       {
-        "author_name": "Fiona Gaughran",
-        "author_inst": "King's College London"
+        "author_name": "Abdulla Ismael AlAwadhi",
+        "author_inst": "National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Bahrain Defence Force hospital, Bahrain"
       },
       {
-        "author_name": "Sonia Johnson",
-        "author_inst": "University College London"
+        "author_name": "Manaf AlQahtani",
+        "author_inst": "Royal College of Surgeons in Ireland, Bahrain ; National Taskforce for Combating the Coronavirus (COVID-19), Bahrain ; Bahrain Defence Force hospital, Bahrain"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.11.30.402487",
@@ -1012804,25 +1016308,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.11.24.20238139",
-    "rel_title": "Prediction of evolution of the second wave of Covid-19 pandemic in Italy",
+    "rel_doi": "10.1101/2020.11.25.20237776",
+    "rel_title": "Body mass index and risk of COVID-19 diagnosis, hospitalisation, and death: a population-based multi-state cohort analysis including 2,524,926 people in Catalonia, Spain",
     "rel_date": "2020-11-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.24.20238139",
-    "rel_abs": "A relevant problem in the study of the Covid-19 pandemic is the study of its temporal evolution. Such evolution depends on a number of factors, among which the average rate of contacts between susceptible and infected individuals, the duration of infectiousness and the transmissibility, that is the probability of infection after a contact between susceptible and infected individuals. In a previous study, we analyzed the potentiality of a number of distributions to describe the evolution of the pandemic and the potentiality of each distribution to mathematically predict the evolution of the pandemic in Italy. Since the number of daily tests was changing and increasing with time, we used the ratio of the new daily cases per swab. We considered distributions of the type of Gauss (normal), Gamma, Beta, Weibull, Lognormal and in addition of the type of the Planck blackbody radiation law. The Planck law, describing the amount of energy of the electromagnetic radiation emitted by a black body at each wavelength or at each frequency, marked in 1900 the beginning of Quantum Mechanics. The result of our analysis was that, among the considered distributions, the Planck law has the best potentiality to mathematically predict the evolution of the pandemic and the best fitting capability. In this paper, we analyze the time evolution of the second wave of the Covid-19 pandemic in Italy and in particular we predict the ratio of the new daily cases per swab at Christmas 2020 using the data in the interval from 17 Oct to 21 Nov. According to Figure 4 and Figure 8, the prediction for such a ratio around Christmas is approximately within 6% and 7%. In this study there is also an attempt to account for the effects of the governmental containment measures.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20237776",
+    "rel_abs": "ObjectiveTo investigate associations between body mass index (BMI) and risk of COVID-19 diagnosis, hospitalisation with COVID-19, and COVID-19-related death, accounting for potential effect modification by age and sex.\n\nDesignPopulation-based cohort study.\n\nSettingPrimary care records covering >80% of the Catalonian population (Spain), linked to region-wide testing, hospital, and mortality records from March to May 2020.\n\nParticipantsPeople aged [&ge;]18 years with at least one measurement of weight and height from the general population and with at least one year of prior medical history available.\n\nMain outcome measuresCause-specific hazard ratios (HR) with 95% confidence intervals for each outcome.\n\nResultsOverall, 2,524,926 participants were followed up for a median of 67 days. A total of 57,443 individuals were diagnosed with COVID-19, 10,862 were hospitalised with COVID-19, and 2,467 had a COVID-19-related death. BMI was positively associated with being diagnosed as well as hospitalised with COVID-19. Compared to a BMI of 22kg/m2, the HR (95%CI) of a BMI of 31kg/m2 was 1.22 (1.19-1.24) for COVID-19 diagnosis, and 1.88 (1.75-2.03) and 2.01 (1.86-2.18) for hospitalisation without and with a prior outpatient diagnosis, respectively. The relation between BMI and risk of COVID-19 related death was J-shaped. There was a modestly higher risk of death among individuals with BMIs[&le;]19 kg/m2 and a more pronounced increasing risk for BMIs [&ge;]37 kg/m2 and [&ge;]40 kg/m2 among those who were previously hospitalised with COVID-19 and diagnosed with COVID-19 in outpatient settings, respectively. The increase in risk for COVID-19 outcomes was particularly pronounced among younger patients.\n\nConclusionsThere is a monotonic association between BMI and COVID-19 infection and hospitalisation risks, but a J-shaped one with mortality. More research is needed to unravel the mechanisms underlying these relationships.\n\nSummary boxesO_ST_ABSSection 1: What is already known on this topicC_ST_ABSO_LIA high body mass index (BMI) has previously been associated in a linear and non-linear fashion with an increased risk of multiple health outcomes; these associations may vary by individual factors such as age and sex.\nC_LIO_LIObesity has been identified as a risk factor for COVID-19 severity and mortality. However, the role of general adiposity in relation to COVID-19 outcomes has mostly been studied by dichotomizing BMI (below or above 30 kg/m2) or by a diagnostic code indicating obesity.\nC_LIO_LITwo studies have investigated BMI (as a continuous variable) in relation to COVID-19 outcomes, accounting for non-linearity: one conducted in a tested population sample of the UK Biobank found BMI is related in a dose-response manner with the risk of testing positive for COVID-19; another conducted in a hospital setting in New York reported a J-shaped association between BMI and the risk of intubation or death. These studies were limited in sample size and were prone to collider bias due to the participants restriction to tested and hospitalised patients. No studies have described the association between BMI and COVID-19 outcomes across the natural history of the disease (from no disease to symptomatic disease, hospitalisation, and mortality) using data from diverse health settings.\nC_LI\n\nSection 2: What this study addsO_LIWe provide a comprehensive analysis of the association between BMI and the course of the COVID-19 disease in the general population of a Spanish region during the first wave of the pandemic, using linked data capturing outpatient clinical diagnoses, RT-PCR test results, hospitalisations, and mortality (inside and outside of the hospital setting).\nC_LIO_LIWe found that BMI is positively associated with being diagnosed as well as hospitalised with COVID-19, and is linked in a J-shaped fashion with the risk of COVID-19 related death.\nC_LIO_LIThe association between BMI and COVID-19 related outcomes is modified by age and sex; particularly, the risk of COVID-19 outcomes related to increased BMI is higher for those aged between 18 and 59 years, compared to those in older age groups.\nC_LI",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Ignazio Ciufolini",
-        "author_inst": "University of Salento"
+        "author_name": "Martina Recalde",
+        "author_inst": "1) Fundacio Institut Universitari per a la recerca a l Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; 2) Universitat Autonoma de Ba"
       },
       {
-        "author_name": "Antonio Paolozzi",
-        "author_inst": "School of Aerospace Engineering, Sapienza University of Rome"
+        "author_name": "Andrea Pistillo",
+        "author_inst": "1) Fundacio Institut Universitari per a la recerca a l Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain"
+      },
+      {
+        "author_name": "Sergio Fernandez-Bertolin",
+        "author_inst": "1) Fundacio Institut Universitari per a la recerca a l Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain"
+      },
+      {
+        "author_name": "Elena Roel",
+        "author_inst": "1) Fundacio Institut Universitari per a la recerca a l Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; 2) Universitat Autonoma de Ba"
+      },
+      {
+        "author_name": "Maria Aragon",
+        "author_inst": "1) Fundacio Institut Universitari per a la recerca a l Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain"
+      },
+      {
+        "author_name": "Heinz Freisling",
+        "author_inst": "1) International Agency for Research on Cancer (IARC-WHO), 150 Cours Albert Thomas, 69008 Lyon, France"
+      },
+      {
+        "author_name": "Daniel Prieto-Alhambra",
+        "author_inst": "1) Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, UK"
+      },
+      {
+        "author_name": "Edward Burn",
+        "author_inst": "1) Fundacio Institut Universitari per a la recerca a l Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; 2) Centre for Statistics in M"
+      },
+      {
+        "author_name": "Talita Duarte-Salles",
+        "author_inst": "1) Fundacio Institut Universitari per a la recerca a l Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1014730,45 +1018262,61 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2020.11.25.399055",
-    "rel_title": "Triple Combination Nitazoxanide, Ribavirin, and Hydroxychloroquine results in the multiplicative reduction of in vitro SARS-CoV-2 viral replication",
+    "rel_doi": "10.1101/2020.11.26.399436",
+    "rel_title": "Host-directed FDA-approved drugs with antiviral activity against SARS-CoV-2 identified by hierarchical in silico/in vitro screening methods",
     "rel_date": "2020-11-26",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.25.399055",
-    "rel_abs": "BackgroundAn immediate unmet medical need exists to test and develop existing approved drugs against SARS-COV-2. Despite many efforts, very little progress has been made regarding finding low-cost oral medicines that can be made widely available worldwide to address the global pandemic.\n\nMethodsWe sought to examine if a triple combination of nitazoxanide (using its active metabolite tizoxanide), ribavirin, and hydroxychloroquine would lead to a multiplicative effects on viral replication of SARS-COV-2 resulting in a significant reduction of virus yield using VERO E6 cells as a model of viral replication.\n\nResultsVirus yield measured in PFU/ml was ~ 2 logs lower with triple combination versus either drug alone, resulting in the prolongation of time to peak cytopathic effects (CPE). The time to produce 50% CPE increased from 2.8 days for viral controls versus 5.3 days for triple combination therapy. Finally, for each 1-log reduction in virus yield 24 hours post-infection, there was an additional 0.7-day delay in onset of CPE.\n\nConclusionsA triple combination of tizoxanide, ribavirin, and hydroxychloroquine produced a reduction in SARS-COV-2 viral replication in Vero E6 cells, warranting exploration in additional cell lines as well as human clinical trials.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.26.399436",
+    "rel_abs": "The unprecedent situation generated by the COVID-19 global emergency prompted us to actively work to fight against this pandemic by searching for repurposable agents among FDA approved drugs to shed light into immediate opportunities for the treatment of COVID-19 patients.\n\nIn the attempt to proceed toward a proper rationalization of the search for new antivirals among approved drugs, we carried out a hierarchical in silico/in vitro protocol which successfully combines virtual and biological screening to speed up the identification of host-directed therapies against COVID-19 in an effective way.\n\nTo this end a multi-target virtual screening approach focused on host-based targets related to viral entry followed by the experimental evaluation of the antiviral activity of selected compounds has been carried out. As a result, five different potentially repurposable drugs interfering with viral entry, cepharantine, clofazimine, metergoline, imatinib and efloxate, have been identified.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Elena Lian",
-        "author_inst": "Colorado State University"
+        "author_name": "Tiziana Ginez",
+        "author_inst": "CIB-CSIC"
       },
       {
-        "author_name": "Carley McAlister",
-        "author_inst": "Colorado State University"
+        "author_name": "Urtzi Garaigorta",
+        "author_inst": "CNB-CSIC"
       },
       {
-        "author_name": "Gabriela Ramirez",
-        "author_inst": "Colorado State University"
+        "author_name": "David Ramirez",
+        "author_inst": "Universidad Autonoma de Chile"
       },
       {
-        "author_name": "David N Chernoff",
-        "author_inst": "Synavir Corporation"
+        "author_name": "Victoria Castro",
+        "author_inst": "CNB-CSIC"
       },
       {
-        "author_name": "Gregory Went",
-        "author_inst": "Synavir Corporation"
+        "author_name": "Vanesa Nozal",
+        "author_inst": "CIB-CSIC"
       },
       {
-        "author_name": "Justin Hoopes",
-        "author_inst": "Synavir Corporation"
+        "author_name": "Ines Maestro",
+        "author_inst": "CIB-CSIC"
       },
       {
-        "author_name": "Rushika Perera",
-        "author_inst": "Colorado State University"
+        "author_name": "Javier Garcia-Carceles",
+        "author_inst": "CIB-CSIC"
+      },
+      {
+        "author_name": "Nuria E Campillo",
+        "author_inst": "CIB-CSIC"
+      },
+      {
+        "author_name": "Ana Martinez",
+        "author_inst": "CSIC"
+      },
+      {
+        "author_name": "Pablo Gastaminza",
+        "author_inst": "CNB-CSIC"
+      },
+      {
+        "author_name": "Carmen Gil",
+        "author_inst": "CSIC"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "new results",
     "category": "microbiology"
   },
@@ -1016428,45 +1019976,73 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2020.11.23.20237198",
-    "rel_title": "The sensitivity of SARS-CoV-2 antigen tests in the view of large-scale testing",
+    "rel_doi": "10.1101/2020.11.24.20237560",
+    "rel_title": "Demography, social contact patterns and the COVID-19 burden in different settings of Ethiopia: a modeling study",
     "rel_date": "2020-11-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.23.20237198",
-    "rel_abs": "ObjectivesAntigen tests have recently emerged as an interesting alternative to SARS-CoV-2 diagnostic PCR, thought to be valuable especially for the screening of bigger communities. To check appropriateness of the antigen based testing, we determined sensitivity of two point-of-care antigen tests when applied to a cohort of COVID-19 symptomatic, COVID-19 asymptomatic and healthy persons.\n\nMethodsWe examined nasopharyngeal swabs with antigen test 1 (Panbio Covid-19 Ag Rapid Test, Abbott) and antigen test 2 (Standard F Covid-19 Ag FIA, SD Biosensor). An additional nasopharyngeal and oropharyngeal swab of the same individual was checked with PCR (Allplex SARS-nCoV-2, Seegene). Within a 4-day period in October 2020, we collected specimens from 591 subjects. Of them, 290 had COVID-19 associated symptoms.\n\nResultsWhile PCR positivity was detected in 223 cases, antigen test 1 and antigen test 2 were found positive in 148 (sensitivity 0.664, 95% CI 0.599 - 0.722) and 141 (sensitivity 0.623, 95% CI 0.558 - 0.684) patients, respectively. When only symptomatic patients were analysed, sensitivity increased to 0.738 (95% CI 0.667 - 0.799) for the antigen test 1 and to 0.685 (95% CI 0.611 - 0.750) for the antigen test 2. The substantial drop in sensitivity to 12.9% (95% CI 0.067 - 0.234) was observed for samples with the PCR threshold cycle above > 30.\n\nConclusionsLow sensitivity of antigen tests leads to the considerable risk of false negativity. It is advisable to implement repeated testing with high enough frequency if the antigen test is used as a frontline screening tool.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.24.20237560",
+    "rel_abs": "BackgroundCOVID-19 spread may have a dramatic impact in countries with vulnerable economies and limited availability of, and access to, healthcare resources and infrastructures. However, in sub-Saharan Africa a low prevalence and mortality have been observed so far.\n\nMethodsWe collected data on individuals social contacts in Ethiopia across geographical contexts characterized by heterogeneous population density, work and travel opportunities, and access to primary care. We assessed how socio-demographic factors and observed mixing patterns can influence the COVID-19 disease burden, by simulating SARS-CoV-2 transmission in remote settlements, rural villages, and urban neighborhoods, under the current school closure mandate.\n\nResultsFrom national surveillance data, we estimated a net reproduction number of 1.62 (95%CI 1.55-1.70). We found that, at the end of an epidemic mitigated by school closure alone, 10-15% of the overall population would have been symptomatic and 0.3-0.4% of the population would require mechanical ventilation and/or possibly result in a fatal outcome. Higher infection attack rates are expected in more urbanized areas, but the highest incidence of critical disease is expected in remote subsistence farming settlements.\n\nConclusionsThe relatively low burden of COVID-19 in Ethiopia can be explained by the estimated mixing patterns, underlying demography and the enacted school closures. Socio-demographic factors can also determine marked heterogeneities across different geographical contexts within the same country. Our findings can contribute to understand why sub-Saharan Africa is experiencing a relatively lower attack rate of severe cases compared to high income countries.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Pavel Drevinek",
-        "author_inst": "2nd Faculty of Medicine, Charles University and Motol University Hospital"
+        "author_name": "Filippo Trentini",
+        "author_inst": "Bruno Kessler Foundation"
       },
       {
-        "author_name": "Jakub Hurych",
-        "author_inst": "2nd Faculty of Medicine, Charles University and Motol University Hospital"
+        "author_name": "Giorgio Guzzetta",
+        "author_inst": "Bruno Kessler Foundation"
       },
       {
-        "author_name": "Zdenek Kepka",
-        "author_inst": "Motol University Hospital"
+        "author_name": "Margherita Galli",
+        "author_inst": "Bruno Kessler Foundation"
       },
       {
-        "author_name": "Ales Briksi",
-        "author_inst": "Motol University Hospital"
+        "author_name": "Agnese Zardini",
+        "author_inst": "Bruno Kessler Foundation"
       },
       {
-        "author_name": "Michal Kulich",
-        "author_inst": "Faculty of Mathematics and Physics, Charles University"
+        "author_name": "Fabio Manenti",
+        "author_inst": "Doctors with Africa CUAMM"
+      },
+      {
+        "author_name": "Giovanni Putoto",
+        "author_inst": "Doctors with Africa CUAMM"
       },
       {
-        "author_name": "Miroslav Zajac",
-        "author_inst": "Motol University Hospital"
+        "author_name": "Valentina Marziano",
+        "author_inst": "Bruno Kessler Foundation"
       },
       {
-        "author_name": "Petr Hubacek",
-        "author_inst": "2nd Faculty of Medicine, Charles University and Motol University Hospital"
+        "author_name": "Worku Gamshie Nigussa",
+        "author_inst": "Doctors with Africa CUAMM"
+      },
+      {
+        "author_name": "Ademe Tsegaye",
+        "author_inst": "Doctors with Africa CUAMM"
+      },
+      {
+        "author_name": "Alessandro Greblo",
+        "author_inst": "Doctors with Africa CUAMM"
+      },
+      {
+        "author_name": "Alessia Melegaro",
+        "author_inst": "Bocconi University"
+      },
+      {
+        "author_name": "Marco Ajelli",
+        "author_inst": "Indiana University School of Public Health"
+      },
+      {
+        "author_name": "Stefano Merler",
+        "author_inst": "Bruno Kessler Foundation"
+      },
+      {
+        "author_name": "Piero Poletti",
+        "author_inst": "Bruno Kessler Foundation"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1018174,43 +1021750,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.11.20.20233890",
-    "rel_title": "A Data Driven Change-point Epidemic Model for Assessing the Impact of Large Gathering and Subsequent Movement Control Order on COVID-19 Spread in Malaysia",
+    "rel_doi": "10.1101/2020.11.20.20220749",
+    "rel_title": "Community Transmission of SARS-CoV-2 by Fomites: Risks and Risk Reduction Strategies",
     "rel_date": "2020-11-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20233890",
-    "rel_abs": "The second wave of COVID-19 in Malaysia is largely attributed to a mass gathering held in Sri Petaling between February 27, 2020 and March 1, 2020, which contributed to an exponential rise of COVID-19 cases in the country. Starting March 18, 2020, the Malaysian government introduced four consecutive phases of a Movement Control Order (MCO) to stem the spread of COVID-19. The MCO was implemented through various non-pharmaceutical interventions (NPIs). The reported number of cases reached its peak by the first week of April and then started to reduce, hence proving the effectiveness of the MCO. To gain a quantitative understanding of the effect of MCO on the dynamics of COVID-19, this paper develops a class of mathematical models to capture the disease spread before and after MCO implementation in Malaysia. A heterogeneous variant of the Susceptible-Exposed-Infected-Recovered (SEIR) model is developed with additional compartments for asymptomatic transmission. Further, a change-point is incorporated to model the before and after disease dynamics, and is inferred based on data. Related statistical analyses for inference are developed in a Bayesian framework and are able to provide quantitative assessments of (1) the impact of the Sri Petaling gathering, and (2) the extent of decreasing transmission during the MCO period. The analysis here also quantitatively demonstrates how quickly transmission rates fall under effective NPI implemention within a short time period.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20220749",
+    "rel_abs": "SARS-CoV-2, the virus responsible for the COVID-19 pandemic, is perceived to be primarily transmitted via person-to-person contact, through droplets produced while talking, coughing, and sneezing. Transmission may also occur through other routes, including contaminated surfaces; nevertheless, the role that surfaces have on the spread of the disease remains contested. Here we use the Quantitative Microbial Risk Assessment framework to examine the risks of community transmission of SARS-CoV-2 through contaminated surfaces and to evaluate the effectiveness of hand and surface disinfection as potential interventions. The risks posed by contacting surfaces in communities are low (average of the median risks 1.6x10-4 - 5.6x10-9) for community infection prevalence rates ranging from 0.2-5%. Hand disinfection substantially reduces relative risks of transmission independently of the diseases prevalence and the frequency of contact, even with low (25% of people) or moderate (50% of people) compliance. In contrast, the effectiveness of surface disinfection is highly dependent on the prevalence and the frequency of contacts. The work supports the current perception that contaminated surfaces are not a primary mode of transmission of SARS-CoV-2 and affirms the benefits of making hand disinfectants widely available.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Sarat Chandra Dass",
-        "author_inst": "Heriot-Watt University Malaysia Campus"
-      },
-      {
-        "author_name": "Wai Meng Kwok",
-        "author_inst": "Heriot-Watt University Malaysia Campus"
-      },
-      {
-        "author_name": "Gavin J Gibson",
-        "author_inst": "Heriot-Watt University Edinburgh Campus"
-      },
-      {
-        "author_name": "Balvinder S Gill",
-        "author_inst": "Institute for Medical Research Malaysia"
-      },
-      {
-        "author_name": "Bala M Sundram",
-        "author_inst": "Institute for Medical Research Malaysia"
+        "author_name": "Ana K Pitol",
+        "author_inst": "Imperial College London"
       },
       {
-        "author_name": "Sarbhan Singh",
-        "author_inst": "Institute for Medical Research Malaysia"
+        "author_name": "Timothy R Julian",
+        "author_inst": "Eawag, Swiss Federal Institute of Aquatic Science and Technology"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.11.21.20236067",
@@ -1019596,51 +1023156,43 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.11.21.392555",
-    "rel_title": "Interactions of anti-COVID-19 drug candidates with multispecific ABC and OATP drug transporters",
+    "rel_doi": "10.1101/2020.11.21.392670",
+    "rel_title": "A repurposed, blood gene signature is associated with poor outcomes in SARS-CoV-2",
     "rel_date": "2020-11-23",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.21.392555",
-    "rel_abs": "In the COVID-19 epidemic, several repurposed drugs have been proposed to alleviate the major health effects of the disease. These drugs are often applied together with analgesics or non-steroid anti-inflammatory compounds, and co-morbid patients may also be treated with anticancer, cholesterol-lowering or antidiabetic agents. Since drug ADME-tox properties may be significantly affected by multispecific transporters, here we examined the interactions of the repurposed drugs with the key human multidrug transporters, present in the major tissue barriers and strongly affecting pharmacokinetics. Our in vitro studies, using a variety of model systems, explored the interactions of the antimalarial agents chloroquine and hydroxychloroquine, the antihelmintic ivermectin, and the proposed antiviral compounds, ritonavir, lopinavir, favipiravir and remdesivir with the ABCB1/Pgp, ABCG2/BCRP and ABCC1/MRP1 exporters, as well as the OATP2B1 and OATP1A2 uptake transporters. The results presented here show numerous pharmacologically relevant transporter interactions and may provide a warning for the potential toxicities of these repurposed drugs, especially in drug combinations at the clinic.",
-    "rel_num_authors": 8,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.21.392670",
+    "rel_abs": "Poor outcomes after SARS-CoV-2 infection are difficult to predict. Survivors may develop pulmonary fibrosis. We previously identified a 52-gene signature in peripheral blood, predictive of mortality in Idiopathic Pulmonary Fibrosis. In this study, we analyzed this signature in SARS-CoV-2 infected individuals and identified genomic risk profiles with significant differences in outcomes. Analysis of single cell expression data shows that monocytes, red blood cells, neutrophils and dendritic cells are the cellular source of the high risk gene signature.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Agnes Telbisz",
-        "author_inst": "Research Centre for Natural Sciences"
-      },
-      {
-        "author_name": "Csilla Ambrus",
-        "author_inst": "Solvo Biotechnology Ltd"
-      },
-      {
-        "author_name": "Orsolya Mozner",
-        "author_inst": "Research Centre for Natural Sciences"
+        "author_name": "Brenda M Juan-Guardela",
+        "author_inst": "NCH Healthcare System, University of South Florida"
       },
       {
-        "author_name": "Edit Szabo",
-        "author_inst": "Research Centre for Natural Sciences"
+        "author_name": "Jiehuan Sun",
+        "author_inst": "University of Illinois at Chicago"
       },
       {
-        "author_name": "Gyorgy Varady",
-        "author_inst": "Research Centre for Natural Sciences"
+        "author_name": "Tong Zhang",
+        "author_inst": "University of Illinois at Chicago"
       },
       {
-        "author_name": "Eva Bakos",
-        "author_inst": "Research Centre for Natural Sciences"
+        "author_name": "Bing Xu",
+        "author_inst": "University of Illinois at Chicago"
       },
       {
-        "author_name": "Balazs Sarkadi",
-        "author_inst": "Research Centre for Natural Sciences"
+        "author_name": "Gaetane Michaud",
+        "author_inst": "University of South Florida"
       },
       {
-        "author_name": "Csilla Ozvegy-Laczka",
-        "author_inst": "Research Centre for Natural Sciences"
+        "author_name": "Jose D. Herazo-Maya",
+        "author_inst": "NCH Healthcare System, University of South Florida"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "pharmacology and toxicology"
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.11.21.392407",
@@ -1021362,47 +1024914,63 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.11.19.20234849",
-    "rel_title": "Community factors and excess mortality in first wave of the COVID-19 pandemic.",
+    "rel_doi": "10.1101/2020.11.21.392639",
+    "rel_title": "Anti-COVID-19 efficacy of ivermectin in the golden hamster",
     "rel_date": "2020-11-22",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.19.20234849",
-    "rel_abs": "Risk factors for increased risk of death from Coronavirus Disease 19 (COVID-19) have been identified1,2 but less is known on characteristics that make communities resilient or vulnerable to the mortality impacts of the pandemic. We applied a two-stage Bayesian spatial model to quantify inequalities in excess mortality at the community level during the first wave of the pandemic in England. We used geocoded data on all deaths in people aged 40 years and older during March-May 2020 compared with 2015-2019 in 6,791 local communities. Here we show that communities with an increased risk of excess mortality had a high density of care homes, and/or high proportion of residents on income support, living in overcrowded homes and/or high percent of people with a non-White ethnicity (including Black, Asian and other minority ethnic groups). Conversely, after accounting for other community characteristics, we found no association between population density or air pollution and excess mortality. Overall, the social and environmental variables accounted for around 15% of the variation in mortality at community level. Effective and timely public health and healthcare measures that target the communities at greatest risk are urgently needed if England and other industrialised countries are to avoid further widening of inequalities in mortality patterns during the second wave.",
-    "rel_num_authors": 7,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.21.392639",
+    "rel_abs": "The devastating coronavirus disease 2019 (COVID-19) pandemic, due to SARS-CoV-2, has caused more than 47 million confirmed cases and more than 1.2 million human deaths around the globe1, and most of the severe cases of COVID-19 in humans are associated with neurological symptoms such as anosmia and ageusia, and uncontrolled inflammatory immune response2-5. Among therapeutic options6-8, the use of the anti-parasitic drug ivermectin (IVM), has been proposed, given its possible anti-SARS-CoV-2 activity9. Ivermectin is a positive allosteric modulator of the -7 nicotinic acetylcholine receptor10, which has been suggested to represent a target for the control of Covid-19 infection11, with a potential immunomodulatory activity12. We assessed the effects of IVM in SARS-CoV-2-intranasally-inoculated golden Syrian hamsters. Even though ivermectin had no effect on viral load, SARS-Cov-2-associated pathology was greatly attenuated. IVM had a sex-dependent and compartmentalized immunomodulatory effect, preventing clinical deterioration and reducing olfactory deficit in infected animals. Importantly, ivermectin dramatically reduced the Il-6/Il-10 ratio in lung tissue, which likely accounts for the more favorable clinical presentation in treated animals. Our data support IVM as a promising anti-COVID-19 drug candidate.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Bethan Davies",
-        "author_inst": "Imperial College London"
+        "author_name": "Guilherme Dias de Melo",
+        "author_inst": "Institut Pasteur"
       },
       {
-        "author_name": "Brandon L Parkes",
-        "author_inst": "Imperial College London"
+        "author_name": "Fran\u00e7oise Lazarini",
+        "author_inst": "Institut Pasteur"
       },
       {
-        "author_name": "James Bennett",
-        "author_inst": "Imperial College London"
+        "author_name": "Florence Larrous",
+        "author_inst": "Institut Pasteur"
       },
       {
-        "author_name": "Daniela Fecht",
-        "author_inst": "Imperial College London"
+        "author_name": "Lena Feige",
+        "author_inst": "Institut Pasteur"
       },
       {
-        "author_name": "Marta Blangiardo",
-        "author_inst": "Imperial College London"
+        "author_name": "Lauriane Kergoat",
+        "author_inst": "Institut Pasteur"
       },
       {
-        "author_name": "Majid Ezzati",
-        "author_inst": "Imperial College London"
+        "author_name": "Agnes Marchio",
+        "author_inst": "Institut Pasteur"
       },
       {
-        "author_name": "Paul Elliott",
-        "author_inst": "Imperial College London"
+        "author_name": "Pascal Pineau",
+        "author_inst": "Institut Pasteur"
+      },
+      {
+        "author_name": "Marc Lecuit",
+        "author_inst": "Institut Pasteur"
+      },
+      {
+        "author_name": "Pierre-Marie Lledo",
+        "author_inst": "Institut Pasteur"
+      },
+      {
+        "author_name": "Jean-Pierre Changeux",
+        "author_inst": "Institut Pasteur"
+      },
+      {
+        "author_name": "Herve Bourhy",
+        "author_inst": "Institut Pasteur"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.11.20.392381",
@@ -1023844,47 +1027412,67 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.11.18.20225029",
-    "rel_title": "The Invasive Respiratory Infection Surveillance (IRIS) Initiative reveals significant reductions in invasive bacterial infections during the COVID-19 pandemic",
-    "rel_date": "2020-11-20",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.18.20225029",
-    "rel_abs": "BackgroundStreptococcus pneumoniae, Haemophilus influenzae and Neisseria meningitidis are leading causes of invasive diseases including bacteraemic pneumonia and meningitis, and of secondary infections post-viral respiratory disease. They are typically transmitted via respiratory droplets. We investigated rates of invasive disease due to these pathogens during the early phase of the COVID-19 pandemic.\n\nMethodsLaboratories in 26 countries across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae and N meningitidis from 1 January 2018 to 31 May 2020. Weekly cases in 2020 vs 2018-2019 were compared. Streptococcus agalactiae data were collected from nine laboratories for comparison to a non-respiratory pathogen. The stringency of COVID-19 containment measures was quantified by the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed by Google COVID-19 Community Mobility Reports. Interrupted time series modelling quantified changes in rates of invasive disease in 2020 relative to when containment measures were imposed.\n\nFindingsAll countries experienced a significant, sustained reduction in invasive diseases due to S pneumoniae, H influenzae and N meningitidis, but not S agalactiae, in early 2020, which coincided with the introduction of COVID-19 containment measures in each country. Similar impacts were observed across most countries despite differing stringency in COVID-19 control policies. There was no evidence of a specific effect due to enforced school closures.\n\nInterpretationThe introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of these bacterial respiratory pathogens, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide.",
-    "rel_num_authors": 7,
+    "rel_doi": "10.1101/2020.11.18.388140",
+    "rel_title": "Detecting SARS-CoV-2 variants with SNP genotyping",
+    "rel_date": "2020-11-19",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.18.388140",
+    "rel_abs": "Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020- and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 76% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with our marker panel at a cost of < {pound}1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Angela B Brueggemann",
-        "author_inst": "University of Oxford"
+        "author_name": "Helen Harper",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Melissa J Jansen van Rensburg",
-        "author_inst": "University of Oxford"
+        "author_name": "Amanda  J Burridge",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "David Shaw",
-        "author_inst": "University of Oxford"
+        "author_name": "Mark Winfield",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Noel D McCarthy",
-        "author_inst": "University of Warwick"
+        "author_name": "Adam Finn",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Keith A Jolley",
-        "author_inst": "University of Oxford"
+        "author_name": "Andrew  D Davidson",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Martin CJ Maiden",
-        "author_inst": "University of Oxford"
+        "author_name": "David Matthews",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Mark PG van der Linden",
-        "author_inst": "University Hospital RWTH Aachen"
+        "author_name": "Stephanie Hutchings",
+        "author_inst": "Public Health England South West"
+      },
+      {
+        "author_name": "Barry Vipond",
+        "author_inst": "Public Health England South West"
+      },
+      {
+        "author_name": "Nisha Jain",
+        "author_inst": "3CR Biosciences"
+      },
+      {
+        "author_name": "Keith  J Edwards",
+        "author_inst": "University of Bristol"
+      },
+      {
+        "author_name": "Gary Barker",
+        "author_inst": "University of Bristol"
+      },
+      {
+        "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium",
+        "author_inst": "-"
       }
     ],
     "version": "1",
     "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "type": "new results",
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.11.18.388850",
@@ -1025458,27 +1029046,39 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.11.16.20232850",
-    "rel_title": "The impact of COVID-19 employment shocks on suicide and poverty alleviation programs: An early-stage investigation",
+    "rel_doi": "10.1101/2020.11.16.20227389",
+    "rel_title": "Designing Efficient Contact Tracing Through Risk-Based Quarantining",
     "rel_date": "2020-11-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20232850",
-    "rel_abs": "This paper examines whether the COVID-19-induced employment shocks are associated with increases in suicides and safety net use in the second and third quarters of 2020. We exploit plausibly exogenous regional variation in the magnitude of the employment shocks in Japan and adopt a difference-in-differences research design to examine and control for possible confounders. Our preferred point estimates suggest that a one-percentage-point increase in the unemployment rate in the second quarter of 2020 is associated with, approximately, an additional 0.52 suicides, 28 unemployment benefit recipients, 88 recipients of a temporary loan program, and 10 recipients of public assistance per 100,000 population per month. A simple calculation based on these estimates suggests that if a region experienced a one-percentage-point increase in the unemployment rate caused by the COVID-19 crisis in the second quarter of 2020, which is roughly equivalent to the third-highest regional employment shock, this would be associated with 37.4%, 60.5%, and 26.5% increases in the total, female, and male suicide rates respectively in July 2020 compared with July 2019. Our baseline findings are robust to several different model specifications, although we do not assert that our research design perfectly solves the problem of estimation bias.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20227389",
+    "rel_abs": "Contact tracing for COVID-19 is especially challenging because transmission often occurs in the absence of symptoms and because a purported 20% of cases cause 80% of infections, resulting in a small risk of infection for some contacts and a high risk for others. Here, we introduce risk-based quarantine, a system for contact tracing where each cluster (a group of individuals with a common source of exposure) is observed for symptoms when tracing begins, and clusters that do not display them are released from quarantine. We show that, under our assumptions, risk-based quarantine reduces the amount of quarantine time served by more than 30%, while achieving a reduction in transmission similar to standard contact tracing policies where all contacts are quarantined for two weeks. We compare our proposed risk-based quarantine approach against test-driven release policies, which fail to achieve a comparable level of transmission reduction due to the inability of tests to detect exposed people who are not yet infectious but will eventually become so. Additionally, test-based release policies are expensive, limiting their effectiveness in low-resource environments, whereas the costs imposed by risk-based quarantine are primarily in terms of labor and organization.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Michihito Ando",
-        "author_inst": "Rikkyo University"
+        "author_name": "Andrew Perrault",
+        "author_inst": "Center for Research on Computation and Society, Harvard University, Cambridge, MA"
+      },
+      {
+        "author_name": "Marie Charpignon",
+        "author_inst": "Institute for Data, Systems, and Society, MIT, Cambridge, MA"
       },
       {
-        "author_name": "Masato Furuichi",
-        "author_inst": "Teikyo University"
+        "author_name": "Jonathan Gruber",
+        "author_inst": "Department of Economics, MIT, Cambridge, MA"
+      },
+      {
+        "author_name": "Milind Tambe",
+        "author_inst": "Center for Research on Computation and Society, Harvard University, Cambridge, MA"
+      },
+      {
+        "author_name": "Maimuna S. Majumder",
+        "author_inst": "Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA and Department of Pediatrics, Harvard Medical School, Boston, MA, USA"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health economics"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2020.11.16.20232488",
@@ -1026864,25 +1030464,101 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.11.16.20232884",
-    "rel_title": "Comparative Efficacy and Safety of Current Drugs against COVID-19: a Systematic Review and Net-work Meta Analysis",
+    "rel_doi": "10.1101/2020.11.17.20233080",
+    "rel_title": "COVID-19: more than a little flu? Insights from the Swiss hospital-based surveillance of Influenza and COVID-19",
     "rel_date": "2020-11-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20232884",
-    "rel_abs": "The rapid spread of coronavirus disease (COVID-19) has greatly disrupted the livelihood of many people around the world. To date, more than 35.16 million COVID-19 cases with 1.037million total deaths have been reported worldwide. Compared with China, where the disease was first reported, cases of COVID-19, the number of confirmed cases for the disease in the rest of the world have been incredibly high. Even though several dugs have been suggested to be used against the disease, the said interventions should be backed by empirical clinical evidence. Therefore, this paper provides a systematic review and a meta-analysis of efficacy and safety of different COVID-19 drugs.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSCurrently, Covid-19 is one of the most urgent and significant health challenge, globally. However, so far there is no specific and effective treatment strategy against the disease. Nonetheless, there are numerous debates over the effectiveness and potential adverse effects of different COVID-19 antivirals. In general, there is invaluable need to continually report on new advances and successes against COVID-19, apparently to aid in managing the pandemic.\n\nAdded value of this studyThis study provides a comprehensive, evidence-based guide on the management of multiple COVID-19 symptoms. In particular, we provide a review of 14 drugs, placebos and standard treatments against COVID 19. Meanwhile, we also performed a meta-analysis based on four clinical outcome indicators, to measure and compare the efficacy and safety of current interventions.\n\nImplications of all the available evidenceFindings of this research will guide clinical decision in COVID-19 patients. It will also provide a basis for predicting clinical outcomes such as efficacy, mortality and safety of interventions against the disease.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20233080",
+    "rel_abs": "BackgroundCoronavirus disease 19 (COVID-19) has frequently been colloquially compared to the seasonal influenza, but comparisons based on empirical data are scarce.\n\nAimsTo compare in-hospital outcomes for patients admitted with community-acquired COVID-19 to patients with community-acquired influenza in Switzerland.\n\nMethodsPatients >18 years, who were admitted with PCR proven COVID-19 or influenza A/B infection to 14 participating Swiss hospitals were included in a prospective surveillance. Primary and secondary outcomes were the in-hospital mortality and intensive care unit (ICU) admission between influenza and COVID-19 patients. We used Cox regression (cause-specific models, and Fine & Gray subdistribution) to account for time-dependency and competing events with inverse probability weighting to account for confounders.\n\nResultsIn 2020, 2843 patients with COVID-19 were included from 14 centers and in years 2018 to 2020, 1361 patients with influenza were recruited in 7 centers. Patients with COVID-19 were predominantly male (n=1722, 61% vs. 666 influenza patients, 48%, p<0.001) and were younger than influenza patients (median 67 years IQR 54-78 vs. median 74 years IQR 61-84, p<0.001). 363 patients (12.8%) died in-hospital with COVID-19 versus 61 (4.4%) patients with influenza (p<0.001). The final, adjusted subdistribution Hazard Ratio for mortality was 3.01 (95% CI 2.22-4.09, p<0.001) for COVID-19 compared to influenza, and 2.44 (95% CI, 2.00-3.00, p<0.001) for ICU admission.\n\nConclusionEven in a national healthcare system with sufficient human and financial resources, community-acquired COVID-19 was associated with worse outcomes compared to community-acquired influenza, as the hazards of in-hospital death and ICU admission were [~]3-fold higher.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Yi Li",
-        "author_inst": "China Pharmaceutical University"
+        "author_name": "Georg Froehlich",
+        "author_inst": "HeartClinic Lucerne, St. Annastrasse 32, 6006 Lucerne, Switzerland and Charite  Universitaetsmedizin Berlin, Berlin, Germany"
       },
       {
-        "author_name": "Wei He",
-        "author_inst": "China Pharmaceutical University"
+        "author_name": "Marlieke De Kraker",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Mohammed Abbas",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Olivia Keiser",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Amaury Thiabaud",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Maroussia Roulens",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Alexia Cusini",
+        "author_inst": "Kantonsspital Graubuenden, Department for General Medicine, Loestrasse 170, CH-7000 Chur"
+      },
+      {
+        "author_name": "Domenica Flury",
+        "author_inst": "Kantonsspital St. Gallen, Rorschacher Strasse 95, CH-9007 St. Gallen, Switzerland"
+      },
+      {
+        "author_name": "Peter Schreiber",
+        "author_inst": "University Hospital Zurich, Department of Infectious Diseases and Hospital Epidemiology, Raemistrasse 100, 8091 Zuerich"
+      },
+      {
+        "author_name": "Michael Buettcher",
+        "author_inst": "Cantonal Hospital Lucerne, Pediatric Infectious Diseases, Spitalstrasse, 6000 Luzern, Switzerland"
+      },
+      {
+        "author_name": "Natascia Corti",
+        "author_inst": "Department for General Medicine, Klinik Hirslanden, Witellikerstrasse 40, 8032 Zuerich,  Switzerland"
+      },
+      {
+        "author_name": "Danielle Vuichard-Gysin",
+        "author_inst": "Department for General Medicine, Spital Thurgau, Waldeggstrasse 8A, 8501 Frauenfeld"
+      },
+      {
+        "author_name": "Nicolas Troillet",
+        "author_inst": "Department for Infectious Diseases, Hopital du Valais, Av. Grand-Champsec 80, 1951 Sion"
+      },
+      {
+        "author_name": "Julien Sauser",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Roman Gaudenz",
+        "author_inst": "Department for General Medicine, Kantonsspital Nidwalden, Ennetmooserstrasse 19, 6370 Stans"
+      },
+      {
+        "author_name": "Lauro Damonti",
+        "author_inst": "Department of Infectious Diseases, Bern University Hospital, Freiburgstrasse, 3010 Bern"
+      },
+      {
+        "author_name": "Carlo Balmelli",
+        "author_inst": "Ente Ospedaliero Cantonale Ticino, Division of Infection control and Hospital Epidemiology, CH-6500 Bellinzona, Switzerland"
+      },
+      {
+        "author_name": "Anne Iten",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Andreas Widmer",
+        "author_inst": "Department for Infectious Diseases, University Hospital Basel, Spitalstrasse 21/Petersgraben 4, 4031 Basel, Switzerland"
+      },
+      {
+        "author_name": "Stephan Harbarth",
+        "author_inst": "Geneva University Hospitals and Faculty of Medicine, Infection Control program,Gabrielle-Perret-Gentil4, 1205 Geneva, Switzerland"
+      },
+      {
+        "author_name": "Rami Sommerstein",
+        "author_inst": "Bern University Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1028426,43 +1032102,47 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.11.16.20231100",
-    "rel_title": "Deconditioning in people living with dementia during the COVID-19 pandemic: findings from the Promoting Activity, Independence and Stability in Early Dementia (PrAISED) process evaluation",
+    "rel_doi": "10.1101/2020.11.16.20232009",
+    "rel_title": "The total number and mass of SARS-CoV-2 virions in an infected person",
     "rel_date": "2020-11-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20231100",
-    "rel_abs": "BackgroundRestrictions introduced in response to the COVID-19 pandemic led to increased risk of deconditioning in the general population. No empirical evidence of this effect however has been empirically gathered in people living with dementia.\n\nObjectiveThis study aims to identify the causes and effects of COVID-19-related deconditioning in people living with dementia.\n\nDesignLongitudinal phenomenological qualitative study.\n\nSubjectsParticipants living with dementia, their carers and therapists involved in the Promoting Activity, Independence and Stability in Early Dementia (PrAISED) process evaluation during the COVID-19 pandemic.\n\nMethodsQualitative interviews with participants were conducted remotely at two time points. The data were analysed through deductive thematic analysis.\n\nResultsTwenty-four participants living with dementia, 19 carers and 15 therapists took part in the study. A self-reinforcing pattern was common, whereby lockdown made the person apathetic, demotivated, socially-disengaged, and frailer. This reduced activity levels, which in turn reinforced the effects of deconditioning over time. Without external supporters, most participants lacked the motivation / cognitive abilities to keep active. Provided the proper infrastructure and support, some participants could use tele-rehabilitation to combat deconditioning.\n\nConclusionThe added risks and effects of deconditioning on people with dementia require considerable efforts from policy makers and clinicians to ensure that they initiate and maintain physical activity in prolonged periods of social distancing. Delivering rehabilitation in the same way as before the pandemic might not be feasible or sustainable and innovative approaches must be found. Digital support for this population has shown promising results, but still remains a challenge.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20232009",
+    "rel_abs": "Quantitatively describing the time course of the SARS-CoV-2 infection within an infected individual is important for understanding the current global pandemic and possible ways to combat it. Here we integrate the best current knowledge about the typical viral load of SARS-CoV-2 in bodily fluids and host tissues to estimate the total number and mass of SARS-CoV-2 virions in an infected person. We estimate that each infected person carries 109-1011 virions during peak infection, with a total mass in the range of 1-100 g, which curiously implies that all SARS-CoV-2 virions currently circulating within human hosts have a collective mass of only 0.1-10 kg. We combine our estimates with the available literature on host immune response and viral mutation rates to demonstrate how antibodies markedly outnumber the spike proteins and the genetic diversity of virions in an infected host covers all possible single nucleotide substitutions.\n\nSignificanceKnowing the absolute numbers of virions in an infection promotes better understanding of the disease dynamics and the response of the immune system. Here we use the best current knowledge on the concentrations of virions in infected individuals to estimate the total number and mass of SARS-CoV-2 virions in an infected person. Although each infected person carries an estimated 1-100 billion virions during peak infection, their total mass is no more than 0.1 mg. This curiously implies that all SARS-CoV-2 virions currently in all human hosts have a mass of between 100 gram and 10 kilogram. Combining the known mutation rate and our estimate of the number of infectious virions we quantify the formation rate of genetic variants.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Claudio Di Lorito",
-        "author_inst": "University of Nottingham"
+        "author_name": "Ron Sender",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Tahir Masud",
-        "author_inst": "Nottingham University Hospitals NHS Trust"
+        "author_name": "Yinon Moise Bar-On",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "John Gladman",
-        "author_inst": "University of Notitngham"
+        "author_name": "Shmuel Gleizer",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Maureen Godfrey",
-        "author_inst": "University of Nottingham"
+        "author_name": "Biana Bernsthein",
+        "author_inst": "Ragon Institute of MGH, MIT and Harvard"
       },
       {
-        "author_name": "Marianne Dunlop",
-        "author_inst": "University of Nottingham"
+        "author_name": "Avi Flamholz",
+        "author_inst": "University of California"
       },
       {
-        "author_name": "Rowan H Harwood",
-        "author_inst": "University of Nottingham"
+        "author_name": "Rob Phillips",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Ron Milo",
+        "author_inst": "Weizmann Institute of Science"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "geriatric medicine"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.11.16.20230003",
@@ -1030524,77 +1034204,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.11.12.20230912",
-    "rel_title": "Prevalence of IgG antibodies against the severe acute respiratory syndrome coronavirus-2 among healthcare workers in Tennessee during May and June, 2020",
+    "rel_doi": "10.1101/2020.11.12.20230656",
+    "rel_title": "Development and validation of a highly sensitive and specific electrochemical assay to quantify anti-SARS-CoV-2 IgG antibodies to facilitate pandemic surveillance and monitoring of vaccine response",
     "rel_date": "2020-11-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20230912",
-    "rel_abs": "SARS-CoV-2 seroprevalence was low (<1%) in this large population of healthcare workers (HCWs) across the state of Tennessee (n=11,787) in May-June 2020. Among those with PCR results, 81.5% of PCR and antibody test results were concordant. SARS-CoV-2 seroprevalence was higher among HCWs working in high-community-transmission regions and among younger workers.\n\nImportanceThese results may be seen as a baseline assessment of SARS-CoV-2 seroprevalence among HCWs in the American South during a period of growth, but not yet saturation, of infections among susceptible populations. In fact, this period of May-June 2020 was marked by the extension of renewed and sustained community-wide transmission after mandatory quarantine periods expired in several more populous regions of Tennessee. Where community transmission remains low, HCWs may still be able to effectively mitigate SARS-CoV-2 transmission, preserving resources for populations at high risk of severe disease, and these sorts of data help highlight such strategies.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20230656",
+    "rel_abs": "Amperial is a novel assay platform that uses immobilized antigen in a conductive polymer gel followed by an electrochemical detection. A highly specific and sensitive assay was developed to quantify levels of IgG antibodies to SARS-CoV-2 in saliva. After establishing linearity and limit of detection we established a reference range of 5 standard deviations above the mean. There were no false positives in 667 consecutive saliva samples obtained prior to 2019. Saliva was obtained from 34 patients who had recovered from documented COVID-19 or had documented positive serologies. All of the patients with symptoms severe enough to seek medical attention had positive antibody tests and 88% overall had positive results.\n\nWe obtained blinded paired saliva and plasma samples from 14 individuals. The plasma was analyzed using an EUA-FDA cleared ELISA kit and the saliva was analyzed by our Amperial assay. All 5 samples with negative plasma titers were negative in saliva testing. Eight of the 9 positive plasma samples were positive in saliva and 1 had borderline results. A CLIA validation was performed as a laboratory developed test in a high complexity laboratory.\n\nA quantitative non-invasive saliva based SARSCoV-2 antibody test was developed and validated with sufficient specificity to be useful for population-based monitoring and monitoring of individuals following vaccination.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Peter F Rebeiro",
-        "author_inst": "Vanderbilt University School of Medicine, Department of Medicine, Divisions of Infectious Diseases & Epidemiology; Department of Biostatistics"
-      },
-      {
-        "author_name": "Kara J Levinson",
-        "author_inst": "Tennessee Department of Health, Division of Laboratory Services"
-      },
-      {
-        "author_name": "Lindsay Jolly",
-        "author_inst": "Tennessee Department of Health, Division of Laboratory Services"
-      },
-      {
-        "author_name": "Elizabeth Kassens",
-        "author_inst": "Tennessee Department of Health, Division of Laboratory Services"
-      },
-      {
-        "author_name": "George J Dizikes",
-        "author_inst": "Tennessee Department of Health, Division of Laboratory Services"
+        "author_name": "Samantha H. Chiang",
+        "author_inst": "UCLA School of Dentistry"
       },
       {
-        "author_name": "Richard S Steece",
-        "author_inst": "Tennessee Department of Health, Division of Laboratory Services"
+        "author_name": "Michael Tu",
+        "author_inst": "Liquid Diagnostics, LLC"
       },
       {
-        "author_name": "David C Metzger",
-        "author_inst": "Ballad Health"
+        "author_name": "Jordan Cheng",
+        "author_inst": "UCLA School of Dentistry"
       },
       {
-        "author_name": "Matthew Loos",
-        "author_inst": "Ballad Health"
+        "author_name": "Fang Wei",
+        "author_inst": "UCLA School of Dentistry"
       },
       {
-        "author_name": "Ron Buchheit",
-        "author_inst": "Department Of Emergency Medicine, University Of Tennessee College of Medicine Chattanooga, Erlanger Health System"
+        "author_name": "Feng Li",
+        "author_inst": "UCLA School of Dentistry"
       },
       {
-        "author_name": "Lisa D Duncan",
-        "author_inst": "University of Tennessee Medical Center, Department of Pathology"
+        "author_name": "David Chia",
+        "author_inst": "UCLA Health"
       },
       {
-        "author_name": "Lori A Rolando",
-        "author_inst": "Vanderbilt University School of Medicine, Department of Medicine, Division of General Internal Medicine & Public Health and Vanderbilt Health and Wellness"
+        "author_name": "Omai B Garner",
+        "author_inst": "University of California Los Angeles"
       },
       {
-        "author_name": "Jonathan Schmitz",
-        "author_inst": "Vanderbilt University School of Medicine , Department of Pathology, Microbiology and Immunology"
+        "author_name": "Sukantha Chandrasekaran",
+        "author_inst": "UCLA Department of Pathology and Laboratory Medicine"
       },
       {
-        "author_name": "Heather A Hart",
-        "author_inst": "Vanderbilt University School of Medicine, Department of Surgery, Division of Trauma"
+        "author_name": "Richard Bender",
+        "author_inst": "Liquid Diagnostics LLC"
       },
       {
-        "author_name": "David M Aronoff",
-        "author_inst": "Vanderbilt University School of Medicine, Department of Medicine, Division of Infectious Diseases; Department of Pathology, Microbiology and Immunology"
+        "author_name": "Charles Strom",
+        "author_inst": "UCLA"
       },
       {
-        "author_name": "- Tennessee COVID-19 Serology Study Team",
-        "author_inst": ""
+        "author_name": "David T. W. Wong",
+        "author_inst": "University of California Los Angeles School of Dentistry"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1032186,39 +1035850,39 @@
     "category": "cardiovascular medicine"
   },
   {
-    "rel_doi": "10.1101/2020.11.13.20231571",
-    "rel_title": "No evidence of increase in suicide in Greece during the first wave of Covid-19",
+    "rel_doi": "10.1101/2020.11.14.20229096",
+    "rel_title": "Chest CT features of COVID-19 in the region of Abu Dhabi, UAE- A single institute study",
     "rel_date": "2020-11-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.13.20231571",
-    "rel_abs": "Background and ObjectiveMental health outcomes have reportedly worsened in several countries during the Covid-19 pandemic and associated lockdowns. In the present study we examined whether suicides increased in Greece during the first wave of the pandemic.\n\nMethodsWe used daily suicide estimates from a Suicide Observatory in Greece from 2015-2020 and followed three methodologies: A descriptive approach, an interrupted time series analysis, and a differences-in-differences econometric model.\n\nResultsWe did not find any empirical evidence of any increase in suicides during the first wave of Covid-19 and the lockdown in any of the three approaches used.\n\nConclusionsSuicides did not seem to increase during the first wave of covid-19 and lockdown in Greece. However, this does not mean that mental health did not deteriorate, or that we will not observe an increase in suicides during the second wave. Protective factors for Greece during the first wave may include working from home (for those able to tele-work), strong family ties, advertising of a suicide hotline and income support for the unemployed.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.14.20229096",
+    "rel_abs": "OBJECTIVEOur aim is to investigate high resolution CT features of COVID-19 infection in Abu Dhabi, UAE, and to compare the diagnostic performance of CT scan with RT-PCR test.\n\nMETHODSData of consecutive patients who were suspected to have COVID-19 infection and presented to our hospital, was collected from March 2, 2020, until April 12, 2020. All patients underwent RT-PCR test; out of which 53.8% had chest CT scan done. Using RT-PCR as a standard reference, the sensitivity and specify of CT scan was calculated. We also analyzed the most common imaging findings in patients with positive RT-PCR results.\n\nRESULTSThe typical HRCT findings were seen in 50 scans (65.8%) out of total positive ones; 44 (77.2%) with positive RT-PCR results and 6 (31.6%) with negative results. The peripheral disease distribution was seen in 86%, multilobe involvement in 70%, bilateral in 82%, and posterior in 82% of the 50 scans.\n\nThe ground glass opacities were seen in 50/74 (89.3%) of positive RT-PCR group. The recognized GGO patterns in these scans were: rounded 50%, linear 38%, and crazy-paving 24%.\n\nUsing RT-PCR as a standard of reference, chest HRCT scan revealed sensitivity of 68.8% and specificity of 70%.\n\nCONCLUSIONThe commonest HRCT findings in patients with COVID-19 pneumonia were peripheral, posterior, bilateral, multilobe rounded ground glass opacities.",
     "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Sotiris Vandoros",
-        "author_inst": "King's College London and Harvard T.H. Chan School of Public Health, Harvard University"
+        "author_name": "Ghufran Saeed",
+        "author_inst": "Sheikh Khalifa Medical City"
       },
       {
-        "author_name": "Olga Theodorikakou",
-        "author_inst": "Suicide Prevention Center, KLIMAKA NGO"
+        "author_name": "Abeer Al Helali",
+        "author_inst": "SKMC"
       },
       {
-        "author_name": "Kyriakos Katsadoros",
-        "author_inst": "Suicide Prevention Center, KLIMAKA NGO"
+        "author_name": "Safaa Almazrouei",
+        "author_inst": "SKMC"
       },
       {
-        "author_name": "Dimitra Zafeiropoulou",
-        "author_inst": "Suicide Prevention Center, KLIMAKA NGO"
+        "author_name": "Asad Shah",
+        "author_inst": "SKMC"
       },
       {
-        "author_name": "Ichiro Kawachi",
-        "author_inst": "Harvard T.H. Chan School of Public Health, Harvard University"
+        "author_name": "Luai Ahmed",
+        "author_inst": "UAEU"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2020.11.15.20231795",
@@ -1034128,33 +1037792,29 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.11.11.20229815",
-    "rel_title": "Excess mortality for care home residents during the first 23 weeks of the COVID-19 pandemic in England: a national cohort study",
+    "rel_doi": "10.1101/2020.11.11.20229393",
+    "rel_title": "Using Convergent Sequential Design for Rapid Complex Case Study Descriptions: Example of Public Health Briefings During the Onset of the COVID-19 Pandemic",
     "rel_date": "2020-11-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.11.20229815",
-    "rel_abs": "BackgroundTo estimate excess mortality for care home residents during the COVID-19 pandemic in England, exploring associations with care home characteristics.\n\nMethodsDaily number of deaths in all residential and nursing homes in England notified to the Care Quality Commission (CQC) from 1st January 2017 to 7th August 2020. Care home level data linked with CQC care home register to identify homes characteristics: client type (over 65s/children and adults), ownership status (for-profit/not-for-profit; branded/independent), and size (small/medium/large).\n\nExcess deaths computed as the difference between observed and predicted deaths using local authority fixed-effect Poisson regressions on pre-pandemic data. Fixed-effect logistic regressions were used to model odds of experiencing COVID-19 suspected/confirmed deaths.\n\nFindingsUp to 7th August 2020 there were 29,542 (95%CI: 25,176 to 33,908) excess deaths in all care homes. Excess deaths represented 6.5% (95%CI: 5.5% to 7.4%) of all care home beds, higher in nursing (8.4%) than residential (4.6%) homes. 64.7% (95%CI: 56.4% to 76.0%) of the excess deaths were confirmed/suspected COVID-19. Almost all excess deaths were recorded in the quarter (27.4%) of homes with any COVID-19 fatalities.\n\nThe odds of experiencing COVID-19 attributable deaths were higher in homes providing nursing services (OR: 1.8, 95%CI: 1.6 to 2.0); to older people and/or with dementia (OR: 5.5, 95%CI: 4.4 to 6.8); among larger (vs. small) homes (OR: 13.3, 95%CI: 11.5 to 15.4); belonging to a large provider/brand (OR: 1.2, 95%CI: 1.1 to 1.3). There was no significant association with for-profit status of providers.\n\nInterpretationTo limit excess mortality, policy should be targeted at care homes to minimise the risk of ingress of disease and limit subsequent transmission. Our findings provide specific characteristic targets for further research on mechanisms and policy priority.\n\nFundingNIHR.\n\nSummary boxO_ST_ABSEvidence before this studyC_ST_ABSGlobally, residents in care homes have experienced disproportionately high morbidity and mortality from COVID-19. Excess mortality incorporates all direct and indirect mortality effects of the pandemic.\n\nWe searched MEDLINE for published literature, pre-publication databases (medRxiv and Lancet pre-print) and grey literature (ONS and Google) for care homes AND COVID-19 AND mortality, to 31st October 2020. We screened for evidence on excess deaths in care homes in England, and international evidence of the association of COVID-19 deaths and outbreaks with care home characteristics.\n\nOfficial estimates from England and Wales have reported aggregated excess deaths by place of occurrence, but we identified no peer-reviewed excess deaths study in this setting. These aggregates, however, do not account for care home residents dying in other settings (e.g. hospital), nor provide sufficient information to reflect on the impacts of enacted policies over the period, or to inform new policies for future virus waves.\n\nPrevious peer-reviewed and pre-publication studies have also shown the heterogeneous effects of COVID-19 by care home characteristics in other countries. Particularly important from the current literature appears to be care home size, with larger care homes tending to be associated with more negative outcomes in studies with smaller sample sizes. A study from the Lothian region of Scotland additionally found excess deaths concentrated in a minority of homes that experienced an outbreak. However, a national breakdown of excess deaths by care home characteristics is largely lacking from the current literature in England, with a specific market structure and policy context.\n\nAdded value of this studyWe use nationally representative administrative data from all care homes in England to estimate overall excess deaths and by care home characteristics: setting type (nursing or residential home), client types (offering services for people aged 65+ and/or people with dementia or offering services to children and adults), ownership status (whether not-for-profit - charity/NHS/LA-run homes - or for-profit), whether known to be affiliated to a large provider/brand or independent, and classification according to their registered maximum bed capacity (small, medium and large).\n\nWe then used multivariable logistic regression to estimate the adjusted odds of a care home experiencing a suspected or confirmed COVID-19 death across these characteristics.\n\nWe found that only 65% of excess deaths were flagged as officially confirmed/suspected COVID-19 attributed. However, almost all excess deaths occurred in the roughly quarter of care homes that reported at least one suspected/confirmed COVID-19 death. After adjusting for other care home characteristics, larger care homes (vs. small) had the highest odds of experiencing at least one suspected/confirmed COVID-19 death. These findings confirm those from the previous literature, in a unique policy context and with national data.\n\nImplications of all the available evidenceThe fact that nearly all excess deaths occurred in care homes with at least one COVID-19 attributed death suggests that directly-attributed deaths are very likely to be under-recorded. It also suggests that any indirect mortality effect, of COVID-19 and any enacted policies, were predominantly constrained to those homes experiencing an outbreak.\n\nLarger homes are likely to experience higher footfall in general, and so higher probability of contact with an infected individual, which is likely a contributing factor to the association. Furthermore, it might be easier to ensure person-centred protocols in small care homes due to the scale.\n\nThere is an urgent need for further research to explore the mechanisms in relation to care home characteristics. Also, to empirically test effective interventions, in consideration of additional impacts on quality of life and psychological wellbeing. However, until this is possible, prioritising existing resources, such as testing and PPE equipment, for care homes to prevent ingress of disease is key to preventing large excess mortality.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.11.20229393",
+    "rel_abs": "Conceptualizing the public health response to the COVID-19 pandemic response as a complex adaptive system is useful to study its key features of emergence, interdependency, and adaptation yet practical guidance for mixed methods researchers remains limited. This study contributes an illustrative example and discussion for guiding how a mixed methods convergent sequential research design, informed by complexity theory and drawing upon open-access datasets, can rapidly generate complex case study descriptions. This article serves as an essential reference for identifying points of integration within a sequential convergent design using text mining to manage large data volumes and studying complex phenomena using a complexity-informed case study-mixed methods approach to generate novel public health insights.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Marcello Morciano",
-        "author_inst": "University of Manchester"
-      },
-      {
-        "author_name": "Jonathan M Stokes",
-        "author_inst": "University of Manchester"
+        "author_name": "Cheryl Poth",
+        "author_inst": "University of Alberta"
       },
       {
-        "author_name": "Evangelos Kontopantelis",
-        "author_inst": "University of Manchester"
+        "author_name": "Okan Bulut",
+        "author_inst": "University of Alberta"
       },
       {
-        "author_name": "Ian Hall",
-        "author_inst": "University of Manchester"
+        "author_name": "Alexandra M. Aquilina",
+        "author_inst": "University of Alberta"
       },
       {
-        "author_name": "Alexander J Turner",
-        "author_inst": "University of Manchester"
+        "author_name": "Simon J G Otto",
+        "author_inst": "University of Alberta"
       }
     ],
     "version": "1",
@@ -1035834,113 +1039494,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.11.10.20229005",
-    "rel_title": "Non-occupational and occupational factors associated with specific SARS-CoV-2 antibodies among Hospital Workers - a multicentre cross-sectional study",
+    "rel_doi": "10.1101/2020.11.10.20228973",
+    "rel_title": "Comparison of SARS-COV-2 nasal antigen test to nasopharyngeal RT-PCR in mildly symptomatic patients",
     "rel_date": "2020-11-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.10.20229005",
-    "rel_abs": "ObjectivesProtecting healthcare workers (HCW) from Coronavirus Disease-19 (COVID-19) is critical to preserve the functioning of healthcare systems. We therefore assessed seroprevalence and identified risk factors for Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) seropositivity in this population.\n\nMethodsBetween June 22nd and August 15th 2020, HCW from institutions in Northern/Eastern Switzerland were screened for SARS-CoV-2 antibodies. We recorded baseline characteristics, non-occupational and occupational risk factors. We used pairwise tests of associations and multivariable logistic regression to identify factors associated with seropositivity.\n\nResultsAmong 4664 HCW from 23 healthcare facilities, 139 (3%) were seropositive. Non-occupational exposures independently associated with seropositivity were contact with a COVID-19-positive household (adjusted OR=54, 95%-CI: 31-97) and stay in a COVID-19 hotspot (aOR=2.2, 95%-CI: 1.1-3.9). Blood group 0 vs. non-0 (aOR=0.4, 95%-CI: 0.3-0.7), active smoking (aOR=0.5, 95%-CI: 0.3-0.9) and living with children <12 years (aOR=0.3, 95%-CI: 0.2-0.6) were associated with decreased risk. Occupational risk factors were close contact to COVID-19 patients (aOR=2.8, 95%-CI: 1.5-5.5), exposure to COVID-19-positive co-workers (aOR=2.0, 95%-CI: 1.2-3.1), poor knowledge of standard hygiene precautions (aOR=2.0, 95%-CI: 1.3-3.2), and frequent visits to the hospital canteen (aOR=1.9, 95%-CI: 1.2-3.1).\n\nConclusionsLiving with COVID-19-positive households showed by far the strongest association with SARS-CoV-2 seropositivity. We identified several potentially modifiable risk factors, which might allow mitigation of the COVID-19 risk among HCW. The lower risk among those living with children, even after correction for multiple confounders, is remarkable and merits further study.",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.10.20228973",
+    "rel_abs": "IntroductionCOVID 19 has been vastly spreading since December 2019 and the medical teams worldwide are doing their best to limit its spread. In the absence of a vaccine the best way to fight it is by detecting infected cases early and isolate them to prevent its spread. Therefore, a readily available, rapid, and cost-effective test with high specificity and sensitivity for early detection of COVID 19 is required. In this study, we are testing the diagnostic performance of a rapid antigen detection test in mildly symptomatic cases. (RADT).\n\nMethodsThe study included 4183 patients who were mildly symptomatic. A nasal sample for the rapid antigen test and a nasopharyngeal sample was taken from each patient. Statistical analysis was conducted to calculate the sensitivity, specificity, positive predictive value, negative predictive value and kappa coefficient of agreement.\n\nResultsThe prevalence of COVID 19 in the study population was 17.5% (733/4183). The calculated sensitivity and specificity were 82.1% and 99.1% respectively. Kappas coefficient of agreement between the rapid antigen test and RT-PCR was 0.859 (p < 0.001). A stratified analysis was performed and it showed that the sensitivity of the test improved significantly with lowering the cutoff Ct value to 24.\n\nConclusionThe results of the diagnostic assessment of nasal swabs in the RADT used in our study are promising regarding the potential benefit of using them as a screening tool in mildly symptomatic patients. The diagnostic ability was especially high in cases with high viral load. The rapid antigen test is intended to be used alongside RT-PCR and not replace it. RADT can be of benefit in reducing the use of PCR.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Christian R. Kahlert",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland; Children's Hospital of Eastern Switzerland, Depa"
-      },
-      {
-        "author_name": "Raphael Persi",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
-      },
-      {
-        "author_name": "Sabine Guesewell",
-        "author_inst": "Clinical Trials Unit, Cantonal Hospital of St. Gallen, St. Gallen, Switzerland"
-      },
-      {
-        "author_name": "Thomas Egger",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
-      },
-      {
-        "author_name": "Onicio B. Leal-Neto",
-        "author_inst": "Epitrack, Recife, Brazil; Department of Economics, University of Zurich, Zurich, Switzerland"
-      },
-      {
-        "author_name": "Johannes Sumer",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
-      },
-      {
-        "author_name": "Domenica Flury",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
-      },
-      {
-        "author_name": "Angela Brucher",
-        "author_inst": "Psychiatry Services of the Canton of St. Gallen (South), Switzerland"
-      },
-      {
-        "author_name": "Eva Lemmenmeier",
-        "author_inst": "Clienia Littenheid AG, Private Clinic for Psychiatry and Psychotherapy, Littenheid, Switzerland"
-      },
-      {
-        "author_name": "Carsten Moeller",
-        "author_inst": "Rehabilitation Clinic, Zihlschlacht, Switzerland"
-      },
-      {
-        "author_name": "Philip Rieder",
-        "author_inst": "Hirslanden Clinic, Zurich, Switzerland"
-      },
-      {
-        "author_name": "Reto Stocker",
-        "author_inst": "Hirslanden Clinic, Zurich, Switzerland"
-      },
-      {
-        "author_name": "Danielle Vuichard-Gysin",
-        "author_inst": "Thurgau Hospital Group, Division of Infectious Diseases and Hospital Epidemiology, Muensterlingen, Switzerland; Swiss National Center for Infection Prevention ("
-      },
-      {
-        "author_name": "Benedikt Wiggli",
-        "author_inst": "Kantonsspital Baden, Division of Infectious Diseases and Hospital Epidemiology, Baden, Switzerland"
-      },
-      {
-        "author_name": "Werner C. Albrich",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
-      },
-      {
-        "author_name": "Baharak Babouee Flury",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
-      },
-      {
-        "author_name": "Ulrike Besold",
-        "author_inst": "Geriatric Clinic St. Gallen, St. Gallen, Switzerland"
-      },
-      {
-        "author_name": "Jan Fehr",
-        "author_inst": "Department of Public and Global Health, University of Zurich, Zurich, Switzerland"
-      },
-      {
-        "author_name": "Stefan P. Kuster",
-        "author_inst": "Federal Office of Public Health, Bern, Switzerland; University Hospital and University of Zurich, Division of Infectious Diseases and Hospital Epidemiology, Zur"
+        "author_name": "Abdulkarim Abdulrahman",
+        "author_inst": "National task force for combating the corona virus (COVID-19), Mohammed bin Khalifa Cardiac Centre, Bahrain"
       },
       {
-        "author_name": "Allison McGeer",
-        "author_inst": "Sinai Health System, Toronto, Canada"
+        "author_name": "Fathi Mustafa",
+        "author_inst": "Royal College of Surgeons in Ireland - Medical University of Bahrain , Bahrain"
       },
       {
-        "author_name": "Lorenz Risch",
-        "author_inst": "Labormedizinisches Zentrum Dr Risch Ostschweiz AG, Buchs, Switzerland; Private Universitaet im Fuerstentum Liechtenstein, Triesen, Liechtenstein; Center of Labo"
+        "author_name": "Abdulla Ismael AlAwadhi",
+        "author_inst": "National task force for combating the corona virus (COVID-19), Bahrain Defense Force Hospital, Bahrain"
       },
       {
-        "author_name": "Matthias Schlegel",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
+        "author_name": "Qadar Alansari",
+        "author_inst": "Ministry of Finance and National Economy, Bahrain"
       },
       {
-        "author_name": "Pietro Vernazza",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
-      },
-      {
-        "author_name": "Andree Friedl",
-        "author_inst": "Kantonsspital Baden, Division of Infectious Diseases and Hospital Epidemiology, Baden, Switzerland"
+        "author_name": "Batool AlAlawi",
+        "author_inst": "Ministry of Health, Bahrain"
       },
       {
-        "author_name": "Philipp Kohler",
-        "author_inst": "Cantonal Hospital St Gallen, Division of Infectious Diseases and Hospital Epidemiology, St Gallen, Switzerland"
+        "author_name": "Manaf AlQahtani",
+        "author_inst": "National task force for combating the corona virus (COVID-19), Bahrain Defense Force Hospital, Bahrain"
       }
     ],
     "version": "1",
@@ -1037748,47 +1041332,43 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.11.08.20227819",
-    "rel_title": "Detection of COVID-19 Disease from Chest X-Ray Images: A Deep Transfer Learning Framework",
+    "rel_doi": "10.1101/2020.11.08.20227884",
+    "rel_title": "Host genetic liability for severe COVID-19 overlaps with alcohol drinking behavior and diabetic outcomes and in over 1 million participants",
     "rel_date": "2020-11-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.08.20227819",
-    "rel_abs": "World economy as well as public health have been facing a devastating effect caused by the disease termed as Coronavirus (COVID-19). A significant step of COVID-19 affected patients treatment is the faster and accurate detection of the disease which is the motivation of this study. In this paper, implementation of a deep transfer learning-based framework using a pre-trained network (ResNet-50) for detecting COVID-19 from the chest X-rays was done. Our dataset consists of 2905 chest X-ray images of three categories: COVID-19 affected (219 cases), Viral Pneumonia affected (1345 cases), and Normal Chest X-rays (1341 cases). The implemented neural network demonstrates significant performance in classifying the cases with an overall accuracy of 96%. Most importantly, the model has shown a significantly good performance over the current research-based methods in detecting the COVID-19 cases in the test dataset (Precision = 1.00, Recall = 1.00, F1-score = 1.00 and Specificity = 1.00). Therefore, our proposed approach can be adapted as a reliable method for faster and accurate COVID-19 affected case detection.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.08.20227884",
+    "rel_abs": "To distinguish correlation from causation, we performed in-silico analyses of three COVID-19 outcomes (N>1,000,000). We show genetic correlation and putative causality with depressive symptoms, metformin use, and alcohol use. COVID-19 risk loci associated with several hematologic biomarkers. Comprehensive findings inform genetic contributions to COVID-19 epidemiology, molecular mechanisms, and risk factors.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Shadman Sakib",
-        "author_inst": "Leading University"
-      },
-      {
-        "author_name": "Md. Abu Bakr Siddique",
-        "author_inst": "International University of Business Agriculture and Technology"
+        "author_name": "Frank R Wendt",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Mohammad Mahmudur Rahman Khan",
-        "author_inst": "Vanderbilt University"
+        "author_name": "Antonella De Lillo",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Nowrin Yasmin",
-        "author_inst": "Ahsanullah University of Science and Technology"
+        "author_name": "Gita A Pathak",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Anas Aziz",
-        "author_inst": "Military Institute of Science and Technology"
+        "author_name": "Flavio De Angelis",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Madiha Chowdhury",
-        "author_inst": "Bangladesh University of Engineering and Technology"
+        "author_name": "- COVID-19 Host Genetics Initiative",
+        "author_inst": ""
       },
       {
-        "author_name": "Ihtyaz Kader Tasawar",
-        "author_inst": "BRAC University"
+        "author_name": "Renato Polimanti",
+        "author_inst": "Yale School of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "genetic and genomic medicine"
   },
   {
     "rel_doi": "10.1101/2020.11.08.20227470",
@@ -1039730,37 +1043310,153 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2020.11.09.20228684",
-    "rel_title": "Retrospective Analyses of Interventions to Epidemics using a Continuously Updated Model, with Application to the COVID-19 Crisis in New York City",
+    "rel_doi": "10.1101/2020.11.09.20228098",
+    "rel_title": "Peginterferon-lambda for the treatment of COVID-19 in outpatients",
     "rel_date": "2020-11-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228684",
-    "rel_abs": "Retrospective analyses of interventions to epidemics, in which the effectiveness of strategies implemented are compared to hypothetical alternatives, are valuable for performing the cost-benefit calculations necessary to optimize infection countermeasures. SIR (susceptible-infected-removed) models are useful in this regard but are limited by the challenge of deciding how and when to update the numerous parameters as the epidemic changes in response to population behaviors. Behaviors of particular interest include facemasks adoption (at various levels) and social distancing. We present a method that uses a \"dynamic spread function\" to systematically capture the continuous variation in the population behavior, and the gradual change in infection evolution, resulting from interventions. No parameter updates are made by the user. We use the tool to quantify the reduction in infection rate realizable from the population of New York City adopting different facemask strategies during COVID-19. Assuming a baseline facemask of 67% filtration efficiency, calculations show that increasing the efficiency to 80% could have reduced the roughly 5000 new infections per day occurring at the peak of the epidemic to around 4000. Population behavior that may not be varied as part of the retrospective analysis, such as social distancing in a facemask analysis, are automatically captured as part of the calibration of the dynamic spread function.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228098",
+    "rel_abs": "BackgroundThere are currently no effective treatments for outpatients with coronavirus disease 2019 (COVID-19). Interferon-lambda-1 is a Type III interferon involved in the innate antiviral response with activity against respiratory pathogens.\n\nMethodsIn this double-blind, placebo-controlled trial, outpatients with laboratory-confirmed COVID-19 were randomized to a single subcutaneous injection of peginterferon-lambda 180g or placebo within 7 days of symptom onset or first positive swab if asymptomatic. The primary endpoint was proportion negative for SARS-CoV-2 RNA on Day 7 post-injection.\n\nFindingsThere were 30 patients per arm, with median baseline SARS-CoV-2 viral load of 6.71 (IQR 1.3-8.0) log copies/mL. The decline in SARS-CoV-2 RNA was greater in those treated with peginterferon-lambda than placebo (p=0.04). On Day 7, 24 participants (80%) in the peginterferon-lambda group had an undetectable viral load compared to 19 (63%) in the placebo arm (p=0.15). After controlling for baseline viral load, peginterferon lambda treatment resulted in a 4.12-fold (95CI 1.15-16.7, p=0.029) higher likelihood of viral clearance by Day 7. Of those with baseline viral load above 10E6 copies/mL, 15/19 (79%) in the peginterferon-lambda group were undetectable on Day 7 compared to 6/16 (38%) in the placebo group (p=0.012). Adverse events were similar between groups with only mild reversible transaminase elevations more frequently observed in the peginterferon-lambda group.\n\nInterpretationPeginterferon-lambda accelerated viral decline in outpatients with COVID-19 resulting in a greater proportion with viral clearance by Day 7, particularly in those with high baseline viral load. Peginterferon-lambda may have potential to prevent clinical deterioration and shorten duration of viral shedding.\n\n(NCT04354259)\n\nFundingThis study was supported by the Toronto COVID-19 Action Initiative, University of Toronto and the Ontario First COVID-19 Rapid Research Fund. Medication was supplied by Eiger BioPharma.\n\nResearch in ContextTreatment trials for COVID-19 have largely focused on hospitalized patients and no treatments are approved for people with mild to moderate disease in the outpatient setting. A number of studies in ambulatory populations have been registered but no controlled studies in the outpatient setting have been reported to date (Pubmed Search October 20, 2020, COVID-19 treatment; controlled trials). Uncontrolled case series of hydroxychloroquine with or without azithromycin have been reported with mixed results but no clear signal of efficacy and some concerns raised about cardiac toxicity. Treamtent in the outpatient setting has potential to prevent infected individuals from deteriorating and perhaps more importantly, may shorten the duration of viral shedding, reducing the risk of transmission and the duration required for self-isolation, with significant public health and societal impact.\n\nAdded value of this studyThis is the first study to show an antiviral effect in outpatients with COVID-19. After controlling for baseline viral load, those treated with peginterferon-lambda had a 4.12-fold (95%CI 1.15-16.7, p=0.029) higher odds of viral clearance by Day 7 compared to those who received placebo. The viral load decline was faster with pegterferon-lambda and the effect was most pronounced in those with high viral loads. In individuals with a baseline viral load of 10E6 copies/mL or higher, 15/19 (79%) in the peginterferon-lambda arm cleared by Day 7 compared to 6/16 (38%) (p=0.012) in the placebo arm (OR 6.25, 95%CI 1.49-31.1, p=0.012), translating to a median time to viral clearance of 7 days (95%CI 6.2-7.8 days) with peginterferon-lambda compared to 10 days (95%CI 7.8-12.2 days) with placebo (p=0.038). Those with low viral loads (<10E6 copies/mL) cleared quickly in both groups. Peginterferon-lambda was well-tolerated with a similar side effect profile to placebo and no concerning laboratory adverse events.\n\nImplications of all available evidenceThere is no currently approved therapy for outpatients with COVID-19. This study showed that peginterferon-lambda accelerated viral clearance, particularly in those with high baseline viral loads, highlighting the importance of quantitative viral load testing in the evaluation of antiviral agents for COVID-19. Treatment early in the course of disease may prevent clinical deterioration and shorenting of the duration of viral shedding may have important public health impact by limiting transmission and reducing the duration required for self-isolation. Additional trials of peginterferon-lambda and other antiviral strategies in the outpatient setting are required.",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Jenna Osborn",
-        "author_inst": "U. S. FDA"
+        "author_name": "Jordan J. Feld",
+        "author_inst": "Toronto Centre for Liver Disease, Toronto General Hospital, University of Toronto"
+      },
+      {
+        "author_name": "Christopher Kandel",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Shayna Berman",
-        "author_inst": "U. S. FDA"
+        "author_name": "Mia J Biondi",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
       },
       {
-        "author_name": "Sara Bender_Bier",
-        "author_inst": "U. S. FDA"
+        "author_name": "Robert A Kozak",
+        "author_inst": "Sunnybrook Health Sciences Centre, University of Toronto"
+      },
+      {
+        "author_name": "Muhammad Atif Zahoor",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Camille Lemieux",
+        "author_inst": "University Health Network, University of Toronto"
       },
       {
-        "author_name": "Gavin D'Souza",
-        "author_inst": "U. S. FDA"
+        "author_name": "Sergio M Borgia",
+        "author_inst": "Division of Infectious Diseases, William Osler Health System and McMaster University, Hamilton"
+      },
+      {
+        "author_name": "Andrea K Boggild",
+        "author_inst": "University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Jeff Powis",
+        "author_inst": "Michael Garron Hospital, University of Toronto"
+      },
+      {
+        "author_name": "Janine McCready",
+        "author_inst": "Michael Garron Hospital, University of Toronto"
+      },
+      {
+        "author_name": "Darrell HS Tan",
+        "author_inst": "St Michaels Hospital, University of Toronto"
+      },
+      {
+        "author_name": "Tiffany Chan",
+        "author_inst": "Trillium Health Partners, Toronto"
+      },
+      {
+        "author_name": "Bryan Coburn",
+        "author_inst": "University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Deepali Kumar",
+        "author_inst": "University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Atul Humar",
+        "author_inst": "University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Adrienne Chan",
+        "author_inst": "Sunnybrook Health Sciences Centre, University of Toronto"
+      },
+      {
+        "author_name": "Seham Noureldin",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Joshua Booth",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Rachel Hong",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "David Smookler",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Wesam Aleyadeh",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Anjali Patel",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Bethany Barber",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Julia Casey",
+        "author_inst": "Toronto Centre for Liver Disease, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Ryan Hiebert",
+        "author_inst": "Sunnybrook Health Sciences Centre, University of Toronto"
+      },
+      {
+        "author_name": "Henna Mistry",
+        "author_inst": "Sunnybrook Health Sciences Centre, University of Toronto"
+      },
+      {
+        "author_name": "Ingrid Choong",
+        "author_inst": "Eiger BioPharmaceuticals, Palo Alto, California"
       },
       {
-        "author_name": "Matthew Myers",
-        "author_inst": "U. S. FDA"
+        "author_name": "Colin Hislop",
+        "author_inst": "Eiger BioPharmaceuticals, Palo Alto, California"
+      },
+      {
+        "author_name": "Deanna Santer",
+        "author_inst": "The Li Ka Shing Institute of Virology, University of Alberta"
+      },
+      {
+        "author_name": "D. Lorne Tyrrell",
+        "author_inst": "The Li Ka Shing Institute of Virology, University of Alberta"
+      },
+      {
+        "author_name": "Jeffrey S. Glenn",
+        "author_inst": "Departments of Medicine and Microbiology & Immunology, Stanford University School of Medicine, Palo Alto, Ca"
+      },
+      {
+        "author_name": "Adam J. Gehring",
+        "author_inst": "Toronto Centre for Liver Disease, Toronto General Hospital, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Harry LA Janssen",
+        "author_inst": "Toronto Centre for Liver Disease, Toronto General Hospital, University Health Network, University of Toronto"
+      },
+      {
+        "author_name": "Bettina Hansen",
+        "author_inst": "Institute of Health Policy, Management and Evaluation, University of Toronto"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1041852,53 +1045548,69 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.11.07.20227462",
-    "rel_title": "Synthetic Reproduction and Augmentation of COVID-19 Case Reporting Data by Agent-Based Simulation",
+    "rel_doi": "10.1101/2020.11.06.20227330",
+    "rel_title": "The COVID-19 epidemic in the Czech Republic: retrospective analysis of measures (not) implemented during the spring first wave",
     "rel_date": "2020-11-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.07.20227462",
-    "rel_abs": "We generate synthetic data documenting COVID-19 cases in Austria by the means of an agent-based simulation model. The model simulates the transmission of the SARS-CoV-2 virus in a statistical replica of the population and reproduces typical patient pathways on an individual basis while simultaneously integrating historical data on the implementation and expiration of population-wide countermeasures. The resulting data semantically and statistically aligns with an official epidemiological case reporting data set and provides an easily accessible, consistent and augmented alternative. Our synthetic data set provides additional insight into the spread of the epidemic by synthesizing information that cannot be recorded in reality.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.06.20227330",
+    "rel_abs": "Running across the globe for more than a year, the COVID-19 pandemic keeps demonstrating its strength. Despite a lot of understanding, uncertainty regarding the efficiency of interventions still persists. We developed an age-structured epidemic model parameterized with sociological data for the Czech Republic and found that (1) delaying the spring 2020 lockdown by four days produced twice as many confirmed cases by the end of the lockdown period, (2) personal protective measures such as face masks appear more effective than just a reduction of social contacts, (3) only sheltering the elderly is by no means effective, and (4) leaving schools open is a risky strategy. Despite the onset of vaccination, an evidence-based choice and timing of non-pharmaceutical interventions still remains the most important weapon against the COVID-19 pandemic.\n\nOne sentence summaryWe address several issues regarding COVID-19 interventions that still elicit controversy and pursue ignorance",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Nikolas Popper",
-        "author_inst": "Information and Software Engineering, Vienna University of Technology"
+        "author_name": "Jan Smycka",
+        "author_inst": "Center for Theoretical Study, Praha, Czech Republic"
       },
       {
-        "author_name": "Melanie Zechmeister",
-        "author_inst": "DEXHELPP - Decision Support for Health Policy and Planning"
+        "author_name": "Rene Levinsky",
+        "author_inst": "CERGE-EI, Praha, Czech Republic"
       },
       {
-        "author_name": "Dominik Brunmeir",
-        "author_inst": "dwh simulation services"
+        "author_name": "Eva Hromadkova",
+        "author_inst": "CERGE-EI, Praha, Czech Republic"
       },
       {
-        "author_name": "Claire Rippinger",
-        "author_inst": "dwh simulation services"
+        "author_name": "Michal Soltes",
+        "author_inst": "CERGE-EI, Praha, Czech Republic"
       },
       {
-        "author_name": "Nadine Weibrecht",
-        "author_inst": "DEXHELPP - Decision Support for Health Policy and Planning"
+        "author_name": "Josef Slerka",
+        "author_inst": "New Media Studies, Faculty of Arts at the Charles University, Czech Republic"
       },
       {
-        "author_name": "Christoph Urach",
-        "author_inst": "dwh simulation services"
+        "author_name": "Vit Tucek",
+        "author_inst": "Department of Mathematics, University of Zagreb, Croatia"
       },
       {
-        "author_name": "Martin Bicher",
-        "author_inst": "Information and Software Engineering, Vienna University of Technology"
+        "author_name": "Jan Trnka",
+        "author_inst": "Department of Biochemistry, Cell and Molecular Biology, Third Faculty of Medicine, Charles University, Praha, Czech Republic"
       },
       {
-        "author_name": "G\u00fcnter Schneckenreither",
-        "author_inst": "Information and Software Engineering, Vienna University of Technology"
+        "author_name": "Martin Smid",
+        "author_inst": "Czech Academy of Sciences, Institute of Information Theory and Automation, Praha, Czech Republic"
+      },
+      {
+        "author_name": "Milan Zajicek",
+        "author_inst": "Czech Academy of Sciences, Institute of Information Theory and Automation, Praha, Czech Republic"
       },
       {
-        "author_name": "Andreas Rauber",
-        "author_inst": "Information and Software Engineering, Vienna University of Technology"
+        "author_name": "Tomas Diviak",
+        "author_inst": "Department of Criminology, School of Social Sciences, University of Manchester"
+      },
+      {
+        "author_name": "Roman Neruda",
+        "author_inst": "Czech Academy of Sciences, Institute of Computer Science, Praha, Czech Republic"
+      },
+      {
+        "author_name": "Petra Vidnerova",
+        "author_inst": "Czech Academy of Sciences, Institute of Computer Science, Praha, Czech Republic"
+      },
+      {
+        "author_name": "Ludek Berec",
+        "author_inst": "Faculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1043398,91 +1047110,59 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2020.11.10.376673",
-    "rel_title": "SARS-CoV-2 infection causes transient olfactory dysfunction in mice",
+    "rel_doi": "10.1101/2020.11.05.20224436",
+    "rel_title": "Anxiety and depression among people living in quarantine centers during COVID-19 pandemic: A mixed method study from western Nepal",
     "rel_date": "2020-11-10",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.10.376673",
-    "rel_abs": "Olfactory dysfunction caused by SARS-CoV-2 infection represents as one of the most predictive and common symptoms in COVID-19 patients. However, the causal link between SARS-CoV-2 infection and olfactory disorders remains lacking. Herein we demonstrate intranasal inoculation of SARS-CoV-2 induces robust viral replication in the olfactory epithelium (OE), resulting in transient olfactory dysfunction in humanized ACE2 mice. The sustentacular cells and Bowmans gland cells in OE were identified as the major targets of SARS-CoV-2 before the invasion into olfactory sensory neurons. Remarkably, SARS-CoV-2 infection triggers cell death and immune cell infiltration, and impairs the uniformity of OE structure. Combined transcriptomic and proteomic analyses reveal the induction of antiviral and inflammatory responses, as well as the downregulation of olfactory receptors in OE from the infected animals. Overall, our mouse model recapitulates the olfactory dysfunction in COVID-19 patients, and provides critical clues to understand the physiological basis for extrapulmonary manifestations of COVID-19.",
-    "rel_num_authors": 18,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.05.20224436",
+    "rel_abs": "BackgroundIn response to the COVID-19 pandemic, incoming travelers were quarantined at specific centers in Nepal and major checkpoints in Nepal-India border. Nepal adopted a generic public health approaches to control and quarantine returnee migrants, with little attention towards the quality of quarantine facilities and its aftermath, such as the poor mental health of the returnee migrants. The main objective of this study was to explore the status of anxiety and depression, and factors affecting them among returnee migrants living in institutional quarantine centers of western Nepal.\n\nMethodsA mixed method approach was used which included a quantitative survey and in-depth interviews (IDIs). Survey questionnaire utilized Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) tools, which were administered among 441 quarantined returnee migrants and IDIs were conducted among 12 participants which included a mix of quarantined migrants and healthcare workers from the quarantine centres. Descriptive and inferential analyses were conducted on quantitative data; and thematic analysis was utilized for qualitative data.\n\nResultsMild depression (9.1%; 40/441) and anxiety (16.1%, 71/441) was common among respondents followed by moderate depression and anxiety {depression (3.4%; 15/441), anxiety (4.1%, 18/441)} and severe depression and anxiety {depression (1.1%; 5/441), anxiety (0.7%, 3/441)}. Anxiety and depression were independent of their socio-demographic characteristics. Perceived fear of contracting COVID-19, severity and death were prominent among the respondents.\n\nRespondents experienced stigma and discrimination in addition to being at the risk of disease and possible loss of employment and financial responsibilities. In addition, poor (quality and access to) health services, and poor living condition at the quarantine centres adversely affected respondents mental health.\n\nConclusionDepression and anxiety among quarantined population warrants more research. Institutional quarantine centers of Karnali province of Nepal were in poor conditions which adversely impacted mental health of the respondents. Poor resources allocation for health, hygiene and living conditions can be counterproductive to the population quarantined.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Cheng-Feng Qin",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
-      },
-      {
-        "author_name": "Qing Ye",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
-      },
-      {
-        "author_name": "Jia Zhou",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
-      },
-      {
-        "author_name": "Guan Yang",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
-      },
-      {
-        "author_name": "Rui-Ting Li",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Udaya Bahadur BC",
+        "author_inst": "Public Health Service Office Surkhet, Ministry of Social Development, Karnali Province, Nepal"
       },
       {
-        "author_name": "Qi He",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
-      },
-      {
-        "author_name": "Yao Zhang",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
-      },
-      {
-        "author_name": "Shu-Jia Wu",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
-      },
-      {
-        "author_name": "Qi Chen",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Sunil Pokharel",
+        "author_inst": "Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK"
       },
       {
-        "author_name": "Jia-Hui Shi",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
+        "author_name": "Sabika Munikar",
+        "author_inst": "Post Basic Nursing Science Faculty, Om Health Campus, Purbanchal University, Kathmandu, Nepal"
       },
       {
-        "author_name": "Rong-Rong Zhang",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
-      },
-      {
-        "author_name": "Hui-Min Zhu",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
+        "author_name": "Chetan Nidhi Wagle",
+        "author_inst": "Public Health Service Office Surkhet, Ministry of Social Development, Karnali Province, Nepal"
       },
       {
-        "author_name": "Hong-Ying Qiu",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Pratik Adhikary",
+        "author_inst": "School of Public Health, UC Berkeley, USA"
       },
       {
-        "author_name": "Tao Zhang",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
+        "author_name": "Brish Bahadur Shahi",
+        "author_inst": "Health Division, Ministry of Social Development, Karnali Province, Nepal"
       },
       {
-        "author_name": "Yong-Qiang Deng",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Chandra Thapa",
+        "author_inst": "Savitribai Phule Pune University, Pune, Maharashtra, India"
       },
       {
-        "author_name": "Xiao-Feng Li",
-        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
+        "author_name": "Ram Prasad Bhandari",
+        "author_inst": "Province Hospital, Ministry of Social Development, Karnali Province, Nepal"
       },
       {
-        "author_name": "Ping Xu",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
+        "author_name": "Bipin Adhikari",
+        "author_inst": "Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand"
       },
       {
-        "author_name": "Xiao Yang",
-        "author_inst": "State Key Laboratory of Proteomics, National Center for Protein Science (Beijing), Beijing Institute of Lifeomics"
+        "author_name": "Kanchan Thapa",
+        "author_inst": "Central Department of Population Studies, Tribhuvan University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_by",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.11.09.20228320",
@@ -1045111,71 +1048791,99 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.11.06.20226977",
-    "rel_title": "Team contact sports in times of the COVID-19 pandemic- a scientific concept for the Austrian football league",
-    "rel_date": "2020-11-08",
+    "rel_doi": "10.1101/2020.11.05.20226654",
+    "rel_title": "Multiplexed, quantitative serological profiling of COVID-19 from a drop of blood by a point-of-care test",
+    "rel_date": "2020-11-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.06.20226977",
-    "rel_abs": "BackgroundSince the beginning of the COVID -19 pandemic, many contact sport teams are facing major challenges to safely continue training and competition.\n\nObjectiveWe present the design and implementation of a structured monitoring concept for the Austrian national football league\n\nMethods146 professional players from five clubs of the professional Austrian football league were monitored for a period of 12 weeks. Subjective health parameters, PCR- test results and data obtained from a geo-tracking app were collected. Simulations modelling the consequences of a COVID-19 case with increasing reproduction number were computed.\n\nResultsNo COVID-19 infection occurred during the observation period in the players. Infections in the nearer surroundings lead to increased perceived risk of infection. Geo tracking was particularly hindered due to technical problems and reluctance of users. Simulation models suggested a hypothetical shut-down of all training and competition activities.\n\nConclusionsA structured monitoring concept can help to continue contact sports safely in times of a pandemic. Cooperation of all involved is essential.\n\nTrial registrationID: DRKS00022166 15/6/2020 https://www.who.int/ictrp/search/en/\n\nKey Points- The results of this study can inform the development of future prevention and monitoring strategies in professional football and beyond, potentially serving as a blueprint for the safe continuation of sports and physical activity, across a broad range of settings, during and following a pandemic such as COVID-19.\n- Health parameters should be digitally recorded and closely monitored to enable quick response in case of a COVID-19 infection.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.05.20226654",
+    "rel_abs": "Highly sensitive, specific, and point-of-care (POC) serological assays are an essential tool to manage the COVID-19 pandemic. Here, we report on a microfluidic, multiplexed POC test that can profile the antibody response against multiple SARS-CoV-2 antigens--Spike S1 (S1), Nucleocapsid (N), and the receptor binding domain (RBD)--simultaneously from a 60 {micro}L drop of blood, plasma, or serum. We assessed the levels of anti-SARS-CoV-2 antibodies in plasma samples from 19 individuals (at multiple time points) with COVID-19 that required admission to the intensive care unit and from 10 healthy individuals. This POC assay shows good concordance with a live virus microneutralization assay, achieved high sensitivity (100%) and specificity (100%), and successfully tracked the longitudinal evolution of the antibody response in infected individuals. We also demonstrated that we can detect a chemokine, IP-10, on the same chip, which may provide prognostic insight into patient outcomes. Because our test requires minimal user intervention and is read by a handheld detector, it can be globally deployed in the fight against COVID-19 by democratizing access to laboratory quality tests.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Antje van der Zee-Neuen",
-        "author_inst": "Paracelsus Medical University"
+        "author_name": "Jacob T Heggestad",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Dagmar Schaffler-Schaden",
-        "author_inst": "Paracelsus Medical University"
+        "author_name": "David Kinnamon",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Juergen Herfert",
-        "author_inst": "Red Bull Athlete Performance Centre"
+        "author_name": "Lyra Olson",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "James O Brien",
-        "author_inst": "Red Bull Athlete Performance Centre"
+        "author_name": "Jason Liu",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Tim Johansson",
-        "author_inst": "Paracelsus Medical University"
+        "author_name": "Garrett Kelly",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Patrick Kutschar",
-        "author_inst": "patrick.kutschar@pmu.ac.at"
+        "author_name": "Simone Wall",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Alexander Seymer",
-        "author_inst": "University of Salzburg"
+        "author_name": "Cassio Fontes",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Stephan Ludwig",
-        "author_inst": "University of Muenster"
+        "author_name": "Daniel Joh",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Thomas Stoeggl",
-        "author_inst": "University of Salzburg"
+        "author_name": "Angus Hucknall",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "David Keeley",
-        "author_inst": "Electronic Caregiver"
+        "author_name": "Carl Pieper",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Herbert Resch",
-        "author_inst": "Paracelsus Medical University"
+        "author_name": "Ibtehaj Naqvi",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Juergen Osterbrink",
-        "author_inst": "Paracelsus Medical University"
+        "author_name": "Lingye Chen",
+        "author_inst": "Duke University"
       },
       {
-        "author_name": "Maria Flamm",
-        "author_inst": "Paracelsus Medical University"
+        "author_name": "Loretta Que",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Thomas Oguin III",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Smita Nair",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Bruce Sullenger",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Christopher Woods",
+        "author_inst": "Duke University School of Medicine"
+      },
+      {
+        "author_name": "Gregory Sempowski",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Bryan Kraft",
+        "author_inst": "Duke University"
+      },
+      {
+        "author_name": "Asutosh Chilkoti",
+        "author_inst": "Duke University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.11.05.20226449",
@@ -1046885,51 +1050593,71 @@
     "category": "radiology and imaging"
   },
   {
-    "rel_doi": "10.1101/2020.11.05.20226472",
-    "rel_title": "How has Covid-19 affected mental health nurses and the delivery of mental health nursing care in the UK? Results of a mixed methods study",
+    "rel_doi": "10.1101/2020.11.04.20226118",
+    "rel_title": "Elevated COVID-19 outcomes among persons living with diagnosed HIV infection in New York State: Results from a population-level match of HIV, COVID-19, and hospitalization databases",
     "rel_date": "2020-11-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.05.20226472",
-    "rel_abs": "IntroductionWhile evidence has emerged concerning the impact of Covid-19 on the general population and the challenges facing health services, much less is known regarding how the pandemic has directly affected the delivery of mental health nursing care.\n\nAimThis paper aims to explore how Covid-19 has affected the ability of mental health nurses to deliver care in community and inpatient mental health services in the UK.\n\nMethodWe investigated staff reports regarding the impact of the Covid-19 pandemic on mental healthcare and mental health service users in the UK, using a mixed methods online survey. A total of 897 nurses across a range of inpatient and community settings participated.\n\nDiscussionKey themes within the data explore: new ways of working; remote working; risks of infection/infection control challenges; and the impact on service users. Targeted guidelines are required to support mental health nurses providing care and support during a pandemic to people in severe mental distress, often in unsuitable environments.\n\nImplications for PracticeService developments need to occur alongside tailored guidance and support for staff welfare supported by clear leadership. These findings identify areas requiring attention and investment to prepare for future crises and the consequences of the pandemic.\n\nAccessible SummaryO_ST_ABSWhat is known on the subject?C_ST_ABSDuring the Covid-19 pandemic there has been research considering the impact on medical healthcare professionals and the mental health needs of the general population. However, limited focus has been placed on mental health services or mental health staff providing care in the community and in hospitals. Whilst nurses make up the largest section of the mental health workforce in the UK, the impact that this pandemic has had on their work has been largely ignored.\n\nWhat the paper adds to existing knowledge?This paper provides a unique insight into the experiences and impact that the Covid-19 pandemic has had on mental health nurses across a range of community and inpatient settings to understand what has changed in their work and the care they can and do provide during this crisis. This includes exploring how services have changed, the move to remote working, the impact of the protective equipment crisis on nurses, and the difficult working conditions facing those in inpatient settings where there is minimal guidance provided.\n\nWhat are the implications for practice?By understanding the impact the pandemic has had on mental health nursing care, we can understand the gaps in guidance that exist, the challenges being faced, and the impact the crisis has had on care for mental health service users. By doing so we can plan for the ongoing nature of this pandemic as well as the aftermath that the crisis may leave for our service users and workforce alike.\n\nRelevance StatementThis paper provides insight into the impact that the Covid-19 pandemic has had on the service and care that mental health nurses are expected to and can provide. As a workforce that often requires ongoing face to face contact with service users, many in serious distress, in inpatient and community settings, it is important that we understand their experiences and the challenges and risks that face this workforce. This will enable us to ensure that future planning, guidance, support and safeguarding can take place during the ongoing and future crises.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.04.20226118",
+    "rel_abs": "BackgroundNew York State (NYS) has been an epicenter for both COVID-19 and HIV/AIDS epidemics. Persons Living with diagnosed HIV (PLWDH) may be more prone to COVID-19 infection and severe outcomes, yet few population-based studies have assessed the extent to which PLWDH are diagnosed, hospitalized, and have died with COVID-19, relative to non-PLWDH.\n\nMethodsNYS HIV surveillance, COVID-19 laboratory confirmed diagnoses, and hospitalization databases were matched. COVID-19 diagnoses, hospitalization, and in-hospital death rates comparing PLWDH to non-PLWDH were computed, with unadjusted rate ratios (RR) and indirect standardized RR (sRR), adjusting for sex, age, and region. Adjusted RR (aRR) for outcomes among PLWDH were assessed by age/CD4-defined HIV disease stage, and viral load suppression, using Poisson regression models.\n\nResultsFrom March 1-June 7, 2020, PLWDH were more frequently diagnosed with COVID-19 than non-PLWDH in unadjusted (RR [95% confidence interval (CI)]: 1.43[1.38-1.48), 2,988 PLWDH], but not in adjusted comparisons (sRR [95% CI]: 0.94[0.91-0.97]). Per-population COVID-19 hospitalization was higher among PLWDH (RR [95% CI]: 2.61[2.45-2.79], sRR [95% CI]: 1.38[1.29-1.47], 896 PLWDH), as was in-hospital death (RR [95% CI]: 2.55[2.22-2.93], sRR [95%CI]: 1.23 [1.07-1.40], 207 PLWDH), albeit not among those hospitalized (sRR [95% CI]: 0.96[0.83-1.09]). Among PLWDH, hospitalization risk increased with disease progression from HIV Stage 1 to Stage 2 (aRR [95% CI]:1.27[1.09-1.47]) and Stage 3 (aRR [95% CI]: 1.54[1.24-1.91]), and for those virally unsuppressed (aRR [95% CI]: 1.54[1.24-1.91]).\n\nConclusionPLWDH experienced poorer COVID-related outcomes relative to non-PLWDH, with 1-in-522 PLWDH dying with COVID-19, seemingly driven by higher rates of severe disease requiring hospitalization.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Una Foye",
-        "author_inst": "King's College London"
+        "author_name": "James M Tesoriero",
+        "author_inst": "New York State Department of Health"
       },
       {
-        "author_name": "Christian Dalton-Locke",
-        "author_inst": "University College London"
+        "author_name": "Carol-Ann E Swain",
+        "author_inst": "New York State Department of Health"
       },
       {
-        "author_name": "Jasmine Harju-Seppanen",
-        "author_inst": "University College London"
+        "author_name": "Jennifer L Pierce",
+        "author_inst": "New York State Department of Health"
       },
       {
-        "author_name": "Rebecca Lane",
-        "author_inst": "Kings College London"
+        "author_name": "Lucila Zamboni",
+        "author_inst": "New York State Department of Health"
       },
       {
-        "author_name": "Lewys Beams",
-        "author_inst": "South London and Maudsley Foundation Trust"
+        "author_name": "Meng Wu",
+        "author_inst": "New York State Department of Health"
       },
       {
-        "author_name": "Norha Vera San Juan",
-        "author_inst": "King's College London"
+        "author_name": "David R Holtgrave",
+        "author_inst": "University at Albany School of Public Health"
       },
       {
-        "author_name": "Sonia Johnson",
-        "author_inst": "University College London"
+        "author_name": "Charles J Gonzalez",
+        "author_inst": "New York State Department of Health"
       },
       {
-        "author_name": "Alan Simpson",
-        "author_inst": "Kings College London"
+        "author_name": "Tomoko Udo",
+        "author_inst": "University at Albany School of Public Health"
+      },
+      {
+        "author_name": "Johanne E Morne",
+        "author_inst": "New York State Department of Health"
+      },
+      {
+        "author_name": "Rachel Hart-Malloy",
+        "author_inst": "New York State Department of Health"
+      },
+      {
+        "author_name": "Deepa T Rajulu",
+        "author_inst": "New York State Department of Health"
+      },
+      {
+        "author_name": "Shu-Yin John Leung",
+        "author_inst": "New York State Department of Health"
+      },
+      {
+        "author_name": "Eli S Rosenberg",
+        "author_inst": "University at Albany School of Pubic Health"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "nursing"
+    "category": "hiv aids"
   },
   {
     "rel_doi": "10.1101/2020.11.04.20225862",
@@ -1048847,123 +1052575,183 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.11.06.370676",
-    "rel_title": "Potent SARS-CoV-2 neutralizing antibodies selected from a human antibody library constructed decades ago",
-    "rel_date": "2020-11-06",
+    "rel_doi": "10.1101/2020.11.03.367391",
+    "rel_title": "Evolution of Antibody Immunity to SARS-CoV-2",
+    "rel_date": "2020-11-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.06.370676",
-    "rel_abs": "Combinatorial antibody libraries not only effectively reduce antibody discovery to a numbers game, but enable documentation of the history of antibody responses in an individual. The SARS-CoV-2 pandemic has prompted a wider application of this technology to meet the public health challenge of pandemic threats in the modern era. Herein, we used a combinatorial human antibody library constructed 20 years before the COVID-19 pandemic to discover three highly potent antibodies that selectively bind SARS-CoV-2 spike protein and neutralize authentic SARS-CoV-2 virus. Compared to neutralizing antibodies from COVID-19 patients with generally low somatic hypermutation (SHM), these antibodies contain over 13-22 SHMs, many of which are involved in specific interactions in crystal structures with SARS-CoV-2 spike RBD. The identification of these somatically mutated antibodies in a pre-pandemic library raises intriguing questions about the origin and evolution of human immune responses to SARS-CoV-2.",
-    "rel_num_authors": 26,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.03.367391",
+    "rel_abs": "Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has infected 78 million individuals and is responsible for over 1.7 million deaths to date. Infection is associated with development of variable levels of antibodies with neutralizing activity that can protect against infection in animal models. Antibody levels decrease with time, but the nature and quality of the memory B cells that would be called upon to produce antibodies upon re-infection has not been examined. Here we report on the humoral memory response in a cohort of 87 individuals assessed at 1.3 and 6.2 months after infection. We find that IgM, and IgG anti-SARS-CoV-2 spike protein receptor binding domain (RBD) antibody titers decrease significantly with IgA being less affected. Concurrently, neutralizing activity in plasma decreases by five-fold in pseudotype virus assays. In contrast, the number of RBD-specific memory B cells is unchanged. Memory B cells display clonal turnover after 6.2 months, and the antibodies they express have greater somatic hypermutation, increased potency and resistance to RBD mutations, indicative of continued evolution of the humoral response. Analysis of intestinal biopsies obtained from asymptomatic individuals 4 months after coronavirus disease-2019 (COVID-19) onset, using immunofluorescence, or polymerase chain reaction, revealed persistence of SARS-CoV-2 nucleic acids and immunoreactivity in the small bowel of 7 out of 14 volunteers. We conclude that the memory B cell response to SARS-CoV-2 evolves between 1.3 and 6.2 months after infection in a manner that is consistent with antigen persistence.",
+    "rel_num_authors": 41,
     "rel_authors": [
       {
-        "author_name": "Min Qiang",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Christian Gaebler",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Peixiang Ma",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Zijun Wang",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Yu Li",
-        "author_inst": "ShanghaiTech University; Chinese Academy of Sciences; University of Chinese Academy of Sciences"
+        "author_name": "Julio C. C. Lorenzi",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Hejun Liu",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Frauke Muecksch",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Adam Harding",
-        "author_inst": "University of Oxford"
+        "author_name": "Shlomo Finkin",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Chenyu Min",
-        "author_inst": "Velox Pharmaceuticals"
+        "author_name": "Minami Tokuyama",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Lili Liu",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Alice Cho",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Meng Yuan",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Mila Jankovic",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Qun Ji",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Dennis Schaefer-Babajew",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Pingdong Tao",
-        "author_inst": "ShanghaiTech University; Chinese Academy of Sciences; University of Chinese Academy of Sciences"
+        "author_name": "Thiago Y. Oliveira",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Xiaojie Shi",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Melissa Cipolla",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Zhean Li",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Charlotte Viant",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Fulian Wang",
-        "author_inst": "ShanghaiTech University; Chinese Academy of Sciences; University of Chinese Academy of Sciences"
+        "author_name": "Christopher O. Barnes",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Yu Zhang",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Arlene Hurley",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Nicholas C. Wu",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Martina Turroja",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Chang-Chun D. Lee",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Kristie Gordon",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Xueyong Zhu",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Katrina G. Millard",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Javier Gilbert-Jaramillo",
-        "author_inst": "University of Oxford"
+        "author_name": "Victor Ramos",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Abhishek Saxena",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Fabian Schmidt",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Xingxu Huang",
-        "author_inst": "ShanghaiTech University"
+        "author_name": "Yiska Weisblum",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Hou Wang",
-        "author_inst": "ShOx Science Limited"
+        "author_name": "Divya Jha",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "William James",
-        "author_inst": "University of Oxford"
+        "author_name": "Michael Tankelevich",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
       },
       {
-        "author_name": "Raymond A. Dwek",
-        "author_inst": "Oxford Glycobiology Institute"
+        "author_name": "Jim Yee",
+        "author_inst": "Weill Cornell Medicine"
       },
       {
-        "author_name": "Ian A. Wilson",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Irina Shimeliovich",
+        "author_inst": "The Rockefeller University"
       },
       {
-        "author_name": "Guang Yang",
-        "author_inst": "ShanghaiTech University;Velox Pharmaceuticals"
+        "author_name": "Davide F. Robbiani",
+        "author_inst": "Institute for Research in Biomedicine"
       },
       {
-        "author_name": "Richard A. Lerner",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Zhen Zhao",
+        "author_inst": "Weill Cornell Medicine"
+      },
+      {
+        "author_name": "Anna Gazumyan",
+        "author_inst": "The Rockefeller University"
+      },
+      {
+        "author_name": "Theodora Hatziioannou",
+        "author_inst": "The Rockefeller University"
+      },
+      {
+        "author_name": "Pamela J. Bjorkman",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Saurabh Mehandru",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Paul D. Bieniasz",
+        "author_inst": "The Rockefeller University"
+      },
+      {
+        "author_name": "Marina Caskey",
+        "author_inst": "The Rockefeller University"
+      },
+      {
+        "author_name": "Michel C. Nussenzweig",
+        "author_inst": "The Rockefeller University"
+      },
+      {
+        "author_name": "Thomas Hagglof",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Robert  E. Schwartz",
+        "author_inst": "Weill Cornell Graduate School of Medical Sciences"
+      },
+      {
+        "author_name": "Yaron Bram",
+        "author_inst": "Weill Cornell"
+      },
+      {
+        "author_name": "Gustavo Martinez-Delgado",
+        "author_inst": "Mount Sinai"
+      },
+      {
+        "author_name": "Pilar Mendoza",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Gaelle Breton",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Juan Dizon",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Roshni Patel",
+        "author_inst": "Rockefeller University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.11.04.367359",
@@ -1051308,99 +1055096,23 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2020.11.05.370239",
-    "rel_title": "SARS-CoV-2 Assembly and Egress Pathway Revealed by Correlative Multi-modal Multi-scale Cryo-imaging",
+    "rel_doi": "10.1101/2020.11.05.368647",
+    "rel_title": "SLAMF7 engagement super-activates macrophages in acute and chronic inflammation",
     "rel_date": "2020-11-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.05.370239",
-    "rel_abs": "Since the outbreak of the SARS-CoV-2 pandemic, there have been intense structural studies on purified recombinant viral components and inactivated viruses. However, investigation of the SARS-CoV-2 infection in the native cellular context is scarce, and there is a lack of comprehensive knowledge on SARS-CoV-2 replicative cycle. Understanding the genome replication, assembly and egress of SARS-CoV-2, a multistage process that involves different cellular compartments and the activity of many viral and cellular proteins, is critically important as it bears the means of medical intervention to stop infection. Here, we investigated SARS-CoV-2 replication in Vero cells under the near-native frozen-hydrated condition using a unique correlative multi-modal, multi-scale cryo-imaging approach combining soft X-ray cryo-tomography and serial cryoFIB/SEM volume imaging of the entire SARS-CoV-2 infected cell with cryo-electron tomography (cryoET) of cellular lamellae and cell periphery, as well as structure determination of viral components by subtomogram averaging. Our results reveal at the whole cell level profound cytopathic effects of SARS-CoV-2 infection, exemplified by a large amount of heterogeneous vesicles in the cytoplasm for RNA synthesis and virus assembly, formation of membrane tunnels through which viruses exit, and drastic cytoplasm invasion into nucleus. Furthermore, cryoET of cell lamellae reveals how viral RNAs are transported from double-membrane vesicles where they are synthesized to viral assembly sites; how viral spikes and RNPs assist in virus assembly and budding; and how fully assembled virus particles exit the cell, thus stablishing a model of SARS-CoV-2 genome replication, virus assembly and egress pathways.",
-    "rel_num_authors": 20,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.05.368647",
+    "rel_abs": "Macrophages regulate protective immune responses to infectious microbes, but aberrant macrophage activation frequently drives pathological inflammation. To identify regulators of vigorous macrophage activation, we analyzed RNA-seq data from synovial macrophages and identified SLAMF7 as a receptor associated with a super-activated macrophage state in rheumatoid arthritis. We implicated IFN-{gamma} as a key regulator of SLAMF7 expression. Engaging this receptor drove an exuberant wave of inflammatory cytokine expression, and induction of TNF- following SLAMF7 engagement amplified inflammation through an autocrine signaling loop. We observed SLAMF7-induced gene programs not only in macrophages from rheumatoid arthritis patients, but in gut macrophages from active Crohns disease patients and lung macrophages from severe COVID-19 patients. This suggests a central role for SLAMF7 in macrophage super-activation with broad implications in pathology.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Luiza Mendonca",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Andrew Howe",
-        "author_inst": "Diamond Light Source"
-      },
-      {
-        "author_name": "James B Gilchrist",
-        "author_inst": "Diamond Light Source"
-      },
-      {
-        "author_name": "Dapeng Sun",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Michael Knight",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Laura C Zanetti-Domingues",
-        "author_inst": "Science and Technology Facility Council"
-      },
-      {
-        "author_name": "Benji Bateman",
-        "author_inst": "Science and Technology Facility Council"
-      },
-      {
-        "author_name": "Anna-Sophia Krebs",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Long Chen",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Julika Radecke",
-        "author_inst": "Diamond Light Source"
-      },
-      {
-        "author_name": "Yuewen Sheng",
-        "author_inst": "Diamond Light Source"
-      },
-      {
-        "author_name": "Vivian D Li",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Tao Ni",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Ilias Kounatidis",
-        "author_inst": "Diamond Light Source"
-      },
-      {
-        "author_name": "Mohamed A Koronfel",
-        "author_inst": "Diamond Light Source"
-      },
-      {
-        "author_name": "Marta Szynkiewicz",
-        "author_inst": "Science and Technology Facility Council"
-      },
-      {
-        "author_name": "Maria Harkiolaki",
-        "author_inst": "Diamond Light Source"
-      },
-      {
-        "author_name": "Marisa L Martin-Fernandez",
-        "author_inst": "Science and Technology Facility Council"
-      },
-      {
-        "author_name": "William James",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Peijun Zhang",
-        "author_inst": "University of Oxford"
+        "author_name": "Accelerating Medicines Partnership (AMP) RA/SLE Network",
+        "author_inst": "."
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.10.30.20223115",
@@ -1052842,83 +1056554,23 @@
     "category": "neurology"
   },
   {
-    "rel_doi": "10.1101/2020.11.02.20224519",
-    "rel_title": "Are Mobile Phones part of the chain of transmission of SARS-CoV-2 in the hospital?",
+    "rel_doi": "10.1101/2020.11.01.20214122",
+    "rel_title": "Simulation model for productivity, risk and GDP impact forecasting of the COVID-19 portfolio vaccines",
     "rel_date": "2020-11-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224519",
-    "rel_abs": "SARS-CoV-2 cross-transmission has become an concern in hospitals. We investigate healthcare workers(HCWs) knowledge about SARS-CoV-2 cross-transmission and conceptions whether the virus can remain on HCWs mobile phones(MPs) and be part of the chain of transmission.\n\nA cross-sectional study was conducted at a COVID-19 Intensive Care Unit of a teaching-hospital. Fifty-one MPs were swabbed and a questionnaire about hand hygiene and MP use and disinfection was applied after an educational campaign. Although most of HCWs believed on the importance of cross-transmission and increased hand hygiene adhesion and MP disinfection during the pandemic, SARS-CoV-2 RNA was detected in two MPs(culture of the samples was negative).\n\nImplementation of official hospital policies to guide HCWs regarding disinfection and care of personal MP are needed.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.01.20214122",
+    "rel_abs": "Executive summaryThe paper presents the methodology and modeling results for COVID-19 vaccines portfolio forecasting, including R&D output (rate and likelihood of approvals at a vaccine technology platform level) and manufacturing production output to meet worldwide demand.\n\nIn order to minimize the time and risk of global vaccination, scaling up of Operation Warp Speed (OWS) and other programs could be very beneficial, leading to increased financing for additional vaccine development programs, in both Phase III clinical trials and in manufacturing. It would also lead to a reduction of the global production time for world vaccination, from 75 months for a baseline scenario to 36 months, reducing potential global GDP loss by as much as US$4.2 trillion (US [~] $1 trillion) when compared to the baseline scenario.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Evelyn Patricia Sanchez Espinoza",
-        "author_inst": "Department of Infectious Diseases, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Marina Farrel Cortes",
-        "author_inst": "Department of Infectious Diseases, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Saidy Vasconez Nogueira",
-        "author_inst": "Department of Infectious Diseases, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Anderson Vincente de Paula",
-        "author_inst": "LIM52 Virology Laboratory, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Thais Guimaraes",
-        "author_inst": "Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Lucy Santos Vilas Boas",
-        "author_inst": "LIM52 Virology Laboratory, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Marcelo Park",
-        "author_inst": "Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Cristina Carvalho da Silva",
-        "author_inst": "Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Ingra Morales",
-        "author_inst": "Department of Infectious Diseases, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Lauro Vieira Perdigao Neto",
-        "author_inst": "Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Tania Regina Tozetto-Mendoza",
-        "author_inst": "Instituto de Medicina Tropical de Sao Paulo. Universidade de Sao Paulo."
-      },
-      {
-        "author_name": "Icaro Boszczowski",
-        "author_inst": "Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Ester Sabino",
-        "author_inst": "Department of Infectious Diseases, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Maria Cassia Mendes-Correa",
-        "author_inst": "LIM52 Virology Laboratory, Universidade de Sao Paulo, Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Anna Sara Shafferman Levin",
-        "author_inst": "Department of Infectious Diseases, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."
-      },
-      {
-        "author_name": "Silvia Figueiredo Costa",
-        "author_inst": "Department of Infectious diseases, Instituto de Medicina Tropical, Universidade de Sao Paulo, Sao Paulo, Brazil"
+        "author_name": "Vladimir Shnaydman",
+        "author_inst": "ORBee Consulting"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "category": "health economics"
   },
   {
     "rel_doi": "10.1101/2020.11.02.20224568",
@@ -1054500,31 +1058152,47 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.11.02.20224642",
-    "rel_title": "Vascular Thrombosis in COVID-19: A Potential Association with Antiphospholipid Antibodies. A Rapid Systematic Review",
+    "rel_doi": "10.1101/2020.11.02.20224709",
+    "rel_title": "Gender-affirming care, mental health, and economic stability in the time of COVID-19: a global cross-sectional study of transgender and non-binary people",
     "rel_date": "2020-11-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224642",
-    "rel_abs": "BackgroundVascular thrombosis is common in patients with coronavirus disease 2019 (COVID-19). Etiologies underlying this complication are unclear.\n\nPurposeTo determine the prevalence of antiphospholipid (aPL), including lupus anticoagulant, anti-cardiolipin and anti-{beta}2-glycoprotein-1 antibodies, and its possible association with thrombotic manifestations of COVID-19.\n\nData SourcesWe searched MEDLINE indexed journals on September 24, 2020 using the tool LitCovid and the pre-print server medRxIV.\n\nStudy SelectionOriginal investigations (cross-sectional studies, cohort studies, case series, and research letters) on COVID-19 and thrombosis were included.\n\nData ExtractionData were independently extracted, and compiled into spreadsheets based on the PRISMA principles.\n\nData SynthesisHospitalized patients with COVID-19 showed a higher prevalence of lupus anticoagulant compared to non-COVID-19 patients. Temporally, lupus anticoagulant was generally positive early in the course of illness, whereas anti-cardiolipin and anti-{beta}2-glycoprotein-1 antibodies appeared to emerge later in the disease. Some patients who were aPL-negative at an early time-point after disease onset became aPL-positive at a later time-point. Lupus anticoagulant was independently associated with thrombosis in 60 COVID-19 patients in New York had who had 32 thrombotic events (8 arterial and 24 venous). In 88 patients in Wuhan, who had more than 20 each of arterial and venous thrombotic events, medium/high positivity for multiple aPL was significantly associated with arterial thrombosis. However, the association of aPL with thrombosis was not evident in reports that had an overall lower number of or predominantly venous thrombotic events. Analysis of pooled patients revealed that aPL were significantly more frequent in COVID-19 patients with stroke than stroke patients in the general population. Furthermore, injection of IgG aPL fractions from COVID-19 patients into mice accelerated venous thrombosis.\n\nLimitationLimited data and paucity of prospective studies.\n\nConclusionThe aPL are prevalent in patients with COVID-19 and their presence is associated with thrombosis. Importantly, these antibodies may be a key mechanism of thrombosis in COVID-19. Follow-up studies are required to understand the relationship between aPL and the spectrum of vascular thrombosis during and after infection with SARS-CoV-2.\n\nPrimary Funding SourceNone.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20224709",
+    "rel_abs": "BackgroundTransgender and non-binary people are disproportionately burdened by barriers to quality healthcare, mental health challenges, and economic hardship. This study examined the impact of the novel coronavirus disease (COVID-19) pandemic and subsequent control measures on gender-affirming care, mental health, and economic stability among transgender and non-binary people globally.\n\nMethodsWe collected global cross-sectional data from 964 transgender and non-binary adult users of the Hornet and Her apps from April to August 2020 to characterize changes in gender-affirming care, mental health, and economic stability as a result of the COVID-19 pandemic. We conducted Poisson regression models to assess if access to gender-affirming care and ability to live according to ones gender were related to depressive symptoms, anxiety, and changes in suicidal ideation.\n\nResultsIndividuals resided in 76 countries, including Turkey (27.4%,n=264/964) and Thailand (20.6%,n=205). A majority were non-binary (66.8%,n=644) or transfeminine (29.4%,n=283). Due to the COVID-19 pandemic, 55.0% (n=320/582) reported reduced access to gender- affirming resources, and 38.0% (n=327/860) reported reduced time lived according to their gender. About half screened positive for depression (50.4%,442/877) and anxiety (45.8%,n=392/856). One in six (17.0%,n=112/659) expected losses of health insurance, and 77.0% (n=724/940) expected income reductions. The prevalence of depressive symptoms, anxiety, and increased suicidal ideation were 1.63 (95% CI: 1.36-1.97), 1.61 (95% CI: 1.31-1.97), and 1.74 (95% CI: 1.07-2.82) times higher for individuals whose access to gender- affirming resources was reduced versus not.\n\nDiscussionThe COVID-19 pandemic has reduced access to gender-affirming resources and the ability of transgender and non-binary people to live according to their gender worldwide. These reductions may drive the increased depressive symptoms, anxiety, and suicidal ideation reported in this sample. To improve transgender and non-binary health globally, increased access to gender-affirming resources should be achieved through policies (e.g., digital prescriptions), flexible interventions (e.g., telehealth), and support for existing transgender health initiatives.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Aneesh S Kallapur",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Brooke Jarrett",
+        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
       },
       {
-        "author_name": "Eric Y Yen",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Sarah M Peitzmeier",
+        "author_inst": "University of Michigan School of Nursing"
       },
       {
-        "author_name": "Ram Raj Singh",
-        "author_inst": "UCLA"
+        "author_name": "Arjee Restar",
+        "author_inst": "JohnsHopkins Bloomberg School of Public Health"
+      },
+      {
+        "author_name": "Tyler Adamson",
+        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+      },
+      {
+        "author_name": "Sean Howell",
+        "author_inst": "Hornet"
+      },
+      {
+        "author_name": "Stefan Baral",
+        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+      },
+      {
+        "author_name": "S. Wilson Beckham",
+        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "cardiovascular medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.11.03.20225268",
@@ -1056086,37 +1059754,33 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.28.20221077",
-    "rel_title": "Simple discrete-time self-exciting models can describe complex dynamic processes: a case study of COVID-19",
+    "rel_doi": "10.1101/2020.10.28.20221408",
+    "rel_title": "ROLE OF CYTOKINES AND OTHER PROPHETIC VARIABLES IN THE DEVELOPMENT AND PROGRESSION OF DISEASE IN PATIENTS SUFFERING FROM COVID-19",
     "rel_date": "2020-11-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221077",
-    "rel_abs": "Hawkes processes are a form of self-exciting process that has been used in numerous applications, including neuroscience, seismology, and terrorism. While these self-exciting processes have a simple formulation, they are able to model incredibly complex phenomena. Traditionally Hawkes processes are a continuous-time process, however we enable these models to be applied to a wider range of problems by considering a discrete-time variant of Hawkes processes. We illustrate this through the novel coronavirus disease (COVID-19) as a substantive case study. While alternative models, such as compartmental and growth curve models, have been widely applied to the COVID-19 epidemic, the use of discrete-time Hawkes processes allows us to gain alternative insights. This paper evaluates the capability of discrete-time Hawkes processes by retrospectively modelling daily counts of deaths as two distinct phases in the progression of the COVID-19 outbreak: the initial stage of exponential growth and the subsequent decline as preventative measures become effective. We consider various countries that have been adversely affected by the epidemic, namely, Brazil, China, France, Germany, India, Italy, Spain, Sweden, the United Kingdom and the United States. These countries are all unique concerning the spread of the virus and their corresponding response measures, in particular, the types and timings of preventative actions. However, we find that this simple model is useful in accurately capturing the dynamics of the process, despite hidden interactions that are not directly modelled due to their complexity, and differences both within and between countries. The utility of this model is not confined to the current COVID-19 epidemic, rather this model could be used to explain many other complex phenomena. It is of interest to have simple models that adequately describe these complex processes with unknown dynamics. As models become more complex, a simpler representation of the process can be desirable for the sake of parsimony.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221408",
+    "rel_abs": "INTRODUCTIONOutbreak of the novel COVID-19 infection identifies both causative agents that threaten global pandemic in 2003 and 2011. It is an enveloped virus with spike (S) protein attached that facilitates its receptor binding on the surface. Although it has brought about the global interest for the researchers and medical practitioner in the identification of potential targets that may be addressed in order to cope up with the situation. In the current study potential role of cytokines and related inflammatory markers have been identified that interplays in the progression of disease in COVID-19 patients.\n\nMATERIALS AND METHODSCurrent study substitutes hundred and fifty (n=150) patients with novel-COVID-19 and hundred (n=100) healthy controls. After getting informed consent serum samples of the participants were collected and analyzed for their significance in the disease progression. Levels of Interleukins i.e., (IL- 1,6,8,10,11) and tumor necrosis factor-alpha (TNF-) were determined with help of their specific spectrophotometric and ELISA methods.\n\nRESULTSFindings of study show significant increase in the levels of interleukins and TNF- that signifies the presence of \"cytokine storm\" in worsening the condition in respect to the exposure of COVID-19. Levels of IL-1 and 6 were significantly higher in patients (98.69{+/-}39.35pg/ml and 71.95{+/-}28.41 pg/ml) as compared to controls (30.06{+/-}14.19pg/ml and 9.46{+/-}3.43pg/ml) where, (p=0.001 and 0.007). It also suggests that IL-6 is most sensitive test with about (98%) sensitivity in comparison with 96%,95%, 95%,93% and 92% in case of IL-10,1,8,11 and TNF- respectively.\n\nCONCLUSIONCurrent study elucidate the effects of cytokines and respective inflammatory markers in the progression of the COVID-19. Findings show that activation of macrophages and neutrophils have significant role in the worsening of the symptoms and progression of the viral infection. Thus, use of certain blockers in initial stages could serve with potent benefits in coping up the infectious condition.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Raiha Browning",
-        "author_inst": "Queensland University of Technology"
-      },
-      {
-        "author_name": "Deborah Sulem",
-        "author_inst": "University of Oxford"
+        "author_name": "arif malik",
+        "author_inst": "Institute of Molecular Biology and Biotechnology, The University of Lahore"
       },
       {
-        "author_name": "Kerrie Mengersen",
-        "author_inst": "Queensland University of Technology"
+        "author_name": "Saima Iqbal",
+        "author_inst": "Institute of Molecular Biology and Biotechnology, The University of Lahore"
       },
       {
-        "author_name": "Vincent Rivoirard",
-        "author_inst": "Universit\u00e9 Paris-Dauphine"
+        "author_name": "Sulayman Waquar",
+        "author_inst": "Institute of Molecular Biology and Biotechnology, The University of Lahore"
       },
       {
-        "author_name": "Judith Rousseau",
-        "author_inst": "University of Oxford; Universit\u00e9 Paris-Dauphine"
+        "author_name": "Muhammad Mansoor Hafeez",
+        "author_inst": "The University of Lahore"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1058028,73 +1061692,49 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.29.20222505",
-    "rel_title": "The use of compassionate Ivermectin in the management of symptomatic outpatients and hospitalized patients with clinical diagnosis of COVID-19 at the Medical Center Bournigal and the Medical Center Punta Cana, Rescue Group, Dominican Republic, from may 1 to august 10, 2020.",
+    "rel_doi": "10.1101/2020.10.29.20219931",
+    "rel_title": "A longitudinal comparison of spike and nucleocapsid SARS-CoV-2 antibody responses in a tertiary hospitals laboratory workers with validation of DBS specimen analysis.",
     "rel_date": "2020-11-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.29.20222505",
-    "rel_abs": "No antiviral has been shown to reduce mortality in SARS-COV-2 patients to date. In the present observational and retrospective report, 3,099 patients with a definitive or highly probable diagnosis of infection due to COVID-19 were evaluated between May 1st to August 10th, 2020, at Centro Medico Bournigal (CMBO) and Centro Medico Punta Cana (CMPC), and all received compassionate treatment with Ivermectin. A total of 2,706 (87.3%) were discharged for outpatient treatment, all with mild severity of the infection. In 2,688 (99.33%) with outpatient treatment, the disease did not progress to warrant further hospitalization and there were no deaths. In 16 (0.59%) with outpatient treatment, it was necessary their subsequent hospitalization to a room without any death. In 2 (0.08%) with outpatient treatment, it was necessary their admission to the Intensive Care Unit (ICU) and 1 (0.04%) patient died. There were 411 (13.3%) patients hospitalized, being admitted at a COVID-19 room with a moderate disease 300 (9.7%) patients of which 3 (1%) died; and with a severe to critical disease were hospitalized in the ICU 111 (3.6%), 34 (30.6%) of whom died. The mortality percentage of patients admitted to the ICU of 30.6%, is similar with the percentage found in the literature of 30.9%. Total mortality was 37 (1.2%) patients, which is much lower than that reported in world statistics, which are around 3%.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.29.20219931",
+    "rel_abs": "There is a requirement for easily accessible, high throughput serological testing as part of the SARS-CoV-2 pandemic response. Whilst of limited diagnostic use in an acute individual setting, its use on a population level is key to informing a coherent public health response. As experience of commercial assays increases, so too does knowledge of their precision and limitations. Here we present our experience of these systems thus far. We perform a spot sero-prevalence study amongst staff in a tertiary hospitals clinical microbiology laboratory, before undertaking validation of DBS serological testing as an alternate specimen for analysis. Finally, we characterise the spike and nucleocapsid antibody response over 160 days post a positive PCR test in nine non-hospitalised staff members.\n\nAmongst a cohort of 195 staff, 17 tested positive for SARS-CoV-2 antibodies (8.7%). Self-reporting of SARS-CoV2 infection (P=<0.0001) and testing of a household contact (P = 0.027) were significant variables amongst the positive and negative sub-groups. Testing of 28 matched serum and DBS samples demonstrated 96% accuracy between the sample types. A differential rate of decline of SARS-CoV-2 antibodies against nucleocapsid or spike protein was observed. At 4 months post a positive PCR test 7/9 (78%) individuals had detectable antibodies against spike protein, but only 2/9 (22%) had detectable antibodies against nucleocapsid protein. This study reveals a broad agreement amongst commercial platforms tested and suggests the use of DBS as an alternate specimen option to enable widespread population testing for SARS-CoV-2 antibodies. These results suggest potential limitations of these platforms in estimating historical infection. By setting this temporal point of reference for this cohort of non-patient facing laboratory staff, future exposure risks and mitigation strategies can be evaluated more fully.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Jose Morgenstern",
-        "author_inst": "Rescue Group"
-      },
-      {
-        "author_name": "Jose N Redondo",
-        "author_inst": "Rescue Group"
-      },
-      {
-        "author_name": "Albida De Leon",
-        "author_inst": "Rescue Group"
-      },
-      {
-        "author_name": "Juan M Canela",
-        "author_inst": "Rescue Group"
-      },
-      {
-        "author_name": "Nelson Torres",
-        "author_inst": "Rescue Group"
-      },
-      {
-        "author_name": "Johnny Tavares",
-        "author_inst": "Rescue Group"
-      },
-      {
-        "author_name": "Migulina Minaya",
-        "author_inst": "Rescue Group"
+        "author_name": "Isa Murrell",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Oscar Lopez",
-        "author_inst": "Rescue Group"
+        "author_name": "Donall Forde",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Ana M Placido",
-        "author_inst": "Rescue Group"
+        "author_name": "Linda Tyson",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Ana Castillo",
-        "author_inst": "Rescue Group"
+        "author_name": "Lisa Chichester",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Rafael Pena Cruz",
-        "author_inst": "Rescue Group"
+        "author_name": "Anna Garratt",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Yudelka Merrete",
-        "author_inst": "Rescue Group"
+        "author_name": "Owen Vineall",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Marlenin Toribio",
-        "author_inst": "Rescue Group"
+        "author_name": "Nicki Palmer",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Juan A Francisco",
-        "author_inst": "Rescue Group"
+        "author_name": "Rachel Jones",
+        "author_inst": "Public Health Wales"
       },
       {
-        "author_name": "Santiago Roca",
-        "author_inst": "Rescue Group"
+        "author_name": "Catherine Moore",
+        "author_inst": "Public Health Wales"
       }
     ],
     "version": "1",
@@ -1059733,35 +1063373,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.27.20220707",
-    "rel_title": "Association of Mass Gatherings and COVID-19 Hospitalization",
+    "rel_doi": "10.1101/2020.11.03.366609",
+    "rel_title": "Modelling the active SARS-CoV-2 helicase complex as a basis for structure-based inhibitor design",
     "rel_date": "2020-11-03",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20220707",
-    "rel_abs": "We examined COVID-19 hospitalizations following mass gatherings in Wisconsin and Minnesota, United States (September 17-18, 2020). We found that the hospitalization rate increased 15-fold in the Minnesota gathering county, and 12.7-fold in the Wisconsin gathering county. On the state level, it increased 2-fold in Minnesota, and 2.3-fold in Wisconsin, while not increasing significantly in states without gatherings. Our findings suggest that mass gatherings are followed by increased COVID-19 hospitalizations, and that precautions should be taken.",
-    "rel_num_authors": 4,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.03.366609",
+    "rel_abs": "Having claimed over 1 million lives worldwide to date, the ongoing COVID-19 pandemic has created one of the biggest challenges to develop an effective drug to treat infected patients. Among all the proteins expressed by the virus, RNA helicase is a fundamental protein for viral replication, and it is highly conserved among the coronaviridae family. To date, there is no high-resolution structure of helicase bound with ATP and RNA. We present here structural insights and molecular dynamics (MD) simulation results of the SARS-CoV-2 RNA helicase both in its apo form and in complex with its natural substrates. Our structural information of the catalytically competent helicase complex provides valuable insights for the mechanism and function of this enzyme at the atomic level, a key to develop specific inhibitors for this potential COVID-19 drug target.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Oren Miron",
-        "author_inst": "Ben Gurion University"
+        "author_name": "D\u00e9nes Berta",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Kun-Hsing Yu",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Sam Alexander Martino",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Rachel Wilf-Miron",
-        "author_inst": "Tel Aviv University"
+        "author_name": "Andrei Pisliakov",
+        "author_inst": "University of Dundee"
       },
       {
-        "author_name": "Nadav Davidovitch",
-        "author_inst": "Ben Gurion University"
+        "author_name": "Nadia Elghobashi-Meinhardt",
+        "author_inst": "Technische Universit\u00e4t Berlin"
+      },
+      {
+        "author_name": "Geoffrey Wells",
+        "author_inst": "University College London"
+      },
+      {
+        "author_name": "Sarah A Harris",
+        "author_inst": "University of Leeds"
+      },
+      {
+        "author_name": "Elisa Frezza",
+        "author_inst": "Universit\u00e9 de Paris"
+      },
+      {
+        "author_name": "Edina Rosta",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2020.11.02.365049",
@@ -1061563,55 +1065219,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.28.20221093",
-    "rel_title": "Features of creatine-kinase in COVID-19 patients with different ages, clinical types and outcomes: A cohort study",
+    "rel_doi": "10.1101/2020.10.28.20221069",
+    "rel_title": "Psychological and social impact of COVID-19 in Pakistan: Need for Gender Responsive Policies",
     "rel_date": "2020-11-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221093",
-    "rel_abs": "ObjectivesTo study the features of creatine-kinase (CK) in COVID-19 patients with different ages, clinical types and outcomes and quantify the relationship between CK value and clinical type.\n\nMethodsAll laboratory confirmed COVID-19 patients hospitalized in Xiangyang No.1 Peoples Hospital were included. Patients general information, clinical type, all CK values and outcome were collected.\n\nResultsThe peak median value of CK in cases aged [&ge;] 71 years old (appeared at T2) was higher than that in cases aged [&le;] 70 years old. There was statistical difference between the two groups (P=0.001). Similarly, the peak in critical cases (appeared at T2) was higher than moderate and severe types, and significant difference were existed among moderate, severe, and critical types (P=0.000). Moreover, the peak value in death group (appeared at T2) was higher than those in survival group. Significant difference was also found between them (P=0.000). According to the optimal scale regression model, the CK value (P=0.000) and age (P=0.000) were associated with the clinical type.\n\nConclusionsDifference of the CK in different ages, clinical types, and outcomes were significant. The results of the optimal scale regression model are helpful to judge the clinical type of COVID-19 patients.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.28.20221069",
+    "rel_abs": "BACKGROUNDCOVID-19 has rapidly crossed borders, infecting people throughout the world. Women may be especially vulnerable to depression and anxiety due to the pandemic,\n\nAIMSThis study attempted to assess how gender impacts risk perceptions, anxiety levels behavioral responses to the COVID 19 pandemic in Pakistan in order to recommend gender responsive health policies\n\nMETHODSA cross-sectional online survey was conducted. Participants were asked to complete a sociodemographic data form, the Hospital Anxiety and Depression Scale (HADS), and questions on their risk perceptions, preventive behavior and information exposure. Regression analysis was used to assess effects of factors such as age, gender and household income on anxiety levels.\n\nRESULTSOf the 1390 respondents, 478 were women, and 913 were men. Women considered their chances of survival to be relatively lower than men (59 % women vs 73% men). They were also more anxious (62% women vs 50% men), and more likely to adopt precautionary behavior, such as avoiding going to the hospital (78% women vs. 71% men), not going to work (72% women and 57% men), and using disinfectants (93% women and 86% men). Men were more likely to trust friends, family and social media as reliable sources of COVID-19 information, while women were more likely to trust doctors.\n\nCONCLUSIONWomen experience a disproportion burden of the psychological and social impact of the pandemic compared to men. Involving doctors in healthcare communication targeting women, might prove effective. Social media and radio programs may be effective in disseminating information related to COVID among men.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Shanshan Wan",
-        "author_inst": "Postgraduate Training Basement of Jinzhou Medical University, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
-      },
-      {
-        "author_name": "Gaojing Qu",
-        "author_inst": "Center of Evidence-based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
-      },
-      {
-        "author_name": "Hui Yu",
-        "author_inst": "Center of Evidence-based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
-      },
-      {
-        "author_name": "Haoming Zhu",
-        "author_inst": "Center of Evidence-based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
-      },
-      {
-        "author_name": "Guoxin Huang",
-        "author_inst": "Center of Evidence-based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
+        "author_name": "Dr. Fauziah Rabbani",
+        "author_inst": "Aga Khan University"
       },
       {
-        "author_name": "Lei Chen",
-        "author_inst": "Center of Evidence-based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
+        "author_name": "Dr. Hyder Ali Khan",
+        "author_inst": "Aga Khan University"
       },
       {
-        "author_name": "Meiling Zhang",
-        "author_inst": "Center of Evidence-based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
+        "author_name": "Dr. Suneel Piryani",
+        "author_inst": "Aga Khan University"
       },
       {
-        "author_name": "Jiangtao Liu",
-        "author_inst": "Department of Orthopedics, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
+        "author_name": "Areeba Raza Khan",
+        "author_inst": "Aga Khan University"
       },
       {
-        "author_name": "Bin Pei",
-        "author_inst": "Center of Evidence-based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China"
+        "author_name": "Dr. Fahad Abid",
+        "author_inst": "Specialist Early Intervention in Psychosis Pakistan"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.10.31.363473",
@@ -1063161,149 +1066801,69 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.27.20220731",
-    "rel_title": "Mental Health Impact of the First Wave of COVID-19 Pandemic on Spanish Healthcare Workers: a Large Cross-sectional Survey",
+    "rel_doi": "10.1101/2020.10.29.20222372",
+    "rel_title": "The COVID-19 Healthcare Personnel Study (CHPS): Overview, Methods and Preliminary Report",
     "rel_date": "2020-10-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20220731",
-    "rel_abs": "IntroductionHealthcare workers are vulnerable to adverse mental health impacts of COVID-19. We assessed prevalence of mental disorders and associated factors during the first wave of the pandemic among healthcare professionals in Spain.\n\nMethodsAll workers in 18 healthcare institutions (6 AACC) in Spain were invited to a series of online surveys assessing a wide range of individual characteristics, COVID-19 infection status and exposure, and mental health status. Here we report: current mental disorders (Major Depressive Disorder-MDD- [PHQ-8[&ge;]10], Generalized Anxiety Disorder-GAD- [GAD-7[&ge;]10], Panic attacks, Posttraumatic Stress Disorder -PTSD- [PCL-5[&ge;]7]; and Substance Use Disorder -SUD-[CAGE-AID[&ge;]2]. Severe disability assessed by the Sheehan Disability Scale was used to identify \"disabling\" current mental disorders.\n\nResults9,138 healthcare workers participated. Prevalence of screen-positive disorder: 28.1% MDD; 22.5% GAD, 24.0% Panic; 22.2% PTSD; and 6.2% SUD. Overall 45.7% presented any current and 14.5% any disabling current mental disorder. Healthcare workers with prior lifetime mental disorders had almost twice the prevalence of current disorders than those without. Adjusting for all other variables, odds of any disabling mental disorder were: prior lifetime disorders (TUS: OR=5.74; 95%CI 2.53-13.03; Mood: OR=3.23; 95%CI:2.27-4.60; Anxiety: OR=3.03; 95%CI:2.53-3.62); age category 18-29 years (OR=1.36; 95%CI:1.02-1.82), caring \"all of the time\" for COVID-19 patients (OR=5.19; 95%CI: 3.61-7.46), female gender (OR=1.58; 95%CI: 1.27-1.96) and having being in quarantine or isolated (OR= 1.60; 95CI:1.31-1.95).\n\nConclusionsCurrent mental disorders were very frequent among Spanish healthcare workers during the first wave of COVID-19. As the pandemic enters its second wave, careful monitoring and support is needed for healthcare workers, especially those with previous mental disorders and those caring COVID-19 very often.",
-    "rel_num_authors": 33,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.29.20222372",
+    "rel_abs": "IntroductionThe COVID-19 Healthcare Personnel Study (CHPS) was designed to assess and mitigate adverse short and long-term physical and mental health impacts of the COVID-19 pandemic on New Yorks health care workforce. Here we report selected baseline results.\n\nMethodsOnline survey of New York State physicians, nurse practitioners and physician assistants registered with the New York State Department of Health. Survey-weighted descriptive results were analyzed using frequencies, proportions, and means, with 95% confidence intervals. Odds ratios were calculated for association using survey-weighted logistic regression.\n\nResultsApproximately 51.5% (95% CI 49.1, 54.0) of the survey-weighted respondents reported having worked directly or in close physical contact with COVID-19 patients. Of those tested for COVID-19, 27.3% (95% CI 22.5, 32.2) were positive. Having symptoms consistent with COVID-19 was associated with reporting a subsequent positive COVID-19 test (OR=14.0, 95% CI 5.7, 34.7). Over half of the respondents, (57.6%) reported a negative impact of the COVID-19 efforts on their mental health. Respondents who indicated that they were redeployed or required to do different functions than usual in response to COVID-19 were more likely to report negative mental health impacts (OR=1.3, 95% CI 1.1, 1.6).\n\nConclusionsAt the height of the COVID-19 pandemic in New York State in Spring 2020, more than half of physicians, nurse practitioners and physician assistants included in this study responded to the crisis, often at a cost to their physical and mental health and disruption to their lives.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Jordi Alonso",
-        "author_inst": "Health Services Research Unit, IMIM-Institut Hospital del Mar d'Investigacions M\u00e8diques"
-      },
-      {
-        "author_name": "Gemma Vilagut",
-        "author_inst": "Health Services Research Unit, IMIM-Institut Hospital del Mar d'Investigacions M\u00e8diques"
-      },
-      {
-        "author_name": "Philippe Mortier",
-        "author_inst": "Health Services Research Unit, IMIM-Institut Hospital del Mar d'Investigacions M\u00e8diques"
-      },
-      {
-        "author_name": "Montse Ferrer",
-        "author_inst": "Health Services Research Unit, IMIM-Institut Hospital del Mar d'Investigacions M\u00e8diques"
-      },
-      {
-        "author_name": "Itxaso Alayo",
-        "author_inst": "Health Services Research Unit, IMIM-Institut Hospital del Mar d'Investigacions M\u00e8diques"
-      },
-      {
-        "author_name": "Andr\u00e9s Arag\u00f3n-Pe\u00f1a",
-        "author_inst": "Epidemiology Unit, Regional Ministry of Health, Community of Madrid"
-      },
-      {
-        "author_name": "Enric Aragon\u00e8s",
-        "author_inst": "Institut d'Investigaci\u00f3 en Atenci\u00f3 Prim\u00e0ria IDIAP Jordi Gol"
-      },
-      {
-        "author_name": "Mireia Campos",
-        "author_inst": "Service of Prevention of Labor Risks, Medical Emergencies System, Generalitat de Catalunya"
-      },
-      {
-        "author_name": "Isabel del Cura-Gonz\u00e1lez",
-        "author_inst": "Research Unit. Primary Care Management. Madrid Health Service"
-      },
-      {
-        "author_name": "Jos\u00e9 I. Emparanza",
-        "author_inst": "Hospital Universitario Donostia"
-      },
-      {
-        "author_name": "Meritxell Espuga",
-        "author_inst": "Occupational Health Service. Hospital Universitari Vall d'Hebron"
-      },
-      {
-        "author_name": "Joao Forjaz",
-        "author_inst": "National Center of Epidemiology, Instituto de Salud Carlos III (ISCIII)"
-      },
-      {
-        "author_name": "Ana Gonz\u00e1lez Pinto",
-        "author_inst": "Hospital Universitario Araba-Santiago"
-      },
-      {
-        "author_name": "Josep M. Haro",
-        "author_inst": "Parc Sanitari Sant Joan de D\u00e9u"
-      },
-      {
-        "author_name": "Nieves L\u00f3pez Fresne\u00f1a",
-        "author_inst": "Hospital General Universitario Gregorio Mara\u00f1\u00f3n"
-      },
-      {
-        "author_name": "Alma Mart\u00ednez de Sal\u00e1zar",
-        "author_inst": "UGC Salud Mental, Hospital Universitario Torrec\u00e1rdenas"
-      },
-      {
-        "author_name": "Juan D. Molina",
-        "author_inst": "Villaverde Mental Health Center. Clinical Management Area of Psychiatry and Mental Health, Psychiatric Service, Hospital Universitario 12 de Octubre"
-      },
-      {
-        "author_name": "Rafael M. Ort\u00ed Lucas",
-        "author_inst": "Hospital Cl\u00ednic Universitari de Valencia"
-      },
-      {
-        "author_name": "Mara Parellada",
-        "author_inst": "Hospital General Universitario Gregorio Mara\u00f1\u00f3n"
-      },
-      {
-        "author_name": "Jos\u00e9 Maria Pelayo-Ter\u00e1n",
-        "author_inst": "Hospital El Bierzo"
-      },
-      {
-        "author_name": "Aurora P\u00e9rez Zapata",
-        "author_inst": "Pr\u00edncipe de Asturias University Hospital"
+        "author_name": "- The COVID-19 Healthcare Personnel Study (CHPS)",
+        "author_inst": ""
       },
       {
-        "author_name": "Jos\u00e9 I. Pijoan",
-        "author_inst": "Hospital Universitario Cruces/ OSI EEC"
+        "author_name": "Charles DiMaggio",
+        "author_inst": "NYU Grossman School of Medicine, Department of Surgery"
       },
       {
-        "author_name": "Nieves Plana",
-        "author_inst": "Pr\u00edncipe de Asturias University Hospital"
+        "author_name": "David Abramson",
+        "author_inst": "NYU Global Institute for Public Health"
       },
       {
-        "author_name": "Teresa Puig",
-        "author_inst": "Department of Epidemiology and Public Health, Hospital de la Santa Creu i Sant Pau"
+        "author_name": "Ezra Susser",
+        "author_inst": "Mailman School of Public Health, Columbia University"
       },
       {
-        "author_name": "Cristina Rius",
-        "author_inst": "Ag\u00e8ncia de Salut P\u00fablica de Barcelona"
+        "author_name": "Christina Hoven",
+        "author_inst": "New York State Psychiatric Institute, Mailman School of Public Health, Columbia University"
       },
       {
-        "author_name": "Carmen Rodriguez-Blazquez",
-        "author_inst": "National Center of Epidemiology, Instituto de Salud Carlos III (ISCIII)"
+        "author_name": "Qixuan Chen",
+        "author_inst": "Mailman School of Public Health, Columbia University"
       },
       {
-        "author_name": "Ferran Sanz",
-        "author_inst": "Research Progamme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)"
+        "author_name": "Howard Andrews",
+        "author_inst": "Columbia University Irving Medical Center, NY State Psychiatric Institute"
       },
       {
-        "author_name": "Consol Serra",
-        "author_inst": "Parc de Salut Mar PSMAR"
+        "author_name": "Daniel Herman",
+        "author_inst": "Silberman School of Social Work, Hunter College, CUNY"
       },
       {
-        "author_name": "Ronald C. Kessler",
-        "author_inst": "Department of Health Care Policy, Harvard Medical School"
+        "author_name": "Jonah Kreniske",
+        "author_inst": "Department of Global Health and Social Medicine, Harvard Medical School"
       },
       {
-        "author_name": "Ronny Bruffaerts",
-        "author_inst": "Center for Public Health Psychiatry, Universitair Psychiatrisch Centrum, KU Leuven"
+        "author_name": "Megan Ryan",
+        "author_inst": "Global Psychiatric Epidemiology Group, New York State Psychiatric Institute"
       },
       {
-        "author_name": "Eduard Vieta",
-        "author_inst": "Fundaci\u00f3 Cl\u00ednic per a la Recerca Biom\u00e8dica de Barcelona"
+        "author_name": "Ida Susser",
+        "author_inst": "Hunter College and Graduate Center, City University of New York"
       },
       {
-        "author_name": "V\u00edctor P\u00e9rez-Sol\u00e1",
-        "author_inst": "Parc de Salut Mar PSMAR"
+        "author_name": "Lorna Thorpe",
+        "author_inst": "Department of Population Health NYU Grossman School of Medicine"
       },
       {
-        "author_name": "- MINDCOVID Working group",
-        "author_inst": ""
+        "author_name": "Guohua Li",
+        "author_inst": "Department of Anesthesiology, Columbia University Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1063496,868 +1067056,56 @@
     "rel_date": "2020-10-30",
     "rel_site": "bioRxiv",
     "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.29.339317",
-    "rel_abs": "The COVID-19 pandemic was a stark reminder that a barren global antiviral pipeline has grave humanitarian consequences. Pandemics could be prevented in principle by accessible, easily deployable broad-spectrum oral antivirals. Here we report the results of the COVID Moonshot, a fully open-science, crowd sourced, structure-enabled drug discovery campaign targeting the SARS-CoV-2 main protease. We discovered a novel chemical series that is differentiated from current Mpro inhibitors in that it maintains a new non-covalent, non-peptidic scaffold with nanomolar potency. Our approach leveraged crowdsourcing, high-throughput structural biology, machine learning, and exascale molecular simulations and high-throughput chemistry. In the process, we generated a detailed map of the structural plasticity of the SARS-CoV-2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. In a first for a structure-based drug discovery campaign, all compound designs (>18,000 designs), crystallographic data (>840 ligand-bound X-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2,400 compounds) for this campaign were shared rapidly and openly, creating a rich open and IP-free knowledgebase for future anti-coronavirus drug discovery.",
-    "rel_num_authors": 215,
+    "rel_abs": "We report the results of the COVID Moonshot, a fully open-science, crowd sourced, structure-enabled drug discovery campaign targeting the SARS-CoV-2 main protease. We discovered a non-covalent, non-peptidic inhibitor scaffold with lead-like properties that is differentiated from current main protease inhibitors. Our approach leveraged crowdsourcing, machine learning, exascale molecular simulations, and high-throughput structural biology and chemistry. We generated a detailed map of the structural plasticity of the SARS-CoV- 2 main protease, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data. All compound designs (>18,000 designs), crystallographic data (>840 ligand-bound X-ray structures), assay data (>10,000 measurements), and synthesized molecules (>2,400 compounds) for this campaign were shared rapidly and openly, creating a rich open and IP-free knowledgebase for future anti-coronavirus drug discovery.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "- The COVID Moonshot Consortium",
-        "author_inst": ""
-      },
-      {
-        "author_name": "Hagit Achdout",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Anthony Aimon",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
-      },
-      {
-        "author_name": "Dominic S Alonzi",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Robert Arbon",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Elad Bar-David",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Haim Barr",
-        "author_inst": "The Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Amir Ben-Shmuel",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "James Bennett",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Vitaliy A. Bilenko",
-        "author_inst": "Enamine Ltd"
-      },
-      {
-        "author_name": "Vitaliy A. Bilenko",
-        "author_inst": "Enamine Ltd"
-      },
-      {
-        "author_name": "Melissa L. Boby",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Bruce Borden",
-        "author_inst": "Folding@home Consortium"
-      },
-      {
-        "author_name": "Pascale Boulet",
-        "author_inst": "DNDi"
-      },
-      {
-        "author_name": "Gregory R. Bowman",
-        "author_inst": "Washington University School of Medicine"
-      },
-      {
-        "author_name": "Juliane Brun",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Lennart Brwewitz",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Sarma BVNBS",
-        "author_inst": "Sai Life Sciences"
-      },
-      {
-        "author_name": "Mark Calmiano",
-        "author_inst": "UCB"
-      },
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-        "author_inst": "University of Oxford;Diamond Light Source"
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-        "author_name": "Daniel Carney",
-        "author_inst": "Takeda Development Center Americas, Inc."
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-        "author_name": "Emma Cattermole",
-        "author_inst": "University of Oxford"
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-      {
-        "author_name": "Edcon Chang",
-        "author_inst": "Takeda Development Center Americas, Inc."
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-        "author_name": "Eugene Chernyshenko",
-        "author_inst": "Enamine Ltd"
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-        "author_name": "John D. Chodera",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
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-        "author_name": "Austin Clyde",
-        "author_inst": "Argonne National Laboratory"
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-        "author_name": "Joseph E. Coffland",
-        "author_inst": "N/A"
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-      {
-        "author_name": "Galit Cohen",
-        "author_inst": "The Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Jason Cole",
-        "author_inst": "Cambridge Crystallographic Datacentre"
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-      {
-        "author_name": "Alessandro Contini",
-        "author_inst": "University of Milan"
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-      {
-        "author_name": "Lisa Cox",
-        "author_inst": "Life Compass Consulting Ltd"
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-      {
-        "author_name": "Tristan Ian Croll",
-        "author_inst": "Cambridge Institute for Medical Research, The University of Cambridge"
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-        "author_name": "Milan Cvitkovic",
-        "author_inst": "PostEra Inc."
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-        "author_name": "Alex Dias",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
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-      {
-        "author_name": "Kim Donckers",
-        "author_inst": "Katholieke Universiteit Leuven"
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-      {
-        "author_name": "David L. Dotson",
-        "author_inst": "N/A"
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-      {
-        "author_name": "Alice Douangamath",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
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-        "author_name": "Shirly Duberstein",
-        "author_inst": "The Weizmann Institute of Science"
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-        "author_name": "Tim Dudgeon",
-        "author_inst": "Informatics Matters"
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-      {
-        "author_name": "Louise Dunnett",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
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-        "author_name": "Peter K. Eastman",
-        "author_inst": "Department of Bioengineering until Sept. 1, then Department of Chemistry"
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-      {
-        "author_name": "Noam Erez",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Charles J. Eyermann",
-        "author_inst": "Northeastern University"
-      },
-      {
-        "author_name": "Mike Fairhead",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Gwen Fate",
-        "author_inst": "Thames Pharma Partners"
+        "author_name": "Melissa L Bobby",
+        "author_inst": "Pharmacology Graduate Program, Weill Cornell Graduate School of Medical Sciences, New York, NY 10065, USA; Program in Chemical Biology, Sloan Kettering Institut"
       },
       {
         "author_name": "Daren Fearon",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
-      },
-      {
-        "author_name": "Oleg Fedorov",
-        "author_inst": "University of Oxford"
+        "author_inst": "Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot, OX11 0QX, UK; Research Complex at Harwell, Harwell Science and Innovation Campus, Didc"
       },
       {
         "author_name": "Matteo Ferla",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Rafaela S. Fernandes",
-        "author_inst": "University of Sao Paulo"
-      },
-      {
-        "author_name": "Lori Ferrins",
-        "author_inst": "Northeastern University"
+        "author_inst": "Oxford Biomedical Research Centre, National Institute for Health Research, University of Oxford, Oxford, UK"
       },
       {
         "author_name": "Mihajlo Filep",
-        "author_inst": "Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Richard Foster",
-        "author_inst": "University of Leeds"
-      },
-      {
-        "author_name": "Holly Foster",
-        "author_inst": "University of Leeds"
-      },
-      {
-        "author_name": "Laurent Fraisse",
-        "author_inst": "DNDi"
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-      {
-        "author_name": "Ronen Gabizon",
-        "author_inst": "The Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Adolfo Garcia-Sastre",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Victor O. Gawriljuk",
-        "author_inst": "University of Sao Paulo"
-      },
-      {
-        "author_name": "Paul Gehrtz",
-        "author_inst": "The Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Carina Gileadi",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Charline Giroud",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "William G. Glass",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Robert Glen",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Itai Glinert",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Andre S. Godoy",
-        "author_inst": "University of Sao Paulo"
-      },
-      {
-        "author_name": "Marian Gorichko",
-        "author_inst": "Taras Shevchenko National University of Kyiv"
-      },
-      {
-        "author_name": "Tyler Gorrie-Stone",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
-      },
-      {
-        "author_name": "Ed J. Griffen",
-        "author_inst": "MedChemica Ltd"
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-        "author_name": "Sophie Hahn",
-        "author_inst": "DNDi"
-      },
-      {
-        "author_name": "Amna Haneef",
-        "author_inst": "Illinois Institute of Technology"
-      },
-      {
-        "author_name": "Storm Hassell Hart",
-        "author_inst": "University of Sussex"
-      },
-      {
-        "author_name": "Jag Heer",
-        "author_inst": "UCB"
-      },
-      {
-        "author_name": "Michael Henry",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Michelle Hill",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Sam Horrell",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
-      },
-      {
-        "author_name": "Qiu Yu Huang",
-        "author_inst": "University of Massachusetts Chan Medical School"
-      },
-      {
-        "author_name": "Victor D. Huliak",
-        "author_inst": "Enamine Ltd"
-      },
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-        "author_name": "Victor D. Huliak",
-        "author_inst": "Enamine Ltd"
-      },
-      {
-        "author_name": "Matthew F.D. Hurley",
-        "author_inst": "Temple University"
-      },
-      {
-        "author_name": "Tomer Israely",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Andrew Jajack",
-        "author_inst": "PostEra Inc."
-      },
-      {
-        "author_name": "Jitske Jansen",
-        "author_inst": "Radboud University Medical Center"
-      },
-      {
-        "author_name": "Eric Jnoff",
-        "author_inst": "UCB"
-      },
-      {
-        "author_name": "Dirk Jochmans",
-        "author_inst": "Katholieke Universiteit Leuven"
-      },
-      {
-        "author_name": "Tobias John",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Steven De Jonghe",
-        "author_inst": "Katholieke Universiteit Leuven"
-      },
-      {
-        "author_name": "Benjamin Kaminow",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Lulu Kang",
-        "author_inst": "Illinois Institute of Technology"
-      },
-      {
-        "author_name": "Anastassia L. Kantsadi",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Peter W. Kenny",
-        "author_inst": "Independent Scientist"
-      },
-      {
-        "author_name": "J. L. Kiappes",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Serhii O. Kinakh",
-        "author_inst": "Enamine Ltd"
-      },
-      {
-        "author_name": "Serhii O. Kinakh",
-        "author_inst": "Enamine Ltd"
+        "author_inst": "Department of Chemical and Structural Biology, The Weizmann Institute of Science, Rehovot, Israel, 7610001"
       },
       {
         "author_name": "Lizbe Koekemoer",
-        "author_inst": "University of Oxford"
+        "author_inst": "Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK"
       },
       {
-        "author_name": "Boris Kovar",
-        "author_inst": "M2M solutions, s.r.o"
+        "author_name": "Matthew C Robinson",
+        "author_inst": "PostEra Inc., 1 Broadway, 14th Floor,Cambridge, MA 02142, USA"
       },
       {
-        "author_name": "Tobias Krojer",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Van La",
-        "author_inst": "Illinois Institute of Technology"
-      },
-      {
-        "author_name": "Alpha A. Lee",
-        "author_inst": "PostEra Inc.; University of Cambridge"
-      },
-      {
-        "author_name": "Bruce A. Lefker",
-        "author_inst": "Thames Pharma Partners LLC"
-      },
-      {
-        "author_name": "Haim Levy",
-        "author_inst": "Israel Institution of Biological Research"
+        "author_name": "- The COVID Moonshot Consortium",
+        "author_inst": ""
       },
       {
-        "author_name": "Ivan G. Logvinenko",
-        "author_inst": "Enamine Ltd"
+        "author_name": "John D Chodera",
+        "author_inst": "Program in Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA"
       },
       {
-        "author_name": "Ivan G. Logvinenko",
-        "author_inst": "Enamine Ltd"
+        "author_name": "Alpha A Lee",
+        "author_inst": "PostEra Inc., 1 Broadway, 14th Floor,Cambridge, MA 02142, USA"
       },
       {
         "author_name": "Nir London",
-        "author_inst": "The Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Petra Lukacik",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
-      },
-      {
-        "author_name": "Hannah Bruce Macdonald",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Elizabeth M. MacLean",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Laetitia L Makower",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Tika R. Malla",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Tatiana Matviiuk",
-        "author_inst": "Enamine Ltd"
-      },
-      {
-        "author_name": "Willam McCorkindale",
-        "author_inst": "University of Cambridge"
-      },
-      {
-        "author_name": "Briana L. McGovern",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Sharon Melamed",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Kostiantyn P. Melnykov",
-        "author_inst": "Enamine Ltd"
-      },
-      {
-        "author_name": "Kostiantyn P. Melnykov",
-        "author_inst": "Enamine Ltd"
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-        "author_name": "Oleg Michurin",
-        "author_inst": "Enamine Ltd"
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-      {
-        "author_name": "Pascal Miesen",
-        "author_inst": "Radboud University Medical Center"
-      },
-      {
-        "author_name": "Halina Mikolajek",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
-      },
-      {
-        "author_name": "Bruce F. Milne",
-        "author_inst": "University of Coimbra and University of Aberdeen"
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-      {
-        "author_name": "David Minh",
-        "author_inst": "Illinois Institute of Technology"
-      },
-      {
-        "author_name": "Aaron Morris",
-        "author_inst": "PostEra Inc"
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-        "author_inst": "University of Oxford"
-      },
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-        "author_name": "Melody Jane Morwitzer",
-        "author_inst": "Department of Pathology and Microbiology"
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-        "author_name": "Demetri Moustakas",
-        "author_inst": "Relay Therapeutics"
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-        "author_name": "Charles Mowbray",
-        "author_inst": "DNDi"
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-        "author_name": "Aline M. Nakamura",
-        "author_inst": "University of Sao Paulo"
-      },
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-        "author_name": "Jose Brandao Neto",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
-      },
-      {
-        "author_name": "Johan Neyts",
-        "author_inst": "Katholieke Universiteit Leuven"
-      },
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-        "author_name": "Luong Nguyen",
-        "author_inst": "PostEra Inc."
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-      {
-        "author_name": "Gabriela D. Noske",
-        "author_inst": "University of Sao Paulo"
-      },
-      {
-        "author_name": "Vladas Oleinikovas",
-        "author_inst": "UCB"
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-      {
-        "author_name": "Glaucius Oliva",
-        "author_inst": "University of Sao Paulo"
-      },
-      {
-        "author_name": "Gijs J. Overheul",
-        "author_inst": "Radboud University Medical Center"
-      },
-      {
-        "author_name": "David Owen",
-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
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-        "author_name": "Ruby Pai",
-        "author_inst": "PostEra Inc."
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-      {
-        "author_name": "Jin Pan",
-        "author_inst": "PostEra Inc."
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-        "author_name": "Nir Paran",
-        "author_inst": "Israel Institution of Biological Research"
-      },
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-        "author_inst": "Memorial Sloan Kettering Cancer Center"
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-        "author_inst": "DNDi"
-      },
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-        "author_name": "Maneesh Pingle",
-        "author_inst": "Sai Life Sciences"
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-        "author_inst": "Sai Life Sciences"
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-        "author_name": "Boaz Politi",
-        "author_inst": "Israel Institution of Biological Research"
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-        "author_inst": "Diamond Light Source Ltd; Research Complex at Harwell"
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-        "author_inst": "M2M solutions, s.r.o"
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-        "author_inst": "Memorial Sloan Kettering Cancer Center"
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-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Victor L. Rangel",
-        "author_inst": "School of Pharmaceutical Sciences of Ribeirao Preto"
-      },
-      {
-        "author_name": "Rambabu N. Reddi",
-        "author_inst": "The Weizmann Institute of Science"
-      },
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-        "author_name": "Paul Rees",
-        "author_inst": "Compass Bussiness Partners Ltd"
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-        "author_name": "St Patrick Reid",
-        "author_inst": "Department of Pathology and Microbiology"
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-        "author_inst": "PostEra Inc."
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-        "author_inst": "Memorial Sloan Kettering Cancer Center"
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-        "author_inst": "University of Cambridge"
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-        "author_inst": "Takeda Development Center Americas, Inc."
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-        "author_inst": "University of Oxford"
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-        "author_inst": "Charite Universitatsmedizin Berlin"
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-        "author_inst": "Memorial Sloan Kettering Cancer Center"
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-        "author_inst": "University of Massachusetts Chan Medical School"
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-        "author_inst": "University of Oxford"
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-        "author_inst": "Enamine Ltd"
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-        "author_inst": "University of Massachusetts Chan Medical School"
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-        "author_inst": "The Weizmann Institute of Science"
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-        "author_inst": "Israel Institution of Biological Research"
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-        "author_inst": "University of Oxford"
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-        "author_inst": "University of Oxford"
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-        "author_name": "Frank von Delft",
-        "author_inst": "Diamond Light Source Ltd; University of Oxford; Research Complex at Harwell; University of Johannesburg"
+        "author_inst": "Department of Chemical and Structural Biology, The Weizmann Institute of Science, Rehovot, Israel, 7610001"
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         "author_name": "Annette von Delft",
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-      {
-        "author_name": "Walter Ward",
-        "author_inst": "Walter Ward Consultancy & Training"
-      },
-      {
-        "author_name": "Charlie Weatherall",
-        "author_inst": "Collaborative Drug Discovery"
-      },
-      {
-        "author_name": "Shay Weiss",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Kris M. White",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Conor Francis Wild",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Karolina D Witt",
-        "author_inst": "University of Oxford"
+        "author_inst": "Oxford Biomedical Research Centre, National Institute for Health Research, University of Oxford, Oxford, UK; Centre for Medicines Discovery, Nuffield Department"
       },
       {
-        "author_name": "Matthew Wittmann",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Nathan Wright",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Yfat Yahalom-Ronen",
-        "author_inst": "Israel Institution of Biological Research"
-      },
-      {
-        "author_name": "Nese Kurt Yilmaz",
-        "author_inst": "University of Massachusetts Chan Medical School"
-      },
-      {
-        "author_name": "Daniel Zaidmann",
-        "author_inst": "The Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Ivy Zhang",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
-      },
-      {
-        "author_name": "Hadeer Zidane",
-        "author_inst": "The Weizmann Institute of Science"
-      },
-      {
-        "author_name": "Nicole Zitzmann",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Sarah N Zvornicanin",
-        "author_inst": "University of Massachusetts Chan Medical School"
+        "author_name": "Frank von Delft",
+        "author_inst": "Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot, OX11 0QX, UK; Research Complex at Harwell, Harwell Science and Innovation Campus, Didc"
       }
     ],
     "version": "1",
@@ -1066863,49 +1069611,37 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.28.355305",
-    "rel_title": "5-amino levulinic acid inhibits SARS-CoV-2 infection in vitro",
+    "rel_doi": "10.1101/2020.10.28.359257",
+    "rel_title": "In vitro assessment of the virucidal activity of four mouthwashes containing Cetylpyridinium Chloride, ethanol, zinc and a mix of enzyme and proteins against a human coronavirus",
     "rel_date": "2020-10-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.28.355305",
-    "rel_abs": "The current COVID-19 pandemic requires urgent development of effective therapeutics. 5-amino levulinic acid (5-ALA) is a naturally synthesized amino acid and has been used for multiple purposes including as an anticancer therapy and as a dietary supplement due to its high bioavailability. In this study, we demonstrated that 5-ALA treatment potently inhibited infection of SARS-CoV-2, a causative agent of COVID-19. The antiviral effects could be detected in both human and non-human cells, without significant cytotoxicity. Therefore, 5-ALA is a candidate as an oral antiviral drug for COVID-19.",
-    "rel_num_authors": 9,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.28.359257",
+    "rel_abs": "Backgroundsaliva is established to contain high counts SARS-CoV-2 virus and contact with saliva droplets, contaminated surfaces or airborne particles are sources of viral transmission. The generation of infective aerosols during clinical procedures is of particular concern. Therefore, a fuller understanding of the potential of mouthwash to reduce viral counts and modulate the risk of transmission in medical professional and public context is an important research topic.\n\nMethodwe determined the virucidal activity of four anti-bacterial mouthwashes against a surrogate for SARS-CoV-2, Human CoV-SARS 229E, using a standard ASTM suspension test, with dilution and contact times applicable to recommended mouthwash use.\n\nResultsthe mouthwash formulated with 0.07% Cetylpyridinium Chloride exhibited virucidal effects providing a [&ge;]3.0 log reduction HCoV-229E viral count. Mouthwashes containing 15.7% ethanol, 0.2% zinc sulphate heptahydrate and a mix of enzymes and proteins did not demonstrate substantive virucidal activity in this test.\n\nConclusionmouthwash containing 0.07% Cetylpyridinium Chloride warrants further laboratory and clinical assessment to determine their potential benefit in reducing the risk of SARS-CoV-2.\n\nHighlightsSARS-CoV-2 can be transmitted through contact with infective saliva.\n\nStudies are needed to understand if mouthwash can lower SARS-CoV-2 transmission risk.\n\n0.07% Cetylpyridinium Chloride (CPC) mouthwash exhibited virucidal effects against HCoV-SARS 229E.\n\nFurther studies on potential of 0.07% CPC mouthwash against SARS-CoV-2 are warranted.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Yasuteru Sakurai",
-        "author_inst": "Nagasaki University"
+        "author_name": "Alison Green",
+        "author_inst": "Unilever Research and Development Port Sunlight, Quarry Road East, Bebington, Wirral, UK, CH63 3JW"
       },
       {
-        "author_name": "Mya Myat Ngwe Tun",
-        "author_inst": "Nagasaki University"
+        "author_name": "Glyn Roberts",
+        "author_inst": "Unilever Research and Development Port Sunlight, Quarry Road East, Bebington, Wirral, UK, CH63 3JW"
       },
       {
-        "author_name": "Yohei Kurosaki",
-        "author_inst": "Nagasaki University"
+        "author_name": "Timothy Tobery",
+        "author_inst": "Unilever Research and Development Trumbull, 40 Merritt Boulevard, Trumbull, CT 06611, USA"
       },
       {
-        "author_name": "Takaya Sakura",
-        "author_inst": "Nagasaki University"
+        "author_name": "Carol Vincent",
+        "author_inst": "Unilever Research and Development Trumbull, 40 Merritt Boulevard, Trumbull, CT 06611, USA"
       },
       {
-        "author_name": "Daniel Ken Inaoka",
-        "author_inst": "Nagasaki University"
-      },
-      {
-        "author_name": "Kiyotaka Fujine",
-        "author_inst": "neopharma Japan Co., Ltd."
-      },
-      {
-        "author_name": "Kiyoshi Kita",
-        "author_inst": "Nagasaki University"
+        "author_name": "Matteo Barili",
+        "author_inst": "Unilever Oral Care, Via Lever Gibbs, 3, Casalpusterlengo, 26841, LO, Italy"
       },
       {
-        "author_name": "Kouichi Morita",
-        "author_inst": "Nagasaki University"
-      },
-      {
-        "author_name": "Jiro Yasuda",
-        "author_inst": "Nagasaki University"
+        "author_name": "Carolyn Jones",
+        "author_inst": "Unilever Oral Care, Via Lever Gibbs, 3, Casalpusterlengo, 26841, LO, Italy"
       }
     ],
     "version": "1",
@@ -1068441,75 +1071177,71 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.23.20218255",
-    "rel_title": "Characteristics and outcomes of hospitalized adult COVID-19 patients in Georgia",
+    "rel_doi": "10.1101/2020.10.23.20218164",
+    "rel_title": "SARS-CoV-2 seroprevalence in healthcare workers of dedicated COVID hospitals and non COVID hospitals of District Srinagar, Kashmir",
     "rel_date": "2020-10-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.23.20218255",
-    "rel_abs": "ObjectiveDescribe presenting characteristics of hospitalized patients and explore factors associated with in-hospital mortality during the first wave of pandemic in Georgia.\n\nMethodsThis retrospective study included 582 adult patients admitted to 9 dedicated COVID-19 hospitals as of July 30, 2020 (72% of all hospitalizations). Data were abstracted from medical charts. Factors associated with mortality were evaluated in multivariable Poisson regression analysis.\n\nResultsAmong 582 adults included in this analysis 14.9% were 65+ years old, 49.1% were women, 59.3% had uni- or bi-lateral lung involvement on chest computed tomography, 27.1% had any co-morbidity, 13.2% patients had lymphopenia, 4.1% had neutophilosis, 4.8% had low platelet count, 37.6% had d-dimer levels of >0.5 mcg/l. Overall mortality was 2.1% (12/582). After excluding mild infections, mortality among patients with moderate-to-critical disease was 3.0% (12/399), while among patients with severe-to-critical disease mortality was 12.7% (8/63). Baseline characteristics associated with increased risk of mortality in multivariate regression analysis included: age [&ge;]65 years (RR: 10.38, 95% CI: 1.30-82.75), presence of any chronic co-morbidity (RR: 20.71, 95% CI: 1.58-270.99), lymphopenia (RR: 4.76, 95% CI: 1.52-14.93), neutrophilosis (RR: 7.22, 95% CI: 1.27-41.12), low platelet count (RR: 6.92, 95% CI: 1.18-40.54), elevated d-dimer (RR: 4.45, 95% CI: 1.48-13.35), elevated AST (RR: 6.33, 95% CI: 1.18-33.98).\n\nConclusionIn-hospital mortality during the first wave of pandemic in Georgia was low. We identified several risk factors (older age, co-morbidities and laboratory abnormalities) associated with poor outcome that should provide guidance for planning health sector response as pandemic continues to evolve.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.23.20218164",
+    "rel_abs": "Background and objectiveSARS-CoV-2 infection poses tremendous challenge to the healthcare system of nations across the globe. Serological testing for SARS-CoV-2 infection in healthcare workers, which form a high-risk group, helps in identifying the burden of hidden infection in an institutional setting.\n\nMethodsWe present the results of a cross-sectional serosurvey in healthcare workers from two different hospital settings based on their role in the management of SARS-CoV-2 patients in District Srinagar, Kashmir. In addition to testing for the presence of SARS-CoV-2 specific IgG, we collected information on influenza-like symptoms in the last four weeks and the status of RT-PCR testing. SARS-CoV-2 specific IgG antibodies were detected in serum samples using a sensitive and specific chemiluminescent microparticle immunoassay technology.\n\nInterpretation and ConclusionOf 2915 healthcare workers who participated in the study, we analysed data from 2905 healthcare workers. The overall prevalence of SARS-CoV-2 specific IgG antibodies was 2.5% (95% CI 2.0-3.1) in the healthcare workers of District Srinagar. Healthcare workers who had ever worked at a dedicated-COVID hospital had a substantially lower seroprevalence of 0.6% (95% CI: 0.2 - 1.9). Among healthcare workers who had tested positive for RT-PCR, seroprevalence was 27.6% (95% CI: 14.0 - 47.2).The seroprevalence of SARS-CoV-2 infection in healthcare workers of District Srinagar is low, reflecting that a high proportion of healthcare workers are still susceptible to the infection. It is crucial to lay thrust on infection prevention and control activities and standard hygiene practices by the healthcare staff to protect them from acquiring infection within the healthcare setting.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Tengiz Tsertsvadze",
-        "author_inst": "1) Infectious Diseases, AIDS and Clinical Immunology Research Center, Tbilisi, Georgia; 2) Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia"
-      },
-      {
-        "author_name": "Marina Ezugbaia",
-        "author_inst": "Infectious Diseases, AIDS and Clinical Immunology Research Center, Tbilisi, Georgia"
+        "author_name": "Muhammad S Khan",
+        "author_inst": "government medical college srinagar"
       },
       {
-        "author_name": "Marina Endeladze",
-        "author_inst": "Infectious Diseases, AIDS and Clinical Immunology Research Center, Tbilisi, Georgia"
+        "author_name": "Inaamul Haq",
+        "author_inst": "government medical college srinagar"
       },
       {
-        "author_name": "Levani Ratiani",
-        "author_inst": "First University Clinic, Tbilisi, Georgia"
+        "author_name": "mariya A qurieshi",
+        "author_inst": "Department of Community Medicine Government Medical College, Srinagar, India"
       },
       {
-        "author_name": "Neli Javakhishvili",
-        "author_inst": "Giorgi Abramishvili Military Hospital, Gori, Georgia"
+        "author_name": "Sabhiya Majid",
+        "author_inst": "government medical college"
       },
       {
-        "author_name": "Lika Mumladze",
-        "author_inst": "St. King Mirian and Queen Nana Mtskheta Regional Medical Center, Georgia"
+        "author_name": "Arif Bhat",
+        "author_inst": "government medical college"
       },
       {
-        "author_name": "Manana Khotcholava",
-        "author_inst": "Childrens Infectious Diseases Hospital, Tbilisi, Georgia"
+        "author_name": "tanzeela Qazi",
+        "author_inst": "GMC SRINAGAR"
       },
       {
-        "author_name": "Maiko Janashia",
-        "author_inst": "University Clinic Rukhi, Georgia"
+        "author_name": "iqra chowdry",
+        "author_inst": "GMC SRINAGAR"
       },
       {
-        "author_name": "Diana Zviadadze",
-        "author_inst": "LJ Clinic, Kutaisi, Georgia"
+        "author_name": "muhammad Obaid",
+        "author_inst": "GMC SRINAGAR"
       },
       {
-        "author_name": "Levan Gopodze",
-        "author_inst": "Central Republican Hospital, Tbilisi, Georgia"
+        "author_name": "Iram Sabah",
+        "author_inst": "GMC"
       },
       {
-        "author_name": "Alex Gokhelashvili",
-        "author_inst": "Medalpha Clinic, Batumi, Georgia"
+        "author_name": "Misbah Kawoosa",
+        "author_inst": "GMC"
       },
       {
-        "author_name": "Revaz Metchurchtlishvili",
-        "author_inst": "Infectious Diseases, AIDS and Clinical Immunology Research Center, Tbilisi, Georgia"
+        "author_name": "Abdul Lone",
+        "author_inst": "GMC"
       },
       {
-        "author_name": "Akaki Abutidze",
-        "author_inst": "1) Infectious Diseases, AIDS and Clinical Immunology Research Center, Tbilisi, Georgia; 2) Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia"
+        "author_name": "Shahroz Nabi",
+        "author_inst": "GMC"
       },
       {
-        "author_name": "Nikoloz Chkhartishvili",
-        "author_inst": "1) Infectious Diseases, AIDS and Clinical Immunology Research Center; 2) Caucasus International University"
+        "author_name": "Ishtiyaq Sumji",
+        "author_inst": "GMC"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.10.23.20218073",
@@ -1070011,51 +1072743,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.24.20218685",
-    "rel_title": "Increasing SARS-CoV-2 RT-qPCR testing capacity by sample pooling",
+    "rel_doi": "10.1101/2020.10.24.20218974",
+    "rel_title": "Low serum vitamin D level and COVID-19 infection and outcomes, a multivariate meta-analysis",
     "rel_date": "2020-10-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.24.20218685",
-    "rel_abs": "ObjectivesLimited testing capacity has characterized the ongoing COVID-19 pandemic in Spain, hampering a timely control of outbreaks and the possibilities to reduce the escalation of community transmissions. Here we investigated the potential of using pooling of samples followed by one-step retrotranscription and quantitative PCR (RT-qPCR) to increase SARS-CoV-2 testing capacity.\n\nMethodsWe first evaluated different sample pooling (1:5, 1:10 and 1:15) prior to RNA extractions followed by standard RT-qPCR for SARS-CoV-2/COVID-19 diagnosis. The pool size achieving reproducible results in independent tests was then used for assessing nasopharyngeal samples in a tertiary hospital during August 2020.\n\nResultsWe found that pool size of five samples achieved the highest sensitivity compared to pool sizes of 10 and 15, showing a mean ({+/-} SD) Ct shift of 3.5 {+/-} 2.2 between the pooled test and positive samples in the pool. We then used a pool size of five to test a total of 895 pools (4,475 prospective samples) using two different RT-qPCR kits available at that time. The Real Accurate Quadruplex corona-plus PCR Kit (PathoFinder) reported the lowest mean Ct ({+/-} SD) shift (2.2 {+/-} 2.4) among the pool and the individual samples. The strategy allows detecting individual samples in the positive pools with Cts in the range of 16.7-39.4.\n\nConclusionsWe found that pools of five samples combined with RT-qPCR solutions helped to increase SARS-CoV-2 testing capacity with minimal loss of sensitivity compared to that resulting from testing the samples independently.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.24.20218974",
+    "rel_abs": "ObjectiveThis study aimed to determine whether serum vitamin D is independently associated with COVID-19 infection and outcomes in patients with COVID-19.\n\nMethodsWe identified relevant studies by searching the PubMed, Embase, and medRxiv databases from December 2019 to October 1, 2020. Odds ratios (ORs) were pooled using random-effects models. Only reports with multivariate adjusted results were included to avoid the impact of potential confounding factors.\n\nResultsA total of six studies with 377,265 patients were identified. Overall, in the categorical analysis, a low serum vitamin D level was associated with an increased risk of COVID-19 infection (OR: 1.47, 95% CI: 1.09- 1.97, I2=81%), hospitalization (OR: 1.83, 95% CI: 1.22-2.74, I2=0%), but not in-hospital death (OR: 2.73, 95% CI: 0.27-27.61). Notably, when vitamin D level was analyzed as a continuous variable, each 5 ng/ml increase in vitamin D level was not associated with any increased risk of COVID-19 infection (OR: 1.04, 95% CI: 0.96-1.12, I2=74%) or in-hospital death (OR: 1.02, 95% CI: 0.93-1.12).\n\nConclusionsLow serum vitamin D is associated with an increased risk of COVID-19 infection and hospitalization. In-hospital death showed a tendency to be increased in COVID-19 patients with low vitamin D levels. The ongoing clinical trials for evaluation of vitamin D supplementation will be key to the validation of this adjunctive treatment for COVID-19 patients.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Julia Alcoba-Florez",
-        "author_inst": "Servicio de Microbiologia, Hospital Universitario Nuestra Senora de Candelaria"
+        "author_name": "jie chen",
+        "author_inst": "the Third Affiliated Hospital of Nanchang University"
       },
       {
-        "author_name": "Helena Gil-Campesino",
-        "author_inst": "Servicio de Microbiologia, Hospital Universitario Nuestra Senora de Candelaria"
+        "author_name": "lixia xie",
+        "author_inst": "the Second Affiliated Hospital of Nanchang University"
       },
       {
-        "author_name": "Diego Garcia-Martinez de Artola",
-        "author_inst": "Servicio de Microbiologia, Hospital Universitario Nuestra Senora de Candelaria"
+        "author_name": "ping yuan",
+        "author_inst": "the Second Affiliated Hospital of Nanchang University"
       },
       {
-        "author_name": "Oscar Diez-Gil",
-        "author_inst": "Servicio de Microbiologia, Hospital Universitario Nuestra Senora de Candelaria"
-      },
-      {
-        "author_name": "Agustin Valenzuela-Fernandez",
-        "author_inst": "Laboratorio de Inmunologia Celular y Viral, Unidad de Farmacologia, Universidad de La Laguna"
+        "author_name": "peng yu",
+        "author_inst": "the Second Affiliated Hospital of Nanchang University"
       },
       {
-        "author_name": "Rafaela Gonzalez-Montelongo",
-        "author_inst": "Genomics Division, Instituto Tecnologico y de Energias Renovables"
+        "author_name": "jianyong ma",
+        "author_inst": "the Second Affiliated Hospital of Nanchang University"
       },
       {
-        "author_name": "Laura Ciuffreda",
-        "author_inst": "Unidad de Investigacion, Hospital Universitario Nuestra Senora de Candelaria"
+        "author_name": "chunhua zheng",
+        "author_inst": "the Third Affiliated Hospital of Nanchang University"
       },
       {
-        "author_name": "Carlos Flores",
-        "author_inst": "Hospital Universitario Nuestra Senora de Candelaria"
+        "author_name": "xiao liu",
+        "author_inst": "Second affiliated Hospital of Nanchang University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "cardiovascular medicine"
   },
   {
     "rel_doi": "10.1101/2020.10.25.20216671",
@@ -1071489,21 +1074217,33 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.26.20219626",
-    "rel_title": "Hyper-Exponential Growth of COVID-19 during Resurgence of the Disease in Russia",
+    "rel_doi": "10.1101/2020.10.22.20184630",
+    "rel_title": "COVID-19 infections following outdoor mass gatherings in low incidence areas: retrospective cohort study",
     "rel_date": "2020-10-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20219626",
-    "rel_abs": "In Russia, COVID-19 has currently been growing hyper-exponentially. This type of a spread pattern was not seen during the first wave of the pandemic the world over. Indeed when the disease had first appeared, in the accelerating stage the spread pattern was observed to have followed a highly nonlinear pattern that could be said to be approximately exponential or sub-exponential. As to why in the resurgence the growth has become hyper-exponential is another matter. But this has been happening in Europe and how long this would continue cannot be predicted. It may so happen that in the countries in which retardation has already been taking place, there may be resurgence of the disease. It was observed that in the World as a whole, retardation was on the threshold during the second half of September. But if the resurgence happens to follow the hyper-exponential growth pattern in different countries, there may be resurgence in the World as a whole.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.22.20184630",
+    "rel_abs": "ObjectiveIndoor mass gatherings in counties with high COVID-19 incidence have been linked to infections. We examined if outdoor mass gatherings in counties with low COVID-19 incidence are also followed by infections.\n\nMethodsWe retrospectively examined COVID-19 incidence in 20 counties that held mass gathering rallies (19 outdoor and 1 indoor) in the United States in August-September 2020. They were compared to the rest of the United States counties. We utilized a 7-day moving average and compared the change on the gathering date and 15 days later, based on the 95% confidence interval. For control counties we used the median of the gathering dates.\n\nSettingThe United States\n\nPopulation8.4 million in the counties holding mass gatherings, and 324 Million in the rest of the counties in the United States.\n\nMain Outcome MeasureChange in COVID-19 incidence rate per 100,000 capita during the two weeks following mass gatherings.\n\nResultsIn the two weeks following the gatherings, the COVID-19 incidence increased significantly in 14 of 20 counties. The county with the highest incidence increase (3.8-fold) had the 2nd lowest incidence before the gathering. The county with the highest decrease (0.4-fold) had the 3rd highest incidence before the gathering. At the gathering date, the average incidence of counties with gatherings was lower than the rest of the United States, and after the gathering, it increased 1.5-fold, while the rest of the United States increased 1.02-fold.\n\nConclusionThese results suggest that even outdoor gatherings in areas with low COVID-19 incidence are followed by increased infections, and that further precautions should be taken at such gatherings.\n\nWhat is already known on the topicMass gatherings have been linked to COVID-19 infections, but it is less clear how much it happens outdoors, and in areas with low incidence.\n\nWhat this study addsCOVID-19 infections increased significantly in 14 of 20 counties that held mass gathering rallies in the United States, 19 of which were outdoors. The county with the highest incidence increase (3.8-fold) was outdoors and had a low incidence before the gathering. The average incidence of all 20 counties with gatherings was lower at the gathering day compared with the rest of the United State, and it increased 1.5-fold following the gatherings. Our findings suggest a need for precautions in mass gatherings, even when outdoors and in areas with a low incidence of COVID-19.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Hemanta Kumar Baruah",
-        "author_inst": "The Assam Royal Global University"
+        "author_name": "Oren Miron",
+        "author_inst": "Ben Gurion University"
+      },
+      {
+        "author_name": "Kun-Hsing Yu",
+        "author_inst": "Harvard Medical School"
+      },
+      {
+        "author_name": "Rachel Wilf-Miron",
+        "author_inst": "Tel Aviv University"
+      },
+      {
+        "author_name": "Nadav Davidovich",
+        "author_inst": "Ben Gurion University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1073655,29 +1076395,45 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.10.27.357954",
-    "rel_title": "Tuning Intrinsic Disorder Predictors for Virus Proteins",
+    "rel_doi": "10.1101/2020.10.27.357731",
+    "rel_title": "SARS-CoV-2 viroporin triggers the NLRP3 inflammatory pathway",
     "rel_date": "2020-10-27",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.27.357954",
-    "rel_abs": "Many virus-encoded proteins have intrinsically disordered regions that lack a stable folded threedimensional structure. These disordered proteins often play important functional roles in virus replication, such as down-regulating host defense mechanisms. With the widespread availability of next-generation sequencing, the number of new virus genomes with predicted open reading frames is rapidly outpacing our capacity for directly characterizing protein structures through crystallography. Hence, computational methods for structural prediction play an important role. A large number of predictors focus on the problem of classifying residues into ordered and disordered regions, and these methods tend to be validated on a diverse training set of proteins from eukaryotes, prokaryotes and viruses. In this study, we investigate whether some predictors outperform others in the context of virus proteins. We evaluate the prediction accuracy of 21 methods, many of which are only available as web applications, on a curated set of 126 proteins encoded by viruses. Furthermore, we apply a random forest classifier to these predictor outputs. Based on cross-validation experiments, this ensemble approach confers a substantial improvement in accuracy, e.g., a mean 36% gain in Matthews correlation coefficient. Lastly, we apply the random forest predictor to SARS-CoV-2 ORF6, an accessory gene that encodes a short (61 AA) and moderately disordered protein that inhibits the host innate immune response.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.27.357731",
+    "rel_abs": "Cytokine storm resulting from a heightened inflammatory response is a prominent feature of severe COVID-19 disease. This inflammatory response results from assembly/activation of a cell-intrinsic defense platform known as the inflammasome. We report that the SARS-CoV-2 viroporin encoded by ORF3a activates the NLRP3 inflammasome, the most promiscuous of known inflammasomes. ORF3a triggers IL-1{beta} expression via NF{kappa}B, thus priming the inflammasome while also activating it via ASC-dependent and -independent modes. ORF3a-mediated inflammasome activation requires efflux of potassium ions and oligomerization between NEK7 and NLRP3. With the selective NLRP3 inhibitor MCC950 able to block ORF3a-mediated inflammasome activation and key ORF3a residues needed for virus release and inflammasome activation conserved in SARS-CoV-2 isolates across continents, ORF3a and NLRP3 present prime targets for intervention.\n\nSummaryDevelopment of anti-SARS-CoV-2 therapies is aimed predominantly at blocking infection or halting virus replication. Yet, the inflammatory response is a significant contributor towards disease, especially in those severely affected. In a pared-down system, we investigate the influence of ORF3a, an essential SARS-CoV-2 protein, on the inflammatory machinery and find that it activates NLRP3, the most prominent inflammasome by causing potassium loss across the cell membrane. We also define key amino acid residues on ORF3a needed to activate the inflammatory response, and likely to facilitate virus release, and find that they are conserved in virus isolates across continents. These findings reveal ORF3a and NLRP3 to be attractive targets for therapy.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Gal Almog",
-        "author_inst": "Department of Pathology & Laboratory Medicine, Western University, London, Canada"
+        "author_name": "Huanzhou Xu",
+        "author_inst": "College of Medicine University of Florida"
       },
       {
-        "author_name": "Abayomi Samuel Olabode",
-        "author_inst": "Department of Pathology & Laboratory Medicine, Western University, London, Canada"
+        "author_name": "Siddhi A Chitre",
+        "author_inst": "College of Medicine University of Florida"
       },
       {
-        "author_name": "Art FY Poon",
-        "author_inst": "Department of Pathology & Laboratory Medicine, Western University, London, Canada"
+        "author_name": "Ibukun A Akinyemi",
+        "author_inst": "College of Medicine University of Florida"
+      },
+      {
+        "author_name": "Julia C Loeb",
+        "author_inst": "University of Florida"
+      },
+      {
+        "author_name": "John A Lednicky",
+        "author_inst": "University of Florida"
+      },
+      {
+        "author_name": "Michael T McIntosh",
+        "author_inst": "College of Medicine University of Florida"
+      },
+      {
+        "author_name": "Sumita Bhaduri-McIntosh",
+        "author_inst": "College of Medicine University of Florida"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "new results",
     "category": "microbiology"
   },
@@ -1075233,63 +1077989,47 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.10.25.354571",
-    "rel_title": "Comparison of the in vitro-efficacy of different mouthwash solutions targeting SARS-CoV-2 based on the European Standard EN 14476",
-    "rel_date": "2020-10-26",
+    "rel_doi": "10.1101/2020.10.23.353219",
+    "rel_title": "The papain-like protease of coronaviruses cleaves ULK1 to disrupt host autophagy",
+    "rel_date": "2020-10-25",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.25.354571",
-    "rel_abs": "The SARS-Cov-2 pandemic is triggering a global health emergency alert, and recent research is indicating the relevance of aerosols in the spread of SARS-CoV-2. Thus, in this study antiseptic mouthwashes based on the actives chlorhexidine (CHX) and octenidine (OCT) were investigated regarding their efficacy against SARS-CoV-2 using EN 14476. Based on the requirement of EN 14476 (i.e. reduction of viral titer by [&ge;] 4 log 10), the OCT-based formulation was effective within only 15 sec against SARS-CoV-2, and thus constitutes an interesting candidate for future clinical studies to prove its effectiveness in a potential prevention of SARS-CoV-2 transmission by aerosols.",
-    "rel_num_authors": 11,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.23.353219",
+    "rel_abs": "The ongoing pandemic of COVID-19 alongside the outbreaks of SARS in 2003 and MERS in 2012 underscore the significance to understand betacoronaviruses as a global health challenge. SARS-CoV-2, the etiological agent for COVID-19, has infected more than 29 million individuals worldwide with nearly ~1 million fatalities. Understanding how SARS-CoV-2 initiates viral pathogenesis is of the utmost importance for development of antiviral drugs. Autophagy modulators have emerged as potential therapeutic candidates against SARS-CoV-2 but recent clinical setbacks underline the urgent need for better understanding the mechanism of viral subversion of autophagy. Using murine hepatitis virus-A59 (MHV-A59) as a model betacoronavirus, time-course infections revealed a significant loss in the protein level of ULK1, a canonical autophagy regulating serine-threonine kinase, and the concomitant appearance of a possible cleavage fragment. To investigate whether virus-encoded proteases target this protein, we conducted in vitro and cellular cleavage assays and identified ULK1 as a novel bona fide substrate of SARS-CoV-2 papain-like protease (PLpro). Mutagenesis studies discovered that ULK1 is cleaved at a conserved PLpro recognition sequence (LGGG) after G499, separating its N-terminal kinase domain from the C-terminal substrate recognition region. Consistent with this, over-expression of SARS-CoV-2 PLpro is sufficient to impair starvation-induced canonical autophagy and disrupt formation of ULK1-ATG13 complex. Finally, we demonstrated a dual role for ULK1 in MHV-A59 replication, serving a pro-viral functions during early replication that is inactivated at late stages of infection. In conclusion, our study identified a new mechanism by which PLpro of betacoronaviruses induces viral pathogenesis by targeting cellular autophagic pathway (Word count=250)\n\nIMPORTANCEThe recent COVID-19 global pandemic alongside the 2003 SARS and 2012 MERS outbreaks underscore an urgent need to better understand betacoronaviruses as pathogens that pose global challenge to human health. Studying the underlying biology of how betacoronaviruses subvert innate cellular defense pathways such as autophagy will help to guide future efforts to develop anti-viral therapy. (Word count= 55)",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Katrin Steinhauer",
-        "author_inst": "Department Research & Scientific Services, Schuelke & Mayr GmbH, Norderstedt, Germany; Faculty of Mechanical Engineering, Kiel University of Applied Sciences, K"
-      },
-      {
-        "author_name": "Toni Luise Meister",
-        "author_inst": "Department of Molecular and Medical Virology, Ruhr University Bochum, 44801 Bochum, Germany"
-      },
-      {
-        "author_name": "Daniel Todt",
-        "author_inst": "Department of Molecular and Medical Virology, Ruhr University Bochum, 44801 Bochum, Germany; European Virus Bioinformatics Center (EVBC), 07743 Jena, Germany"
-      },
-      {
-        "author_name": "Adalbert Krawczyk",
-        "author_inst": "Department of Molecular and Medical Virology, Ruhr University Bochum, 44801 Bochum, Germany; European Virus Bioinformatics Center (EVBC), 07743 Jena, Germany"
-      },
-      {
-        "author_name": "Lars Passvogel",
-        "author_inst": "Department Research & Scientific Services, Schuelke & Mayr GmbH, Norderstedt, Germany"
+        "author_name": "Yasir Mohamud",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Britta Becker",
-        "author_inst": "Dr. Brill + Partner GmbH Institut for Hygiene and Microbiology, Hamburg, Germany"
+        "author_name": "Yuan Chao Xue",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Dajana Paulmann",
-        "author_inst": "Dr. Brill + Partner GmbH Institut for Hygiene and Microbiology, Hamburg, Germany"
+        "author_name": "Huitao Liu",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Birte Bischoff",
-        "author_inst": "Dr. Brill + Partner GmbH Institut for Hygiene and Microbiology, Hamburg, Germany"
+        "author_name": "Chen Seng Ng",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Stephanie Pfaender",
-        "author_inst": "Department of Molecular and Medical Virology, Ruhr University Bochum, 44801 Bochum, Germany"
+        "author_name": "Amirhossein Bahreyni",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Florian Brill",
-        "author_inst": "Dr. Brill + Partner GmbH Institut for Hygiene and Microbiology, Hamburg, Germany"
+        "author_name": "Eric Jan",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Eike Steinmann",
-        "author_inst": "Ruhr University Bochum"
+        "author_name": "Honglin Luo",
+        "author_inst": "University of British Columbia"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "cell biology"
   },
   {
     "rel_doi": "10.1101/2020.10.21.20217117",
@@ -1076591,43 +1079331,83 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2020.10.20.20215608",
-    "rel_title": "Evidence for secondary thrombotic microangiopathy in COVID-19",
+    "rel_doi": "10.1101/2020.10.21.20216192",
+    "rel_title": "Broadly-targeted autoreactivity is common in severe SARS-CoV-2 Infection",
     "rel_date": "2020-10-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20215608",
-    "rel_abs": "The causes of coagulopathy associated with COVID-19 disease are poorly understood. We aimed to investigate the relationship between markers of endothelial activation, intravascular hemolysis, coagulation, and organ damage in COVID-19 patients and study their association with disease severity and mortality. We conducted a retrospective study of 181 hospitalized COVID-19 patients randomly selected with equal distribution of survivors and non-survivors. Patients who died had significantly lower ADAMTS13 activity, significantly higher LDH, schistocytes and von Willebrand Factor levels compared to patients discharged alive. Only 30% of patients with an initial ADAMTS13 activity <43% survived vs. 60% with ADAMTS13 [&ge;]43% who survived. In conclusion, COVID-19 may manifest as a TMA-like illness in a subset of hospitalized patients. Presence of schistocytes on admission may warrant a work-up for TMA. These findings indicate the need for future investigation to study the relationship between endothelial and coagulation activation and the efficacy of TMA treatments in COVID-19.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20216192",
+    "rel_abs": "An emerging feature of COVID-19 is the identification of autoreactivity in patients with severe disease that may contribute to disease pathology, however the origin and resolution of these responses remain unclear. Previously, we identified strong extrafollicular B cell activation as a shared immune response feature between both severe COVID-19 and patients with advanced rheumatic disease. In autoimmune settings, this pathway is associated with relaxed peripheral tolerance in the antibody secreting cell compartment and the generation of de novo autoreactive responses. Investigating these responses in COVID-19, we performed single-cell repertoire analysis on 7 patients with severe disease. In these patients, we identify the expansion of a low-mutation IgG1 fraction of the antibody secreting cell compartment that are not memory derived, display low levels of selective pressure, and are enriched for autoreactivity-prone IGHV4-34 expression. Within this compartment, we identify B cell lineages that display specificity to both SARS-CoV-2 and autoantigens, including pathogenic autoantibodies against glomerular basement membrane, and describe progressive, broad, clinically relevant autoreactivity within these patients correlated with disease severity. Importantly, we identify anti-carbamylated protein responses as a common hallmark and candidate biomarker of broken peripheral tolerance in severe COVID-19. Finally, we identify the contraction of this pathway upon recovery, and re-establishment of tolerance standards coupled with a concomitant loss of acute-derived ASCs irrespective of antigen specificity. In total, this study reveals the origins, breadth, and resolution of acute-phase autoreactivity in severe COVID-19, with significant implications in both early interventions and potential treatment of patients with post-COVID sequelae.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Joseph Sweeney",
-        "author_inst": "Albert Einstein College of Medicine"
+        "author_name": "Matthew Woodruff",
+        "author_inst": "Emory University"
       },
       {
-        "author_name": "Mohammad Barouqa",
-        "author_inst": "Montefiore Medical Center"
+        "author_name": "Richard P Ramonell",
+        "author_inst": "Emory University"
       },
       {
-        "author_name": "Gregory J J Krause",
-        "author_inst": "Albert Einstein College of Medicine"
+        "author_name": "Ankur Singh Saini",
+        "author_inst": "Emory University"
       },
       {
-        "author_name": "Jesus Gonzalez Lugo",
-        "author_inst": "Montefiore Medical Center"
+        "author_name": "Natalie S. Haddad",
+        "author_inst": "Emory University"
       },
       {
-        "author_name": "Shafia Rahman",
-        "author_inst": "Montefiore Medical Center"
+        "author_name": "Fabliha A Anam",
+        "author_inst": "Emory University"
       },
       {
-        "author_name": "Morayma Reyes Gil",
-        "author_inst": "Montefiore Medical Center"
+        "author_name": "Mark E. Rudolph",
+        "author_inst": "Exagen, Inc."
+      },
+      {
+        "author_name": "Regina Bugrovsky",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Jennifer Hom",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Kevin S. Cashman",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Doan C. Nguyen",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Shuya Kyu",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Michael Piazza",
+        "author_inst": "Nicoya"
+      },
+      {
+        "author_name": "Christopher M. Tipton",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Scott Jenks",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "F. Eun-Hyung Lee",
+        "author_inst": "Emory University"
+      },
+      {
+        "author_name": "Ignacio Sanz",
+        "author_inst": "Emory University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "hematology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.10.22.20213207",
@@ -1078277,87 +1081057,39 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.10.21.20216960",
-    "rel_title": "Emergency Response for Evaluating SARS-CoV-2 Immune Status, Seroprevalence and Convalescent Plasma in Argentina",
+    "rel_doi": "10.1101/2020.10.21.20216945",
+    "rel_title": "The effect of COVID-19 on critical care research: A prospective longitudinal multinational survey",
     "rel_date": "2020-10-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20216960",
-    "rel_abs": "We report the emergency development and application of a robust serologic test to evaluate acute and convalescent antibody responses to SARS-CoV-2 in Argentina. The assays, COVIDAR IgG and IgM, which were produced and provided for free to health authorities, private and public health institutions and nursing homes, use a combination of a trimer stabilized spike protein and the receptor binding domain (RBD) in a single enzyme-linked immunosorbent assay (ELISA) plate. Over half million tests have already been distributed to detect and quantify antibodies for multiple purposes, including assessment of immune responses in hospitalized patients and large seroprevalence studies in neighborhoods, slums and health care workers, which resulted in a powerful tool for asymptomatic detection and policy making in the country. Analysis of antibody levels and longitudinal studies of symptomatic and asymptomatic SARS-CoV-2 infections in over one thousand patient samples provided insightful information about IgM and IgG seroconversion time and kinetics, and IgM waning profiles. At least 35% of patients showed seroconversion within 7 days, and 95% within 45 days of symptoms onset, with simultaneous or close sequential IgM and IgG detection. Longitudinal studies of asymptomatic cases showed a wide range of antibody responses with median levels below those observed in symptomatic patients. Regarding convalescent plasma applications, a protocol was standardized for the assessment of end point IgG antibody titers with COVIDAR with more than 500 plasma donors. The protocol showed a positive correlation with neutralizing antibody titers, and was used to assess antibody titers for clinical trials and therapies across the country. Here, we demonstrate the importance of providing a robust and specific serologic assay for generating new information about antibody kinetics in infected individuals and mitigation policies to cope with pandemic needs.\n\nAUTHOR SUMMARYThe development of robust and specific serologic assays to detect antibodies to SARS-CoV-2 is essential to understand the pandemic evolution and to stablish mitigation strategies. Here, we report the emergency development, production and application of a versatile ELISA test for detecting antibodies against the whole spike protein and its receptor binding domain. Over half million tests have been freely distributed in public and private health institutions of Argentina for evaluating immune responses, convalescent plasma programs and for large seroprevalence studies in neighborhoods and health care workers. We are still learning how and when to use serologic testing in different epidemiological settings. This program allowed us to produce large amount of high quality data on antibody levels in symptomatic and asymptomatic SARS-CoV-2 infections and generate relevant information about IgM and IgG seroconversion time and kinetics. We also present standardized protocols for antibody quantification as guidance for convalescent donor plasma selection in hospitals throughout the country for compassionate use and clinical trials. Here, we provide a framework for generating widely available tools, protocols and information of antibody responses for pandemic management.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20216945",
+    "rel_abs": "ImportanceThe COVID-19 pandemic has increased the need for high-quality evidence in critical care, while also increasing the barriers to conducting the research needed to produce such evidence.\n\nObjectiveTo determine the effect of the first wave of the COVID-19 pandemic on critical care clinical research.\n\nDesignMonthly electronic survey (March 2020 - February 2021).\n\nSettingAdult or pediatric intensive care units (ICUs) from any country participating in at least one research study before the COVID-19 pandemic.\n\nParticipantsWe recruited one researcher or research coordinator per center, identified via established research networks.\n\nIntervention(s)None\n\nMain Outcome(s) and Measure(s)Primary: Suspending recruitment in clinical research; Secondary: impact of specific factors on research conduct (5-point scales from no effect to very large effect). We assessed the association between research continuity and month, presence of hospitalized patients with COVID-19, and population (pediatric vs. adult ICU) using mixed-effects logistic regression.\n\nResults127 centers (57% pediatric) from 23 countries participated. 95 (75%) of centers suspended recruitment in at least some studies and 37 (29%) suspended recruitment in all studies on at least one month. The proportion of centers reporting recruitment in all studies increased over time (OR per month 1.3, 95% CI 1.2 to 1.4, p < 0.001), controlling for hospitalized patients with COVID-19 and type of ICU (pediatric vs. other). The five factors most frequently identified as having a large or very large effect on clinical research were: local prioritization of COVID-19 specific research (68, 54%), infection control policies limiting access to patients with COVID-19 (61, 49%), infection control policies limiting access to the ICU (52, 41.6%), increased workload of clinical staff (38, 30%), and safety concerns of research staff (36, 29%).\n\nConclusions and RelevanceDecisions to pause or pursue clinical research varied across centers. Research activity increased over time, despite the presence of hospitalized patients with COVID-19. Guiding principles with local adaptation to safely sustain research during this and future pandemics are urgently needed.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat was the effect of the COVID-19 pandemic on research in 127 adult and pediatric intensive care units (ICUs) between March 2020 and February 2021?\n\nFindings95 (75%) centers suspended recruitment into at least some studies. Active recruitment into studies increased over time (OR per month 1.3, 95% CI 1.2 to 1.4, p < 0.001), controlling for ICU type and the presence of patients with COVID-19.\n\nMeaningResearch activity varied across centers and increased over time, despite the presence of hospitalized patients with COVID-19. Guiding principles to safely sustain research during this and future pandemics are urgently needed.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Diego Ojeda",
-        "author_inst": "Fundacion Instituto Leloir-CONICET"
-      },
-      {
-        "author_name": "Maria Mora Gonzalez Lopez Ledesma",
-        "author_inst": "Fundacion Instituto Leloir CONICET"
-      },
-      {
-        "author_name": "Horacio Palleres",
-        "author_inst": "Fundacion Instituto Leloir-CONICET"
-      },
-      {
-        "author_name": "Guadalupe Costa Navarro",
-        "author_inst": "Fundacion Instituto Leloir-CONICET"
-      },
-      {
-        "author_name": "Lautaro Sanchez",
-        "author_inst": "Fundacion Instituto Leloir CONICET"
-      },
-      {
-        "author_name": "Beatriz Perazzi",
-        "author_inst": "Facultad de Farmacia y Bioquimica UBA"
-      },
-      {
-        "author_name": "Sergio Villordo",
-        "author_inst": "Fundacion Instituto Leloir"
-      },
-      {
-        "author_name": "Diego Alvarez",
-        "author_inst": "Instituto de Investigaciones Biotecnologicas, Universidad Nacional de San Martin"
-      },
-      {
-        "author_name": "- BioBanco Working Group",
-        "author_inst": ""
-      },
-      {
-        "author_name": "Marcela Echavarria",
-        "author_inst": "Centro de Educacion Medica e Investigaciones Clinicas"
-      },
-      {
-        "author_name": "Kasopefoluwa Y. Oguntuyo",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Christian Stevens",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Benhur Lee",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Mark Duffett",
+        "author_inst": "McMaster University"
       },
       {
-        "author_name": "Jorge Carradori",
-        "author_inst": "Laboratorio Lemos"
+        "author_name": "Deborah J Cook",
+        "author_inst": "McMaster University"
       },
       {
-        "author_name": "Julio Caramelo",
-        "author_inst": "Fundacion Instituto Leloir CONICET"
+        "author_name": "Geoff Strong",
+        "author_inst": "McMaster University"
       },
       {
-        "author_name": "Marcelo Yanovsky",
-        "author_inst": "Fundacion Instituto Leloir"
+        "author_name": "Jan Hau Lee",
+        "author_inst": "KK Women's and Children's Hospital"
       },
       {
-        "author_name": "Andrea Gamarnik",
-        "author_inst": "FUNDACION INSTITUTO LELOIR"
+        "author_name": "Michelle E Kho",
+        "author_inst": "McMaster University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "intensive care and critical care medicine"
   },
   {
     "rel_doi": "10.1101/2020.10.21.20216986",
@@ -1079939,61 +1082671,41 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.19.20213421",
-    "rel_title": "PREVALENCE OF ANTIBODIES AGAINST SARS-CoV-2 IN PROFESSIONALS OF A PUBLIC HEALTH LABORATORY AT SAO PAULO, SP, BRAZIL",
+    "rel_doi": "10.1101/2020.10.20.20212522",
+    "rel_title": "Analytical solution of equivalent SEIR and agent-based model of COVID-19; showing the bounds of contact tracing",
     "rel_date": "2020-10-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.19.20213421",
-    "rel_abs": "BackgroundCovid-19 Serology may document exposure and perhaps protection to the virus and serological test may help understand epidemic dynamics. We tested health workers form a public laboratory to evaluate previous exposure to the virus and estimate the prevalence of antibodies against-SARS-CoV-2 in Adolfo Lutz Institute, State of Sao Paulo, Brazil.\n\nMethodsThis study was an open, prospective evaluation among professionals of Adolfo Lutz Institute some administrative personnel from the Secretary of Health that shares common areas with the institute. We used a lateral flow immunoassay (rapid test) to detect IgG and IgM for SARS-CoV-2; positive samples were further evaluated using Roche Electrochemiluminescence assay. SARS-CoV-2 RNA by real time reverse transcriptase polymerase chain reaction (RT-PCR) was also offered to participants.\n\nResultsA total of 406 HPs participated. Thirty five (8.6%) tested positive on rapid test and 32 these rapid test seropositive cases were confirmed by ECLIA. 43 HPs had SARS-CoV-2 RNA detected at a median of 33 days, and the three cases not reactive at Roche ECLIA had a previous positive RNA. Outsourced professionals (34% seropositive), males (15%) workers referring COVID-19 patients at home (22%) and those living farther form the institute tended to have higher prevalence of seropositivity, but in multivariable logistic analysis only outsourced workers and those with COVID patients at home remained independently associated to seropositivity. We observed no relation of seropositivity to COVID samples handling. Presence of at least one symptom was common but some clinical manifestations as anosmia/dysgeusia. Fatigue, cough and fever were associated to seropositivity.\n\nConclusionsWe documented a relatively high (8.6%) of anti-SARS-CoV-2 serological reactivity in this population, higher among outsourced workers and those residing with COVID-19 patients. COVID related work did not increased seropositivity. Some symptoms show strong association to COVID-19 serology and may be used in scoring tools for screening or diagnosis in resort limited settings.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20212522",
+    "rel_abs": "Mathematical models not only forecast the possible future but also is used to find hidden parameters of the COVID-19 pandemic. Numerical estimates can inform us of both goals. Still, the interdependencies of parameters stay obscure. Many numerical solutions have been proposed so far; however, the analytical relationship between the outbreak growth, decay and equilibrium are much less studied. In this study, we have employed both an equivalent agent-based model and a Susceptible-Exposed-Infected-Recovered (SEIR)-like model to prove that the growth rate can be determined analytically in terms of other model parameters, including contact tracing rate. We identify the most sensitive parameters as undocumented transmission rate and documentation ratio. Unfortunately, these are the parameters we have the least knowledge. We derived an identity that predicts the effectiveness of contact tracing in a country from observable parameters. We underline an unavoidable dilemma: that even in the case of high contact tracing, we cannot bring the outbreak to stalemate without applying substantial quarantine; however, some countries are benefiting from contact tracing. Besides, we have shown that the seemingly same parameters of the SEIR models and agent-based models are not equivalent. We propose a correction to bridge both models.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Valeria Oliveira Silva",
-        "author_inst": "Instituto Adolfo Lutz"
-      },
-      {
-        "author_name": "Elaine Lopes de Oliveira",
-        "author_inst": "Instituto Adolfo Lutz"
+        "author_name": "Huseyin Tunc",
+        "author_inst": "Yildiz Technical University, Department of Mathematics"
       },
       {
-        "author_name": "Marcia Jorge Castejon",
-        "author_inst": "Instituto Adolfo Lutz"
+        "author_name": "Fatma Zehra Sari",
+        "author_inst": "Gebze Technical University, Institute of Biotechnology"
       },
       {
-        "author_name": "Rosemeire Yamashiro",
-        "author_inst": "Instituto Adolfo Lutz"
+        "author_name": "Busra Darendeli",
+        "author_inst": "Yildiz Technical University, Department of Bioengineering"
       },
       {
-        "author_name": "Cintia Mayumi Ahagon",
-        "author_inst": "Instituto Adolfo Lutz"
-      },
-      {
-        "author_name": "Giselle Ibette Lopez-Lopes",
-        "author_inst": "Instituto Adolfo Lutz"
-      },
-      {
-        "author_name": "Edilene Peres Real da Silveira",
-        "author_inst": "Instituto Adolfo Lutz"
-      },
-      {
-        "author_name": "Marisa Ailin Hong",
-        "author_inst": "Instituto Adolfo Lutz"
-      },
-      {
-        "author_name": "Maria do Carmo Timenetsky",
-        "author_inst": "Instituto Adolfo Lutz"
+        "author_name": "Ramin Nashebi",
+        "author_inst": "Yildiz Technical University, Department of Mathematics"
       },
       {
-        "author_name": "Carmem aparecida de Freitas Oliveira",
-        "author_inst": "Instituto Adolfo Lutz"
+        "author_name": "Murat Sari",
+        "author_inst": "Yildiz Technical University, Department of Mathematics"
       },
       {
-        "author_name": "Luis Fernando de Macedo Brigido",
-        "author_inst": "Instituto Adolfo Lutz"
+        "author_name": "Seyfullah Enes Kotil",
+        "author_inst": "Bahcesehir University Medical School, Department of Medicinal Microbiology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1081544,63 +1084256,23 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.14.20212662",
-    "rel_title": "Antibody Immunological Imprinting on COVID-19 Patients",
+    "rel_doi": "10.1101/2020.10.15.20213223",
+    "rel_title": "Prediction of Covid-19 Infections Through December 2020 for 10 US States Incorporating Outdoor Temperature and School Re-Opening Effects-September Update",
     "rel_date": "2020-10-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.14.20212662",
-    "rel_abs": "While the current pandemic remains a thread to human health, the polyclonal nature of the antibody response against SARS-CoV-2 is not fully understood. Other than SARS-CoV-2, humans are susceptible to six different coronaviruses, and previous exposure to antigenically related and divergent seasonal coronaviruses is frequent. We longitudinally profiled the early humoral immune response against SARS-CoV-2 on hospitalized COVID-19 patients, and quantify levels of pre-existing immunity to OC43, HKU1 and 223E seasonal coronaviruses. A strong back-boosting effect to conserved, but not variable regions of OC43 and HKU1 betacoronaviruses spike protein was observed. All patients developed antibodies against SARS-CoV-2 spike and nucleoprotein, with peak induction at day 7 post hospitalization. However a negative correlation was found between antibody memory boost to human coronaviruses and induction of IgG and IgM against SARS-CoV-2 spike. Our findings provide evidence of immunological imprinting that determine the antibody profile to COVID-19 patients in an original antigenic sin fashion.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.15.20213223",
+    "rel_abs": "A two-parameter, human behavior Covid-19 infection growth model predicts total infections between-4.2% (overprediction) and 4.5% (underprediction) of actual infections from July 27, 2020 to September 30, 2020 for 10 US States (NY, WA, GA, IL, MN, FL, OH, MI, CA, NC). During that time, total Covid-19 infections for 9 of the 10 modeled US States grew by 60% (MI) to 95% (MN). Only NY limited Covid-19 infection growth with an 11% increase from July 27 to September 30, 2020.\n\nSeptember is a month with contraposing effects of increased social interaction (eg, physical school openings) and outdoor temperatures decreasing to the 50F (10C) to 70F (21C) range in which outdoor activities and building ventilation are beneficially increased. All State infection predictions except GA, FL and CA predictions through September 30 are bounded by four prediction scenarios (no school with outdoor temperature effect, no school with no outdoor temperature effect, school with temperature effect, school with no temperature effect). GA, FL and CA continued along a path slightly below the linear infection growth boundary separating infection growth and decay, resulting in overprediction of infection growth over the two month simulation period(-3.1% for GA, -1.9% for FL, and -4.5% for CA).\n\nThree eastern States (NY, NC, and GA) are most accurately represented by models that assume no significant change in social interactions coupled with minor outdoor temperature effects. Four midwestern States (IL, MI, MN, OH) are most accurately modeled with minor outdoor temperature effects due to a delayed decrease in average outdoor temperatures in the Midwest. The remaining three States (WA, FL, and CA) are also in good agreement with the model but with differing weather condition and social interaction impacts.\n\nOverall, model predictions continue to support the basic premise that human behavior in the US oscillates across a linear infection growth boundary that divides accelerated infection growth and decaying infection transmission.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Teresa Aydillo",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York;"
-      },
-      {
-        "author_name": "Alexander Rombauts",
-        "author_inst": "Department of Infectious Diseases, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), University of Barcelona, LHospitalet de Llo"
-      },
-      {
-        "author_name": "Daniel Stadlbauer",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York"
-      },
-      {
-        "author_name": "Sadaf Aslam",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York"
-      },
-      {
-        "author_name": "Gabriela Abelenda-Alonso",
-        "author_inst": "Department of Infectious Diseases, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), University of Barcelona, LHospitalet de Llo"
-      },
-      {
-        "author_name": "Alba Escalera",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York"
-      },
-      {
-        "author_name": "Fatima Amanat",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York"
-      },
-      {
-        "author_name": "Kaijun Jiang",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York"
-      },
-      {
-        "author_name": "Florian Krammer",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York"
-      },
-      {
-        "author_name": "Jordi Carratala",
-        "author_inst": "Department of Infectious Diseases, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), University of Barcelona, LHospitalet de Llo"
-      },
-      {
-        "author_name": "Adolfo Garcia-Sastre",
-        "author_inst": "Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York"
+        "author_name": "Ty A Newell",
+        "author_inst": "University of Illinois"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.10.14.20212829",
@@ -1083334,25 +1086006,29 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.17.20214312",
-    "rel_title": "Echo chambers as early warning signals of widespread vaccine refusal in social-epidemiological networks",
+    "rel_doi": "10.1101/2020.10.16.20214049",
+    "rel_title": "Quantifying Asymptomatic Infection and Transmission of COVID-19 in New York City using Observed Cases, Serology and Testing Capacity",
     "rel_date": "2020-10-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.17.20214312",
-    "rel_abs": "Sudden shifts in population health and vaccination rates occur as the dynamics of some epidemiological models go through a critical point; literature shows that this is sometimes foreshadowed by early warning signals (EWS). We investigate different structural measures of a network as candidate EWS of infectious disease outbreaks and changes in popular vaccine sentiment. We construct a multiplex disease model coupling infectious disease spread and social contact dynamics. We find that the number and mean size of echo chambers predict transitions in the infection dynamics, as do opinion-based communities. Graph modularity also gives early warnings, though the clustering coefficient shows no significant pre-outbreak changes. Change point tests applied to the EWS show decreasing efficacy as social norms strengthen. Therefore, many measures of social network connectivity can predict approaching critical changes in vaccine uptake and aggregate health, thereby providing valuable tools for improving public health.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.16.20214049",
+    "rel_abs": "The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13% to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with pre-symptomatic ones. If asymptomatic infections transmit at similar rates than symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, pre-symptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection sub-populations have reproductive numbers lower than 3. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of SARS-Cov-2 should be reconsidered.\n\nSignificance StatementAs health officials face another wave of COVID-19, they require estimates of the proportion of infected cases that develop symptoms, and the extent to which symptomatic and asymptomatic cases contribute to community transmission. Recent asymptomatic testing guidelines are ambiguous. Using an epidemiological model that includes testing capacity, we show that most infections are asymptomatic but contribute substantially to community transmission in the aggregate. Their individual transmissibility remains uncertain. If they transmit as well as symptomatic infections, the epidemic may spread at faster rates than current models often assume. If they do not, then each symptomatic case generates on average a higher number of secondary infections than typically assumed. Regardless, controlling transmission requires community-wide interventions informed by extensive, well-documented asymptomatic testing.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Brendon C Phillips",
-        "author_inst": "University of Waterloo"
+        "author_name": "Rahul Subramanian",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Chris Bauch",
-        "author_inst": "University of Waterloo"
+        "author_name": "Qixin He",
+        "author_inst": "University of Chicago"
+      },
+      {
+        "author_name": "Mercedes Pascual",
+        "author_inst": "University of Chicago"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1084880,111 +1087556,139 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.10.15.20208041",
-    "rel_title": "Analysis of respiratory and systemic immune responses in COVID-19 reveals mechanisms of disease pathogenesis",
+    "rel_doi": "10.1101/2020.10.17.343863",
+    "rel_title": "Development and pre-clinical characterization of two therapeutic equine formulations towards SARS-CoV-2 proteins for the potential treatment of COVID-19",
     "rel_date": "2020-10-19",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.15.20208041",
-    "rel_abs": "Immune responses to respiratory viruses like SARS-CoV-2 originate and function in the lung, yet assessments of human immunity are often limited to blood. Here, we conducted longitudinal, high-dimensional profiling of paired airway and blood samples from patients with severe COVID-19, revealing immune processes in the respiratory tract linked to disease pathogenesis. Survival from severe disease was associated with increased CD4+T cells and decreased monocyte/macrophage frequencies in the airway, but not in blood. Airway T cells and macrophages exhibited tissue-resident phenotypes and activation signatures, including high level expression and secretion of monocyte chemoattractants CCL2 and CCL3 by airway macrophages. By contrast, monocytes in blood expressed the CCL2-receptor CCR2 and aberrant CD163+ and immature phenotypes. Extensive accumulation of CD163+monocyte/macrophages within alveolar spaces in COVID-19 lung autopsies suggested recruitment from circulation. Our findings provide evidence that COVID-19 pathogenesis is driven by respiratory immunity, and rationale for site-specific treatment and prevention strategies.",
-    "rel_num_authors": 23,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.17.343863",
+    "rel_abs": "In the current global emergency due to SARS-CoV-2 outbreak, passive immunotherapy emerges as a promising treatment for COVID-19. Among animal-derived products, equine formulations are still the cornerstone therapy for treating envenomations due to animal bites and stings. Therefore, drawing upon decades of experience in manufacturing snake antivenom, we developed and preclinically evaluated two anti-SARS-CoV-2 polyclonal equine formulations as potential alternative therapy for COVID-19. We immunized two groups of horses with either S1 (anti-S1) or a mixture of S1, N, and SEM mosaic (anti-Mix) viral recombinant proteins. Horses reached a maximum anti-viral antibody level at 7 weeks following priming, and showed no major adverse acute or chronic clinical alterations. Two whole-IgG formulations were prepared via hyperimmune plasma precipitation with caprylic acid and then formulated for parenteral use. Both preparations had similar physicochemical and microbiological quality and showed ELISA immunoreactivity towards S1 protein and the receptor binding domain (RBD). The anti-Mix formulation also presented immunoreactivity against N protein. Due to high anti-S1 and anti-RBD antibody content, final products exhibited high in vitro neutralizing capacity of SARS-CoV-2 infection, 80 times higher than a pool of human convalescent plasma. Pre-clinical quality profiles were similar among both products, but clinical efficacy and safety must be tested in clinical trials. The technological strategy we describe here can be adapted by other producers, particularly in low- and middle-income countries.",
+    "rel_num_authors": 30,
     "rel_authors": [
       {
-        "author_name": "Peter A. Szabo",
-        "author_inst": "Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Guillermo Le\u00f3n",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Pranay Dogra",
-        "author_inst": "Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Mar\u00eda Herrera",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Joshua I. Gray",
-        "author_inst": "Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Mari\u00e1ngela Vargas",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Steven B. Wells",
-        "author_inst": "Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Mauricio Arguedas",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Thomas J. Connors",
-        "author_inst": "Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Andr\u00e9s S\u00e1nchez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Stuart P. Weisberg",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "\u00c1lvaro Segura",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Izabela Krupska",
-        "author_inst": "Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Aar\u00f3n G\u00f3mez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Rei Matsumoto",
-        "author_inst": "Department of Surgery, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Gabriela Solano",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Maya M.L. Poon",
-        "author_inst": "Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY 10032 and Medical Scientist Training Program, Columbia Univer"
+        "author_name": "Eugenia Corrales-Aguilar",
+        "author_inst": "Virology-CIET (Research Center for Tropical Diseases), Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Emma Idzikowski",
-        "author_inst": "Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Kenneth Risner",
+        "author_inst": "National Center for Biodefense and Infectious Diseases, George Mason University"
       },
       {
-        "author_name": "Sinead E. Morris",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Aarthi Narayanan",
+        "author_inst": "National Center for Biodefense and Infectious Diseases, George Mason University"
       },
       {
-        "author_name": "Pasin Chloe",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Charles Bailey",
+        "author_inst": "National Center for Biodefense and Infectious Diseases, George Mason University"
       },
       {
-        "author_name": "Andrew J. Yates",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Mauren Villalta",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Amy Ku",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Andr\u00e9s Hern\u00e1ndez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Michael Chait",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Adriana S\u00e1nchez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Julia M. Davis-Porada",
-        "author_inst": "Medical Scientist Training Program, Columbia University"
+        "author_name": "Daniel Cordero",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Jing Zhou",
-        "author_inst": "IsoPlexis Corporation, Branford, CT 06405"
+        "author_name": "Daniela Solano",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Matthew Steinle",
-        "author_inst": "IsoPlexis Corporation, Branford, CT 06405"
+        "author_name": "Gina Dur\u00e1n",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Sean Mackay",
-        "author_inst": "IsoPlexis Corporation, Branford, CT 06405"
+        "author_name": "Eduardo Segura",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Anjali Saqi",
-        "author_inst": "Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Maykel Cerdas",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
+      },
+      {
+        "author_name": "Deibid Uma\u00f1a",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Matthew R. Baldwin",
-        "author_inst": "Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032"
+        "author_name": "Edwin Moscoso",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Peter A. Sims",
-        "author_inst": "Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032 and Department of Biochemistry and Molecular Biophysics, Columbia U"
+        "author_name": "Ricardo Estrada",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       },
       {
-        "author_name": "Donna L Farber",
-        "author_inst": "Columbia University"
+        "author_name": "Jairo Guti\u00e9rrez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
+      },
+      {
+        "author_name": "Marcos M\u00e9ndez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
+      },
+      {
+        "author_name": "Ana Cecilia Castillo",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
+      },
+      {
+        "author_name": "Laura S\u00e1nchez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
+      },
+      {
+        "author_name": "Jos\u00e9 Mar\u00eda Guti\u00e9rrez",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
+      },
+      {
+        "author_name": "Cecilia D\u00edaz",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
+      },
+      {
+        "author_name": "Alberto Alape",
+        "author_inst": "Instituto Clodomiro Picado, Facultad de Microbiolog\u00eda, Universidad de Costa Rica"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.10.19.344713",
@@ -1086413,25 +1089117,153 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2020.10.14.20212449",
-    "rel_title": "TREATMENT PROFILES AND CLINICAL OUTCOMES OF COVID-19 PATIENTS AT PRIVATE HOSPITAL IN JAKARTA",
+    "rel_doi": "10.1101/2020.10.10.20207449",
+    "rel_title": "Recovery of monocyte exhaustion is associated with resolution of lung injury in COVID-19 convalescence.",
     "rel_date": "2020-10-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.14.20212449",
-    "rel_abs": "BackgroundSevere Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a virus that causes COVID-19, which has become a worldwide pandemic. However, until now, there is no vaccine or specific drug to prevent or treat COVID-19.\n\nObjectivesTo find out the effective treatment as an antiviral agent for COVID-19, to determine the correlation between sociodemography with clinical outcomes and duration of treatment, and to determine the relationship between comorbidities with clinical outcomes and duration of treatment for COVID-19 patients.\n\nMethodsA prospective cohort study was conducted in this study. This study included only confirmed COVID-19 patients who were admitted to the hospital during April-May 2020. Convenience sampling was used to select 103 patients, but only 72 patients were suitable for inclusion.\n\nResultsThe survival analysis for COVID-19 patients using the Kaplan Meier method showed that patients receiving Oseltamivir + Hydroxychloroquine had an average survival rate of about 83% after undergoing treatment for about ten days. Gender (p = 0.450) and age (p = 0.226) did not have a significant correlation with the duration of treatment for COVID-19 patients. Gender (p = 0.174) and age (p = 0.065) also did not have a significant correlation with clinical outcome of COVID-19 patients. Comorbidities showed a significant correlation with duration of treatment (p = 0.002) and clinical outcome (p = 0.014) of COVID-19 patients.\n\nConclusionThe most effective antiviral agent in this study based on treatment duration was the combination of Oseltamivir + Hydroxychloroquine. The higher the patients average treatment duration, the lower the average survival rate for COVID-19 patients.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.10.20207449",
+    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection resulting in the clinical syndrome COVID-19 is associated with an exaggerated immune response and monocyte infiltrates in the lungs and other peripheral tissues. It is now increasingly recognised that chronic morbidity persists in some patients. We recently demonstrated profound alterations of monocytes in hospitalised COVID-19 patients. It is currently unclear whether these abnormalities resolve or progress following patient discharge. We show here that blood monocytes in convalescent patients at their 12 week follow up, have a greater propensity to produce pro-inflammatory cytokines TNF and IL-6, which was consistently higher in patients with resolution of lung injury as indicated by a normal chest X-ray and no shortness of breath (a key symptom of lung injury). Furthermore, monocytes from convalescent patients also displayed enhanced levels of molecules involved in leucocyte migration, including chemokine receptor CXCR6, adhesion molecule CD31/PECAM and integrins VLA-4 and LFA-1. Expression of migration molecules on monocytes was also consistently higher in convalescent patients with a normal chest X-ray. These data suggest persistent changes in innate immune function following recovery from COVID-19 and indicate that immune modulating therapies targeting monocytes and leucocyte migration may be useful in recovering COVID-19 patients with persistent symptoms.",
+    "rel_num_authors": 34,
     "rel_authors": [
       {
-        "author_name": "Diana Laila Ramatillah",
-        "author_inst": "Universitas 17 Agustus 1945 Jakarta"
+        "author_name": "Nicholas A Scott",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Sean Blandin Knight",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Laurence Pearmain",
+        "author_inst": "North West Lung Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust"
+      },
+      {
+        "author_name": "Oliver Brand",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "David J Morgan",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Chris Jagger",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Saba Khan",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Pamela Hackney",
+        "author_inst": "Research Innovation, Manchester University NHS Foundation Trust"
+      },
+      {
+        "author_name": "Lara Smith",
+        "author_inst": "Research Innovation, Manchester University NHS Foundation Trust"
+      },
+      {
+        "author_name": "Madhvi Menon",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Joanne Konkel",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Halima A Shuwa",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Miriam Franklin",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Verena Kaestele",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Sarah Harbach",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Seema Brij",
+        "author_inst": "Department of Respiratory Medicine, Manchester Royal Infirmary, Manchester University NHS Foundation Trust"
+      },
+      {
+        "author_name": "Andrew Ustianowski",
+        "author_inst": "Regional Infectious Diseases Unit, North Manchester General Hospital, Manchester"
+      },
+      {
+        "author_name": "Alison Uriel",
+        "author_inst": "Regional Infectious Diseases Unit, North Manchester General Hospital, Manchester"
+      },
+      {
+        "author_name": "Gabriella Lindergard",
+        "author_inst": "Regional Infectious Diseases Unit, North Manchester General Hospital, Manchester"
+      },
+      {
+        "author_name": "Nawar Diar Bakerly",
+        "author_inst": "Department of Respiratory Medicine, Salford Royal NHS Foundation Trust, Manchester"
+      },
+      {
+        "author_name": "Paul Dark",
+        "author_inst": "Division of Infection, Immunity and Respiratory Medicine, NIHR Manchester Biomedical Research Centre, University of Manchester, Education and Research Centre, W"
+      },
+      {
+        "author_name": "Alexander Mathioudakis",
+        "author_inst": "Division of Infection, Immunity and Respiratory Medicine, NIHR Manchester Biomedical Research Centre, University of Manchester, Education and Research Centre, W"
+      },
+      {
+        "author_name": "Kathryn Gray",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Graham Lord",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Timothy Felton",
+        "author_inst": "Division of Infection, Immunity and Respiratory Medicine, Manchester NIHR BRC, Education and Research Centre, Wythenshawe Hospital, Manchester"
+      },
+      {
+        "author_name": "Chris Brightling",
+        "author_inst": "Department of Respiratory Sciences, Leicester NIHR BRC, University of Leicester"
+      },
+      {
+        "author_name": "Ling-Pei Ho",
+        "author_inst": "MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford"
+      },
+      {
+        "author_name": "- NIHR Respiratory TRC",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "- CIRCO",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "Karen Piper Hanley",
+        "author_inst": "Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science "
+      },
+      {
+        "author_name": "Angela Simpson",
+        "author_inst": "Division of Infection, Immunity and Respiratory Medicine, Manchester NIHR BRC, Education and Research Centre, Wythenshawe Hospital, Manchester"
       },
       {
-        "author_name": "Suri Isnaini",
-        "author_inst": "Pharmacy Faculty, Universitas 17 Agustus 1945 Jakarta"
+        "author_name": "John R Grainger",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Tracy Hussell",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
+      },
+      {
+        "author_name": "Elizabeth R Mann",
+        "author_inst": "Lydia Becker Institute of Immunology and Inflammation, University of Manchester"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1088143,25 +1090975,29 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.14.20090985",
-    "rel_title": "An attempt to optimize human resources allocation based on spatial diversity of COVID-19 cases in Poland",
+    "rel_doi": "10.1101/2020.10.13.20211284",
+    "rel_title": "Stay-at-home policy: is it a case of exception fallacy? An internet-based ecological study",
     "rel_date": "2020-10-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.14.20090985",
-    "rel_abs": "Our task is to examine the relationship between the SARS-CoV-2 arrival and the number of confirmed COVID-19 cases in the first wave (period from March 4 to May 22, 2020 (unofficial data)), and socio-economic variables at the powiat (county) level (NUTS-4) using simple statistical techniques such as data visualization, correlation analysis, spatial clustering and multiple linear regression. We showed that immigration and the logarithm of general mobility is the best predictor of SARS-CoV-2 arrival times, while emigration, industrialization and air quality explain the most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20211284",
+    "rel_abs": "BackgroundCountries with strict lockdown had a spike on the number of deaths. A recent mathematical model has suggested that staying at home did not play a dominant role in reducing COVID-19 transmission. Comparison between number of deaths and social mobility is difficult due to the non-stationary nature of the COVID-19 data.\n\nObjectiveTo propose a novel approach to assess the association between staying at home values and the reduction/increase in the number of deaths due to COVID-19 in several regions around the world.\n\nMethodsIn this ecological study, data from www.google.com/covid19/mobility/, ourworldindata.org and covid.saude.gov.br were combined. Countries with >100 deaths and with a Healthcare Access and Quality Index of [&ge;]67 were included. Data were preprocessed and analyzed using the difference between number of deaths/million between 2 regions and the difference between the percentage of staying at home. Analysis was performed using linear regression and residual analysis\n\nResultsAfter preprocessing the data, 87 regions around the world were included, yielding 3,741 pairwise comparisons for linear regression analysis. Only 63 (1.6%) comparisons were significant.\n\nDiscussionWith our results, we were not able to explain if COVID-19 mortality is reduced by staying as home in [~]98% of the comparisons after epidemiological weeks 9 to 34.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Andrzej Jarynowski",
-        "author_inst": "Institute for Interdisciplinary Research"
+        "author_name": "Ricardo F Savaris",
+        "author_inst": "Universidade Federal do Rio Grande do Sul"
       },
       {
-        "author_name": "Monika Wojta-Kempa",
-        "author_inst": "Wroclaw Medical Universtity"
+        "author_name": "Guilherme Pumi",
+        "author_inst": "Universidade Federal do Rio Grande do Sul"
+      },
+      {
+        "author_name": "Jovani Dalzochio",
+        "author_inst": "University of Vale do Rio dos Sinos (UNISINOS)"
       },
       {
-        "author_name": "Lukasz Krzowski",
-        "author_inst": "Military University of Technology in Warsaw"
+        "author_name": "Rafael Kunst",
+        "author_inst": "University of Vale do Rio dos Sinos (UNISINOS)"
       }
     ],
     "version": "1",
@@ -1089673,21 +1092509,29 @@
     "category": "emergency medicine"
   },
   {
-    "rel_doi": "10.1101/2020.10.11.20211045",
-    "rel_title": "Understanding the Los Angeles County Coronavirus Epidemic: The Critical Role of Intrahousehold Transmission",
+    "rel_doi": "10.1101/2020.10.12.20211094",
+    "rel_title": "Prioritisation of population groups with the most interactions for COVID-19 vaccination can substantially reduce total fatalities",
     "rel_date": "2020-10-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.11.20211045",
-    "rel_abs": "We tracked the course of the COVID-19 epidemic among the approximately 300 communities comprising Los Angeles County. The epidemic, we found, had three distinct phases. During Phase I, from early March through about April 4, initial seeding of infection in relatively affluent areas was followed by radial geographic extension to adjoining communities. During Phase II, lasting until about July 11, COVID-19 cases continued to rise at a slower rate, and became increasingly concentrated in four geographic foci of infection across the county. Those communities with larger reductions in social mobility during April - as measured by the proportion of smartphones staying at home and number of smartphones visiting a gym - reported fewer COVID-19 cases in May. During Phase III, COVID-19 incidence only gradually declined, remaining as high as the incidence seen at the end of Phase I. Across communities, the prevalence of households at high risk for intergenerational transmission was strongly correlated with the persistence of continued COVID-19 propagation. This association was even stronger in those communities with a higher rate of gym attendance in Phase II. The map of the prevalence of at-risk households in Los Angeles County coincided strikingly with the map of cumulative COVID-19 incidence. These findings, taken together, support the critical role of household structure in the persistent propagation of COVID-19 infections in Los Angeles County. Public health policy needs to be reoriented from a focus on protecting the individual to a focus on protecting the household.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211094",
+    "rel_abs": "Background: The unprecedented rapid development of vaccines against the SARS-CoV-2 virus creates in itself a new challenge for governments and health authorities: the effective vaccination of large numbers of people in a short time and, possibly, with shortage of vaccine doses. To whom vaccinate first and in what sequence, if any at all, to avoid the most fatalities remains an open question. Methods: A compartmental model considering age-related groups was developed to evaluate and compare vaccine distribution strategies in terms of the total avoidable fatalities. Population groups are established based on relevant differences in mortality (due to e.g. their age) and risk-related traits (such as their behaviour and number of daily person-to-person interactions). Vaccination distribution strategies were evaluated for different vaccine effectiveness levels, population coverage and vaccination rate using data mainly from Spain. Findings: Our results show that, if children could also be included in the vaccination, a rollout by priority to groups with the highest number of daily person-to-person interactions can achieve large reductions in total fatalities. This is due to the importance of the avoided subsequent infections inflicted on the rest of the population by highly interactive individuals. If children are excluded from the vaccination, the differences between priority strategies become smaller and appear highly depending on rollout rate, coverage and the levels of self-protection and awareness exercised by the population. Interpretation: These results are in possible contradiction with several published plans for COVID-19 vaccination and highlight the importance of conducting an open comprehensive and thorough analysis of this problem leaving behind possible preconceptions.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jeffrey E Harris",
-        "author_inst": "Massachusetts Institute of Technology"
+        "author_name": "Jorge Rodriguez",
+        "author_inst": "Khalifa University"
+      },
+      {
+        "author_name": "Mauricio Paton",
+        "author_inst": "Khalifa University"
+      },
+      {
+        "author_name": "Juan M Acuna",
+        "author_inst": "Khalifa University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1091279,31 +1094123,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.12.20211557",
-    "rel_title": "Nonspecific blood tests as proxies for COVID-19 hospitalization: are there plausible associations after excluding noisy predictors?",
+    "rel_doi": "10.1101/2020.10.13.20212118",
+    "rel_title": "Does autism protect against COVID quarantine effects?",
     "rel_date": "2020-10-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211557",
-    "rel_abs": "This study applied causal criteria in directed acyclic graphs for handling covariates in associations for prognosis of severe COVID-19 (Corona virus disease 19) cases. To identify nonspecific blood tests and risk factors as predictors of hospitalization due to COVID-19, one has to exclude noisy predictors by comparing the concordance statistics (AUC) for positive and negative cases of SARS-CoV-2 (acute respiratory syndrome coronavirus 2). Predictors with significant AUC at negative stratum should be either controlled for their confounders or eliminated (when confounders are unavailable). Models were classified according to the difference of AUC between strata. The framework was applied to an open database with 5644 patients from Hospital Israelita Albert Einstein in Brazil with SARS-CoV-2 RT-PCR (Reverse Transcription - Polymerase Chain Reaction) exam. C-reactive Protein (CRP) was a noisy predictor: hospitalization could have happen due to causes other than COVID-19 even when SARS-CoV-2 RT-PCR is positive and CRP is reactive, as most cases are asymptomatic to mild. Candidates of characteristic response from moderate to severe inflammation of COVID-19 were: combinations of eosinophils, monocytes and neutrophils, with age as risk factor; and creatinine, as risk factor, sharpens the odds ratio of the model with monocytes, neutrophils, and age.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20212118",
+    "rel_abs": "IntroductionCOVID-19 outbreak has imposed an eight-week confinement in France. During this period, children and their families were exposed to a full-time home life. The aim of this study was to assess the emotional experience and tolerance of children with autism spectrum disorder (ASD) in this particular context.\n\nMethodA clinical survey was proposed to parents and rated by professionals once a week during the quarantine period in France. 95 autistic children followed by the child and adolescent psychiatry department of Tours university hospital were assessed from the 18th of March to the 8th of May. The following clinical points were investigated: child anxiety, family anxiety, behavior problems, impact on sleep, impact on appetite, impact on school work, family tension, confinement intolerance, difficulties to follow a schedule, isolation behavior.\n\nResultsDespite minor changes in family anxiety and school work, no difference was highlighted between clinical scores collected at the beginning and at the end of this period. ASD children with or without intellectual disability had non-significant clinical changes during quarantine. This evolution was also independent of the accommodation type (house or apartment) and the parental status (relationship, separated or isolated).\n\nConclusionThe sameness dimension in autism and parents adaptation may be involved in this clinical stability during COVID confinement. Moreover, specialized tools and support provided by professionals could have participated to these outcomes and must be regularly promoted in order to help families in this still difficult period.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Gerson Ishikawa",
-        "author_inst": "Universidade Tecnologica Federal do Parana"
+        "author_name": "Marco Guidotti",
+        "author_inst": "EXcellence Center in Autism and neurodevelopmental disorders - Tours"
       },
       {
-        "author_name": "Graziela Argenti",
-        "author_inst": "Universidade Estadual de Ponta Grossa"
+        "author_name": "Adrien Gateau",
+        "author_inst": "EXcellence Center in Autism and neurodevelopmental disorders - Tours"
       },
       {
-        "author_name": "Cristina Berger Fadel",
-        "author_inst": "Universidade Estadual de Ponta Grossa"
+        "author_name": "Joelle Malvy",
+        "author_inst": "EXcellence Center in Autism and neurodevelopmental disorders - Tours"
+      },
+      {
+        "author_name": "Frederique Bonnet-Brilhault",
+        "author_inst": "EXcellence Center in Autism and neurodevelopmental disorders - Tours"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.10.13.20212092",
@@ -1093005,95 +1095853,59 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.10.09.20210039",
-    "rel_title": "EVALUATION OF ELEVEN IMMUNOCHROMATOGRAPHIC ASSAYS FOR SARS-CoV-2 DETECTION: INVESTIGATING DENGUE CROSS-REACTION",
+    "rel_doi": "10.1101/2020.10.08.20209544",
+    "rel_title": "What Specimen Urologists Should Be Most Concerned About ? A Systematic Review and Meta-Analysis",
     "rel_date": "2020-10-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.09.20210039",
-    "rel_abs": "BackgroundCOVID-19 disease (Coronavirus disease 2019) caused by SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) is widespread worldwide, affecting more than 11 million people globally (July 6th, 2020). Diagnostic techniques have been studied in order to contain the pandemic. Immunochromatographic (IC) assays are feasible and low cost alternative for monitoring the spread of COVID-19 in the population.\n\nMethodsHere we evaluate the sensitivity and specificity of eleven different immunochromatographic tests in 98 serum samples from confirmed cases of COVID-19 through RT-PCR and 100 negative serum samples from blood donors collected in February 2019. Considering the endemic situation of Dengue in Brazil, we also evaluated the cross-reactivity with Dengue using 20 serum samples from patients with confirmed diagnosis for Dengue collected in early 2019 through four different tests.\n\nResultsOur results demonstrated agreement between immunochromatographic assays and RT-PCR, especially after 10 days since the onset of symptoms. The evaluation of IgG and IgM antibodies combined demonstrated a strong level of agreement (0.85) of IC assays and RT-PCR. It was observed cross-reactivity between Dengue and COVID-19 using four different IC assays for COVID-19 diagnosis. The specificity of IC assays to detected COVID-19 IgM antibodies using Dengue serum samples varied from 80% to 85%; the specificity of IgG detection was 100% and total antibody was 95%.\n\nConclusionsWe found high sensitivity, specificity and good agreement of IC assays, especially after 10 days onset of symptoms. However, we detected cross-reactivity between Dengue and COVID-19 mainly with IgM antibodies demonstrating the need for better studies about diagnostic techniques for these diseases.\n\nHighlightsO_LIImmunochromatographic assays demonstrated high sensitivity and specificity and good agreement with the gold-standard RT-PCR;\nC_LIO_LIIncrease in sensitivity and specificity of assays using samples collected after the 10th day of symptoms;\nC_LIO_LICross-reaction with Dengue serology in evaluation of IgM.\nC_LI",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.08.20209544",
+    "rel_abs": "ObjectiveInvestigating the infectivity of body fluid can be useful for preventative measures in the community and ensuring safety in the operating rooms and on the laboratory practices.\n\nMethodsWe performed a literature search of clinical trials, cohorts, and case series using PubMed/MEDLINE, Google Scholar, and Cochrane library, and downloadable database of CDC. We excluded case reports and searched all-language articles for review and repeated until the final drafting. The search protocol was registered in the PROSPERO database.\n\nResultsThirty studies with urinary sampling for viral shedding were included. A total number of 1,271 patients were enrolled initially, among which 569 patients had undergone urinary testing. Nine studies observed urinary viral shedding in urine from 41 patients. The total incidence of urinary SARS-CoV-2 shedding was 8%, compared to 21.3% and 39.5 % for blood and stool, respectively. The summarized risk ratio (RR) estimates for urine positive rates compared to the pharyngeal rate was 0.08. The pertaining RR urine compared to blood and stool positive rates were 0.20 and 0.33 respectively.\n\nConclusionsOur review concludes that not only the SARS-CoV-2 can be excreted in the urine in eight percent of patients but also its incidence may have associations with the severity of the systemic disease, ICU admission, and fatality rates. Moreover, the findings in our review suggest that a larger population size may reveal more positive urinary cases possibly by minimizing biases. However, it is important to notice that it is the naso-pharyngeal specimens, stool, and serum that show more possibilities to became positive, respectively.\n\nTake-home bullet points The urinary shedding incidence was 8%, compared to 21.3% and 39.5 % for blood and stool, respectively.\nUrinary shedding may have associations with the severity of the systemic disease, ICU admission, and fatality rates.\nRepeat urinary testing is warranted throughout the disease phases, especially in clinically suspected cases with an initially negative results.\nTechnical errors in handling samples, as well as different rRT-PCR methods can be responsible for diversity found in results, in part.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Beatriz Araujo Oliveira",
-        "author_inst": "Instituto de Medicina Tropical"
-      },
-      {
-        "author_name": "Lea Campos de Oliveira",
-        "author_inst": "Instituto de Medicina Tropical"
-      },
-      {
-        "author_name": "Franciane Mendes de Oliveira",
-        "author_inst": "Instituto de Medicina Tropical"
-      },
-      {
-        "author_name": "Geovana Maria Pereira",
-        "author_inst": "Instituto de Medicina Tropical"
-      },
-      {
-        "author_name": "Regina Maia de Souza",
-        "author_inst": "Instituto de Medicina Tropical"
-      },
-      {
-        "author_name": "Erika Regina Manuli",
-        "author_inst": "Instituto de Medicina Tropical"
-      },
-      {
-        "author_name": "Fabricio Klerynton Marchini",
-        "author_inst": "Instituto Carlos Chagas, Fiocruz"
-      },
-      {
-        "author_name": "Evelyn Patr\u00edcia Sanchez Espinoza",
-        "author_inst": "Instituto de Medicina Tropical"
+        "author_name": "M. Reza Roshandel",
+        "author_inst": "Icahn School of Medicine, Mount Sinai Hospitals"
       },
       {
-        "author_name": "Marcelo Park",
-        "author_inst": "Hospital das Cl\u00ednicas"
+        "author_name": "Masoud Nateqi",
+        "author_inst": "Texas Tech University"
       },
       {
-        "author_name": "Leandro Taniguchi",
-        "author_inst": "Hospital das Cl\u00ednicas"
+        "author_name": "Ramin Lak",
+        "author_inst": "Pars Advanced and Minimally Invasive Medical Manners Research Center"
       },
       {
-        "author_name": "Pedro Vitale Mendes",
-        "author_inst": "Hospital das Cl\u00ednicas"
+        "author_name": "Pooya Aavani",
+        "author_inst": "Department of Biology, Emory University, Atlanta, Georgia"
       },
       {
-        "author_name": "Lucas Augusto Moyses Franco",
-        "author_inst": "Instituto de Medicina Tropical"
+        "author_name": "Reza Sari Motlagh",
+        "author_inst": "Urology Department of Medical University of Vienna"
       },
       {
-        "author_name": "Ana Catharina Nastri",
-        "author_inst": "Hospital das Cl\u00ednicas"
+        "author_name": "Tannaz Aghaei Badr",
+        "author_inst": "Icahn School of Medicine, Mount Sinai Hospitals"
       },
       {
-        "author_name": "Maura Salaroli de Oliveira",
-        "author_inst": "Hospital das Cl\u00ednicas"
+        "author_name": "John Sfakianos",
+        "author_inst": "Urology Department of Icahn School of Medicine, Mount Sinai Hospitals"
       },
       {
-        "author_name": "Jos\u00e9 Mauro Vieira Junior",
-        "author_inst": "Hospital S\u00edrio Liban\u00eas"
+        "author_name": "Steven A Kaplan",
+        "author_inst": "Urology Department of Icahn School of Medicine, Mount Sinai Hospitals"
       },
       {
-        "author_name": "Esper Georges Kallas",
-        "author_inst": "Faculdade de Medicina da Universidade de S\u00e3o Paulo"
+        "author_name": "Shahrokh Shariat",
+        "author_inst": "Urology Department of Medical University of Vienna, Austria; European Association of Urology, Research Foundation, Arnhem, Netherland"
       },
       {
-        "author_name": "Anna Sara Levin",
-        "author_inst": "Faculdade de Medicina da Universidade de S\u00e3o Paulo"
-      },
-      {
-        "author_name": "Ester Cerdeira Sabino",
-        "author_inst": "Instituto de Medicina Tropical"
-      },
-      {
-        "author_name": "Silvia Figueiredo Costa",
-        "author_inst": "Instituto de Medicina Tropical"
+        "author_name": "Ashutosh K. Tewari",
+        "author_inst": "Urology Department of Icahn School of Medicine, Mount Sinai Hospitals"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "urology"
   },
   {
     "rel_doi": "10.1101/2020.10.09.20210377",
@@ -1095166,37 +1097978,17 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.08.20204750",
-    "rel_title": "Estimating the effect of social inequalities in the mitigation of COVID-19 across communities in Santiago de Chile",
+    "rel_doi": "10.1101/2020.10.08.20209437",
+    "rel_title": "Estimating the Burden of COVID-19 Symptoms Among Participants at the 2020 USA Curling Club Nationals Tournament",
     "rel_date": "2020-10-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.08.20204750",
-    "rel_abs": "We study the spatio-temporal spread of SARS-CoV-2 in Santiago de Chile using anonymized mobile phone data from 1.4 million users, 22% of the whole population in the area, characterizing the effects of non-pharmaceutical interventions (NPIs) on the epidemic dynamics. We integrate these data into a mechanistic epidemic model calibrated on surveillance data. As of August 1st 2020, we estimate a detection rate of 102 cases per 1,000 infections (90% CI: [95 - 112 per 1,000]). We show that the introduction of a full lockdown on May 15th, 2020, while causing a modest additional decrease in mobility and contacts with respect to previous NPIs, was decisive in bringing the epidemic under control, highlighting the importance of a timely governmental response to COVID-19 outbreaks. We find that the impact of NPIs on individuals mobility correlates with the Human Development Index of comunas in the city. Indeed, more developed and wealthier areas became more isolated after government interventions and experienced a significantly lower burden of the pandemic. The hetero-geneity of COVID-19 impact raises important issues in the implementation of NPIs and highlights the challenges that communities affected by systemic health and social inequalities face adapting their behaviors during an epidemic.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.08.20209437",
+    "rel_abs": "The COVID-19 pandemic has been a significant cause of global morbidity and mortality, with evidence suggesting that activities involving heavier breathing, such as singing and exercise, can result in increased risk for disease transmission. The USA Curling Club Nationals is a week-long curling tournament to determine the mens and womens club-level champions. The 2020 tournament took place March 7-14 at the Potomac Curling Club in Laurel, MD, and featured teams from across the United States. Preventative measures, such as increased cleaning and disinfection of surfaces, single use and disposable food containers, and canceling traditional event banquets were implemented. Despite these measures, players, coaches, officials, volunteers, and spectators contracted the virus as a result of participation in the event. We surveyed participants to assess total positivity, potential days of transmission, and the burden of symptoms experienced among the participants. We found that 55.6% of all participants reported experiencing symptoms consistent with COVID-19, with nearly all experiencing more than one symptom. Although most participants symptoms resolved quickly, 9.6% of all participants experienced symptoms for at least one month and 12.6% of all participants reported taking at least 30 days before they felt they had returned to normal. As a result of this study, we believe curling tournaments have the potential to be high-risk events for the transmission of COVID-19. Further infection prevention measures that were not yet publicly implemented at the time of this tournament may be an effective method of lowering transmission risk, although further research is required.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Nicol\u00f2 Gozzi",
-        "author_inst": "Networks and Urban Systems Centre, University of Greenwich, London, UK"
-      },
-      {
-        "author_name": "Michele Tizzoni",
-        "author_inst": "ISI Foundation, Turin, Italy"
-      },
-      {
-        "author_name": "Matteo Chinazzi",
-        "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA"
-      },
-      {
-        "author_name": "Leo Ferres",
-        "author_inst": "Data Science Institute, Universidad del Desarrollo, Santiago, Chile"
-      },
-      {
-        "author_name": "Alessandro Vespignani",
-        "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA"
-      },
-      {
-        "author_name": "Nicola Perra",
-        "author_inst": "Networks and Urban Systems Centre, University of Greenwich, London, UK"
+        "author_name": "Paul M Luethy",
+        "author_inst": "University of Maryland School of Medicine"
       }
     ],
     "version": "1",
@@ -1096799,27 +1099591,31 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.10.20203034",
-    "rel_title": "Clarifying predictions for COVID-19 from testing data: the example of New-York State",
+    "rel_doi": "10.1101/2020.10.07.20208744",
+    "rel_title": "One size fits all?: Modeling face-mask fit on population-based faces",
     "rel_date": "2020-10-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.10.20203034",
-    "rel_abs": "In this article, we use testing data as an input of a new epidemic model. We get nice a concordance between the best fit the model to the reported cases data for New-York state. We also get a good concordance of the testing dynamic and the epidemics dynamic in the cumulative cases. Finally, we can investigate the effect of multiplying the number of tests by 2, 5, 10, and 100 to investigate the consequences on the reduction of the number of reported cases.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208744",
+    "rel_abs": "The use of face masks by the general population during viral outbreaks such as the COVID-19 pandemic, although at times controversial, has been effective in slowing down the spread of the virus. The fit of simple cloth masks on the face as well as the resulting perimeter leakage and face mask efficacy are expected to be highly dependent on the type of mask and facial topology. However, this effect has to date, not been examined and quantified. Here, we study the leakage of a rectangular cloth mask on a large virtual population of subjects with diverse facial features, using computational mechanics modeling. The effect of weight, age, gender, and height on the leakage is studied. The Centers for Disease Control and Prevention (CDC) recommended mask size was used as a basis for comparison and was found not to be the most effective design for all subjects. Thin, feminine, and young faces benefit from mask sizes smaller than that recommended by the CDC. The results show that side-edge tuck-in of the masks could lead to a larger localized gap opening in many face categories, and is therefore not recommended for all. The perimeter leakage from the face mask worn by thin/feminine faces is mostly from the leakage area along the bottom edge of the mask and therefore, a tuck-in of the bottom edge of the mask or a mask smaller than the CDC recommended mask size are proposed as a more effective design. The leakage from the top edge of the mask is determined to be largely unaffected by mask size and tuck-in ratio, meaning that other mechanical alterations such as a nose wire strip are necessary to reduce the leakage at this site.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Pierre Griette",
-        "author_inst": "University of Bordeaux"
+        "author_name": "Tomas Solano",
+        "author_inst": "Florida State University"
       },
       {
-        "author_name": "Pierre Magal",
-        "author_inst": "University of Bordeaux"
+        "author_name": "Rajat Mittal",
+        "author_inst": "Johns Hopkins University"
+      },
+      {
+        "author_name": "Kourosh Shoele",
+        "author_inst": "Florida State University"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.10.07.20208801",
@@ -1098541,35 +1101337,71 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.10.20210328",
-    "rel_title": "SARS-CoV-2 infections in Italian schools: preliminary findings after one month of school opening during the second wave of the pandemic",
+    "rel_doi": "10.1101/2020.10.07.20208389",
+    "rel_title": "A Comparative COVID 19 Characterizations and Clinical Course Analysis between ICU and Non ICU Settings",
     "rel_date": "2020-10-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.10.20210328",
-    "rel_abs": "IntroductionThe impact of school opening on the SARS-CoV-2 pandemic is still unknown. This study aims to provide preliminary information about the number of SARS-CoV-2 cases among students attending Italian schools.\n\nMethodsData are extracted and analysed from an open access, online dataset that monitor, on a daily basis, media news about SARS-CoV-2 infections of students attending Italian schools\n\nResultsAs of 5 October 2020, a total of 1350 cases of SARS-CoV-2 infections have been registered in the Italian territory schools (involving 1059 students, 145 teachers and 146 other school members), for a total of 1212 out of 65104 (1.8%) Italian schools involved. National schools reported only 1 case of SARS-CoV-2 infection in more than 90% of cases, and only in one high school a cluster of more than 10 cases have been described (P 0.015). The detection of one or more SARS-CoV-2 infections leaded to the closure of 192 (14.2%) entire schools, more frequently nursery/kindergartens (P<0.0005).\n\nDiscussionOur preliminary data support low transmission of SARS-CoV-2 within schools, at least among younger students. However, entire schools are frequently closed in the fear of larger outbreaks. Continuous monitoring of school settings, hopefully through daily updated open access datasets, are needed to better understand the impact of schools on the pandemic, and provide guidelines that better consider different risks within different age groups.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208389",
+    "rel_abs": "ObjectiveWith COVID-19 pandemic severely affecting India and Ahmedabad city being one accounting for half COVID cases, objective was to determine disease course and severity of in patients at a COVID care hospital.\n\nDesignA Clinical trial registry of India registered observational study (CTRI/2020/05/025247).\n\nSettingCertified COVID hospital located in Ahmedabad, Gujarat, India.\n\nParticipants549 COVID positive patients hospitalized between 15 th May to 10 th August, 2020 and treated in ICU and non ICU settings.\n\nMain Outcome MeasureComparative analysis of demographic, clinical characteristics, investigations, treatment, complications and outcome of COVID patients in ICU and non ICU settings.\n\nResultsOf the 549 hospitalized COVID positive patients, 159 were admitted in ICU during disease course while 390 had ward admissions. Overall median age was 52 (1-86) years. The ICU group was older (>65years), with associated comorbidities like hypertension and diabetes (p<0.001); higher proportion of males (79.25%); with dyspnea as a major clinical characteristic and consolidation in lungs as a major radiological finding as compared to ward patients. C - reactive protein, D-Dimer and Ferritin were higher in ICU patients. Overall 50% females depicted elevated Ferritin levels. Steriods(92.45%)and tocilizumab (69.18%) were more frequently used for ICU patients. Remdesivir was prescribed to both ICU and non ICU patients. Favirapir was also a line of treatment for 25% of ICU patients. Convalescent plasma therapy was given to 7 ICU patients. Complications like acute kidney injury (13.84%), shock (10.69 %), sepsis and encephalopathy were observed in ICU patients. Overall mortality rate was 5.47 % with higher mortality among males in comparison to females (p<0.0001).\n\nConclusionAbout 29% of overall patients required ICU admission that was commonly elderly males. Chances of ICU admission were higher with baselines comorbidities (1.5 times) and dyspnea (3.4 times) respectively. A multi-specialty COVID care team and updated treatment protocols improves outcomes.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Danilo Buonsenso",
-        "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy"
+        "author_name": "Amit Patel",
+        "author_inst": "Care Institute of Medical Sciences"
       },
       {
-        "author_name": "Cristina De Rose",
-        "author_inst": "Fondazione Universitaria Policlinico Gemelli, IRCSS, Rome, Italy"
+        "author_name": "Parloop Bhatt",
+        "author_inst": "Care Institute of Medical Sciences"
       },
       {
-        "author_name": "Rosanna Moroni",
-        "author_inst": "Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy"
+        "author_name": "Surabhi Madan",
+        "author_inst": "Care Institute of Medical Sciences"
       },
       {
-        "author_name": "Piero Valentini",
-        "author_inst": "Fondazione Universitaria Policlinico A. Gemelli, IRCSS, Rome, Italy"
+        "author_name": "Nitesh Shah",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Vipul Thakkar",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Bhagyesh Shah",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Rashmi Chovatia",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Hardik Shah",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Minesh Patel",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Pradip Dabhi",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Aditi Nanavati",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Milan Chag",
+        "author_inst": "Care Institute of Medical Sciences"
+      },
+      {
+        "author_name": "Keyur Parikh",
+        "author_inst": "Care Institute of Medical Sciences"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pediatrics"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.10.08.20193623",
@@ -1100323,75 +1103155,27 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.10.09.20209965",
-    "rel_title": "Pulmonary Embolism in Patients with COVID-19: A Systematic review and Meta-analysis",
+    "rel_doi": "10.1101/2020.10.07.20207845",
+    "rel_title": "Isolation of infected people and their contacts is likely to be effective against many short-term epidemics",
     "rel_date": "2020-10-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.09.20209965",
-    "rel_abs": "BackgroundThere is an increasing evidence that COVID-19 could be complicated by coagulopathy which may lead to death; especially in severe cases. Hence, this study aimed to build concrete evidence regarding the incidence and mortality of pulmonary embolism (PE) in patients with COVID-19.\n\nMethodsWe performed a systematic search for trusted databases/search engines including PubMed, Scopus, Cochrane library and Web of Science. After screening, the relevant data were extracted and the incidences and mortality rates from the different included studies were pooled for meta-analysis.\n\nResultsTwenty studies were finally included in our study consisting of 1896 patients. The results of the meta-analysis for the all included studies showed that the incidence of PE in patients with COVID-19 was 17.6% with the 95% confidence interval (CI) of 12.7 to 22.5%. There was significant heterogeneity (I2{square}={square}91.17%). Additionally, the results of meta-analysis including 8 studies showed that the mortality in patients with both PE and COVID-19 was 43.1% with the 95% confidence interval (CI) of 19 to 67.1%. There was significant heterogeneity (I2{square}={square}86.96%).\n\nConclusionPE was highly frequent in patients with COVID-19. The mortality in patients with both COVID-19 and PE was remarkable representing almost half of the patients. Appropriate prophylaxis and management are vital for better outcomes.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20207845",
+    "rel_abs": "BackgroundIsolation of infected people and their contacts may be an effective way to control outbreaks of infectious disease, such as influenza and SARS-CoV-2. Models can provide insights into the efficacy of contact tracing, coupled with isolating or quarantining at risk people.\n\nMethodsWe developed an agent-based model and simulated 15, 000 short term illnesses, with varying characteristics. For each illness we ran ten simulations on the following scenarios: (1) No tracing or isolation (None), (2) isolation of agents who have tested positive (Isolation), (3) scenario 2 coupled with minimal contact tracing and quarantine of contacts (Minimum), (4) scenario 3 with more effective contact tracing (Moderate), and (5) perfect isolation of agents who test positive and perfect tracing and quarantine of all their contacts (Maximum).\n\nResultsThe median total infections of the Isolation, Minimum, Moderate and Maximum scenarios were 80%, 40%, 17% and 4% of the no intervention scenario respectively.\n\nConclusionsIsolation of infected patients and quarantine of their contacts, even if moderately well implemented, is likely to substantially reduce the number of infections in an outbreak. Randomized controlled trials to confirm these results in the real world and to analyse the cost effectiveness of contact tracing and isolation during coronavirus and influenza outbreaks are warranted.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Omar Hamam",
-        "author_inst": "Alexandria Faculty of Medicine"
-      },
-      {
-        "author_name": "Ahmed Goda",
-        "author_inst": "Faculty of Medicine, October 6th University, Cairo, 12585 Egypt"
-      },
-      {
-        "author_name": "Radwa Awad",
-        "author_inst": "Faculty of Medicine, Benha University, Benha, 13518 Egypt"
-      },
-      {
-        "author_name": "Amr Ussama",
-        "author_inst": "Faculty of Medicine, Al-azhar University, Cairo, 11651 Egypt"
-      },
-      {
-        "author_name": "Moustafa Eldalal",
-        "author_inst": "Faculty of Medicine, Alexandria University, Alexandria21131, Egypt"
-      },
-      {
-        "author_name": "Ahmed Fayez",
-        "author_inst": "Faculty of Medicine, October 6th University, Cairo, 12585 Egypt"
-      },
-      {
-        "author_name": "Karim Elyamany",
-        "author_inst": "Faculty of Medicine, Alexandria University, Alexandria21131, Egypt"
-      },
-      {
-        "author_name": "Renu Bhandari",
-        "author_inst": "Department of Internal Medicine, Manipal College of Medical Sciences, Kaski, 33700 Nepal."
-      },
-      {
-        "author_name": "Waleed Ikram",
-        "author_inst": "Lahore Medical and Dental College, Lahore, 30022 Pakistan"
-      },
-      {
-        "author_name": "Abdelrhman Elbaz",
-        "author_inst": "Bascom Palmer Eye Institute, Miami, FL 33136 United States of America"
-      },
-      {
-        "author_name": "Smarika Baral",
-        "author_inst": "Department of Internal Medicine, Nepalgunj Medical College, Banke, 21900 Nepal."
-      },
-      {
-        "author_name": "Yomna Elbandrawy",
-        "author_inst": "Faculty of Medicine, Tanta University, Tanta, 31951 Egypt"
-      },
-      {
-        "author_name": "Alexander Egbe",
-        "author_inst": "Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, 55905 United States of America."
+        "author_name": "Nathan Geffen",
+        "author_inst": "University of Cape Town"
       },
       {
-        "author_name": "Iraida Sharina",
-        "author_inst": "Division of Cardiology, Department of Internal Medicine, McGovern Medical School, The University of Texas Health Science Center Houston, Houston, TX 77225, Unit"
+        "author_name": "Marcus O Low",
+        "author_inst": "University of Cape Town"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "intensive care and critical care medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.10.07.20207795",
@@ -1101932,17 +1104716,33 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.06.20207993",
-    "rel_title": "Sars-Cov-2 in Argentina: Following Virus Spreading using Granger Causality",
+    "rel_doi": "10.1101/2020.10.06.20208009",
+    "rel_title": "Misinterpretation of viral load in COVID-19.",
     "rel_date": "2020-10-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20207993",
-    "rel_abs": "There is a debate in Argentina on how COVID-19 outbreak in one district ends up infecting its neighbor districts. This contribution aims to use tools of time series analysis for understanding processes of contagious through regions. I use VAR and Granger causality for testing neighbor spreading via sequential rate of contagion. Results show that in the case of Argentina, contagion began in the capital city of Buenos Aires and then spread to its hinterland via specific districts. Once interior districts were infected a positive feedback dynamics emerge creating regions of high reproducibility of the virus where interventions may be focus in the very near future. This specific use of time series analysis may provide a tool for tracing infectiousness along regions that may help to anticipate infection and then for intervening for reducing the problems derived by the disease.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20208009",
+    "rel_abs": "Knowledge of viral load is essential for formulating strategies for antiviral treatment, vaccination, and epidemiological control of COVID-19. Moreover, patients identification with high viral load could also be useful to understand risk factors such as age, comorbidities, severity of symptoms and hypoxia to decide the need for hospitalization. Several studies are evaluating the importance of analyzing viral load in different types of samples, clinical outcomes and viral transmission pathways. However, in a great number of emerging studies cycle threshold (Ct) values by itself is often used as a viral load indicator, which may be a mistake. In this study, we compared tracheal aspirate with nasopharyngeal samples obtained from critically ill COVID-19 patients and demonstrate how the raw Ct could lead to misinterpretation of results. Further, we analyzed nasopharyngeal swabs positive samples and propose a method to reduce evaluation error that could occur from using raw Ct. Based on these findings, we show the impact that normalization of Ct values has on interpretation of viral load data from different biological samples from patients with COVID-19, transmission and lastly in relations with clinical outcomes.\n\nImportanceIn a pandemic, prevention of disease transmission is key. Reliable data for profiles of viral load are needed and important to guide antiviral treatment, infection control and vaccination. The differential expression of SARS-CoV-2 viral RNA among patient groups is a current topic of interest and viral load has been associated with a diversity of outcomes. However, in a great number of emerging studies cycle threshold (Ct) values by itself is often used as a viral load indicator, which may be a mistake. In this study, we compared tracheal aspirate with nasopharyngeal samples obtained from critically ill COVID-19 patients and demonstrate how the raw Ct could lead to misinterpretation of results. Based on these findings, we show the impact that normalization of Ct values has on interpretation of viral load data from different biological samples from patients with COVID-19, transmission and lastly in relations with clinical outcomes.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Juan M.C. Larrosa",
-        "author_inst": "Universidad Nacional del Sur"
+        "author_name": "Renan Lyra Miranda",
+        "author_inst": "Neuropathology and Molecular Genetics Laboratory, Instituto Estadual do C\u00e9rebro Paulo Niemeyer"
+      },
+      {
+        "author_name": "Alexandro Guterres",
+        "author_inst": "Instituto Estadual do C\u00e9rebro Paulo Niemeyer"
+      },
+      {
+        "author_name": "Carlos Henrique de Azeredo Lima",
+        "author_inst": "Neuropathology and Molecular Genetics Laboratory, Instituto Estadual do C\u00e9rebro Paulo Niemeyer"
+      },
+      {
+        "author_name": "Paulo Niemeyer Filho",
+        "author_inst": "Instituto Estadual do C\u00e9rebro Paulo Niemeyer"
+      },
+      {
+        "author_name": "M\u00f4nica Roberto Gadelha",
+        "author_inst": "Neuropathology and Molecular Genetics Laboratory, Instituto Estadual do C\u00e9rebro Paulo Niemeyer"
       }
     ],
     "version": "1",
@@ -1103738,67 +1106538,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.03.20205328",
-    "rel_title": "The Impact of COVID-19 on the Management of Heart Failure -A United Kingdom Patient Questionnaire Study",
+    "rel_doi": "10.1101/2020.10.04.20206318",
+    "rel_title": "The relationship between neighborhood poverty and COVID-19 mortality within racial/ethnic groups (Cook County, Illinois)",
     "rel_date": "2020-10-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.03.20205328",
-    "rel_abs": "AimThe coronavirus disease 2019 (COVID-19) pandemic has created significant challenges to healthcare globally, necessitating rapid restructuring of service provision. This questionnaire survey was conducted amongst adult heart failure (HF) patients in the United Kingdom (UK), to understand the impact of COVID-19 upon HF services.\n\nMethods and ResultsThe survey was conducted by the Pumping Marvellous Foundation (PMF), a UK HF patient charity. \"Survey Monkey\" was used to disseminate the questionnaire in the PMFs online patient group and in 10 UK hospitals (out-patient hospital and community HF clinics). 1050 responses were collected (693/1050-66% women); 55% (579/1050) were aged over 60 years. Anxiety level was significantly higher regarding COVID19 (mean 7{+/-}2.5 on anxiety scale of 0 to 10) compared to anxiety regarding HF (6.1{+/-}2.4; p<0.001). Anxiety was higher amongst patients aged [&le;]60 years about HF (6.3{+/-}2.2 versus 5.9{+/-}2.5 in those aged >60 years; p=0.005) and COVID-19 (7.3{+/-}2.3 versus 6.7{+/-}2.6 those aged >60 years; p<0.001). 65% respondents (686/1050) reported disruption to HF appointments (cancellation or postponement) during the lockdown period. 37% reported disruption to medication prescription services and 34% reported inability to access their HF teams promptly. 32% expressed reluctance to attend hospital (25% stated they would only attend hospital if there was no alternative and 7% stated that they would not attend hospital at all).\n\nConclusionsThe COVID-19 pandemic has caused significant anxiety amongst HF patients regarding COVID-19 and HF. Cancellation or postponement of scheduled clinic appointments, investigations, procedures, prescription and monitoring services were implicated as sources of anxiety.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.04.20206318",
+    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSPrior research has identified higher rates of COVID-19 mortality among people of color (relative to non-Hispanic whites) and populations in high-poverty neighborhoods (relative to wealthier neighborhoods). It is unclear, however, whether non-Hispanic whites in high-poverty neighborhoods experience elevated mortality, or whether people of color living in wealthy areas are relatively protected. Exploring socioeconomic position in combination with race/ethnicity can lead to a more detailed understanding of the specific processes that result in COVID-19 inequities.\n\nMethods and FindingsWe used census and individual-level mortality data for the non-Hispanic white, non-Hispanic Black, and Hispanic/Latinx populations of Cook County, Illinois, USA. We excluded deaths related to nursing homes and other institutions. We calculated age and gender-adjusted mortality rates by race/ethnicity, census tract poverty quartile, and age group (0-64 and [&ge;]65 years).\n\nWithin all racial/ethnic groups, COVID-19 mortality rates were greatest in the highest-poverty quartile and lowest in the lowest-poverty quartile. The mortality rate for younger non-Hispanic whites in the highest-poverty quartile was 13.5 times that of younger non-Hispanic whites in the lowest-poverty quartile (95% CI: 8.5, 21.4). For young people in the highest-poverty quartile, the non-Hispanic white and Black mortality rates were similar. Among younger people in the lowest-poverty quartile, non-Hispanic Black and Hispanic/Latinx people had mortality rates nearly three times that of non-Hispanic whites. For the older population, the mortality rate among non-Hispanic whites in the highest-poverty quartile was less than that of lowest-poverty non-Hispanic Black and Hispanic/Latinx populations.\n\nConclusionsOur findings suggest racial/ethnic inequalities in COVID-19 mortality are partly, but not entirely, attributable to the higher average socioeconomic position of non-Hispanic whites relative to the non-Hispanic Black and Hispanic/Latinx populations. Future research on health equity in COVID-19 outcomes should collect and analyze individual-level data on the potential mechanisms driving population distributions of exposure, severe illness, and death.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Rajiv Sankaranarayanan",
-        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "Nick Hartshorne-Evans",
-        "author_inst": "The Pumping Marvellous Foundation"
-      },
-      {
-        "author_name": "Sam Redmond-Lyon",
-        "author_inst": "The Pumping Marvellous Foundation"
-      },
-      {
-        "author_name": "Jill Wilson",
-        "author_inst": "The Pumping Marvellous Foundation"
-      },
-      {
-        "author_name": "Hani Essa",
-        "author_inst": "Liverpool University Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "Alastair Gray",
-        "author_inst": "Craigavon Area Hospital"
-      },
-      {
-        "author_name": "Louise Clayton",
-        "author_inst": "University Hospitals of Leicester NHS Trust"
-      },
-      {
-        "author_name": "Carys Barton",
-        "author_inst": "Imperial College Healthcare NHS Trust"
-      },
-      {
-        "author_name": "Fozia Z Ahmed",
-        "author_inst": "Manchester University NHS Foundation Trust"
-      },
-      {
-        "author_name": "Colin Cunnington",
-        "author_inst": "Manchester University NHS Foundation Trust"
-      },
-      {
-        "author_name": "Duwarakan Satchithananda",
-        "author_inst": "University Hospital North Midlands"
+        "author_name": "Justin M Feldman",
+        "author_inst": "Harvard University"
       },
       {
-        "author_name": "Clare Murphy",
-        "author_inst": "Royal Alexandra and Vale of Leven Hospitals"
+        "author_name": "Mary T Bassett",
+        "author_inst": "Harvard University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "cardiovascular medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.10.04.20206136",
@@ -1105088,29 +1107848,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.10.05.20207100",
-    "rel_title": "Updating Herd Immunity Models for the U.S. in 2020: Implications for the COVID-19 Response",
+    "rel_doi": "10.1101/2020.10.03.20206359",
+    "rel_title": "PREDICTIONS FOR EUROPE FOR THE COVID-19 PANDEMICAFTER LOCKDOWN WAS LIFTED USING AN SIR MODEL",
     "rel_date": "2020-10-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.05.20207100",
-    "rel_abs": "ObjectivesTo understand what levels of herd immunity are required in the COVID-19 pandemic, given spatial population heterogeneity, to best inform policy and action.\n\nMethodsUsing a network of counties in the United States connected by transit data we considered a set of coupled differential equations for susceptible-infectious-removed populations. We calculated the classical herd immunity level plus a version reflecting the heterogeneity of connections in the network by running the model forward in time until the epidemic completed.\n\nResultsNecessary levels of herd immunity vary greatly from county to county. A population weighted average for the United States is 47.5% compared to a classically estimated level of 77.1%.\n\nConclusionsCommon thinking argues that the nation needs to achieve at least 60% herd immunity to emerge from the COVID-19 pandemic. Heterogeneity in contact structure and individual variation in infectivity, susceptibility, and resistance are key factors that reduce the disease-induced herd immunity levels to 34.2-47.5% in our models. Looking forward toward vaccination strategies, these results suggest we should consider not just who is vaccinated but where those vaccinations will do the most good.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.03.20206359",
+    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWI analyze a simplified SIR model developed from a paper written by Gyan Bhanot and Charles de Lisi in May of 2020 to find the successes and limitations of their predictions. In particular, I study the predicted cases and deaths fitted to data from March and its potential application to data in September. The data is observed to fit the model as predicted until around 150 days after December 31, 2019, after which many countries lift their lockdowns and begin to reopen. A plateau in cases followed by an increase approximately 1.5 months after is also observed. In terms of deaths, the data fits the shape of the model, but the model mostly underestimates the death toll after around 160 days. An analysis of the residuals is provided to locate the precise date of the departure of each country from its accepted data estimates and test each data point to its predicted value using a Z-test to determine whether each observation can fit the given model. The observed behavior is matched to policy measures taken in each country to attach an explanation to these observations. I notice that an international reopening results in a sharp increase in cases, and aim to plot this new growth in cases and predict when the pandemic will end for each country.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Natalie Elizabeth Sheils",
-        "author_inst": "UnitedHealth Group"
-      },
-      {
-        "author_name": "Gregory D Lyng",
-        "author_inst": "UnitedHealth Group"
-      },
-      {
-        "author_name": "Ethan M Berke",
-        "author_inst": "UnitedHealth Group"
+        "author_name": "Jay Patwardhan",
+        "author_inst": "John P Stevens High School"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1106694,29 +1109446,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.02.20200931",
-    "rel_title": "Association of Pre-COVID-19 Lymphocytopenia with Fatality",
+    "rel_doi": "10.1101/2020.10.02.20205880",
+    "rel_title": "Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity irrespective of virus",
     "rel_date": "2020-10-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.02.20200931",
-    "rel_abs": "Lymphocytopenia during the COVID-19 has been associated with fatality. We tested whether pre-existing lymphocytopenia reported prior to any possible exposure to SARS-COV2 (from 2010 to 2019) was associated with fatality. Using all patients diagnosed on testing in a single regional laboratory, we identified 1137 subjects with PCR positive for SARS-COV2 and at least one available complete blood count from the decade prior to any possible exposure to the virus. Bivariate analysis indicated an association between pre-existing lymphocytopenia (defined as absolute lymphocyte count <0.9x109 /L) and fatality (18% versus 4%). Furthermore, a logistic regression model, accounting for both patient age and number of blood counts obtained, indicated the subjects with pre-existing lymphocytopenia were 1.4 times as likely to die. Because the absolute lymphocyte count is almost universally available and easily interpreted, this biomarker of the risk of fatality could be widely useful.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.02.20205880",
+    "rel_abs": "SARS-CoV-2 pandemic, the fourth pandemic of the decade, has underscored gaps in global pandemic preparedness and the need for generalizable tests to avert overwhelming healthcare systems worldwide, irrespective of a virus. We integrated 4,780 blood transcriptome profiles from patients infected with one of 16 viruses across 34 independent cohorts from 18 countries, and 71 scRNA-seq profiles of 264,224 immune cells across three independent cohorts. We found a myeloid cell-dominated conserved host response associated with severity. It showed increased hematopoiesis, myelopoiesis, and myeloid-derived suppressor cells with increased severity. We identified four gene modules that delineate distinct trajectories associated with mild and severe outcomes, and show the interferon response was decoupled from protective host response during severe viral infection. These modules distinguished non-severe from severe viral infection with clinically useful accuracy. Together, our findings provide insights into immune response dynamics during viral infection, and identify factors that may influence patient outcomes.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Richard Burack",
-        "author_inst": "University of Rochester"
+        "author_name": "Hong Zheng",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Philip Rock",
-        "author_inst": "University of Rochester"
+        "author_name": "Aditya M Rao",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "David Burtoon",
-        "author_inst": "University of Rochester"
+        "author_name": "Denis Dermadi",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Xueya Cai",
-        "author_inst": "University of Rochester"
+        "author_name": "Jiaying Toh",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Lara Murphy Jones",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Michele Donato",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Yiran Liu",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Yapeng Su",
+        "author_inst": "Institute for Systems Biology"
+      },
+      {
+        "author_name": "Minas Karagiannis",
+        "author_inst": "National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Theodoros Marantos",
+        "author_inst": "National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Yehudit Hasin-Brumshtein",
+        "author_inst": "Inflammatix, Inc"
+      },
+      {
+        "author_name": "Yudong D He",
+        "author_inst": "Inflammatix, Inc"
+      },
+      {
+        "author_name": "Evangelos J Giamarellos-Bourboulis",
+        "author_inst": "National and Kapodistrian University of Athens"
+      },
+      {
+        "author_name": "Jim Heath",
+        "author_inst": "Institute for Systems Biology"
+      },
+      {
+        "author_name": "Purvesh Khatri",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
@@ -1108268,55 +1111064,35 @@
     "category": "radiology and imaging"
   },
   {
-    "rel_doi": "10.1101/2020.09.30.20204537",
-    "rel_title": "SARS-CoV-2 seroprevalence and clinical features of COVID-19 in a German liver transplant recipient cohort: a prospective serosurvey study.",
+    "rel_doi": "10.1101/2020.10.01.20204255",
+    "rel_title": "COVID-19 Pandemic in University Hospital: Impact on Medical Training of Medical Interns",
     "rel_date": "2020-10-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.30.20204537",
-    "rel_abs": "In liver transplant (LT) recipients with severe COVID-19 fatal outcome has been reported in a substantial subset of patients. Whether LT recipients are at increased risk for severe COVID-19 compared to the general population is controversial. Here we report the first results of a SARS-CoV-2 serosurvey in a large LT recipient cohort.\n\nTaking into account known risk factors, LT recipients a priori represented a high-risk cohort for severe COVID-19 with 101/219 (46.1 %) presenting with more than 2 risk factors for severe COVID-19. Out of 219 LT recipients 8 (3.7%) were either tested positive for nasopharyngeal SARS-CoV-2 RNA or anti-SARS-CoV-2 serum IgG. 5/8 (62.5 %) did not show any clinical signs of infection, 3/8 (37.5%) had self-limited disease, none required hospitalization for COVID-19. 5/8 (67.5%) SARS-CoV-2 positive patients showed high utilization of the healthcare system. 2/8 (25 %) had known exposure to infected health care personal. A majority of 65.4 % often or always avoided outside family social contacts. Face masks were commonly worn by all patients.\n\nIn summary, LT recipients showed a SARS-CoV-2 seroconversion rate similar to the general population with a substantial percentage of unrecognized infections. The health care system can be the assumed source of infection in most of these cases.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.01.20204255",
+    "rel_abs": "IntroductionCoronavirus 2019 (COVID-19) has strike all nations hard since the end of year 2019, Malaysia unable to escape the fate as well. Healthcare system, financial growth, industrial development and educational programme are stunted. Inevitably, professional training and education are affected which include the medical training of medical interns.\n\nMethodsThis is a cross-sectional, pilot study to determine the impact of the pandemic on University Malaya Medical Centre (UMMC) medical interns. A survey which comprises 37-items was used. Data are analysed by Ordinal Logistic Regression Analysis.\n\nResultsMedical interns feel that they lack clinical skills (p = 0.005) and need more exposure in surgical operations (p =0.029). Some are satisfied with the introduction of triage (p = 0.024), online teaching (p = 0.005) and bedside teaching (p=0.023). Most of them think they are fit and ready to handle the pandemic (p = 0.012 and 0.025 respectively) except first year medical interns (p = 0.029). Some feel like their time are wasted (p <0.05) as they are involved in many non-clinical activities (p = 0.003).\n\nConclusionIn summary, COVID-19 has a great impact on medical training amongst medical interns. Alternative measures should be taken to minimize the interruption in training of our future leaders in medical field.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Conrad Rauber",
-        "author_inst": "Universitaetsklinikum Heidelberg"
-      },
-      {
-        "author_name": "Shilpa Tiwari-Heckler",
-        "author_inst": "Universitaetsklinikum Heidelberg"
-      },
-      {
-        "author_name": "Jan Pfeiffenberger",
-        "author_inst": "Universitaetsklinikum Heidelberg"
-      },
-      {
-        "author_name": "Arianeb Mehrabi",
-        "author_inst": "Universitaetsklinikum Heidelberg"
-      },
-      {
-        "author_name": "Frederike Lund",
-        "author_inst": "Universitaetsklinikum Heidelberg"
-      },
-      {
-        "author_name": "Philip Gath",
-        "author_inst": "Staedtisches Klinikum Ludwigshafen"
+        "author_name": "WeiHonn Lim",
+        "author_inst": "University Malaya Medical Centre"
       },
       {
-        "author_name": "Markus Mieth",
-        "author_inst": "Universitaetsklinikum Heidelberg"
+        "author_name": "Li Ying Teoh",
+        "author_inst": "University of Malaya Medical Centre"
       },
       {
-        "author_name": "Uta Merle",
-        "author_inst": "Universitaetsklinikum Heidelberg"
+        "author_name": "Kanesh Kumaran Seevalingam",
+        "author_inst": "University of Malaya Medical Centre"
       },
       {
-        "author_name": "Christian Rupp",
-        "author_inst": "Universitaetsklinikum Heidelberg"
+        "author_name": "Shanggar Kuppusamy",
+        "author_inst": "University of Malaya Medical Centre"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "transplantation"
+    "category": "medical education"
   },
   {
     "rel_doi": "10.1101/2020.10.02.20205070",
@@ -1109982,55 +1112758,103 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.10.02.323915",
-    "rel_title": "A Multiscale Coarse-grained Model of the SARS-CoV-2 Virion",
+    "rel_doi": "10.1101/2020.10.02.324145",
+    "rel_title": "SARS-CoV-2 infected cells present HLA-I peptides from canonical and out-of-frame ORFs",
     "rel_date": "2020-10-02",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.02.323915",
-    "rel_abs": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 pandemic. Computer simulations of complete viral particles can provide theoretical insights into large-scale viral processes including assembly, budding, egress, entry, and fusion. Detailed atomistic simulations, however, are constrained to shorter timescales and require billion-atom simulations for these processes. Here, we report the current status and on-going development of a largely \"bottom-up\" coarse-grained (CG) model of the SARS-CoV-2 virion. Structural data from a combination of cryo-electron microscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular models of structural SARS-CoV-2 proteins, which were then assembled into a complete virion model. We describe how CG molecular interactions can be derived from all-atom simulations, how viral behavior difficult to capture in atomistic simulations can be incorporated into the CG models, and how the CG models can be iteratively improved as new data becomes publicly available. Our initial CG model and the detailed methods presented are intended to serve as a resource for researchers working on COVID-19 who are interested in performing multiscale simulations of the SARS-CoV-2 virion.\n\nSignificance StatementThis study reports the construction of a molecular model for the SARS-CoV-2 virion and details our multiscale approach towards model refinement. The resulting model and methods can be applied to and enable the simulation of SARS-CoV-2 virions.",
-    "rel_num_authors": 9,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.02.324145",
+    "rel_abs": "T cell-mediated immunity may play a critical role in controlling and establishing protective immunity against SARS-CoV-2 infection; yet the repertoire of viral epitopes responsible for T cell response activation remains mostly unknown. Identification of viral peptides presented on class I human leukocyte antigen (HLA-I) can reveal epitopes for recognition by cytotoxic T cells and potential incorporation into vaccines. Here, we report the first HLA-I immunopeptidome of SARS-CoV-2 in two human cell lines at different times post-infection using mass spectrometry. We found HLA-I peptides derived not only from canonical ORFs, but also from internal out-of-frame ORFs in Spike and Nucleoprotein not captured by current vaccines. Proteomics analyses of infected cells revealed that SARS-CoV-2 may interfere with antigen processing and immune signaling pathways. Based on the endogenously processed and presented viral peptides that we identified, we estimate that a pool of 24 peptides would provide one or more peptides for presentation by at least one HLA allele in 99% of the human population. These biological insights and the list of naturally presented SARS-CoV-2 peptides will facilitate data-driven selection of peptides for immune monitoring and vaccine development.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Alvin Yu",
-        "author_inst": "University of Chicago"
+        "author_name": "Shira Weingarten-Gabbay",
+        "author_inst": "Broad Institute"
       },
       {
-        "author_name": "Alexander J Pak",
-        "author_inst": "University of Chicago"
+        "author_name": "Susan Klaeger",
+        "author_inst": "Broad Institute of MIT and Harvard"
       },
       {
-        "author_name": "Peng He",
-        "author_inst": "University of Chicago"
+        "author_name": "Siranush Sarkizova",
+        "author_inst": "Broad Institute of MIT and Harvard"
       },
       {
-        "author_name": "Viviana Monje-Galvan",
-        "author_inst": "University of Chicago"
+        "author_name": "Leah R Pearlman",
+        "author_inst": "Broad Institute of MIT and Harvard"
       },
       {
-        "author_name": "Lorenzo Casalino",
-        "author_inst": "University of California San Diego"
+        "author_name": "Da-Yuan Chen",
+        "author_inst": "Department of Biochemistry, Boston University School of Medicine"
       },
       {
-        "author_name": "Zied Gaieb",
-        "author_inst": "University of California, San Diego"
+        "author_name": "Matthew R Bauer",
+        "author_inst": "Broad Institute of MIT and Harvard"
       },
       {
-        "author_name": "Abigail C Dommer",
-        "author_inst": "University of California San Diego"
+        "author_name": "Hannah B Taylor",
+        "author_inst": "Broad Institute of MIT and Harvard"
       },
       {
-        "author_name": "Rommie E Amaro",
-        "author_inst": "University of California, San Diego"
+        "author_name": "Hasahn L Conway",
+        "author_inst": "Department of Biochemistry, Boston University School of Medicine"
       },
       {
-        "author_name": "Gregory A Voth",
-        "author_inst": "University of Chicago"
+        "author_name": "Christopher H Tomkins-Tinch",
+        "author_inst": "Broad Institute of MIT and Harvard"
+      },
+      {
+        "author_name": "Yaara Finkel",
+        "author_inst": "Department of Molecular Genetics, Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Aharon Nachshon",
+        "author_inst": "Department of Molecular Genetics, Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Matteo Gentili",
+        "author_inst": "Broad Institute of MIT and Harvard"
+      },
+      {
+        "author_name": "Keith D Rivera",
+        "author_inst": "Broad Institute of MIT and Harvard"
+      },
+      {
+        "author_name": "Derin B Keskin",
+        "author_inst": "Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute"
+      },
+      {
+        "author_name": "Charles M Rice",
+        "author_inst": "Laboratory of Virology and Infectious Disease, The Rockefeller University"
+      },
+      {
+        "author_name": "Karl R Clauser",
+        "author_inst": "Broad Institute of MIT and Harvard"
+      },
+      {
+        "author_name": "Nir Hacohen",
+        "author_inst": "Broad Institute of MIT and Harvard"
+      },
+      {
+        "author_name": "Steven A Carr",
+        "author_inst": "Broad Institute of MIT and Harvard"
+      },
+      {
+        "author_name": "Jennifer G Abelin",
+        "author_inst": "Broad Institute of MIT and Harvard"
+      },
+      {
+        "author_name": "Mohsan Saeed",
+        "author_inst": "Department of Biochemistry, Boston University School of Medicine"
+      },
+      {
+        "author_name": "Pardis C Sabeti",
+        "author_inst": "Broad Institute of MIT and Harvard"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "biophysics"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.10.02.324046",
@@ -1111772,29 +1114596,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.29.20202416",
-    "rel_title": "Virus evolution affected early COVID-19 spread",
+    "rel_doi": "10.1101/2020.09.30.20204644",
+    "rel_title": "Estimation of novel coronavirus (covid-19) reproduction number and case fatality rate: a systematic review and meta-analysis",
     "rel_date": "2020-09-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20202416",
-    "rel_abs": "As the SARS-Cov-2 virus spreads around the world afflicting millions of people, it has undergone divergent genetic mutations. Although most of these mutations are expected to be inconsequential, some mutations in the spike protein structure have been hypothesized to affect the critical stage at which the virus invades human cells, which could affect transmission probability and disease expression. If true, then we expect an increased growth rate of reported COVID-19 cases in regions dominated by viruses with these altered proteins. We modeled early global infection dynamics based on clade assignment along with other demographic and meteorological factors previously found to be important. Clade, but not variant D614G which has been associated with increased viral load, enhanced our ability to describe early COVID-19 growth dynamics. Including clade identity in models significantly improved predictions over earlier work based only on weather and demographic variables. In particular, higher proportions of clade 19A and 19B were negatively correlated with COVID-19 growth rate, whereas higher proportions of 20A and 20C were positively correlated with growth rate. A strong interaction between the prevalence of clade 20C and relative humidity suggests that the impact of clade identity might be more important when coupled with certain weather conditions. In particular, 20C an 20A generate the highest growth rates when coupled with low humidity. Projections based on data through April 2020 suggest that, without intervention, COVID-19 has the potential to grow more quickly in regions dominated by the 20A and 20C clades, including most of South and North America.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.30.20204644",
+    "rel_abs": "Understanding the transmission dynamics and the severity of the novel coronavirus disease 2019 (COVID-19) informs public health interventions, surveillance, and planning. Two important parameters, the basic reproduction number (R0) and case fatality rate (CFR) of COVID-19, help in this understanding process. The objective of this study was to estimate the R0 and CFR of COVID-19 and assess whether the parameters vary in different regions of the world. We carried out a systematic review to retrieve the published estimates of the R0 and the CFR in articles from international databases between 1st January and 31st August 2020. Random-effect models and Forest plots were implemented to evaluate the mean effect size of the R0 and the CFR. Furthermore, the R0 and CFR of the studies were quantified based on geographic location, the tests/thousand population, and the median population age of the countries where studies were conducted. The I2 statistic and the Cochrans Q test were applied to assess statistical heterogeneity among the selected studies. Forty-five studies involving R0 and thirty-four studies involving CFR were included. The pooled estimation of the R0 was 2.69 (95% CI: 2.40, 2.98), and that of the CFR was 2.67 (2.25, 3.13). The CFR in different regions of the world varied significantly, from 2.51 (2.12, 2.95) in Asia to 7.11 (6.38, 7.91) in Africa. We observed higher mean CFR values for the countries with lower tests (3.15 vs. 2.16) and greater median population age (3.13 vs. 2.27). However, the R0 did not vary significantly in different regions of the world. An R0 of 2.69 and CFR of 2.67 indicate the severity of the COVID-19. Although R0 and CFR may vary over time, space, and demographics, we recommend considering these figures in control and prevention measures.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Derek Corcoran",
-        "author_inst": "University of Connecticut"
+        "author_name": "Tanvir Ahammed",
+        "author_inst": "Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh"
       },
       {
-        "author_name": "Mark C Urban",
-        "author_inst": "University of Connecticut"
+        "author_name": "Aniqua Anjum",
+        "author_inst": "Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh"
       },
       {
-        "author_name": "Jill Wegrzyn",
-        "author_inst": "University of Connecticut"
+        "author_name": "Mohammad Meshbahur Rahman",
+        "author_inst": "Biomedical Research Foundation, Dhaka-1230, Bangladesh"
       },
       {
-        "author_name": "Cory Merow",
-        "author_inst": "University of Connecticut"
+        "author_name": "Najmul Haider",
+        "author_inst": "Royal Veterinary College"
+      },
+      {
+        "author_name": "Richard Kock",
+        "author_inst": "Royal Veterinary College"
+      },
+      {
+        "author_name": "Md. Jamal Uddin",
+        "author_inst": "Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh"
       }
     ],
     "version": "1",
@@ -1113546,45 +1116378,41 @@
     "category": "obstetrics and gynecology"
   },
   {
-    "rel_doi": "10.1101/2020.09.28.20200915",
-    "rel_title": "COVID-19 seroprevalence surveys and antibody decline - A note of caution on antibody decline",
+    "rel_doi": "10.1101/2020.09.27.20199737",
+    "rel_title": "High-Quality Masks Can Reduce Infections and Deaths in the US",
     "rel_date": "2020-09-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.28.20200915",
-    "rel_abs": "We analyzed 21,676 residual specimens from Ontario, Canada collected between March-August, 2020 to investigate the effect of antibody decline on SARS-CoV-2 seroprevalence estimates. Testing specimens orthogonally using the Abbott (anti-nucleocapsid) and then the Ortho (anti-spike) assays, seroprevalence estimates ranged from 0.4%-1.4%, despite ongoing disease activity. The geometric mean concentration (GMC) of antibody-positive specimens decreased over time (p=0.015), and the GMC of antibody-negative specimens increased over time (p=0.0018). The association between the two tests decreased each month (p<0.001), suggesting anti-N antibody decline. Lowering the Abbott index cut-off from 1.4 to 0.7 resulted in a 16% increase in positive specimens.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.27.20199737",
+    "rel_abs": "ObjectivesTo evaluate the effectiveness of widespread adoption of masks or face coverings to reduce community transmission of the SARS-CoV-2 virus that causes Covid-19.\n\nMethodsWe employed an agent-based stochastic network simulation model, where Covid-19 progresses across census tracts according to a variant of SEIR. We considered a mask order that was initiated 3.5 months after the first confirmed Covid-19 case. We evaluated scenarios where wearing a mask reduces transmission and susceptibility by 50% or 80%; an individual wears a mask with a probability of 0%, 20%, 40%, 60%, 80%, or 100%.\n\nResultsIf 60% of the population wears masks that are 50% effective, this decreases the cumulative infection attack rate (CAR) by 25%, the peak prevalence by 51%, and the population mortality by 25%. If 100% of people wear masks (or 60% wear masks that are 80% effective), this decreases the CAR by 38%, the peak prevalence by 67%, and the population mortality by 40%.\n\nConclusionsAfter community transmission is present, masks can significantly reduce infections.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Shelly Bolotin",
-        "author_inst": "Public Health Ontario"
-      },
-      {
-        "author_name": "Vanessa Tran",
-        "author_inst": "Public Health Ontario"
+        "author_name": "Erik Rosenstrom",
+        "author_inst": "North Carolina State University"
       },
       {
-        "author_name": "Selma Osman",
-        "author_inst": "Public Health Ontario"
+        "author_name": "Buse Oruc Aglar",
+        "author_inst": "Georgia Institute of Technology"
       },
       {
-        "author_name": "Kevin A. Brown",
-        "author_inst": "Public Health Ontario"
+        "author_name": "Nathaniel Hupert",
+        "author_inst": "Cornell University"
       },
       {
-        "author_name": "Sarah A. Buchan",
-        "author_inst": "Public Health Ontario"
+        "author_name": "Julie S. Ivy",
+        "author_inst": "North Carolina State University"
       },
       {
-        "author_name": "Eugene Joh",
-        "author_inst": "Public Health Ontario"
+        "author_name": "Pinar Keskinocak",
+        "author_inst": "Georgia Institute of Technology"
       },
       {
-        "author_name": "Shelley L. Deeks",
-        "author_inst": "Public Health Ontario"
+        "author_name": "Maria Mayorga",
+        "author_inst": "North Carolina State University"
       },
       {
-        "author_name": "Vanessa G. Allen",
-        "author_inst": "Public Health Ontario"
+        "author_name": "Julie L Swann",
+        "author_inst": "North Carolina State University"
       }
     ],
     "version": "1",
@@ -1115360,61 +1118188,97 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.09.29.317289",
-    "rel_title": "Susceptibility of midge and mosquito vectors to SARS-CoV-2 by natural route of infection",
+    "rel_doi": "10.1101/2020.09.28.317685",
+    "rel_title": "SARS-CoV-2 D614G Variant Exhibits Enhanced Replication ex vivo and Earlier Transmission in vivo",
     "rel_date": "2020-09-29",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.29.317289",
-    "rel_abs": "SARS-CoV-2 is a recently emerged, highly contagious virus and the cause of the current pandemic. It is a zoonotic virus, although its animal origin is not clear yet. Person-to-person transmission occurs by inhalation of infected droplets and aerosols, or by direct contact with contaminated fomites. Arthropods transmit numerous viral, parasitic, and bacterial diseases; however, the potential role of arthropods in SARS-CoV-2 transmission is not fully understood. Thus far, a few studies have demonstrated that SARS-CoV-2 replication is not supported in cells from certain insect species nor in certain species of mosquitoes after intrathoracic inoculation. In this study, we expanded the work of SARS-CoV-2 susceptibility to biting insects after ingesting a SARS-CoV-2infected blood meal. Species tested included Culicoides sonorensis biting midges, as well as Culex tarsalis and Culex quinquefasciatus mosquitoes, all known biological vectors for numerous RNA viruses. Arthropods were allowed to feed on SARS-CoV-2 spiked blood and at various time points post infection analyzed for the presence of viral RNA and infectious virus. Additionally, cell lines derived from C. sonorensis (W8a), Ae. aegypti (C6/36), Cx. quinquefasciatus (HSU), and Cx. tarsalis (CxTrR2) were tested for SARS-CoV-2 susceptibility. Our results indicate that none of the biting insects, nor the insect cell lines support SARS-CoV-2 replication. We conclude, that biting insect do not pose a risk for transmission of SARS-CoV-2 to humans or animals following a SARS-CoV-2 infected blood meal.",
-    "rel_num_authors": 11,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.28.317685",
+    "rel_abs": "The D614G substitution in the S protein is most prevalent SARS-CoV-2 strain circulating globally, but its effects in viral pathogenesis and transmission remain unclear. We engineered SARS-CoV-2 variants harboring the D614G substitution with or without nanoluciferase. The D614G variant replicates more efficiency in primary human proximal airway epithelial cells and is more fit than wildtype (WT) virus in competition studies. With similar morphology to the WT virion, the D614G virus is also more sensitive to SARS-CoV-2 neutralizing antibodies. Infection of human ACE2 transgenic mice and Syrian hamsters with the WT or D614G viruses produced similar titers in respiratory tissue and pulmonary disease. However, the D614G variant exhibited significantly faster droplet transmission between hamsters than the WT virus, early after infection. Our study demonstrated the SARS-CoV2 D614G substitution enhances infectivity, replication fitness, and early transmission.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Velmurugan Balaraman",
-        "author_inst": "Kansas State University"
+        "author_name": "Yixuan J Hou",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Barbara S. Drolet",
-        "author_inst": "United States Department of Agriculture, Agricultural Research Service"
+        "author_name": "Shiho Chiba",
+        "author_inst": "University of Wisconsin-Madison"
       },
       {
-        "author_name": "Natasha N Gaudreault",
-        "author_inst": "Kansas State University"
+        "author_name": "Peter Halfmann",
+        "author_inst": "University of Wisconsin-Madison"
       },
       {
-        "author_name": "William C. Wilson",
-        "author_inst": "United States Department of Agriculture, Agricultural Research Service"
+        "author_name": "Camille Ehre",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Jeana Owens",
-        "author_inst": "United States Department of Agriculture, Agricultural Research Service"
+        "author_name": "Makoto Kuroda",
+        "author_inst": "University of Wisconsin-Madison"
       },
       {
-        "author_name": "Dashzeveg Bold",
-        "author_inst": "Kansas State University"
+        "author_name": "Kenneth H Dinnon III",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Dustin A Swanson",
-        "author_inst": "United States Department of Agriculture, Agricultural Research Service"
+        "author_name": "Sarah R Leist",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Dane C Jasperson",
-        "author_inst": "United States Department of Agriculture, Agricultural Research Service"
+        "author_name": "Alexandra Sch\u00e4fer",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Leela E Noronha",
-        "author_inst": "United States Department of Agriculture, Agricultural Research Service"
+        "author_name": "Noriko Nakajima",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Juergen A Richt",
-        "author_inst": "Kansas State University"
+        "author_name": "Kenta Takahashi",
+        "author_inst": "University of North Carolina at Chapel Hill"
       },
       {
-        "author_name": "Dana Mitzel",
-        "author_inst": "United States Department of Agriculture, Agricultural Research Service"
+        "author_name": "Rhianna E Lee",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Teresa M Mascenik",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Caitlin E Edwards",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Longping V Tse",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Richard C Boucher",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Scott H Randell",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Tadaki Suzuki",
+        "author_inst": "National Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Lisa E Gralinski",
+        "author_inst": "University of North Carolina at Chapel Hill"
+      },
+      {
+        "author_name": "Yoshihiro Kawaoka",
+        "author_inst": "University of Wisconsin-Madison"
+      },
+      {
+        "author_name": "Ralph S. Baric",
+        "author_inst": "University of North Carolina at Chapel Hill"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc_nd",
     "type": "new results",
     "category": "microbiology"
   },
@@ -1117018,47 +1119882,107 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.09.27.315796",
-    "rel_title": "A Tethered Ligand Assay to Probe the SARS-CoV-2 ACE2 Interaction under Constant Force",
+    "rel_doi": "10.1101/2020.09.27.316174",
+    "rel_title": "Discovery and Development of Human SARS-CoV-2 Neutralizing Antibodies using an Unbiased Phage Display Library Approach",
     "rel_date": "2020-09-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.27.315796",
-    "rel_abs": "The current COVID-19 pandemic has a devastating global impact and is caused by the SARS-CoV-2 virus. SARS-CoV-2 attaches to human host cells through interaction of its receptor binding domain (RBD) located on the viral Spike (S) glycoprotein with angiotensin converting enzyme-2 (ACE2) on the surface of host cells. RBD binding to ACE2 is a critical first step in SARS-CoV-2 infection. Viral attachment occurs in dynamic environments where forces act on the binding partners and multivalent interactions play central roles, creating an urgent need for assays that can quantitate SARS-CoV-2 interactions with ACE2 under mechanical load and in defined geometries. Here, we introduce a tethered ligand assay that comprises the RBD and the ACE2 ectodomain joined by a flexible peptide linker. Using specific molecular handles, we tether the fusion proteins between a functionalized flow cell surface and magnetic beads in magnetic tweezers. We observe repeated interactions of RBD and ACE2 under constant loads and can fully quantify the force dependence and kinetics of the binding interaction. Our results suggest that the SARS-CoV-2 ACE2 interaction has higher mechanical stability, a larger free energy of binding, and a lower off-rate than that of SARS-CoV-1, the causative agents of the 2002-2004 SARS outbreak. In the absence of force, the SARS-CoV-2 RBD rapidly (within [&le;]1 ms) engages the ACE2 receptor if held in close proximity and remains bound to ACE2 for 400-800 s, much longer than what has been reported for other viruses engaging their cellular receptors. We anticipate that our assay will be a powerful tool investigate the roles of mutations in the RBD that might alter the infectivity of the virus and to test the modes of action of neutralizing antibodies and other agents designed to block RBD binding to ACE2 that are currently developed as potential COVID-19 therapeutics.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.27.316174",
+    "rel_abs": "SARS-CoV-2 neutralizing antibodies represent an important component of the ongoing search for effective treatment of and protection against COVID-19. We report here on the use of a naive phage display antibody library to identify a panel of fully human SARS-CoV-2 neutralizing antibodies. Following functional profiling in vitro against an early pandemic isolate as well as a recently emerged isolate bearing the D614G Spike mutation, the clinical candidate antibody, STI-1499, and the affinity-engineered variant, STI-2020, were evaluated for in vivo efficacy in the Syrian golden hamster model of COVID-19. Both antibodies demonstrated potent protection against the pathogenic effects of the disease and a dose-dependent reduction of virus load in the lungs, reaching undetectable levels following a single dose of 500 micrograms of STI-2020. These data support continued development of these antibodies as therapeutics against COVID-19 and future use of this approach to address novel emerging pandemic disease threats.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Magnus S. Bauer",
-        "author_inst": "LMU Munich"
+        "author_name": "Xia Cao",
+        "author_inst": "Sorrento Therapeutics, Inc."
       },
       {
-        "author_name": "Sophia Gruber",
-        "author_inst": "LMU Munich"
+        "author_name": "Junki Maruyama",
+        "author_inst": "University of Texas Medical Branch, Department of Pathology, Galveston National Laboratory"
       },
       {
-        "author_name": "Lukas F. Milles",
-        "author_inst": "University of Washington, Seattle"
+        "author_name": "Heyue Zhou",
+        "author_inst": "Sorrento Therapeutics, Inc."
       },
       {
-        "author_name": "Thomas Nicolaus",
-        "author_inst": "LMU Munich"
+        "author_name": "Lisa Kerwin",
+        "author_inst": "Sorrento Therapeutics, Inc."
       },
       {
-        "author_name": "Leonard C. Schendel",
-        "author_inst": "LMU Munich"
+        "author_name": "Rachel Sattler",
+        "author_inst": "University of Texas Medical Branch, Department of Pathology, Galveston National Laboratory"
       },
       {
-        "author_name": "Hermann E. Gaub",
-        "author_inst": "LMU Munich"
+        "author_name": "John T Manning",
+        "author_inst": "University of Texas Medical Branch, Department of Pathology, Galveston National Laboratory"
       },
       {
-        "author_name": "Jan Lipfert",
-        "author_inst": "LMU Munich"
+        "author_name": "Sachi Johnson",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Susan Richards",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Yan Li",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Weiqun Shen",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Benjamin Blair",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Na Du",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Kyndal Morais",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Kate Lawrence",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Lucy Lu",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Chin-I Pai",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Donghui Li",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Mark Brunswick",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Yanliang Zhang",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Henry Ji",
+        "author_inst": "Sorrento Therapeutics, Inc."
+      },
+      {
+        "author_name": "Slobodan Paessler",
+        "author_inst": "University of Texas Medical Branch, Department of Pathology, Galveston National Laboratory"
+      },
+      {
+        "author_name": "Robert D Allen",
+        "author_inst": "Sorrento Therapeutics, Inc."
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "biophysics"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.09.28.316604",
@@ -1118364,65 +1121288,21 @@
     "category": "pediatrics"
   },
   {
-    "rel_doi": "10.1101/2020.09.22.20195628",
-    "rel_title": "Public health information on COVID-19 for international travellers: Lessons learned from a rapid mixed-method evaluation in the UK containment phase",
+    "rel_doi": "10.1101/2020.09.23.20200212",
+    "rel_title": "Impact of Personal Care Habits on Post-Lockdown COVID-19 Contagion: Insights from Agent-based Simulations",
     "rel_date": "2020-09-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20195628",
-    "rel_abs": "Introduction In the containment phase of the response to the COVID-19 outbreak, Public Health England (PHE) delivered advice to travellers arriving at major UK ports. We aimed to rapidly evaluate the impact and effectiveness of these communication materials for passengers in the early stages of the pandemic. Methods In stage I (Patient and Public Involvement, PPI) we interviewed seven travellers who had returned from China in January and February 2020. We used these results to develop a questionnaire and topic guides for stage II, a cross-sectional survey and follow-up interviews with passengers arriving at London Heathrow Airport on scheduled flights from China and Singapore. The survey assessed passengers' knowledge of symptoms, actions to take and attitudes towards PHE COVID-19 public health information; interviews explored their views of official public health information and self-isolation. Results In stage II, 121 passengers participated in the survey and 15 in follow-up interviews. 83% of surveyed passengers correctly identified all three COVID-19 associated symptoms listed in PHE information at that time. Most could identify the recommended actions and found the advice understandable and trustworthy. Interviews revealed that passengers shared concerns about the lack of wider official action, and that passengers' knowledge had been acquired elsewhere as much from PHE. Respondents also noted their own agency in choosing to self-isolate, partially as a self-protective measure. Conclusion PHE COVID-19 public health information was perceived as clear and acceptable, but we found that passengers acquired knowledge from various sources and they saw the provision of information alone on arrival as an insufficient official response. Our study provides fresh insights into the importance of taking greater account of diverse information sources and of the need for public assurance in creating public health information materials to address global health threats. Keywords COVID-19, public health advice, government, policy, airport, international travel",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20200212",
+    "rel_abs": "After the first wave of spread of the COVID-19 pandemic, countries around the world are struggling to recover their economies by slowly lifting the mobility restrictions and social distance measures enforced during the crisis. Therefore, the post-lockdown containment of the disease will depend strongly not any more on government-imposed interventions but on personal care measures, taken voluntarily by their citizens. In this respect, recent studies have shed some light regarding the effectiveness individual protection habits may have in preventing SARS-Cov-2 transmission, particularly physical contact distancing, facial mask wearing and hand-washing habits. In this paper we describe experiments performed on a simulated COVID-19 epidemic in an artificial population using an agent based model, so as to illustrate to what extent the interplay between such personal care habits contributes to mitigate the spread of the disease, assuming the lack of other population-wide non-pharmaceutical interventions or vaccines. We discuss scenarios where wide adherence to these voluntary care habits alone, can be enough to contain the unfold of the contagion. Our model purpose is illustrative and contributes to ratify the importance of disseminating the message regarding the collective benefits of mass adoption of personal protection and hygiene habits, as an exit strategy for COVID-19 in the new normal state.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Tingting Zhang",
-        "author_inst": "Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK"
-      },
-      {
-        "author_name": "Charlotte Robin",
-        "author_inst": "Field Epidemiology, Field Service, National Infection Service, Public Health England, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science a"
-      },
-      {
-        "author_name": "Shenghan Cai",
-        "author_inst": "Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK"
-      },
-      {
-        "author_name": "Clare Sawyer",
-        "author_inst": "UK Field Epidemiology Training Programme, Global Public Health Division, Public Health England, London, UK; Communicable Disease Surveillance Centre, Public Hea"
-      },
-      {
-        "author_name": "Wendy Rice",
-        "author_inst": "Field Epidemiology, Field Service, National Infection Service, Public Health England, Bristol, UK"
-      },
-      {
-        "author_name": "Louise E. Smith",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Health Protection Research Unit in Emergency Preparedness and Resp"
-      },
-      {
-        "author_name": "Richard Aml\u00f4t",
-        "author_inst": "NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Health Protection R"
-      },
-      {
-        "author_name": "G. James Rubin",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Health Protection Research Unit in Emergency Preparedness and Resp"
-      },
-      {
-        "author_name": "Rosy Reynolds",
-        "author_inst": "Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluati"
-      },
-      {
-        "author_name": "Lucy Yardley",
-        "author_inst": "Health Protection Research Unit in Behavioural Science and Evaluation, Bristol Medical School, University of Bristol, Bristol, UK; School of Psychological Scien"
-      },
-      {
-        "author_name": "Matthew Hickman",
-        "author_inst": "Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluati"
-      },
-      {
-        "author_name": "Isabel Oliver",
-        "author_inst": "Population Health Sciences, Bristol Medical School, University of Bristol; Field Epidemiology, Field Service, National Infection Service, Public Health England;"
+        "author_name": "Lindsay Alvarez-Pomar",
+        "author_inst": "Universidad Distrital Francisco Jose de Caldas"
       },
       {
-        "author_name": "Helen Lambert",
-        "author_inst": "Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Health Protection Research Unit in Behavioural Science and Evaluati"
+        "author_name": "Sergio Rojas-Galeano",
+        "author_inst": "Universidad Distrital Francisco Jose de Caldas"
       }
     ],
     "version": "1",
@@ -1120150,129 +1123030,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.25.20201459",
-    "rel_title": "Performance of a point of care test for detecting IgM and IgG antibodies against SARS-CoV-2 and seroprevalence in blood donors and health care workers in Panama",
+    "rel_doi": "10.1101/2020.09.24.20200394",
+    "rel_title": "Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer",
     "rel_date": "2020-09-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.25.20201459",
-    "rel_abs": "Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic, which has reached 28 million cases worldwide in eight months. The serological detection of antibodies against the virus will play a pivotal role in complementing molecular tests to improve diagnostic accuracy, contact tracing, vaccine efficacy testing and seroprevalence surveillance. Here, we aimed first to evaluate a lateral flow assays ability to identify specific IgM and IgG antibodies against SARS-CoV-2 and second, to report the seroprevalence of these antibodies among health care workers and healthy volunteer blood donors in Panama. We recruited study participants between April 30th and July 7th, 2020. For the test validation and performance evaluation, we analyzed serum samples from participants with clinical symptoms and confirmed positive RT-PCR for SARS-CoV-2, participants with other confirmed infectious diseases, and a set of pre-pandemic serum samples. We used two by two table analysis to determine the test sensitivity and specificity as well as the kappa agreement value with a 95% confidence interval. Then, we used the lateral flow assay to determine seroprevalence among serum samples from COVID-19 patients, potentially exposed health care workers, and healthy volunteer donors. Our results show this assay reached a positive percent agreement of 97.2% (95% CI 84.2-100.0%) for detecting both IgM and IgG. The assay showed a kappa of 0.898 (95%CI 0.811-0.985) and 0.918 (95% CI 0.839-0.997) for IgM and IgG, respectively. The evaluation of serum samples from hospitalized COVID-19 patients indicates a correlation between test sensitivity and the number of days since symptom onset; the highest positive percent agreement (87% (95% CI 67.0-96.3%)) was observed at [&ge;]15 days post-symptom onset. We found an overall antibody seroprevalence of 11.6% (95% CI 8.5-15.8%) among both health care workers and healthy blood donors. Our findings suggest this lateral flow assay could contribute significantly to implementing seroprevalence testing in locations with active community transmission of SARS-CoV-2.",
-    "rel_num_authors": 29,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.24.20200394",
+    "rel_abs": "Significant barriers to the diagnosis of latent and acute SARS-CoV-2 infection continue to hamper population-based screening efforts required to contain the COVID-19 pandemic in the absence of effective antiviral therapeutics or vaccines. We report an aptamer-based SARS-CoV-2 salivary antigen assay employing only low-cost reagents ($3.20/test) and an off-the-shelf glucometer. The test was engineered around a glucometer as it is quantitative, easy to use, and the most prevalent piece of diagnostic equipment globally making the test highly scalable with an infrastructure that is already in place. Furthermore, many glucometers connect to smartphones providing an opportunity to integrate with contract tracing apps, medical providers, and electronic medical records. In clinical testing, the developed assay detected SARS-CoV-2 infection in patient saliva across a range of viral loads - as benchmarked by RT-qPCR - within one hour, with 100% sensitivity (positive percent agreement) and distinguished infected specimens from off-target antigens in uninfected controls with 100% specificity (negative percent agreement). We propose that this approach can provide an inexpensive, rapid, and accurate diagnostic for distributed screening of SARS-CoV-2 infection at scale.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Alcibiades Villarreal",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Giselle Rangel",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Xu Zhang",
-        "author_inst": "CAS"
-      },
-      {
-        "author_name": "Digna Wong",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Carolina De La Guardia",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Gabrielle Britton",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Patricia L. Fernandez",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Carlos M Restrepo",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Ambar Perez",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Diana Oviedo",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Maria B Carreira",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Gilberto A. Eskildsen",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Dilcia Sambrano",
-        "author_inst": "INDICASAT-AIP"
-      },
-      {
-        "author_name": "Yamitzel Zaldivar",
-        "author_inst": "GORGAS"
-      },
-      {
-        "author_name": "Danilo Franco",
-        "author_inst": "GORGAS"
-      },
-      {
-        "author_name": "Sandra Lopez Verges",
-        "author_inst": "GORGAS"
-      },
-      {
-        "author_name": "Dexi Zhang",
-        "author_inst": "CAS"
-      },
-      {
-        "author_name": "Fangjing Fan",
-        "author_inst": "CAS"
-      },
-      {
-        "author_name": "Baojun Wang",
-        "author_inst": "KEWEI"
-      },
-      {
-        "author_name": "Xavier Saez-Llorens",
-        "author_inst": "CEVAXIN"
-      },
-      {
-        "author_name": "Rodrigo DeAntonio",
-        "author_inst": "CEVAXIN"
-      },
-      {
-        "author_name": "Ivonne Torres-Atencio",
-        "author_inst": "UP"
+        "author_name": "Naveen K Singh",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Fernando Diaz Subia",
-        "author_inst": "Pacifica Salud"
+        "author_name": "Partha Ray",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Eduardo Ortega-Barria",
-        "author_inst": "GSK"
+        "author_name": "Aaron F Carlin",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Rao Kosagisharaf",
-        "author_inst": "INDICASAT-AIP"
+        "author_name": "Celestine Magallanes",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Ricardo Lleonart",
-        "author_inst": "INDICASAT-AIP"
+        "author_name": "Sydney Morgan",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Chong Li",
-        "author_inst": "CAS"
+        "author_name": "Louise C Laurent",
+        "author_inst": "University of California, San Diego"
       },
       {
-        "author_name": "Amador Goodridge",
-        "author_inst": "INDICASAT-AIP"
+        "author_name": "Eliah Aronoff-Spencer",
+        "author_inst": "UC San Diego"
       },
       {
-        "author_name": "- COVID-19 SEROLOGY COLLABORATOR GROUP",
-        "author_inst": ""
+        "author_name": "Drew A. Hall",
+        "author_inst": "University of California, San Diego"
       }
     ],
     "version": "1",
@@ -1121956,39 +1124752,43 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2020.09.23.310565",
-    "rel_title": "COVID-19 CG: Tracking SARS-CoV-2 mutations by locations and dates of interest",
+    "rel_doi": "10.1101/2020.09.24.310490",
+    "rel_title": "Broad-spectrum, patient-adaptable inhaled niclosamide-lysozyme particles are efficacious against coronaviruses in lethal murine infection models",
     "rel_date": "2020-09-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.23.310565",
-    "rel_abs": "COVID-19 CG is an open resource for tracking SARS-CoV-2 single-nucleotide variations (SNVs) and lineages while filtering by location, date, gene, and mutation of interest. COVID-19 CG provides significant time, labor, and cost-saving utility to diverse projects on SARS-CoV-2 transmission, evolution, emergence, immune interactions, diagnostics, therapeutics, vaccines, and intervention tracking. Here, we describe case studies in which users can interrogate (1) SNVs in the SARS-CoV-2 Spike receptor binding domain (RBD) across different geographic regions to inform the design and testing of therapeutics, (2) SNVs that may impact the sensitivity of commonly used diagnostic primers, and (3) the recent emergence of a dominant lineage harboring an S477N RBD mutation in Australia. To accelerate COVID-19 research and public health efforts, COVID-19 CG will be continually upgraded with new features for users to quickly and reliably pinpoint mutations as the virus evolves throughout the pandemic and in response to therapeutic and public health interventions.",
-    "rel_num_authors": 5,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.24.310490",
+    "rel_abs": "Niclosamide (NIC) has demonstrated promising in vitro antiviral efficacy against SARS-CoV-2, the causative agent of the COVID-19 pandemic. Though NIC is already FDA-approved, the oral formulation produces systemic drug levels that are too low to inhibit SARS-CoV-2. As an alternative, direct delivery of NIC to the respiratory tract as an aerosol could target the primary site of for SARS-CoV-2 acquisition and spread. We have developed a niclosamide powder suitable for delivery via dry powder inhaler, nebulizer, and nasal spray through the incorporation of human lysozyme (hLYS) as a carrier molecule. This novel formulation exhibits potent in vitro and in vivo activity against MERS-CoV and SARS-CoV-2 and may protect against methicillin-resistance staphylococcus aureus pneumonia and inflammatory lung damage occurring secondary to CoV infections. The suitability of the formulation for all stages of the disease and low-cost development approach will ensure wide-spread utilization",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Albert Tian Chen",
-        "author_inst": "Broad Institute of MIT & Harvard"
+        "author_name": "Ashlee D Brunaugh",
+        "author_inst": "University of Texas at Austin"
       },
       {
-        "author_name": "Kevin Altschuler",
-        "author_inst": "NA"
+        "author_name": "Hyojong Seo",
+        "author_inst": "University of Texas at Austin"
       },
       {
-        "author_name": "Shing Hei Zhan",
-        "author_inst": "University of British Columbia"
+        "author_name": "Zachary Warnken",
+        "author_inst": "University of Texas at Austin"
       },
       {
-        "author_name": "Yujia Alina Chan",
-        "author_inst": "Broad Institute of MIT & Harvard"
+        "author_name": "Li Ding",
+        "author_inst": "University of Texas at Austin"
       },
       {
-        "author_name": "Benjamin E Deverman",
-        "author_inst": "Broad Institute of MIT and Harvard"
+        "author_name": "Sang Heui Seo",
+        "author_inst": "Chungnam National University"
+      },
+      {
+        "author_name": "Hugh D.C. Smyth",
+        "author_inst": "University of Texas at Austin"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "pharmacology and toxicology"
   },
   {
     "rel_doi": "10.1101/2020.09.24.311027",
@@ -1123698,43 +1126498,47 @@
     "category": "hiv aids"
   },
   {
-    "rel_doi": "10.1101/2020.09.22.20198465",
-    "rel_title": "Seroprevalence of immunoglobulin M and G antibodies against SARS-CoV-2 in ophthalmic patients",
+    "rel_doi": "10.1101/2020.09.20.20198432",
+    "rel_title": "COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior",
     "rel_date": "2020-09-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20198465",
-    "rel_abs": "Using serological test to estimate the prevalence and infection potential of coronavirus disease 2019 in ocular diseases patients help understand the relationship between ocular diseases and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We conducted a cross-sectional study assaying the IgG and IgM antibodies in 1331 individuals with ocular diseases by using a magnetic chemiluminescence enzyme immunoassay kit, during the period from February 2020 to May 2020. In our study, the seroposivity in total ocular disease patients was 0.83% (11/1331). The patients with different ocular diseases including xerophthalmia, keratitis, conjunctival cyst, cataract, glaucoma, refractive error, strabismus and others had seroposivity of 2.94%, 12.5%, 25%, 4.41%, 2.63%, 1.6%, 2.22% and 0%, respectively. Among that, two ocular surface disease groups (keratitis and conjunctival cyst) had higher seroprevalence compared with others. All the participants were reverse transcription polymerase chain reaction negative for SARS-CoV-2 from throat swabs. Our study evaluated the seroprevalence in patients with different ocular diseases, which will help us understand the relationship between ocular disease and SARS-CoV-2 infection. Furthermore, the serological test for the presence of IgM and/or IgG antibodies against SARS-CoV-2 might provide accurate estimate of the prevalence of SARS-CoV-2 infection in patients with ocular diseases.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.20.20198432",
+    "rel_abs": "This paper presents a deep learning framework for epidemiology system identification from noisy and sparse observations with quantified uncertainty. The proposed approach employs an ensemble of deep neural networks to infer the time-dependent reproduction number of an infectious disease by formulating a tensor-based multi-step loss function that allows us to efficiently calibrate the model on multiple observed trajectories. The method is applied to a mobility and social behavior-based SEIR model of COVID-19 spread. The model is trained on Google and Unacast mobility data spanning a period of 66 days, and is able to yield accurate future forecasts of COVID-19 spread in 203 US counties within a time-window of 15 days. Strikingly, a sensitivity analysis that assesses the importance of different mobility and social behavior parameters reveals that attendance of close places, including workplaces, residential, and retail and recreational locations, has the largest impact on the basic reproduction number. The model enables us to rapidly probe and quantify the effects of government interventions, such as lock-down and re-opening strategies. Taken together, the proposed framework provides a robust workflow for data-driven epidemiology model discovery under uncertainty and produces probabilistic forecasts for the evolution of a pandemic that can judiciously inform policy and decision making. All codes and data accompanying this manuscript are available at https://github.com/PredictiveIntelligenceLab/DeepCOVID19.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "shengjie li Sr.",
-        "author_inst": "Fudan University"
+        "author_name": "Mohamed Aziz Bhouri",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "yichao qiu",
-        "author_inst": "fudan university"
+        "author_name": "Francisco Sahli Costabal",
+        "author_inst": "Pontificia Universidad Catolica de Chile"
       },
       {
-        "author_name": "li tang",
-        "author_inst": "fudan university"
+        "author_name": "Hanwen Wang",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "zhujian wang",
-        "author_inst": "fudan university"
+        "author_name": "Kevin Linka",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "wenjun cao",
-        "author_inst": "fudan university"
+        "author_name": "Mathias Peirlinck",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "xinghuai sun",
-        "author_inst": "fudan university"
+        "author_name": "Ellen Kuhl",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Paris Perdikaris",
+        "author_inst": "University of Pennsylvania"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.09.21.20198416",
@@ -1125528,31 +1128332,95 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.09.20.20197608",
-    "rel_title": "At home and online during the early months of the COVID-19 pandemic and the relationship to alcohol consumption in a national sample of U.S. adults",
+    "rel_doi": "10.1101/2020.09.20.20196907",
+    "rel_title": "Microfluidic Affinity Profiling reveals a Broad Range of Target Affinities for Anti-SARS-CoV-2 Antibodies in Plasma of Covid Survivors",
     "rel_date": "2020-09-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.20.20197608",
-    "rel_abs": "ObjectiveThe current study seeks to understand the links between social media use and alcohol consumption during the early months of the COVID-19 pandemic.\n\nMethodData were from the national Understanding American Study, a probability-based Internet panel weighted to represent the U.S. population. Subjects (N=5874; 51% female) were adults, 18 years and older, who completed a March survey (wave 1) and a follow-up survey one month later (wave 3). Analyses assessed the relationship of social media use at wave 1 with wave 3 alcohol use, accounting for wave 1 alcohol use and the sociodemographic characteristics of the sample. We examined the effect of working or studying from home as a moderator.\n\nResultsTwitter and Instagram users, but not Facebook users, drank more frequently at wave 3 than non-users. For Instagram users, more frequent alcohol use at wave 3 was at least partially attributed to the frequency of drinking at wave 1. The interaction between Twitter use and working or studying from home was statistically significant. The combination of being on Twitter and working or studying from home was associated with drinking more days a week.\n\nConclusionsExposure to content about COVID-19 and increased alcohol consumption during the pandemic may contribute to more frequent alcohol use for some social media users, especially those sheltering at home. The study of public health messaging via social media to change alcohol use behaviors during traumatic events is warranted.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.20.20196907",
+    "rel_abs": "The clinical outcome of SARS-CoV-2 infections, which can range from asymptomatic to lethal, is crucially shaped by the concentration of antiviral antibodies and by their affinity to their targets. However, the affinity of polyclonal antibody responses in plasma is difficult to measure. Here we used Microfluidic Antibody Affinity Profiling (MAAP) to determine the aggregate affinities and concentrations of anti-SARS-CoV-2 antibodies in plasma samples of 42 seropositive individuals, 19 of which were healthy donors, 20 displayed mild symptoms, and 3 were critically ill. We found that dissociation constants, Kd, of anti-receptor binding domain antibodies spanned 2.5 orders of magnitude from sub-nanomolar to 43 nM. Using MAAP we found that antibodies of seropositive individuals induced the dissociation of pre-formed spike-ACE2 receptor complexes, which indicates that MAAP can be adapted as a complementary receptor competition assay. By comparison with cytopathic-effect based neutralisation assays, we show that MAAP can reliably predict the cellular neutralisation ability of sera, which may be an important consideration when selecting the most effective samples for therapeutic plasmapheresis and tracking the success of vaccinations.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Karen G Chartier",
-        "author_inst": "Virginia Commonwealth University"
+        "author_name": "Matthias M. Schneider",
+        "author_inst": "University of Cambridge"
       },
       {
-        "author_name": "Jeanine P.D. Guidry",
-        "author_inst": "Virginia Commonwealth University"
+        "author_name": "Marc Emmenegger",
+        "author_inst": "Institute of Neuropathology"
       },
       {
-        "author_name": "Catherine A. Lee",
-        "author_inst": "George Mason University"
+        "author_name": "Catherine K. Xu",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Itzel Condado Morales",
+        "author_inst": "Insitute of Neuropathology, University Hospital Zurich"
+      },
+      {
+        "author_name": "Georg Meisl",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Priscilla Turelli",
+        "author_inst": "Ecole Polytechnique Federale de Lausanne"
+      },
+      {
+        "author_name": "Chryssa Zografou",
+        "author_inst": "University of Zurich"
+      },
+      {
+        "author_name": "Manuela R. Zimmermann",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Beat M. Frey",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Sebastian Fiedler",
+        "author_inst": "Fluidic Analytics"
+      },
+      {
+        "author_name": "Viola Denninger",
+        "author_inst": "Fluidic Analytics"
+      },
+      {
+        "author_name": "Raphael P.B. Jacquat",
+        "author_inst": "Department of Chemistry, University of Cambridge"
+      },
+      {
+        "author_name": "Lidia Madrigal",
+        "author_inst": "University Hospital Zurich"
+      },
+      {
+        "author_name": "Alison Isley",
+        "author_inst": "Fluidic Analytics, Cambridge"
+      },
+      {
+        "author_name": "Vasilis Kosmoliaptsis",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Heike Fiegler",
+        "author_inst": "Fluidic Analytics"
+      },
+      {
+        "author_name": "Didier Trono",
+        "author_inst": "Ecole Polytechnique Federale de Lausanne"
+      },
+      {
+        "author_name": "Tuomas P. J. Knowles",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Adriano AA Aguzzi",
+        "author_inst": "University of Zurich"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "addiction medicine"
+    "category": "allergy and immunology"
   },
   {
     "rel_doi": "10.1101/2020.09.23.20197756",
@@ -1127254,35 +1130122,87 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.22.20199372",
-    "rel_title": "Limits and opportunities of SARS-CoV-2 antigen rapid Tests: an experience based perspective",
+    "rel_doi": "10.1101/2020.09.21.20199133",
+    "rel_title": "Reorganization of Substance Use Treatment and Harm Reduction Services during the COVID-19 Pandemic: A Global Survey",
     "rel_date": "2020-09-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20199372",
-    "rel_abs": "Due to the currently increasing case numbers of SARS-CoV-2 infections worldwide there is an increasing need for rapid diagnostic devices in addition to existing PCR-capacities. Therefore, rapid antigen assays including lateral flow assays are discussed as an alternative method. In comparison to an established RT-PCR protocol, however the novel lateral flow assay unfortunately lowered the expectations set in these assays.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.21.20199133",
+    "rel_abs": "BackgroundThe COVID-19 pandemic has impacted people with substance use disorders (SUDs) worldwide and healthcare systems have reorganized their services in response to the pandemic.\n\nMethodsOne week after the announcement of the COVID-19 as a pandemic, in a global survey, 177 addiction medicine professionals described COVID-19-related health responses in their own 77 countries in terms of SUD treatment and harm reduction services. The health response is categorized around (1) managerial measures and systems, (2) logistics, (3) service providers and (4) vulnerable groups.\n\nResultsRespondents from over 88% of countries reported that core medical and psychiatric care for SUDs had continued; however, only 56% of countries reported having had any business continuity plan, and, 37.5% of countries reported shortages of methadone or buprenorphine supplies. Participants of 41% of countries reported partial discontinuation of harm-reduction services such as needle and syringe programs and condom distribution. 57% of overdose prevention interventions and 81% of outreach services also having been negatively impacted.\n\nConclusionsParticipants reported that SUD treatment and harm reduction services had been significantly impacted globally early during the COVID-19 pandemic. Based on our findings, we provide a series of recommendations to support countries to be prepared more efficiently for future waves or similar pandemics to 1) help policymakers generate business continuity plans, 2) maintain use of evidence-based interventions for people with SUDs, 3) be prepared for adequate medication supplies, 4) integrate harm reduction programs with other treatment modalities and 5) have specific considerations for vulnerable groups such as immigrants and refugees.\n\nHighlightsO_LICOVID-19 negatively impacted services for PWSUD globally.\nC_LIO_LIAddiction medicine downgraded more than other psychiatry services.\nC_LIO_LIBusiness continuity plan for PWSUD services reported only in about half of the countries.\nC_LIO_LIRefugees & migrants had more negative impact compared to other vulnerable groups.\nC_LIO_LIHarm reduction services discontinued partially or totally during pandemic.\nC_LI",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Verena Schildgen",
-        "author_inst": "Kliniken der Stadt Koeln gGmbH, Klinikum der Privaten Universitaet Witten/Herdecke"
+        "author_name": "Seyed Ramin Radfar",
+        "author_inst": "Integrated Substance Abuse Programs Department, University of California, Los Angeles, USA;  Department of Psychiatry, Tehran University of Medical Sciences, Te"
+      },
+      {
+        "author_name": "Cornelis A J De Jong",
+        "author_inst": "Radboud University, Netherlands"
+      },
+      {
+        "author_name": "Ali Farhoudian",
+        "author_inst": "Department of Psychiatry, Tehran University of Medical Sciences, Tehran, Iran; Substance Abuse and Dependence Research Center, University of Social Welfare and "
+      },
+      {
+        "author_name": "Mohsen Ebrahimi",
+        "author_inst": "Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Iran; Materials and Energy Research Center, Iran"
+      },
+      {
+        "author_name": "Parnian Rafei",
+        "author_inst": "Department of Psychology, Faculty of Psychology and Education, University of Tehran, Iran"
+      },
+      {
+        "author_name": "Mehrnoosh Vahidi",
+        "author_inst": "Department of Psychiatry, Tehran University of Medical Sciences, Tehran, Iran"
+      },
+      {
+        "author_name": "Masud Yunesian",
+        "author_inst": "School of Public Health, Tehran University of Medical Sciences, Tehran, Iran"
+      },
+      {
+        "author_name": "Christos Kouimtsidis",
+        "author_inst": "Surrey and Borders Partnership NHS Foundation Trust, UK"
+      },
+      {
+        "author_name": "Shalini Arunogiri",
+        "author_inst": "Turning Point, Eastern Health, Box Hill, Australia"
+      },
+      {
+        "author_name": "Omid Massah",
+        "author_inst": "Substance Abuse and Dependence Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran"
+      },
+      {
+        "author_name": "Abbas Deylamizadeh",
+        "author_inst": "Rebirth Charity Society NGO, Tehran, Iran"
+      },
+      {
+        "author_name": "Kathleen T Brady",
+        "author_inst": "Medical University of South Carolina, USA"
+      },
+      {
+        "author_name": "Anja Busse",
+        "author_inst": "Prevention, Treatment and Rehabilitation Section; Drug Prevention and Health Branch, Division for Operations, United Nations Office on Drugs and Crime, Vienna, "
+      },
+      {
+        "author_name": "- ISAM-PPIG Global Survey Consortium",
+        "author_inst": ""
       },
       {
-        "author_name": "Sabrina Demuth",
-        "author_inst": "Kliniken der Stadt Koeln"
+        "author_name": "Marc N Potenza",
+        "author_inst": "Yale School of Medicine, Connecticut Council on Problem Gambling and Connecticut Mental Health Center, USA"
       },
       {
-        "author_name": "Jessica Lusebrink",
-        "author_inst": "Kliniken der Stadt Koeln"
+        "author_name": "Hamed Ekhtiari",
+        "author_inst": "Laureate Institute for Brain Research, Tulsa, OK, USA"
       },
       {
-        "author_name": "Oliver Schildgen",
-        "author_inst": "Kliniken der Stadt Koeln gGmbH, Klinikum der Privaten Universtaet Witten/Herdecke"
+        "author_name": "Alexander Mario Baldacchino",
+        "author_inst": "University of St Andrews, UK"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "addiction medicine"
   },
   {
     "rel_doi": "10.1101/2020.09.22.20199398",
@@ -1129007,91 +1131927,47 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.09.20.297242",
-    "rel_title": "Comparative analysis reveals the species-specific genetic determinants of ACE2 required for SARS-CoV-2 entry",
+    "rel_doi": "10.1101/2020.09.21.306357",
+    "rel_title": "Cryo-EM structure of S-Trimer, a subunit vaccine candidate for COVID-19",
     "rel_date": "2020-09-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.20.297242",
-    "rel_abs": "Coronavirus interaction with its viral receptor is a primary genetic determinant of host range and tissue tropism. SARS-CoV-2 utilizes ACE2 as the receptor to enter host cell in a species-specific manner. We and others have previously shown that ACE2 orthologs from New World monkey, koala and mouse cannot interact with SARS-CoV-2 to mediate viral entry, and this defect can be restored by humanization of the restrictive residues in New World monkey ACE2. To better understand the genetic determinants behind the ability of ACE2 orthologs to support viral entry, we compared koala and mouse ACE2 sequences with that of human and identified the key residues in koala and mouse ACE2 that restrict viral receptor activity. Humanization of these critical residues rendered both koala and mouse ACE2 capable of binding the spike protein and facilitating viral entry. The single mutation that allowed for mouse ACE2 to serve as a viral receptor provides a potential avenue for the development of SARS-CoV-2 mouse model.",
-    "rel_num_authors": 18,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.21.306357",
+    "rel_abs": "Less than a year after its emergence, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 22 million people worldwide with a death toll approaching 1 million. Vaccination remains the best hope to ultimately put this pandemic to an end. Here, using Trimer-Tag technology, we produced both wild-type (WT) and furin site mutant (MT) S-Trimers for COVID-19 vaccine studies. Cryo-EM structures of the WT and MT S-Trimers, determined at 3.2 [A] and 2.6 [A] respectively, revealed that both antigens adopt a tightly closed conformation and their structures are essentially identical to that of the previously solved full-length WT S protein in detergent. These results validate Trimer-Tag as a platform technology in production of metastable WT S-Trimer as a candidate for COVID-19 subunit vaccine.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Wenlin Ren",
-        "author_inst": "Tsinghua University"
+        "author_name": "Jiahao Ma",
+        "author_inst": "Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University; National Institute of Biological Sciences, 102206 Beijing, China"
       },
       {
-        "author_name": "Gaowei Hu",
-        "author_inst": "Fudan University"
-      },
-      {
-        "author_name": "Xiaomin Zhao",
-        "author_inst": "Tsinghua University"
-      },
-      {
-        "author_name": "Yuyan Wang",
-        "author_inst": "Fudan University"
-      },
-      {
-        "author_name": "Hongyang Shi",
-        "author_inst": "Institut Pasteur of Shanghai, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Jun Lan",
-        "author_inst": "Tsinghua University"
-      },
-      {
-        "author_name": "Yunkai Zhu",
-        "author_inst": "Fudan University"
-      },
-      {
-        "author_name": "Jianping Wu",
-        "author_inst": "Westlake University"
-      },
-      {
-        "author_name": "Devin J. Kenney",
-        "author_inst": "Boston University School of Medicine"
-      },
-      {
-        "author_name": "Douam Florian",
-        "author_inst": "Boston University School of Medicine"
-      },
-      {
-        "author_name": "Yimin Tong",
-        "author_inst": "Institut Pasteur of Shanghai"
-      },
-      {
-        "author_name": "Jin Zhong",
-        "author_inst": "Institut Pasteur of Shanghai"
-      },
-      {
-        "author_name": "Youhua Xie",
-        "author_inst": "Fudan University"
+        "author_name": "Danmei Su",
+        "author_inst": "Clover Biopharmaceuticals, Chengdu, China"
       },
       {
-        "author_name": "Xinquan Wang",
-        "author_inst": "Tsinghua University"
+        "author_name": "Xueqin Huang",
+        "author_inst": "Clover Biopharmaceuticals, Chengdu, China"
       },
       {
-        "author_name": "Zhenghong Yuan",
-        "author_inst": "Fudan University"
+        "author_name": "Ying Liang",
+        "author_inst": "Clover Biopharmaceuticals, Chengdu, China"
       },
       {
-        "author_name": "Dongming Zhou",
-        "author_inst": "School of Basic Medical Sciences, Tianjin Medical University"
+        "author_name": "Yan Ma",
+        "author_inst": "National Institute of Biological Sciences, Beijing; Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, 102206 Beijing, China."
       },
       {
-        "author_name": "Rong Zhang",
-        "author_inst": "Fudan University Shanghai Medical College"
+        "author_name": "Peng Liang",
+        "author_inst": "Clover Biopharmaceuticals, Chengdu, China"
       },
       {
-        "author_name": "Qiang Ding",
-        "author_inst": "Tsinghua University"
+        "author_name": "Sanduo Zheng",
+        "author_inst": "National Institute of Biological Sciences, Beijing; Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, 102206 Beijing, China."
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2020.09.21.306720",
@@ -1130385,81 +1133261,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.09.15.20194258",
-    "rel_title": "COVID-19 epidemic severity is associated with timing of non-pharmaceutical interventions",
+    "rel_doi": "10.1101/2020.09.14.20194589",
+    "rel_title": "Improved estimation of time-varying reproduction numbers at low case incidence and between epidemic waves",
     "rel_date": "2020-09-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20194258",
-    "rel_abs": "Background: Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non-pharmaceutical interventions is still debated. International comparisons are hampered by highly variable conditions under which epidemics spread and differences in the timing and scale of interventions. Cumulative COVID-19 morbidity and mortality are functions of both the rate of epidemic growth and the duration of uninhibited growth before interventions were implemented. Incomplete and sporadic testing during the early COVID-19 epidemic makes it difficult to identify how long SARS-CoV-2 was circulating in different places. SARS-CoV-2 genetic sequences can be analyzed to provide an estimate of both the time of epidemic origin and the rate of early epidemic growth in different settings. Methods: We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were cross-referenced with dates of the most stringent interventions in each location as well as the number of cumulative COVID-19 deaths following maximum intervention. Phylodynamic methods were used to estimate the rate of early epidemic growth and proxy estimates of epidemic size. Findings: The time elapsed between epidemic origin and maximum intervention is strongly associated with different measures of epidemic severity and explains 46% of variance in numbers infected at time of maximum intervention. The reproduction number is independently associated with epidemic severity. In multivariable regression models, epidemic severity was not associated with census population size. The time elapsed between detection of initial COVID-19 cases to interventions was not associated with epidemic severity, indicating that many locations experienced long periods of cryptic transmission. Interpretation: Locations where strong non-pharmaceutical interventions were implemented earlier experienced much less severe COVID-19 morbidity and mortality during the period of study.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20194589",
+    "rel_abs": "We construct a recursive Bayesian smoother, termed EpiFilter, for estimating the effective reproduction number, R, from the incidence of an infectious disease in real time and retrospectively. Our approach borrows from Kalman filtering theory, is quick and easy to compute, generalisable, deterministic and unlike many current methods, requires no change-point or window size assumptions. We model R as a flexible, hidden Markov state process and exactly solve forward-backward algorithms, to derive R estimates that incorporate all available incidence information. This unifies and extends two popular methods, EpiEstim, which considers past incidence, and the Wallinga-Teunis method, which looks forward in time. We find that this combination of maximising information and minimising assumptions significantly reduces the bias and variance of R estimates. Moreover, these properties make EpiFilter more statistically robust in periods of low incidence, where existing methods can become destabilised. As a result, EpiFilter offers improved inference of time-varying transmission patterns that are especially advantageous for assessing the risk of upcoming waves of infection in real time and at various spatial scales.\n\nAuthor SummaryInferring changes in the transmissibility of an infectious disease is crucial for understanding and controlling epidemic spread. The effective reproduction number, R, is widely used to assess transmissibility. R measures the average number of secondary cases caused by a primary case and has provided insight into many diseases including COVID-19. An upsurge in R can forewarn of upcoming infections, while suppression of R can indicate if public health interventions are working. Reliable estimates of temporal changes in R can contribute important evidence to policymaking. Popular R-inference methods, while powerful, can struggle when cases are few because data are noisy. This can limit detection of crucial variations in transmissibility that may occur, for example, when infections are waning or when analysing transmissibility over fine geographic scales. In this paper we improve the general reliability of R-estimates and specifically increase robustness when cases are few. By adapting principles from control engineering, we formulate EpiFilter, a novel method for inferring R in real time and retrospectively. EpiFilter can potentially double the information extracted from epidemic time-series (when compared to popular approaches), significantly filtering the noise within data to minimise both bias and uncertainty of R-estimates and enhance the detection of salient changepoints in transmissibility.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Manon Ragonnet-Cronin",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Olivia Boyd",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Lily Geidelberg",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "David Jorgensen",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Fabricia F Nascimento",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Igor Siveroni",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Robert Johnson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Marc Baguelin",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Zulma M Cucunuba",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Elita Jauneikaite",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Swapnil Mishra",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Hayley A Thompson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Oliver J Watson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Neil Ferguson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Christl A Donnelly",
-        "author_inst": "Imperial College London; University of Oxford"
-      },
-      {
-        "author_name": "Erik Volz",
+        "author_name": "Kris Varun Parag",
         "author_inst": "Imperial College London"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1132379,51 +1135195,35 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2020.09.16.20195685",
-    "rel_title": "Integrative Genomics Analysis Reveals a Novel 21q22.11 Locus Contributing to Susceptibility of COVID-19",
+    "rel_doi": "10.1101/2020.09.17.20190595",
+    "rel_title": "The \"Great Lockdown\": Inactive Workers and Mortality by Covid-19",
     "rel_date": "2020-09-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20195685",
-    "rel_abs": "The systematic identification of host genetic risk factors is essential for the understanding and treatment of COVID-19. By performing a meta-analysis of two independent genome-wide association (GWAS) summary datasets (N = 680,128), a novel locus at 21q22.11 was identified to be associated with COVID-19 infection (rs9976829 in IFNAR2 and upstream of IL10RB, OR = 1.16, 95% CI = 1.09 - 1.23, P = 2.57x10-6). The rs9976829 represents a strong splicing quantitative trait locus (sQTL) for both IFNAR2 and IL10RB genes, especially in lung tissue (P 1.8x10-24). Gene-based association analysis also found IFNAR2 was significantly associated with COVID-19 infection (P = 2.58x10-7). Integrative genomics analysis of combining GWAS with eQTL data showed the expression variations of IFNAR2 and IL10RB have prominent effects on COVID-19 in various types of tissues, especially in lung tissue. The majority of IFNAR2-expressing cells were dendritic cells (40%) and plasmacytoid dendritic cells (38.5%), and IL10RB-expressing cells were mainly nonclassical monocytes (29.6%). IFNAR2 and IL10RB are targeted by several interferons-related drugs. Together, our results uncover 21q22.11 as a novel susceptibility locus for COVID-19, in which individuals with G alleles of rs9976829 have a higher probability of COVID-19 susceptibility than those with non-G alleles.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20190595",
+    "rel_abs": "In response to the Covid-19 outbreak the Italian Government imposed an economic lockdown on March 22, 2020 and ordered the closing of all non-essential economic activities. This paper estimates the causal effects of this measure on mortality by Covid-19 and on mobility patterns. The identification of the causal effects exploits the variation in the active population across municipalities induced by the economic lockdown. The difference-in-differences empirical design compares outcomes in municipalities above and below the median variation in the share of active population before and after the lockdown within a province, also controlling for municipality-specific dynamics, daily-shocks at the provincial level and municipal unobserved characteristics. Our results show that the intensity of the economic lockdown is associated with a statistically significant reduction in mortality by Covid-19 and, in particular, for age groups between 40-64 and older (with larger and more significant effects for individuals above 50). Back of the envelope calculations indicate that 4,793 deaths were avoided, in the 26 days between April 5 to April 30, in the 3,518 municipalities which experienced a more intense lockdown. Several robustness checks corroborate our empirical findings.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Yunlong Ma",
-        "author_inst": "Wenzhou Medical University"
+        "author_name": "Nicola Borri",
+        "author_inst": "Luiss University"
       },
       {
-        "author_name": "Yukuan Huang",
-        "author_inst": "Institute of Biomedical Big Data, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China"
-      },
-      {
-        "author_name": "Sen Zhao",
-        "author_inst": "Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China"
-      },
-      {
-        "author_name": "Yinghao Yao",
-        "author_inst": "Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou 325011, China"
-      },
-      {
-        "author_name": "Yaru Zhang",
-        "author_inst": "Institute of Biomedical Big Data, School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 32"
-      },
-      {
-        "author_name": "Jia Qu",
-        "author_inst": "Institute of Biomedical Big Data, School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 32"
+        "author_name": "Francesco Drago",
+        "author_inst": "University of Catania"
       },
       {
-        "author_name": "Nan Wu",
-        "author_inst": "Department of Orthopedic Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China"
+        "author_name": "Chiara Santantonio",
+        "author_inst": "Luiss University"
       },
       {
-        "author_name": "Jianzhong Su",
-        "author_inst": "Institute of Biomedical Big Data, School of Biomedical Engineering, School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou 32"
+        "author_name": "Francesco Sobbrio",
+        "author_inst": "University of Rome Tor Vergata"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "genetic and genomic medicine"
+    "category": "health economics"
   },
   {
     "rel_doi": "10.1101/2020.09.17.20185090",
@@ -1134229,33 +1137029,41 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.09.17.20195131",
-    "rel_title": "Seroprevalence of Antibodies to SARS-CoV-2 in US Blood Donors",
+    "rel_doi": "10.1101/2020.09.17.20196832",
+    "rel_title": "COVID-19 pediatric mortality rates are heterogenous between countries",
     "rel_date": "2020-09-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20195131",
-    "rel_abs": "BackgroundTo identify blood donors eligible to donate Coronavirus Disease-2019 (COVID-19) Convalescent Plasma (CCP), a large blood center began testing for antibodies to SARS-CoV-2, the etiologic agent of COVID-19. We report the seroprevalence of total immunoglobulin directed against the S1 spike protein of SARS-CoV-2 in US blood donors.\n\nMethodsUnique non-CCP donor sera from June 1-July 31, 2020 were tested with the Ortho VITROS Anti-SARS-CoV-2 total immunoglobulin assay (positive: signal-to-cutoff (S/C) [&ge;]1). Donor age, sex, race/ethnicity, ABO/RhD, education, and experience were compared to June and July 2019. Multivariate regressions were conducted to identify demographics associated with the presence of antibodies and with S/C values.\n\nResultsUnique donors (n=252,882) showed an overall seroprevalence of 1.83% in June (1.37%) and July (2.26%), with the highest prevalence in northern New Jersey (7.3%). In a subset of donors with demographic information (n=189,565), higher odds of antibody reactivity were associated with non-Hispanic Native American/Alaskan (NH-NAA/A) and Black (NH-B), and Hispanic (H) race/ethnicity, age 18-64, middle school or lesser education, blood Group A, and never or non-recent donor status. In positive donors (n=2,831), antibody signal was associated with male sex, race/ethnicity (NH-NAA/A, NH-B and H) and geographic location.\n\nConclusionsSeroprevalence remains low in US blood donors but varies significantly by region. Temporal trends in reactivity may be used to gauge the effectiveness of public health measures. Before generalizing these data from healthy donors to the general population however, rates must be corrected for false positive test results among low prevalence test subjects and adjusted to match the wider demography.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.17.20196832",
+    "rel_abs": "Introduction: Severe COVID-19 is infrequent in children, with a lethality rate of about 0.08%. This study aims to explore differences in the pediatric mortality rate between countries. Methods: Countries with populations over 5 million that report COVID-19 deaths disaggregated data by quinquennial or decennial age groups were analyzed. Data were extracted from COVID-19 Cases and Deaths by Age Database, national ministries of health, and the World Health Organization. Results: 23 countries were included in the analysis. Pediatric mortality varied from 0 to 12.1 deaths per million people of the corresponding age group, with the highest rate in Peru. In most countries, deaths were more frequent in the 0-4 years old age group, except for Brazil. The pediatric/ general COVID-19 mortality showed a great variation between countries and ranged from 0 (Republic of Korea) to 10.4% (India). Pediatric and Pediatric/general COVID mortality have a strong correlation with 2018 neonatal mortality (r=0.77, p<0.001 and r= 0.88, p<0.001 respectively), while it has a moderate or absent (r=0.47, p=0.02 and r=0.19, p=0.38, respectively) correlation with COVID-19 mortality in the general population. Conclusions: There is an important heterogenicity in pediatric COVI-19 mortality between countries that parallels historical neonatal mortality. Neonatal mortality is a known index of the quality of a country s Health System which points to the importance of social determinants of health in pediatric COVID-19 mortality disparities, an issue which should be further explored.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Ralph R Vassallo",
-        "author_inst": "Vitalant"
+        "author_name": "Nadia Gonzalez-Garcia",
+        "author_inst": "HOSPITAL INFANTIL DE MEXICO FEDERICO GOMEZ"
       },
       {
-        "author_name": "Marjorie D Bravo",
-        "author_inst": "Vitalant"
+        "author_name": "America Liliana Miranda-Lora",
+        "author_inst": "HOSPITAL INFANTIL DE MEXICO FEDERICO GOMEZ"
       },
       {
-        "author_name": "Larry J Dumont",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Jorge Mendez-Galvan",
+        "author_inst": "HOSPITAL INFANTIL DE MEXICO FEDERICO GOMEZ"
       },
       {
-        "author_name": "Kelsey Hazegh",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Javier T Granados-Riveron",
+        "author_inst": "HOSPITAL INFANTIL DE MEXICO FEDERICO GOMEZ"
       },
       {
-        "author_name": "Hany Kamel",
-        "author_inst": "Vitalant"
+        "author_name": "Jaime Nieto-Zermeno",
+        "author_inst": "HOSPITAL INFANTIL DE MEXICO FEDERICO GOMEZ"
+      },
+      {
+        "author_name": "Juan Garduno-Espinosa",
+        "author_inst": "HOSPITAL INFANTIL DE MEXICO FEDERICO GOMEZ"
+      },
+      {
+        "author_name": "MARIA F CASTILLA-PEON",
+        "author_inst": "HOSPITAL INFANTIL DE MEXICO FEDERICO GOMEZ"
       }
     ],
     "version": "1",
@@ -1136003,67 +1138811,47 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.09.16.300871",
-    "rel_title": "Distinct SARS-CoV-2 Antibody Reactivity Patterns in Coronavirus Convalescent Plasma Revealed by a Coronavirus Antigen Microarray",
+    "rel_doi": "10.1101/2020.09.16.300319",
+    "rel_title": "A soluble ACE2 microbody protein fused to a single immunoglobulin Fc domain is a potent inhibitor of SARS-CoV-2 infection in cell culture",
     "rel_date": "2020-09-17",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.16.300871",
-    "rel_abs": "A coronavirus antigen microarray (COVAM) was constructed containing 11 SARS-CoV-2, 5 SARS-1, 5 MERS, and 12 seasonal coronavirus recombinant proteins. The array is designed to measure immunoglobulin isotype and subtype levels in serum or plasma samples against each of the individual antigens printed on the array. We probed the COVAM with COVID-19 convalescent plasma (CCP) collected from 99 donors who recovered from a PCR+ confirmed SARS-CoV-2 infection. The results were analyzed using two computational approaches, a generalized linear model (glm) and Random Forest (RF) prediction model, to classify individual specimens as either Reactive or Non-Reactive against the SARS-CoV-2 antigens. A training set of 88 pre-COVID-19 specimens (PreCoV) collected in August 2019 and102 positive specimens from SARS-CoV-2 PCR+ confirmed COVID-19 cases was used for these analyses. Results compared with an FDA emergency use authorized (EUA) SARS-CoV2 S1-based total Ig chemiluminescence immunoassay (Ortho Clinical Diagnostics VITROS(R) Anti-SARS-CoV-2 Total, CoV2T) and with a SARS-CoV-2 S1-S2 spike-based pseudovirus micro neutralization assay (SARS-CoV-2 reporter viral particle neutralization titration (RVPNT) showed high concordance between the 3 assays. Three CCP specimens that were negative by the VITROS CoV2T immunoassay were also negative by both COVAM and the RVPNT assay. Concordance between VITROS CoV2T and COVAM was 96%, VITROS CoV2T and RVPNT 93%, and RVPNT and COVAM 95%. The discordances were all weakly reactive samples near the cutoff threshold of the VITROS CoV2T immunoassay. The multiplex COVAM allows CCP to be grouped according to antibody reactivity patterns against 11 SARS-CoV-2 antigens. Unsupervised K-means analysis, via the gap statistics, as well as hierarchical clustering analysis revealed 3 main clusters with distinct reactivity intensities and patterns. These patterns were not recapitulated by adjusting the VITROS CoV2T or RVPNT assay thresholds. Plasma classified according to these reactivity patterns may be better associated with CCP treatment efficacy than antibody levels alone. The use of a SARS-CoV-2 antigen array may be useful to qualify CCP for administration as a treatment for acute COVID-19 and to interrogate vaccine immunogenicity and performance in preclinical and clinical studies to understand and recapitulate antibody responses associated with protection from infection and disease.",
-    "rel_num_authors": 12,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.16.300319",
+    "rel_abs": "Soluble forms of ACE2 have recently been shown to inhibit SARS-CoV-2 infection. We report on an improved soluble ACE2, termed a \"microbody\" in which the ACE2 ectodomain is fused to Fc domain 3 of the immunoglobulin heavy chain. The protein is smaller than previously described ACE2-Ig Fc fusion proteins and contains an H345A mutation in the ACE2 catalytic active site that inactivates the enzyme without reducing its affinity for the SARS-CoV-2 spike. The disulfide-bonded ACE2 microbody protein inhibited entry of lentiviral SARS-CoV-2 spike protein pseudotyped virus and live SARS-CoV-2 with a potency 10-fold higher than unmodified soluble ACE2 and was active after initial virus binding to the cell. The ACE2 microbody inhibited the entry of ACE2-specific {beta} coronaviruses and viruses with the high infectivity variant D614G spike. The ACE2 microbody may be a valuable therapeutic for COVID-19 that is active against SARS-CoV-2 variants and future coronaviruses that may arise.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Rafael Ramiro de Assis",
-        "author_inst": "University of California, Irvine"
-      },
-      {
-        "author_name": "Aarti Jain",
-        "author_inst": "University of California, Irvine"
-      },
-      {
-        "author_name": "Rie Nakajima",
-        "author_inst": "University of California, Irvine"
-      },
-      {
-        "author_name": "Algis Jasinskas",
-        "author_inst": "University of California, Irvine"
-      },
-      {
-        "author_name": "Saahir Khan",
-        "author_inst": "University of Southern California"
-      },
-      {
-        "author_name": "Larry J Dumont",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Takuya Tada",
+        "author_inst": "NYU Langone Medical Center"
       },
       {
-        "author_name": "Kathleen Kelly",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Chen Fan",
+        "author_inst": "Weill Cornell Medical College"
       },
       {
-        "author_name": "Graham Simmons",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Ramanjit Kaur",
+        "author_inst": "NYU Langone Medical Center"
       },
       {
-        "author_name": "Mars Stone",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Kenneth A Stapleford",
+        "author_inst": "NYU Langone Medical Center"
       },
       {
-        "author_name": "Clara Di Germanio",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Harry Gristick",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Michael P Busch",
-        "author_inst": "Vitalant Research Institute"
+        "author_name": "Crina Nimigean",
+        "author_inst": "Weill Cornell Medical College"
       },
       {
-        "author_name": "Philip L Felgner",
-        "author_inst": "University of California, Irvine"
+        "author_name": "Nathaniel R Landau",
+        "author_inst": "NYU Langone Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.09.17.299933",
@@ -1137841,35 +1140629,123 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.09.13.20193896",
-    "rel_title": "Are we there yet? An adaptive SIR model for continuous estimation of COVID-19 infection rate and reproduction number in the United States",
+    "rel_doi": "10.1101/2020.09.03.20187112",
+    "rel_title": "Treatment with an Anti-CK2 Synthetic Peptide Improves Clinical Response in Covid-19 Patients with Pneumonia. A Randomized and Controlled Clinical Trial",
     "rel_date": "2020-09-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.13.20193896",
-    "rel_abs": "BackgroundThe dynamics of the COVID-19 epidemic vary due to local population density and policy measures. When making decisions, policy makers consider an estimate of the effective reproduction number [R]t which is the expected number of secondary infections by a single infected individual.\n\nObjectiveWe propose a simple method for estimating the time-varying infection rate and reproduction number [R]t.\n\nMethodsWe use a sliding window approach applied to a Susceptible-Infectious-Removed model. The infection rate is estimated using the reported cases for a seven-day window to obtain continuous estimation of [R]t. The proposed adaptive SIR (aSIR) model was applied to data at the state and county levels.\n\nResultsThe aSIR model showed an excellent fit for the number of reported COVID-19 positive cases, a one-day forecast MAPE was less than 2.6% across all states. However, a seven-day forecast MAPE reached 16.2% and strongly overestimated the number of cases when the reproduction number was high and changing fast. The maximal [R]t showed a wide range of 2.0 to 4.5 across all states, with the highest values for New York (4.4) and Michigan (4.5). We demonstrate that the aSIR model can quickly adapt to an increase in the number of tests and associated increase in the reported cases of infections. Our results also suggest that intensive testing may be one of the effective methods of reducing [R]t.\n\nConclusionThe aSIR model provides a simple and accurate computational tool to obtain continuous estimation of the reproduction number and evaluate the efficacy of mitigation measures.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.03.20187112",
+    "rel_abs": "PurposeThe instrumental role of CK2 in the SARS-Cov2 infection has pointed out this protein kinase as a promising therapeutic target in Covid-19. Anti-SARS-Cov2 activity has been reported by CK2 inhibitors in vitro; however, any anti-CK2 clinical approach has been investigated in Covid-19. This exploratory trial aimed to explore safety and putative clinical benefit of CIGB-325, an anti-CK2 peptide previously assessed in cancer.\n\nMethodsA monocentric, parallel group design, therapeutic exploratory trial of intravenous CIGB-325 in adults hospitalized with Covid-19 was performed. Twenty patients were randomly assigned to receive CIGB-325 (2.5 mg/kg/day during 5-consecutive days) plus standard-of-care (10 patients) or standard-of-care (10 patients). Adverse events were classified by the WHO Adverse Reaction Terminology. Parametric and non-parametric statistical analyses were performed according to the type of variable. Considering the small sample size, differences between groups were estimated by Bayesian analysis.\n\nFindingsCIGB-325 induced transient mild and/or moderate adverse events like pruritus, flushing and rash in some patients. Both therapeutic regimens were similar respect to SARS-Cov2 clearance in nasopharynx swabs over the time. However, CIGB-325 significantly reduced the median number of pulmonary lesions (9.5 to 5.5, p = 0.042) at day 7 and proportion of patients with such effect was also higher according to Bayesian analysis (pDif > 0; 0.951). Additionally, CIGB-325 significantly reduced the CPK (p = 0.007) and LDH (p = 0.028) plasma levels at day 7.\n\nImplicationsOur preliminary findings suggest that this anti-CK2 clinical approach could be combined with standard-of-care in Covid-19 thus warranting larger studies.",
+    "rel_num_authors": 26,
     "rel_authors": [
       {
-        "author_name": "Mark B Shapiro",
-        "author_inst": "Anthem, Inc."
+        "author_name": "Leticia R. Cruz",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Idania Baladron",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "Aliusha Rittoles",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Pablo A. Diaz",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "Carmen Valenzuela",
+        "author_inst": "Center for Molecular Immunology"
+      },
+      {
+        "author_name": "Raul Santana",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Maria M. Vazquez",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "Ariadna Garcia",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Deyli Chacon",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Delvin Thompson",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Gustavo Perera",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Ariel Gonzalez",
+        "author_inst": "International Center of Health La Pradera"
       },
       {
-        "author_name": "Fazle Karim",
-        "author_inst": "Anthem, Inc."
+        "author_name": "Rafael Reyes",
+        "author_inst": "National Institute of Oncology and Radiobiology"
       },
       {
-        "author_name": "Guido Muscioni",
-        "author_inst": "Anthem, Inc."
+        "author_name": "Loida Torres",
+        "author_inst": "International Center of Health La Pradera"
       },
       {
-        "author_name": "Abel Saju Augustine",
-        "author_inst": "Anthem, Inc."
+        "author_name": "Jesus Perez",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Yania Valido",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Ralysmay Rodriguez",
+        "author_inst": "Luis Diaz Soto Hospital"
+      },
+      {
+        "author_name": "Dania M. Vazquez",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "Mauro Rosales",
+        "author_inst": "Faculty of Biology, University of Havana"
+      },
+      {
+        "author_name": "Ailyn C. Ramon",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "George V. Perez",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "Gerardo Guillen",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "Verena Muzio",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "Yasser Perera",
+        "author_inst": "China-Cuba Biotechnology Joint Innovation Center"
+      },
+      {
+        "author_name": "Silvio E. Perea",
+        "author_inst": "Center for Genetic Engineering and Biotechnology"
+      },
+      {
+        "author_name": "- ATENEA-Co-300 Group",
+        "author_inst": "-"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pharmacology and therapeutics"
   },
   {
     "rel_doi": "10.1101/2020.09.10.20187427",
@@ -1139651,39 +1142527,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.12.20193334",
-    "rel_title": "Analysis of the interventions adopted due to the COVID-19 on ARI morbility for Colombia",
+    "rel_doi": "10.1101/2020.09.12.20193409",
+    "rel_title": "Clinical characteristics and outcomes of patients with COVID-19 and ARDS admitted to a third level health institution in Mexico City",
     "rel_date": "2020-09-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.12.20193334",
-    "rel_abs": "Acute Respiratory Infections are among the leading causes of death globally, particularly in developing countries, and are highly correlated with the quality of health and surveillance systems and effective early interventions in high-risk age groups. According to the World Health Organization, about four million people die each year from mostly preventable respiratory tract infections, making it a public health concern. The official declaration of a pandemic in March 2020 due to the Sars-CoV-2 virus coincided with the influenza season in Colombia and with environmental alerts about low air quality that increase its incidence. The objective of this document is the application of a flexible model for the identification of the pattern and monitoring of ARI morbility for Colombia by age group that shows atypical patterns in the reported series for 5 departments and that coincide with the decisions implemented to contain the COVID-19.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.12.20193409",
+    "rel_abs": "BackgroundIn December 2019, the first cases of severe pneumonia associated with a new coronavirus were reported in Wuhan, China. Severe respiratory failure requiring intensive care was reported in up to 5% of cases. There is, however, limited information available in Mexico.\n\nObjectivesThe purpose of this study was to describe the clinical manifestations, and outcomes in a COVID-19 cohort attended to from March to May 2020 in our RICU. In addition, we explored the association of clinical variables with mortality.\n\nMethodsThe first consecutive patients admitted to the RICU from March 3, 2020, to Jun 24, 2020, with confirmed COVID-19 were investigated. Clinical and laboratory data were obtained. Odds ratios (ORs) were calculated using a logistic regression model. The survival endpoint was mortality at discharge from the RICU.\n\nResultsData from 68 consecutive patients were analyzed. Thirty-eight patients survived, and 30 died (mortality: 44.1 %). Of the 16 predictive variables analyzed, only 6 remained significant in the multivariate analysis [OR (95% confidence interval)]: no acute kidney injury (AKI)/AKI 1: [.61 (.001;.192)]; delta lymphocyte count: [.061 (.006;.619)]; delta ventilatory ratio: [8.19 (1.40;47.8)]; norepinephrine support at admission: [34.3 (2.1;550)]; body mass index: [1.41 (1.09;1.83)]; and bacterial coinfection: [18.5 (1.4;232)].\n\nConclusionsWe report the characteristics and outcome of patients with ARDS and COVID-19. We found six independent factors associated with the mortality risk: delta lymphocyte count, delta ventilatory ratio, BMI, norepinephrine support, no AKI/AKI 1, and bacterial coinfection.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Alvaro Quijano-Angarita",
-        "author_inst": "Instituto de Evaluacion Tecnologica en Salud - IETS"
+        "author_name": "GUSTAVO LUGO GOYTIA",
+        "author_inst": "INSTITUTO NACIONAL DE ENFERMEDADES RESPIRATORIAS ISMAEL COSIO VILLEGAS"
       },
       {
-        "author_name": "Oscar Espinosa",
-        "author_inst": "Instituto de Evaluacion Tecnologica en Salud - IETS"
+        "author_name": "Carmen Hernandez-Cardenas,",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
       },
       {
-        "author_name": "Marcela M Mercado-Reyes",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Carlos Torruco-Sotelo",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
       },
       {
-        "author_name": "Diana Walteros",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Felipe Jurado",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
       },
       {
-        "author_name": "Diana Carolina Malo",
-        "author_inst": "Instituto Nacional de Salud"
+        "author_name": "Hector Serna-secundino",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
+      },
+      {
+        "author_name": "Cristina Aguilar",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
+      },
+      {
+        "author_name": "Jose Garcia-Olanzaran",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
+      },
+      {
+        "author_name": "Diana Hernandez-Garcia",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "intensive care and critical care medicine"
   },
   {
     "rel_doi": "10.1101/2020.09.13.20193532",
@@ -1141153,107 +1144041,67 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.09.20184143",
-    "rel_title": "The Effect of Early Hydroxychloroquine-based Therapy in COVID-19 Patients in Ambulatory Care Settings: A Nationwide Prospective Cohort Study",
+    "rel_doi": "10.1101/2020.09.11.20180521",
+    "rel_title": "On Machine Learning-Based Short-Term Adjustment of Epidemiological Projections of COVID-19 in US",
     "rel_date": "2020-09-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20184143",
-    "rel_abs": "ABSTRACT BACKGROUND: Currently, there is no proven effective therapy nor vaccine for the treatment of SARS-CoV-2. Evidence regarding the potential benefit of early administration of hydroxychloroquine (HCQ) therapy in symptomatic patients with Coronavirus Disease (COVID-19) is not clear. METHODS: This observational prospective cohort study took place in 238 ambulatory fever clinics in Saudi Arabia, which followed the Ministry of Health (MOH) COVID-19 treatment guideline. This guideline included multiple treatment options for COVID-19 based on the best available evidence at the time, among which was Hydroxychloroquine (HCQ). Patients with confirmed COVD-19 (by reverse transcriptase polymerase chain reaction (PCR) test) who presented to these clinics with mild to moderate symptoms during the period from 5-26 June 2020 were included in this study. Our study looked at those who received HCQ-based therapy along with supportive care (SC) and compared them to patients who received SC alone. The primary outcome was hospital admission within 28-days of presentation. The secondary outcome was a composite of intensive care admission (ICU) and/or mortality during the follow-up period. Outcome data were assessed through a follow-up telephonic questionnaire at day 28 and were further verified with national hospitalisation and mortality registries. Multiple logistic regression model was used to control for prespecified confounders. RESULTS: Of the 7,892 symptomatic PCR-confirmed COVID-19 patients who visited the ambulatory fever clinics during the study period, 5,541 had verified clinical outcomes at day 28 (1,817 patients in the HCQ group vs 3,724 in the SC group). At baseline, patients who received HCQ therapy were more likely to be males who did not have hypertension or chronic lung disease compared to the SC group. No major differences were noted regarding other comorbid conditions. All patients were presenting with active complaints; however, the HCQ groups had higher rates of symptoms compared to the SC group (fever: 84% vs 66.3, headache: 49.8 vs 37.4, cough: 44.5 vs 35.6, respectively). Early HCQ-based therapy was associated with a lower hospital admission within 28-days compared to SC alone (9.4% compared to 16.6%, RRR 43%, p-value <0.001). The composite outcome of ICU admission and/or mortality at 28-days was also lower in the HCQ group compared to the SC (1.2% compared to 2.6%, RRR 54%, p-value 0.001). Adjusting for age, gender, and major comorbid conditions, a multivariate logistic regression model showed a decrease in the odds of hospitalisation in patients who received HCQ compared to SC alone (adjusted OR 0.57 [95% CI 0.47-0.69], p-value <0.001). The composite outcome of ICU admission and/or mortality was also lower for the HCQ group compared to the SC group controlling for potential confounders (adjusted OR 0.55 [95% CI 0.34-0.91], p-value 0.019). CONCLUSION: Early intervention with HCQ-based therapy in patients with mild to moderate symptoms at presentation is associated with lower adverse clinical outcomes among COVID-19 patients, including hospital admissions, ICU admission, and/or death.",
-    "rel_num_authors": 22,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.11.20180521",
+    "rel_abs": "Epidemiological models have provided valuable information for the outlook of COVID-19 pandemic and relative impact of different mitigation scenarios. However, more accurate forecasts are often needed at near term for planning and staffing. We present our early results from a systemic analysis of short-term adjustment of epidemiological modeling of COVID 19 pandemic in US during March-April 2020. Our analysis includes the importance of various types of features for short term adjustment of the predictions. In addition, we explore the potential of data augmentation to address the data limitation for an emerging pandemic. Following published literature, we employ data augmentation via clustering of regions and evaluate a number of clustering strategies to identify early patterns from the data. From our early analysis, we used CovidActNow as our underlying epidemiological model and found that the most impactful features for the one-day prediction horizon are population density, workers in commuting flow, number of deaths in the day prior to prediction date, and the autoregressive features of new COVID-19 cases from three previous dates of the prediction. Interestingly, we also found that counties clustered with New York County resulted in best preforming model with maximum of R2= 0.90 and minimum of R2= 0.85 for state-based and COVID-based clustering strategy, respectively.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Tarek Sulaiman",
-        "author_inst": "King Fahad Medical City, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Abdulrhman Mohana",
-        "author_inst": "Saudi Center for Disease Prevention and Control"
-      },
-      {
-        "author_name": "Laila Alawdah",
-        "author_inst": "King Fahad Medical City, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Nagla Mahmoud",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Mustafa Hassanein",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Tariq Wani",
-        "author_inst": "King Fahad Medical City, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Amel Alfaifi",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Eissa Alenazi",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Nashwa Radwan",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
-      },
-      {
-        "author_name": "Nasser AlKhalifah",
-        "author_inst": "King Fahad Medical City, Riyadh. Saudi Arabia"
-      },
-      {
-        "author_name": "Ehab Elkady",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Sarah KEFAYATI",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Manwer AlAnazi",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Hu Huang",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Mohammed Alqahtani",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Prithwish Chakraborty",
+        "author_inst": "IBM Research"
       },
       {
-        "author_name": "Khalid Abdalla",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Fred Roberts",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Yousif Yousif",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Vishrawas Gopalakrishnan",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Fouad AboGazalah",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Raman Srinivasan",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Fuad Awwad",
-        "author_inst": "Quantitative analysis department, College of Business Administration, King Saud University, Riyadh, Saudi Arabia"
+        "author_name": "Sayali Pethe",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Khaled AlabdulKareem",
-        "author_inst": "Assisting Deputyship for Primary Health Care, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Piyush Madan",
+        "author_inst": "IBM Research"
       },
       {
-        "author_name": "Fahad AlGhofaili",
-        "author_inst": "King Fahad Medical City, Riyadh. Saudi Arabia"
+        "author_name": "Ajay Deshpande",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Ahmed AlJedai",
-        "author_inst": "Assistant Deputy Minister for Therapeutic Affairs, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Xuan Liu",
+        "author_inst": "IBM Watson Health"
       },
       {
-        "author_name": "Hani Jokhdar",
-        "author_inst": "Deputyship of Public Health, Ministry of Health, Riyadh, Saudi Arabia"
+        "author_name": "Jianying Hu",
+        "author_inst": "IBM Research"
       },
       {
-        "author_name": "Fahad Alrabiah",
-        "author_inst": "King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia"
+        "author_name": "Gretchen Jackson",
+        "author_inst": "IBM Watson Health"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.09.11.20192971",
@@ -1142927,27 +1145775,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.10.20192195",
-    "rel_title": "Mathematical Modeling and a Month Ahead Forecast of the Coronavirus Disease 2019 (COVID-19) Pandemic: An Indian Scenario",
+    "rel_doi": "10.1101/2020.09.11.20192450",
+    "rel_title": "Impacts of the COVID-19 epidemic on the department of stomatology in a tertiary hospital: a case study in the General Hospital of the Central Theater Command, Wuhan, China",
     "rel_date": "2020-09-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20192195",
-    "rel_abs": "India, the second-most populous country in the world, has been lately witnessing a daily surge in the COVID-19 infected cases. India is currently among the worst-hit nations worldwide, due to the COVID-19 pandemic, and ranks just behind Brazil and USA. In order to prevent the further worsening of the situation, predicting the future course of the pandemic is of utmost importance. In this paper, we model the past trajectory (March 01, 2020 - July 25, 2020) and make a month-long (July 26, 2020 - August 24, 2020) forecast of the future evolution of the COVID-19 pandemic in India using an autoregressive integrated moving average (ARIMA) model. According to our forecasting results, India is likely to have 3,800,989 cumulative infected cases, 1,634,142 cumulative active cases, 2,110,697 cumulative recoveries and 56,150 cumulative deaths by August 24, 2020, if the current trend of the pandemic continues to prevail. The implications of these forecasts are that in the upcoming month the infection rate of COVID-19 in India is going to escalate, while as the rate of recovery and the case-fatality rate is likely to reduce. In order to avert these possible scenarios, the administration and health-care personnel need to formulate and implement robust control measures, while the general public needs to be more responsible and strictly adhere to the established and newly formulated guidelines to slow down the spread of the pandemic and prevent it from transforming into a catastrophe.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.11.20192450",
+    "rel_abs": "ObjectivesThe aim of this study is to depict the impacts of COVID-19 pandemic on the clinical services and academic activities in the department of stomatology of a tertiary hospitals in Wuhan, China.\n\nMethodsWe obtained historical data of the Department of Stomatology from the Health Information System of the General Hospital of Central Theater Command, Wuhan, China between January 2018 and June 2020. Line plots were used to illustrate temporal trend of the variables. Mean {+/-} standard deviation and median with interquartile range were used to summarize the variables. The Kruskal-Wallis equality-of-populations rank test was used to compare the difference between groups.\n\nResultsA significant decrease was noted in the monthly average number of patients seeking the outpatient services for the year 2020. The monthly numbers of patients seeking outpatient services were decreased by two thirds from 2018 to 2020. The number of emergency cases also decreased significantly by 64% in 2020. The monthly number of teaching hours decreased from 3.8 {+/-} 1.5 in 2018 and 4.7 {+/-} 1.4 in 2019 to 1.7 {+/-} 1.9 in 2020. The number of interns also decreased more than 70% in 2020.\n\nConclusionsThe impacts of COVID 19 in the stomatology clinic were significant with notable decreases in clinical services and education offered to the stomatology students. We must find solutions to keep as many as needed dental profession stay on thriving and to remain on the frontline of healthcare.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Suhail Ganiny",
-        "author_inst": "National Institute of Technology, Srinagar"
+        "author_name": "Qingshan Dong",
+        "author_inst": "Department of Stomatology, General Hospital of the Central Theater Command, Wuhan  Hubei Province, China"
+      },
+      {
+        "author_name": "Angelica Kuria",
+        "author_inst": "Department of Health, Nyandarua County, Kenya"
+      },
+      {
+        "author_name": "Yanming Weng",
+        "author_inst": "Department of Stomatology, General Hospital of the Central Theater Command, Wuhan  Hubei Province, China"
+      },
+      {
+        "author_name": "Yu Liu",
+        "author_inst": "Department of Stomatology, General Hospital of the Central Theater Command, Wuhan  Hubei Province, China"
       },
       {
-        "author_name": "Owais Nisar",
-        "author_inst": "SKUAST-K"
+        "author_name": "Yang Cao",
+        "author_inst": "Orebro University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "dentistry and oral medicine"
   },
   {
     "rel_doi": "10.1101/2020.09.09.20191270",
@@ -1144509,71 +1147369,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.11.20192526",
-    "rel_title": "Increased extravascular lung water index (EVLWI) reflects rapid inflammatory oedema and mortality in COVID-19 associated ARDS",
+    "rel_doi": "10.1101/2020.09.10.20191932",
+    "rel_title": "Evaluating the effects of cardiometabolic exposures on circulating proteins which may contribute to SARS-CoV-2 severity",
     "rel_date": "2020-09-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.11.20192526",
-    "rel_abs": "OBJECTIVENearly 5 % of the patients with COVID-19 develop an acute respiratory distress syndrome (ARDS). Extravascular lung water index (EVLWI) is a marker of pulmonary oedema which is associated with mortality in ARDS. In this study we evaluate whether EVLWI is higher in patients with COVID-19 associated ARDS as compared to controls and whether EVLWI has the potential to monitor disease progression.\n\nMETHODSFrom the day of intubation, EVLWI, cardiac function were monitored by transpulmonary thermodilution in n=25 patients with COVID-19 and compared to a control group of 49 non-COVID-19 ARDS-patients.\n\nRESULTSEVLWI in COVID-19-patients was noticeably elevated and significantly higher than in the control group (17 (11-38) vs. 11 (6-26) mL/kg; p<0.001). High pulmonary vascular permeability index values (2.9 (1.0-5.2) versus 1.9 (1.0-5.2); p=0.003) suggest inflammatory oedema. By contrast, the cardiac parameters SVI, GEF and GEDVI were comparable. High EVLWI values were associated with viral persistence, prolonged intensive care treatment and mortality (23.2{+/-}6.7% vs. 30.3{+/-}6.0%, p=0.025).\n\nCONCLUSIONSCompared to the control group, COVID-19 results in markedly elevated EVLWI-values in patients with ARDS. EVLWI reflects a non-cardiogenic pulmonary oedema in COVID-19 associated ARDS and could serve as parameter to monitor ARDS progression.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20191932",
+    "rel_abs": "Background: Developing insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of critical importance to overcome the global pandemic caused by coronavirus disease 2019 (covid-19). In this study, we have applied Mendelian randomization (MR) to systematically evaluate the effect of 10 cardiometabolic risk factors and genetic liability to lifetime smoking on 97 circulating host proteins postulated to either interact or contribute to the maladaptive host response of SARS-CoV-2. Methods: We applied the inverse variance weighted (IVW) approach and several robust MR methods in a two-sample setting to systemically estimate the genetically predicted effect of each risk factor in turn on levels of each circulating protein. Multivariable MR was conducted to simultaneously evaluate the effects of multiple risk factors on the same protein. We also applied MR using cis-regulatory variants at the genomic location responsible for encoding these proteins to estimate whether their circulating levels may influence SARS-CoV-2 severity. Findings: In total, we identified evidence supporting 105 effects between risk factors and circulating proteins which were robust to multiple testing corrections and sensitivity analyses. For example, body mass index provided evidence of an effect on 23 circulating proteins with a variety of functions, such as inflammatory markers c-reactive protein (IVW Beta=0.34 per standard deviation change, 95% CI=0.26 to 0.41, P=2.19x10-16) and interleukin-1 receptor antagonist (IVW Beta=0.23, 95% CI=0.17 to 0.30, P=9.04x10-12). Further analyses using multivariable MR provided evidence that the effect of BMI on lowering immunoglobulin G, an antibody class involved in protecting the body from infection, is substantially mediated by raised triglycerides levels (IVW Beta=-0.18, 95% CI=-0.25 to -0.12, P=2.32x10-08, proportion mediated=44.1%). The strongest evidence that any of the circulating proteins highlighted by our initial analysis influence SARS-CoV-2 severity was identified for soluble glycoprotein 130 (odds ratio=1.81, 95% CI=1.25 to 2.62, P=0.002), a signal transductor for interleukin-6 type cytokines which are involved in the bodys inflammatory response. However, based on current case samples for severe SARS-CoV-2 we were unable to replicate findings in independent samples. Interpretation: Our findings highlight several key proteins which are influenced by established exposures for disease. Future research to determine whether these circulating proteins mediate environmental effects onto risk of SARS-CoV-2 are warranted to help elucidate therapeutic strategies for covid-19 disease severity.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Sebastian Rasch",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
-      },
-      {
-        "author_name": "Paul Schmidle",
-        "author_inst": "Technical University of Munich, School of Medicine, Department of Dermatology and Allergology, Biedersteiner Str. 29, 80802 Munich"
-      },
-      {
-        "author_name": "Senguel Sancak",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
-      },
-      {
-        "author_name": "Alexander Herner",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
-      },
-      {
-        "author_name": "Christina Huberle",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
-      },
-      {
-        "author_name": "Dominik Schulz",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
-      },
-      {
-        "author_name": "Ulrich Mayr",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
-      },
-      {
-        "author_name": "Jochen Schneider",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
-      },
-      {
-        "author_name": "Christoph Spinner",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
+        "author_name": "Tom G Richardson",
+        "author_inst": "MRC Integrative Epidemiology Unit"
       },
       {
-        "author_name": "Fabian Geisler",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
+        "author_name": "Si Fang",
+        "author_inst": "MRC Integrative Epidemiology Unit"
       },
       {
-        "author_name": "Roland M. Schmid",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
+        "author_name": "Ruth E Mitchell",
+        "author_inst": "MRC Integrative Epidemiology Unit"
       },
       {
-        "author_name": "Tobias Lahmer",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
+        "author_name": "Michael V Holmes",
+        "author_inst": "MRC Population Health Research Unit"
       },
       {
-        "author_name": "Wolfgang Huber",
-        "author_inst": "Technical University of Munich, School of Medicine, University hospital rechts der Isar, Department of Internal Medicine II, Ismaninger Str. 22, 81675 Munich, G"
+        "author_name": "George Davey Smith",
+        "author_inst": "MRC Integrative Epidemiology Unit"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "intensive care and critical care medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.09.09.20191296",
@@ -1146087,35 +1148915,35 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.09.09.20191700",
-    "rel_title": "Altered blood cell traits underlie a major genetic locus of severe COVID-19",
+    "rel_doi": "10.1101/2020.09.08.20190884",
+    "rel_title": "Prison population reductions and COVID-19: A latent profile analysis synthesizing recent evidence from the Texas state prison system",
     "rel_date": "2020-09-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20191700",
-    "rel_abs": "PurposeThe genetic locus 3p21.31 has been associated with severe coronavirus disease 2019 (COVID-19), but the underlying pathophysiological mechanism is unknown.\n\nMethodsTo identify intermediate traits of the COVID-19 risk variant, we performed a phenome-wide association study (PheWAS) with 923 phenotypes in 310,999 European individuals from UK Biobank. For candidate target genes, we examined associations between their expression and the polygenic score (PGS) of 1,263 complex traits in a meta-analysis of 31,684 blood samples.\n\nResultsOur PheWAS identified and replicated multiple blood cell traits to be associated with the COVID-19 risk variant, including monocyte count and percentage (p = 1.07x10-8, 4.09x10-13), eosinophil count and percentage (p = 5.73x10-3, 2.20x10-3), and neutrophil percentage (p = 3.23x10-3). The PGS analysis revealed positive associations between the expression of candidate genes and genetically predicted counts of specific blood cells: CCR3 with eosinophil and basophil (p = 5.73x10-21, 5.08x10-19); CCR2 with monocytes (p = 2.40x10-10); and CCRl with monocytes and neutrophil (p = 1.78x10-6, 7.17x10-5).\n\nConclusionsMultiple blood cell traits, especially monocyte, eosinophil, and neutrophil numbers, are associated with the COVID-19 risk variant and the expression of its candidate target genes, representing probable mechanistic links between the genetic locus 3p21.31 and severe COVID-19.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.08.20190884",
+    "rel_abs": "ImportancePeople in prison are particularly vulnerable to infectious disease due to close living conditions and the lack of protective equipment. Public health professionals and prison administrators seek information to guide best practices regarding prison population to capacity rates for the COVID-19 outbreak.\n\nObjectiveUsing latent profile analysis, we sought to characterize Texas prisons on levels of COVID-19 cases and deaths among incarcerated residents, and COVID-19 cases among prison staff.\n\nDesignThis observational study was a secondary data analysis of publicly available data from the Texas Department of Criminal Justice (TBDJ). Data were downloaded and analyzed on July 24, 2020. This project was completed in collaboration with the COVID Prison Project.\n\nSettingOne-hundred and three prisons in the state of Texas.\n\nParticipantsThe unit of analysis is the individual prison units that comprise the TDCJ.\n\nExposuresNone\n\nMain Outcomes and MeasuresLatent profiles on levels of incarcerated resident COVID-19 cases, staff COVID-19 cases, and incarcerated resident COVID-19 deaths.\n\nResultsWe identified relevant profiles from the data: a low outbreak profile, a high outbreak profile, and a high death profile. Additionally, current prison population and level of employee staffing predicted membership in the high outbreak and high death profiles when compared to the low outbreak profile.\n\nConclusions and RelevanceHousing persons at 85% of prison capacity may minimize the risk of infection and death related to COVID-19. Implementing this 85% standard as an absolute minimum should be prioritized at prisons across the US.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSIs there a population to capacity ratio for prisons to successfully reduce the number of COVID-19 infections and deaths among its incarcerated populations?\n\nFindingsThe prisons that were most effective in reducing prison outbreaks and deaths operated at 85% of their current capacity.\n\nMeaningPrisons should operate at 85% of capacity or less to successfully minimize the harmful effects of COVID-19 on incarcerated populations.",
     "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Jingqi Zhou",
-        "author_inst": "University of Georgia"
+        "author_name": "Noel A. Vest",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Yitang Sun",
-        "author_inst": "University of Georgia"
+        "author_name": "Oshea D. Johnson",
+        "author_inst": "University of Miami"
       },
       {
-        "author_name": "Weishan Huang",
-        "author_inst": "Louisiana State University"
+        "author_name": "Kathryn M Nowotny",
+        "author_inst": "University of Miami"
       },
       {
-        "author_name": "Kaixiong Ye",
-        "author_inst": "University of Georgia"
+        "author_name": "Lauren Brinkley-Rubinstein",
+        "author_inst": "University of North Carolina"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "genetic and genomic medicine"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2020.09.08.20190751",
@@ -1147601,21 +1150429,25 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.09.07.20188003",
-    "rel_title": "The Geography of Excess Deaths in England during the Covid-19 pandemic: Longer term impacts and monthly dynamics",
+    "rel_doi": "10.1101/2020.09.04.20188235",
+    "rel_title": "Trend prediction of COVID-19 based on ARIMA model in mainland of China",
     "rel_date": "2020-09-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.07.20188003",
-    "rel_abs": "Physical social interaction relevant to the spread of infectious diseases occurs, by its nature, at a local level. If infection and related mortality are associated with social background, it is therefore natural to study variation in them in relation to the social composition of local areas. The first part of the paper studies the geographical impact of Covid-19 infection on age-standardised sex-specific excess death rates during the peak months of the pandemic so far, March through May 2020. The second part examines monthly mortality dynamics in relation to predictions from a spatial SIR (Susceptible, Infected, Recovered) model of infection introduced by Bisin and Moro (2020). The analysis indicates that during the peak months of the Covid-19 pandemic, a larger non-white population and higher social deprivation in an area were associated with higher excess mortality, particularly among men. Regarding dynamics, higher population density accelerated the growth in mortality during the upsurge in infection and increased its rate of decline after the peak of the epidemic, thereby producing a more peaked mortality profile. There is also evidence of a slower post-peak decline in mortality in more socially deprived areas but a more rapid decline in areas with a larger non-white population.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20188235",
+    "rel_abs": "The ongoing pandemic of COVID-19 has aroused widespread concern around the world and poses a severe threat to public health worldwide. In this paper, the autoregressive integrated moving average (ARIMA) model was used to predict the epidemic trend of COVID-19 in mainland of China. We collected the cumulative cases, cumulative deaths, and cumulative recovery in mainland of China from January 20 to June 30, 2020, and divided the data into experimental group and test group. The ARIMA model was fitted with the experimental group data, and the optimal model was selected for prediction analysis. The predicted data were compared with the test group. The average relative errors of actual cumulative cases, deaths, recovery and predicted values in each province are between -22.32%-22.66%, -9.52%-0.08%, -8.84%-1.16, the results of the comprehensive experimental group and test group show The error of fitting and prediction is small, the degree of fitting is good, the model supports and is suitable for the prediction of the epidemic situation, which has practical guiding significance for the prevention and control of the epidemic situation.\n\nHighlightsO_LIWe predicted future COVID-19 occurrences in mainland of China based on ARIMA model.\nC_LIO_LIWe validated the model based on the previous outbreak data with actual data for June, 2020.\nC_LIO_LIThe measures taken by the government have contained spread of the epidemic\nC_LIO_LIThe combination of multiple models may improve the robustness of the model\nC_LI",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Richard Breen",
-        "author_inst": "University of Oxford"
+        "author_name": "Han Chuqiao",
+        "author_inst": "Xinjiang University"
       },
       {
-        "author_name": "John Ermisch",
-        "author_inst": "University of Oxford"
+        "author_name": "Ju xifeng",
+        "author_inst": "xinjiang University"
+      },
+      {
+        "author_name": "zheng jianghua",
+        "author_inst": "Xinjiang University"
       }
     ],
     "version": "1",
@@ -1149247,29 +1152079,33 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.09.08.20190397",
-    "rel_title": "The impact of COVID-19 restriction measures on loneliness among older adults in Austria",
+    "rel_doi": "10.1101/2020.09.08.20190470",
+    "rel_title": "Modelling the epidemic growth of preprints on COVID-19 and SARS-CoV-2",
     "rel_date": "2020-09-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.08.20190397",
-    "rel_abs": "BackgroundTo halt the spread of COVID-19, Austria implemented a 7-week  shut-down of public life in March/April 2020 which was followed by a gradual withdrawal of these restriction measures in May/June 2020. We expect that the ensuing reduction in social contacts led to increased loneliness among older adults (60+).\n\nMethodsWe conducted three analyses to assess the association between COVID-19 public health restriction measures and loneliness: (1) A comparison between pre-pandemic (SHARE: 2013-2017) and pandemic (May 2020) levels of loneliness (UCLA-3 scale), (2) an analysis of the correlation between being affected by COVID-19 restriction measures and loneliness based on cross-sectional survey data from early May 2020, and (3) a longitudinal analysis of weekly changes in loneliness (Corona panel data) from late March to early June 2020.\n\nResultsWe found (1) loneliness levels to have increased in 2020 in comparison with previous years, (2) an association between the number of restriction measures older adults reported to be affected from and loneliness, and (3) that loneliness was higher during  shut-down compared to the subsequent re-opening phase, particularly among those who live alone.\n\nDiscussionOur results provide evidence that COVID-19 restriction measures in Austria have indeed resulted in increased levels of loneliness among older adults. However, these effects seem to be short-lived, and thus we do not expect strong negative consequences for older adults mental health downstream. Nonetheless, effects of longer and/or repeated future restriction measures aiming at social distancing should be closely monitored.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.08.20190470",
+    "rel_abs": "The response of the scientific community to the global health emergency caused by the COVID-19 pandemic has produced an unprecedented number of manuscripts in a short period of time, the vast majority of which have been shared in the form of preprints posted on online preprint repositories before peer review. This surge in preprint publications has in itself attracted considerable attention, although mostly in the bibliometrics literature. In the present study we apply a mathematical growth model, known as the generalized Richards model, to describe the time evolution of the cumulative number of COVID-19 related preprints. This mathematical approach allows us to infer several important aspects concerning the underlying growth dynamics, such as its current stage and its possible evolution in the near future. We also analyze the rank-frequency distribution of preprints servers, ordered by the number of COVID-19 preprints they host, and find that it follows a power law in the low rank (high frequency) region, with the high rank (low frequency) tail being better described by a q-exponential function. The Zipf-like law in the high frequency regime indicates the presence of a cumulative advantage effect, whereby servers that already have more preprints receive more submissions.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Erwin Stolz",
-        "author_inst": "Medical University of Graz"
+        "author_name": "Giovani L. Vasconcelos",
+        "author_inst": "Universidade Federal do Parana"
       },
       {
-        "author_name": "Hannes Mayerl",
-        "author_inst": "Medical University of Graz"
+        "author_name": "Luan P. Cordeiro",
+        "author_inst": "Universidade Federal do Parana"
       },
       {
-        "author_name": "Wolfgang Freidl",
-        "author_inst": "Medical University of Graz"
+        "author_name": "Gerson C. Duarte-Filho",
+        "author_inst": "Universidade Federal de Sergipe"
+      },
+      {
+        "author_name": "Arthur A. Brum",
+        "author_inst": "Universidade Federal de Pernambuco"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1151213,45 +1154049,65 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.09.06.20189480",
-    "rel_title": "Antibody Responses to SARS-CoV-2 in Coronavirus Diseases 2019 Patients with Different Severity",
+    "rel_doi": "10.1101/2020.09.05.20188821",
+    "rel_title": "Ethnicity and clinical outcomes in COVID-19A Systematic Review and Meta-analysis",
     "rel_date": "2020-09-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.06.20189480",
-    "rel_abs": "BackgroundMore understanding of antibody responses in the SARS-CoV-2 infected population is useful for vaccine development.\n\nAimTo investigate SARS-CoV-2 IgA and IgG among COVID-19 Thai patients with different severity.\n\nMethodsWe used plasma from 118 adult patients who have confirmed SARS-CoV-2 infection and 49 patients under investigation without infection, 20 patients with other respiratory infections, and 102 healthy controls. Anti-SARS-CoV-2 IgA and IgG were performed by enzyme-linked immunosorbent assay from Euroimmun. The optical density ratio cut off for positive test was 1.1 for IgA and 0.8 for IgG. The association of antibody response with the severity of diseases and the day of symptoms was performed.\n\nResultsFrom Mar 10 to May 31, 2020, 289 participants were enrolled, and 384 samples were analyzed. Patients were categorized by clinical manifestations to mild (n = 59), moderate (n = 27) and severe (n = 32). The overall sensitivity of IgA and IgG from samples collected after day 7 is 87.9% (95% CI 79.8-93.6) and 84.8% (95% CI 76.2-91.3), respectively. The severe group had a significantly higher level of specific IgA and IgG to S1 antigen compared to the mild group. All moderate to severe patients have specific IgG while 20% of the mild group did not have any IgG detected after two weeks. Interestingly, SARS-CoV-2 IgG level was significantly higher in males compared to females among the severe group (p = 0.003).\n\nConclusionThe serologic test for SARS-CoV-2 has high sensitivity after the second week after onset of illness. Serological response differs among patients with different severity and different sex.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.05.20188821",
+    "rel_abs": "ImportanceThe association of ethnicity with outcomes in patients with COVID-19 is unclear.\n\nObjectiveTo determine whether the risk of SARS-CoV-2 infection, COVID-19 intensive care unit (ICU) admission and mortality are associated with ethnicity.\n\nData SourcesWe searched all English language articles published 1st December 2019 - 30th June 2020 within MEDLINE, EMBASE, PROSPERO and the Cochrane library using indexing terms for COVID-19 and ethnicity, as well as manuscripts awaiting peer review on MedRxiv during the same period.\n\nStudy SelectionIncluded studies reported original clinical data, disaggregated by ethnicity, on patients with confirmed or suspected COVID-19. We excluded correspondence, area level, modelling and basic science articles. Two independent reviewers screened articles for inclusion. Of 926 identified articles, 35 were included in the meta-analyses.\n\nData Extraction and SynthesisThe review was conducted according to PRISMA guidelines. Reviewers independently extracted data using a piloted form on: (1) rates of infection, ICU admission and mortality by ethnicity; and (2) unadjusted and adjusted data comparing ethnic minority and White groups. Data were pooled using random effects models.\n\nMain Outcomes and MeasuresOutcomes were: (1) infection with SARS-CoV-2 confirmed on molecular testing; (2) ICU admission; and (3) mortality in COVID-19 confirmed and suspected cases.\n\nResults13,535,562 patients from 35 studies were included in the meta-analyses. Black, Asian and Hispanic individuals had a greater risk of infection compared to White individuals (Black: pooled adjusted RR: 2.06, 95% CI: 1.59-2.67; Asian: 1.35, 95%CI: 1.15-1.59; Hispanic: 1.77, 95% CI: 1.39-2.25). Black individuals were significantly more likely to be admitted to ICU than White individuals (pooled adjusted RR: 1.61, 95% CI: 1.02-2.55). Risk of mortality was similar across ethnicities among hospitalised patients, but increased among Asian and Mixed ethnic groups in the general population.\n\nConclusionsBlack, Asian and Hispanic ethnic groups are at increased risk of SARS-CoV-2 infection. Black individuals may be more likely to require ICU admission for COVID-19. There may also be disparities in risk of death from COVID-19 at a population level. Our findings are of critical public health importance and should inform policy on minimising SARS-CoV-2 exposure in ethnic minority groups.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSIs ethnicity associated with vulnerability to, and outcomes from, coronavirus disease 2019 (COVID-19)?\n\nFindingsIn this systematic review and meta-analysis, rates of infection and outcomes from COVID-19 were compared between ethnic groups. Individuals from Black, Asian and Hispanic ethnicity were significantly more vulnerable to SARS-CoV-2 infection than those of White ethnicity. Black individuals were more likely to need intensive care unit (ICU) admission for COVID-19 than White individuals. Risk of mortality was similar across ethnicities among hospitalised patients, but increased among Asian and Mixed ethnic groups in the general population.\n\nMeaningThere is strong evidence for an increased risk of SARS-CoV-2 infection amongst ethnic minorities, and targeted public health policies are required to reduce this risk.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Ekasit Kowitdamrong",
-        "author_inst": "Faculty of Medicine, Chulalongkorn University"
+        "author_name": "Shirley Sze",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Thanyawee Puthanakit",
-        "author_inst": "Faculty of Medicine, Chulalongkorn University"
+        "author_name": "Daniel Pan",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Watsamon Jantarabenjakul",
-        "author_inst": "Faculty of Medicine, Chulalongkorn University"
+        "author_name": "Laura J Gray",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Eakachai Prompetchara",
-        "author_inst": "Faculty of Medicine, Chulalongkorn University"
+        "author_name": "Clareece R Nevill",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Pintip Suchartlikitwong",
-        "author_inst": "Faculty of Medicine, Chulalongkorn University"
+        "author_name": "Christopher A Martin",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Opass Putcharoen",
-        "author_inst": "Faculty of Medicine, Chulalongkorn University"
+        "author_name": "Joshua Nazareth",
+        "author_inst": "University of Leicester"
       },
       {
-        "author_name": "Nattiya Hirankarn",
-        "author_inst": "Faculty of Medicine, Chulalongkorn University"
+        "author_name": "Jatinder S Minhas",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Pip Divall",
+        "author_inst": "University Hospitals of Leicester NHS Trust"
+      },
+      {
+        "author_name": "Kamlesh Khunti",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Keith Abrams",
+        "author_inst": "University of Leicester"
+      },
+      {
+        "author_name": "Laura B Nellums",
+        "author_inst": "University of Nottingham"
+      },
+      {
+        "author_name": "Manish Pareek",
+        "author_inst": "University of Leicester"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1154051,67 +1156907,195 @@
     "category": "emergency medicine"
   },
   {
-    "rel_doi": "10.1101/2020.09.04.20185645",
-    "rel_title": "Predicting illness trajectory and hospital resource utilization of COVID-19 hospitalized patients - a nationwide study",
+    "rel_doi": "10.1101/2020.09.04.20184523",
+    "rel_title": "MOLECULAR EPIDEMIOLOGY TO UNDERSTAND THE SARS-CoV-2 EMERGENCE IN THE BRAZILIAN AMAZON REGION",
     "rel_date": "2020-09-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20185645",
-    "rel_abs": "BackgroundThe spread of COVID-19 has led to a severe strain on hospital capacity in many countries. There is a need for a model to help planners assess expected COVID-19 hospital resource utilization.\n\nMethodsRetrospective nationwide cohort study following the day-by-day clinical status of all hospitalized COVID-19 patients in Israel from March 1st to May 2nd, 2020. Patient clinical course was modelled with a machine learning approach based on a set of multistate Cox regression-based models with adjustments for right censoring, recurrent events, competing events, left truncation, and time-dependent covariates. The model predicts the patients entire disease course in terms of clinical states, from which we derive the patients hospital length-of-stay, length-of-stay in critical state, the risk of in-hospital mortality, and total and critical care hospital-bed utilization. Accuracy assessed over eight cross-validation cohorts of size 330, using per-day Mean Absolute Error (MAE) of predicted hospital utilization averaged over 64 days; and area under the receiver operating characteristics (AUROC) for individual risk of critical illness and in-hospital mortality, assessed on the first day of hospitalization. We present predicted hospital utilization under hypothetical incoming patient scenarios.\n\nFindingsDuring the study period, 2,703 confirmed COVID-19 patients were hospitalized in Israel. The per-day MAEs for total and critical-care hospital-bed utilization, were 4{middle dot}72 {+/-} 1{middle dot}07 and 1{middle dot}68 {+/-} 0{middle dot}40 respectively; the AUROCs for prediction of the probabilities of critical illness and in-hospital mortality were 0{middle dot}88 {+/-} 0{middle dot}04 and 0{middle dot}96 {+/-} 0{middle dot}04, respectively. We further present the impact of several scenarios of patient influx on healthcare system utilization, and provide an R software package for predicting hospital-bed utilization.\n\nInterpretationWe developed a model that, given basic easily obtained data as input, accurately predicts total and critical care hospital utilization. The model enables evaluating the impact of various patient influx scenarios on hospital utilization and planning ahead of hospital resource allocation.\n\nFundingThe work was funded by the Israeli Ministry of Health. M.G. received support from the U.S.-Israel Binational Science Foundation (BSF, 2016126).\n\nO_TEXTBOXResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSCOVID19 outbreaks are known to lead to severe case load in hospital systems, stretching resources, partially due to the long hospitalizations needed for some of the patients. There is a crucial need for tools helping planners assess future hospitalization load, taking into account the specific characteristics and heterogeneity of currently hospitalized COVID19 patients, as well as the characteristics of incoming patients. We searched PubMed for articles published up to September 9, 2020, containing the words \"COVID19\" and combinations of \"hospital\", \"utilization\", \"resource\", \"capacity\" and \"predict\". We found 145 studies; out of them, several included models that predict the future trend of hospitalizations using compartment models (e.g. SIR models), or by using exponential or logistic models. We discuss two of the more prominent ones, which model explicitly the passage of patients through the ICU. These models (i) do not take into account individual patient characteristics; (ii) do not consider length-of-stay heterogeneity, despite the fact that bed utilization is in part determined by a long tail of patients requiring significantly longer stays than others; (iii) do not correct for competing risks bias. We further searched for studies containing the words \"COVID19\" and \"multistate\", and \"COVID19\" and \"length\" and \"stay\". Out of 317 papers, we found two using multistate models focusing only on patients undergoing ECMO treatment.\n\nAdded value of this studyWe present the first model predicting hospital load based on the individual characteristics of hospitalized patients: age, sex, clinical state, and time already spent in-hospital. We combine this with scenarios for incoming patients, allowing for variations by age, sex and clinical state. The models precise predictions are based on a large sample of complete, day-by-day disease trajectories of patients, with a full coverage of the entire COVID-19 hospitalized population in Israel up to early May, 2020 (n =2, 703). We provide the model, as well as software for fitting such a model to local data, and an anonymized version of the dataset used to create the model.\n\nImplications of all the available evidenceAccurate predictions for hospital utilization can be made based on easy to obtain patient data: age, sex, and patient clinical state (moderate, severe or critical). The model allows hospital-and regional-level planners to allocate resources in a timely manner, preparing for different patient influx scenarios.\n\nC_TEXTBOX",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20184523",
+    "rel_abs": "The COVID-19 pandemic in Brazil has demonstrated an important public health impact, as has been observed in the world. In Brazil, the Amazon Region contributed with a large number of cases of COVID-19, especially in the beginning of the circulation of SARS-CoV-2 in the country. Thus, we describe the epidemiological profile of COVID-19 and the genetic diversity of SARS-CoV-2 strains circulating in the Amazon Region. We observe an extensive spread of virus in this Brazilian site. The data on sex, age and symptoms presented by the investigated individuals were similar to what has been observed worldwide. The genomic analysis of the viruses revealed important amino acid changes, including the D614G and the I33T in Spike and ORF6 proteins, respectively. The latter found in strains originating in Brazil. The phylogenetic analyzes demonstrated the circulation of the lineages B.1 and B.1.1, whose circulation in Brazil has already been previous reported. Our data reveals molecular epidemiology of SARS-CoV-2 in the Amazon Region. These findings also reinforce the importance of continuous genomic surveillance this virus with the aim of providing accurate and updated data to understand and map the transmission network of this agent in order to subsidize operational decisions in public health.",
+    "rel_num_authors": 44,
     "rel_authors": [
       {
-        "author_name": "Michael Roimi",
-        "author_inst": "Rambam Health Care Campus"
+        "author_name": "Mirleide C dos Santos",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Rom Gutman",
-        "author_inst": "Technion - Israel Institute of Technology"
+        "author_name": "Edivaldo Costa Sousa Jr.",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Jonathan Somer",
-        "author_inst": "Technion - Israel Institute of Technology"
+        "author_name": "Jessylene A Ferreira",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Asaf Ben Arie",
-        "author_inst": "Tel Aviv University"
+        "author_name": "Sandro P Silva",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Ido Calman",
-        "author_inst": "Independent"
+        "author_name": "Michel PC Souza",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Yaron Bar-Lavie",
-        "author_inst": "Rambam Health Care Campus"
+        "author_name": "Jedson F Cardoso",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Udi Gelbshtein",
-        "author_inst": "Israel Ministry of Health"
+        "author_name": "Amanda M Silva",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Sigal Liverant-Taub",
-        "author_inst": "Israel Ministry of Health"
+        "author_name": "Luana S Barbagelata",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Arnona Ziv",
-        "author_inst": "Gertner Institute for Epidemiology and Health Policy Research"
+        "author_name": "Wanderley D Chagas Jr.",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Danny Eytan",
-        "author_inst": "Technion - Israel Institute of Technology and Rambam Health Care Campus"
+        "author_name": "James L Ferreira",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Malka Gorfine",
-        "author_inst": "Tel Aviv University"
+        "author_name": "Edna MA Souza",
+        "author_inst": "Instituto Evandro Chagas"
       },
       {
-        "author_name": "Uri Shalit",
-        "author_inst": "Technion - Israeli Institute of Technology"
+        "author_name": "Patricia LA Vilaca",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Jainara CS Alves",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Michelle C Abreu",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Patricia S Lobo",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Fabiolla S Santos",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Alessandra AP Lima",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Camila M Bragagnolo",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Luana S Soares",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Patricia SM Almeida",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Darleise S Oliveira",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Carolina KN Amorim",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Iran B Costa",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Dielle M Teixeira",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Edvaldo T Penha Jr.",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Delana AM Bezerra",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Jones AM Siqueira",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Fernando N Tavares",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Felipe B Freitas",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Janete TN Rodrigues",
+        "author_inst": "Laboratorio Central de Saude Publica do Acre"
+      },
+      {
+        "author_name": "Janaina Mazaro",
+        "author_inst": "Laboratorio Central de Saude Publica do Acre"
+      },
+      {
+        "author_name": "Andreia S Costa",
+        "author_inst": "Laboratorio Central de Saude Publica do Amapa"
+      },
+      {
+        "author_name": "Marcia SP Cavalcante",
+        "author_inst": "Laboratorio Central de Saude Publica do Amapa"
+      },
+      {
+        "author_name": "Marineide Souza Silva",
+        "author_inst": "Laboratorio Central de Saude Publica do Amazonas"
+      },
+      {
+        "author_name": "Ilvanete A Silva",
+        "author_inst": "Laboratorio Central de Saude Publica do Para"
+      },
+      {
+        "author_name": "Gleissy AL Borges",
+        "author_inst": "Laboratorio Central de Saude Publica do Para"
+      },
+      {
+        "author_name": "Lidio G Lima",
+        "author_inst": "Laboratorio Central de Saude Publica do Maranhao"
+      },
+      {
+        "author_name": "Hivylla LS Ferreira",
+        "author_inst": "Laboratorio Central de Saude Publica do Maranhao"
+      },
+      {
+        "author_name": "Miriam TFP Livorati",
+        "author_inst": "Secretaria de Vigilancia em Saude"
+      },
+      {
+        "author_name": "Andre L Abreu",
+        "author_inst": "Secretaria de Vigilancia em Saude"
+      },
+      {
+        "author_name": "Arnaldo C Medeiros",
+        "author_inst": "Secretaria de Vigilancia em Saude"
+      },
+      {
+        "author_name": "Hugo R Resque",
+        "author_inst": "Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Rita CM Sousa",
+        "author_inst": "Programa de Pos Graduacao em Virologia - Instituto Evandro Chagas"
+      },
+      {
+        "author_name": "Giselle MR Viana",
+        "author_inst": "Instituto Evandro Chagas"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.09.04.20184721",
@@ -1155661,21 +1158645,57 @@
     "category": "hematology"
   },
   {
-    "rel_doi": "10.1101/2020.09.03.20187757",
-    "rel_title": "The role of school reopening in the spread of COVID-19",
+    "rel_doi": "10.1101/2020.09.03.20187062",
+    "rel_title": "College campuses and COVID-19 mitigation: clinical and economic value",
     "rel_date": "2020-09-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.03.20187757",
-    "rel_abs": "Many countries chose to close schools as part of their response to the SARS-CoV2 coronavirus (COVID-19) pandemic. Whilst nations are gradually reopening schools, and many politicians advise that schools remain safe and the risks of increases in the spread of COVID-19 are low, little evidence has been presented to confirm those statements.\n\nA review of the numbers of new confirmed COVID-19 cases by country suggests that the reopening of schools is likely to be a driver in the increase of the number of new cases. This is likely exacerbated by accompanying changes and easing of restrictions. However, with the exception of China, notable for its robust test, track, trace, and isolate processes, no other countries that had significant numbers of COVID-19 cases have successfully reopened schools without an increase in cases as a consequence.\n\nWhilst reopening of schools following an initial peak and decrease in COVID-19 infections is desirable for a range of reasons, doing so without adequate controls and protections may lead to an exacerbation of spread within the school environment, which could then lead to increased community spread of disease.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.03.20187062",
+    "rel_abs": "BackgroundDecisions around US college and university operations will affect millions of students and faculty amidst the COVID-19 pandemic. We examined the clinical and economic value of different COVID-19 mitigation strategies on college campuses.\n\nMethodsWe used the Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation that tracks infections accrued by students and faculty, accounting for community transmissions. Outcomes include infections, $/infection-prevented, and $/quality-adjusted-life-year ($/QALY). Strategies included extensive social distancing (ESD), masks, and routine laboratory tests (RLT). We report results per 5,000 students (1,000 faculty) over one semester (105 days).\n\nResultsMitigation strategies reduced COVID-19 cases among students (faculty) from 3,746 (164) with no mitigation to 493 (28) with ESD and masks, and further to 151 (25) adding RLTq3 among asymptomatic students and faculty. ESD with masks cost $168/infection-prevented ($49,200/QALY) compared to masks alone. Adding RLTq3 ($10/test) cost $8,300/infection-prevented ($2,804,600/QALY). If tests cost $1, RLTq3 led to a favorable cost of $275/infection-prevented ($52,200/QALY). No strategies without masks were cost-effective.\n\nConclusionExtensive social distancing with mandatory mask-wearing could prevent 87% of COVID-19 cases on college campuses and be very cost-effective. Routine laboratory testing would prevent 96% of infections and require low cost tests to be economically attractive.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Richard Beesley",
-        "author_inst": "Juvenile Arthritis Research"
+        "author_name": "Elena Losina",
+        "author_inst": "BWH"
+      },
+      {
+        "author_name": "Valia Leifer",
+        "author_inst": "Brigham and Women's Hospital"
+      },
+      {
+        "author_name": "Lucia Millham",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Christopher Panella",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Emily P. Hyle",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Amir M. Mohareb",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Anne M. Neilan",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Andrea L. Ciaranello",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Pooyan Kazemian",
+        "author_inst": "Case Western Reserve University"
+      },
+      {
+        "author_name": "Kenneth A. Freedberg",
+        "author_inst": "Massachusetts General Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1157175,111 +1160195,35 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.09.01.20185793",
-    "rel_title": "Prognostic accuracy of emergency department triage tools for children with suspected COVID-19: The PRIEST observational cohort study",
+    "rel_doi": "10.1101/2020.08.29.20184325",
+    "rel_title": "Face-masking, an acceptable protective measure against COVID-19: Findings of Ugandan high-risk groups",
     "rel_date": "2020-09-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20185793",
-    "rel_abs": "ObjectivesEmergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection.\n\nMethodsWe undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Childrens Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome.\n\nResultsWe collected data from 1530 children, including 26 (1.7%) with an adverse outcome. C-statistics were 0.80 (95% confidence interval 0.73-0.87) for the WHO algorithm, 0.80 (0.71-0.90) for POPS, 0.76 (0.67-0.85) for COAST, and 0.71 (0.59-0.82) for SFHPC. Using pre-specified thresholds, the WHO algorithm had the highest sensitivity (0.85) and lowest specificity (0.75), but POPS and COAST could optimise sensitivity (0.96 and 0.92 respectively) at the expense of specificity (0.25 and 0.38 respectively) by using a threshold of any score above zero instead of the pre-specified threshold.\n\nConclusionExisting triage tools have good but not excellent prediction for adverse outcome in children with suspected COVID-19. POPS and COAST could achieve an appropriate balance of sensitivity and specificity for supporting decisions to discharge home by considering any score above zero to be positive.\n\nRegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533",
-    "rel_num_authors": 23,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.29.20184325",
+    "rel_abs": "Face-masking could reduce the risk of COVID-19 transmission. We assessed: knowledge, attitudes, perceptions, and practices towards COVID-19 and face-mask use among 644 high risk-individuals in Kampala, Uganda. In data analysis, descriptive, bivariate and multivariate logistic regression analyses, with a 95% confidence interval were considered. Adjusted-odds ratios were used to determine the magnitude of associations. P-values < 0.05 were considered statistically-significant. Majority: 99.7% and 87.3% of the participants respectively had heard and believed that face-masks were protective against COVID-19, while 67.9% reported having received information on face-mask use. Males, food market vendors, those with no formal education, and those aged 24-33, 44-53 and 54-63 years were 0.58, 0.47, 0.25, 1.9, 2.12, and 3.39 times less likely to have received information about face-mask use respectively. Majority, 67.8% owned locally-made, non-medical face-masks, while 77.0% of face-mask owners believed that they knew the right procedure of wearing them. Those who had received information on face-mask use were 2.85 and 1.83 times more likely to own face-masks and to perceive them as protective. Food market vendors were 3.92 times more likely to re-use their face-masks. Our findings suggest that Ugandan high-risk groups have good knowledge, optimistic attitudes and perceptions, and relatively appropriate practices towards COVID-19.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Katie Biggs",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Ben Thomas",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Steve Goodacre",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Ellen Lee",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Laura Sutton",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Matthew Bursnall",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Amanda Loban",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Simon Waterhouse",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Richard Simmonds",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Carl Marincowitz",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Jose Schutter",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Sarah Connelly",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Elena Sheldon",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Jamie Hall",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Emma Young",
-        "author_inst": "University of Sheffield"
-      },
-      {
-        "author_name": "Andrew Bentley",
-        "author_inst": "Manchester University NHS Foundation Trust"
-      },
-      {
-        "author_name": "Kirsty Challen",
-        "author_inst": "Lancashire Teaching Hospitals NHS Foundation Trust"
-      },
-      {
-        "author_name": "Chris Fitzsimmons",
-        "author_inst": "Sheffield Children's NHS Foundation Trust"
-      },
-      {
-        "author_name": "Tim Harris",
-        "author_inst": "Barts Health NHS Trust"
-      },
-      {
-        "author_name": "Fiona Lecky",
-        "author_inst": "University of Sheffield"
+        "author_name": "Dickson Aruhomukama",
+        "author_inst": "Makerere University"
       },
       {
-        "author_name": "Andrew Lee",
-        "author_inst": "University of Sheffield"
+        "author_name": "Gerald Mboowa",
+        "author_inst": "Makerere University"
       },
       {
-        "author_name": "Ian Maconochie",
-        "author_inst": "Imperial College Healthcare NHS Trust"
+        "author_name": "David Musoke",
+        "author_inst": "Makerere University"
       },
       {
-        "author_name": "Darren Walter",
-        "author_inst": "Manchester University NHS Foundation Trust"
+        "author_name": "Douglas Bulafu",
+        "author_inst": "Makerere University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "emergency medicine"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.09.01.20184333",
@@ -1158665,45 +1161609,25 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.09.02.20186916",
-    "rel_title": "Maximizing and evaluating the impact of test-trace-isolate programs",
+    "rel_doi": "10.1101/2020.09.02.20186734",
+    "rel_title": "Could seasonal influenza vaccination influence COVID-19 risk?",
     "rel_date": "2020-09-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20186916",
-    "rel_abs": "September 2, 2020\n\nBackgroundTest-trace-isolate programs are an essential part of COVID-19 control that offer a more targeted approach than many other non-pharmaceutical interventions. Effective use of such programs requires methods to estimate their current and anticipated impact.\n\nMethods and FindingsWe present a mathematical modeling framework to evaluate the expected reductions in the reproductive number, R, from test-trace-isolate programs. This framework is implemented in a publicly available R package and an online application. We evaluated the effects of case detection, speed of isolation, contact tracing completeness and speed of quarantine using parameters consistent with COVID-19 transmission (R0 = 2.5, generation time 6.5 days). We show that R is most sensitive to changes to the proportion of infections detected in almost all scenarios, and other metrics have a reduced impact when case detection levels are low (< 30%). Although test-trace-isolate programs can contribute substantially to reducing R, exceptional performance across all metrics is needed to bring R below one through test-trace-isolate alone, highlighting the need for comprehensive control strategies. Formally framing the dynamical process also indicates that metrics used to evaluate performance of test-trace-isolate, such as the proportion of identified infections among traced contacts, may be misleading. While estimates of program performance are sensitive to assumptions about COVID-19 natural history, our qualitative findings are robust across numerous sensitivity analyses.\n\nConclusionsEffective test-trace-isolate programs first need to be strong in the \"test\" component, as case detection underlies all other program activities. Even moderately effective test-trace-isolate programs are an important tool for controlling the COVID-19 pandemic, and can alleviate the need for more restrictive social distancing measures.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20186734",
+    "rel_abs": "BackgroundWith possible resurgence of the SARS-CoV-2 and low seasonal influenza virus circulation next winter, reviewing evidence on a possible interaction between influenza vaccination and COVID-19 risk is important.\n\nObjectiveTo review studies on the effect of influenza vaccines on non-influenza respiratory disease (NIRD).\n\nMethodsUsing different search strategies, 18 relevant studies were identified and their strength, limitations and significance were assessed.\n\nResultsAnalysis of 4 RCT datasets did not suggest increased NIRD risk in recipients of live-attenuated vaccines (LAIV) and results of a cohort study suggested short-term protection consistent with the hypothesis of  trained immunity. One RCT, four cohort studies and one test-negative case-control suggested increased NIRD risk in recipients of inactivated influenza vaccines (IIV), whereas five test-negative case-control studies did not show an increased risk associated with a specific viral pathogen. Cross-protection against COVID-19 was suggested in one cross-sectional study on IIV but major biases could not be excluded. Results of four recent ecological studies on COVID-19 were challenging to interpret.\n\nConclusionsAvailable data on LAIV are reassuring but not all those on IIV. A drastic reorientation of 2020-2021 influenza campaigns is probably not warranted but studies aiming to test COVID-19 risk modification among recipients of seasonal influenza vaccines should be planned and funded.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Kyra H Grantz",
-        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Elizabeth C Lee",
-        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Lucy D'Agostino McGowan",
-        "author_inst": "Department of Mathematics and Statistics, Wake Forest University"
-      },
-      {
-        "author_name": "Kyu Han Lee",
-        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "C. Jessica E. Metcalf",
-        "author_inst": "Department of Ecology and Evolutionary Biology, Princeton University; Princeton School of Public and International Affairs, Princeton University"
-      },
-      {
-        "author_name": "Emily S Gurley",
-        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Philippe De wals",
+        "author_inst": "Laval University"
       },
       {
-        "author_name": "Justin Lessler",
-        "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Maziar Divangahi",
+        "author_inst": "McGill University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1160311,75 +1163235,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.09.01.20184101",
-    "rel_title": "Rapid 'mix and read' assay for scalable detection of SARS-CoV-2 antibodies in patient plasma",
+    "rel_doi": "10.1101/2020.09.02.20186742",
+    "rel_title": "The role of masks in reducing the risk of new waves of COVID-19 in low transmission settings: a modeling study",
     "rel_date": "2020-09-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20184101",
-    "rel_abs": "The human beta coronavirus SARS-CoV-2, causative virus of COVID-19, has infected more than 15 million people globally and continues to spread. Widespread, population level testing to detect active and past infections is critical to curb the COVID-19 pandemic. Antibody (serological) testing is the only option for detecting past infections outside the narrow window accessible to nucleic acid-based tests. However, currently available serological assays commonly lack scalability. Here, we describe the development of a rapid homogenous serological assay for the detection of antibodies to SARS-CoV-2 in patient plasma. We show that the fluorescence-based assay accurately detects seroconversion in COVID-19 patients from less than 1 L of plasma. Using a cohort of samples from COVID-19 infected or healthy individuals, we demonstrate detection with 100% sensitivity and specificity. This assay addresses an important need for a robust, low barrier to implementation, and scalable serological assay with complementary strengths to currently available serological platforms.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20186742",
+    "rel_abs": "ObjectivesTo evaluate the risk of a new wave of coronavirus disease 2019 (COVID-19) in a setting with ongoing low transmission, high mobility, and an effective test-and-trace system, under different assumptions about mask uptake.\n\nDesignWe used a stochastic agent-based microsimulation model to create multiple simulations of possible epidemic trajectories that could eventuate over a five-week period following prolonged low levels of community transmission.\n\nSettingWe calibrated the model to the epidemiological and policy environment in New South Wales, Australia, at the end of August 2020.\n\nParticipantsNone\n\nInterventionFrom September 1, 2020, we ran the stochastic model with the same initial conditions(i.e., those prevailing at August 31, 2020), and analyzed the outputs of the model to determine the probability of exceeding a given number of new diagnoses and active cases within five weeks, under three assumptions about future mask usage: a baseline scenario of 30% uptake, a scenario assuming no mask usage, and a scenario assuming mandatory mask usage with near-universal uptake (95%).\n\nMain outcome measureProbability of exceeding a given number of new diagnoses and active cases within five weeks.\n\nResultsThe policy environment at the end of August is sufficient to slow the rate of epidemic growth, but may not stop the epidemic from growing: we estimate a 20% chance that NSW will be diagnosing at least 50 new cases per day within five weeks from the date of this analysis. Mandatory mask usage would reduce this to 6-9%.\n\nConclusionsMandating the use of masks in community settings would significantly reduce the risk of epidemic resurgence.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Hong Yue",
-        "author_inst": "Dana-Farber Cancer Institute"
-      },
-      {
-        "author_name": "Rados\u0142aw P Nowak",
-        "author_inst": "Dana-Farber Cancer Institute"
-      },
-      {
-        "author_name": "Daan Overwijn",
-        "author_inst": "Dana-Farber Cancer Institute"
-      },
-      {
-        "author_name": "N Connor Payne",
-        "author_inst": "Harvard University"
-      },
-      {
-        "author_name": "Stephanie Fischinger",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
-      },
-      {
-        "author_name": "Caroline Atyeo",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
-      },
-      {
-        "author_name": "Lindsey R Baden",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Robyn M Stuart",
+        "author_inst": "University of Copenhagen"
       },
       {
-        "author_name": "Eric James Nilles",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Romesh G Abeysuriya",
+        "author_inst": "Burnet Institute"
       },
       {
-        "author_name": "Elizabeth W Karlson",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Cliff C Kerr",
+        "author_inst": "Institute for Disease Modeling"
       },
       {
-        "author_name": "Xu G Yu",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
+        "author_name": "Dina Mistry",
+        "author_inst": "Institute for Disease Modeling"
       },
       {
-        "author_name": "Jonathan Z Li",
-        "author_inst": "Brigham and Women's Hospital"
+        "author_name": "Daniel J Klein",
+        "author_inst": "Institute for Disease Modeling"
       },
       {
-        "author_name": "Galit Alter",
-        "author_inst": "Ragon Institute of MGH, MIT, and Harvard"
+        "author_name": "Richard Gray",
+        "author_inst": "The Kirby Institute, UNSW Sydney"
       },
       {
-        "author_name": "Ralph Mazitschek",
-        "author_inst": "Massachusetts General Hospital"
+        "author_name": "Margaret Hellard",
+        "author_inst": "Burnet Institute"
       },
       {
-        "author_name": "Eric S Fischer",
-        "author_inst": "Dana-Farber Cancer Institute"
+        "author_name": "Nick Scott",
+        "author_inst": "Burnet Institute"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.09.01.20182469",
@@ -1162041,37 +1164941,53 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.29.20184176",
-    "rel_title": "Estimating Unreported Deaths Associated with COVID-19",
+    "rel_doi": "10.1101/2020.08.30.20184804",
+    "rel_title": "To isolate or not to isolate: The impact of changing behavior on COVID-19 transmission",
     "rel_date": "2020-09-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.29.20184176",
-    "rel_abs": "Efforts to mitigate the spread of coronavirus disease 2019 (COVID-19) in the United States require an accurate understanding of how the epidemic is progressing. The National Center for Health Statistics (NCHS) releases weekly numbers of deaths attributed to a set of  select causes, including deaths from COVID-19 in the entire United States (US), by state, and cumulatively for individual counties. Comparing US and state level deaths from select causes recorded in 2020 with values from 2014-2019 identifies a number of differences that exceeded 95% confidence limits on historical mean values, including three states with deaths possibly from COVID-19 in December 2019. Comparing county-level NCHS datasets with county-level data on deaths from COVID-19 compiled by four public pandemic tracking sites suggests that a large number of COVID-19 deaths have not yet been reported to the NCHS. Dividing the numbers of COVID-19 deaths counted by the public tracking sites by the percentage of COVID-19 deaths reported to the NCHS suggests that approximately 20% of all US deaths from Natural Causes, as many as 200,000, may not yet have been reported to the NCHS. Evaluating changes in the fractions of deaths attributed to COVID-19 and other specific causes or nonspecific outcomes during the epidemic, relative to 2020 totals or historical mean values, can provide a valuable perspective on the public health consequences of COVID-19.\n\nSignificance StatementEstimating total deaths from natural causes using the percentage of natural cause deaths from COVID-19 reported to the CDC and the number of COVID-19 deaths counted by public tracking sites suggests that up to 200,000 deaths from natural causes between 22 April and 15 August, 2020, around 20% of the total recorded as of 26 August, have not yet been reported to the CDC.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.30.20184804",
+    "rel_abs": "The COVID-19 pandemic has caused more than 25 million cases and 800 thousand deaths worldwide to date. Neither vaccines nor therapeutic drugs are currently available for this novel coronavirus. All measures to prevent the spread of COVID-19 are thus based on reducing contact between infected and susceptible individuals. Most of these measures such as quarantine and self-isolation require voluntary compliance by the population. However, humans may act in their (perceived) self-interest only. We construct a mathematical model of COVID-19 transmission with quarantine and hospitalization coupled with a dynamic game model of adaptive human behavior. Susceptible and infected individuals adopt various behavioral strategies based on perceived prevalence and burden of the disease and sensitivity to isolation measures, and they evolve their strategies using a social learning algorithm (imitation dynamics). This results in complex interplay between the epidemiological model, which affects success of different strategies, and the game-theoretic behavioral model, which in turn affects the spread of the disease. We found that the second wave of the pandemic, which has been observed in the US, can be attributed to rational behavior of susceptible individuals, and that multiple waves of the pandemic are possible if the rate of social learning of infected individuals is sufficiently high. To reduce the burden of the disease on the society, it is necessary to incentivize such altruistic behavior by infected individuals as voluntary self-isolation.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Benjamin Stear",
-        "author_inst": "The Children's Hospital of Philadelphia"
+        "author_name": "Folashade B. Agusto",
+        "author_inst": "University of Kansas, Lawrence, KS 66045 USA"
       },
       {
-        "author_name": "Kyle Hernandez",
-        "author_inst": "University of Chicago,"
+        "author_name": "Igor V. Erovenko",
+        "author_inst": "University of North Carolina at Greensboro, Greensboro, NC 27412 USA"
       },
       {
-        "author_name": "Vidya Manian",
-        "author_inst": "University of Puerto Rico"
+        "author_name": "Alexander Fulk",
+        "author_inst": "University of Kansas, Lawrence, KS 66045 USA"
       },
       {
-        "author_name": "Som Dutta",
-        "author_inst": "Utah State University"
+        "author_name": "Qays Abu-Saymeh",
+        "author_inst": "University of Kansas, Lawrence, KS 66045 USA"
       },
       {
-        "author_name": "Deanne Taylor",
-        "author_inst": "University of Pennsylvania Perelman Medical School"
+        "author_name": "Daniel Daniel Romero-Alvarez",
+        "author_inst": "University of Kansas, Lawrence, KS 66045 USA"
       },
       {
-        "author_name": "Catharine Conley",
-        "author_inst": "NASA Ames Research Center"
+        "author_name": "Joan Ponce",
+        "author_inst": "Purdue University, West Lafayette, IN  47907 USA"
+      },
+      {
+        "author_name": "Suzanne Sindi",
+        "author_inst": "University of California Merced, Merced, CA  95343 USA"
+      },
+      {
+        "author_name": "Omayra Ortega",
+        "author_inst": "Sonoma State University, Rohnert Park, CA  94928"
+      },
+      {
+        "author_name": "Jarron M. Saint Onge",
+        "author_inst": "University of Kansas, Lawrence, KS 66045 USA  and University of Kansas Medical Center, Kansas City, KS 66160 USA"
+      },
+      {
+        "author_name": "A. Townsend Peterson",
+        "author_inst": "University of Kansas, Lawrence, KS 66045 USA"
       }
     ],
     "version": "1",
@@ -1163799,87 +1166715,51 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2020.08.31.20185314",
-    "rel_title": "HYDROXICLOROQUINE FOR PRE-EXPOSURE PROPHYLAXIS FOR SARS-CoV-2",
+    "rel_doi": "10.1101/2020.09.01.20183145",
+    "rel_title": "Impact of COVID-19 pandemic on cancer care delivery : A Real World Experience",
     "rel_date": "2020-09-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20185314",
-    "rel_abs": "SARS-CoV-2 infection has a high transmission level. At the present time there is not a specific treatment approved but it is known that, in vitro, chloroquine and hydroxychloroquine can inhibit the coronavirus.\n\nObjectiveverifying if patients with autoimmune diseases that are on treatment with HCQ have less incidence and severity on COVID-19.\n\nMaterial and methodsthis is a retrospective cohort study. The exposed cohort was formed by individuals with autoimmune diseases with HCQ treatment. The control cohort was randomly selected using the Health Card database. To deal with confounding variables and evaluate the effect of HCQ on the incidence and severity of SARS-CoV-2 infection, propensity score matching was used. Risk difference and paired percentage difference between exposed and non-exposed groups was estimated.\n\nResults919 individuals formed the exposed cohort and 1351 the control cohort. After matching, there were 690 patients on each group. During the time of the study, in the exposed group there were 42 (6.1%) individuals with suspected COVID-19, 12(1.7%) with confirmed COVID-19 and 3(0.4%) were hospitalized. In the control group there were 30(4.3%) individuals with suspected COVID-19, 13(1.9%) with confirmed COVID-19 and 2(0.3%) were hospitalized. The risk difference between each cohort was: 0.017(-0.05-0.04) for suspected COVID-19; -0.014(-0.015-0.012) for confirmed COVID-19 and 0.001(-0.007-0.007) for hospitalized patients. There were not significant differences.\n\nConclusionthere is no difference neither on the incidence nor on the severity of COVID-19 between patients with autoimmune diseases with HCQ treatment and patients that do not take HCQ.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20183145",
+    "rel_abs": "BackgroundThere is lack of information on impact of Corona Virus Disease (COVID-19) pandemic on routine cancer care delivery.\n\nAims and ObjectivesTo evaluate the change in Day Care Chemotherapy (DCC) and Out Patient Department (OPD) patient numbers before and after COVID-19 national lockdown.\n\nMaterial and MethodsDemographic data, diagnosis, type and frequency of chemotherapy delivered in Day Care between 1st February 2020 to 31st July 2020 were retrieved. Out Patient Department daily patient numbers were collected. Descriptive statistics, Odds ratio, Chi-square and Student T test were used to measure change in pattern of DDC and OPD patient numbers before and after 24th March 2020 (day of Lockdown). Pearson correlation coefficient was used to measure the strength of correlation between rise in COVID-19 cases and patient numbers.\n\nResults3192 DCC and 8209 OPD visits were recorded in 126 working days. Median age was 47 years(SD + 19.06). Breast (17%) and Gall bladder(15%) were the most common cancers receiving chemotherapy. There was a significant decrease in number of DCC delivered in post COVID lockdown [mean 21.97 (+ 9.7)] compared to pre COVID lockdown [mean 33.30 (+11.4)], t=4.11, p = 0.001.There was a significant decrease in number of OPD visits in post COVID lockdown [mean 47.13 (+ 18.8)] compared to pre COVID lockdown [mean 89.91 (+30.0)], t=7.09, p = 0.001. The odds of receiving weekly chemotherapy over non weekly regimes significantly decreased post COVID lockdown with Odds ratio of 0.52 (95% CI, 0.36-0.75) with Chi square of 12.57, p =0.001. Daily COVID cases in State and OPD patient number were found to be moderately positively correlated on Pearson correlation coefficient, r = 0.35,p =0.001.\n\nConclusionThere was a significant fall in patient visit and chemotherapy cycles immediately after lockdown. The numbers increased later despite rise in COVID-19 cases.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Jaime Lopez de la Iglesia",
-        "author_inst": "GAP Leon"
-      },
-      {
-        "author_name": "Naiara Cubelos",
-        "author_inst": "Licenciada en Medicina. GAP Leon (Spain)."
-      },
-      {
-        "author_name": "Roi Naveiro",
-        "author_inst": "Instituto de Ciencias Matematicas. Estadistica e investigacion operativa. Consejo Superior de Investigacion Cientifica (ICMAT-CSIC)."
-      },
-      {
-        "author_name": "Marina Montoro Gomez",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)"
-      },
-      {
-        "author_name": "Francisco Javier Gonzalez de Haro",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)."
-      },
-      {
-        "author_name": "Maria Ajenjo Gonzalez",
-        "author_inst": "Doctora en Medicina.GAP Leon (Spain)"
-      },
-      {
-        "author_name": "Estefania Tobal Vicente",
-        "author_inst": "Doctora en Medicina. GAP Leon (Spain)"
-      },
-      {
-        "author_name": "Maria Lamuedra Gil de Gomez",
-        "author_inst": "Graduada en Medicina. GAP Leon (Spain)"
-      },
-      {
-        "author_name": "Maria Teresa Nuevo Guisado",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)."
-      },
-      {
-        "author_name": "Isabel Torio Gomez",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)."
+        "author_name": "Avinash Pandey",
+        "author_inst": "Indira Gandhi Institute of Medical Sciences, Patna"
       },
       {
-        "author_name": "Ana Penalver Andrada",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)."
+        "author_name": "Mala Rani",
+        "author_inst": "Indira Gandhi Institue of Medical Sciences, Patna"
       },
       {
-        "author_name": "Nuria Martinez Cao",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)."
+        "author_name": "Neelam Chandra",
+        "author_inst": "Indira Gandhi Institue of Medical Sciences, Patna"
       },
       {
-        "author_name": "Paula Gonzalez Figaredo",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)."
+        "author_name": "Mridula Pandey",
+        "author_inst": "Indira Gandhi Institue of Medical Sciences, Patna"
       },
       {
-        "author_name": "Carlos Robles Garcia",
-        "author_inst": "Graduado en Medicina. GAP Leon (Spain)."
+        "author_name": "Ravindra Singh",
+        "author_inst": "Indira Gandhi Institue of Medical Sciences, Patna"
       },
       {
-        "author_name": "Lidia Anastasia Alvarado Machon",
-        "author_inst": "Doctora en Medicina. GAP Leon (Spain)."
+        "author_name": "Kanchan Monalisa",
+        "author_inst": "Indira Gandhi Institue of Medical Sciences, Patna"
       },
       {
-        "author_name": "Angeles Lafont Alcalde",
-        "author_inst": "Doctora en Medicina. GAP Leon (Spain)."
+        "author_name": "Vikash Yadav",
+        "author_inst": "Indira Gandhi Institue of Medical Sciences, Patna"
       },
       {
-        "author_name": "Jose Cesareo Naveiro Rilo",
-        "author_inst": "Doctor en Salud Publica y Medicina Preventiva. Unidad Docente de Medicina Familiar y Comunitaria de Leon (Spain)."
+        "author_name": "Shivkant Singh",
+        "author_inst": "Indira Gandhi Institue of Medical Sciences, Patna"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "rheumatology"
+    "category": "oncology"
   },
   {
     "rel_doi": "10.1101/2020.08.31.20185371",
@@ -1165741,33 +1168621,45 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2020.08.27.20182923",
-    "rel_title": "Evaluation of production lots of a rapid point-of-care lateral flow serological test intended for identification of IgM and IgG against the N-terminal part of the spike protein (S1) of SARS-CoV-2",
+    "rel_doi": "10.1101/2020.08.26.20182675",
+    "rel_title": "Epidemiological and socio-economic characteristics of the COVID-19 spring outbreak in Quebec, Canada: A population-based study",
     "rel_date": "2020-09-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20182923",
-    "rel_abs": "Background and objectivesSeveral antibody tests are available to detect SARS-CoV-2 specific antibodies, many of which address different antigens. Rapid point-of-care (POC) tests have been doubted due to an eventual risk of production errors, although it is unstudied whether such error would affect test sensitivity and/or specificity. We aimed to evaluate two separate production lots of a commercially available test intended for rapid detection of IgM and IgG against the N-terminal part of the SARS-CoV-2 spike protein (S1).\n\nMaterials and methodsSerum samples from individuals with confirmed SARS-CoV-2 infection, by RT-PCR and/or serology, and pre-COVID-19 negative control sera gathered from a biobank during 2018 were collected. The presence of anti-S1 IgM/IgG was verified by an in-house Luminex-based serological assay, serving as reference method. The index test was a commercially available rapid POC-test (the COVID-19 IgG/IgM Rapid Test Cassette [Zhejiang Orient Gene Biotech Co Ltd, Huzhou, Zhejiang, China/Healgen Scientific, LLC, U.S.A.]).\n\nResultsOne hundred samples were verified positive for anti-S1 IgG (median fluorescence intensity (MFI) [&ge;]900) and 74 for anti-S1 IgM (MFI [&ge;]700), confirmed by RT-PCR (n=90) and/or serology (n=89). None of the negative controls (n=200; MFI <300) had SARS-CoV-2 anti-S1 IgM, while one tested positive for SARS-CoV-2 anti-S1 IgG. For the two lots, the sensitivities of the rapid test were 93.2% (69/74; 95% CI: 85.1% - 97.1%) and 87.8% (65/74; 95% CI: 78.5% - 93.5%) for IgM, respectively 93.0% (93/100; 95% CI: 86.3% - 96.6%) and 100.0% for IgG (100/100; 95% CI: 96.3% - 100.0%). The specificity for both lots was 100% for IgM (200/200; 95% CI: 98.1% - 100%) and 99.5% for IgG (199/200; 95% CI: 97.2% - 99.9%). The positive predictive value was 100% for IgM and 98.9% and 99.0% for IgG. The negative predictive value was 95.7% and 97.6% for IgM, and 96.6% and 100.0% for IgG.\n\nConclusionThe rapid POC-test used in this study is suitable to assess SARS-CoV-2 anti-S1 specific IgM/IgG, as a measure of previous virus exposure on an individual level. While the specificity was not affected by production lot, external validation of separate lots of rapid POC-tests is encouraged to ensure high sensitivity before market introduction.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20182675",
+    "rel_abs": "BackgroundBy mid-July 2020, more than 108,000 COVID-19 cases had been diagnosed in Canada with more than half in the province of Quebec. To be prepared for a potential second wave of COVID-19 in the fall, it seems of utmost importance to analyze the epidemiological and socio-economic characteristics of the spring outbreak in the population.\n\nMethodWe conducted an online survey of the participants of the CARTaGENE population-based cohort, composed of middle-aged and older adults. We collected information on socio-demographic, lifestyle, health condition, COVID-related symptoms and COVID-19 testing. We studied the association between these factors and two outcomes: the status of having been tested for SARS-CoV-2 and the status of having received a positive test when having been tested. These associations were evaluated with univariate and multivariate analyzes using a hybrid tree-based regression model.\n\nResultsAmong the 8,129 respondents from the CARTaGENE cohort, 649 were tested for COVID-19 and 41 were positive. Medical workers and individuals having a contact with a COVID-19 patient had the highest probabilities of being tested (32% and 42.4%, respectively) and of being positive (17.2% and 13.0%, respectively) among those tested. 7.6% of the participants declared that they have experienced at least one of the four COVID-related symptoms chosen by the Public Health authorities (fever, cough, dyspnea, anosmia) but were not tested. Results from the tree-based model analyzes adjusted on exposure factors show that the combination of dyspnea, dry cough and fever was highly associated with being tested whereas anosmia, fever, and headache were the most discriminant factors for having a positive test among those tested. During the spring outbreak, more than one third of the participants have experienced a decrease in access to health services. There were sex and age differences in the socio-economic and emotional impacts of the pandemic.\n\nConclusionWe have shown some discrepancies between the symptoms associated with being tested and being positive. In particular, the anosmia is a major discriminant symptom for positivity whereas ear-nose-throat symptoms seem not to be COVID-related. The results also emphasize the need of increasing the accessibility of testing for the general population.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Tove Hoffman",
-        "author_inst": "Uppsala University"
+        "author_name": "Rodolphe Jantzen",
+        "author_inst": "CARTaGENE, CHU Ste-Justine Research Center, 3175 Chemin de la Cote-Sainte-Catherine, H3T1C5, Montreal, Canada"
       },
       {
-        "author_name": "Linda Kolstad",
-        "author_inst": "Uppsala University"
+        "author_name": "Nolwenn Noisel",
+        "author_inst": "CARTaGENE, CHU Ste-Justine Research Center, 3175 Chemin de la Cote-Sainte-Catherine, H3T1C5, Montreal, Canada"
       },
       {
-        "author_name": "Bengt Ronnberg",
-        "author_inst": "Uppsala University Hospital"
+        "author_name": "Sophie Camilleri-Broet",
+        "author_inst": "McGill University"
       },
       {
-        "author_name": "Ake Lundkvist",
-        "author_inst": "Uppsala University"
+        "author_name": "Catherine Labbe",
+        "author_inst": "CARTaGENE, CHU Ste-Justine Research Center, 3175 Chemin de la Cote-Sainte-Catherine, H3T1C5, Montreal, Canada"
+      },
+      {
+        "author_name": "Thibault de Malliard",
+        "author_inst": "CARTaGENE, CHU Ste-Justine Research Center, 3175 Chemin de la Cote-Sainte-Catherine, H3T1C5, Montreal, Canada"
+      },
+      {
+        "author_name": "Yves Payette",
+        "author_inst": "CARTaGENE, CHU Ste-Justine Research Center, 3175 Chemin de la Cote-Sainte-Catherine, H3T1C5, Montreal, Canada"
+      },
+      {
+        "author_name": "Philippe Broet",
+        "author_inst": "CARTaGENE, CHU Ste-Justine Research Center, 3175 Chemin de la Cote-Sainte-Catherine, H3T1C5, Montreal, Canada"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1167331,29 +1170223,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.26.20182477",
-    "rel_title": "Modelling COVID-19 contagion:Risk assessment and  targeted mitigation policies",
+    "rel_doi": "10.1101/2020.08.26.20181990",
+    "rel_title": "Empowering the crowd: Feasible strategies to minimize the spread of COVID-19 in high-density informal settlements",
     "rel_date": "2020-09-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20182477",
-    "rel_abs": "We use a spatial epidemic model with demographic and geographic heterogeneity to study the regional dynamics of COVID-19 across 133 regions in England.\n\nOur model emphasises the role of variability of regional outcomes and heterogeneity across age groups and geographic locations, and provides a framework for assessing the impact of policies targeted towards sub-populations or regions. We define a concept of efficiency for comparative analysis of epidemic control policies and show targeted mitigation policies based on local monitoring to be more efficient than country-level or non-targeted measures. In particular, our results emphasise the importance of shielding vulnerable sub-populations and show that targeted policies based on local monitoring can considerably lower fatality forecasts and, in many cases, prevent the emergence of second waves which may occur under centralised policies.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20181990",
+    "rel_abs": "More than 1 billion people live in informal settlements worldwide, where precarious living conditions pose unique challenges to managing a COVID-19 outbreak. Taking Northwest Syria as a case-study, we simulated an outbreak in high-density informal Internally Displaced Persons (IDP) camps using a stochastic Susceptible-Exposed-Infectious-Recovered model. Expanding on previous studies, taking social conditions and population health/structure into account, we modeled several interventions feasible in these settings: moderate self-distancing, self-isolation of symptomatic cases, and protection of the most vulnerable in \"safety zones\". We considered complementary measures to these interventions that can be implemented autonomously by these communities, such as buffer zones, health-checks, and carers for isolated individuals, quantifying their impact on the micro-dynamics of disease transmission. All interventions significantly reduce outbreak probability and some of them reduce mortality when an outbreak does occur. Self-distancing reduces mortality by up to 35% if contacts are reduced by 50%. A reduction in mortality by up to 18% can be achieved by providing 1 self-isolation tent per 8 people. Protecting the most vulnerable in a safety zone reduces the outbreak probability in the vulnerable population and has synergistic effects with the other interventions. Our model predicts that a combination of all simulated interventions may reduce mortality by more than 90% and delay an outbreaks peak by almost two months. Our results highlight the potential for non-medical interventions to mitigate the effects of the pandemic. Similar measures may be applicable to controlling COVID-19 in other informal settlements, particularly IDP camps in conflict regions, around the world.\n\nKey questionsO_ST_ABSWhat is already known?C_ST_ABSO_LISince the onset of the COVID-19 pandemic, many studies have provided evidence for the effectiveness of strategies such as social distancing, testing, contact tracing, case isolation, use of personal protective equipment/facemasks and improved hygiene to reduce the spread of the disease. These studies underlie the recommendations of the World Health Organisation, but their implementation is contingent on local conditions and resources.\nC_LIO_LIMathematical modelling is the basis of many epidemiological studies and has helped inform policymakers considering COVID-19 responses around the world. Nevertheless, only a limited number of studies have applied these models to informal settlements.\nC_LI\n\nWhat are the new findings?O_LIWe developed a mathematical model to study the dynamics of COVID-19 in Syrian IDP camps, elaborating on previous efforts done in similar settings by explicitly parameterizing the camps demographics, living conditions and micro-dynamics of interpersonal contacts in our modelization.\nC_LIO_LIWe designed interventions such as self-distancing, self-isolation and the creation of safety zones to protect the most vulnerable members of the population, among others, through conversations with camp managers with on-the-ground knowledge of what interventions would be feasible and have community buy-in.\nC_LIO_LIOur results show how low-cost, feasible, community-led non-medical interventions can significantly mitigate the impact of COVID-19 in Northwest Syrian IDP camps.\nC_LI\n\nWhat do the new findings imply?O_LIOur model represents a step forward in the much-needed search for epidemiological models that are sufficiently flexible to consider specific social questions. The model can also help inform similar interventions in refugee camps in conflict-torn regions, and potentially be adapted to other informal settlements and vulnerable communities around the world.\nC_LI",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Rama Cont",
-        "author_inst": "University of Oxford"
+        "author_name": "Alberto Pascual-Garc\u00eda",
+        "author_inst": "ETH-Zurich"
       },
       {
-        "author_name": "RenYuan Xu",
-        "author_inst": "University of Oxford"
+        "author_name": "Jordan Klein",
+        "author_inst": "Princeton University"
       },
       {
-        "author_name": "Artur Kotlicki",
-        "author_inst": "University of Oxford"
+        "author_name": "Jennifer Villers",
+        "author_inst": "Princeton University"
+      },
+      {
+        "author_name": "Eduard Campillo-Funollet",
+        "author_inst": "University of Sussex"
+      },
+      {
+        "author_name": "Chamsy Sarkis",
+        "author_inst": "Pax Syriana Foundation"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1169001,83 +1171901,27 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2020.08.29.20126201",
-    "rel_title": "Sex-based clinical and immunological differences in COVID-19",
+    "rel_doi": "10.1101/2020.08.27.20183616",
+    "rel_title": "A Comparison of Covid-19 Patient Characteristics Before versus After Partial Lockdown in Vietnam",
     "rel_date": "2020-09-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.29.20126201",
-    "rel_abs": "BackgroundMales and females differ in their immunological responses to foreign pathogens. However, most of the current COVID-19 clinical practices and trials do not take sex as consideration.\n\nMethodsWe performed an unbiased sex-based comparative analysis for the clinical outcomes, peripheral immune cells, and SARS-CoV-2 specific antibody levels of 1,558 males and 1,499 females COVID-19 patients from a single center. The lymphocyte subgroups were measured by Flow cytometry. Total antibody, Spike protein (S)-, receptor binding domain (RBD)-, and nucleoprotein (N)-specific IgM and IgG levels were measured by chemiluminescence.\n\nResultsWe found that the mortality and ICU admission rates were approximately 2-fold higher in males than that in females (P<0.005). Survival analysis revealed that sex is an independent prognostic factor for COVID-19 (Hazard ratio=2.2, P=0.003). The concentration of inflammatory factors in peripheral blood was significantly higher in males. Besides, the renal and hepatic abnormality induced by COVID-19 was more common in males during the hospitalization. The analysis of lymphocyte subsets revealed that the percentage of CD19+ B cell and CD4+ T cell was significantly higher in females (P<0.001) during hospitalization, indicating the stronger humoral immunity in females than males. Notably, the protective IgG sharply increased and reached a peak in the fourth week after symptom onset in females, while gradually increased and reached a peak in the seventh week in males.\n\nConclusionsThe unfavorable prognosis of male COVID-19 patients may result from the weak humoral immunity and indolent antibody responses during SARS-CoV-2 infection and recovery. Early medical intervention and close monitoring are important, especially for male COVID-19 patients. Hormonal or convalescent plasma therapy may help improve the immunity of males to fight against SARS-CoV-2 infection.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20183616",
+    "rel_abs": "BackgroundGiven the Covid-19 sudden rapid spread in the community since 25 July 2020, an updated analysis of Covid-19 cases was conducted to examine the differences of characteristics of Covid-19 patients before versus after partial lockdown end in Vietnam.\n\nMethodsData of 569 Covid-19 patients confirmed SARS-CoV-2 infection from 23 January to 31 July was collected from available official databases. We divided Covid-19 situation timeline into two main periods, before lockdown end (23 January - 22 April) and after lockdown end (23 April - 31 July).\n\nResultsWe found significant variations in the distribution of Covid-19 patients among different provinces between two periods. Covid-19 confirmed patients were older in the time after lockdown end compared to in the period before lockdown end by a median of 5 years. All discharged Covid-19 patients and no Covid-19 death were in the phase before lockdown, while post lockdown period had still remained significant patients being under treatment, especially reported first fatalities. The number of Covid-19 patients who returned from other countries (excluding China) slightly increased through two stages (p >0.05), partially showing that the continuous volume of people returning Vietnam from abroad during the Covid-19 epidemic.\n\nConclusionsOur analysis indicated demographic and epidemiological disparity of Covid-19 patients before versus after loosening the national partial lockdown in Vietnam. It is important to suggest that, proactive efforts in Covid-19 control after partial lockdown end will be effective when the measures to closely control and monitor repatriation and immigration via the borders of Vietnam are strictly enforced.\n\nWhat is already known on this topicO_LIMost of Covid-19 confirmed patients in Vietnam were acquired overseas.\nC_LIO_LIIn Vietnam, Covid-19 epidemic had the low estimated reproduction ratio (R0) and SARS-CoV-2 spread was on the downward trend before July 25.\nC_LI\n\nWhat this study addsO_LICovid-19 confirmed patients were older in the time after lockdown end compared to in the period before lockdown end by a median of 5 years.\nC_LIO_LIAll discharged Covid-19 patients and no Covid-19 death were in the phase before lockdown, while post lockdown period had still remained significant patients being under treatment, especially reported first fatalities.\nC_LIO_LIContinuous volume of people returning Vietnam from abroad through two stages during the Covid-19 epidemic.\nC_LIO_LIOur analysis might be considered as a prompt reference source for further in-depth surveys to understand the adaptive models of Covid-19 patients among different provinces.\nC_LI",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Kening Li",
-        "author_inst": "COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine"
-      },
-      {
-        "author_name": "Bin Huang",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Yun Cai",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
+        "author_name": "Hoang-Long Vo",
+        "author_inst": "Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi 100000, Vietnam"
       },
       {
-        "author_name": "Zhihua Wang",
-        "author_inst": "Department of Laboratory Medicine & Blood Transfusion, the 907th Hospital"
-      },
-      {
-        "author_name": "Lu Li",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Lingxiang Wu",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Mengyan Zhu",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Jie Li",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Ziyu Wang",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Min Wu",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Wanlin Li",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Wei Wu",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Lishen Zhang",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
-      },
-      {
-        "author_name": "Xinyi Xia",
-        "author_inst": "COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine"
-      },
-      {
-        "author_name": "Shukui Wang",
-        "author_inst": "Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University"
-      },
-      {
-        "author_name": "Qianghu Wang",
-        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University"
+        "author_name": "Kim-Duy Vu",
+        "author_inst": "Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi 100000, Vietnam"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.08.28.20174946",
@@ -1170931,29 +1173775,281 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.25.20181487",
-    "rel_title": "Risk of COVID-19 hospitalisation rises exponentially with age, inversely proportional to T-cell production",
+    "rel_doi": "10.1101/2020.08.25.20154252",
+    "rel_title": "SARS-CoV-2-RNA viremia is associated to hypercytokinemia and critical illness in COVID-19",
     "rel_date": "2020-08-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20181487",
-    "rel_abs": "Here we report that COVID-19 hospitalisation rates follow an exponential relationship with age, doubling for every 16 years of age or equivalently increasing by 4.5% per year of life (R2=0.98). This mirrors the well studied exponential decline of both thymus volume and T-cell production, which halve every 16 years. COVID-19 can therefore be added to the list of other diseases with this property, including those caused by MRSA, MERS-CoV, West Nile virus, Streptococcus Pneumonia and certain cancers, such as chronic myeloid leukemia and brain cancers. In addition, incidence of severe disease and mortality due to COVID-19 are both higher in men, consistent with the degree to which thymic involution (and the decrease in T-cell production with age) is more severe in men compared to women. Since these properties are shared with some non-contagious diseases, we hypothesised that the age-dependence does not come from social-mixing patterns, i.e. that the probability of hospitalisation given infection rises exponentially, doubling every 16 years. A Bayesian analysis of daily hospitalisations, incorporating contact matrices, found that this relationship holds for every age group except for the under 20s. While older adults have less contacts than young adults, our analysis suggests that there is an approximate cancellation between the effects of less contacts for the elderly and higher infectiousness due to a higher probability of developing severe disease. Our model fitting suggests under 20s have 49-75% additional immune protection beyond that predicted by strong thymus function alone, consistent with increased juvenile cross-immunity from other viruses. We found no evidence for differences between age groups in susceptibility to infection or infectiousness to others (given disease state), i.e. the only important factor in the age-dependence of hospitalisation rates is the probability of hospitalisation given infection. These findings suggest the existence of a T-cell exhaustion threshold, proportional to thymic output, and that clonal expansion of peripheral T-cells does not affect disease risk. The strikingly simple inverse relationship between risk and thymic T-cell output adds to the evidence that thymic involution is an important factor in the decline of the immune system with age and may also be an important clue in understanding disease progression, not just for COVID-19 but other diseases as well.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20154252",
+    "rel_abs": "BackgroundSevere COVID-19 is characterized by clinical and biological manifestations typically observed in sepsis. SARS-CoV-2 RNA is commonly detected in nasopharyngeal swabs, however viral RNA can be found also in peripheral blood and other tissues.\n\nWhether systemic spreading of the virus or viral components plays a role in the pathogenesis of the sepsis-like disease observed in severe COVID-19 is currently unknown.\n\nMethodsWe determined the association of plasma SARS-CoV-2 RNA with the biological responses and the clinical severity of patients with COVID-19. 250 patients with confirmed COVID-19 infection were recruited (50 outpatients, 100 hospitalised ward patients, and 100 critically ill). The association between plasma SARS-CoV-2 RNA and laboratory parameters was evaluated using multivariate GLM with a gamma distribution. The association between plasma SARS-CoV-2 RNA and severity was evaluated using multivariate ordinal logistic regression analysis and Generalized Linear Model (GLM) analysis with a binomial distribution.\n\nResultsThe presence of SARS-CoV-2-RNA viremia was independently associated with a number of features consistently identified in sepsis: 1) high levels of cytokines (including CXCL10, CCL-2, IL-10, IL-1ra, IL-15, and G-CSF); 2) higher levels of ferritin and LDH; 3) low lymphocyte and monocyte counts 4) and low platelet counts. In hospitalised patients, the presence of SARS-CoV-2-RNA viremia was independently associated with critical illness: (adjusted OR= 8.30 [CI95%=4.21 - 16.34], p < 0.001). CXCL10 was the most accurate identifier of SARS-CoV-2-RNA viremia in plasma (area under the curve (AUC), [CI95%], p) = 0.85 [0.80 - 0.89), <0.001]), suggesting its potential role as a surrogate biomarker of viremia. The cytokine IL-15 most accurately differentiated clinical ward patients from ICU patients (AUC: 0.82 [0.76 - 0.88], <0.001).\n\nConclusionssystemic dissemination of genomic material of SARS-CoV-2 is associated with a sepsis-like biological response and critical illness in patients with COVID-19. RNA viremia could represent an important link between SARS-CoV-2 infection, host response dysfunction and the transition from moderate illness to severe, sepsis-like COVID-19 disease.",
+    "rel_num_authors": 66,
     "rel_authors": [
       {
-        "author_name": "Sam Palmer",
-        "author_inst": "University of Oxford"
+        "author_name": "Jesus F Bermejo-Martin",
+        "author_inst": "Group for Biomedical Research in Sepsis (BioSepsis). Instituto de Investigacion Biomedica de Salamanca, (IBSAL) Salamanca / Hospital Universitario Rio Hortega, "
       },
       {
-        "author_name": "Nik Cunniffe",
-        "author_inst": "University of Cambridge"
+        "author_name": "Milagros Gonzalez-Rivera",
+        "author_inst": "Biochemistry Service, Hospital General Universitario Gregorio Maranon, Madrid, Spain."
       },
       {
-        "author_name": "Ruairi Donnelly",
-        "author_inst": "University of Cambridge"
+        "author_name": "Raquel Almansa",
+        "author_inst": "Group for Biomedical Research in Sepsis (BioSepsis). Instituto de Investigacion Biomedica de Salamanca, (IBSAL) Salamanca / Hospital Universitario Rio Hortega, "
+      },
+      {
+        "author_name": "Dariela Micheloud",
+        "author_inst": "Emergency Department, Hospital General Universitario Gregorio Maranon, Madrid, Spain"
+      },
+      {
+        "author_name": "Ana P. Tedim",
+        "author_inst": "IBSAL"
+      },
+      {
+        "author_name": "Marta Dominguez-Gil",
+        "author_inst": "Microbiology Service, Hospital Universitario Rio Hortega, Valladolid, Spain."
+      },
+      {
+        "author_name": "Salvador Resino",
+        "author_inst": "Unidad de Infeccion Viral e Inmunidad, Centro Nacional de Microbiologia, Instituto de Salud Carlos III, Majadahonda, Spain."
+      },
+      {
+        "author_name": "Marta Martin-Fernandez",
+        "author_inst": "Group for Biomedical Research in Sepsis (BioSepsis). Instituto de Investigacion Biomedica de Salamanca, (IBSAL), Salamanca / Hospital Universitario Rio Hortega,"
+      },
+      {
+        "author_name": "Pablo Ryan Murua",
+        "author_inst": "Internal Medicine, Hospital Universitario Infanta Leonor, Madrid, Spain"
+      },
+      {
+        "author_name": "Felipe Perez-Garcia",
+        "author_inst": "Servicio de Microbiologia Clinica, Hospital Universitario Principe de Asturias, Alcala de Henares, Madrid,Spain"
+      },
+      {
+        "author_name": "Luis Tamayo",
+        "author_inst": "Intensive Care Unit, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Raul Lopez-Izquierdo",
+        "author_inst": "Emergency Department, Hospital Universitario Rio Hortega, Valladolid, Spain."
+      },
+      {
+        "author_name": "Elena Bustamante",
+        "author_inst": "Intensive Care Unit, Hospital Clinico Universitario de Valladolid. Spain."
+      },
+      {
+        "author_name": "Cesar Aldecoa",
+        "author_inst": "Department of Anesthesiology, Facultad de Medicina de Valladolid, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Jose Manuel Gomez",
+        "author_inst": "Intensive Care Unit. Hospital General Universitario Gregorio Maranon. Madrid. Spain."
+      },
+      {
+        "author_name": "Jesus Rico-Feijoo",
+        "author_inst": "Anesthesiology and Reanimation Service, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Antonio Orduna",
+        "author_inst": "Microbiology Service, Hospital Clinico Universitario de Valladolid, Spain."
+      },
+      {
+        "author_name": "Raul Mendez",
+        "author_inst": "Pulmonology Service, University and Polytechnic Hospital La Fe, Valencia, Spain."
+      },
+      {
+        "author_name": "Isabel Fernandez Natal",
+        "author_inst": "Clinical Analysis Service. Hospital de Leon, Spain."
+      },
+      {
+        "author_name": "Gregoria Megias",
+        "author_inst": "Microbiology Service, Hospital Universitario de Burgos, Spain."
+      },
+      {
+        "author_name": "Montserrat Gonzalez-Estecha",
+        "author_inst": "Biochemistry Service, Hospital General Universitario Gregorio Maranon, Madrid, Spain."
+      },
+      {
+        "author_name": "Demetrio Carriedo",
+        "author_inst": "Intensive Care Unit. Hospital de Leon, Spain."
+      },
+      {
+        "author_name": "Cristina Doncel",
+        "author_inst": "Group for Biomedical Research in Sepsis (BioSepsis) Hospital Universitario Rio Hortega, Valladolid / Centro de Investigacion Biomedica en Red en Enfermedades Re"
+      },
+      {
+        "author_name": "Noelia Jorge",
+        "author_inst": "Group for Biomedical Research in Sepsis (BioSepsis) Hospital Universitario Rio Hortega, Valladolid / Centro de Investigacion Biomedica en Red en Enfermedades Re"
+      },
+      {
+        "author_name": "Alicia Ortega",
+        "author_inst": "IBSAL"
+      },
+      {
+        "author_name": "Amanda de la Fuente",
+        "author_inst": "IBSAL"
+      },
+      {
+        "author_name": "Felix del Campo",
+        "author_inst": "Pneumology Service , Rio Hortega University Hospital / Biomedical Engineering Group , University of Valladolid , Valladolid , Spain."
+      },
+      {
+        "author_name": "Jose Antonio Fernandez-Ratero",
+        "author_inst": "Intensive Care Unit. Hospital Universitario de Burgos, Spain."
+      },
+      {
+        "author_name": "Wysali Trapiello",
+        "author_inst": "Clinical Analysis Service. Hospital Clinico Universitario de Valladolid, Spain."
+      },
+      {
+        "author_name": "Paula Gonzalez-Jimenez",
+        "author_inst": "Pulmonology Service, University and Polytechnic Hospital La Fe, Valencia, Spain."
+      },
+      {
+        "author_name": "Guadalupe Ruiz",
+        "author_inst": "Clinical Analysis Service. Hospital Clinico Universitario de Valladolid, Spain."
+      },
+      {
+        "author_name": "Alyson A. Kelvin",
+        "author_inst": "Dalhousie University, Halifax, Nova Scotia, Canada"
+      },
+      {
+        "author_name": "Ali Toloue Ostadgavahi",
+        "author_inst": "Dalhousie University, Halifax, Nova Scotia, Canada"
+      },
+      {
+        "author_name": "Ruth Oneizat",
+        "author_inst": "Microbiology Service, Hospital Universitarios Rio Hortega, Valladolid, Spain."
+      },
+      {
+        "author_name": "Luz Maria Ruiz",
+        "author_inst": "Microbiology Service, Hospital Universitarios Rio Hortega, Valladolid, Spain."
+      },
+      {
+        "author_name": "Iria Miguens",
+        "author_inst": "Emergency Department, Hospital General Universitario Gregorio Maranon, Madrid, Spain"
+      },
+      {
+        "author_name": "Esther Gargallo",
+        "author_inst": "Emergency Department, Hospital General Universitario Gregorio Maranon, Madrid, Spain"
+      },
+      {
+        "author_name": "Iona Munoz",
+        "author_inst": "Emergency Department, Hospital General Universitario Gregorio Maranon, Madrid, Spain"
+      },
+      {
+        "author_name": "Sara Pelegrin",
+        "author_inst": "Anesthesiology and Reanimation Service, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Silvia Martin",
+        "author_inst": "Anesthesiology and Reanimation Service, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Pablo Garcia-Olivares",
+        "author_inst": "Intensive Care Unit. Hospital General Universitario Gregorio Maranon. Madrid. Spain."
+      },
+      {
+        "author_name": "Jamil Antonio Cedeno",
+        "author_inst": "Intensive Care Unit. Hospital General Universitario Gregorio Maranon. Madrid. Spain."
+      },
+      {
+        "author_name": "Tomas Ruiz-Albi",
+        "author_inst": "Pneumology Service , Rio Hortega University Hospital, Valladolid, Spain."
+      },
+      {
+        "author_name": "Carolina Puertas",
+        "author_inst": "Biochemistry Service, Hospital General Universitario Gregorio Maranon, Madrid, Spain."
+      },
+      {
+        "author_name": "Jose Angel Berezo",
+        "author_inst": "Intensive Care Unit, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Gloria Renedo",
+        "author_inst": "Intensive Care Unit, Hospital Clinico Universitario de Valladolid. Spain"
+      },
+      {
+        "author_name": "Ruben Herran",
+        "author_inst": "Intensive Care Unit, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Juan Bustamante-Munguira",
+        "author_inst": "Department of Cardiovascular Surgery, Hospital Clinico Universitario de Valladolid. Spain."
+      },
+      {
+        "author_name": "Pedro Enriquez",
+        "author_inst": "Intensive Care Unit. Hospital Universitario Rio Hortega. Valladolid, Spain."
+      },
+      {
+        "author_name": "Ramon Cicuendez",
+        "author_inst": "Intensive Care Unit, Hospital Clinico Universitario de Valladolid. Spain."
+      },
+      {
+        "author_name": "Jesus Blanco",
+        "author_inst": "Intensive Care Unit, Hospital Universitario Rio Hortega, Valladolid, Spain"
+      },
+      {
+        "author_name": "Jessica Abadia",
+        "author_inst": "Infectious diseases clinic, Internal Medicine Department, Rio Hortega University Hospital, Valladolid, Spain"
+      },
+      {
+        "author_name": "Julia Gomez-Barquero",
+        "author_inst": "Infectious diseases clinic,  Internal Medicine Department, Rio Hortega University Hospital, Valladolid, Spain;"
+      },
+      {
+        "author_name": "Nuria Mamolar",
+        "author_inst": "Intensive Care Unit, Hospital Clinico Universitario de Valladolid. Spain."
+      },
+      {
+        "author_name": "Natalia Blanca-Lopez",
+        "author_inst": "Internal Medicine, Hospital Universitario Infanta Leonor, Madrid, Spain"
+      },
+      {
+        "author_name": "Luis Jorge Valdivia",
+        "author_inst": "Intensive Care Unit. Hospital de Leon, Spain."
+      },
+      {
+        "author_name": "Belen Fernandez Caso",
+        "author_inst": "Clinical Analysis Service. Hospital de Leon, Spain."
+      },
+      {
+        "author_name": "Maria Angeles Mantecon",
+        "author_inst": "Microbiology Service, Hospital Universitario de Burgos, Spain"
+      },
+      {
+        "author_name": "Anna Motos",
+        "author_inst": "Department of Pulmonology, Hospital Clinic de Barcelona, Universidad de Barcelona, Institut D investigacions August Pi I Sunyer (IDIBAPS), Carrer del Rossello, "
+      },
+      {
+        "author_name": "Laia Fernandez-Barat",
+        "author_inst": "Department of Pulmonology, Hospital Clinic de Barcelona, Universidad de Barcelona, Institut D investigacions August Pi I Sunyer (IDIBAPS), Carrer del Rossello, "
+      },
+      {
+        "author_name": "Ricard Ferrer",
+        "author_inst": "Intensive Care Department, Vall d Hebron Hospital Universitari. SODIR Research Group, Vall d Hebron Institut de Recerca, Passeig de la Vall d Hebron, 119, 08035"
+      },
+      {
+        "author_name": "Ferran Barbe",
+        "author_inst": "Respiratory Department, Institut Ricerca Biomedica de Lleida, Hospital Universitari Arnau de Vilanova, Lleida / Centro de Investigacion Biomedica en Red en Enfe"
+      },
+      {
+        "author_name": "Antoni Torres",
+        "author_inst": "Department of Pulmonology, Hospital Clinic of Barcelona, University of Barcelona, Institut Dinvestigacions August Pi I Sunyer (IDIBAPS), Ciber de Enfermedades R"
+      },
+      {
+        "author_name": "Rosario Menendez",
+        "author_inst": "Pulmonology Service, University and Polytechnic Hospital La Fe, Valencia / Centro de Investigacion Biomedica en Red en Enfermedades Respiratorias, Spain"
+      },
+      {
+        "author_name": "Jose Maria Eiros",
+        "author_inst": "Microbiology Service, Hospital Universitarios Rio Hortega, Valladolid, Spain."
+      },
+      {
+        "author_name": "David J Kelvin",
+        "author_inst": "Department of Microbiology and Immunology, Faculty of Medicine, Dalhousie University,Halifax, Nova Scotia, Canada / International Institute of Infection and Imm"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1172813,77 +1175909,45 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.29.272864",
-    "rel_title": "A simplified cell-based assay to identify coronavirus 3CL protease inhibitors",
+    "rel_doi": "10.1101/2020.08.29.257360",
+    "rel_title": "The SARS-CoV-2 ORF10 is not essential in vitro or in vivo in humans.",
     "rel_date": "2020-08-29",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.29.272864",
-    "rel_abs": "We describe a mammalian cell-based assay capable of identifying coronavirus 3CL protease (3CLpro) inhibitors without requiring the use of live virus. By enabling the facile testing of compounds across a range of coronavirus 3CLpro enzymes, including the one from SARS-CoV-2, we are able to quickly identify compounds with broad or narrow spectra of activity. We further demonstrate the utility of our approach by performing a curated compound screen along with structure-activity profiling of a series of small molecules to identify compounds with antiviral activity. Throughout these studies, we observed concordance between data emerging from this assay and from live virus assays. By democratizing the testing of 3CL inhibitors to enable screening in the majority of laboratories rather than the few with extensive biosafety infrastructure, we hope to expedite the search for coronavirus 3CL protease inhibitors, to address the current epidemic and future ones that will inevitably arise.",
-    "rel_num_authors": 15,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.29.257360",
+    "rel_abs": "SARS-CoV-2 genome annotation revealed the presence of 10 open reading frames (ORFs), of which the last one (ORF10) is positioned downstream the N gene. It is a hypothetical gene, which was speculated to encode a 38 aa protein. This hypothetical protein does not share sequence similarity with any other known protein and cannot be associated with a function. While the role of this ORF10 was proposed, there is a growing evidence showing that the ORF10 is not a coding region.\n\nHere, we identified SARS-CoV-2 variants in which the ORF10 gene was prematurely terminated. The disease was not attenuated, and the transmissibility between humans was not hampered. Also in vitro, the strains replicated similarly, as the related viruses with the intact ORF10. Altogether, based on clinical observation and laboratory analyses, it appears that the ORF10 protein is not essential in humans. This observation further proves that the ORF10 should not be treated as the protein-coding gene, and the genome annotations should be amended.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Samuel J Resnick",
-        "author_inst": "Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Sho Iketani",
-        "author_inst": "Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Seo Jung Hong",
-        "author_inst": "Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Arie Zask",
-        "author_inst": "Columbia University"
+        "author_name": "Katarzyna Pancer",
+        "author_inst": "Department of Virology, National Institute of Public Health-National Institute of Hygiene, Chocimska 24, 00-791 Warsaw, Poland."
       },
       {
-        "author_name": "Hengrui Liu",
-        "author_inst": "Columbia University"
-      },
-      {
-        "author_name": "Sungsoo Kim",
-        "author_inst": "Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Schuyler Melore",
-        "author_inst": "Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Manoj S Nair",
-        "author_inst": "Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Yaoxing Huang",
-        "author_inst": "Columbia University Irving Medical Center"
-      },
-      {
-        "author_name": "Nicholas E S Tay",
-        "author_inst": "Columbia University"
+        "author_name": "Aleksandra Milewska",
+        "author_inst": "Malopolska Centre of Biotechnology; Jagiellonian University; ul. Gronostajowa 7A; 30-387 Krakow, Poland, Europe"
       },
       {
-        "author_name": "Tomislav Rovis",
-        "author_inst": "Columbia University"
+        "author_name": "Katarzyna Owczarek",
+        "author_inst": "Malopolska Centre of Biotechnology; Jagiellonian University; ul. Gronostajowa 7A; 30-387 Krakow, Poland, Europe"
       },
       {
-        "author_name": "Hee Won Yang",
-        "author_inst": "Columbia University Irving Medical Center"
+        "author_name": "Agnieszka Dabrowska",
+        "author_inst": "Malopolska Centre of Biotechnology; Jagiellonian University; ul. Gronostajowa 7A; 30-387 Krakow, Poland, Europe"
       },
       {
-        "author_name": "Brent R Stockwell",
-        "author_inst": "Columbia University"
+        "author_name": "Wojciech Branicki",
+        "author_inst": "Malopolska Centre of Biotechnology; Jagiellonian University; ul. Gronostajowa 7A; 30-387 Krakow, Poland, Europe"
       },
       {
-        "author_name": "David D Ho",
-        "author_inst": "Columbia University Irving Medical Center"
+        "author_name": "Marek Sanak",
+        "author_inst": "Department of Internal Medicine, Faculty of Medicine, Jagiellonian University Medical College, ul. Skawinska 8, 31-066 Krakow, Poland, Europe"
       },
       {
-        "author_name": "Alejandro Chavez",
-        "author_inst": "Columbia University Irving Medical Center"
+        "author_name": "Krzysztof Pyrc",
+        "author_inst": "Malopolska Centre of Biotechnology; Jagiellonian University; ul. Gronostajowa 7A; 30-387 Krakow, Poland, Europe"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
     "category": "microbiology"
   },
@@ -1174582,43 +1177646,55 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.08.27.270637",
-    "rel_title": "Structure of SARS-CoV-2 ORF8, a rapidly evolving coronavirus protein implicated in immune evasion",
+    "rel_doi": "10.1101/2020.08.26.267781",
+    "rel_title": "Compositional Variability and Mutation Spectra of Monophyletic SARS-CoV-2 Clades",
     "rel_date": "2020-08-27",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.27.270637",
-    "rel_abs": "The molecular basis for the severity and rapid spread of the COVID-19 disease caused by SARS-CoV-2 is largely unknown. ORF8 is a rapidly evolving accessory protein that has been proposed to interfere with immune responses. The crystal structure of SARS-CoV-2 ORF8 was determined at 2.04 [A] resolution by x-ray crystallography. The structure reveals a ~60 residue core similar to SARS-CoV ORF7a with the addition of two dimerization interfaces unique to SARS-CoV-2 ORF8. A covalent disulfide-linked dimer is formed through an N-terminal sequence specific to SARS-CoV-2, while a separate non-covalent interface is formed by another SARS-CoV-2-specific sequence, 73YIDI76. Together the presence of these interfaces shows how SARS-CoV-2 ORF8 can form unique large-scale assemblies not possible for SARS-CoV, potentially mediating unique immune suppression and evasion activities.",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.26.267781",
+    "rel_abs": "COVID-19 and its causative pathogen SARS-CoV-2 have rushed the world into a staggering pandemic in a few months and a global fight against both is still going on. Here, we describe an analysis procedure where genome composition and its variables are related, through the genetic code, to molecular mechanisms based on understanding of RNA replication and its feedback loop from mutation to viral proteome sequence fraternity including effective sites on replicase-transcriptase complex. Our analysis starts with primary sequence information and identity-based phylogeny based on 22,051 SARS-CoV-2 genome sequences and evaluation of sequence variation patterns as mutation spectrum and its 12 permutations among organized clades tailored to two key mechanisms: strand-biased and function-associated mutations. Our findings include: (1) The most dominant mutation is C-to-U permutation whose abundant second-codon-position counts alter amino acid composition toward higher molecular weight and lower hydrophobicity albeit assumed most slightly deleterious. (2) The second abundance group includes: three negative-strand mutations U-to-C, A-to-G, G-to-A and a positive-strand mutation G-to-U generated through an identical mechanism as C-to-U. (3) A clade-associated and biased mutation trend is found attributable to elevated level of the negative-sense strand synthesis. (4) Within-clade permutation variation is very informative for associating non-synonymous mutations and viral proteome changes. These findings demand a bioinformatics platform where emerging mutations are mapped on to mostly subtle but fast-adjusting viral proteomes and transcriptomes to provide biological and clinical information after logical convergence for effective pharmaceutical and diagnostic applications. Such thoughts and actions are in desperate need, especially in the middle of the War against COVID-19.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Thomas G Flower",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Xufei Teng",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Cosmo Z Buffalo",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Qianpeng Li",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Richard M Hooy",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Zhao Li",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Marc Allaire",
-        "author_inst": "Lawrence Berkeley National Laboratory"
+        "author_name": "Yuansheng Zhang",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
       },
       {
-        "author_name": "Xuefeng Ren",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Guangyi Niu",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
       },
       {
-        "author_name": "James H Hurley",
-        "author_inst": "UC Berkeley"
+        "author_name": "Jingfa Xiao",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Jun Yu",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Zhang Zhang",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
+      },
+      {
+        "author_name": "Shuhui Song",
+        "author_inst": "Beijing Institute of Genomics, Chinese Academy of Sciences"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "biophysics"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.08.27.269738",
@@ -1176184,91 +1179260,99 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.08.26.266825",
-    "rel_title": "Multi-species ELISA for the detection of antibodies against SARS-CoV-2 in animals",
+    "rel_doi": "10.1101/2020.08.25.267328",
+    "rel_title": "A unique view of SARS-CoV-2 through the lens of ORF8 protein",
     "rel_date": "2020-08-26",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.26.266825",
-    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with millions of infected humans and hundreds of thousands of fatalities. As the novel disease - referred to as COVID-19 - unfolded, occasional anthropozoonotic infections of animals by owners or caretakers were reported in dogs, felid species and farmed mink. Further species were shown to be susceptible under experimental conditions. The extent of natural infections of animals, however, is still largely unknown. Serological methods will be useful tools for tracing SARS-CoV-2 infections in animals once test systems are validated for use in different species. Here, we developed an indirect multi-species ELISA based on the receptor-binding domain (RBD) of SARS-CoV-2. The newly established ELISA was validated using 59 sera of infected or vaccinated animals including ferrets, raccoon dogs, hamsters, rabbits, chickens, cattle and a cat, and a total of 220 antibody-negative sera of the same animal species. Overall, a diagnostic specificity of 100.0% and sensitivity of 98.31% was achieved, and the functionality with every species included in this study could be demonstrated. Hence, a versatile and reliable ELISA protocol was established that enables high-throughput antibody detection in a broad range of animal species, which may be used for outbreak investigations, to assess the seroprevalence in susceptible species or to screen for reservoir or intermediate hosts.",
-    "rel_num_authors": 18,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.25.267328",
+    "rel_abs": "Immune evasion is one of the unique characteristics of COVID-19 attributed to the ORF8 protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This protein is involved in modulating the host adaptive immunity through downregulating MHC (Major Histocompatibility Complex) molecules and innate immune responses by surpassing the interferon mediated antiviral response of the host. To understand the immune perspective of the host with respect to the ORF8 protein, a comprehensive study of the ORF8 protein as well as mutations possessed by it, is performed. Chemical and structural properties of ORF8 proteins from different hosts, that is human, bat and pangolin, suggests that the ORF8 of SARS-CoV-2 and Bat RaTG13-CoV are very much closer related than that of Pangolin-CoV. Eighty-seven mutations across unique variants of ORF8 (SARS-CoV-2) are grouped into four classes based on their predicted effects. Based on geolocations and timescale of collection, a possible flow of mutations was built. Furthermore, conclusive flows of amalgamation of mutations were endorsed upon sequence similarity and amino acid conservation phylogenies. Therefore, this study seeks to highlight the uniqueness of rapid evolving SARS-CoV-2 through the ORF8.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Kerstin Wernike",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Sk. Sarif Hassan",
+        "author_inst": "Department of Mathematics, Pingla Thana Mahavidyalaya, Maligram 721140, India"
       },
       {
-        "author_name": "Andrea Aebischer",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Shinjini Ghosh",
+        "author_inst": "Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata 700009, West Bengal, India"
       },
       {
-        "author_name": "Anna Michelitsch",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Diksha Attrish",
+        "author_inst": "Dr. B. R. Ambedkar Centre For Biomedical Research (ACBR), University of Delhi (North Campus), Delhi 110007, India"
       },
       {
-        "author_name": "Donata Hoffmann",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Pabirtra Pal Choudhury",
+        "author_inst": "Applied Statistics Unit, Indian Statistical Institute, Kolkata 700108, West Bengal, India"
       },
       {
-        "author_name": "Conrad Freuling",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Murat Seyran",
+        "author_inst": "Doctoral studies in natural and technical sciences (SPL 44), University of Vienna"
       },
       {
-        "author_name": "Anne Balkema-Buschmann",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Damiano Pizzol",
+        "author_inst": "Italian Agency for Development Cooperation - Khartoum, Sudan Street 33, Al Amarat, Sudan"
       },
       {
-        "author_name": "Annika Graaf",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Parise Adadi",
+        "author_inst": "Department of Food Science, University of Otago, Dunedin 9054, New Zealand"
       },
       {
-        "author_name": "Thomas Mueller",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Tarek Muhammed Abd El Aziz",
+        "author_inst": "Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229-3900, USA"
       },
       {
-        "author_name": "Nikolaus Osterrieder",
-        "author_inst": "Freie Universitaet Berlin"
+        "author_name": "Antonio Soares",
+        "author_inst": "Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229-3900, USA"
       },
       {
-        "author_name": "Melanie Rissmann",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Ramesh Kandimalla",
+        "author_inst": "CSIR-Indian Institute of Chemical Technology Uppal Road, Tarnaka, Hyderabad-500007, Telangana State, India"
       },
       {
-        "author_name": "Dennis Rubbenstroth",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Kenneth Lundstrom",
+        "author_inst": "PanTherapeutics, Rte de Lavaux 49, CH1095 Lutry, Switzerland"
       },
       {
-        "author_name": "Jacob Schoen",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Murtaza Tambuwala",
+        "author_inst": "School of Pharmacy and Pharmaceutical Science, Ulster University, Coleraine BT52 1SA, Northern Ireland, UK"
       },
       {
-        "author_name": "Claudia Schulz",
-        "author_inst": "University of Veterinary Medicine Hannover"
+        "author_name": "Alaa AA Aljabali",
+        "author_inst": "Department of Pharmaceutics and Pharmaceutical Technology, Yarmouk University-Faculty of Pharmacy, Irbid 566, Jordan"
       },
       {
-        "author_name": "Jakob Trimpert",
-        "author_inst": "Freie Universitaet Berlin"
+        "author_name": "Amos Lal",
+        "author_inst": "Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, USA"
       },
       {
-        "author_name": "Lorenz Ulrich",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Gajendra Kumar Azad",
+        "author_inst": "Department of Zoology, Patna University, Patna-800005, Bihar, India"
       },
       {
-        "author_name": "Asisa Volz",
-        "author_inst": "University of Veterinary Medicine Hannover"
+        "author_name": "Vladimir N Uversky",
+        "author_inst": "Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA"
       },
       {
-        "author_name": "Thomas Mettenleiter",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Samendra P Sherchan",
+        "author_inst": "Department of Environmental Health Sciences, Tulane University, New Orleans, LA, 70112, USA"
       },
       {
-        "author_name": "Martin Beer",
-        "author_inst": "Friedrich-Loeffler-Institut"
+        "author_name": "Wagner Baetas-da-Cruz",
+        "author_inst": "ranslational Laboratory in Molecular Physiology, Centre for Experimental Surgery, College of Medicine, Federal University of Rio de Janeiro (UFRJ), Rio de Janei"
+      },
+      {
+        "author_name": "Bruce Uhal",
+        "author_inst": "Department of Physiology, Michigan State University, East Lansing, MI 48824, USA"
+      },
+      {
+        "author_name": "Adam Brufsky",
+        "author_inst": "UPMC Hillman Cancer Center, 300 Halket Street, Suite 4628, University of Pittsburgh, Pittsburgh, PA, USA"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2020.08.25.265074",
@@ -1178122,51 +1181206,39 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.08.23.20180307",
-    "rel_title": "Hesitant or not? A global survey of potential acceptance of a COVID-19 vaccine",
+    "rel_doi": "10.1101/2020.08.23.20180513",
+    "rel_title": "3D Printed N95 Equivalent for PPE Shortages: The Kansas City Mask",
     "rel_date": "2020-08-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.23.20180307",
-    "rel_abs": "A number of COVID-19 vaccines are under development, with one or more possibly becoming available in 2021. We conducted a global survey in June 2020 of 13,426 people in 19 countries to determine potential acceptance rates of a COVID-19 vaccine and factors influencing acceptance. We ran univariate logistic regressions to examine the associations with demographic variables. 71.5% reported they would be very or somewhat likely to take a COVID-19 vaccine; 61.4% reported they would accept their employers recommendation to take a COVID-19 vaccine. Differences in acceptance across countries ranged from almost 9 in 10 (China) to fewer than 6 in 10 (Russia). Respondents reporting higher levels of trust in information from government sources were more likely to accept a vaccine, and take their employers advice to do so. Targeted interventions addressing age, sex, income, and education level are required to increase and sustain public acceptance of a COVID-19 vaccine.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.23.20180513",
+    "rel_abs": "IntroductionDuring the COVID-19 pandemic, the shortage of personal protective equipment (PPE) was well-reported and discussed, not only in the healthcare sector but across all of society as the demands for PPE skyrocketed. As hospitalizations for COVID-19-related illness continue to increase, many recent reports indicate the supply of PPE is persistently and significantly less than the demand. These PPE shortages encouraged communities of 3D printing experts and hobbyists to design and distribute homemade, 3D-printed PPE, including N95 mask substitutes. The mask presented, the Kansas City Mask (KC Mask), is one such product which was created from the maker community in partnership with local physicians and hospitals. This report discusses the design, manufacturing, and validation of the KC Mask design and its usage in the COVID-19 pandemic as well as future use as stopgap PPE.\n\nMethodsThe KC Mask was adapted from a similar design called the Montana Mask. Mask components were 3D printed and assembled then fit tested by qualitative fit testing (QLFT) at Truman Medical Center in Kansas City, MO as a proof of concept.\n\nResultsThe QLFT was successful and the KC Mask was approved for use by pandemic response administration staff at the hospital. Fortunately, the KC Mask has not required wide utilization, however, because supply chains for Kansas City area hospitals have, at the time of this publication, not yet been exhausted by the pandemic.\n\nConclusionThe results of Truman Medical Centers approval of the KC Mask are promising for this N95 stop-gap substitute. Although further analysis and study is needed for this design, persistently increasing caseloads and PPE shortages necessitate an urgent dissemination of these preliminary results. The authors do not advocate for the KC Mask as a replacement of traditional N95 masks or other PPE but do endorse the KC Mask as a stopgap measure, proven to be effective in situations of dire PPE shortage based on CDC guidelines.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Jeffrey V Lazarus",
-        "author_inst": "Barcelona Institute for Global Health (ISGlobal)"
-      },
-      {
-        "author_name": "Scott Ratzan",
-        "author_inst": "City University of New York (CUNY) Graduate School of Public Health & Health Policy, New York, USA"
-      },
-      {
-        "author_name": "Adam Palayew",
-        "author_inst": "Barcelona Institute for Global Health (ISGlobal)"
-      },
-      {
-        "author_name": "Lawrence O Gostin",
-        "author_inst": "Georgetown University, Washington, DC, USA"
+        "author_name": "Shiv Dalla",
+        "author_inst": "University of Kansas School of Medicine"
       },
       {
-        "author_name": "Heidi J Larson",
-        "author_inst": "London School of Hygiene and Tropical Medicine, London, United Kingdom"
+        "author_name": "Brandon Bacon",
+        "author_inst": "University of Missouri - Kansas City, Truman Medical Center"
       },
       {
-        "author_name": "Kenneth Rabin",
-        "author_inst": "City University of New York (CUNY) Graduate School of Public Health & Health Policy, New York, USA"
+        "author_name": "Jack M Ayres",
+        "author_inst": "University of Kansas School of Medicine"
       },
       {
-        "author_name": "Spencer Kimball",
-        "author_inst": "Emerson College, Boston, Mass, USA"
+        "author_name": "Stephen Holmstead",
+        "author_inst": "Unaffiliated"
       },
       {
-        "author_name": "Ayman El-Mohandes",
-        "author_inst": "City University of New York (CUNY) Graduate School of Public Health & Health Policy, New York, USA"
+        "author_name": "Alan J Ahlberg Elliot",
+        "author_inst": "Unaffiliated"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "occupational and environmental health"
   },
   {
     "rel_doi": "10.1101/2020.08.22.20179994",
@@ -1179895,55 +1182967,103 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2020.08.24.264077",
-    "rel_title": "An hACE2 peptide mimic blocks SARS-CoV-2 Pulmonary Cell Infection",
+    "rel_doi": "10.1101/2020.08.24.264630",
+    "rel_title": "SARS-CoV-2 neutralizing human antibodies protect against lower respiratory tract disease in a hamster model",
     "rel_date": "2020-08-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.24.264077",
-    "rel_abs": "In the light of the recent accumulated knowledge on SARS-CoV-2 and its mode of human cells invasion, the binding of viral spike glycoprotein to human Angiotensin Converting Enzyme 2 (hACE2) receptor plays a central role in cell entry. We designed a series of peptides mimicking the N-terminal helix of hACE2 protein which contains most of the contacting residues at the binding site and have a high helical folding propensity in aqueous solution. Our best peptide mimics bind to the virus spike protein with high affinity and are able to block SARS-CoV-2 human pulmonary cell infection with an inhibitory concentration (IC50) in the nanomolar range. These first in class blocking peptide mimics represent powerful tools that might be used in prophylactic and therapeutic approaches to fight the coronavirus disease 2019 (COVID-19).",
-    "rel_num_authors": 9,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.24.264630",
+    "rel_abs": "Effective clinical intervention strategies for COVID-19 are urgently needed. Although several clinical trials have evaluated the use of convalescent plasma containing virus-neutralizing antibodies, the effectiveness has not been proven. We show that hamsters treated with a high dose of human convalescent plasma or a monoclonal antibody were protected against weight loss showing reduced pneumonia and pulmonary virus replication compared to control animals. However, a ten-fold lower dose of convalescent plasma showed no protective effect. Thus, variable and relatively low levels of virus neutralizing antibodies in convalescent plasma may limit their use for effective antiviral therapy, favouring concentrated, purified (monoclonal) antibodies.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Philippe Karoyan",
-        "author_inst": "Sorbonne Universite"
+        "author_name": "Bart L Haagmans",
+        "author_inst": "Erasmus Medical Center"
       },
       {
-        "author_name": "Vincent Vieillard",
-        "author_inst": "Sorbonne Universite"
+        "author_name": "Danny Noack",
+        "author_inst": "Erasmus Medical Center"
       },
       {
-        "author_name": "Estelle Odile",
-        "author_inst": "Sorbonne Universite"
+        "author_name": "Nisreen M.A. Okba",
+        "author_inst": "Erasmus MC"
       },
       {
-        "author_name": "Alexis Denis",
-        "author_inst": "Oncodesign"
+        "author_name": "Wentao LI",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Chunyan Wang",
+        "author_inst": "Utrecht University"
       },
       {
-        "author_name": "amelie guihot",
-        "author_inst": "Assistance Publique Hopitaux de Paris Hopital Pitie Salpetriere Service de Medecine Intensive Reanimation Institut de Cardiologie 75013, Paris, France"
+        "author_name": "Theo Bestebroer",
+        "author_inst": "Erasmus Medical Center"
       },
       {
-        "author_name": "charles edouard luyt",
-        "author_inst": "Assistance Publique Hopitaux de Paris, Hopital Pitie Salpetriere, Service de Medecine Intensive Reanimation, Institut de Cardiologie 75013 Paris France"
+        "author_name": "Rory de Vries",
+        "author_inst": "Erasmus Medical Center"
       },
       {
-        "author_name": "Luis Gomes-Morales",
-        "author_inst": "Sorbonne Universite"
+        "author_name": "Sander Herfst",
+        "author_inst": "Erasmus MC"
       },
       {
-        "author_name": "Pascal Grondin",
-        "author_inst": "Oncodesign"
+        "author_name": "Dennis de Meulder",
+        "author_inst": "Erasmus Medical Center"
       },
       {
-        "author_name": "Olivier Lequin",
-        "author_inst": "Sorbonne Universite"
+        "author_name": "Peter van Run",
+        "author_inst": "Erasmus Medical Center"
+      },
+      {
+        "author_name": "Mart M Lamers",
+        "author_inst": "Erasmus MC"
+      },
+      {
+        "author_name": "Bart Rijnders",
+        "author_inst": "Erasmus Medical Center"
+      },
+      {
+        "author_name": "Casper Rokx",
+        "author_inst": "Erasmus Medical Center"
+      },
+      {
+        "author_name": "Frank J.M. van Kuppeveld",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Frank Grosveld",
+        "author_inst": "Erasmus Medical Center Rotterdam"
+      },
+      {
+        "author_name": "Dubravka Drabek",
+        "author_inst": "Erasmus Medical Center"
+      },
+      {
+        "author_name": "Corine GeurtsvanKessel",
+        "author_inst": "Erasmus Medical Center"
+      },
+      {
+        "author_name": "Marion Koopmans",
+        "author_inst": "Erasmus Medical Center"
+      },
+      {
+        "author_name": "Berend Jan Bosch",
+        "author_inst": "Utrecht University"
+      },
+      {
+        "author_name": "Thijs Kuiken",
+        "author_inst": "Erasmus MC"
+      },
+      {
+        "author_name": "Barry Rockx",
+        "author_inst": "Erasmus University Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "pharmacology and toxicology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.08.22.258459",
@@ -1181433,47 +1184553,47 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.08.23.255364",
-    "rel_title": "Antiviral activity of lambda-carrageenan against influenza viruses in mice and severe acute respiratory syndrome coronavirus 2 in vitro",
-    "rel_date": "2020-08-24",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.23.255364",
-    "rel_abs": "Influenza virus and coronavirus, belonging to enveloped RNA viruses, are major causes of human respiratory diseases. The aim of this study was to investigate the broad spectrum antiviral activity of a naturally existing sulfated polysaccharide, lambda-carrageenan ({lambda}-CGN), purified from marine red algae. Cell culture-based assays revealed that the macromolecule efficiently inhibited both influenza A and B viruses, as well as currently circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with EC50 values ranging from 0.3-1.4 g/ml. No toxicity to host cells was observed at concentrations up to 300 g/ml. Plaque titration and western blot analysis verified that {lambda}-CGN reduced expression of viral proteins in cell lysates and suppressed progeny virus production in culture supernatants in a dose-dependent manner. This polyanionic compound exerts antiviral activity by targeting viral attachment to cell surface receptors and preventing entry. Moreover, intranasal administration to mice during influenza A viral challenge not only alleviated infection-mediated reductions in body weight but also protected 60% of mice from virus-induced mortality. Thus, {lambda}-CGN could be a promising antiviral agent for preventing infection by several respiratory viruses.",
+    "rel_doi": "10.1101/2020.08.20.20178723",
+    "rel_title": "Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)",
+    "rel_date": "2020-08-23",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20178723",
+    "rel_abs": "COVID-19 is a pandemic infectious disease caused by the SARS-CoV-2 virus, having reached more than 210 countries and territories. It produces symptoms such as fever, dry cough, dyspnea, fatigue, pneumonia, and radiological manifestations.\n\nThe most common reported RX and CT findings include lung consolidation and ground-glass opacities.\n\nIn this paper, we describe a machine learning-based system (XrayCoviDetector; until the image has a size www.covidetector.net), that detects automatically, the probability that a thorax radiological image includes COVID-19 lung patterns.\n\nXrayCoviDetector has an accuracy of 0.93, a sensitivity of 0.96, and a specificity of 0.90.",
     "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Ye Jin Jang",
-        "author_inst": "Korea Research Institute of Chemical Technology"
+        "author_name": "Juan Nicolas Schlotterbeck",
+        "author_inst": "Health Innovation Center, Clinica las Condes, Santiago, Chile"
       },
       {
-        "author_name": "Heegwon Shin",
-        "author_inst": "Korea Advanced Institute of Science and Technology"
+        "author_name": "Carlos E Montoya",
+        "author_inst": "Health Innovation Center, Clinica las Condes, Santiago, Chile"
       },
       {
-        "author_name": "Myoung Kyu Lee",
-        "author_inst": "Korea Research Institute of Chemical Technology"
+        "author_name": "Patricia Bitar",
+        "author_inst": "Department of Radiology, Clinica las Condes, Santiago, Chile"
       },
       {
-        "author_name": "Oh Seung Kwon",
-        "author_inst": "Korea Research Institute of Chemical Technology"
+        "author_name": "Jorge A Fuentes",
+        "author_inst": "Health Innovation Center, Clinica las Condes, Santiago, Chile"
       },
       {
-        "author_name": "Jin Soo Shin",
-        "author_inst": "Korea Research Institute of Chemical Technology"
+        "author_name": "Victor Dinamarca",
+        "author_inst": "Department of Radiology, Clinica las Condes, Santiago, Chile"
       },
       {
-        "author_name": "Yongil Kim",
-        "author_inst": "Hanmi Pharmaceutical Co."
+        "author_name": "Gonzalo M Rojas",
+        "author_inst": "Health Innovation Center, Clinica las Condes, Santiago, Chile"
       },
       {
-        "author_name": "Meehyein Kim",
-        "author_inst": "Korea Research Institute of Chemical Technology"
+        "author_name": "Marcelo Galvez",
+        "author_inst": "Academic Direction, Clinica Las Condes, Santiago, Chile"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2020.08.20.20178780",
@@ -1183119,29 +1186239,57 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.19.20178129",
-    "rel_title": "Epidemic Analysis of COVID-19 in Egypt, Qatar and Saudi Arabia using the Generalized SEIR Model",
+    "rel_doi": "10.1101/2020.08.19.20177956",
+    "rel_title": "Disparities in COVID-19 Hospitalizations and Mortality among Black and Hispanic Patients: Cross-Sectional Analysis from the Greater Houston Metropolitan Area",
     "rel_date": "2020-08-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.19.20178129",
-    "rel_abs": "BackgroundSince its emergence in late December 2019 and its declaration as a global pandemic by World Health Organization (WHO) on March 11, 2020, the novel coronavirus disease known as (COVID-19) has attracted global attention. The process of modeling and predicting the pandemic behavior became crucial as the different states needed accurate predictions to be able to adopt suitable policies to minimize the pressure on their health care systems. Researchers have employed modified variants of classical SIR/SEIR models to describe the dynamics of this pandemic. In this paper, after proven effective in numerous countries, a modified variant of SEIR is implemented to predict the behavior of COVID-19 in Egypt and other countries in the Middle East and North Africa region (MENA).\n\nMethodsWe built MATLAB simulations to fit the real data of COVID-19 Active, recovered and death Cases in Egypt, Qatar and Saudi Arabia to the modified SEIR model via Nelder-Mead algorithm to be able to estimate the future dynamics of the pandemic.\n\nFindingsWe estimate several characteristics of COVID-19 future dynamics in Egypt, Qatar and Saudi Arabia. We also estimate that the pandemic will resolve in the countries under investigation in February 2021, January 2021 and 28th August 2020 With total death cases of 9,742, 5,600, 185 and total cases of 187,600, 490,000, 120,000, respectively.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.19.20177956",
+    "rel_abs": "BackgroundDisparate racial and ethnic burdens of the Coronavirus Disease 2019 (COVID-19) pandemic may be attributable to higher susceptibility to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or to factors such as differences in hospitalization and care provision.\n\nMethodsIn our cross-sectional analysis of lab-confirmed COVID-19 cases from a tertiary, eight-hospital healthcare system (Houston Methodist) across greater Houston, multivariable logistic regression models were fitted to evaluate the odds of hospitalization and mortality for non-Hispanic Blacks (NHBs) vs. non-Hispanic Whites (NHWs) and Hispanics vs. non-Hispanics.\n\nFindingsBetween March 3rd and July 18th, 2020, 70,496 individuals were tested for SARS-CoV-2; 12,084 (17{middle dot}1%) tested positive, of whom 3,536 (29{middle dot}3%) were hospitalized. Among positive cases, NHBs and Hispanics were significantly younger than NHWs and Hispanics, respectively (mean age NHBs vs. NHWs: 46.0 vs. 51.7 year and Hispanic vs. non-Hispanic: 44.0 vs. 48.7 years). Despite younger age, NHBs (vs. NHWs) had a higher prevalence of diabetes (25.2%), hypertension (47.7%), and chronic kidney disease (5.0%). Both minority groups resided in lower median income and higher population density areas. In fully adjusted models, NHBs and Hispanics had higher likelihoods of hospitalization, aOR (CI): 1{middle dot}42 (1{middle dot}24-1{middle dot}63) and 1{middle dot}61 (1{middle dot}46-1{middle dot}78), respectively. No differences were observed in intensive care unit (ICU) utilization or treatment parameters. Models adjusted for demographics, vital signs, laboratory parameters, hospital complications, and ICU admission demonstrated non-significantly lower likelihoods of in-hospital mortality among NHBs and Hispanics, aOR (CI): 0{middle dot}65 (0{middle dot}40-1{middle dot}03) and 0{middle dot}89 (0{middle dot}59-1{middle dot}31), respectively.\n\nInterpretationOur data did not demonstrate racial and ethnic differences in care provision and hospital outcomes. Higher susceptibility of racial and ethnic minorities to SARS-CoV-2 and subsequent hospitalization may be driven primarily by social determinants.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Ahmed E Fahmy",
-        "author_inst": "Zewail University of Science and Technology"
+        "author_name": "Alan Pan",
+        "author_inst": "Houston Methodist"
+      },
+      {
+        "author_name": "Osman Khan",
+        "author_inst": "Houston Methodist"
       },
       {
-        "author_name": "Mohammed M Eldesouky",
-        "author_inst": "Zewail University of Science and Technology"
+        "author_name": "Jennifer Meeks",
+        "author_inst": "Houston Methodist"
+      },
+      {
+        "author_name": "Marc Boom",
+        "author_inst": "Houston Methodist"
       },
       {
-        "author_name": "Ahmed S.A. Mohamed",
-        "author_inst": "Zewail University of Science and Technology"
+        "author_name": "Faisal Masud",
+        "author_inst": "Houston Methodist"
+      },
+      {
+        "author_name": "Julia Andrieni",
+        "author_inst": "Houston Methodist"
+      },
+      {
+        "author_name": "Robert Phillips",
+        "author_inst": "Houston Methodist"
+      },
+      {
+        "author_name": "Yordanos Tiruneh",
+        "author_inst": "University of Texas Health Science Center at Tyler"
+      },
+      {
+        "author_name": "Bita Kash",
+        "author_inst": "Houston Methodist"
+      },
+      {
+        "author_name": "Farhaan Vahidy",
+        "author_inst": "Houston Methodist Research Institute"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1184613,37 +1187761,57 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.17.20176735",
-    "rel_title": "Comparing the Fit of N95, KN95, Surgical, and Cloth Face Masks and Assessing the Accuracy of Fit Checking",
+    "rel_doi": "10.1101/2020.08.17.20175117",
+    "rel_title": "Real-time spatial health surveillance: mapping the UK COVID-19 epidemic",
     "rel_date": "2020-08-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.17.20176735",
-    "rel_abs": "IntroductionThe COVID-19 pandemic has made well-fitting face masks a critical piece of protective equipment for healthcare workers and civilians. While the importance of wearing face masks has been acknowledged, there remains a lack of understanding about the role of good fit in rendering protective equipment useful. In addition, supply chain constraints have caused some organizations to abandon traditional quantitative or qualitative fit testing, and instead, have implemented subjective fit checking. Our study seeks to quantitatively evaluate the level of fit offered by various types of masks, and most importantly, assess the accuracy of implementing fit checks by comparing fit check results to quantitative fit testing results.\n\nMethodsSeven participants first evaluated N95 and KN95 masks by performing a fit check. Participants then underwent quantitative fit testing wearing five N95 masks, a KN95 mask, a surgical mask, and fabric masks.\n\nResultsN95 masks offered higher degrees of protection than the other categories of masks tested; however, it should be noted that most N95 masks failed to fit the participants adequately. Fit check responses had poor correlation with quantitative fit scores. All non-N95 masks achieved low fit scores.\n\nConclusionFit is critical to the level of protection offered by masks. For an N95 mask to provide the promised protection, it must fit the participant. Performing a fit check was an unreliable way of determining fit.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.17.20175117",
+    "rel_abs": "The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. A pre-requisite to an effective control strategy is that predictions need to be accompanied by estimates of their precision, to guard against over-reaction to potentially spurious features of  best guess predictions. In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Eugenia O'Kelly",
-        "author_inst": "Cambridge University"
+        "author_name": "Richard Fry",
+        "author_inst": "Swansea University"
       },
       {
-        "author_name": "Anmol Arora",
-        "author_inst": "Cambridge University"
+        "author_name": "Joe Hollinghurst",
+        "author_inst": "Swansea University"
       },
       {
-        "author_name": "Sophia Pirog",
-        "author_inst": "Northwestern University"
+        "author_name": "Helen R Stagg",
+        "author_inst": "Edinburgh University"
       },
       {
-        "author_name": "James Ward",
-        "author_inst": "Cambridge University"
+        "author_name": "Daniel A Thompson",
+        "author_inst": "Swansea University"
       },
       {
-        "author_name": "P John Clarkson",
-        "author_inst": "Cambridge University"
+        "author_name": "Claudio Fronterre",
+        "author_inst": "Lancaster University"
+      },
+      {
+        "author_name": "Chris Orton",
+        "author_inst": "Swansea University"
+      },
+      {
+        "author_name": "Ronan A Lyons",
+        "author_inst": "Swansea University"
+      },
+      {
+        "author_name": "David V Ford",
+        "author_inst": "Swansea University"
+      },
+      {
+        "author_name": "Aziz Sheikh",
+        "author_inst": "Edinburgh University"
+      },
+      {
+        "author_name": "Peter J Diggle",
+        "author_inst": "Lancaster University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1186231,47 +1189399,31 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.20.260190",
-    "rel_title": "Astodrimer sodium, dendrimer antiviral, inhibits replication of SARS-CoV-2 in vitro",
+    "rel_doi": "10.1101/2020.08.21.261289",
+    "rel_title": "Ubiquitous Forbidden Order in R-group classified protein sequence of SARS-CoV-2 and other viruses",
     "rel_date": "2020-08-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.20.260190",
-    "rel_abs": "An effective response to the ongoing coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will involve a range of complementary preventive modalities. The current studies were conducted to evaluate the in vitro SARS-CoV-2 antiviral and virucidal activity of astodrimer sodium, a dendrimer with broad spectrum antimicrobial activity, including against enveloped viruses in in vitro and in vivo models, that is marketed for antiviral and antibacterial applications. We report that astodrimer sodium inhibits replication of SARS-CoV-2 in Vero E6 and Calu-3 cells, with 50% effective concentrations (EC50) for i) reducing virus-induced cytopathic effect of 0.002 to 0.012 mg/mL in Vero E6 cells, and ii) infectious virus release by plaque assay of 0.019 to 0.031 mg/mL in Vero E6 cells and 0.031 to 0.045 mg/mL in Calu-3 cells. The selectivity index (SI) in these assays was as high as 2197. Astodrimer sodium was also virucidal, reducing SARS-CoV-2 infectivity by >99.9% (>3 log10) within 1 minute of exposure, and up to >99.999% (>5 log10) shown at astodrimer sodium concentrations of 10 to 30 mg/mL in Vero E6 and Calu-3 cell lines. Astodrimer sodium also inhibited infection in a primary human airway epithelial cell line. The data were similar for all investigations and were consistent with the potent antiviral and virucidal activity of astodrimer sodium being due to inhibition of virus-host cell interactions, as previously demonstrated for other viruses. Further studies will confirm if astodrimer sodium binds to SARS-CoV-2 spike protein and physically blocks initial attachment of the virus to the host cell. Given the in vitro effectiveness and significantly high SI, astodrimer sodium warrants further investigation for potential as a nasally administered or inhaled antiviral agent for SARS-CoV-2 prevention and treatment applications.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.21.261289",
+    "rel_abs": "Each amino acid in a polypeptide chain has a distinctive R-group associated with it. We report here a novel method of species characterization based upon the order of these R-group classified amino acids in the linear sequence of the side chains associated with the codon triplets. In an otherwise pseudo-random sequence, we search for forbidden combinations of kth order. We applied this method to analyze the available protein sequences of various viruses including SARS-CoV-2. We found that these ubiquitous forbidden orders (UFO) are unique to each of the viruses we analyzed. This unique structure of the viruses may provide an insight into viruses chemical behavior and the folding patterns of the proteins. This finding may have a broad significance for the analysis of coding sequences of species in general.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jeremy R.A. Paull",
-        "author_inst": "Starpharma Pty Ltd"
-      },
-      {
-        "author_name": "Graham P. Heery",
-        "author_inst": "Starpharma Pty Ltd"
-      },
-      {
-        "author_name": "Michael D Bobardt",
-        "author_inst": "Scripps Research Institute"
-      },
-      {
-        "author_name": "Alex Castellarnau",
-        "author_inst": "Starpharma Pty Ltd"
-      },
-      {
-        "author_name": "Carolyn A. Luscombe",
-        "author_inst": "Starpharma Pty Ltd"
+        "author_name": "Pratibha Pratibha",
+        "author_inst": "Indian Institute of Technology Roorkee India"
       },
       {
-        "author_name": "Jacinth K. Fairley",
-        "author_inst": "Starpharma Pty Ltd"
+        "author_name": "Cyril Shaju",
+        "author_inst": "Indian Institute of Technology Roorkee India"
       },
       {
-        "author_name": "Philippe A Gallay",
-        "author_inst": "Scripps Research Institute"
+        "author_name": "Kamal Kamal",
+        "author_inst": "INDIAN INSTITUTE OF TECHNOLOGY ROORKEE INDIA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2020.08.18.20177261",
@@ -1187977,39 +1191129,39 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.16.20175901",
-    "rel_title": "Air pollution, SARS-CoV-2 transmission, and COVID-19 outcomes: A state-of-the-science review of a rapidly evolving research area",
+    "rel_doi": "10.1101/2020.08.19.257493",
+    "rel_title": "Exploring G and C-quadruplex structures as potential targets against the severe acute respiratory syndrome coronavirus 2",
     "rel_date": "2020-08-20",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.16.20175901",
-    "rel_abs": "BackgroundAs the coronavirus pandemic rages on, 692,000 (August 7, 2020) human lives and counting have been lost worldwide to COVID-19. Understanding the relationship between short- and long-term exposure to air pollution and adverse COVID-19 health outcomes is crucial for developing solutions to this global crisis.\n\nObjectivesTo conduct a scoping review of epidemiologic research on the link between short- and long-term exposure to air pollution and COVID-19 health outcomes.\n\nMethodWe searched PubMed, Web of Science, Embase, Cochrane, MedRxiv, and BioRxiv for preliminary epidemiological studies of the association between air pollution and COVID-19 health outcomes. 28 papers were finally selected after applying our inclusion/exclusion criteria; we categorized these studies as long-term studies, short-term time-series studies, or short-term cross-sectional studies. One study included both short-term time-series and a cross-sectional study design.\n\nResults27 studies of the 28 reported evidence of statistically significant positive associations between air pollutant exposure and adverse COVID-19 health outcomes; 11 of 12 long-term studies and all 16 short-term studies reported statistically significant positive associations. The 28 identified studies included various confounders, spatial and temporal resolutions of pollution concentrations, and COVID-19 health outcomes.\n\nDiscussionWe discuss methodological challenges and highlight additional research areas based on our findings. Challenges include data quality issues, ecological study design limitations, improved adjustment for confounders, exposure errors related to spatial resolution, geographic variability in testing, mitigation measures and pandemic stage, clustering of health outcomes, and a lack of publicly available data and code.",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.19.257493",
+    "rel_abs": "In this paper we report the analysis of the 2019-nCoV genome and related viruses using an upgraded version of the open-source algorithm G4-iM Grinder. This version improves the functionality of the software, including an easy way to determine the potential biological features affected by the candidates found. The quadruplex definitions of the algorithm were optimized for 2019-nCoV. Using a lax quadruplex definition ruleset, which accepts amongst other parameters two residue G- and C-tracks, hundreds of potential quadruplex candidates were discovered. These sequences were evaluated by their in vitro formation probability, their position in the viral RNA, their uniqueness and their conservation rates (calculated in over three thousand different COVID-19 clinical cases and sequenced at different times and locations during the ongoing pandemic). These results were compared sequentially to other Coronaviridae members, other Group IV (+)ssRNA viruses and the entire realm. Sequences found in common with other species were further analyzed and characterized. Sequences with high scores unique to the 2019-nCoV were studied to investigate the variations amongst similar species. Quadruplex formation of the best candidates was then confirmed experimentally. Using NMR and CD spectroscopy, we found several highly stable RNA quadruplexes that may be suitable theranostic targets against the 2019-nCoV.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC=\"FIGDIR/small/257493v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (50K):\norg.highwire.dtl.DTLVardef@1ab4843org.highwire.dtl.DTLVardef@152ebeorg.highwire.dtl.DTLVardef@afd7aforg.highwire.dtl.DTLVardef@793707_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
     "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Anushka Bhaskar",
-        "author_inst": "Harvard University"
+        "author_name": "Efres Belmonte Reche",
+        "author_inst": "Advanced (magnetic) Theranostic Nanostructures Lab, INL-International Iberian Nanotechnology Laboratory, Av. Mestre Jose Veiga, 4715-330 Braga, Portugal."
       },
       {
-        "author_name": "Jay Chandra",
-        "author_inst": "Harvard University"
+        "author_name": "Israel Serrano-Chacon",
+        "author_inst": "Instituto de Quimica Fisica Rocasolano, CSIC, 28006 Madrid, Spain."
       },
       {
-        "author_name": "Danielle Braun",
-        "author_inst": "Harvard TH Chan School of Public Health"
+        "author_name": "Carlos Gonzalez",
+        "author_inst": "Instituto de Quimica Fisica Rocasolano, CSIC, 28006 Madrid, Spain."
       },
       {
-        "author_name": "Jacqueline Cellini",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Juan Gallo",
+        "author_inst": "Advanced (magnetic) Theranostic Nanostructures Lab, INL-International Iberian Nanotechnology Laboratory, Av. Mestre Jose Veiga, 4715-330 Braga, Portugal."
       },
       {
-        "author_name": "Francesca Dominici",
-        "author_inst": "Harvard TH Chan School of Public Health"
+        "author_name": "Manuel Banobre-Lopez",
+        "author_inst": "Advanced (magnetic) Theranostic Nanostructures Lab, INL-International Iberian Nanotechnology Laboratory, Av. Mestre Jose Veiga, 4715-330 Braga, Portugal."
       }
     ],
     "version": "1",
     "license": "cc_by_nc",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "occupational and environmental health"
+    "type": "new results",
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2020.08.19.255901",
@@ -1189923,43 +1193075,115 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.08.17.20174821",
-    "rel_title": "Quantifying the efficiency of non-pharmaceutical interventions against SARS-COV-2 transmission in Europe",
+    "rel_doi": "10.1101/2020.08.17.20176552",
+    "rel_title": "SARS-CoV-2 antibody responses in children with MIS-C and mild and severe COVID-19",
     "rel_date": "2020-08-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.17.20174821",
-    "rel_abs": "Since the emergence of SARS-CoV-2, governments around the World have implemented a combination of public health responses based on non-pharmaceutical interventions (NPIs), with significant social and economic consequences. Though most European countries have overcome the first epidemic wave, it remains of high priority to quantify the efficiency of different NPIs to inform preparedness for an impending second wave. In this study, combining capture-recapture methods with Bayesian inference in an age-structured mathematical model, we use a unique European dataset compiled by the European Centre for Disease Control (ECDC) to quantify the efficiency of 24 NPIs and their combinations (referred to as public health responses, PHR) in reducing SARS-Cov-2 transmission rates in 32 European countries. Of 166 unique PHR tested, we found that median decrease in viral transmission was 74%, which is enough to suppress the epidemic. PHR efficiency was positively associated with the number of NPIs implemented. We found that bans on mass gatherings had the largest effect among NPIs, followed by school closures, teleworking, and stay home orders. Partial implementation of most NPIs resulted in lower than average response efficiency. This first large-scale estimation of NPI and PHR efficiency against SARS-COV-2 transmission in Europe suggests that a combination of NPIs targeting different population groups should be favored to control future epidemic waves.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.17.20176552",
+    "rel_abs": "SARS-CoV-2 antibody responses in children remain poorly characterized. Here, we show that pediatric patients with multisystem inflammatory syndrome in children (MIS-C) possess higher SARS-CoV-2 spike IgG titers compared to those with severe coronavirus disease 2019 (COVID-19), likely reflecting a longer time since onset of infection in MIS-C patients.",
+    "rel_num_authors": 24,
     "rel_authors": [
       {
-        "author_name": "Andres Garchitorena",
-        "author_inst": "Institut de Recherche pour le Developpement"
+        "author_name": "Elizabeth M. Anderson",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "Hugo Gruson",
-        "author_inst": "IRD"
+        "author_name": "Caroline Diorio",
+        "author_inst": "CHOP"
       },
       {
-        "author_name": "Bernard Cazelles",
-        "author_inst": "Sorbonne Universite"
+        "author_name": "Eileen C. Goodwin",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "Tommi Karki",
-        "author_inst": "European Centre for Disease Control"
+        "author_name": "Kevin O. McNerney",
+        "author_inst": "CHOP"
       },
       {
-        "author_name": "Bertrand Sudre",
-        "author_inst": "European Centre for Disese Control"
+        "author_name": "Madison E. Weirick",
+        "author_inst": "University of Pennsylvania"
       },
       {
-        "author_name": "Benjamin ROCHE",
-        "author_inst": "IRD"
+        "author_name": "Sigrid Gouma",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Marcus J. Bolton",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Claudia P. Arevalo",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Julie Chase",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "Philip Hicks",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Tomaz B. Manzoni",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Amy E. Baxter",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Kurt P. Andrea",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Chakkapong Burudpakdee",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "Jessica H. Lee",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "Laura A. Vella",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "Sarah E. Henrickson",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "Rebecca M. Harris",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "E. John Wherry",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Paul Bates",
+        "author_inst": "University of Pennsylvania"
+      },
+      {
+        "author_name": "Hamid Bassiri",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "Edward M Behrens",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "David T. Teachey",
+        "author_inst": "CHOP"
+      },
+      {
+        "author_name": "Scott Hensley",
+        "author_inst": "University of Pennsylvania"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.08.17.20176636",
@@ -1191713,47 +1194937,103 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.08.15.20175513",
-    "rel_title": "Behavioral preventive measures and the use of medicines and herbal products among the public in response to Covid-19 in Bangladesh: A cross-sectional study",
+    "rel_doi": "10.1101/2020.08.15.20175786",
+    "rel_title": "Universal PCR and antibody testing demonstrate little to no transmission of SARS-CoV-2 in a rural community",
     "rel_date": "2020-08-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.15.20175513",
-    "rel_abs": "The present study was conducted to assess the behavioral preventive measures and the use of medicines and herbal foods/products among the public in response to Covid-19. A cross-sectional survey was conducted from 27 June to 20 July 2020, and 1222 people participated. Kruskal-Wallis test was used to identify the differences in behavioral preventive practices across different demographic categories. To identify the factors associated with the use of preventive medicines and herbal foods/products, multivariable logistic regression was performed. Most participants adopted the recommended preventive practices such as washing hands more frequently (87.5%), staying home more often (85.5%), avoiding crowds (86%), and wearing masks (91.6%). About half of the smokers reported a decreased rate of smoking during the pandemic. Also, 14.8% and 57.6% of the participants took medicines and herbal foods/products as preventive measures against Covid-19. Arsenicum album and Zinc supplements were the most commonly used preventive medicines. Gender, age, and fear of Covid-19 were significantly associated with the use of both preventive medicines and herbal products. For the management of Covid-19 related symptoms, Paracetamols, Fexofenadine, and Zinc supplements were used most often. Most participants sought information from non-medical sources while using medicines and herbal products. Moreover, potentially inappropriate and unnecessary use of drugs were identified.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.15.20175786",
+    "rel_abs": "BackgroundThe absence of systematic surveillance for SARS-CoV-2 has curtailed accurate appraisal of transmission intensity. Our objective was to perform case detection of an entire rural community to quantify SARS-CoV-2 transmission using PCR and antibody testing.\n\nMethodsWe conducted a cross-sectional survey of the prevalence and cumulative incidence of SARSCoV-2 infection in the rural town of Bolinas, California (population 1,620), four weeks following shelter-in-place orders. Residents and county essential workers were tested between April 20th - 24th, 2020. Prevalence by PCR and seroprevalence combining data from two forms of antibody testing were performed in parallel (Abbott ARCHITECT IgG to nucleocapsid protein and in-house IgG ELISA to the receptor binding domain).\n\nResultsOf 1,891 participants, 1,312 were confirmed Bolinas residents (>80% community ascertainment). Zero participants were PCR positive. Assuming 80% sensitivity, it would have been unlikely to observe these results (p< 0.05) if there were > 3 active infections in the community. Based on antibody results, estimated prevalence of prior infection was 0.16% (95% CrI: 0.02%, 0.46%). Seroprevalence estimates using only one of the two tests would have been higher, with greater uncertainty. The positive predictive value (PPV) of a positive result on both tests was 99.11% (95% CrI: 95.75%, 99.94%), compared to PPV 44.19%-63.32% (95% CrI range 3.25%-98.64%) if only one test was utilized.\n\nConclusionsFour weeks following shelter-in-place, active and prior SARS-CoV-2 infection in a rural Northern California community was extremely rare. In this low prevalence setting, use of two antibody tests increased the PPV and precision of seroprevalence estimates.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Iftekhar Ahmed",
-        "author_inst": "Department of Pharmacy, Jahangirnagar University, Dhaka, Bangladesh"
+        "author_name": "Ayesha Appa",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Saki Takahashi",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Isabel Rodriguez-Barraquer",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Maruf Hasan",
-        "author_inst": "Department of Pharmacy, Jahangirnagar University, Dhaka, Bangladesh"
+        "author_name": "Gabriel Chamie",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Rahima Akter",
-        "author_inst": "Department of Pharmacy, World University of Bangladesh, Dhaka, Bangladesh"
+        "author_name": "Aenor Sawyer",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Bidduth Kumar Sarkar",
-        "author_inst": "Department of Pharmacy, Ranada Prasad Shaha University, Narayanganj, Bangladesh"
+        "author_name": "- CLIAHUB Consortium",
+        "author_inst": ""
       },
       {
-        "author_name": "Marufa Rahman",
-        "author_inst": "Department of Pharmacy, Jahangirnagar University, Savar, Dhaka, Bangladesh"
+        "author_name": "Elias Duarte",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jill Hakim",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Md Samun Sarker",
-        "author_inst": "Bangladesh Livestock Research Institute (BLRI), Savar, Dhaka, Bangladesh"
+        "author_name": "Keirstinne Turcios",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Joanna Vinden",
+        "author_inst": "University of California, Berkeley"
+      },
+      {
+        "author_name": "Owen Janson",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Aashish Manglik",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Michael J. Peluso",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Steven G Deeks",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Timothy J. Henrich",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Leonel Torres",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Mary Rodgers",
+        "author_inst": "Abbott Laboratories"
+      },
+      {
+        "author_name": "John Hackett",
+        "author_inst": "Abbott Laboratories"
+      },
+      {
+        "author_name": "Charles Y Chiu",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Diane Havlir",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Mohammed A. Samad",
-        "author_inst": "Bangladesh Livestock Research Institute (BLRI), Bangladesh"
+        "author_name": "Bryan Greenhouse",
+        "author_inst": "University of California, San Francisco"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.08.15.20175794",
@@ -1193339,39 +1196619,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.14.20170878",
-    "rel_title": "Estimating the epidemic growth dynamics within the first week",
+    "rel_doi": "10.1101/2020.08.14.20175190",
+    "rel_title": "Bidirectional associations between COVID-19 and psychiatric disorder: a study of 62,354 COVID-19 cases",
     "rel_date": "2020-08-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20170878",
-    "rel_abs": "Information about the early growth of infectious outbreaks are indispensable to estimate the epidemic spreading. A large number of mathematical tools have been developed to this end, facing as much large number of different dynamic evolutions, ranging from sub-linear to super-exponential growth. Of course, the crucial point is that we do not have enough data during the initial outbreak phase to make reliable inferences. Here we propose a methodology to estimate the epidemic growth dynamics from the infected cumulative data of just a week, provided a surveillance system is available over the whole territory. The methodology, based on the Newcomb-Benford Law, is applied to Italian covid 19 case-study. Results show that it is possible to discriminate the epidemic dynamics using the first seven data points collected over fifty Italian cities. Moreover, the form of the most probable approximating function of the growth, within a six weeks epidemic scenario, is identified.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20175190",
+    "rel_abs": "BackgroundAdverse mental health consequences of COVID-19, including anxiety and depression, have been widely predicted but not yet accurately measured. There are a range of physical health risk factors for COVID-19, but it is not known if there are also psychiatric risk factors.\n\nMethodsWe addressed both questions using cohort studies derived from an electronic health records (EHR) network of 69 million patients including over 62,000 cases of COVID-19. Propensity score matching was used to control for confounding by risk factors for COVID-19 and for more severe illness.\n\nFindingsIn patients with no prior psychiatric history, COVID-19 was associated with an increased incidence of psychiatric diagnoses in the three months after infection compared to 6 other health events (hazard ratio [95% CI] 2.1 [1.8-2.5] compared to influenza; 1.7 [1.5-1.9] compared to other respiratory tract infections; 1.6 [1.4-1.9] compared to skin infection; 1.6 [1.3-1.9] compared to cholelithiasis; 2.2 [1.9-2.6] compared to urolithiasis, and 2.1 [1.9-2.5] compared to fracture of a large bone; all p< 0.0001). The increase was greatest for anxiety disorders but also present for depression, insomnia, and dementia. The results were robust to several sensitivity analyses. There was a [~]30% reduction in psychiatric diagnoses in the total EHR population over the same period. A psychiatric diagnosis in the previous year was associated with a 65% higher incidence of COVID-19 (relative risk 1.65, 95% CI: 1.59-1.71, p< 0.0001). This was independent of known physical health risk factors for COVID-19.\n\nInterpretationCOVID-19 infection has both psychiatric sequelae and psychiatric antecedents. Survivors have an increased rate of new onset psychiatric disorders, and prior psychiatric disorders are associated with a higher risk of COVID-19. The findings have implications for research into aetiology and highlight the need for clinical services to provide multidisciplinary follow-up, and prompt detection and treatment.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "VINCENZO FIORITI",
-        "author_inst": "ENEA"
-      },
-      {
-        "author_name": "IVAN ROSELLI",
-        "author_inst": "ENEA"
+        "author_name": "Maxime Taquet",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "MARTA CHINNICI",
-        "author_inst": "ENEA"
+        "author_name": "Sierra Luciano",
+        "author_inst": "TriNetX Inc, Cambridge, MA"
       },
       {
-        "author_name": "ANDREA ARBORE",
-        "author_inst": "ICT CONSULTANT"
+        "author_name": "John R Geddes",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "NICOLA SIGISMONDI",
-        "author_inst": "ICT CONSULTANT"
+        "author_name": "Paul J Harrison",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.08.14.20158535",
@@ -1195353,95 +1198629,23 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2020.08.14.248880",
-    "rel_title": "In plain sight: the role of alpha-1-antitrypsin in COVID-19 pathogenesis and therapeutics.",
+    "rel_doi": "10.1101/2020.08.13.20174508",
+    "rel_title": "Data Mining Approach to Analyze Covid19 Dataset of Brazilian Patients",
     "rel_date": "2020-08-15",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.14.248880",
-    "rel_abs": "RationaleSARS-CoV-2 entry into host cells is facilitated by endogenous and exogenous proteases that proteolytically activate the spike glycoprotein and antiproteases inhibiting this process. Understanding the key actors in viral entry is crucial for advancing knowledge of virus tropism, pathogenesis, and potential therapeutic targets.\n\nObjectivesWe aimed to investigate the role of naive serum and alpha-1-antitrypsin (AAT) in inhibiting protease-mediated SARS-CoV-2 entry and explore the implications of AAT deficiency on susceptibility to different SARS-CoV-2 variants.\n\nFindingsOur study demonstrates that naive serum exhibits significant inhibition of SARS-CoV-2 entry, with AAT identified as the major serum protease inhibitor potently restricting entry. Using pseudoparticles, replication-competent pseudoviruses, and authentic SARS-CoV-2, we show that AAT inhibition occurs at low concentrations compared with those in serum and bronchoalveolar tissues, suggesting physiological relevance. Furthermore, sera from subjects with an AAT-deficient genotype show reduced ability to inhibit entry of both Wuhan-Hu-1 (WT) and B.1.617.2 (Delta) but exhibit no difference in inhibiting B.1.1.529 (Omicron) entry.\n\nConclusionsAAT may have a variant-dependent therapeutic potential against SARS-CoV-2. Our findings highlight the importance of further investigating the complex interplay between proteases, antiproteases, and spike glycoprotein activation in SARS-CoV-2 and other respiratory viruses to identify potential therapeutic targets and improve understanding of disease pathogenesis.",
-    "rel_num_authors": 19,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174508",
+    "rel_abs": "The pandemic originated by coronavirus(covid19), name coined by World Health Organization during the first month in 2020. Actually, almost all the countries presented covid19 positive cases and governments are choosing different health policies to stop the infection and many research groups are working on patients data to understand the virus, at the same time scientists are looking for a vacuum to enhance imnulogy system to tack covid19 virus. One of top countries with more infections is Brazil, until August 11 had a total of 3,112,393 cases. Research Foundation of Sao Paulo State(Fapesp) released a dataset, it was an innovative in collaboration with hospitals(Einstein, Sirio-Libanes), laboratory(Fleury) and Sao Paulo University to foster reseach on this trend topic. The present paper presents an exploratory analysis of the datasets, using a Data Mining Approach, and some inconsistencies are found, i.e. NaN values, null references values for analytes, outliers on results of analytes, encoding issues. The results were cleaned datasets for future studies, but at least a 20% of data were discarded because of non numerical, null values and numbers out of reference range.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Christian S Stevens",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Kasopefoluwa Y Oguntuyo",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Shreyas Kowdle",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Aditya Gowlikar",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Mohammed NA Siddiquey",
-        "author_inst": "Louisiana State University Health Sciences Center Shreveport"
-      },
-      {
-        "author_name": "Joshua A Acklin",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Griffin Haas",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Robert M Schilke",
-        "author_inst": "Louisiana State University Health Sciences Center Shreveport"
-      },
-      {
-        "author_name": "Matthew D Woolard",
-        "author_inst": "Louisiana State University Health Sciences Center-Shreveport"
-      },
-      {
-        "author_name": "Hongbo Zhang",
-        "author_inst": "Louisiana State University Health Sciences Center-Shreveport"
-      },
-      {
-        "author_name": "Luca Brambilla",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Satoshi Ikegame",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Chuan-tien Hung",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Jean K Lim",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Robert W Cross",
-        "author_inst": "University of Texas Medical Branch-Galveston National Laboratory"
-      },
-      {
-        "author_name": "Thomas W Geisbert",
-        "author_inst": "University of Texas Medical Branch-Galveston National Laboratory"
-      },
-      {
-        "author_name": "Stanimir S Ivanov",
-        "author_inst": "Louisiana State University Health Sciences Center-Shreveport"
-      },
-      {
-        "author_name": "Jeremy P Kamil",
-        "author_inst": "Louisiana State University Health Sciences Center Shreveport"
-      },
-      {
-        "author_name": "Benhur Lee",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Josimar E. Chire Saire",
+        "author_inst": "University of Sao Paulo"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.08.13.20174615",
@@ -1196927,57 +1200131,81 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.11.20145086",
-    "rel_title": "Face Coverings and Respiratory Tract Droplet Dispersion",
+    "rel_doi": "10.1101/2020.08.11.20173062",
+    "rel_title": "Quantitative analysis of SARS-CoV-2 RNA from wastewater solids in communities with low COVID-19 incidence and prevalence",
     "rel_date": "2020-08-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20145086",
-    "rel_abs": "Respiratory droplets are the primary transmission route for SARS-CoV-2. Evidence suggests that virus transmission can be reduced by face coverings, but robust evidence for how mask usage might affect safe distancing parameters is lacking. Accordingly, we investigate the effectiveness of surgical masks and single-layer cotton masks on mitigating dispersion of large respiratory droplets (i.e. non aerosol). We tested a manikin ejecting fluorescent droplets and human volunteers in speaking and coughing conditions. We quantified the number of droplets in flight using laser sheet illumination and UV-light for those that had landed at table height at up to 2m. For human volunteers, expiratory droplets were caught on a microscope slide 5cm from the mouth. Whether manikin or human, wearing a face covering decreased the number of projected droplets by >1000-fold. We estimated that a person standing 2m from someone coughing without a mask is exposed to over 1000 times more respiratory droplets than from someone standing 5 cm away wearing a basic single layer mask. Our results indicate that face coverings show consistent efficacy at blocking respiratory droplets. If aerosol transmission is later determined to be a significant driver of infection, then our findings may overestimate the effectiveness of face coverings.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20173062",
+    "rel_abs": "In the absence of an effective vaccine to prevent COVID-19 it is important to be able to track community infections to inform public health interventions aimed at reducing the spread and therefore reduce pressures on health-care units, improve health outcomes and reduce economic uncertainty. Wastewater surveillance has rapidly emerged as a potential tool to effectively monitor community infections for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), through measuring trends of viral RNA signal in wastewater systems. In this study SARS-CoV-2 viral RNA N1 and N2 genes are quantified in solids collected from influent post grit solids (PGS) and primary clarified sludge (PCS) in two water resource recovery facilities (WRRF) serving Canadas national capital region, i.e., the City of Ottawa, ON (pop. {approx} 1.1M) and the City of Gatineau, QC (pop. {approx} 280K). PCS samples show signal inhibition using RT-ddPCR compared to RT-qPCR, with PGS samples showing similar quantifiable concentrations of RNA using both assays. RT-qPCR shows higher frequency of detection of N1 and N2 genes in PCS (92.7, 90.6%) as compared to PGS samples (79.2, 82.3%). Sampling of PCS may therefore be an effective approach for SARS-CoV-2 viral quantification, especially during periods of declining and low COVID-19 incidence in the community. The pepper mild mottle virus (PMMV) is determined to have a less variable RNA signal in PCS over a three month period for two WRRFs, regardless of environmental conditions, compared to Bacteroides 16S rRNA or human eukaryotic 18S rRNA, making PMMV a potentially useful biomarker for normalization of SARS-CoV-2 signal. PMMV-normalized PCS RNA signal from WRRFs of two cities correlated with the regional public health epidemiological metrics, identifying PCS normalized to a fecal indicator (PMMV) as a potentially effective tool for monitoring trends during decreasing and low-incidence of infection of SARS-Cov-2 in communities.",
+    "rel_num_authors": 16,
     "rel_authors": [
       {
-        "author_name": "Lucia Bandiera",
-        "author_inst": "School of Engineering, University of Edinburgh"
+        "author_name": "Patrick M. D'Aoust",
+        "author_inst": "University of Ottawa - Civil Engineering"
+      },
+      {
+        "author_name": "Elisabeth Mercier",
+        "author_inst": "University of Ottawa - Chemical and Biological Engineering"
+      },
+      {
+        "author_name": "Danika Montpetit",
+        "author_inst": "University of Ottawa - Chemical and Biological Engineering"
       },
       {
-        "author_name": "Geethanjali Pavar",
-        "author_inst": "School of Engineering, University of Edinburgh"
+        "author_name": "Jian-Jun Jia",
+        "author_inst": "Children's Hospital of Eastern Ontario - Research Institute"
       },
       {
-        "author_name": "Gabriele Pisetta",
-        "author_inst": "School of Engineering, University of Edinburgh"
+        "author_name": "Ilya Alexandrov",
+        "author_inst": "ActivSignal LLC."
       },
       {
-        "author_name": "Shuji Otomo",
-        "author_inst": "School of Engineering, University of Edinburgh"
+        "author_name": "Nafisa Neault",
+        "author_inst": "Children's Hospital of Eastern Ontario - Research Institute"
       },
       {
-        "author_name": "Enzo Mangano",
-        "author_inst": "School of Engineering, University of Edinburgh"
+        "author_name": "Aiman Tariq Baig",
+        "author_inst": "Children's Hospital of Eastern Ontario - Research Institute"
       },
       {
-        "author_name": "Jonathan R. Seckl",
-        "author_inst": "Queen`s Medical Research Institute, University of Edinburgh"
+        "author_name": "Janice Mayne",
+        "author_inst": "University of Ottawa - Biochemistry, Microbiology and Immunology"
       },
       {
-        "author_name": "Paul Digard",
-        "author_inst": "The Roslin Institute, University of Edinburgh"
+        "author_name": "Xu Zhang",
+        "author_inst": "University of Ottawa - Biochemistry, Microbiology and Immunology"
+      },
+      {
+        "author_name": "Tommy Alain",
+        "author_inst": "Children's Hospital of Eastern Ontario - Research Institute"
+      },
+      {
+        "author_name": "Mark R. Servos",
+        "author_inst": "University of Waterloo - Department of Biology"
       },
       {
-        "author_name": "Emanuela Molinari",
-        "author_inst": "School of Informatics, University of Edinburgh"
+        "author_name": "Malcolm MacKenzie",
+        "author_inst": "ActivSignal LLC."
       },
       {
-        "author_name": "Filippo Menolascina",
-        "author_inst": "School of Engineering, University of Edinburgh"
+        "author_name": "Daniel Figeys",
+        "author_inst": "University of Ottawa - Biochemistry, Microbiology and Immunology"
       },
       {
-        "author_name": "Ignazio Maria Viola",
-        "author_inst": "School of Engineering, University of Edinburgh"
+        "author_name": "Alex E. MacKenzie",
+        "author_inst": "Children's Hospital of Eastern Ontario - Research Institute"
+      },
+      {
+        "author_name": "Tyson E. Graber",
+        "author_inst": "Children's Hospital of Eastern Ontario - Research Institute"
+      },
+      {
+        "author_name": "Robert Delatolla",
+        "author_inst": "University of Ottawa - Civil Engineering"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1198673,33 +1201901,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.13.20174060",
-    "rel_title": "Comprehensive Systematic Review to Identify putative COVID-19 Treatments: Roles for Immunomodulator and Antiviral Treatments",
+    "rel_doi": "10.1101/2020.08.12.20173104",
+    "rel_title": "First report of tocilizumab use in a cohort of Latin American patients hospitalized for severe COVID-19 pneumonia",
     "rel_date": "2020-08-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20174060",
-    "rel_abs": "ObjectivesTo identify putative COVID-19 treatments and identify the roles of immunomodulators and antivirals in disease management.\n\nDesignSystematic review.\n\nData sourcesPubMed, bioRxiv.org and medRxiv.org were searched for studies suggestive of effective treatments for COVID-19. Additional studies were identified via a snowballing method applied to the references of retrieved papers as well as a subsequent targeted search for drug names.\n\nReview methodsInclusion criteria included any case series or randomised control trials in any language that were published from 18th December 2019 to 18th April 2020 and described COVID-19 treatment. Of an initial 2140 studies identified from the initial search, 29 studies were found to meet the inclusion criteria and included in this comprehensive systematic review.\n\nResults19 studies of antiviral treatments for COVID-19 have been reported and seven studies for immunomodulatory treatments. Six randomised controlled trials have been published with one positive trial for Hydroxychloroquine. This small study consisted of 31 patients though subsequent studies showed contradictory findings. All the remaining studies were observational studies, retrospective case reviews or non-randomised trials and these results are difficult to interpret due to methodological issues.\n\nConclusionsTo date, an impressive number of studies have been performed in a short space of time, indicative of a resilient clinical trials infrastructure. However, there is a lack of high quality evidence to support any novel treatments for COVID-19 to be incorporated into the current standard of care. The majority of the studies of treatments for COVID-19 could only be found in pre-print servers. Future clinical reviews should therefore be Comprehensive Systematic Reviews involving pre-print studies to prevent potential unnecessary replications of clinical studies.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.12.20173104",
+    "rel_abs": "Introduction/objectivesAn interleukin-6 inhibition strategy could be effective in selected COVID-19 patients. The objective is to present our experience of tocilizumab use in patients with severe COVID-19.\n\nMethodsObservational retrospective cohort study. Hospitalized patients were evaluated by our multidisciplinary team for eventual use of tocilizumab. Patients with progressive ventilatory impairment and evidence of a hyperinflammatory state despite usual treatment received tocilizumab 8 mg/kg intravenous (maximum dose 800 mg), in addition to standard treatment. The use and time of use of mechanical ventilation (MV), the change of the Alveolar-arterial (A-a) gradient, of the ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2) and of inflammation laboratory parameters after 72 hours of tocilizumab use was evaluated.\n\nResults29 patients received tocilizumab. 93.1% were men, 37.9% were obese, and 34.5% had hypertension. Of the 20 patients who were not on MV when receiving tocilizumab, 11 required non-invasive MV, for an average of five days, and one of them required intubation. A-a gradient, PaO2/FiO2, and inflammation parameters improved significantly. A better lymphocyte count, which improved significantly after tocilizumab use, was significantly associated with less use of MV. Five patients presented positive culture samples after tocilizumab, three being of clinical significance. A lower lymphocyte count was associated with having a positive culture. No other significant adverse events were seen.\n\nConclusionOur study suggests the utility and shows the safety of tocilizumab use in COVID-19 patients who have respiratory failure and evidence of hyperinflammation. Lymphocyte improvement was a predictor of good response.\n\nKey-pointsO_LIThe use of tocilizumab in patients with severe COVID-19 was safe.\nC_LIO_LIMost of the patients presented a good response in terms of ventilatory and inflammatory parameters.\nC_LIO_LILymphocyte improvement after using tocilizumab was the main predictor of a good outcome.\nC_LI",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Thomas Hill",
-        "author_inst": "Department of Oncology, Queen Elizabeth Hospital Birmingham, Mindelsohn Way, Edgbaston, B152GW"
+        "author_name": "Omar Valenzuela",
+        "author_inst": "Clinica Alemana de Santiago"
       },
       {
-        "author_name": "Mark Baker",
-        "author_inst": "Birmingham Medical School, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT"
+        "author_name": "Sebastian E Ibanez",
+        "author_inst": "Clinica Alemana de Santiago"
       },
       {
-        "author_name": "Lawrence Isherwood",
-        "author_inst": "Birmingham Medical School, College of Medical and Dental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT"
+        "author_name": "Maria Poli",
+        "author_inst": "Clinica Alemana de Santiago"
       },
       {
-        "author_name": "Lennard YW Lee",
-        "author_inst": "Department of Oncology, Queen Elizabeth Hospital Birmingham, Mindelsohn Way, Edgbaston B15 2GW, United Kingdom. Institute of Cancer and Genomic Sciences, Univer"
+        "author_name": "Patricia Roessler",
+        "author_inst": "Clinica Alemana de Santiago"
+      },
+      {
+        "author_name": "Mabel Aylwin",
+        "author_inst": "Clinica Alemana de Santiago"
+      },
+      {
+        "author_name": "Gigia Roizen",
+        "author_inst": "Clinica Alemana de Santiago"
+      },
+      {
+        "author_name": "Mirentxu Iruretagoyena",
+        "author_inst": "Clinica Alemana de Santiago"
+      },
+      {
+        "author_name": "Vivianne Agar",
+        "author_inst": "Clinica Alemana de Santiago"
+      },
+      {
+        "author_name": "Javiera Donoso",
+        "author_inst": "Clinica Alemana de Santiago"
+      },
+      {
+        "author_name": "Margarita Fierro",
+        "author_inst": "Clinica Alemana de Santiago"
+      },
+      {
+        "author_name": "Jose Montes",
+        "author_inst": "Clinica Alemana de Santiago"
       }
     ],
     "version": "1",
-    "license": "cc0_ng",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1200007,47 +1203263,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.12.20172726",
-    "rel_title": "Testing of Healthcare Workers Exposed to COVID19 with Rapid Antigen Detection",
+    "rel_doi": "10.1101/2020.08.13.20170068",
+    "rel_title": "A novel approach for evaluating contact patterns and risk mitigation strategies for COVID-19 in English Primary Schools with application of Structured Expert Judgement",
     "rel_date": "2020-08-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.12.20172726",
-    "rel_abs": "There is a need to develop safe and cost-effective ways to test healthcare workers for COVID19. Here we describe a rapid antigen testing strategy in a cohort of 497 Healthcare workers exposed to SARS-CoV-2 that can be applied by systems facing a surge of COVID19 cases, increased number of exposures in their workforce and limited RT-PCR availability. Our findings support an expanded use for antigen testing beyond its current indication and highlights the importance of further evaluating this modality for the diagnosis of COVID19 on asymptomatic individuals.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20170068",
+    "rel_abs": "BackgroundContact patterns are the drivers of close-contacts infections, such as COVID-19. In an effort to control COVID-19 transmission in the UK, schools were closed on 23 March 2020. With social distancing in place, Primary Schools were partially re-opened on 1 June 2020, with plans to fully re-open in September 2020. The impact of social distancing and risk mitigation measures on childrens contact patterns is not known.\n\nMethodsWe conducted a structured expert elicitation of a sample of Primary Headteachers to quantify contact patterns within schools in pre-COVID-19 times and how these patterns were expected to change upon re-opening. Point estimates with uncertainty were determined by a formal performance-based algorithm. Additionally, we surveyed school Headteachers about risk mitigation strategies and their anticipated effectiveness.\n\nResultsExpert elicitation provides estimates of contact patterns that are consistent with contact surveys. We report mean number of contacts per day for four cohorts within schools along with a range at 90% confidence for the variations of contacts among individuals. Prior to lockdown, we estimate that, mean numbers per day, younger children (Reception and Year 1) made 15 contacts [range 8..35] within school, older children (Year 6) 18 contacts [range 5.. 55], teaching staff 25 contacts [range 4.. 55) and non-classroom staff 11 contacts [range 2.. 27]. Compared to pre-COVID times, after schools re-opened the mean number of contacts were reduced by about 53% for young children, about 62% for older children, about 60% for classroom staff and about 64% for other staff. Contacts between teaching and non-teaching staff reduced by 80%, which is consistent with other independent estimates. The distributions of contacts per person are asymmetric indicating a heavy tail of individuals with high contact numbers.\n\nConclusionsWe interpret the reduction in childrens contacts as a consequence of efforts to reduce mixing with interventions such as forming groups of children (bubbles) who are organized to learn together to limit contacts. Distributions of contacts for children and adults can be used to inform COVID-19 transmission modelling. Our findings suggest that while official DfE guidelines form the basis for risk mitigation in schools, individual schools have adopted their own bespoke strategies, often going beyond the guidelines.",
     "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Victor Herrera",
-        "author_inst": "Adventhealth"
+        "author_name": "Stephen RJ Sparks",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Vincent Hsu",
-        "author_inst": "AdventHealth"
+        "author_name": "William P Aspinall",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Ademola Adewale",
-        "author_inst": "Adventhealth"
+        "author_name": "Ellen Brooks-Pollock",
+        "author_inst": "University of Bristol"
       },
       {
-        "author_name": "Timothy Hendrix",
-        "author_inst": "AdventHealth"
+        "author_name": "Leon Danon",
+        "author_inst": "University of Exeter"
       },
       {
-        "author_name": "Lee Johnson",
-        "author_inst": "Adventhealth"
+        "author_name": "Roger Cooke",
+        "author_inst": "Delft University of Technology"
       },
       {
-        "author_name": "Jeffrey Kuhlman",
-        "author_inst": "Adventhealth"
+        "author_name": "Jenni Barclay",
+        "author_inst": "University of East Anglia"
       },
       {
-        "author_name": "Neil Finkler",
-        "author_inst": "Adventhealth"
+        "author_name": "Jane Scarrow",
+        "author_inst": "University of Grenada"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.08.12.20173047",
@@ -1201781,123 +1205037,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.07.20166868",
-    "rel_title": "Factors Associated with Disease Severity and Mortality among Patients with Coronavirus Disease 2019: A Systematic Review and Meta-Analysis",
+    "rel_doi": "10.1101/2020.07.26.20162008",
+    "rel_title": "COVID-19 mild cases determination from   correlating COVID-line calls to reported cases",
     "rel_date": "2020-08-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20166868",
-    "rel_abs": "BackgroundUnderstanding the factors associated with disease severity and mortality in Coronavirus disease (COVID-19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19.\n\nMethodsWe searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently.\n\nResultsAmong 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45, 95%CI 1.23-1.71), dyspnea (RR 2.55, 95%CI 1.88-2.46), diabetes (RR 1.59, 95%CI 1.41-1.78), hypertension (RR 1.90, 95%CI 1.69-2.15). Congestive heart failure (OR 4.76, 95%CI 1.34-16.97), hilar lymphadenopathy (OR 8.34, 95%CI 2.57-27.08), bilateral lung involvement (OR 4.86, 95%CI 3.19-7.39) and reticular pattern (OR 5.54, 95%CI 1.24-24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality.\n\nConclusionKnowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.\n\nPrimary Funding SourceNone.",
-    "rel_num_authors": 26,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.26.20162008",
+    "rel_abs": "One of the most challenging keys to understand COVID-19 evolution is to have a measure on those mild cases which are never tested because their few symptoms are soft and/or fade away soon. The problem is not only that they are difficult to identify and test, but also that it is believed that they may constitute the bulk of the cases and could be crucial in the pandemic equation. We present a novel and simple algorithm to extract the number of these mild cases by correlating a COVID-line phone calls to reported cases in given districts. The key assumption is to realize that, being a highly contagious disease, the number of calls by mild cases should be proportional to the number of reported cases. Whereas a background of calls not related to infected people should be proportional to the district population. We present the plain mathematics of the method and as a working example we apply it to Buenos Aires Province (Argentina), where it is being currently used. The implementation of this algorithm by other regions would be straightforward and would provide compelling information to the corresponding Health Care Administration.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Vignesh Chidambaram",
-        "author_inst": "Johns Hopkins Bloomberg school of Public health"
-      },
-      {
-        "author_name": "Nyan Lynn Tun",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Waqas Haque",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Marie Gilbert Majella",
-        "author_inst": "Department of Preventive and Social Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India"
-      },
-      {
-        "author_name": "Ranjith Kumar Sivakumar",
-        "author_inst": "Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China"
-      },
-      {
-        "author_name": "Amudha Kumar",
-        "author_inst": "Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA"
-      },
-      {
-        "author_name": "Angela Ting-Wei Hsu",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Izza Ishak",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Aqsha Nur",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Samuel Ayeh",
-        "author_inst": "Johns Hopkins School of Medicine"
-      },
-      {
-        "author_name": "Emmanuella Salia",
-        "author_inst": "Johns Hopkins School of Medicine"
-      },
-      {
-        "author_name": "Ahsan Zil-E-Ali",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Muhammad Saeed",
-        "author_inst": "Johns Hopkins University"
-      },
-      {
-        "author_name": "Ayu Sarena",
-        "author_inst": "Bhayangkara Setukpa Hospital, Sukabumi, Indonesia"
-      },
-      {
-        "author_name": "Bhavna Seth",
-        "author_inst": "Johns Hopkins School of Medicine"
-      },
-      {
-        "author_name": "Muzzammil Ahmadzada",
-        "author_inst": "Johns Hopkins University"
-      },
-      {
-        "author_name": "Eman Haque",
-        "author_inst": "Southern Methodist University, Dallas, TX, USA"
-      },
-      {
-        "author_name": "Pranita Neupane",
-        "author_inst": "Johns Hopkins School of Medicine"
-      },
-      {
-        "author_name": "Kuang-Heng Wang",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Tzu-Miao Pu",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Syed Ali",
-        "author_inst": "Fatima Memorial Hospital, Lahore, Pakistan"
-      },
-      {
-        "author_name": "Muhammad Arshad",
-        "author_inst": "Nishtar Hospital, Multan, Pakistan"
-      },
-      {
-        "author_name": "Lin Wang",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Sheriza Baksh",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Petros Karakousis",
-        "author_inst": "Johns Hopkins School of Medicine"
+        "author_name": "Ezequiel Alvarez",
+        "author_inst": "University of San Martin"
       },
       {
-        "author_name": "Panagis Galiatsatos",
-        "author_inst": "Johns Hopkins School of Medicine"
+        "author_name": "Franco Marsico",
+        "author_inst": "Ministerio de Salud de la Provincia de Buenos Aires, Argentina"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.08.09.20171132",
@@ -1203383,95 +1206543,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.10.20171371",
-    "rel_title": "Impaired cellular immunity to SARS-CoV-2 in severe COVID-19 patients",
+    "rel_doi": "10.1101/2020.08.10.20171439",
+    "rel_title": "Extended SEIQR type model for COVID-19 epidemic and data analysis",
     "rel_date": "2020-08-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171371",
-    "rel_abs": "The World Health Organization has declared SARS-CoV-2 virus outbreak a world-wide pandemic. Individuals infected by the virus exhibited different degrees of symptoms, the basis of which remains largely unclear. Currently, though convalescent individuals have been shown with both cellular and humoral immune responses, there is very limited understanding on the immune responses, especially adaptive immune responses, in patients with severe COVID-19. Here, we examined 10 blood samples from COVID-19 patients with acute respiratory distress syndrome (ARDS). The majority of them (70%) mounted SARS-CoV-2-specific humoral immunity with production of neutralizing antibodies. However, compared to healthy controls, the percentages and absolute numbers of both NK cells and CD8+ T cells were significantly reduced, accompanied with decreased IFN{gamma} expression in CD4+ T cells in peripheral blood from severe patients. Most notably, we failed in detecting SARS-CoV-2-specific IFN{gamma} production by peripheral blood lymphocytes from these patients. Our work thus indicates that COVID-19 patients with severe symptoms are associated with defective cellular immunity, which not only provides insights on understanding the pathogenesis of COVID-19, but also has implications in developing an effective vaccine to SARS-CoV-2.",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171439",
+    "rel_abs": "An extended SEIQR type model is considered in order to model the COVID-19 epidemic. It contains the classes of susceptible individuals, exposed, infected symptomatic and asymptomatic, quarantined, hospitalized and recovered. The basic reproduction number and the final size of epidemic are determined. The model is used to fit available data for some European countries. A more detailed model with two different subclasses of susceptible individuals is introduced in order to study the influence of social interaction on the disease progression. The coefficient of social interaction K characterizes the level of social contacts in comparison with complete lockdown (K = 0) and the absence of lockdown (K = 1). The fitting of data shows that the actual level of this coefficient in some European countries is about 0.1, characterizing a slow disease progression. A slight increase of this value in the autumn can lead to a strong epidemic burst.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Ling Ni",
-        "author_inst": "Institute for Immunology and School of Medicine,Tsinghua University"
-      },
-      {
-        "author_name": "Meng-Li Cheng",
-        "author_inst": "College of Basic Medical Science, Jilin University"
-      },
-      {
-        "author_name": "Hui Zhao",
-        "author_inst": "Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences"
-      },
-      {
-        "author_name": "Yu Feng",
-        "author_inst": "Institute for Immunology and School of Medicine, Tsinghua University"
-      },
-      {
-        "author_name": "Jingyuan Liu",
-        "author_inst": "Beijing Ditan Hospital, Capital Medical University, and Beijing Key Laboratory of Emerging Infectious Diseases,"
-      },
-      {
-        "author_name": "Fang Ye",
-        "author_inst": "Department of Hematology, Chui Yang Liu Hospital affiliated to Tsinghua University"
-      },
-      {
-        "author_name": "Qing Ye",
-        "author_inst": "Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences,"
-      },
-      {
-        "author_name": "Gengzhen Zhu",
-        "author_inst": "Institute for Immunology and School of Medicine, Tsinghua University"
-      },
-      {
-        "author_name": "Xiaoli Li",
-        "author_inst": "Institute for Immunology and School of Medicine, Tsinghua University"
-      },
-      {
-        "author_name": "Pengzhi Wang",
-        "author_inst": "Institute for Immunology and School of Medicine, Tsinghua University"
-      },
-      {
-        "author_name": "Jing Shao",
-        "author_inst": "Institute for Immunology and School of Medicine, Tsinghua University"
-      },
-      {
-        "author_name": "Yong-qiang Deng",
-        "author_inst": "Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences"
-      },
-      {
-        "author_name": "Peng Wei",
-        "author_inst": "Institute for Immunology and School of Medicine, Tsinghua University"
-      },
-      {
-        "author_name": "Fang Chen",
-        "author_inst": "Department of Cardiology, Chui Yang Liu Hospital affiliated to Tsinghua University"
-      },
-      {
-        "author_name": "Cheng-feng Qin",
-        "author_inst": "Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences"
-      },
-      {
-        "author_name": "Guoqing Wang",
-        "author_inst": "College of Basic Medical Science, Jilin University"
-      },
-      {
-        "author_name": "Fan Li",
-        "author_inst": "College of Basic Medical Science, Jilin University"
+        "author_name": "Swarnali Sharma",
+        "author_inst": "Vijaygarh Jyotish Ray College, Kolkata, INDIA"
       },
       {
-        "author_name": "Hui Zeng",
-        "author_inst": "Beijing Ditan Hospital, Capital Medical University, and Beijing Key Laboratory of Emerging Infectious Diseases"
+        "author_name": "Vitaly Volpert",
+        "author_inst": "Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622 Villeurbanne, France"
       },
       {
-        "author_name": "Chen Dong",
-        "author_inst": "Institute for Immunology and School of Medicine, Tsinghua University"
+        "author_name": "Malay Banerjee",
+        "author_inst": "IIT Kanpur"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.08.10.20171454",
@@ -1205265,49 +1208361,33 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.07.20161737",
-    "rel_title": "LamPORE: rapid, accurate and highly scalable molecular screening for SARS-CoV-2 infection, based on nanopore sequencing",
+    "rel_doi": "10.1101/2020.08.07.20170407",
+    "rel_title": "Model-based projections for COVID-19 outbreak size and student-days lost to closure in Ontario childcare centres and primary schools",
     "rel_date": "2020-08-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20161737",
-    "rel_abs": "LamPORE is a rapid way of testing/screening large numbers of samples for the presence or absence of SARS-CoV-2, the virus causing COVID-19. It combines barcoded multi-target amplification, 15-minute barcoded library preparation and real-time nanopore sequencing. Starting with extracted RNA, results can be obtained from 12 samples in approximately an hour and from 96 samples in under 2 hours. High scalability is achieved by combinatorial barcoding. Performance characteristics are currently being established and regulatory clearance to market is underway.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20170407",
+    "rel_abs": "There is a pressing need for evidence-based scrutiny of plans to re-open childcare during the COVID-19 pandemic. Here we developed an agent-based model of SARS-CoV-2 transmission within a childcare center and households. Scenarios varied the student-to-educator ratio (15:2, 8:2, 7:3), and family clustering (siblings together vs. random assignment). We also evaluated a primary school setting (30:1, 15:1 and 8:1) including cohorts that alternate weekly. In the childcare scenarios, grouping siblings significantly reduced outbreak size and student-days lost. We identify an intensification cascade specific to classroom outbreaks of respiratory viruses with presymptomatic infection. In both childcare and primary school settings, each doubling of class size from 8 to 15 to 30 more than doubled the outbreak size and student-days lost, by factors of 2-5, respectively 2.5-4.5, depending on the scenario. Proposals for childcare and primary school reopening could be enhanced for safety by switching to lower ratios and sibling groupings.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Phillip James",
-        "author_inst": "Oxford Nanopore Technologies"
-      },
-      {
-        "author_name": "David Stoddart",
-        "author_inst": "Oxford Nanopore Technologies"
-      },
-      {
-        "author_name": "Eoghan D Harrington",
-        "author_inst": "Oxford Nanopore Technologies"
-      },
-      {
-        "author_name": "John Beaulaurier",
-        "author_inst": "Oxford Nanopore Technologies"
-      },
-      {
-        "author_name": "Lynn Ly",
-        "author_inst": "Oxford Nanopore Technologies"
+        "author_name": "Brendon Phillips",
+        "author_inst": "University of Waterloo"
       },
       {
-        "author_name": "Stuart Reid",
-        "author_inst": "Oxford Nanopore Technologies"
+        "author_name": "Dillon Browne",
+        "author_inst": "University of Waterloo"
       },
       {
-        "author_name": "Daniel J Turner",
-        "author_inst": "Oxford Nanopore Technologies"
+        "author_name": "Madhur Anand",
+        "author_inst": "University of Guelph"
       },
       {
-        "author_name": "Sissel Juul",
-        "author_inst": "Oxford Nanopore Technologies"
+        "author_name": "Chris Bauch",
+        "author_inst": "University of Waterloo"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1207063,21 +1210143,41 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.10.20172155",
-    "rel_title": "EPIDEMIC ANALYSIS OF COVID-19 IN ALGERIA BY A GENERALIZED SEIR MODEL",
+    "rel_doi": "10.1101/2020.08.10.20172189",
+    "rel_title": "Janus Kinase-Inhibitor and Type I Interferon Ability to Produce Favorable Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-Analysis",
     "rel_date": "2020-08-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20172155",
-    "rel_abs": "The novel coronavirus diseases 2019 (COVID-19) in Wuhan is continuing to impress the world by its fast spread and the number of affected persons attracting an unprecedented attention. In this article, we used the classical SEIR model and a generalized SEIR model called SEIRDP model inspired in a model previously used during the outbreak in China to predict the evolution of COVID-19 in Algeria for a future period of 100 days using official reported data from early April to early August, 2020. Initial evaluation showed that thetwo models had a net correspondence with the reported data during this period for cumulative infected cases but the number of cumulative deaths was underestimated with the classical SEIR model. Model prediction with the SEIRDP concluded that the number of cumulative infected cases will increase in the next days reaching a number of about 60 k in middle November with a median of about 300 daily cases. Also, the number of estimated deaths will be around 2k. These results suggest that the COVID-19 is ongoing to infect more persons which may push national authorities to carefully act in the probable leaving of containment.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20172189",
+    "rel_abs": "BackgroundNovel coronavirus (SARS-CoV-2) has infected over 17 million. Novel therapies are urgently needed. Janus-kinase (JAK) inhibitors and Type I interferons have emerged as potential antiviral candidates for COVID-19 patients for their proven efficacy against diseases with excessive cytokine release and by their ability to promote viral clearance in past coronaviruses, respectively. We conducted a systemic review and meta-analysis to evaluate role of these therapies in COVID-19 patients.\n\nMethodsMEDLINE and MedRxiv were searched until July 30th, 2020, including studies that compared treatment outcomes of humans treated with JAK-inhibitor or Type I interferon against controls. Inclusion necessitated data with clear risk estimates or those that permitted back-calculation.\n\nResultsWe searched 733 studies, ultimately including four randomized and eleven non-randomized clinical trials. JAK-inhibitor recipients had significantly reduced odds of mortality (OR, 0.12; 95%CI, 0.03-0.39, p=0.0005) and ICU admission (OR, 0.05; 95%CI, 0.01-0.26, p=0.0005), and had significantly increased odds of hospital discharge (OR, 22.76; 95%CI, 10.68-48.54, p<0.00001), when compared to standard treatment group. Type I interferon recipients had significantly reduced odds of mortality (OR, 0.19; 95%CI, 0.04-0.85, p=0.03), and increased odds of discharge bordering significance (OR, 1.89; 95%CI, 1.00-3.59, p=0.05).\n\nConclusionsJAK-inhibitor treatment is significantly associated with positive clinical outcomes regarding mortality, ICU admission, and discharge. Type I interferon treatment is associated with positive clinical outcomes regarding mortality and discharge. While these data show promise, additional randomized clinical trials are needed to further elucidate the efficacy of JAK-inhibitors and Type I interferons and clinical outcomes in COVID-19.\n\nKEY MESSAGESO_ST_ABSKey QuestionC_ST_ABSCan treatment of hospitalized COVID-19 patients with JAK-inhibitor or Type I interferon confer favorable clinical outcomes?\n\nBottom LineMeta-analysis demonstrates that JAK-inhibitor treatment was significantly associated with favorable clinical outcomes in terms of mortality, requiring mechanical ventilation, and hospital discharge, while treatment with Type I interferon was significantly associated with decreased mortality.\n\nWhy Read On?This study conducted a systematic review of human trials that treated patients with JAK-inhibitors or Type I interferon, and it elaborates on the potential benefits of administering these therapies at different moments of the disease course despite apparently opposite mechanism of action of these two interventions.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Mohamed LOUNIS Sr.",
-        "author_inst": "University of Ziane Achour Djelfa"
+        "author_name": "Lucas Walz",
+        "author_inst": "Yale School of Public Health; Yale School of Medicine"
+      },
+      {
+        "author_name": "Avi J. Cohen",
+        "author_inst": "Yale School of Medicine"
       },
       {
-        "author_name": "Juarez dos Santos AZEVEDO Sr.",
-        "author_inst": "Universidade Federal da Bahia (UFBA)"
+        "author_name": "Andre P. Rebaza",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "James Vanchieri",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Martin D. Slade",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Charles S. Dela Cruz",
+        "author_inst": "Yale School of Medicine"
+      },
+      {
+        "author_name": "Lokesh Sharma",
+        "author_inst": "Yale School of Medicine"
       }
     ],
     "version": "1",
@@ -1209189,79 +1212289,35 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.08.09.242867",
-    "rel_title": "A potent neutralizing nanobody against SARS-CoV-2 with inhaled delivery potential",
+    "rel_doi": "10.1101/2020.08.04.20168054",
+    "rel_title": "SARS-CoV-2 and the Role of Orofecal Transmission: Systematic Review",
     "rel_date": "2020-08-10",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.09.242867",
-    "rel_abs": "The outbreak of COVID-19 has emerged as a global pandemic. The unprecedented scale and severity call for rapid development of effective prophylactics or therapeutics. We here reported Nanobody (Nb) phage display libraries derived from four camels immunized with the SARS-CoV-2 spike receptor-binding domain (RBD), from which 381 Nbs were identified to recognize SARS-CoV-2-RBD. Furthermore, seven Nbs were shown to block interaction of human angiotensin converting enzyme 2 (ACE2) with SARS-CoV-2-RBD-variants, bat-SL-CoV-WIV1-RBD and SARS-CoV-1-RBD. Among the seven candidates, Nb11-59 exhibited the highest activity against authentic SARS-CoV-2 with ND50 of 0.55 g/mL. Nb11-59 can be produced on a large-scale in Pichia pastoris, with 20 g/L titer and 99.36% purity. It also showed good stability profile, and nebulization did not impact its stability. Overall, Nb11-59 might be a promising prophylactic and therapeutic molecule against COVID-19, especially through inhalation delivery.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC=\"FIGDIR/small/242867v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (42K):\norg.highwire.dtl.DTLVardef@e4434org.highwire.dtl.DTLVardef@9fee79org.highwire.dtl.DTLVardef@1e15bb1org.highwire.dtl.DTLVardef@4adb0c_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
-    "rel_num_authors": 15,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.04.20168054",
+    "rel_abs": "BackgroundHow SARS-CoV-2 is transmitted is of key public health importance. SARS-CoV-2 has been detected in the feces of some Covid-19 patients which suggests the possibility that the virus could additionally be transmitted via the orofecal route.\n\nMethodsThis review is part of an Open Evidence Review on Transmission Dynamics of Covid-19. We conduct ongoing searches using LitCovid, medRxiv, Google Scholar and Google for Covid-19; assess study quality based on five criteria and report important findings on an ongoing basis. Where necessary authors are contacted for further details or clarification on the content of their articles.\n\nResultsWe found 59 studies: nine reviews and 51 primary studies or reports (one cohort study also included a review) examining the potential role of orofecal transmission of SARS-CoV-2. Half (n=29) were done in China. Thirty seven studies reported positive fecal samples for SARS-CoV-2 based on RT-PCR results (n=1,034 patients). Six studies reported isolating the virus from fecal samples of nine patients, one study isolated the virus from rectal tissue and one laboratory study found that SARS-CoV-2 productively infected human small intestinal organoids. Eleven studies report on fecal samples found in sewage, and two sampled bathrooms and toilets.\n\nConclusionsVarious observational and mechanistic evidence support the hypothesis that SARS-CoV-2 can infect and be shed from the human gastrointestinal tract. Policy should emphasize the importance of strict personal hygiene measures, and chlorine-based disinfection of surfaces in locations where there is presumed or known SARS-CoV-2 activity.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Junwei Gai",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
-      },
-      {
-        "author_name": "Linlin Ma",
-        "author_inst": "Shanghai University of Medicine and Health Sciences"
-      },
-      {
-        "author_name": "Guanghui Li",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
-      },
-      {
-        "author_name": "Min Zhu",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
-      },
-      {
-        "author_name": "Peng Qiao",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
-      },
-      {
-        "author_name": "Xiaofei Li",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
-      },
-      {
-        "author_name": "Haiwei Zhang",
-        "author_inst": "Wuhan Institute of Virology,  Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Yanmin Zhang",
-        "author_inst": "School of Science, China Pharmaceutical University"
-      },
-      {
-        "author_name": "Yadong Chen",
-        "author_inst": "School of Science, China Pharmaceutical University"
-      },
-      {
-        "author_name": "Weiwei Ji",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
-      },
-      {
-        "author_name": "Hao Zhang",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
-      },
-      {
-        "author_name": "Huanhuan Cao",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
+        "author_name": "Carl Heneghan",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Xionghui Li",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
+        "author_name": "Elizabeth Spencer",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Rui Gong",
-        "author_inst": "Wuhan Institute of Virology Chinese Academy of Sciences"
+        "author_name": "Jon Brassey",
+        "author_inst": "Trip Database"
       },
       {
-        "author_name": "Yakun Wan",
-        "author_inst": "Shanghai Novamab Biopharmaceuticals Co., Ltd."
+        "author_name": "Tom Jefferson",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "bioengineering"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.08.10.241414",
@@ -1211047,53 +1214103,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.07.20169961",
-    "rel_title": "Neutralizing antibody response in non-hospitalized SARS-CoV-2 patients",
+    "rel_doi": "10.1101/2020.08.05.20168476",
+    "rel_title": "Specificity and Performance of Nucleocapsid and Spike-based SARS-CoV-2 Serologic Assays",
     "rel_date": "2020-08-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20169961",
-    "rel_abs": "The majority of infections with SARS-CoV-2 are asymptomatic or mild without the necessity of hospitalization. It is of importance to reveal if these patients develop an antibody response against SARS-CoV-2 and to define which antibodies confer virus neutralization. We conducted a comprehensive serological survey of 49 patients with a mild course of disease and quantified neutralizing antibody responses against a clinical SARS-CoV-2 isolate employing human cells as targets.\n\nFour patients (8%), even though symptomatic, did not develop antibodies against SARS-CoV-2 and two other patients (4%) were only positive in one of the six serological assays employed. For the remainder, antibody response against the S-protein correlated with serum neutralization whereas antibodies against the nucleocapsid were poor predictors of virus neutralization. Regarding neutralization, only six patients (12%) could be classified as highly neutralizers. Furthermore, sera from several individuals with fairly high antibody levels had only poor neutralizing activity. In addition, employing a novel serological Western blot system to characterize antibody responses against seasonal coronaviruses, we found that antibodies against the seasonal coronavirus 229E might contribute to SARS-CoV-2 neutralization.\n\nAltogether, we show that there is a wide breadth of antibody responses against SARS-CoV-2 in patients that differentially correlate with virus neutralization. This highlights the difficulty to define reliable surrogate markers for immunity against SARS-CoV-2.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20168476",
+    "rel_abs": "There is an urgent need for an accurate antibody test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, we have developed 3 ELISA methods, trimer spike IgA, trimer spike IgG, and nucleocapsid IgG, for detecting anti-SARS-CoV-2 antibodies. We evaluated their performance in comparison with four commercial ELISAs, EDI Novel Coronavirus COVID-19 ELISA IgG and IgM, Euroimmun Anti-SARS-CoV-2 ELISA IgG and IgA, and one lateral flow assay, DPP(R) COVID-19 IgM/IgG System (Chembio). Both sensitivity and specificity were evaluated and the causes of false-positive reactions were determined.\n\nThe assays were compared using 300 pre-epidemic samples and 100 PCR-confirmed COVID-19 samples. The sensitivities and specificities of the assays were as follows: 90%/100% (in-house trimer spike IgA), 90%/99.3% (in-house trimer spike IgG), 89%/98.3% (in-house nucleocapsid IgG), 73.7%/100% (EDI nucleocapsid IgM), 84.5%/95.1% (EDI nucleocapsid IgG), 95%/93.7% (Euroimmun S1 IgA), 82.8%/99.7% (Euroimmun S1 IgG), 82.0%/91.7% (Chembio nucleocapsid IgM), 92%/93.3% (Chembio nucleocapsid IgG).\n\nThe presumed causes of positive signals from pre-epidemic samples in commercial and in-house assays were mixed. In some cases, positivity varied with assay repetition. In other cases, reactivity was abrogated by competitive inhibition (spiking the sample with analyte prior to performing the assay). In other cases, reactivity was consistently detected but not abrogated by analyte spiking.\n\nOverall, there was wide variability in assay performance using our samples, with in-house tests exhibiting the highest combined sensitivity and specificity. The causes of \"false positivity\" in pre-epidemic samples may be due to plasma antibodies apparently reacting with the analyte, or spurious reactivity may be directed against non-specific components in the assay system. Identification of these targets will be essential to improving assay performance.",
     "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Natalia Ruetalo",
-        "author_inst": "Institute for Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen"
+        "author_name": "Zahra Rikhtegaran Tehrani",
+        "author_inst": "University of Maryland, School of Madicine"
       },
       {
-        "author_name": "Ramona Businger",
-        "author_inst": "Institute for Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen"
+        "author_name": "Saman Saadat",
+        "author_inst": "University of Maryland, School of Medicine"
       },
       {
-        "author_name": "Karina Althaus",
-        "author_inst": "Institute for Transfusion Medicine, University Hospital Tuebingen"
+        "author_name": "Ebtehal Saleh",
+        "author_inst": "University of Maryland, School of Madicine"
       },
       {
-        "author_name": "Simon Fink",
-        "author_inst": "NMI, Reutlingen"
+        "author_name": "Xin Ouyang",
+        "author_inst": "University of Maryland, School of Madicine"
       },
       {
-        "author_name": "Felix Ruoff",
-        "author_inst": "NMI, Reutlingen"
+        "author_name": "Niel Constantine",
+        "author_inst": "University of Maryland, School of Madicine"
       },
       {
-        "author_name": "Klaus Hamprecht",
-        "author_inst": "Institute for Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen"
+        "author_name": "Anthony L. DeVico",
+        "author_inst": "University of Maryland, School of Madicine"
       },
       {
-        "author_name": "Bertram Flehmig",
-        "author_inst": "Mediagnost GmbH, Reutlingen"
+        "author_name": "Anthony D. Harris",
+        "author_inst": "University of Maryland, School of Madicine"
       },
       {
-        "author_name": "Tamam Bakchoul",
-        "author_inst": "Institute for Transfusion Medicine, University Hospital Tuebingen"
+        "author_name": "George K. Lewis",
+        "author_inst": "University of Maryland, School of Madicin"
       },
       {
-        "author_name": "Markus F Templin",
-        "author_inst": "NMI, Reutlingen"
+        "author_name": "Shyam Kottilil",
+        "author_inst": "University of Maryland, School of Madicine"
       },
       {
-        "author_name": "Michael Schindler",
-        "author_inst": "University Hospital Tuebingen"
+        "author_name": "Mohammad M. Sajadi",
+        "author_inst": "University of Maryland, School of Madicine"
       }
     ],
     "version": "1",
@@ -1212789,17 +1215845,69 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.05.20168799",
-    "rel_title": "COVID-19 Test & Trace Success Determinants: Modeling On A Network",
+    "rel_doi": "10.1101/2020.08.04.20168518",
+    "rel_title": "Phylodynamics reveals the role of human travel and contact tracing in controlling COVID-19 in four island nations",
     "rel_date": "2020-08-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20168799",
-    "rel_abs": "What determines the success of a COVID-19 Test & Trace policy? We use an SEIR agent-based model on a graph, with realistic epidemiological parameters. Simulating variations in certain parameters of Testing & Tracing, we find that important determinants of successful containment are: (i) the time from symptom onset until a patient is self-isolated and tested, and (ii) the share of contacts of a positive patient who are successfully traced. Comparatively less important is (iii) the time of test analysis and contact tracing. When the share of contacts successfully traced is higher, the Test & Trace Time rises somewhat in importance. These results are robust to a wide range of values for how infectious presymptomatic patients are, to the amount of asymptomatic patients, to the network degree distribution and to base epidemic growth rate. We also provide mathematical arguments for why these simulation results hold in more general settings. Since real world Test & Trace systems and policies could affect all three parameters, Symptom Onset to Test Time should be considered, alongside test turnaround time and contact tracing coverage, as a key determinant of Test & Trace success.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.04.20168518",
+    "rel_abs": "BackgroundNew Zealand, Australia, Iceland, and Taiwan all saw success at controlling the first wave of the COVID-19 pandemic. As islands, they make excellent case studies for exploring the effects of international travel and human movement on the spread of COVID-19.\n\nMethodsWe employed a range of robust phylodynamic methods and genome subsampling strategies to infer the epidemiological history of SARS-CoV-2 in these four countries. We compared these results to transmission clusters identified by the New Zealand Ministry of Health by contract tracing strategies.\n\nFindingsWe estimated the effective reproduction number of COVID-19 as 1-1.4 during early stages of the pandemic, and show that it declined below 1 as human movement was restricted. We also showed that this disease was introduced many times into each country, and that introductions slowed down markedly following the reduction of international travel in mid March 2020. Finally, we confirmed that New Zealand transmission clusters identified via standard health surveillance strategies largely agree with those defined by genomic data.\n\nInterpretationWe have demonstrated how the use of genomic data and computational biology methods can assist health officials in characterising the epidemiology of viral epidemics, and for contact tracing.\n\nFundingThis research was funded by the Health Research Council of New Zealand, the Ministry of Business, Innovation, and Employment, the Royal Society of New Zealand, and the New Zealand Ministry of Health.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSOur study looks at the early months of the COVID-19 pandemic, a period in which the first wave was controlled in four \"island\" nations - New Zealand, Australia, Taiwan, and Iceland. All prior data used in this study was collected from late 2019 until the end of April 2020. This includes over 3000 SARS-CoV-2 genomic sequences which were collected in this period (and subsequently deposited into GISAID), as well as arrival and departure information (provided by official statistics from each country), human mobility data collected from mobile phones (by Apple), and COVID-19 case data (released by the World Health Organisation). Even early on during the COVID-19 pandemic, the properties of SARS-CoV-2 - including the reproduction number and mutation rate - were well characterised, and a range of these estimates have been covered in our article. Our Bayesian phylodynamic models, including their prior distributions, are informed by all of the above sources of information. Finally, we have incorporated all of the available information on COVID-19 transmission clusters identified by the New Zealand Ministry of Health during this period.\n\nAdded value of this studyWe quantified the decline in the reproduction number of SARS-CoV-2, following the decline in human mobility, in four \"island\" countries. We also demonstrated how importation events of SARS-CoV-2 into each considered country declined markedly following the reduction of international travel. Our results shed a different light on these patterns because of (i) our locations of choice - the four countries had success in dealing with the first pandemic wave, with their geographic isolation contributing to cleaner signals of human mobility, and (ii) our novel and empirically driven phylodynamic model, which we built from explicitly modelling mobile phone data in the four islands. Furthermore, by crossing epidemiological against ge3nomic data, our paper quantitatively assesses the ability of contact tracing, as implemented by the New Zealand Ministry of Health (NZMH), in identifying COVID-19 transmission clusters. We find evidence for a high efficacy of the specific measures taken - and when they were taken - by the NZMH in identifying transmission clusters, considered worldwide to have been successful in its response to the pandemic. Our analyses also illustrate the power of viral genomic data in assisting contact tracing.\n\nImplications of all the available evidenceThe conclusions drawn from this research inform effective policy for locations pursuing an elimination strategy. We confirm the accuracy of standard contact tracing methods at identifying clusters and show how these methods are improved using genomic data. We demonstrate how the overseas introduction rates and domestic transmission rates of an infectious viral agent can be surveilled using genomic data, and the important role each plays in overall transmission. Specifically, we have quantified these processes for four countries and have shown that they did decline significantly following declines in human travel and mobility. The phylodynamic methods used in this work is shown to be robust and applicable to a range of scenarios where appropriate subsampling is used.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Ofir Reich",
-        "author_inst": "Google"
+        "author_name": "Jordan Douglas",
+        "author_inst": "University of Auckland"
+      },
+      {
+        "author_name": "Fabio K Mendes",
+        "author_inst": "Centre for Computational Evolution, The University of Auckland, Auckland, New Zealand"
+      },
+      {
+        "author_name": "Remco Bouckaert",
+        "author_inst": "Centre for Computational Evolution, The University of Auckland, Auckland, New Zealand"
+      },
+      {
+        "author_name": "Dong Xie",
+        "author_inst": "Centre for Computational Evolution, The University of Auckland, Auckland, New Zealand"
+      },
+      {
+        "author_name": "Cinthy L Jimenez-Silva",
+        "author_inst": "Centre for Computational Evolution, The University of Auckland, Auckland, New Zealand"
+      },
+      {
+        "author_name": "Christiaan Swanepoel",
+        "author_inst": "Centre for Computational Evolution, The University of Auckland, Auckland, New Zealand"
+      },
+      {
+        "author_name": "Joep de Ligt",
+        "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand"
+      },
+      {
+        "author_name": "Xiaoyun Ren",
+        "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand"
+      },
+      {
+        "author_name": "Matt Storey",
+        "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand"
+      },
+      {
+        "author_name": "James Hadfield",
+        "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA"
+      },
+      {
+        "author_name": "Colin R Simpson",
+        "author_inst": "School of Health, Victoria University of Wellington, Wellington, New Zealand"
+      },
+      {
+        "author_name": "Jemma L Geoghegan",
+        "author_inst": "Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand"
+      },
+      {
+        "author_name": "Alexei J Drummond",
+        "author_inst": "Centre for Computational Evolution, The University of Auckland, Auckland, New Zealand"
+      },
+      {
+        "author_name": "David Welch",
+        "author_inst": "Centre for Computational Evolution, The University of Auckland, Auckland, New Zealand"
       }
     ],
     "version": "1",
@@ -1214707,83 +1217815,27 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.08.06.239798",
-    "rel_title": "IFN signaling and neutrophil degranulation transcriptional signatures are induced during SARS-CoV-2 infection",
+    "rel_doi": "10.1101/2020.08.06.240333",
+    "rel_title": "Computational Hot-Spot Analysis of the SARS-CoV-2 Receptor Binding Domain / ACE2 Complex",
     "rel_date": "2020-08-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.06.239798",
-    "rel_abs": "The novel virus SARS-CoV-2 has infected more than 14 million people worldwide resulting in the Coronavirus disease 2019 (COVID-19). Limited information on the underlying immune mechanisms that drive disease or protection during COVID-19 severely hamper development of therapeutics and vaccines. Thus, the establishment of relevant animal models that mimic the pathobiology of the disease is urgent. Rhesus macaques infected with SARS-CoV-2 exhibit disease pathobiology similar to human COVID-19, thus serving as a relevant animal model. In the current study, we have characterized the transcriptional signatures induced in the lungs of juvenile and old rhesus macaques following SARS-CoV-2 infection. We show that genes associated with Interferon (IFN) signaling, neutrophil degranulation and innate immune pathways are significantly induced in macaque infected lungs, while pathways associated with collagen formation are downregulated. In COVID-19, increasing age is a significant risk factor for poor prognosis and increased mortality. We demonstrate that Type I IFN and Notch signaling pathways are significantly upregulated in lungs of juvenile infected macaques when compared with old infected macaques. These results are corroborated with increased peripheral neutrophil counts and neutrophil lymphocyte ratio in older individuals with COVID-19 disease. In contrast, pathways involving VEGF are downregulated in lungs of old infected macaques. Using samples from humans with SARS-CoV-2 infection and COVID-19, we validate a subset of our findings. Finally, neutrophil degranulation, innate immune system and IFN gamma signaling pathways are upregulated in both tuberculosis and COVID-19, two pulmonary diseases where neutrophils are associated with increased severity. Together, our transcriptomic studies have delineated disease pathways to improve our understanding of the immunopathogenesis of COVID-19 to facilitate the design of new therapeutics for COVID-19.",
-    "rel_num_authors": 16,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.06.240333",
+    "rel_abs": "Infection and replication of SARS CoV-2 (the virus that causes COVID-19) requires entry to the interior of host cells. In humans, a Protein-Protein Interaction (PPI) between the SARS CoV-2 Receptor-Binding Domain (RBD) and the extracellular peptidase domain of ACE2, on the surface of cells in the lower respiratory tract, is an initial step in the entry pathway. Inhibition of the SARS CoV-2 RBD / ACE2 PPI is currently being evaluated as a target for therapeutic and/or prophylactic intervention. However, relatively little is known about the molecular underpinnings of this complex. Employing multiple computational platforms, we predicted  hot-spot residues in a positive control PPI (PMI / MDM2) and the CoV-2 RBD/ACE2 complex. Computational alanine scanning mutagenesis was performed to predict changes in Gibbs free energy that are associated with mutating residues at the positive control (PMI/MDM2) or SARS RBD/ACE2 binding interface to alanine. Additionally, we used the Adaptive Poisson-Boltzmann Solver to calculate macromolecular electrostatic surfaces at the interface of the positive control PPI and SARS CoV-2 / ACE2 PPI. Collectively, this study illuminates predicted hot-spot residues, and clusters, at the SARS CoV-2 RBD / ACE2 binding interface, potentially guiding the development of reagents capable of disrupting this complex and halting COVID-19.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Bruce A. Rosa",
-        "author_inst": "Washington University in Saint Louis School of Medicine"
-      },
-      {
-        "author_name": "Mushtaq Ahmed",
-        "author_inst": "Washington University in St Louis"
-      },
-      {
-        "author_name": "Dhiraj K. Singh",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Jose Alberto Choreno-Parra",
-        "author_inst": "Laboratory of Immunobiology and Genetics, Instituto Nacional de Enfermedades Respiratorias"
-      },
-      {
-        "author_name": "Journey Cole",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Luis Armando Jimenez-Alvarez",
-        "author_inst": "Laboratory of Immunobiology and Genetics, Instituto Nacional de Enfermedades Respiratorias"
-      },
-      {
-        "author_name": "Tatiana Sofia Rodriguez-Reyna",
-        "author_inst": "Department of Immunology and Rheumatology, Instituto Nacional de Ciencias Medicas y Nutricion"
-      },
-      {
-        "author_name": "Bindu Singh",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Olga Golzalez",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Ricardo Carrion",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "Larry S. Schlesinger",
-        "author_inst": "Texas Biomedical Research Institute"
-      },
-      {
-        "author_name": "John Martin",
-        "author_inst": "Washington University School of Medicine"
-      },
-      {
-        "author_name": "Joaquin Zuniga",
-        "author_inst": "Escuela Nacional de Ciencias Biologicas, Instituto Politecnico Nacional"
-      },
-      {
-        "author_name": "Makedonka Mitreva",
-        "author_inst": "Washington University School of Medicine"
-      },
-      {
-        "author_name": "Shabaana A Khader",
-        "author_inst": "Washington University School of Medicine"
+        "author_name": "Pedro A. Rosario",
+        "author_inst": "Delaware State University"
       },
       {
-        "author_name": "Deepak Kaushal",
-        "author_inst": "Texas Biomedical Research Institute"
+        "author_name": "Brian R McNaughton",
+        "author_inst": "Delaware State University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2020.08.06.238915",
@@ -1216685,173 +1219737,65 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.31.20163055",
-    "rel_title": "SARS-CoV-2 Seroprevalence Across a Diverse Cohort of Healthcare Workers",
+    "rel_doi": "10.1101/2020.07.31.20165738",
+    "rel_title": "Early clinical characteristics of Covid-19: scoping review",
     "rel_date": "2020-08-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20163055",
-    "rel_abs": "ImportanceAntibody testing is important for understanding patterns of exposure and potential immunity to SARS-CoV-2. Prior data on seroprevalence have been subject to variations in selection of individuals and nature as well as timing of testing in relation to exposures.\n\nObjectiveWe sought to determine the extent of SARS-CoV-2 seroprevalance and the factors associated with seroprevelance across a diverse cohort of healthcare workers.\n\nDesignObservational cohort study of healthcare workers, including SARS-CoV-2 serology testing and participant questionaires.\n\nParticipantsA diverse and unselected population of adults (n=6,062) employed in a multi-site healthcare delivery system located in Los Angeles County, including individuals with direct patient contact and others with non-patient-oriented work functions.\n\nExposureExposure and infection with the SARS-CoV-2 virus, as determined by seropositivity.\n\nMain OutcomesUsing Bayesian and multi-variate analyses, we estimated seroprevalence and factors associated with seropositivity and antibody titers, including pre-existing demographic and clinical characteristics; potential Covid-19 illness related exposures; and, symptoms consistent with Covid-19 infection.\n\nResultsWe observed a seroprevalence rate of 4.1%, with anosmia as the most prominently associated self-reported symptom in addition to fever, dry cough, anorexia, and myalgias. After adjusting for potential confounders, pre-existing medical conditions were not associated with antibody positivity. However, seroprevalence was associated with younger age, Hispanic ethnicity, and African-American race, as well as presence of either a personal or household member having a prior diagnosis of Covid-19. Importantly, African American race and Hispanic ethnicity were associated with antibody positivity even after adjusting for personal Covid-19 diagnosis status, suggesting the contribution of unmeasured structural or societally factors. Notably, number of people, or children, in the home was not associated with antibody positivity.\n\nConclusion and RelevanceThe demographic factors associated with SARS-CoV-2 seroprevalence among our healthcare workers underscore the importance of exposure sources beyond the workplace. The size and diversity of our study population, combined with robust survey and modeling techniques, provide a vibrant picture of the demographic factors, exposures, and symptoms that can identify individuals with susceptibility as well as potential to mount an immune response to Covid-19.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the SARS-CoV-2 IgG seroprevalence rate across a large and diverse healthcare worker population, and which clinical, envionrmental, and symptom-based measures are associated with seropositivity?\n\nFindingsWe observed a seroprevalence rate of 4.1%. Adjusting for potential confounders, seropositivity was associated with younger age, Hispanic ethnicity, African-American race, and the symptom of anosmia, while not significantly associated with any pre-existing medical conditions.\n\nMeaningFactors associated with SARS-CoV-2 seroprevalence among our healthcare workers underscore the importance of exposure sources beyond the workplace.",
-    "rel_num_authors": 39,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20165738",
+    "rel_abs": "BackgroundThe Coronavirus disease 2019 (covid-19) pandemic has spread rapidly across the globe. Accurate clinical characterisation studies conducted early in the pandemic are essential to informing research, diagnosis and clinical management efforts. In this scoping review we identify the clinical characteristics of patients admitted to hospital in the early months of the pandemic, focusing on symptoms, laboratory and imaging findings, and clinical outcomes.\n\nMethodsA scoping review. MEDLINE, EMBASE and Global Health databases were searched for studies published from January 1st 2020 to April 28th 2020. Studies which reported on at least 100 hospitalised patients with covid-19 of any age were included.\n\nResultsOf 1,249 studies identified through the search 78 studies were eligible for inclusion; one randomized control trial and 77 observational studies presenting data on 77,443 patients admitted with covid-19. Most studies were conducted in China (82%), 9% in the US and 10% in Europe and two studies were set in more than one country. No studies included patients from low and middle income countries. Coagulopathy was underrecognised as a complication in the early months of the pandemic. Use of corticosteroids varied widely, and the use of anticoagulants was reported in only one study. Fever, cough and dyspnoea are less common in older adults; gastrointestinal symptoms, as the only presenting feature was underrecognised. The most common laboratory finding was lymphocytopenia. Inflammatory biomarkers were commonly elevated, including C-reactive protein and interleukin-6. Typical computed tomography findings include bilateral infiltrates however imaging may be normal in early disease. Data on clinical characteristics in children and vulnerable populations were limited.\n\nConclusionsClinical characterisation studies from early in the pandemic indicated that covid-19 is a multisystem disease, with biomarkers indicating inflammation and coagulopathy. However, early data collection on symptoms and clinical outcomes did not consistently reflect this wide spectrum. Corticosteroid use varied widely, and anticoagulants were rarely used. Clinicians should remain vigilant to the possibility of covid-19 in patients presenting without fever, cough and dyspnoea, particularly in older adults. Further characterisation studies in different at-risk populations is needed.\n\nReview registrationAvailable at https://osf.io/r2ch9",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Joseph Ebinger",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Gregory J. Botwin",
-        "author_inst": "Cedars Sinai Medical Center"
-      },
-      {
-        "author_name": "Christine M. Albert",
-        "author_inst": "Cedars Sinai Medical Center"
-      },
-      {
-        "author_name": "Mona Alotaibi",
-        "author_inst": "University of California, San Diego"
-      },
-      {
-        "author_name": "Moshe Arditi",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Anders H. Berg",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Aleksandra Binek",
-        "author_inst": "Cedars Sinai Medical Center"
-      },
-      {
-        "author_name": "Patrick G. Botting",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Justyna Fert-Bober",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Jane C. Figueiredo",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Jonathan D. Grein",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Wohaib Hasan",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Mir Henglin",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Shehnaz K. Hussain",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Mohit Jain",
-        "author_inst": "University of California, San Diego"
-      },
-      {
-        "author_name": "Sandy Joung",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Michael Karin",
-        "author_inst": "University of California, San Diego"
-      },
-      {
-        "author_name": "Elizabeth H Kim",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Dalin Li",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Yunxian Liu",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Eric Luong",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Dermot P.B. McGovern",
-        "author_inst": "Cedars Sinai Medical Center"
-      },
-      {
-        "author_name": "Akil Merchant",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Noah M. Merin",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Peggy B. Miles",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Margo Minissian",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Trevor-Trung Nguyen",
-        "author_inst": "Cedars-Sinai Medical Center"
-      },
-      {
-        "author_name": "Koen Raedschelders",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Lakshmi Manoharan",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Mohamad A. Rashid",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Jonathan W S Cattrall",
+        "author_inst": "Liverpool University Hospitals NHS Foundation Trust, University of Liverpool"
       },
       {
-        "author_name": "Celine E. Riera",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Carlyn Harris",
+        "author_inst": "Emory University School of Medicine"
       },
       {
-        "author_name": "Richard V. Riggs",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Katherine Newell",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sonia Sharma",
-        "author_inst": "La Jolla Institute"
+        "author_name": "Blake Thomson",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sarah Sternbach",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Mark G Pritchard",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Nancy Sun",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Peter G Bannister",
+        "author_inst": "Brighton and Sussex Medical School"
       },
       {
-        "author_name": "Warren G. Tourtellotte",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Louise Sigfrid",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Jennifer E. Van Eyk",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Tom Solomon",
+        "author_inst": "University of Liverpool"
       },
       {
-        "author_name": "Kimia Sobhani",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Peter W Horby",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Jonathan G. Braun",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Gail Carson",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Susan Cheng",
-        "author_inst": "Cedars-Sinai Medical Center"
+        "author_name": "Piero L Olliaro",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1218523,37 +1221467,61 @@
     "category": "surgery"
   },
   {
-    "rel_doi": "10.1101/2020.08.03.20167320",
-    "rel_title": "Retrospective SARS-CoV-2 Real-Time PCR Testing of Stored Bronchoalveolar Lavage Samples from February 2020",
+    "rel_doi": "10.1101/2020.08.02.20166256",
+    "rel_title": "Clinical characteristics and antibody response to SARS-CoV-2 spike 1 protein using the VITROS Anti-SARS-CoV-2 antibody tests in COVID-19 patients in Japan",
     "rel_date": "2020-08-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.03.20167320",
-    "rel_abs": "Bronchoalveolar lavage samples (n=34) collected in February, 2020 prior to the wide availability of molecular testing for SARS-CoV-2 were retrospectively assayed for presence of viral RNA. None of these patients qualified for SARS-CoV-2 testing based on Centers for Disease Control criteria at the time. None of the samples tested positive for SARS-CoV-2, suggesting that the virus was not yet widespread in Minnesota at the time these samples were obtained.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.02.20166256",
+    "rel_abs": "BackgroundWe evaluated clinical characteristics and the clinical utility of VITROS SARS-CoV-2 antibody tests according to COVID-19 severity in patients in Japan.\n\nMethodsWe analyzed 255 serum specimens from 130 COVID-19 patients and examined clinical records and laboratory data. Presence of total (IgA, IgM, and IgG) and specific IgG antibody for the spike 1 antigen of SARS-CoV2 was determined using VITROS Anti-SARS-CoV-2 antibody tests.\n\nFindingsOverall, 98 (75.4%) and 32 (24.6%) patients had mild and severe COVID-19, respectively. On admission, 76 (58.5%) and 45 (34.6%) patients were positive for total and IgG antibody assays. Among 91 patients at discharge, 90 (98.9%) and 81 (89.0%) patients were positive for total and IgG antibody, respectively. Clinical background and laboratory findings on admission, but not the prevalence or concentration of total or IgG antibody, were associated with disease prognosis. Total and IgG antibody intensity were significantly higher in severe cases than in mild cases in serum collected after 11 days from onset, but not within 10 days.\n\nConclusionVITROS Anti-SARS-CoV-2 Total and IgG assays will be useful as supporting diagnostic and surveillance tools and for evaluation of humoral immune response to COVID-19. Clinical background and laboratory findings are preferable predictors of disease prognosis.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Douglas W Challener",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Mayu Nagura-Ikeda",
+        "author_inst": "Self-Defense Forces Central Hospital"
       },
       {
-        "author_name": "Aditya Shah",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Kazuo Imai",
+        "author_inst": "Saitama Medical University"
       },
       {
-        "author_name": "Matthew Binnicker",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Katsumi Kubota",
+        "author_inst": "Saitama Medical University Hospital"
       },
       {
-        "author_name": "Andrew Badley",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Sakiko Noguchi",
+        "author_inst": "Saitama Medical University Hospital"
       },
       {
-        "author_name": "John O'Horo",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Yutaro Kitagawa",
+        "author_inst": "Saitama Medical University Hospital"
+      },
+      {
+        "author_name": "Masaru Matsuoka",
+        "author_inst": "Saitama Medical University Hospital"
+      },
+      {
+        "author_name": "Sakiko Tabata",
+        "author_inst": "Self-Defense Forces Central Hospital"
+      },
+      {
+        "author_name": "Kazuyasu Miyoshi",
+        "author_inst": "Self-Defense Forces Central Hospital"
+      },
+      {
+        "author_name": "Toshimitsu Ito",
+        "author_inst": "Self-Defense Forces Central Hospital"
+      },
+      {
+        "author_name": "Kaku Tamura",
+        "author_inst": "Self-Defense Forces Central Hospital"
+      },
+      {
+        "author_name": "Takuya Maeda",
+        "author_inst": "Saitama Medical University Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1220061,119 +1223029,23 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.08.03.20165233",
-    "rel_title": "Simply saliva: stability of SARS-CoV-2 detection negates the need for expensive collection devices",
+    "rel_doi": "10.1101/2020.08.03.20167304",
+    "rel_title": "Correlation between daily infections and fatality rate due to Covid-19 in Germany",
     "rel_date": "2020-08-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.03.20165233",
-    "rel_abs": "Most currently approved strategies for the collection of saliva for COVID-19 diagnostics require specialized tubes containing buffers promoted for the stabilization of SARS-CoV-2 RNA and virus inactivation. Yet many of these are expensive, in limited supply, and not necessarily validated specifically for viral RNA. While saliva is a promising sample type as it can be reliably self-collected for the sensitive detection of SARS-CoV-2, the expense and availability of these collection tubes are prohibitive to mass testing efforts. Therefore, we investigated the stability of SARS-CoV-2 RNA and infectious virus detection from saliva without supplementation. We tested RNA stability over extended periods of time (2-25 days) and at temperatures representing at-home storage and elevated temperatures which might be experienced when cold chain transport may be unavailable. We found SARS-CoV-2 RNA in saliva from infected individuals is stable at 4{degrees}C, room temperature ([~]19{degrees}C), and 30{degrees}C for prolonged periods and found limited evidence for viral replication in stored saliva samples. This work demonstrates that expensive saliva collection options involving RNA stabilization and virus inactivation buffers are not always needed, permitting the use of cheaper collection options. Affordable testing methods are urgently needed to meet current testing demands and for continued surveillance in reopening strategies.",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.03.20167304",
+    "rel_abs": "The officially reported daily Covid-19 fatality rate is modelled with a trend line based on a nominal day-to-day reproduction rate and a cosine to take account of weekly fluctuations. Although the time trajectories of officially reported infections and fatalities are pronouncedly different, the reproduction rates obtained therefrom are similar. The long-term effective reproduction rate is around 0.835 and the administrative measures to contain the pandemic seem not to have an immediate reducing effect but well the ease of restrictions an increasing one. The fatality trajectory represented by its trend line can be projected from the number of daily infections by assuming a time lapse between symptom onset and death between 17 and 19 days and a time-dependent nominal lethality. The time trajectory of this lethality increases from 2.5% at March 16 when public life was restricted to 6% within 20 days indicating relatively more infections of vulnerable people. After stipulating face mask wearing at April 27, the nominal lethality decreases down to 1% later in summer. A detailed analysis shows that mask wearing really reduces the number of fatal infections and the officially reported daily infections in May and June are less lethal than before.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Isabel M Ott",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Madison S Strine",
-        "author_inst": "Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Anne E Watkins",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Maikel Boot",
-        "author_inst": "Department of Microbial Pathogenesis, Yale University School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Chaney C Kalinich",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Christina A Harden",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Chantal B.F. Vogels",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Arnau Casanovas-Massana",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Adam J Moore",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "M. Catherine Muenker",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Maura Nakahata",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Maria Tokuyama",
-        "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Allison Nelson",
-        "author_inst": "Department of Internal Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "John Fournier",
-        "author_inst": "Department of Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Santos Bermejo",
-        "author_inst": "Department of Internal Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Melissa Campbell",
-        "author_inst": "Department of Pediatrics, Division of Infectious Diseases, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Rupak Datta",
-        "author_inst": "Department of Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "- the Yale IMPACT Research team",
-        "author_inst": ""
-      },
-      {
-        "author_name": "Charles S Dela Cruz",
-        "author_inst": "Department of Internal Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Shelli F Farhadian",
-        "author_inst": "Department of Medicine, Section of Infectious Diseases, Yale School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Albert I Ko",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA; Department of Medicine, Section of Infectious Diseases"
-      },
-      {
-        "author_name": "Akiko Iwasaki",
-        "author_inst": "Department of Immunobiology, Yale School of Medicine, New Haven, CT, 06510, USA; Howard Hughes Medical Institute, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Nathan D Grubaugh",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
-      },
-      {
-        "author_name": "Craig B Wilen",
-        "author_inst": "Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA"
-      },
-      {
-        "author_name": "Anne Louise Wyllie",
-        "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT 06510, USA"
+        "author_name": "Dieter Mergel",
+        "author_inst": "University of Duisburg-Essen, Faculty of Physics"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.08.03.20164137",
@@ -1221999,18 +1224871,39 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.08.04.234880",
-    "rel_title": "SCV-2000bp: a primer panel for SARS-CoV-2 full-genome sequencing",
+    "rel_doi": "10.1101/2020.08.04.236653",
+    "rel_title": "Pathogenetic Perspective of Missense Mutations of ORF3a Protein of SARS-CoV2",
     "rel_date": "2020-08-04",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.04.234880",
-    "rel_abs": "Here we provide technical data for amplifying the complete genome of SARS-CoV-2 from clinical samples using only seventeen pairs of primers. We demonstrate that the [C]V2000bp primer panel successfully produces genomes when used with the residual total RNA extracts from positive clinical samples following diagnostic RT-PCRs (with Ct in the range from 13 to 20). The library preparation method reported here includes genome amplification of ~1750-2000 bp fragments followed by ultrasonic fragmentation combined with the introduction of Illumina compatible adapters. Using the SCV2000bp panel, 25 complete SARS-CoV-2 virus genome sequences were sequenced from clinical samples of COVID-19 patients from Moscow obtained in late March - early April.",
-    "rel_num_authors": 0,
-    "rel_authors": null,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.04.236653",
+    "rel_abs": "One of the most important proteins for COVID-19 pathogenesis in SARS-CoV2 is the ORF3a protein which is the largest accessory protein among others accessory proteins coded by coronavirus genome. The major roles of the protein include virulence, infectivity, ion channel activity, morphogenesis and virus release. The coronavirus, SARS-CoV2 is continuously evolving naturally and thereby the encoded proteins are also mutating rapidly. Therefore, critical study of mutations in ORF3a is certainty important from the pathogenetic perspective. Here, a sum of 175 various non-synonymous mutations in the ORF3a protein of SARS-CoV2 are identified and their corresponding effects in structural stability and functions of the protein ORF3a are studied. Broadly three different classes of mutations, such as neutral, disease and mixed (neutral and disease) type mutations were observed. Consecutive mutations in some ORF3a proteins are established based on timeline of detection of mutations. Considering the amino acid compositions over the ORF3a primary protein sequences, twenty clusters are detected based on K-means clustering method. Our findings on 175 novel mutations of ORF3a proteins will extend our knowledge of ORF3a, a vital accessory protein in SARS-CoV2, which would assist to enlighten on the pathogenicity of this life-threatening COVID-19.",
+    "rel_num_authors": 5,
+    "rel_authors": [
+      {
+        "author_name": "Sk. Sarif Hassan",
+        "author_inst": "Pingla Thana Mahavidyalaya"
+      },
+      {
+        "author_name": "Diksha Attrish",
+        "author_inst": "Dr. B. R. Ambedkar Centre For Biomedical Research (ACBR), University of Delhi (North Campus), Delhi 110007, India"
+      },
+      {
+        "author_name": "Shinjini Ghosh",
+        "author_inst": "Department of Biophysics, Molecular Biology and Bioinformatics, University of Calcutta, Kolkata 700009, West Bengal, India"
+      },
+      {
+        "author_name": "Pabitra Pal Choudhury",
+        "author_inst": "Applied Statistics Unit, Indian Statistical Institute, Kolkata 700108, India"
+      },
+      {
+        "author_name": "Bidyut Roy",
+        "author_inst": "Human Genetics Unit, Indian Statistical Institute, Kolkata 700108, West Bengal, India"
+      }
+    ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "confirmatory results",
-    "category": "molecular biology"
+    "type": "new results",
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.08.02.20159418",
@@ -1224148,97 +1227041,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.30.20163824",
-    "rel_title": "Clinical Utility of a Highly Sensitive Lateral Flow Immunoassay as determined by Titer Analysis for the Detection of anti-SARS-CoV-2 Antibodies at the Point-of-Care",
+    "rel_doi": "10.1101/2020.07.30.20114959",
+    "rel_title": "Impact of tocilizumab administration on mortality in severe COVID-19",
     "rel_date": "2020-08-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20163824",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), became a pandemic in early 2020. Lateral flow immunoassays for antibody testing have been viewed as a cheap and rapidly deployable method for determining previous infection with SARS-CoV-2; however, these assays have shown unacceptably low sensitivity. We report on nine lateral flow immunoassays currently available and compare their titer sensitivity in serum to a best-practice enzyme-linked immunosorbent assay (ELISA) and viral neutralization assay. For a small group of PCR-positive, we found two lateral flow immunoassay devices with titer sensitivity roughly equal to the ELISA; these devices were positive for all PCR-positive patients harboring SARS-CoV-2 neutralizing antibodies. One of these devices was deployed in Northern Italy to test its sensitivity and specificity in a real-world clinical setting. Using the device with fingerstick blood on a cohort of 27 hospitalized PCR-positive patients and seven hospitalized controls, ROC curve analysis gave AUC values of 0.7646 for IgG. For comparison, this assay was also tested with saliva from the same patient population and showed reduced discrimination between cases and controls with AUC values of 0.6841 for IgG. Furthermore, during viral neutralization testing, one patient was discovered to harbor autoantibodies to ACE2, with implications for how immune responses are profiled. We show here through a proof-of-concept study that these lateral flow devices can be as analytically sensitive as ELISAs and adopted into hospital protocols; however, additional improvements to these devices remain necessary before their clinical deployment.",
-    "rel_num_authors": 21,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20114959",
+    "rel_abs": "PurposeThe novel coronavirus disease 2019 (COVID-19) worldwide pandemic has placed a significant burden on hospitals and healthcare providers. The immune response to this disease is thought to lead to a cytokine storm, which contributes to the severity of illness. There is an urgent need to confirm whether the use of tocilizumab provides a benefit in individuals with COVID-19.\n\nMethodsA single-center propensity-score matched cohort study, including all consecutive COVID-19 patients, admitted to the medical center who were either discharged from the medical center or expired between March 1, 2020, and May 5, 2020, was performed. Patients were stratified according to the receipt of tocilizumab for cytokine storm and matched to controls using propensity scores. The primary outcome was in-hospital mortality.\n\nResultsA total of 132 patients were included in the matched dataset (tocilizumab=66; no tocilizumab=66). Approximately 73% of the patients were male. Hypertension (55%), diabetes mellitus (31%), and chronic pulmonary disease (15%) were the most common comorbidities present. There were 18 deaths (27.3%) in the tocilizumab group and 18 deaths (27.3%) in the no tocilizumab group (odds ratio, 1.0; 95% confidence interval, 0.465 - 2.151; p=1.00). Advanced age, history of myocardial infarction, dementia, chronic pulmonary disease, heart failure, and malignancy were significantly more common in patients who died.\n\nConclusionThe current analysis does not support the use of tocilizumab for the management of cytokine storm in patients with COVID-19. Use of this therapeutic agent should be limited to the context of a clinical trial until more evidence is available.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Amanda Haymond",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Claudius Mueller",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Hannah Steinberg",
-        "author_inst": "University of Illinois, Chicago"
-      },
-      {
-        "author_name": "K. Alex Hodge",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Caitlin W Lehman",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Shih-Chao Lin",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Lucia Collini",
-        "author_inst": "Santa Chiara Hospital"
+        "author_name": "Andrew Tsai",
+        "author_inst": "Robert Wood Johnson University Hospital Somerset"
       },
       {
-        "author_name": "Heather Branscome",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Tuong Vi Nguyen",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Sally Rucker",
-        "author_inst": "George Mason University"
+        "author_name": "Oumou Diawara",
+        "author_inst": "Robert Wood Johnson University Hospital Somerset"
       },
       {
-        "author_name": "Lauren Panny",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Rafaela Flor",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Raouf Guirguis",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Richard Hoefer",
-        "author_inst": "Sentara Dorothy G. Hoefer Comprehensive Breast Center"
-      },
-      {
-        "author_name": "Giovanni Lorenzin",
-        "author_inst": "Santa Chiara Hospital"
-      },
-      {
-        "author_name": "Emanuel Petricoin",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Fatah Kashanchi",
-        "author_inst": "George Mason University"
+        "author_name": "Ronald G Nahass",
+        "author_inst": "ID Care"
       },
       {
-        "author_name": "Kylene Kehn-Hall",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Paolo Lanzafame",
-        "author_inst": "Santa Chiara Hospital"
-      },
-      {
-        "author_name": "Lance Liotta",
-        "author_inst": "George Mason University"
-      },
-      {
-        "author_name": "Alessandra Luchini",
-        "author_inst": "George Mason University"
+        "author_name": "Luigi Brunetti",
+        "author_inst": "Ernest Mario School of Pharmacy"
       }
     ],
     "version": "1",
@@ -1225890,99 +1228715,51 @@
     "category": "medical education"
   },
   {
-    "rel_doi": "10.1101/2020.07.31.231746",
-    "rel_title": "Engineered ACE2 receptor traps potently neutralize SARS-CoV-2",
+    "rel_doi": "10.1101/2020.07.31.190454",
+    "rel_title": "Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy",
     "rel_date": "2020-08-01",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.31.231746",
-    "rel_abs": "An essential mechanism for SARS-CoV-1 and -2 infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human Fc domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2 pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50) in the 10-100 ng/ml range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-utilizing coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be pre-designed for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated or generated from convalescent patients.",
-    "rel_num_authors": 20,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.31.190454",
+    "rel_abs": "For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders Expanding (T-REX) was created to identify changes in both very rare and common cells in diverse human immune monitoring settings. T-REX identified cells that were highly similar in phenotype and localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections. Specialized reagents used to detect the rhinovirus-specific CD4+ cells, MHCII tetramers, were not used during unsupervised analysis and instead  left out to serve as a test of whether T-REX identified biologically significant cells. In the rhinovirus challenge study, T-REX identified virus-specific CD4+ T cells based on these cells being a distinct phenotype that expanded by [&ge;]95% following infection. T-REX successfully identified hotspots containing virus-specific T cells using pairs of samples comparing Day 7 of infection to samples taken either prior to infection (Day 0) or after clearing the infection (Day 28). Mapping pairwise comparisons in samples according to both the direction and degree of change provided a framework to compare systems level immune changes during infectious disease or therapy response. This revealed that the magnitude and direction of systemic immune change in some COVID-19 patients was comparable to that of blast crisis acute myeloid leukemia patients undergoing induction chemotherapy and characterized the identity of the immune cells that changed the most. Other COVID-19 patients instead matched an immune trajectory like that of individuals with rhinovirus infection or melanoma patients receiving checkpoint inhibitor therapy. T-REX analysis of paired blood samples provides an approach to rapidly identify and characterize mechanistically significant cells and to place emerging diseases into a systems immunology context.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Anum Glasgow",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Jeff Edward Glasgow",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Daniel Limonta",
-        "author_inst": "University of Alberta"
-      },
-      {
-        "author_name": "Paige Solomon",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Irene Lui",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Yang Zhang",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Matthew A Nix",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Nicholas J Rettko",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Shion A Lim",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Shoshana Zha",
-        "author_inst": "University of California, San Francisco"
-      },
-      {
-        "author_name": "Rachel Yamin",
-        "author_inst": "Rockefeller University"
-      },
-      {
-        "author_name": "Kevin Kao",
-        "author_inst": "Rockefeller University"
-      },
-      {
-        "author_name": "Oren S Rosenberg",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Sierra M. Barone",
+        "author_inst": "Vanderbilt University"
       },
       {
-        "author_name": "Jeffrey V Ravetch",
-        "author_inst": "Rockefeller University"
+        "author_name": "Alberta G.A. Paul",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Arun P Wiita",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Lyndsey M. Muehling",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Kevin K Leung",
-        "author_inst": "UCSF"
+        "author_name": "Joanne A. Lannigan",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Xin X Zhou",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "William W. Kwok",
+        "author_inst": "Benaroya Research Institute at Virginia Mason"
       },
       {
-        "author_name": "Tom C Hobman",
-        "author_inst": "University of Alberta"
+        "author_name": "Ronald B. Turner",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "Tanja K Kortemme",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Judith A. Woodfolk",
+        "author_inst": "University of Virginia School of Medicine"
       },
       {
-        "author_name": "James A. Wells",
-        "author_inst": "University of California, San Francisco"
+        "author_name": "Jonathan M. Irish",
+        "author_inst": "Vanderbilt University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "bioengineering"
+    "category": "systems biology"
   },
   {
     "rel_doi": "10.1101/2020.07.30.230102",
@@ -1227620,47 +1230397,51 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.07.31.231472",
-    "rel_title": "New Pathways of Mutational Change in SARS-CoV-2 Proteomes Involve Regions of Intrinsic Disorder Important for Virus Replication and Release",
+    "rel_doi": "10.1101/2020.07.31.230730",
+    "rel_title": "Biomechanical Characterization of SARS-CoV-2 Spike RBD and Human ACE2 Protein-Protein Interaction",
     "rel_date": "2020-07-31",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.31.231472",
-    "rel_abs": "The massive worldwide spread of the SARS-CoV-2 virus is fueling the COVID-19 pandemic. Since the first whole-genome sequence was published in January 2020, a growing database of tens of thousands of viral genomes has been constructed. This offers opportunities to study pathways of molecular change in the expanding viral population that can help identify molecular culprits of virulence and virus spread. Here we investigate the genomic accumulation of mutations at various time points of the early pandemic to identify changes in mutationally highly active genomic regions that are occurring worldwide. We used the Wuhan NC_045512.2 sequence as a reference and sampled 15,342 indexed sequences from GISAID, translating them into proteins and grouping them by month of deposition. The per-position amino acid frequencies and Shannon entropies of the coding sequences were calculated for each month, and a map of intrinsic disorder regions and binding sites was generated. The analysis revealed dominant variants, most of which were located in loop regions and on the surface of the proteins. Mutation entropy decreased between March and April of 2020 after steady increases at several sites, including the D614G mutation site of the spike (S) protein that was previously found associated with higher case fatality rates and at sites of the NSP 12 polymerase and the NSP13 helicase proteins. Notable expanding mutations include R203K and G204R of the nucleocapsid (N) protein inter-domain linker region and G251V of the viroporin encoded by ORF3a between March and April. The regions spanning these mutations exhibited significant intrinsic disorder, which was enhanced and decreased by the N-protein and viroporin 3a protein mutations, respectively. These results predict an ongoing mutational shift from the spike and replication complex to other regions, especially to encoded molecules known to represent major {beta}-interferon antagonists. The study provides valuable information for therapeutics and vaccine design, as well as insight into mutation tendencies that could facilitate preventive control.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.31.230730",
+    "rel_abs": "The current COVID-19 pandemic has led to a devastating impact across the world. SARS-CoV-2 (the virus causing COVID-19) is known to use receptor-binding domain (RBD) at viral surface spike (S) protein to interact with the angiotensin-converting enzyme 2 (ACE2) receptor expressed on many human cell types. The RBD-ACE2 interaction is a crucial step to mediate the host cell entry of SARS-CoV-2. Recent studies indicate that the ACE2 interaction with the SARS-CoV-2 S protein has higher affinity than its binding with the structurally identical S protein of SARS-CoV-1, the virus causing the 2002-2004 SARS outbreak. However, the biophysical mechanism behind such binding affinity difference is unclear. This study utilizes a combined single-molecule force spectroscopy and steered molecular dynamics (SMD) simulation approach to quantify the specific interactions between CoV-2 or CoV-1 RBD and ACE2. Depending on the loading rates, the unbinding forces between CoV-2 RBD and ACE2 range from 70 to 110 pN, and are 30-50% higher than those of CoV-1 RBD and ACE2 under similar loading rates. SMD results indicate that CoV-2 RBD interacts with the N-linked glycan on Asn90 of ACE2. This interaction is mostly absent in the CoV-1 RBD-ACE2 complex. During the SMD simulations, the extra RBD-N-glycan interaction contributes to a greater force and prolonged interaction lifetime. The observation is confirmed by our experimental force spectroscopy study. After the removal of N-linked glycans on ACE2, its mechanical binding strength with CoV-2 RBD decreases to a similar level of the CoV-1 RBD-ACE2 interaction. Together, the study uncovers the mechanism behind the difference in ACE2 binding between SARS-CoV-2 and SARS-CoV-1, and could aid in the development of new strategies to block SARS-CoV-2 entry.\n\nSTATEMENT OF SIGNIFICANCEThis study utilizes a combined single-molecule force spectroscopy and steered molecular dynamics simulation approach to quantify the specific interactions between SARS-CoV-2 or SARS-CoV-1 receptor-binding domain and human ACE2. The study reveals the mechanism behind the difference in ACE2 binding between SARS-CoV-2 and SARS-CoV-1, and could aid in the development of new strategies to block SARS-CoV-2 entry.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Tre Tomaszewski",
-        "author_inst": "University of Illinois"
+        "author_name": "Wenpeng Cao",
+        "author_inst": "Lehigh University"
       },
       {
-        "author_name": "Ryan S DeVries",
-        "author_inst": "University of Illinois"
+        "author_name": "Chuqiao Dong",
+        "author_inst": "Lehigh University"
       },
       {
-        "author_name": "Mengyi Dong",
-        "author_inst": "University of Illinois"
+        "author_name": "Seonghan Kim",
+        "author_inst": "Lehigh University"
       },
       {
-        "author_name": "Gitanshu Bhatia",
-        "author_inst": "University of Illinois"
+        "author_name": "Decheng Hou",
+        "author_inst": "Lehigh University"
       },
       {
-        "author_name": "Miles D Norsworthy",
-        "author_inst": "University of Illinois"
+        "author_name": "Wanbo Tai",
+        "author_inst": "New York Blood Center"
       },
       {
-        "author_name": "Xuying Zheng",
-        "author_inst": "University of Illinois"
+        "author_name": "Lanying Du",
+        "author_inst": "New York Blood Center"
       },
       {
-        "author_name": "Gustavo Caetano-Anolles",
-        "author_inst": "University of Illinois"
+        "author_name": "Wonpil Im",
+        "author_inst": "Lehigh University"
+      },
+      {
+        "author_name": "X. Frank Zhang",
+        "author_inst": "Lehigh University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2020.07.31.230870",
@@ -1229294,29 +1232075,41 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.28.20163816",
-    "rel_title": "Multimorbidity patterns among COVID-19 deaths: considerations for a better medical practice",
+    "rel_doi": "10.1101/2020.07.28.20163980",
+    "rel_title": "Stochastic modelling of the effects of human-mobility restriction and viral infection characteristics on the spread of COVID-19",
     "rel_date": "2020-07-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20163816",
-    "rel_abs": "Medical care of individuals diagnosed with severe COVID-19 is complex, especially when patients are older adults with multimorbidity. The objective of this study was to describe patterns of multimorbidity among fatal cases of COVID-19. Data of Colombian confirmed deaths of COVID-19 until June 11, 2020, were included in this analysis (1488 deaths). Relationships between COVID-19, combinations of health conditions and age were explored using locally weighted polynomial regressions. Some multimorbidity patterns increase probability of death among older individuals, whereas other patterns are not age-related, or decreases the probability of death among older people. Consider multimorbidity in the medical management of COVID-19 patients is important to determine the more adequate medical interventions. In addition to the co-occurrence of COVID-19 with diseases of high prevalence in the world, in Colombia there are cases more complex with COVID-19 co-occur with endemic and orphan tropical diseases. In these cases, although its occurrence may be low, clinical management requires adjusting to its complex clinical condition.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20163980",
+    "rel_abs": "After several weeks of \"lockdown\" as the sole answer to the COVID-19 pandemic, many countries are restarting their economic and social activities. However, balancing the re-opening of society against the implementation of non-pharmaceutical measures needed for minimizing interpersonal contacts requires a careful assessment of the risks of infection as a function of the confinement relaxation strategies. Here, we present a stochastic coarse grained model that examines this problem. In our model, people are allowed to move between discrete positions on a one-dimensional grid with viral infection possible when two people are collocated at the same site. Our model features three sets of adjustable parameters, which characterize (i) viral transmission, (ii) viral detection, and (iii) degree of personal mobility, and as such, it is able to provide a qualitative assessment of the potential for second-wave infection outbreaks based on the timing, extent, and pattern of the lockdown relaxation strategy. In line with general expectations, our model predicts that a full lockdown yields the best results, namely, the lowest number of total infections. A less anticipated result was that when personal mobility is increased beyond a critical level, the risk of infection rapidly reaches a constant value, which depends solely on the population density. Furthermore, according to our model, confinement alone is not effective if it is not accompanied by a detection capacity (coupled with quarantine) that surpasses 40% of the patients during their symptomatic phase. The results of our simulation also showed that keeping the virus transmission probability to less than 0.4, which can be achieved in real life by respecting social distancing or wearing masks, is as effective as imposing a mild lockdown. Finally, we note that detection and quarantine of pre-symptomatic patients, even with a probability as low as 0.2, would reduce the final numbers of infections by a factor of ten or more.\n\nAvailabilityhttp://domserv.lab.tuat.ac.jp/COVID19.html (under preparation)",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Julian Alfredo Fernandez-Nino",
-        "author_inst": "Fundacion Universidad del Norte"
+        "author_name": "Shiho Ando",
+        "author_inst": "Tokyo University of Agriculture and Technology"
       },
       {
-        "author_name": "Jhon A Guerra-Gomez",
-        "author_inst": "Northeastern University, Silicon Valle"
+        "author_name": "Yuki Matsuzawa",
+        "author_inst": "Tokyo University of Agriculture and Technology"
       },
       {
-        "author_name": "Alvaro Javier Idrovo-Velandia",
-        "author_inst": "Universidad Industrial de Santander"
+        "author_name": "Hiromichi Tsurui",
+        "author_inst": "Juntendo University"
+      },
+      {
+        "author_name": "Tetsuya Mizutani",
+        "author_inst": "Tokyo Noko Daigaku"
+      },
+      {
+        "author_name": "Damien Hall",
+        "author_inst": "Nagoya Institute of Technology"
+      },
+      {
+        "author_name": "Yutaka Kuroda",
+        "author_inst": "Tokyo University of Agriculture and Technology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1231012,43 +1233805,27 @@
     "category": "scientific communication and education"
   },
   {
-    "rel_doi": "10.1101/2020.07.17.20156463",
-    "rel_title": "SARS-CoV-2 Infection and Stroke: Coincident or Causal?",
+    "rel_doi": "10.1101/2020.07.23.20160887",
+    "rel_title": "Divide in Vaccine Belief in COVID-19 Conversations: Implications for Immunization Plans",
     "rel_date": "2020-07-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156463",
-    "rel_abs": "Neurological manifestations of SARS-CoV-2 infection described in isolated case reports and single institutions do not accurately reflect the clinical spectrum of disease across all geographies in a global pandemic. Data collected during peak of the Covid-19 pandemic from stroke centers in five states reveal few similarities to what has recently been published. Given the diversity in phenotype, we caution policymakers and health care providers when considering cerebrovascular complications from SARS-CoV-2 infection.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20160887",
+    "rel_abs": "The development of a viable COVID-19 vaccine is a work in progress, but the success of the immunization campaign will depend upon public acceptance. In this paper, we classify Twitter users in COVID-19 discussion into vaccine refusers (anti-vaxxers) and vaccine adherers (vaxxers) communities. We study the divide between anti-vaxxers and vaxxers in the context of whom they follow. More specifically, we look at followership of 1) the U.S. Congress members, 2) four major religions (Christianity, Hinduism, Judaism and Islam), 3) accounts related to the healthcare community, and 4) news media accounts. Our results indicate that there is a partisan divide between vaxxers and anti-vaxxers. We find a religious community with a higher than expected fraction of anti-vaxxers. Further, we find that the variance of vaccine belief within the news media accounts operated by Russian and Iranian governments is higher compared to news media accounts operated by other governments. Finally, we provide messaging and policy implications to inform the COVID-19 vaccine and future vaccination plans.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Melanie Walker",
-        "author_inst": "University of Washington School of Medicine"
-      },
-      {
-        "author_name": "Christopher C. Young",
-        "author_inst": "University of Washington School of Medicine"
-      },
-      {
-        "author_name": "Malveeka Sharma",
-        "author_inst": "University of Washington School of Medicine"
-      },
-      {
-        "author_name": "Michael R Levitt",
-        "author_inst": "University of Washington School of Medicine"
-      },
-      {
-        "author_name": "David L Tirschwell",
-        "author_inst": "University of Washington School of Medicine"
+        "author_name": "Aman Tyagi",
+        "author_inst": "Carnegie Mellon University"
       },
       {
-        "author_name": "- WWAMI Stroke Investigators",
-        "author_inst": ""
+        "author_name": "Kathleen M. Carley",
+        "author_inst": "Carnegie Mellon University"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "neurology"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2020.07.23.20160796",
@@ -1232578,63 +1235355,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.27.20149757",
-    "rel_title": "Children with COVID-19 like symptoms in Italian Pediatric Surgeries: the dark side of the coin",
+    "rel_doi": "10.1101/2020.07.27.20162057",
+    "rel_title": "Predicting PPE use, post-traumatic stress, and physical symptoms during the early weeks of COVID-19 lockdowns in the USA",
     "rel_date": "2020-07-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20149757",
-    "rel_abs": "BackgroundSymptoms of SARS-CoV-2 infection in children are nonspecific and shared with other common acute viral illnesses (fever, respiratory or gastrointestinal symptoms, and cutaneous signs), thus making clinical differential diagnosis tricky. In Italy, first line management of pediatric care is handed over to Primary Care Pediatricians (PCPs), who were not allowed to directly perform diagnostic tests during the recent COVID-19 outbreak. Without a confirmatory diagnosis, PCPs could only collect information on \"COVID-19 like symptoms\" rather than identify typical COVID-19 symptoms.\n\nAimTo evaluate the prevalence of COVID-19 like symptoms in outpatient children, during Italian lockdown. To provide PCPs a risk score to be used in clinical practice during the differential diagnosis process.\n\nMethodsA survey was submitted to 50 PCPs (assisting 47,500 children) from 7 different Italian regions between the 4th of March and the 23rd of May 2020 (total and partial lockdown period). COVID-19 like symptoms in the assisted children were recorded, as well as presence of confirmed/suspected cases in childrens families, which was taken as proxy of COVID-19. Multivariable logistic regression was accomplished to estimate the risk of having suspected/confirmed cases in families, considering symptoms as potential determinants.\n\nResults2,300 children (4.8% of overall survey population) fell ill with COVID-19 like symptoms, 3.1% and 1.7% during total and partial lockdown period respectively. The concurrent presence of fatigue, cough, and diarrhea in children, in absence of sore throat/earache and abnormal skin signs, represents the maximum risk level of having a suspected/confirmed case of COVID-19 at home.\n\nConclusionsThe percentage of children presenting COVID-19 like symptoms at home has been remarkable also during the total lockdown period. The present study identified a pattern of symptoms which could help, in a cost-effective perspective, PCPs in daily clinical practice to define priorities in addressing children to the proper diagnostic procedure.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20162057",
+    "rel_abs": "The COVID-19 pandemic combined with inconsistent governmental and public health recommendations, media communications emphasizing threat, and widespread lockdowns created a complex psychological environment for Americans. In this study, 450 MTurk workers completed measures of (a) risk for COVID-19, (b) perceived vulnerability to disease, (c) intolerance of uncertainty, (d) mindfulness, (e) COVID-19 preventive health behaviors, (f) post-Trauma symptoms, and (g) stress related physical symptoms. The surveys were completed between April 9, 2020 and April 18, 2020 which is a period that corresponded to the first 2-3 weeks of lockdown for most participants.\n\nA substantial number of participants reported a reduction employment status and 69% were in self-isolation. The participants reported a high degree of perceived vulnerability with 68% indicating they felt there was a 50/50 chance or greater they would contract COVID-19. Mask wearing was variable: 16% \"not at all,\" 20% \"some of the time,\" 42% \"a good part of the time,\" and 26% \"most of the time.\" Using clinical cutoff on the post-trauma scale, 70% of the sample would be considered to have symptoms consistent with PTSD. The mean level of physical symptoms was significantly (p < .001) and substantially higher (d = 1.46) than norms.\n\nPPE use was positively associated with level of education and mindfulness nonreactivity and negatively associated with age, having a current medical condition, and mindfulness nonjudgment. Post trauma and physical health symptoms were strongly predicted by susceptibility variables and intolerance of uncertainty.\n\nHighlightsO_LICOVID-19 created a complex psychological environment for Americans due to threat exposure combined with contradictory communications from government and media.\nC_LIO_LIIn a survey of 450 Americans, 68% reported that there was a 50/50 chance of greater they would contract COVID-19 and 70% of participants reported symptoms that met criteria for PTSD.\nC_LIO_LIMask wearing was variable with only 26% reporting use \"most of the time.\"\nC_LIO_LIParticipants who reported: older age, having one or mode medical conditions, less educational attainment, and less judgmental attitudes about their own thinking reported lower PPE use.\nC_LIO_LIIntolerance of uncertainty and perceived susceptibility were associated with higher PTSD symptoms.\nC_LIO_LIMindfulness awareness and being judgmental attitudes about thinking were associated with lower PTSD symptoms.\nC_LI",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Gianfranco Trapani",
-        "author_inst": "Alfred Nobel's Friends International Association Study Center and Primary Care Pediatrician, Sanremo (IM), Italy"
-      },
-      {
-        "author_name": "Vassilios Fanos",
-        "author_inst": "Neonatal Intensive Care Unit, Department of Surgical Sciences, University of Cagliari, Cagliari, Italy"
-      },
-      {
-        "author_name": "Enrico Bertino",
-        "author_inst": "Neonatal Care Unit, Department of Public Health and Pediatric Sciences, University of Turin, Turin, Italy"
-      },
-      {
-        "author_name": "Giulia Maiocco",
-        "author_inst": "Neonatal Care Unit, Department of Public Health and Pediatric Sciences, University of Turin, Turin, Italy"
-      },
-      {
-        "author_name": "Osama Al Jamal",
-        "author_inst": "Alfred Nobel's Friends International Association Study Center and Primary Care Pediatrician, Cagliari, Italy"
+        "author_name": "William H OBrien",
+        "author_inst": "Bowling Green State University"
       },
       {
-        "author_name": "Michele Fiore",
-        "author_inst": "Primary Care Pediatrician, Genoa, Italy"
+        "author_name": "Shan Wang",
+        "author_inst": "Duke Kunshan University"
       },
       {
-        "author_name": "VIncenzo Bembo",
-        "author_inst": "Primary Care Pediatrician, Frosinone, Italy"
+        "author_name": "Aniko Viktoria Varga",
+        "author_inst": "Bowling Green State University"
       },
       {
-        "author_name": "Domenico Careddu",
-        "author_inst": "Alfred Nobel's Friends International Association Study Center and Primary Care Pediatrician, Novara, Italy"
+        "author_name": "Huanzhen Xu",
+        "author_inst": "Bowling Green State University"
       },
       {
-        "author_name": "Lando Barberio",
-        "author_inst": "Primary Care Pediatrician, Taggia (IM), Italy"
+        "author_name": "Tracy E Sims",
+        "author_inst": "Bowling Green State University"
       },
       {
-        "author_name": "Luisella Zanino",
-        "author_inst": "Alfred Nobel's Friends International Association Study Center and Primary Care Pediatrician, Turin, Italy"
+        "author_name": "Kristin A Horan",
+        "author_inst": "University of Central Florida"
       },
       {
-        "author_name": "Giuseppe Verlato",
-        "author_inst": "Unit of Epidemiology and Medical Statistics, Department of Diagnostics & Public Health, University of Verona, Verona, Italy"
+        "author_name": "Chung Xiann Lim",
+        "author_inst": "Bowling Green State University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pediatrics"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.07.27.20156836",
@@ -1234636,71 +1237397,31 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.28.225581",
-    "rel_title": "Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis",
+    "rel_doi": "10.1101/2020.07.29.227389",
+    "rel_title": "On the molecular mechanism of SARS-CoV-2 retention in the upper respiratory tract",
     "rel_date": "2020-07-29",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.28.225581",
-    "rel_abs": "The novel betacoronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after initially emerging in Wuhan, China. Here we applied a novel, comprehensive bioinformatic strategy to public RNA sequencing and viral genome sequencing data, to better understand how SARS-CoV-2 interacts with human cells. To our knowledge, this is the first meta-analysis to predict host factors that play a specific role in SARS-CoV-2 pathogenesis, distinct from other respiratory viruses. We identified differentially expressed genes, isoforms and transposable element families specifically altered in SARS-CoV-2 infected cells. Well-known immunoregulators including CSF2, IL-32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were overexpressed. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as hnRNPA1, PABPC1 and eIF4b, which may play important roles in the viral life cycle. We also detected four viral sequence variants in the spike, polymerase, and nonstructural proteins that correlate with severity of COVID-19. The host factors we identified likely represent important mechanisms in the disease profile of this pathogen, and could be targeted by prophylactics and/or therapeutics against SARS-CoV-2.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC=\"FIGDIR/small/225581v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (26K):\norg.highwire.dtl.DTLVardef@15ca5a6org.highwire.dtl.DTLVardef@17f455forg.highwire.dtl.DTLVardef@a39f50org.highwire.dtl.DTLVardef@306ec1_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
-    "rel_num_authors": 13,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.29.227389",
+    "rel_abs": "Cell surface receptor engagement is a critical aspect of viral infection. At low pH, binding of SARS-CoV and its ACE2 receptor has a tight interaction that catalyzes the fusion of the spike and endosomal membranes followed by genome release. Largely overlooked has been the role of neutral pH in the respiratory tract, where we find that SARS-CoV stabilizes a transition state that enhances the off-rate from its receptor. An alternative pH-switch is found in CoV-2-like coronaviruses of tropical pangolins, but with a reversed phenotype where the tight interaction with ACE2 is at neutral pH. We show that a single point mutation in pangolin-CoV, unique to CoV-2, that deletes the last His residue in their receptor binding domain perpetuates this tight interaction independent of pH. This tight bond, not present in previous respiratory syndromes, implies that CoV-2 stays bound to the highly expressed ACE2 receptors in the nasal cavity about 100 times longer than CoV. This finding supports the unfamiliar pathology of CoV-2, observed virus retention in upper respiratory tract1, longer incubation times and extended periods of shedding. Implications to combat pandemics that, like SARS-CoV-2, export evolutionarily successful strains via higher transmission rates due to retention in nasal epithelium and their evolutionary origin are discussed.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Mariana G. Ferrarini",
-        "author_inst": "University of Lyon, INSA-Lyon, INRAE, BF2I"
-      },
-      {
-        "author_name": "Avantika Lal",
-        "author_inst": "NVIDIA"
-      },
-      {
-        "author_name": "Rita Rebollo",
-        "author_inst": "University of Lyon, INSA-Lyon, INRAE, BF2I"
-      },
-      {
-        "author_name": "Andreas Gruber",
-        "author_inst": "Oxford Big Data Institute, Nuffield Department of Medicine, University of Oxford"
-      },
-      {
-        "author_name": "Andrea Guarracino",
-        "author_inst": "Centre for Molecular Bioinformatics, Department of Biology, University Of Rome Tor Vergata"
-      },
-      {
-        "author_name": "Itziar Martinez Gonzalez",
-        "author_inst": "Netherlands\tAmsterdam UMC"
-      },
-      {
-        "author_name": "Taylor Floyd",
-        "author_inst": "Center for Neurogenetics, Weill Cornell Medicine, Cornell University"
-      },
-      {
-        "author_name": "Daniel Siqueira de Oliveira",
-        "author_inst": "Laboratoire de Biometrie et Biologie Evolutive, Universite de Lyon, CNRS"
-      },
-      {
-        "author_name": "Justin Shanklin",
-        "author_inst": "Brigham Young University"
-      },
-      {
-        "author_name": "Ethan Beausoleil",
-        "author_inst": "Brigham Young University"
-      },
-      {
-        "author_name": "Taneli Pusa",
-        "author_inst": "Luxembourg Centre for Systems Biomedicine"
+        "author_name": "Kristina A Paris",
+        "author_inst": "University of Pittsburgh"
       },
       {
-        "author_name": "Brett Pickett",
-        "author_inst": "Brigham Young University"
+        "author_name": "Ulises Santiago",
+        "author_inst": "University of Pittsburgh"
       },
       {
-        "author_name": "Vanessa Aguiar-Pulido",
-        "author_inst": "Center for Neurogenetics, Weill Cornell Medicine, Cornell University"
+        "author_name": "Carlos J. Camacho",
+        "author_inst": "University of Pittsburgh"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2020.07.29.226217",
@@ -1236258,27 +1238979,47 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.28.224386",
-    "rel_title": "Comparative Analysis of Human Coronaviruses Focusing on Nucleotide Variability and Synonymous Codon Usage Pattern",
+    "rel_doi": "10.1101/2020.07.22.20154542",
+    "rel_title": "Prophylaxis with tetracyclines in ARDS: Potential therapy for COVID-19-induced ARDS?",
     "rel_date": "2020-07-28",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.28.224386",
-    "rel_abs": "Prevailing pandemic across the world due to SARSCoV-2 drawing great attention towards discovering its evolutionary origin. We perform an exploratory study to understand the variability of the whole coding region of possible proximal evolutionary neighbours of SARSCoV-2. We consider seven (07) human coronavirus strains from six different species as a candidate for our study.\n\nFirst, we observe a good variability of nucleotides across candidate strains. We did not find a significant variation of GC content across the strains for codon position first and second. However, we interestingly see huge variability of GC-content in codon position 3rd (GC3), and pairwise mean GC-content (SARSCoV, MERSCoV), and (SARSCoV-2, hCoV229E) are quite closer. While observing the relative abundance of dinucleotide feature, we find a shared typical genetic pattern, i.e., high usage of GC and CT nucleotide pair at the first two positions (P12) of codons and the last two positions (P23) of codons, respectively. We also observe a low abundance of CG pair that might help in their evolution bio-process. Secondly, Considering RSCU score, we find a substantial similarity for mild class coronaviruses, i.e., hCoVOC43, hCoVHKU1, and hCoVNL63 based on their codon hit with high RSCU value ([&ge;] 1.5), and minim number of codons hit (count-9) is observed for MERSCoV. We see seven codons ATT, ACT, TCT, CCT, GTT, GCT and GGT with high RSCU value, which are common in all seven strains. These codons are mostly from Aliphatic and Hydroxyl amino acid group. A phylogenetic tree built using RSCU feature reveals proximity among hCoVOC43 and hCoV229E (mild). Thirdly, we perform linear regression analysis among GC content in different codon position and ENC value. We observe a strong correlation (significant p-value) between GC2 and GC3 for SARSCoV-2, hCoV229E and hCoVNL63, and between GC1 and GC3 for hCoV229E, hCoVNL63, SARSCoV. We believe that our findings will help in understanding the mechanism of human coronavirus.",
-    "rel_num_authors": 2,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20154542",
+    "rel_abs": "There is an immediate need for therapies related to coronavirus disease 2019 (COVID-19), especially candidate drugs that possess anti-inflammatory and immunomodulatory effects with low toxicity profiles. We hypothesized the application of pleiotropic tetracyclines as potential therapeutic candidates. Here, we present a retrospective multi-institutional cohort study evaluating ventilatory status in patients who had taken a tetracycline antibiotic within a year prior to diagnosis of acute respiratory distress syndrome (ARDS). The primary outcomes were the need for mechanical ventilation and duration of mechanical ventilation. The secondary outcome was the duration of intensive care unit (ICU) stay. Data was evaluated using logistic regression and treatment effects regression models. Minocycline or doxycycline treatment within a year prior to ARDS diagnosis was associated with a 75% reduced likelihood for mechanical ventilation during hospital stay. Furthermore, tetracycline antibiotic therapy corresponded to significant reductions in duration of mechanical ventilation and ICU stay in ARDS patients. These data suggest tetracyclines may provide prophylactic benefit in reducing ventilatory support for ARDS patients and support further evaluation in a randomized prospective trial.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Jayanta Das",
-        "author_inst": "Johns Hopkins University, MD-21205, USA"
+        "author_name": "James D Byrne",
+        "author_inst": "Brigham and Women's Hospital"
       },
       {
-        "author_name": "Swarup Roy",
-        "author_inst": "Sikkim University"
+        "author_name": "Rameen Shakur",
+        "author_inst": "Massachusetts Institute of Technology"
+      },
+      {
+        "author_name": "Joy Collins",
+        "author_inst": "Brigham and Women's Hospital"
+      },
+      {
+        "author_name": "Sarah L Becker",
+        "author_inst": "Brigham and Women's Hospital"
+      },
+      {
+        "author_name": "Cameron C Young",
+        "author_inst": "Brigham and Women's Hospital"
+      },
+      {
+        "author_name": "Hannah Boyce",
+        "author_inst": "Brigham and Women's Hospital"
+      },
+      {
+        "author_name": "Carlo Traverso",
+        "author_inst": "Massachusetts Institute of Technology"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "new results",
-    "category": "genomics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "intensive care and critical care medicine"
   },
   {
     "rel_doi": "10.1101/2020.07.28.225078",
@@ -1238036,101 +1240777,49 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.07.27.223495",
-    "rel_title": "Oligonucleotide capture sequencing of the SARS-CoV-2 genome and subgenomic fragments from COVID-19 individuals",
+    "rel_doi": "10.1101/2020.07.27.222836",
+    "rel_title": "Targeting the endolysosomal host-SARS-CoV-2 interface by the clinically licensed antidepressant fluoxetine",
     "rel_date": "2020-07-27",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.27.223495",
-    "rel_abs": "The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity and provided evidence of expression of ORF10. Heterogeneous allelic frequencies along the 20kb ORF1ab gene suggested the presence of a defective interfering viral RNA species subpopulation in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.",
-    "rel_num_authors": 21,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.27.222836",
+    "rel_abs": "The Corona Virus Disease 2019 (COVID-19) pandemic caused by the Severe Acute Respiratory Syndrome Related Coronavirus 2 (SARS-CoV-2) is a global health emergency. As only very limited therapeutic options are clinically available, there is an urgent need for the rapid development of safe, effective, and globally available pharmaceuticals that inhibit SARS-CoV-2 entry and ameliorate COVID-19. In this study, we explored the use of small compounds acting on the homeostasis of the endolysosomal host-pathogen interface, to fight SARS-CoV-2 infection. We find that fluoxetine, a widely used antidepressant and a functional inhibitor of acid sphingomyelinase (FIASMA), efficiently inhibited the entry and propagation of SARS-CoV-2 in the cell culture model without cytotoxic effects and also exerted potent antiviral activity against two currently circulating influenza A virus subtypes, an effect which was also observed upon treatment with the FIASMAs amiodarone and imipramine. Mechanistically, fluoxetine induced both impaired endolysosomal acidification and the accumulation of cholesterol within the endosomes. As the FIASMA group consists of a large number of small compounds that are well-tolerated and widely used for a broad range of clinical applications, exploring these licensed pharmaceuticals may offer a variety of promising antivirals for host-directed therapy to counteract enveloped viruses, including SARS-CoV-2 and COVID 19.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Harsha Vardhan Doddapaneni",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Sara Javornik Cregeen",
-        "author_inst": "Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Richard Sucgang",
-        "author_inst": "Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Qingchang Meng",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Xiang Qing",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Vasanthi Avadhanula",
-        "author_inst": "Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Hsu Chao",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Vipin Menon",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Erin Nicholson",
-        "author_inst": "Department of Molecular Virology and Microbiology, and Pediatrics , Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "David Henke",
-        "author_inst": "Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Felipe-Andres Piedra",
-        "author_inst": "Department of Molecular Virology and Microbiology , Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Anubama Rajan",
-        "author_inst": "Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Zeineen Momin",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
-      },
-      {
-        "author_name": "Kavya Kottapalli",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Sebastian Schloer",
+        "author_inst": "University of Muenster, Center for Molecular Biology of Inflammation"
       },
       {
-        "author_name": "Kristi L. Hoffman",
-        "author_inst": "Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Linda Brunotte",
+        "author_inst": "Universtity of Muenster, Center for Molecular Biology of Inflammation"
       },
       {
-        "author_name": "Fritz J Sedlazeck",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Jonas Goretzko",
+        "author_inst": "University of Muenster, Center for Molecular Biology of Inflammation"
       },
       {
-        "author_name": "Ginger Metcalf",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Angeles Mecate-Zambrano",
+        "author_inst": "University of Muenster, Center for Molecular Biology of Inflammation"
       },
       {
-        "author_name": "Pedro A Piedra",
-        "author_inst": "Department of Molecular Virology and Microbiology and Pediatrics , Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Nadja Korthals",
+        "author_inst": "University of Muenster, Center for Molecular Biology of Inflammation"
       },
       {
-        "author_name": "Donna M Muzny",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Volker Gerke",
+        "author_inst": "University of Muenster, Center for Molecular Biology of Inflammation"
       },
       {
-        "author_name": "Joseph F Petrosino",
-        "author_inst": "Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Stephan Ludwig",
+        "author_inst": "University of Muenster, Center for Molecular Biology of Inflammation"
       },
       {
-        "author_name": "Richard A Gibbs",
-        "author_inst": "Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA, 77030"
+        "author_name": "Ursula Rescher",
+        "author_inst": "University of Muenster Centre for Molecular Biology of Inflammation"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
     "category": "microbiology"
   },
@@ -1239826,63 +1242515,51 @@
     "category": "health systems and quality improvement"
   },
   {
-    "rel_doi": "10.1101/2020.07.21.20156711",
-    "rel_title": "Healthcare Workers' Mental Health and Wellbeing During the COVID-19 Pandemic in the UK: Contrasting Guidelines with Experiences in Practice",
+    "rel_doi": "10.1101/2020.07.20.20157149",
+    "rel_title": "Association of contact to small children with mild course of COVID-19",
     "rel_date": "2020-07-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20156711",
-    "rel_abs": "BackgroundSubstantial evidence has highlighted the importance of considering healthcare workers (HCW) mental health during the COVID-19 pandemic, and several organisations have issued guidelines with recommendations. However, the definition of wellbeing and the evidence-base behind such guidelines remains unclear.\n\nObjectivesAssessing the applicability of wellbeing guidelines in practice; identifying unaddressed HCWs needs; and providing recommendations for supporting frontline staff during the current and future pandemics.\n\nMethods and DesignThis paper discusses the findings of a qualitative study based on interviews with frontline healthcare staff in the UK and examines them in relation to a rapid review of wellbeing guidelines developed in response to the COVID-19 pandemic.\n\nResults14 guidelines were included in the rapid review and 33 interviews with HCWs were conducted in the qualitative study. As a whole, the guidelines placed greater emphasis on wellbeing at an individual level, while HCWs placed greater emphasis on structural conditions at work, such as understaffing and the invaluable support of the community. This in turn had implications for the focus of wellbeing intervention strategies; staff reported an increased availability of formal mental health support, however, understaffing or clashing schedules prevented them from participating in these activities.\n\nConclusionHCWs expressed wellbeing needs which align with social-ecological conceptualisations of wellbeing related to quality of life. This approach to wellbeing has been highlighted in literature about HCWs support in previous health emergencies, yet it has not been monitored during this pandemic. Wellbeing guidelines should explore staffs needs and contextual characteristics affecting the implementation of recommendations.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20157149",
+    "rel_abs": "It is known that severe COVID-19 cases in small children are rare. If a childhood-related infection would be protective against severe course of COVID-19, it would be expected that adults with intensive and regular contact to small children also may have a mild course of COVID-19 more frequently. To test this hypothesis, a survey among 4,010 recovered COVID-19 patients was conducted in Germany. 1,186 complete answers were collected. 6.9% of these patients reported frequent and regular job-related contact to children below 10 years of age and 23.2% had own small children, which is higher than expected. In the relatively small subgroup with intensive care treatment (n=19), patients without contact to small children were overrepresented. These findings are not well explained by age, gender or BMI distribution of those patients and should be validated in other settings.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Norha Vera San Juan",
-        "author_inst": "Insitute of Psychiatry, Psychology and Neuroscience. King's College London"
-      },
-      {
-        "author_name": "David Aceituno",
-        "author_inst": "Institute of Psychiatry, Psychology and Neuroscience. King's College London"
-      },
-      {
-        "author_name": "Nehla Djellouli",
-        "author_inst": "Institute for Global Health. University College London"
+        "author_name": "Martin Dugas",
+        "author_inst": "University of Muenster, Germany"
       },
       {
-        "author_name": "Kirsi Sumray",
-        "author_inst": "Institute of Epidemiology and Health Care. University College London"
+        "author_name": "Inga Marie Schrempf",
+        "author_inst": "University Hospital Muenster, Germany"
       },
       {
-        "author_name": "Nina Regenold",
-        "author_inst": "Institute of Epidemiology and Health Care. University College London"
+        "author_name": "Kevin Ochs",
+        "author_inst": "University Hospital Muenster, Germany"
       },
       {
-        "author_name": "Aron Syversen",
-        "author_inst": "Institute of Epidemiology and Health Care. University College London"
+        "author_name": "Christopher Froemmel",
+        "author_inst": "University Hospital Muenster, Germany"
       },
       {
-        "author_name": "Sophie Mulcahy Symmons",
-        "author_inst": "Institute of Epidemiology and Health Care. University College London"
-      },
-      {
-        "author_name": "Anna Dowrick",
-        "author_inst": "Institute of Population Health and Science. Queen Mary University of London"
+        "author_name": "Leonard Greulich",
+        "author_inst": "University of Muenster, Germany"
       },
       {
-        "author_name": "Lucy Mitchinson",
-        "author_inst": "Marie Cuerie Pallatieve Care Research Department. University College London"
+        "author_name": "Philipp Neuhaus",
+        "author_inst": "University of Muenster, Germany"
       },
       {
-        "author_name": "Georgina Singleton",
-        "author_inst": "Health Services Research Centre. University College London"
+        "author_name": "Phil-Robin Tepasse",
+        "author_inst": "University Hospital Muenster, Germany"
       },
       {
-        "author_name": "Cecilia Vindrola-Padros",
-        "author_inst": "Rapid Research, Evaluation and Appraisal Lab. University College London"
+        "author_name": "Hartmut HJ Schmidt",
+        "author_inst": "University Hospital Muenster, Germany"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health systems and quality improvement"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.07.20.20156398",
@@ -1242068,27 +1244745,31 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2020.07.18.20156828",
-    "rel_title": "Local public health officials and COVID-19: Evidence from China",
+    "rel_doi": "10.1101/2020.07.23.20158980",
+    "rel_title": "Prevalence of mask wearing in northern Vermont in response to SARS-CoV-2",
     "rel_date": "2020-07-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.18.20156828",
-    "rel_abs": "Local public health authorities are at the forefront of fighting COVID-19. They monitor its spread in the local population and advise the local government on whether to close schools and businesses. Examining their role in battling COVID-19 will inform the public how best to prepare for a public health emergency. This study examined whether more competent local public health officials in China are more effective in fighting COVID-19, where competence was measured by the public health officials professional background. Only 38% of the heads of the public health departments of Chinese cities have a medical background. Cities with medical professionals as the head of public health departments had lower infection rates and death rates from COVID-19. The results were significant only at the start of the outbreak. Our results suggest that we should staff local public health authorities with competent professionals to better combat a pandemic.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20158980",
+    "rel_abs": "ObjectivesInformation on prevalence of face mask usage in response to SARS-CoV-2 is required to both model disease spread and to improve compliance with mask usage. We sought to (1) estimate the prevalence of mask usage in northern Vermont and to (2) assess the effect of age and sex on mask usage.\n\nMethodsWe monitored the entrances to businesses and visually assessed individuals age, sex, and mask usage from a distance. We collected 1004 observations from 16 May through 30 May 2020 as businesses began to reopen following an extended state-wide lockdown. We analyzed these data using Bayesian random effects logistic regression.\n\nResults75.5% of individuals used a mask with significant effects of age and sex on mask usage. Females were more likely than males to wear masks (83.8%, n=488 vs. 67.6%, n=516); the odds of mask usage in males were 53% of those for females. Elders were most likely to wear a mask (91.4%, n=209) followed by young adults (74.8%, n=246), middle-aged adults (70.7%, n=519) and children (53.3%, n=30). The odds of an elder wearing a mask were 16.7 times that of a child, while the odds for young adults and middle-aged adults were [~]3 times greater than for a child. Highest mask usage was in elder females (96.3%, n=109) and lowest mask usage was in male children (43.8%, n=16).\n\nConclusionsWe found high prevalence of mask usage overall, but also large differences in mask usage with age and sex. Females and elders had the highest use of face masks.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "John Jiang",
-        "author_inst": "Michigan State University"
+        "author_name": "Brian Beckage",
+        "author_inst": "University of Vermont"
+      },
+      {
+        "author_name": "Thomas E Buckley",
+        "author_inst": "Colchester High School"
       },
       {
-        "author_name": "Maobin Wang",
-        "author_inst": "The University of International Business and Economics"
+        "author_name": "Maegan E Beckage",
+        "author_inst": "Essex High School"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health policy"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.07.21.20159038",
@@ -1242183,7 +1244864,7 @@
     "rel_date": "2020-07-25",
     "rel_site": "medRxiv",
     "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20155218",
-    "rel_abs": "ISARIC (International Severe Acute Respiratory and emerging Infections Consortium) partnerships and outbreak preparedness initiatives enabled the rapid launch of standardised clinical data collection on COVID-19 in Jan 2020. Extensive global participation has resulted in a large, standardised collection of comprehensive clinical data from hundreds of sites across dozens of countries. Data are analysed regularly and reported publicly to inform patient care and public health response. This report, our 18th and final report, is a part of a series published over 3 years. Data have been entered for 945,317 individuals from 1807 partner institutions and networks across 76 countries. The comprehensive analyses detailed in this report includes hospitalised individuals of all ages for whom data collection occurred between 30 January 2020 and up to and including 10 January 2023, AND who have laboratory-confirmed SARS-COV-2 infection or clinically diagnosed COVID-19. For the 845,291 cases who meet eligibility criteria for this report, selected findings include: o Median age of 57 years, with an approximately equal (50/50) male:female sex distribution o 29% of the cohort are at least 70 years of age, whereas 6% are 0-19 years of age o The most common symptom combination in this hospitalised cohort is shortness of breath, cough, and history of fever, which has remained constant over time o The five most common symptoms at admission were shortness of breath, cough, history of fever, fatigue/malaise, and altered consciousness/confusion, which is unchanged from the previous reports o Age-associated differences in symptoms are evident, including the frequency of altered consciousness increasing with age, and fever, respiratory and constitutional symptoms being present mostly in those 40 years and above o 15% of patients with relevant data available (845,291) were admitted at some point during their illness into an intensive care unit (ICU), which has decreased from 19% during the 3 years of ISARIC reporting o Antibiotic agents were used in 37% of patients for whom relevant data are available (802,241), a significant reduction from our previous reports (80%) which reflects a shifting proportion of data contributed by different institutions; in ICU/HDU admitted patients with data available (64,669), 90% received antibiotics o Use of corticosteroids was reported in 25% of all patients for whom data were available (809,043); in ICU/HDU admitted patients with data available (64,713), 71% received corticosteroids o Outcomes are known for 762,728 patients and the overall estimated case fatality ratio (CFR) is 22% (95%CI 21.9-22), rising to 36% (95%CI 35.6-36.1) for patients who were admitted to ICU/HDU, demonstrating worse outcomes in those with the most severe disease We thank all the data contributors for their ongoing support.",
+    "rel_abs": "ISARIC (International Severe Acute Respiratory and emerging Infections Consortium) partnerships and outbreak preparedness initiatives enabled the rapid launch of standardised clinical data collection on COVID-19 in Jan 2020. Extensive global participation has resulted in a large, standardised collection of comprehensive clinical data from hundreds of sites across dozens of countries. Data are analysed regularly and reported publicly to inform patient care and public health response. This report, our 18th and final report, is a part of a series published over 3 years. Data have been entered for 945,317 individuals from 1807 partner institutions and networks across 76 countries.\n\nThe comprehensive analyses detailed in this report includes hospitalised individuals of all ages for whom data collection occurred between 30 January 2020 and up to and including 10 January 2023, AND who have laboratory-confirmed SARS-COV-2 infection or clinically diagnosed COVID-19.\n\nFor the 845,291 cases who meet eligibility criteria for this report, selected findings include:\n\nO_LIMedian age of 57 years, with an approximately equal (50/50) male:female sex distribution\nC_LIO_LI29% of the cohort are at least 70 years of age, whereas 6% are 0-19 years of age\nC_LIO_LIThe most common symptom combination in this hospitalised cohort is shortness of breath, cough, and history of fever, which has remained constant over time\nC_LIO_LIThe five most common symptoms at admission were shortness of breath, cough, history of fever, fatigue/malaise, and altered consciousness/confusion, which is unchanged from the previous reports\nC_LIO_LIAge-associated differences in symptoms are evident, including the frequency of altered consciousness increasing with age, and fever, respiratory and constitutional symptoms being present mostly in those 40 years and above\nC_LIO_LI15% of patients with relevant data available (845,291) were admitted at some point during their illness into an intensive care unit (ICU), which has decreased from 19% during the 3 years of ISARIC reporting\nC_LIO_LIAntibiotic agents were used in 37% of patients for whom relevant data are available (802,241), a significant reduction from our previous reports (80%) which reflects a shifting proportion of data contributed by different institutions; in ICU/HDU admitted patients with data available (64,669), 90% received antibiotics\nC_LIO_LIUse of corticosteroids was reported in 25% of all patients for whom data were available (809,043); in ICU/HDU admitted patients with data available (64,713), 71% received corticosteroids\nC_LIO_LIOutcomes are known for 762,728 patients and the overall estimated case fatality ratio (CFR) is 22% (95%CI 21.9-22), rising to 36% (95%CI 35.6-36.1) for patients who were admitted to ICU/HDU, demonstrating worse outcomes in those with the most severe disease\nC_LI\n\nTo access previous versions of ISARIC COVID-19 Clinical Data Report please use the link below: https://isaric.org/research/covid-19-clinical-research-resources/evidence-reports/",
     "rel_num_authors": 54,
     "rel_authors": [
       {
@@ -1243714,31 +1246395,135 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.22.20159830",
-    "rel_title": "Clustering, diffusion and evolution of COVID19 infections during lock-down",
+    "rel_doi": "10.1101/2020.07.25.217158",
+    "rel_title": "High neutralizing potency of swine glyco-humanized polyclonal antibodies against SARS-CoV-2",
     "rel_date": "2020-07-25",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20159830",
-    "rel_abs": "Epidemics such as the spreading of the SARS-CoV-2 virus are highly non linear, and therefore difficult to predict. In the present pandemic as time evolves, it appears more and more clearly that a clustered dynamics is a key element of description. This means that the disease rapidly evolves within spatially localized networks, that diffuse and eventually create new clusters. We improve upon the simplest possible compartmental model, the SIR model, by adding an additional compartment associated with the clustered individuals. The so-obtained SBIR model compares satisfactorily with results on the pandemic propagation in a number of European countries, during and immediately after lock-down. Especially, the decay exponent of the number of new cases after the first peak of the epidemic, is observed to be very similar for countries in which a strict lock-down was applied. We derive an analytical expression for the value of this exponent.",
-    "rel_num_authors": 3,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.25.217158",
+    "rel_abs": "Perfusion of convalescent plasma (CP) has demonstrated a potential to improve the pneumonia induced by SARS-CoV-2, but procurement and standardization of CP are barriers to its wide usage. Many monoclonal antibodies (mAbs) have been developed but appear insufficient to neutralize SARS-CoV-2 unless two or three of them are being combined. Therefore, heterologous polyclonal antibodies of animal origin, that have been used for decades to fight against infectious agents might represent a highly efficient alternative to the use of CP or mAbs in COVID-19 by targeting multiple antigen epitopes. However, conventional heterologous polyclonal antibodies trigger human natural xenogeneic antibody responses particularly directed against animal-type carbohydrate epitopes, mainly the N-glycolyl form of the neuraminic acid (Neu5Gc) and the Gal 1,3-galactose (Gal), ultimately forming immune complexes and potentially leading to serum sickness or allergy. To circumvent these drawbacks, we engineered animals lacking the genes coding for the cytidine monophosphate-N-acetylneuraminic acid hydroxylase (CMAH) and 1,3-galactosyl-transferase (GGTA1) enzymes to produce glyco-humanized polyclonal antibodies (GH-pAb) lacking Neu5Gc and -Gal epitopes. We found that pig IgG Fc domains fail to interact with human Fc receptors and thereby should confer the safety advantage to avoiding macrophage dependent exacerbated inflammatory responses, a drawback possibly associated with antibody responses against SARS-CoV-2 or to avoiding a possible antibody-dependent enhancement (ADE). Therefore, we immunized CMAH/GGTA1 double knockout (DKO) pigs with the SARS-CoV-2 spike receptor-binding domain (RBD) to elicit neutralizing antibodies. Animals rapidly developed a hyperimmune response with anti-SARS-CoV-2 end-titers binding dilutions over one to a million and end-titers neutralizing dilutions of 1:10,000. The IgG fraction purified and formulated following clinical Good Manufacturing Practices, named XAV-19, neutralized Spike/angiotensin converting enzyme-2 (ACE-2) interaction at a concentration < 1g/mL and inhibited infection of human cells by SARS-CoV-2 in cytopathic assays. These data and the accumulating safety advantages of using glyco-humanized swine antibodies in humans warranted clinical assessment of XAV-19 to fight against COVID-19.",
+    "rel_num_authors": 29,
     "rel_authors": [
       {
-        "author_name": "Wouter Bos",
-        "author_inst": "CNRS"
+        "author_name": "Bernard Vanhove",
+        "author_inst": "Xenothera"
       },
       {
-        "author_name": "Jean-Pierre Bertoglio",
-        "author_inst": "CNRS"
+        "author_name": "Odile Duvaux",
+        "author_inst": "Xenothera"
       },
       {
-        "author_name": "Louis Gostiaux",
-        "author_inst": "CNRS"
+        "author_name": "Juliette Rousse",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Pierre-Joseph Royer",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Gwenaelle Evanno",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Carine Ciron",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Elsa Lheriteau",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Laurent Vacher",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Nadine Gervois",
+        "author_inst": "University of Nantes"
+      },
+      {
+        "author_name": "Romain Oger",
+        "author_inst": "University of Nantes"
+      },
+      {
+        "author_name": "Yannick Jacques",
+        "author_inst": "University of Nantes"
+      },
+      {
+        "author_name": "Sophie Conchon",
+        "author_inst": "University of Nantes"
+      },
+      {
+        "author_name": "Apolline Salama",
+        "author_inst": "University of Nantes"
+      },
+      {
+        "author_name": "Roberto Duchi",
+        "author_inst": "Avantea"
+      },
+      {
+        "author_name": "Irina Lagutina",
+        "author_inst": "Avantea"
+      },
+      {
+        "author_name": "Andrea Perota",
+        "author_inst": "University of Nantes"
+      },
+      {
+        "author_name": "Philippe Delahaut",
+        "author_inst": "CER Groupe"
+      },
+      {
+        "author_name": "Matthieu Ledure",
+        "author_inst": "CER Groupe"
+      },
+      {
+        "author_name": "Melody Paulus",
+        "author_inst": "CER Groupe"
+      },
+      {
+        "author_name": "Ray So",
+        "author_inst": "The University of Hong Kong"
+      },
+      {
+        "author_name": "Chris Ka Pun Mok",
+        "author_inst": "The University of Hong Kong"
+      },
+      {
+        "author_name": "Roberto Bruzzone",
+        "author_inst": "The University of Hong Kong"
+      },
+      {
+        "author_name": "Marc Bouillet",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Sophie Brouard",
+        "author_inst": "University of Nantes"
+      },
+      {
+        "author_name": "Emanuele Cozzi",
+        "author_inst": "Padua University Hospital"
+      },
+      {
+        "author_name": "Cesare Galli",
+        "author_inst": "Avantea"
+      },
+      {
+        "author_name": "Dominique Blanchard",
+        "author_inst": "Xenothera"
+      },
+      {
+        "author_name": "Jean-Marie Bach",
+        "author_inst": "Oniris"
+      },
+      {
+        "author_name": "Jean-Paul Soulillou",
+        "author_inst": "University of Nantes"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.07.24.205583",
@@ -1245208,63 +1247993,47 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2020.07.24.217562",
-    "rel_title": "Identification, Mapping and Relative Quantitation of SARS-Cov2 Spike Glycopeptides by Mass-Retention Time Fingerprinting",
+    "rel_doi": "10.1101/2020.07.24.219139",
+    "rel_title": "Tissue-specific and interferon-inducible expression of non-functional ACE2 through endogenous retrovirus co-option",
     "rel_date": "2020-07-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.24.217562",
-    "rel_abs": "We describe a novel analytical method for rapid and robust identification, mapping and relative quantitation of glycopeptides from SARS-CoV-2 Spike protein. The method may be executed using any LC-TOF mass spectrometer, requires no specialised knowledge of glycan analysis and makes use of the differential resolving power of reversed phase HPLC. While this separation technique resolves peptides with high efficiency, glycans are resolved poorly, if at all. Consequently, glycopeptides consisting of the same peptide bearing different glycan structures will all possess very similar retention times and co-elute. While this has previously been viewed as a disadvantage, we show that shared retention time can be used to map multiple glycan species to the same peptide and location. In combination with MSMS and pseudo MS3, we have constructed a detailed mass-retention time database for Spike. This database allows any ESI-TOF equipped lab to reliably identify and quantify spike glycans from a single overnight elastase protein digest in less than 90 minutes.",
-    "rel_num_authors": 11,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.24.219139",
+    "rel_abs": "Angiotensin-converting enzyme 2 (ACE2) is an entry receptor for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), as well as a regulator of several physiological processes. ACE2 has recently been proposed to be interferon-inducible, suggesting that SARS-CoV-2 may exploit this phenomenon to enhance viral spread and questioning the efficacy of interferon treatment in Coronavirus disease 2019 (COVID-19). Using a recent de novo transcript assembly that captured previously unannotated transcripts, we describe a novel isoform of ACE2, generated by co-option of an intronic long terminal repeat (LTR) retroelement promoter. The novel transcript, termed LTR16A1-ACE2, exhibits specific expression patterns across the aerodigestive and gastrointestinal tracts and, importantly, is highly responsive to interferon stimulation. In stark contrast, expression of canonical ACE2 is completely unresponsive to interferon stimulation. Moreover, the LTR16A1-ACE2 translation product is a truncated, unstable ACE2 form, lacking domains required for SARS-CoV-2 binding and therefore unlikely to contribute to or enhance viral infection.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Rod Chalk",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
-      },
-      {
-        "author_name": "William Greenland",
-        "author_inst": "Agilent Technologies, Lakeside, Cheadle Royal Business Park, Cheadle, Cheshire, SK8 3GR, UK"
-      },
-      {
-        "author_name": "Tiago Moreira",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
-      },
-      {
-        "author_name": "Jesse Coker",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
-      },
-      {
-        "author_name": "Shubhashish Mukhopadhyay",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
+        "author_name": "Kevin Ng",
+        "author_inst": "Francis Crick Institute"
       },
       {
-        "author_name": "Eleanor Williams",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
+        "author_name": "Jan Attig",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Charlotte Manning",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
+        "author_name": "William Bolland",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Tina Bohstedt",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
+        "author_name": "George Young",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Rama McCrorie",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
+        "author_name": "Jack Major",
+        "author_inst": "The Francis Crick Institute"
       },
       {
-        "author_name": "Alejandra Fernandez-Cid",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
+        "author_name": "Andreas Wack",
+        "author_inst": "Francis Crick Institute"
       },
       {
-        "author_name": "Nicola A Burgess-Brown",
-        "author_inst": "Centre for Medicines Discovery, ORCRB, Oxford University, OX3 7DQ, UK"
+        "author_name": "George Kassiotis",
+        "author_inst": "The Francis Crick Institute"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.07.24.219857",
@@ -1246594,47 +1249363,43 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.23.20160564",
-    "rel_title": "Modelling Palliative and End of Life resource requirements during COVID-19: implications for quality care",
+    "rel_doi": "10.1101/2020.07.22.20160333",
+    "rel_title": "The COVID-19 Pandemic Impact on Primary Health Care services: An Experience from Qatar",
     "rel_date": "2020-07-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20160564",
-    "rel_abs": "BackgroundThere were between 84,891 and 113,139 all-cause excess deaths in the United States (US) from February 1st to 25th May 2020. These deaths are widely attributed directly and indirectly to the COVID-19 pandemic. This surge in death necessitates a matched health system response to relieve serious health related suffering at the end of life (EoL) and achieve a dignified death, through timely and appropriate expertise, medication and equipment. Identifying the human and material resource needed relies on modelling resource and understanding anticipated surges in demand.\n\nMethodsA Discrete Event Simulation model designed in collaboration with health service funders, health providers, clinicians and modellers in the South West of England was created to estimate the resources required during the COVID-19 pandemic to care for deaths from COVID-19 in the community for a geographical area of nearly 1 million people. While our analysis focused on the UK setting, the model is flexible to changes in demand and setting.\n\nResultsThe model predicts that a mean of 11.97 hours (0.18 hours Standard Error (SE), up to a max of 28 hours) of additional community nurse time, up to 33 hours of care assistant time (mean 9.17 hours, 0.23 hours SE), and up to 30 hours additional care from care assistant night-sits (mean of 5.74 hours per day, 0.22 hours SE) will be required per day as a result of out of hospital COVID-19 deaths. Specialist palliative care demand is predicted to increase up to 19 hours per day (mean of 9.32 hours per day, 0.12 hours SE). An additional 286 anticipatory medicine bundles or  just in case prescriptions per month will be necessary to alleviate physical symptoms at the EoL care for patients with COVID-19: an average additional 10.21 bundles (0.06 SE) of anticipatory medication per day. An average additional 9.35 syringe pumps (0.11 SE) could be needed to be in use per day (between 1 and 20 syringe pumps).\n\nConclusionModelling provides essential data to prepare, plan and deliver a palliative care pandemic response tailored to local work patterns and resource. The analysis for a large region in the South West of England shows the significant additional physical and human resource required to relieve suffering at the EoL as part of a pandemic response.\n\nWhy Was This Study Done?The resource required for the relief of suffering at the EoL in the community setting has been poorly described. The stark mortality resulting from the COVID-19 pandemic has highlighted the essential requirement to better understand the demand and available supply of EoL resource to prepare, plan and deliver a palliative care pandemic response.\n\nWhat Did the Researchers Do and Find?This manuscript describes the first open access model to describe EoL resource need during COVID-19 and presents an analysis based on a UK population of nearly 1 million people. The model identified a large increase in need for staff time, including registered community nurses, health care assistants and specialist palliative care nurses and doctors, as well as pressure on resources including syringe pumps and anticipatory medication (such as opioids) used at the EoL for symptom relief from breathlessness and delirium.\n\nWhat Do These Findings Mean?The model findings are critical in planning for a second wave of COVID-19. The open-access nature of the model allows researchers to tailor their analysis to low and middle income or high-income settings worldwide. The model ensures that EoL care is not an afterthought in pandemic planning, but an opportunity to ensure that the relief of suffering at the EoL is available to all.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20160333",
+    "rel_abs": "IntroductionIn March 2020, Qatar started reporting increased numbers of COVID-19 positive cases. The Ministry of Public Health in Qatar has developed an emergency action plan to respond to the outbreak with the Primary Health Care Corporation (PHCC) as a main component of that response.\n\nAimThe aim of this review is to understand and document the Impact of COVID 19 on PHCC in Qatar in terms of response, modifications of services and introduction of new alternatives\n\nMethodologyA retrospective data analysis was conducted for all the COVID-19 swabbing activities and for all the utilization services volume across the PHCC health centers between January 2018 and May 2020.\n\nResultsPHCC allocated testing sites for COVID-19 resulted in conducting 54824 swabs with 11455 positive cases and positivity rate of 20.8% between 14th of March and 15th of June 2020. The overall PHCC services utilization declined with overall reduction of 50% in April 2020. Alternative virtual and remote services were provided, telemedicine was introduced, and it made up 50% of the consultation volumes for April 2020. Home refill delivery medications managed to provide a total of 20920 delivered prescriptions by end of May 2020.\n\nConclusion and recommendationsTo decrease the risk of infection to the patients and health care workers, PHCC in Qatar cancelled the appointments for some high-risk population. However, PHCC introduced virtual remote services that managed to make up for the in-person utilization volume and reflected acceptance in patients behaviours. PHCC continued in detecting positive COVID-19 cases among its targeted communities.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Daniel Chalk",
-        "author_inst": "University of Exeter Medical School"
-      },
-      {
-        "author_name": "Sara Robbins",
-        "author_inst": "University Hospitals Bristol and Weston NHS Foundation Trust"
+        "author_name": "Mohamed Al Kuwari",
+        "author_inst": "Primary Health Care Corporation"
       },
       {
-        "author_name": "Rohan Kandasamy",
-        "author_inst": "North Bristol NHS Trust"
+        "author_name": "Mariam Abdulmalik",
+        "author_inst": "Primary Health Care Corporation"
       },
       {
-        "author_name": "Kate Rush",
-        "author_inst": "Sirona Care and Health"
+        "author_name": "Samya Al Abdulla",
+        "author_inst": "Primary Health Care Corporation"
       },
       {
-        "author_name": "Ajay Aggarwal",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Ahmad Haj Bakri",
+        "author_inst": "Primary Health Care Corporation"
       },
       {
-        "author_name": "Richard Sullivan",
-        "author_inst": "Kings College London"
+        "author_name": "John Gibb",
+        "author_inst": "Primary Health Care Corporation"
       },
       {
-        "author_name": "Charlotte Chamberlain",
-        "author_inst": "Bristol Medical School"
+        "author_name": "Mujeeb Kandy",
+        "author_inst": "Primary Health Care Corporation"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "palliative medicine"
+    "category": "primary care research"
   },
   {
     "rel_doi": "10.1101/2020.07.24.20161315",
@@ -1247828,81 +1250593,125 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2020.07.17.20156075",
-    "rel_title": "A national consensus management pathway for Paediatric Inflammatory Multisystem Syndrome - Temporally associated with SARS-CoV-2 (PIMS-TS): The results of a national Delphi process",
+    "rel_doi": "10.1101/2020.07.16.20155531",
+    "rel_title": "Safety of Hydroxychloroquine among Outpatient Clinical Trial Participants for COVID-19",
     "rel_date": "2020-07-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156075",
-    "rel_abs": "ObjectiveTo develop a consensus management pathway for children with Paediatric Inflammatory Multisystem Syndrome - Temporally associated with SARS-CoV-2 (PIMS-TS).\n\nDesignA three-phase online Delphi process and virtual consensus meeting sought consensus over the investigation, management and research priorities from 98 multidisciplinary participants caring for children with PIMS-TS. 46 participants (47%) completed all three phases. Participants were grouped into three panels and scored each statement from 1 (disagree) to 9 (strongly agree). In phase two participants were shown their panels scores, and in phase three all panels scores.\n\nConsensus agreement was defined as [&ge;]70% of participants in each panel scoring the statement 7-9, and <15% scoring 1-3, and consensus disagreement was the opposite of this. Statements which achieved consensus in 2/3 panels were discussed at the consensus meeting, and when [&ge;]70% participants agreed with the statement it achieved consensus.\n\nResults255 statements were assessed, with  consensus agreement achieved for 111 (44%),  consensus disagreement for 29 (11%), and no consensus for 115 (45%). The 140 consensus statements were used to derive the consensus management pathway.\n\nConclusionsA national consensus pathway has been developed for children suspected of having the novel syndrome PIMS-TS in a timely, cost-efficient manner, in the midst of a global pandemic. Use of a rapid online Delphi process has made this consensus process possible. Future evidence will inform updates to this guidance, which in the interim provides a solid framework to support clinicians caring for children with PIMS-TS.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155531",
+    "rel_abs": "IntroductionUse of hydroxychloroquine in hospitalized patients with COVID-19, especially in combination with azithromycin, has raised safety concerns. Here, we report safety data from three outpatient randomized clinical trials.\n\nMethodsWe conducted three randomized, double-blind, placebo-controlled trials investigating hydroxychloroquine as pre-exposure prophylaxis, post-exposure prophylaxis and early treatment for COVID-19. We excluded individuals with contraindications to hydroxychloroquine. We collected side effects and serious adverse events. We report descriptive analyses of our findings.\n\nResultsWe enrolled 2,795 participants. The median age of research participants was 40 (IQR 34-49) years, and 59% (1633/2767) reported no chronic medical conditions. Overall 2,324 (84%) participants reported side effect data, and 638 (27%) reported at least one medication side effect. Side effects were reported in 29% with daily, 36% with twice weekly, 31% with once weekly hydroxychloroquine compared to 19% with placebo. The most common side effects were upset stomach or nausea (25% with daily, 18% with twice weekly, 16% with weekly, vs. 10% for placebo), followed by diarrhea, vomiting, or abdominal pain (23% for daily, 16% twice weekly, 12% weekly, vs. 6% for placebo). Two individuals were hospitalized for atrial arrhythmias, one on placebo and one on twice weekly hydroxychloroquine. No sudden deaths occurred.\n\nConclusionData from three outpatient COVID-19 trials demonstrated that gastrointestinal side effects were common but mild with the use of hydroxychloroquine, while serious side effects were rare. No deaths occurred related to hydroxychloroquine. Randomized clinical trials can safely investigate whether hydroxychloroquine is efficacious for COVID-19.\n\nShort SummaryData from three randomized clinical trials using hydroxychloroquine for the prevention and treatment of COVID-19 did not suggest significant safety concerns. Gastrointestinal side effects were common but arrhythmias were rare. There were no sudden deaths in any trial.",
+    "rel_num_authors": 27,
     "rel_authors": [
       {
-        "author_name": "Rachel Harwood",
-        "author_inst": "Department of Paediatric Surgery, Alder Hey Childrens Hospital, Eaton Road, Liverpool, L12 2AP"
+        "author_name": "SARAH M LOFGREN",
+        "author_inst": "UNIVERSITY OF MINNESOTA"
       },
       {
-        "author_name": "Benjamin Allin",
-        "author_inst": "National Perinatal Epidemiology Unit, Nuffield Department of Health, University of Oxford, Old Road Campus, Oxford, OX3 9DU"
+        "author_name": "Melanie R Nicol",
+        "author_inst": "University of Minnesota"
       },
       {
-        "author_name": "Christine E Jones",
-        "author_inst": "NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton Foundation NHS Trust and Faculty of Medicine and Ins"
+        "author_name": "Ananta S Bangdiwala",
+        "author_inst": "University of Minnesota"
       },
       {
-        "author_name": "Elizabeth Whittaker",
-        "author_inst": "Department of Paediatrics, Imperial College Healthcare NHS Trust, London, UK"
+        "author_name": "Katelyn A Pastick",
+        "author_inst": "University of Minnesota School of Medicine"
       },
       {
-        "author_name": "Padmanabhan Ramnarayan",
-        "author_inst": "Childrens Acute Transport Service, Great Ormond Street Hospital for Children, London, UK"
+        "author_name": "Elizabeth C Okafor",
+        "author_inst": "University of Minnesota School of Medicine"
       },
       {
-        "author_name": "Athimalaipet Ramanan",
-        "author_inst": "Bristol Royal Hospital for Children, Upper Maudlin Street Bristol, BS2 8BJ, UK"
+        "author_name": "Caleb P Skipper",
+        "author_inst": "Department of Medicine, University of Minnesota"
       },
       {
-        "author_name": "Musa Kaleem",
-        "author_inst": "Department of Paediatric Radiology, Alder Hey Childrens Hospital Eaton Road, Liverpool, L12 2AP, UK"
+        "author_name": "Matthew F Pullen",
+        "author_inst": "Department of Medicine, University of Minnesota"
       },
       {
-        "author_name": "Robert Tulloh",
-        "author_inst": "Bristol Royal Hospital for Children, Upper Maudlin Street Bristol, BS2 8BJ, UK"
+        "author_name": "Nicole W Engen",
+        "author_inst": "Department of Medicine, University of Minnesota"
       },
       {
-        "author_name": "Mark J Peters",
-        "author_inst": "UCL Great Ormond St Institute of Child Health and Great Ormond St Hospital NHS Trust, NIHR Biomedical Research Centre, UK"
+        "author_name": "Mahsa Abassi",
+        "author_inst": "Department of Medicine, University of Minnesota"
       },
       {
-        "author_name": "Sarah Almond",
-        "author_inst": "Department of Paediatric Surgery, Alder Hey Childrens Hospital, Eaton Road, Liverpool, L12 2AP"
+        "author_name": "Darlisha A Williams",
+        "author_inst": "Department of Medicine, University of Minnesota"
       },
       {
-        "author_name": "Peter J Davis",
-        "author_inst": "Bristol Royal Hospital for Children, Upper Maudlin Street Bristol, BS2 8BJ, UK"
+        "author_name": "Alanna A Nascene",
+        "author_inst": "University of Minnesota"
       },
       {
-        "author_name": "Michael Levin",
-        "author_inst": "Department of Paediatrics, Imperial College Healthcare NHS Trust, London, UK"
+        "author_name": "Margaret L Axelrod",
+        "author_inst": "Vanderbilt University"
       },
       {
-        "author_name": "Saul N Faust",
-        "author_inst": "NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton Foundation NHS Trust and Faculty of Medicine and Ins"
+        "author_name": "Sylvian A Lother",
+        "author_inst": "University of Manitoba"
       },
       {
-        "author_name": "Marian Knight",
-        "author_inst": "University of Oxford"
+        "author_name": "Lauren J MacKenzie",
+        "author_inst": "University of Manitoba"
       },
       {
-        "author_name": "Simon Kenny",
-        "author_inst": "NHS England/Improvement, PO Box 16738, Redditch, B97 9PT, UK"
+        "author_name": "Glen Drobot",
+        "author_inst": "University of Manitoba"
       },
       {
-        "author_name": "- PIMS-TS National Consensus Management Study Group",
-        "author_inst": ""
+        "author_name": "Nicole Marten",
+        "author_inst": "George & Fay Yee Centre for Healthcare Innovation, Winnipeg, Manitoba"
+      },
+      {
+        "author_name": "Matthew P Cheng",
+        "author_inst": "McGill University"
+      },
+      {
+        "author_name": "Ryan Zarychanshi",
+        "author_inst": "University of Manitoba"
+      },
+      {
+        "author_name": "Ilan S Schwartz",
+        "author_inst": "University of Alberta"
+      },
+      {
+        "author_name": "Michael Silverman",
+        "author_inst": "Lawson Research Institute, London, Ontario"
+      },
+      {
+        "author_name": "Zain Chagla",
+        "author_inst": "McMaster University"
+      },
+      {
+        "author_name": "Lauren E Kelly",
+        "author_inst": "George & Fay Yee Centre for Healthcare Innovation, Winnipeg, Manitoba"
+      },
+      {
+        "author_name": "Emily G McDonald",
+        "author_inst": "McGill University"
+      },
+      {
+        "author_name": "Todd C Lee",
+        "author_inst": "McGill University"
+      },
+      {
+        "author_name": "Katherine Huppler Hullsiek",
+        "author_inst": "University of Minnesota"
+      },
+      {
+        "author_name": "David R Boulware",
+        "author_inst": "Department of Medicine, University of Minnesota"
+      },
+      {
+        "author_name": "Radha Rajasingham",
+        "author_inst": "Department of Medicine, University of Minnesota"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1249746,43 +1252555,115 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.15.20154955",
-    "rel_title": "The effect of border controls on the risk of COVID-19 reincursion from international arrivals",
+    "rel_doi": "10.1101/2020.07.21.214759",
+    "rel_title": "Escape from neutralizing antibodies by SARS-CoV-2 spike protein variants",
     "rel_date": "2020-07-22",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154955",
-    "rel_abs": "In an attempt to maintain elimination of COVID-19 in New Zealand, all international arrivals are required to spend 14 days in government-managed quarantine and to return a negative test result before being released. We model the testing, isolation and transmission of COVID-19 within quarantine facilities to estimate the risk of community outbreaks being seeded at the border. We use a simple branching process model for COVID-19 transmission that includes a time-dependent probability of a false negative test result. We show that the combination of 14-day quarantine with two tests reduces the risk of releasing an infectious case to around 0.1% per infected arrival. Shorter quarantine periods, or reliance on testing only with no quarantine, substantially increases this risk. We calculate the fraction of cases detected in the second week of their two week stay and show that this may be a useful indicator of the likelihood of transmission occurring within quarantine facilities. Frontline staff working at the border risk exposure to infected individuals and this has the potential to lead to a community outbreak. We use the model to test surveillance strategies and evaluate the likely size of the outbreak at the time it is first detected. We conclude with some recommendations for managing the risk of potential future outbreaks originating from the border.",
-    "rel_num_authors": 6,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.21.214759",
+    "rel_abs": "Neutralizing antibodies elicited by prior infection or vaccination are likely to be key for future protection of individuals and populations against SARS-CoV-2. Moreover, passively administered antibodies are among the most promising therapeutic and prophylactic anti-SARS-CoV-2 agents. However, the degree to which SARS-CoV-2 will adapt to evade neutralizing antibodies is unclear. Using a recombinant chimeric VSV/SARS-CoV-2 reporter virus, we show that functional SARS-CoV-2 S protein variants with mutations in the receptor binding domain (RBD) and N-terminal domain that confer resistance to monoclonal antibodies or convalescent plasma can be readily selected. Notably, SARS-CoV-2 S variants that resist commonly elicited neutralizing antibodies are now present at low frequencies in circulating SARS-CoV-2 populations. Finally, the emergence of antibody-resistant SARS-CoV-2 variants that might limit the therapeutic usefulness of monoclonal antibodies can be mitigated by the use of antibody combinations that target distinct neutralizing epitopes.",
+    "rel_num_authors": 24,
     "rel_authors": [
       {
-        "author_name": "Nicholas Steyn",
-        "author_inst": "University of Auckland"
+        "author_name": "Yiska Weisblum",
+        "author_inst": "Rockefeller"
       },
       {
-        "author_name": "Michael J Plank",
-        "author_inst": "University of Canterbury"
+        "author_name": "Fabian Schmidt",
+        "author_inst": "Rockefeller"
       },
       {
-        "author_name": "Alex James",
-        "author_inst": "University of Canterbury, NZ"
+        "author_name": "Fengwen Zhang",
+        "author_inst": "Rockefeller"
       },
       {
-        "author_name": "Rachelle N Binny",
-        "author_inst": "Manaaki Whenua"
+        "author_name": "Justin DaSilva",
+        "author_inst": "Rockefeller"
       },
       {
-        "author_name": "Shaun C Hendy",
-        "author_inst": "University of Auckland"
+        "author_name": "Daniel Poston",
+        "author_inst": "Rockefeller"
       },
       {
-        "author_name": "Audrey Lustig",
-        "author_inst": "Manaaki Whenua"
+        "author_name": "Julio C C Lorenzi",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Frauke Muecksch",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Magdalena Rutkowska",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Hans-Heinrich Hoffmann",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Eleftherios Michailidis",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Christian Gaebler",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Marianna Agudelo",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Alice Cho",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Zijun Wang",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Anna Gazumyan",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Melissa Cipolla",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Larry Luchsinger",
+        "author_inst": "New York Blood Center"
+      },
+      {
+        "author_name": "Christopher D Hillyer",
+        "author_inst": "New York Blood Center"
+      },
+      {
+        "author_name": "Marina Caskey",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Davide F Robbiani",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Charles Rice",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Michel C Nussenzweig",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Theodora Hatziioannou",
+        "author_inst": "Rockefeller"
+      },
+      {
+        "author_name": "Paul D Bieniasz",
+        "author_inst": "The Rockefeller University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.07.21.214932",
@@ -1251180,65 +1254061,21 @@
     "category": "emergency medicine"
   },
   {
-    "rel_doi": "10.1101/2020.07.20.20157602",
-    "rel_title": "The COVID-19 outbreak in Sichuan, China: epidemiology and impact of interventions",
+    "rel_doi": "10.1101/2020.07.18.20156695",
+    "rel_title": "A preliminary model to describe the transmission dynamics of Covid-19 between two neighboring cities or countries",
     "rel_date": "2020-07-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.20.20157602",
-    "rel_abs": "In January 2020, a COVID-19 outbreak was detected in Sichuan Province of China. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of the performed interventions. We analyzed patient records for all laboratory-confirmed cases reported in the province for the period of January 21 to March 16, 2020. To estimate the basic and daily reproduction numbers, we used a Bayesian framework. In addition, we estimate the number of cases averted by the implemented control strategies. The outbreak resulted in 539 confirmed cases, lasted less than two months, and no further local transmission was detected after February 27. The median age of local cases was 8 years older than that of imported cases. Severity of symptoms increased with age. We estimated R0 at 2.4 (95% CI: 1.6-3.7). The epidemic was self-sustained for about 3 weeks before going below the epidemic threshold 3 days after the declaration of a public health emergency by Sichuan authorities. Our findings indicate that, were the control measures be adopted four weeks later, the epidemic could have lasted 49 days longer (95%CI: 31-68 days), causing 9,216 (95%CI: 1,317-25,545) more cases and possibly overwhelming Sichuan healthcare system.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.18.20156695",
+    "rel_abs": "We present a mathematical model that would allow one to describe the transmission dynamics of Covid-19 between two neighboring cities or countries. This model is analyzed both analytical and numerically. It is a preliminary model because it assumes that the migration rate and the mortality rate are constant over time. Despite these simplifications, only two of the four equilibrium conditions were deduced from the system of equations proposed in this paper. Finally, we show an example the transmission dynamics between Portugal and Spain according to the cases registered before June 3, 2020.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Quanhui Liu",
-        "author_inst": "Sichuan University, Chengdu, China"
-      },
-      {
-        "author_name": "Ana I Bento",
-        "author_inst": "Indiana University"
-      },
-      {
-        "author_name": "Kexin Yang",
-        "author_inst": "Sichuan University"
-      },
-      {
-        "author_name": "Hang Zhang",
-        "author_inst": "Sichuan University"
-      },
-      {
-        "author_name": "Xiaohan Yang",
-        "author_inst": "Department of Engineering and Computer Science, New York University Shanghai, Shanghai, China"
-      },
-      {
-        "author_name": "Stefano Merler",
-        "author_inst": "Bruno Kessler Foundation, Trento, Italy"
-      },
-      {
-        "author_name": "Alessandro Vespignani",
-        "author_inst": "Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA"
-      },
-      {
-        "author_name": "Jiancheng Lv",
-        "author_inst": "Sichuan University"
-      },
-      {
-        "author_name": "Hongjie Yu",
-        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
-      },
-      {
-        "author_name": "Wei Zhang",
-        "author_inst": "Sichuan University"
-      },
-      {
-        "author_name": "Tao Zhou",
-        "author_inst": "University of Electronic Science and Technology of China, Chengdu, China"
-      },
-      {
-        "author_name": "Marco Ajelli",
-        "author_inst": "Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, IN, USA"
+        "author_name": "Raul Isea",
+        "author_inst": "IDEA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1252962,31 +1255799,31 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.15.20154336",
-    "rel_title": "Epidemiological Profile and Transmission Dynamics of COVID-19 in the Philippines",
+    "rel_doi": "10.1101/2020.07.18.20152256",
+    "rel_title": "Providing breastfeeding support during the COVID-19 pandemic: Concerns of mothers who contacted the Australian Breastfeeding Association",
     "rel_date": "2020-07-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154336",
-    "rel_abs": "The Philippines confirmed local transmission of COVID-19 on 7 March 2020. We described the characteristics and epidemiological time-to-event distributions for laboratory-confirmed cases in the Philippines. The median age of 8,212 cases was 46 years (IQR: 32-61), with 46.2% being female and 68.8% living in the National Capital Region. Health care workers represented 24.7% of all detected infections. Mean length of hospitalization for those who were discharged or died were 16.00 days (95% CI: 15.48, 16.54) and 7.27 days (95% CI: 6.59, 8.24). Mean duration of illness was 26.66 days (95% CI: 26.06, 27.28) and 12.61 days (95% CI: 11.88, 13.37) for those who recovered or died. Mean serial interval was 6.90 days (95% CI: 5.81, 8.41). Epidemic doubling time pre-quarantine (11 February and 19 March) was 4.86 days (95% CI: 4.67, 5.07) and the reproductive number was 2.41 (95% CI: 2.33, 2.48). During quarantine (March 20 to April 9), doubling time was 12.97 days (95% CI: 12.57, 13.39) and the reproductive number was 0.89 (95% CI: 0.78, 1.02).",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.18.20152256",
+    "rel_abs": "Concerns of mothers seeking breastfeeding support during the COVID-19 pandemic, and the experiences of Australian Breastfeeding Association (ABA) volunteers who assisted them, were explored via an online survey. Surveys were completed 16th March to 18th of May 2020 and described the COVID-19 related concerns of 340 individuals. One hundred and thirty six mothers (64%) sought support to protect their infants by continuing breastfeeding, increasing milk supply, or restarting breastfeeding. Mothers were commonly stressed, isolated and needing reassurance. Thirty four (10%) raised concerns about COVID-19 and breastfeeding safety. One hundred and twenty nine (61%) informed volunteers they were unable to access face-to-face health services because of fear or unavailability. Most common breastfeeding concerns were related to insufficient milk or weight gain, painful breasts, relactation, and reducing supplemental milk. Volunteers reported mothers were worried stress had reduced milk supply, that milk supply concerns were exacerbated by the inability to weigh infants, and that seeking medical treatment was being delayed. ABA volunteers stated they felt supported and confident assisting mothers while also expressing distress at mothers situation. ABAs role in emergency response should be recognised and national planning for infant and young child feeding in emergencies, must be urgently developed, funded, and implemented.",
     "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Nel Jason Ladiao Haw",
-        "author_inst": "Ateneo de Manila University"
+        "author_name": "Naomi Hull",
+        "author_inst": "Australian Breastfeeding Association"
       },
       {
-        "author_name": "Jhanna Uy",
-        "author_inst": "Ateneo de Manila University"
+        "author_name": "Renee L Kam",
+        "author_inst": "Australian Breastfeeding Association"
       },
       {
-        "author_name": "Karla Therese L. Sy",
-        "author_inst": "Boston University"
+        "author_name": "Karleen D Gribble",
+        "author_inst": "Western Sydney University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2020.07.16.20152033",
@@ -1254468,135 +1257305,71 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.17.20156513",
-    "rel_title": "Large-scale Multi-omic Analysis of COVID-19 Severity",
+    "rel_doi": "10.1101/2020.07.17.20156539",
+    "rel_title": "Quantifying SARS-CoV-2 infection risk within the Apple/Google exposure notification framework to inform quarantine recommendations",
     "rel_date": "2020-07-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156513",
-    "rel_abs": "We performed RNA-Seq and high-resolution mass spectrometry on 128 blood samples from COVID-19 positive and negative patients with diverse disease severities. Over 17,000 transcripts, proteins, metabolites, and lipids were quantified and associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a comparative analysis with published data and a machine learning approach for prediction of COVID-19 severity.",
-    "rel_num_authors": 29,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156539",
+    "rel_abs": "Most Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure: a window of infectiousness in the transmitter, [&ge;]15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long post-exposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes Theorem. We capture a 10-fold range of risk using 6 infectiousness values, 11-fold range using 3 Bluetooth attenuation bins, [~]6-fold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and [~]11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Katherine A Overmyer",
-        "author_inst": "Morgridge Institute for Research"
-      },
-      {
-        "author_name": "Evgenia Shishkova",
-        "author_inst": "University of Wisconsin-Madison, Madison, WI USA"
-      },
-      {
-        "author_name": "Ian Miller",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
-      },
-      {
-        "author_name": "Joseph Balnis",
-        "author_inst": "Albany Medical College, Albany NY, USA"
-      },
-      {
-        "author_name": "Matthew N. Bernstein",
-        "author_inst": "Morgridge Institute for Research"
-      },
-      {
-        "author_name": "Trenton M. Peters-Clarke",
-        "author_inst": "University of Wisconsin-Madison, Madison, WI USA"
-      },
-      {
-        "author_name": "Jesse G. Meyer",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
-      },
-      {
-        "author_name": "Qiuwen Quan",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
-      },
-      {
-        "author_name": "Laura K. Muehlbauer",
-        "author_inst": "University of Wisconsin-Madison, Madison, WI, USA"
-      },
-      {
-        "author_name": "Edna A. Trujillo",
-        "author_inst": "University of Wisconsin-Madison, Madison, WI, USA"
-      },
-      {
-        "author_name": "Yuchen He",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
-      },
-      {
-        "author_name": "Amit Chopra",
-        "author_inst": "Albany Medical Center, Albany NY, USA"
-      },
-      {
-        "author_name": "Hau Chieng",
-        "author_inst": "Albany Medical Center, Albany NY, USA"
-      },
-      {
-        "author_name": "Anupama Tiwari",
-        "author_inst": "Albany Medical Center, Albany NY, USA"
-      },
-      {
-        "author_name": "Marc A. Judson",
-        "author_inst": "Albany Medical College, Albany NY, USA"
-      },
-      {
-        "author_name": "Brett Paulson",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
-      },
-      {
-        "author_name": "Dain R. Brademan",
-        "author_inst": "University of Wisconsin-Madison, Madison, WI, USA"
+        "author_name": "Amanda M Wilson",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Yunyun Zhu",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
+        "author_name": "Nathan Aviles",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Lia R. Serrano",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
+        "author_name": "James I Petrie",
+        "author_inst": "Covid Watch"
       },
       {
-        "author_name": "Vanessa Linke",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
+        "author_name": "Paloma I Beamer",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Lisa A. Drake",
-        "author_inst": "Albany Medical College, Albany NY, USA"
+        "author_name": "Zsombor Szabo",
+        "author_inst": "Covid-Watch"
       },
       {
-        "author_name": "Alejandro P. Adam",
-        "author_inst": "Albany Medical College, Albany NY, USA"
+        "author_name": "Michelle Xie",
+        "author_inst": "Covid Watch"
       },
       {
-        "author_name": "Bradford S. Schwartz",
-        "author_inst": "Morgridge Institute for Research, Madison WI, USA"
+        "author_name": "Janet McIllece",
+        "author_inst": "World Wide Technology"
       },
       {
-        "author_name": "Harold A. Singer",
-        "author_inst": "Albany Medical College, Albany NY, USA"
+        "author_name": "Yijie Chen",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Scott Swanson",
-        "author_inst": "Morgridge Institute for Research, Madison WI, USA"
+        "author_name": "Young-Jun Son",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Deane F. Mosher",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
+        "author_name": "Sameer Halai",
+        "author_inst": "Covid Watch"
       },
       {
-        "author_name": "Ron Stewart",
-        "author_inst": "Morgridge Institute For Research, Madison WI, USA."
+        "author_name": "Tina White",
+        "author_inst": "Covid Watch"
       },
       {
-        "author_name": "Joshua J. Coon",
-        "author_inst": "University of Wisconsin-Madison, Madison WI, USA"
+        "author_name": "Kacey C Ernst",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Ariel Jaitovich",
-        "author_inst": "Albany Medical College, Albany NY, USA"
+        "author_name": "Joanna Masel",
+        "author_inst": "University of Arizona"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.07.15.20154989",
@@ -1256238,25 +1259011,45 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.07.16.20155630",
-    "rel_title": "Emerging Mental Health Challenges, Strategies and Opportunities in the context of the COVID-19 Pandemic: Perspectives from South American Decision-makers.",
+    "rel_doi": "10.1101/2020.07.16.20155572",
+    "rel_title": "Probability of aerosol transmission of SARS-CoV-2",
     "rel_date": "2020-07-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155630",
-    "rel_abs": "BackgroundMental health awareness has increased during the COVID-19 pandemic. Although international guidelines address the mental health and psychosocial support (MHPSS) response to emergencies, regional recommendations on COVID-19 are still insufficient. We identified emerging mental health problems, strategies to address them, and opportunities to reform mental health systems during the COVID-19 pandemic in South America.\n\nMethodsAn anonymous online questionnaire was sent to mental health decision-makers of Ministries of Health in 10 South American countries in mid-April 2020. The semi-structured questionnaire had 12 questions clustered into 3 main sections: emerging challenges in mental health, current and potential strategies to face the pandemic, and, key elements for mental health reform. We identified keywords and themes for each section through summative content analysis.\n\nFindingsAn increasing mental health burden and emerging needs are arising as direct and indirect consequences of the pandemic among health care providers and the general population. National lockdowns challenge the delivery and access to mental health treatment and care. Strategies to meet these health needs rely heavily on timely and adequate responses by strengthened mental health governance and systems, availability of services, virtual platforms, and appropriate capacity building for service providers. Short- and medium-term strategies focused on bolstering community-based mental health networks and telemedicine for high-risk populations. Opportunities for long-term mental health reform entail strengthening legal frameworks, redistribution of financial resources and collaboration with local and international partners.\n\nInterpretationMental health and psychosocial support have been identified as a priority area by South American countries in the COVID-19 response. The pandemic has generated specific needs that require appropriate actions including: implementing virtual based interventions, orienting capacity building towards protection of users and health providers, strengthening evidence-driven decision making and integrating MHPSS in high-level mechanisms guiding the response to COVID-19.\n\nFundingNone.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe COVID-19 pandemic has affected mental health and wellbeing as well as its determinants. General population have reported anxiety and stress while health professionals fear, and bereavement. Mental health services have also been overburdened as the health needs increase as consequence of the pandemic and the isolation measures in place. The WHO General director has recognized mental health and psychological support (MHPPS) as a major pillar in the overall health response to the COVID-19 pandemic. Likewise, the Inter Agency Standing Committee (IASC) published a global briefing recommending eight MHPPS interventions to be implement during the crisis. Nonetheless, evidence to guide action at regional and sub-regional levels is still insufficient.\n\nAdded value of this studyThis study provides expert perspectives of decision-makers about mental health burden and actions during the COVID-19 in South America, currently the most serious hub of infection worldwide. Health services have reported an increase of anxiety, stress and fear among the general population emerging during the pandemic. The pandemic has generated specific needs that require appropriate actions including implementing virtual based interventions, bolstering community-based mental health networks, and integrating MHPSS in high-level mechanisms guiding the response to COVID-19. Decision-makers identified opportunities to seize for long-term mental health reform such as strengthening legal frameworks, redistribution of financial resources and collaboration with local and international partners.\n\nImplications of all the available evidenceThe importance of this research goes beyond documenting the status quo of mental health at country level, but implies fostering, enhancing and expanding collaborations in the Sub-region to strengthen the mental health response to the COVID-19 pandemic. Country-cooperation initiatives in mental health have been an important strategy to improve local mental health systems and services. Our findings are expected to better orient next steps in making decisions on mental health policies and services in South America, but also to inform public health key leaders and mental health experts within and beyond the Region of the Americas.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20155572",
+    "rel_abs": "Transmission of SARS-CoV-2 leading to COVID-19 occurs through exhaled respiratory droplets from infected humans. Currently, however, there is much controversy over whether respiratory aerosol microdroplets play an important role as a route of transmission. By measuring and modeling the dynamics of exhaled respiratory droplets we can assess the relative contribution of aerosols in the spreading of SARS-CoV-2. We measure size distribution, total numbers and volumes of respiratory droplets, including aerosols, by speaking and coughing from healthy subjects. Dynamic modelling of exhaled respiratory droplets allows to account for aerosol persistence times in confined public spaces. The probability of infection by inhalation of aerosols when breathing in the same space can then be estimated using current estimates of viral load and infectivity of SARS-CoV-2. In line with the current known reproduction numbers, our study of transmission of SARS-CoV-2 suggests that aerosol transmission is an inefficient route, in particular from non or mildly symptomatic individuals.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Daniel A Antiporta",
-        "author_inst": "Johns Hopkins School of Public Health"
+        "author_name": "Daniel Bonn",
+        "author_inst": "University of Amsterdam"
       },
       {
-        "author_name": "Andrea Bruni",
-        "author_inst": "Pan American Health Organization"
+        "author_name": "Scott Howard Smith",
+        "author_inst": "University of Amsterdam"
+      },
+      {
+        "author_name": "Aernout Somsen",
+        "author_inst": "Cardiology Centers of the Netherlands"
+      },
+      {
+        "author_name": "Cees van Rijn",
+        "author_inst": "University of Amsterdam"
+      },
+      {
+        "author_name": "Stefan Kooij",
+        "author_inst": "University of Amsterdam"
+      },
+      {
+        "author_name": "Lia van der Hoek",
+        "author_inst": "University of Amsterdam - AMC"
+      },
+      {
+        "author_name": "Reinout A Bem",
+        "author_inst": "Amsterdam University Medical Centers"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1258516,49 +1261309,33 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.15.20153098",
-    "rel_title": "Public's perceived importance of non-pharmacological interventions for COVID-19 control in Greece: preliminary evidence from a cross-sectional study",
+    "rel_doi": "10.1101/2020.07.15.20147041",
+    "rel_title": "A systematic review uncovers a wide-gap between COVID-19 in humans and animal models",
     "rel_date": "2020-07-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20153098",
-    "rel_abs": "BackgroundIn the early stages of coronavirus disease 2019 (COVID-19) pandemic, while effective pharmaceutical approaches are pending, COVID-19 management relies primarily on non-pharmaceutical interventions (NPIs), such as social distancing, which requirepublics engagement and behavioral adjustment. This study aims to evaluate publics perceived importance of the NPIs imposed for COVID-19 control in personal and public health protection in Greece.\n\nMethodsThis cross-sectional online study, enrolled 657 participants of the general Greek population in order to assess their beliefs and evaluate possible factors that influence their perceptions as regards NPI importance in personal and public health protection.\n\nResultsOverall, Greeks considered NPIs important for health protection. The participants who were less likely to consider NPIs important were men (OR versus females=1.64, 95% CI:1.15 to 2.36, p=0.007), people younger than 40 years old (OR between ages over 40 versus ages below 40=0.48, 95% CI:0.34 to 0.68, p<0.001), and people who did not chose the Hellenic National Public Health Organization (EODY) to get informed about COVID-19 (OR of EODY versus other sources of information = 0.65, 95% CI:0.46-0.92, p= 0.014).\n\nConclusionsThis study profiled Greek people who do and do not consider NPIs important, mainly as of their demographic features. Focused communicational strategies in certain population subgroups are recommended.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20147041",
+    "rel_abs": "BackgroundAnimal models of COVID-19 have been rapidly reported after the start of the pandemic. We aimed to assess whether the newly created models reproduce the full spectrum of humans COVID-19.\n\nMethodsWe searched the Medline, as well as BioRxiv and MedRxiv preprint servers for original research published in English from January 1, to May 20, 2020. We used the search terms \"COVID-19\" OR \"SARS-CoV-2\" AND, \"animal models\", \"hamsters\", \"nonhuman primates\", \"macaques\", \"rodent\", \"mice\", \"rats\", \"ferrets\", \"rabbits\", \"cats\", and \"dogs\". Inclusion criteria were the establishment of animal models of COVID-19 as an endpoint. Other inclusion criteria were assessment of prophylaxis, therapies, or vaccines, using animal models of COVID-19.\n\nFindings13 peer-reviewed studies and 14 preprints met inclusion criteria. The animals used were nonhuman primates (n=13), mice (n=7), ferrets (n=4), hamsters (n=4), and cats (n=1). All animals supported high viral replication in the upper and lower respiratory tract associated with mild clinical manifestations, lung pathology and full recovery. Older animals displayed relatively more severe illness than the younger ones. No animal models developed hypoxemic respiratory failure, multiple organ dysfunction, culminating in death. All species elicited a specific IgG antibodies response to the spike proteins, which were protective against a second exposure. Transient systemic inflammation was observed occasionally in Rhesus macaques, hamsters, and mice. Notably, none of the animals unveiled cytokine storm or coagulopathy.\n\nConclusionsMost of the animal models of COVID-19 recapitulated mild pattern of human COVID-19 with full recovery phenotype. No severe illness associated with mortality was observed, suggesting a wide gap between COVID-19 in humans and animal models.\n\nFundingThere was no funding source for this study.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Eleni C. Boutsikari",
-        "author_inst": "National and Kapodistrian University of Athens"
-      },
-      {
-        "author_name": "Anna Christakou",
-        "author_inst": "University of West Attica"
-      },
-      {
-        "author_name": "Michail Elpidoforou",
-        "author_inst": "University of West Attica"
-      },
-      {
-        "author_name": "Ioannis Kopsidas",
-        "author_inst": "National and Kapodistrian University of Athens"
-      },
-      {
-        "author_name": "Nicholas Nikolovienis",
-        "author_inst": "University of West Attica"
+        "author_name": "Salleh N Ehaideb",
+        "author_inst": "Experimental Medicine Department, King Abdullah International Medical Research Center/King Saud bin Abdulaziz University for Health Sciences, King Abdulaziz Med"
       },
       {
-        "author_name": "Despina Kardara",
-        "author_inst": "National and Kapodistrian University of Athens"
+        "author_name": "Mashan L Abdullah",
+        "author_inst": "Experimental Medicine Department, King Abdullah International Medical Research Center/King Saud bin Abdulaziz University for Health Sciences, King Abdulaziz Med"
       },
       {
-        "author_name": "Chrissoula C. Boutsikari",
-        "author_inst": "National and Kapodistrian University of Athens"
+        "author_name": "Bisher Abuyassin",
+        "author_inst": "Experimental Medicine Department, King Abdullah International Medical Research Center/King Saud bin Abdulaziz University for Health Sciences, King Abdulaziz Med"
       },
       {
-        "author_name": "Christos Triantafyllou",
-        "author_inst": "National and Kapodistrian University of Athens"
+        "author_name": "Abderrezak Bouchama",
+        "author_inst": "King Abdullah International Medical Research Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1260398,63 +1263175,95 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.17.20156117",
-    "rel_title": "Training and reployment of non-specialists is an effective solution for the shortage of health care workers in the COVID-19 pandemic",
+    "rel_doi": "10.1101/2020.07.17.20156158",
+    "rel_title": "Multisectoral collaboration for pandemic response and operational support of critical care and emergency departments",
     "rel_date": "2020-07-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156117",
-    "rel_abs": "ImportanceIn the COVID-19 pandemic many countries encounter problems arising from shortage of specialists. Short intensive training and reployment of non-specialists is an option but the effectiveness is unknown.\n\nObjectiveTo investigate whether there was difference in in-hospital mortality rates between COVID-19 patients managed by a mixed team (including non-specialists who had short intensive training and operated to a strict protocol) and those managed by a specialist team of health care workers.\n\nDesignCohort study, from January 26, 2020 to April 7, 2020, follow up to April 7, 2020.\n\nSettingMulticenter - Wuhan Hankou Hospital and Wuhan Xiehe Hospital, Wuhan, China.\n\nParticipants261 HCWs deployed to Wuhan from Guangdong emergency rescue team and the 269 COVID-19 patients they treated.\n\nExposureAmong 261 health care workers, 130 were in the specialist team and included 33 physicians, 32 of whom (97.0%) of whom were from relevant specialties. Each physician was in charge of 25-27 beds, with a 6-hour shift time. The mixed team included 131 health care workers, with 7 of the 28 physicians (25.0%) from relevant specialties. Each physician managed 12-13 beds, with a 4-hour shift time.\n\nNon-specialists received short-term intensive training and then followed strict management protocols. Specialists practiced as normal.\n\nMain Outcomes and MeasuresMain outcome was in-hospital mortality of COVID-19 patients. Another outcome was rate of SARS-CoV-2 infection in health care workers.\n\nResultsA total of 269 patients were included (144 male). In-hospital mortality rate of patients treated by the specialist teams and the mixed teams was 12.6% (20/159) and 12.7% (14/110) respectively (Difference = -0.1%, 95% CI -8.2% to 7.9%, p=.97). None of the health care workers were infected.\n\nConclusions and RelevanceTraining and reployment of non-specialists is an effective solution for the shortage of health care workers in the COVID-19 pandemic.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWas there difference in mortality rates between COVID-19 patients managed by a mixed team (including non-specialists who had short intensive training and operated to a strict protocol) and those managed by a specialist team of health care workers (HCWs)?\n\nFindingsIn-hospital mortality rate among patients managed by specialist team (130 HCWs, 159 patients) and mixed team (131 HCWs, 110 patients) was 12.6% (20/159) and 12.7% (14/110) respectively (Difference = -0.1%, 95% CI -8.2% to 7.9%, p=.97).\n\nMeaningWith shortage of specialist HCWs, training and reployment of non-specialists is an effective option in the management of COVID-19 patients.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20156158",
+    "rel_abs": "BackgroundIn March 2020, an influx of admissions in COVID-19 positive patients threatened to overwhelm healthcare facilities in East Baton Rouge Parish, Louisiana. Exacerbating this problem was a shortage of diagnostic testing capability, resulting in a delay in time-to-result return. An improvement in diagnostic testing availability and timeliness was necessary to improve the allocation of resources and ultimate throughput of patients. The management of a COVID-19 positive patient or patient under investigation requires infection control measures that can quickly consume personal protective equipment (PPE) stores and personnel available to treat these patients. Critical shortages of both PPE and personnel also negatively impact care in patients admitted with non-COVID-19 illnesses.\n\nMethodsA multisectoral partnership of healthcare providers, facilities and academicians created a molecular diagnostic lab within an academic research facility dedicated to testing inpatients and healthcare personnel for SARS-CoV-2. The purpose of the laboratory was to provide a temporary solution to the East Baton Rouge Parish healthcare community until individual facilities were self-sustaining in testing capabilities. We describe the partnership and the impacts of this endeavor by developing a model derived from a combination of data sources, including electronic health records, hospital operations, and state and local resources.\n\nFindingsOur model demonstrates two important principles: the impact of reduced turnaround times (TAT) on potential differences in inpatient population numbers for COVID-19 and savings in PPE attributed to the more rapid TAT.\n\nInterpretationOverall, we provide rationale for and demonstration of the utility of multisectoral partnerships when responding to public health emergencies.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Ming Kuang",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen Univeristy"
+        "author_name": "Rebecca C Christofferson",
+        "author_inst": "Louisiana State University"
       },
       {
-        "author_name": "Jianfeng Wu",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Hollis R O'Neal",
+        "author_inst": "Louisiana State University Health Sciences Center, Baton Rouge"
       },
       {
-        "author_name": "Yifeng Luo",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Tonya Jagneaux",
+        "author_inst": "Louisiana State University Health Sciences Center, Baton Rouge"
       },
       {
-        "author_name": "Han Xiao",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Catherine S O'Neal",
+        "author_inst": "Louisiana State University Health Sciences Center, Baton Rouge"
       },
       {
-        "author_name": "Ruiming Liang",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Christine S Walsh",
+        "author_inst": "Louisiana State University"
       },
       {
-        "author_name": "Wenjie Hu",
-        "author_inst": "The First Affiliate Hospital of Sun Yat-sen University"
+        "author_name": "E. Handly Mayton",
+        "author_inst": "Louisiana State University"
       },
       {
-        "author_name": "Shouzhen Cheng",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Luan V Dinh",
+        "author_inst": "Pennington Biomedical Research Center"
       },
       {
-        "author_name": "Qian Zhou",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Abigail I Fish",
+        "author_inst": "Louisiana State University"
       },
       {
-        "author_name": "Sui Peng",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Anh Phan",
+        "author_inst": "Pennington Biomedical Research Center"
       },
       {
-        "author_name": "KarKeung Cheng",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Thaya E Stoufflet",
+        "author_inst": "Louisiana State University"
       },
       {
-        "author_name": "Haipeng Xiao",
-        "author_inst": "The First Affiliated Hospital of Sun Yat-sen University"
+        "author_name": "Jonathan R Schroeder",
+        "author_inst": "Our Lady of the Lake Regional Medical Center"
+      },
+      {
+        "author_name": "Morgan K Walker",
+        "author_inst": "Louisiana State University Health Sciences Center, Baton Rouge"
+      },
+      {
+        "author_name": "Erik A Turner",
+        "author_inst": "Louisiana State University"
+      },
+      {
+        "author_name": "Christi G Pierce",
+        "author_inst": "Our Lady of the Lake Regional Medical Center"
+      },
+      {
+        "author_name": "K. Scott Wester",
+        "author_inst": "Our Lady of the Lake Regional Medical Center"
+      },
+      {
+        "author_name": "Connie DeLeo",
+        "author_inst": "Baton Rouge General Hospital"
+      },
+      {
+        "author_name": "Edgardo Tenreiro",
+        "author_inst": "Baton Rouge General Hospital"
+      },
+      {
+        "author_name": "Beverly W Ogden",
+        "author_inst": "Woman's Hospital"
+      },
+      {
+        "author_name": "Stephania A Cormier",
+        "author_inst": "Louisiana State University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "intensive care and critical care medicine"
   },
   {
     "rel_doi": "10.1101/2020.07.17.20156034",
@@ -1262236,65 +1265045,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.15.20154906",
-    "rel_title": "Higher Comorbidities and Early Death is Characteristic of Hospitalized African-American Patients with COVID-19",
+    "rel_doi": "10.1101/2020.07.15.20154971",
+    "rel_title": "Time-dependent dynamic transmission potential and instantaneous reproduction number of COVID-19 pandemic in India.",
     "rel_date": "2020-07-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154906",
-    "rel_abs": "BackgroundAfrican-Americans/Blacks have suffered higher morbidity and mortality from COVID-19 than all other racial groups. This study aims to identify the causes of this health disparity, determine prognostic indicators, and assess efficacy of treatment interventions.\n\nMethodWe performed a retrospective cohort study of clinical features and laboratory data of COVID-19 patients admitted over a five-week period at the height of the pandemic in the United States. This study was performed at an urban academic medical center in New York City, declared a COVID-only facility, serving a majority Black population\n\nResultOf the 1,070 consecutive patients who tested positive for COVID-19, 496 critically ill patients were hospitalized and included in the study. 88% of patients were Black; and a majority (53%) were 61-80 years old with a mean body mass index in the \"obese\" range. 97% had one or more comorbidities. Hypertension was the most common (84%) pre-existing condition followed by diabetes mellitus (57%) and chronic kidney disease (24%). Patients with chronic kidney disease and end-stage renal disease who received hemodialysis were found to have significantly lower mortality, then those who did not receive it, suggesting benefit from hemodialysis (11%, OR, 0.35, CI, 0.17 - 0.69 P=0.001). Age >60 years and coronary artery disease were independent predictors of mortality in multivariate analysis. Cox Proportional Hazards modeling for time to death demonstrated a significantly high ratio for COPD/Asthma, and favorable effects on outcomes for pre-admission ACE inhibitors and ARBs. CRP (180, 283 mg/L), LDH (551, 638 U/L), glucose (182, 163 mg/dL), procalcitonin (1.03, 1.68 ng/mL), and neutrophil / lymphocyte ratio (8.5, 10.0) were predictive of mortality on admission and at 48-96 hrs. Of the 496 inpatients, 48% died, one third of patients died within the first three days of admission. 54/488 patients received invasive mechanical ventilation, of which 87% died and of the remaining patients, 32% died.\n\nCONCLUSIONSCOVID-19 patients in our predominantly Black neighborhood had higher mortality, likely due to higher prevalence of comorbidities. Early dialysis and pre-admission intake of ACE inhibitors/ARBs improved patient outcomes. Early escalation of care based on comorbidities and key laboratory indicators is critical for improving outcomes in African-American patients.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20154971",
+    "rel_abs": "IntroductionDynamic tools and methods to assess the ongoing transmission potential of COVID-19 in India are required. We aim to estimate time-dependent transmissibility of COVID-19 for India using a reproducible framework.\n\nMethodsDaily COVID-19 case incidence time series for India and its states was obtained from https://api.covid19india.org/ and pre-processed. Bayesian approach was adopted to quantify transmissibility at a given location and time, as indicated by the instantaneous reproduction number (Reff). Analysis was carried out in R version 4.0.2 using \"EpiEstim_2.2-3\" package. Serial interval distribution was estimated using \"uncertain_si\" algorithm with inputs of mean, standard deviation, minimum and maximum of mean serial interval as 5.1, 1.2, 3.9 and 7.5 days respectively; and mean, standard deviation, minimum, and maximum of standard deviations of serial interval as 3.7, 0.9, 2.3, and 4.7 respectively with 100 simulations and moving average of seven days.\n\nResultsA total of 9,07,544 cumulative incident cases till July 13th, 2020 were analysed. Daily COVID-19 incidence in the country was seen on the rise; however, transmissibility showed a decline from the initial phases of COVID-19 pandemic in India. The maximum Reff reached at the national level during the study period was 2.57 (sliding week ending April 4th, 2020). Reff on July 13th, 2020 for India was 1.16 with a range from 0.59 to 2.98 across various states/UTs.\n\nConclusionReff provides critical feedback for assessment of transmissibility of COVID-19 and thus is a potential dynamic decision support tool for on-ground public health decision making.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Raavi Gupta",
-        "author_inst": "State University of New York, Downstate Medical Center"
-      },
-      {
-        "author_name": "Raag Agrawal",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "Zaheer Bukhari",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "Absia Jabbar",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "Donghai Wang",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "John Diks",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "Mohamed Alshal",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "Dokpe Yvonne Emechebe",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "F. Charles Brunicardi",
-        "author_inst": "SUNY Downstate Medical Center"
-      },
-      {
-        "author_name": "Jason M Lazar",
-        "author_inst": "SUNY Downstate Medical Center"
+        "author_name": "Gurpreet Singh",
+        "author_inst": "Sree Chitra Tirunal Institute for Medical Sciences & Technology, Trivandrum"
       },
       {
-        "author_name": "Robert Chamberlain",
-        "author_inst": "SUNY Downstate Medical Center"
+        "author_name": "Seema Patrikar",
+        "author_inst": "Armed Forces Medical College, Pune."
       },
       {
-        "author_name": "Aaliya Burza",
-        "author_inst": "SUNY Downstate Medical Center"
+        "author_name": "PS Sarma",
+        "author_inst": "Sree Chitra Tirunal Institute for Medical Sciences & Technology, Trivandrum."
       },
       {
-        "author_name": "M. A. Haseeb",
-        "author_inst": "SUNY Downstate Medical Center"
+        "author_name": "Biju Soman",
+        "author_inst": "Sree Chitra Tirunal Institute for Medical Sciences & Technology, Trivandrum."
       }
     ],
     "version": "1",
@@ -1263706,47 +1266479,71 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2020.07.13.20152231",
-    "rel_title": "A Quantitative Lung Computed Tomography Image Feature for Multi-Center Severity Assessment of COVID-19",
+    "rel_doi": "10.1101/2020.07.13.20153130",
+    "rel_title": "Asthma in COVID-19: An extra chain fitting around the neck?",
     "rel_date": "2020-07-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152231",
-    "rel_abs": "The COVID-19 pandemic has affected millions and congested healthcare systems globally. Hence an objective severity assessment is crucial in making therapeutic decisions judiciously. Computed Tomography (CT)-scans can provide demarcating features to identify severity of pneumonia --commonly associated with COVID-19--in the affected lungs. Here, a quantitative severity assessing chest CT image feature is demonstrated for COVID-19 patients. An open-source multi-center Italian database1 was used, among which 60 cases were incorporated in the study (age 27-86, 71% males) from 27 CT imaging centers. Lesions in the form of opacifications, crazy-paving patterns, and consolidations were segmented. The severity determining feature --Lnorm was quantified and established to be statistically distinct for the three --mild, moderate, and severe classes (p-value<0.0001). The thresholds of Lnorm for a 3-class classification were determined based on the optimum sensitivity/specificity combination from Receiver Operating Characteristic (ROC) analyses. The feature Lnorm classified the cases in the three severity categories with 86.88% accuracy.  Substantial to  almost-perfect intra-rater and inter-rater agreements were achieved involving expert and non-expert based evaluations ({kappa}-score 0.79-0.97). We trained machine learning based classification models and showed Lnorm alone has a superior diagnostic accuracy over standard image intensity and texture features. Classification accuracy was further increased when Lnorm was used for 2-class classification i.e. to delineate the severe cases from non-severe ones with a high sensitivity (97.7%), and specificity (97.49%). Therefore, key highlights of this severity assessment feature are accuracy, lower dependency on expert availability, and wide utility across different imaging centers.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20153130",
+    "rel_abs": "IntroductionThe novel coronavirus disease 2019 (COVID-19) has rapidly spread across the globe, overwhelming healthcare systems and depleting resources. The infection has a wide spectrum of presentations, and pre-existing comorbidities have been found to have a dramatic effect on the disease course and prognosis. We sought to analyze the effect of asthma on the disease progression and outcomes of COVID-19 patients.\n\nMethodsWe conducted a multi-center retrospective study of positively confirmed COVID-19 patients from multiple hospitals in Louisiana. Demographics, medical history, comorbidities, clinical presentation, daily laboratory values, complications, and outcomes data were collected and analyzed. The primary outcome of interest was in-hospital mortality. Secondary outcomes were Intensive Care Unit (ICU) admission, risk of intubation, duration of mechanical ventilation, and length of hospital stay.\n\nResultsA total of 502 COVID-19 patients (72 asthma and 430 non-asthma cohorts) were included in the study. The frequency of asthma in hospitalized cohorts was 14.3%, higher than the national prevalence of asthma (7.7%). Univariate analysis revealed that asthma patients were more likely to be obese (75% vs 54.2%, p=0.001), with higher frequency of intubation (40.3% vs 27.8%, p = 0.036), and required longer duration of hospitalization (15.1{+/-}12.5 vs 11.5{+/-}10.6, p=0.015). After adjustment, multivariable analysis showed that asthmatic patients were not associated with higher risk of ICU admission (OR=1.81, 95%CI=0.98-3.09, p=0.06), endotracheal intubation (OR=1.77, 95%CI=0.99-3.04, p=0.06) or complications (OR=1.37, 95%CI=0.82-2.31, p=0.23). Asthmatic patients were not associated with higher odds of prolonged hospital length of stay (OR=1.48, 95%CI=0.82-2.66, p=0.20) or with the duration of ICU stay (OR=0.76, 95%CI=0.28-2.02, p=0.58). Kaplan-Meier curve showed no significant difference in overall survival of the two groups (p=0.65).\n\nConclusionDespite the increased prevalence of hospitalization in asthmatic COVID-19 patients compared to the general population, after adjustment for other variables, it was neither associated with increased severity nor worse outcomes.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Biswajoy Ghosh",
-        "author_inst": "Indian Institute of Technology Kharagpur"
+        "author_name": "Mohammad Hosny Hussein",
+        "author_inst": "Division of Endocrine and Oncologic Surgery, Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
       },
       {
-        "author_name": "Nikhil Kumar",
-        "author_inst": "Indian Institute of Technology Kharagpur"
+        "author_name": "Eman Ali Toraih",
+        "author_inst": "Division of Endocrine and Oncologic Surgery, Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
       },
       {
-        "author_name": "Nitisha Singh",
-        "author_inst": "National Institute of Technology Durgapur"
+        "author_name": "Abdallah S Attia",
+        "author_inst": "Division of Endocrine and Oncologic Surgery, Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
+      },
+      {
+        "author_name": "Mohanad Youssef",
+        "author_inst": "Division of Endocrine and Oncologic Surgery, Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
+      },
+      {
+        "author_name": "Mahmoud Omar",
+        "author_inst": "Division of Endocrine and Oncologic Surgery, Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
+      },
+      {
+        "author_name": "Nicholas Burley",
+        "author_inst": "Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
+      },
+      {
+        "author_name": "Allen D Zhang",
+        "author_inst": "Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
       },
       {
-        "author_name": "Anup K Sadhu",
-        "author_inst": "EKO CT and MRI Scan Centre, Medical College and Hospitals Campus, Kolkata"
+        "author_name": "Jackson Roos",
+        "author_inst": "Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
       },
       {
-        "author_name": "Nirmalya Ghosh",
-        "author_inst": "Indian Institute of Technology Kharagur"
+        "author_name": "August Houghton",
+        "author_inst": "Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
       },
       {
-        "author_name": "Pabitra Mitra",
-        "author_inst": "Indian Institute of Technology Kharagur"
+        "author_name": "Nedum Aniemeka",
+        "author_inst": "Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
       },
       {
-        "author_name": "Jyotirmoy Chatterjee",
-        "author_inst": "Indian Institute of Technology Kharagur"
+        "author_name": "Mohamed Ahmed Shama",
+        "author_inst": "Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
+      },
+      {
+        "author_name": "Juan Duchesne",
+        "author_inst": "Trauma/Acute Care and Critical Care, Department of Surgery, Tulane, Tulane School of Medicine, New Orleans, LA, 70112, USA"
+      },
+      {
+        "author_name": "Emad Kandil",
+        "author_inst": "Division of Endocrine and Oncologic Surgery, Department of Surgery, Tulane University, School of Medicine, New Orleans, Louisiana, 70112, USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "allergy and immunology"
   },
   {
     "rel_doi": "10.1101/2020.07.13.20152439",
@@ -1265264,31 +1268061,47 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.07.15.176933",
-    "rel_title": "Alignment-free machine learning approaches for the lethality prediction of potential novel human-adapted coronavirus using genomic nucleotide",
+    "rel_doi": "10.1101/2020.07.14.203463",
+    "rel_title": "Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: An endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations",
     "rel_date": "2020-07-15",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.15.176933",
-    "rel_abs": "A newly emerging novel coronavirus appeared and rapidly spread worldwide and World Health Organization declared a pandemic on March 11, 2020. The roles and characteristics of coronavirus have captured much attention due to its power of causing a wide variety of infectious diseases, from mild to severe on humans. The detection of the lethality of human coronavirus is key to estimate the viral toxicity and provide perspective for treatment. We developed alignment-free machine learning approaches for an ultra-fast and highly accurate prediction of the lethality of potential human-adapted coronavirus using genomic nucleotide. We performed extensive experiments through six different feature transformation and machine learning algorithms in combination with digital signal processing to infer the lethality of possible future novel coronaviruses using previous existing strains. The results tested on SARS-CoV, MERS-Cov and SARS-CoV-2 datasets show an average 96.7% prediction accuracy. We also provide preliminary analysis validating the effectiveness of our models through other human coronaviruses. Our study achieves high levels of prediction performance based on raw RNA sequences alone without genome annotations and specialized biological knowledge. The results demonstrate that, for any novel human coronavirus strains, this alignment-free machine learning-based approach can offer a reliable real-time estimation for its viral lethality.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.14.203463",
+    "rel_abs": "Accumulation of mutations within the genome is the primary driving force for viral evolution within an endemic setting. This inherent feature often leads to altered virulence, infectivity and transmissibility as well as antigenic shift to escape host immunity, which might compromise the efficacy of vaccines and antiviral drugs. Therefore, we aimed at genome-wide analyses of circulating SARS-CoV-2 viruses for the emergence of novel co-existing mutations and trace their spatial distribution within India. Comprehensive analysis of whole genome sequences of 441 Indian SARS-CoV-2 strains revealed the occurrence of 33 different mutations, 21 being distinctive to India. Emergence of novel mutations were observed in S glycoprotein (7/33), NSP3 (6/33), RdRp/NSP12 (4/33), NSP2 (2/33) and N (2/33). Non-synonymous mutations were found to be 3.4 times more prevalent than synonymous mutations. We classified the Indian isolates into 22 groups based on the co-existing mutations. Phylogenetic analyses revealed that representative strain of each group divided themselves into various sub-clades within their respective clades, based on the presence of unique co-existing mutations. India was dominated by A2a clade (55.60%) followed by A3 (37.38%) and B (7%), but exhibited heterogeneous distribution among various geographical regions. The A2a clade mostly predominated in East India, Western India and Central India, whereas A3 clade prevailed in South and North India. In conclusion, this study highlights the divergent evolution of SARS-CoV-2 strains and co-circulation of multiple clades in India. Monitoring of the emerging mutations would pave ways for vaccine formulation and designing of antiviral drugs.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Rui YIN",
-        "author_inst": "Nanyang Technological University"
+        "author_name": "Rakesh Sarkar",
+        "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases"
       },
       {
-        "author_name": "Zihan Luo",
-        "author_inst": "Huazhong University of Science and Technology"
+        "author_name": "Suvrotoa Mitra",
+        "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases"
       },
       {
-        "author_name": "Chee Keong Kwoh",
-        "author_inst": "Nanyang Technological University"
+        "author_name": "Pritam Chandra",
+        "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases"
+      },
+      {
+        "author_name": "Priyanka Saha",
+        "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases"
+      },
+      {
+        "author_name": "Anindita Banerjee",
+        "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases"
+      },
+      {
+        "author_name": "Shanta Dutta",
+        "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases"
+      },
+      {
+        "author_name": "Mamta Chawla-Sarkar",
+        "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.07.14.203414",
@@ -1267050,71 +1269863,99 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.07.14.202549",
-    "rel_title": "Targeting heparan sulfate proteoglycan-assisted endocytosis as a COVID-19 therapeutic option",
+    "rel_doi": "10.1101/2020.07.13.20152793",
+    "rel_title": "At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR based tests?: A systematic review of individual participant data",
     "rel_date": "2020-07-14",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.14.202549",
-    "rel_abs": "The cell entry of SARS-CoV-2 has emerged as an attractive drug repurposing target for COVID-19. Here we combine genetics and chemical perturbation to demonstrate that ACE2-mediated entry of SARS-CoV and CoV-2 requires the cell surface heparan sulfate (HS) as an assisting cofactor: ablation of genes involved in HS biosynthesis or incubating cells with a HS mimetic both inhibit Spike-mediated viral entry. We show that heparin/HS binds to Spike directly, facilitates the attachment of viral particles to the cell surface to promote cell entry. We screened approved drugs and identified two classes of inhibitors that act via distinct mechanisms to target this entry pathway. Among the drugs characterized, Mitoxantrone is a potent HS inhibitor, while Sunitinib and BNTX disrupt the actin network to indirectly abrogate HS-assisted viral entry. We further show that drugs of the two classes can be combined to generate a synergized activity against SARS-CoV-2-induced cytopathic effect. Altogether, our study establishes HS as an attachment factor that assists SARS coronavirus cell entry, and reveals drugs capable of targeting this important step in the viral life cycle.",
-    "rel_num_authors": 13,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152793",
+    "rel_abs": "STRUCTURED SUMMARYO_ST_ABSBackgroundC_ST_ABSTests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA), using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity.\n\nMethodsWe conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS- 2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites.\n\nFindingsOf 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from -6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 to 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post- symptom onset.\n\nInterpretationRT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond ten days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias so the positivity rates are probably overestimated.\n\nPANEL: RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThere are numerous reports of negative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcription polymerase chain reaction (RT-PCR) test results in participants with known SARS-CoV-2 infection, and increasing awareness that the ability of RT-PCR tests to detect virus depends on the timing of sample retrieval and anatomical sampling site.\n\nIndividual studies suggest that positive test results from RT-PCR with nasopharyngeal sampling declines within a week of symptoms and that a positive test later in the disease course is more likely from sputum, bronchoalveolar lavage (BAL) or stool, but data are inconsistent.\n\nAdded value of this studyWe searched 5078 titles and abstracts for longitudinal studies reporting individual participant data (IPD) for RT-PCR for participants with COVID-19 linked to either time since symptom onset or time since hospitalisation. Search included SARS-CoV-2 and RT-PCR keywords and MeSH terms. Each included study was subject to careful assessment of risk of bias. This IPD systematic review (SR) addresses RT-PCR test detection rates at different times since symptom onset and hospitalisation for different sampling sites, and summarises the duration of detectable virus. To our knowledge, this is the first rapid SR addressing this topic. We identified 32 studies available as published articles or pre-prints between January 1st and April 24th 2020, including participants sampled at 11 different sampling sites and some participants sampled at more than one site. At earlier time points, nasopharyngeal sampling had the highest virus detection, but the duration of shedding was shorter compared to lower respiratory tract sampling. At 10 to 14 days post-symptom onset, the percentage of positive nasopharyngeal test results was 54% compared to 89% at day 0 to 4. Presence and duration of faecal detection varied by participant, and in nearly half duration was shorter than respiratory sample detection. Virus detection varies for participants and can continue to be detected up to 46 days post-symptom onset or hospitalisation. The included studies were open to substantial risk of bias, so the detection rates are probably overestimates. There was also poor reporting of sampling methods and sparse data on sampling methods that are becoming more widely implemented, such as self-sampling and short nasal swab sampling (anterior nares/mid turbinate).\n\nImplications of all the available evidenceResults from this IPD SR of SARS-CoV-2 testing at different time points and using different anatomical sample sites are important to inform strategies of testing. For prevention of ongoing transmission of SARS-CoV-2, samples for RT-PCR testing need to be taken as soon as possible post-symptom onset, as we confirm that RT-PCR misses more people with infection if sampling is delayed. The percentage of positive RT-PCR tests is also highly dependent on the anatomical site sampled in infected people. Sampling at more than one anatomical site may be advisable as there is variation between individuals in the sites that are infected, as well as the timing of SARS-CoV-2 virus detection at an anatomical site. Testing ten days after symptom onset will lead to a higher frequency of negative tests, particularly if using only upper respiratory tract sampling. However, our estimates may considerably understate the frequency of negative RT-PCR results in people with SARS-CoV- 2 infection. Further investment in this IPD approach is recommended as the amount data available was small given the scale of the pandemic and the importance of the question. More studies, learning from our observations about risk of bias and strengths of example studies (Box 1, Box 2) are urgently needed to inform the optimal sampling strategy by including self-collected samples such as saliva and short nasal swabs. Better reporting of anatomical sampling sites with a detailed methodology on sample collection is also urgently needed.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Qi Zhang",
-        "author_inst": "NIH"
+        "author_name": "Sue Mallett",
+        "author_inst": "University College London, UK"
       },
       {
-        "author_name": "Catherine Chen",
-        "author_inst": "NIH"
+        "author_name": "Joy Allen",
+        "author_inst": "Newcastle University, UK"
       },
       {
-        "author_name": "Manju Swaroop",
-        "author_inst": "NIH"
+        "author_name": "Sara Graziadio",
+        "author_inst": "Newcastle upon Tyne Hospitals NHS Foundation Trust, UK"
       },
       {
-        "author_name": "Miao Xu",
-        "author_inst": "NIH"
+        "author_name": "Stuart A Taylor",
+        "author_inst": "University College London, UK"
       },
       {
-        "author_name": "Lihui Wang",
-        "author_inst": "NIH"
+        "author_name": "Naomi S Sakai",
+        "author_inst": "University College London, UK"
       },
       {
-        "author_name": "Juhyung Lee",
-        "author_inst": "NIH"
+        "author_name": "Kile Green",
+        "author_inst": "Newcastle University, UK"
       },
       {
-        "author_name": "Manisha Pradhan",
-        "author_inst": "NIH"
+        "author_name": "Jana Suklan",
+        "author_inst": "Newcastle University, UK"
       },
       {
-        "author_name": "Min Shen",
-        "author_inst": "NIH"
+        "author_name": "Chris Hyde",
+        "author_inst": "University of Exeter, UK"
       },
       {
-        "author_name": "Zhiji Luo",
-        "author_inst": "NIH"
+        "author_name": "Bethany Shinkins",
+        "author_inst": "University of Leeds, UK"
       },
       {
-        "author_name": "Yue Xu",
-        "author_inst": "NIH"
+        "author_name": "Zhivko Zhelev",
+        "author_inst": "University of Exeter, UK"
       },
       {
-        "author_name": "Wenwei Huang",
-        "author_inst": "NIH"
+        "author_name": "Jaime Peters",
+        "author_inst": "University of Exeter, UK"
       },
       {
-        "author_name": "Wei Zheng",
-        "author_inst": "NIH"
+        "author_name": "Philip Turner",
+        "author_inst": "University of Oxford, UK"
       },
       {
-        "author_name": "Yihong Ye",
-        "author_inst": "NIH"
+        "author_name": "Nia W Roberts",
+        "author_inst": "University of Oxford, UK"
+      },
+      {
+        "author_name": "Lavinia Ferrante di Ruffano",
+        "author_inst": "University of Birmingham, UK"
+      },
+      {
+        "author_name": "Robert Wolff",
+        "author_inst": "Kleijnen Systematic Reviews Ltd, UK"
+      },
+      {
+        "author_name": "Penny Whiting",
+        "author_inst": "University of Bristol, UK"
+      },
+      {
+        "author_name": "Amanda Winter",
+        "author_inst": "Newcastle University, UK"
+      },
+      {
+        "author_name": "Gauraang Bhatnagar",
+        "author_inst": "Frimley Health NHS Foundation Trust, UK"
+      },
+      {
+        "author_name": "Brian D Nicholson",
+        "author_inst": "University of Oxford, UK"
+      },
+      {
+        "author_name": "Steve Halligan",
+        "author_inst": "University College London, UK"
       }
     ],
     "version": "1",
-    "license": "cc0",
-    "type": "new results",
-    "category": "cell biology"
+    "license": "cc_by_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.07.13.20152876",
@@ -1268600,229 +1271441,33 @@
     "category": "health policy"
   },
   {
-    "rel_doi": "10.1101/2020.07.13.20152355",
-    "rel_title": "State-level tracking of COVID-19 in the United States",
+    "rel_doi": "10.1101/2020.07.12.20152157",
+    "rel_title": "Quantifying Respiratory Airborne Particle Dispersion Control Through Improvised Reusable Masks",
     "rel_date": "2020-07-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152355",
-    "rel_abs": "As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly modelled the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We used changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. Nationally, we estimated 3.7% [3.4%-4.0%] of the population had been infected by 1st June 2020, with wide variation between states, and approximately 0.01% of the population was infectious. We also demonstrated that good model forecasts of deaths for the next 3 weeks with low error and good coverage of our credible intervals.",
-    "rel_num_authors": 53,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.12.20152157",
+    "rel_abs": "BackgroundFor much of the SARS-CoV-2 (COVID-19) pandemic, many countries have struggled to offer definitive guidance on the wearing of masks or face coverings to reduce the highly infectious disease transmission resulting from a lack of compelling evidence on the effectiveness of communities wearing masks, and slow acceptance that aerosols are a primary SARS-CoV-2 disease transmission mechanism. Recent studies have shown that masks have been effective in several countries and populations, leaving only a lack of quantitative data on the control of airborne dispersion from human exhalation. This current study specifically has the objective to quantify the effectiveness of non-medical grade washable masks or face coverings in controlling airborne dispersion from exhalation (both droplet and aerosol) by measuring changes in direction, particle cloud velocities, and concentration.\n\nDesignThis randomized effectiveness study used a 10% NaCl nebulized polydisperse particle solution (0.3 m up to 10 m in size) delivered by an exhalation simulator to conduct 94 experiment runs with combinations of 8 different fabrics, 5 mask designs, and airflows for both talking and coughing. Multiple particle sensors were instrumented to measure reduction in aerosol dispersion.\n\nResultsThree-way multivariate analysis of variance establishes that fabric, mask design, and exhalation breath level have a statistically significant effect on changing direction, reducing velocity, or concentrations of airborne particles (Fabric: P = < .001, Wilks {Lambda} = .000; Mask design: P = < .001, Wilks' {Lambda} = .000; Breath level: P = < .001, Wilks' {Lambda} = .004). There were also statistically significant interaction effects between combinations of all primary factors.\n\nConclusions and RelevanceThe application of facial coverings or masks can significantly reduce the airborne dispersion of aerosolized particles from exhalation by diffusing the particle cloud direction and slow down its travel speed. Consequently, the results indicate that wearing masks when coupled with social distance can decrease the potentially inhaled dose of SARS-CoV-2 aerosols or droplets especially where infectious contaminants may exist in shared air spaces. The conclusion is well aligned with the concept of \"time-distance-shielding\" from hazardous materials emergency response. However, the effectiveness varies greatly between the specific fabrics and mask designs used.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "H Juliette T Unwin",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Swapnil Mishra",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Valerie C Bradley",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Axel Gandy",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Thomas A Mellan",
-        "author_inst": "Imperial College"
-      },
-      {
-        "author_name": "Helen Coupland",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Jonathan Ish-Horowicz",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Michaela Andrea Christine Vollmer",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Charles Whittaker",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Sarah L Filippi",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Xiaoyue Xi",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "M\u00e9lodie Monod",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Oliver Ratmann",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Michael Hutchinson",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Fabian Valka",
-        "author_inst": "None"
-      },
-      {
-        "author_name": "Harrison Zhu",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Iwona Hawryluk",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Philip Milton",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Kylie E C Ainslie",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Marc Baguelin",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Adhiratha Boonyasiri",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Nick F Brazeau",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Lorenzo Cattarino",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Zulma M Cucunub\u00e1",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Gina Cuomo-Dannenburg",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Ilaria Dorigatti",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Oliver D Eales",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Jeffrey W Eaton",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Sabinee L van Elsland",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Richard G FitzJohn",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Katy A M Gaythorpe",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "William Green",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Wes Hinsley",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Benjamin Jeffrey",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Edward Knock",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Daniel J Laydon",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "John Lees",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Gemma Nedjati-Gilani",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Pierre Nouvellet",
-        "author_inst": "University of Sussex"
-      },
-      {
-        "author_name": "Lucy C Okell",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Kris V Parag",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Igor Siveroni",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Hayley A Thompson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Patrick Walker",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Caroline E Walters",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Oliver J Watson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Lilith K Whittles",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Azra Ghani",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Neil M Ferguson",
-        "author_inst": "Imperial College London"
-      },
-      {
-        "author_name": "Steven Riley",
-        "author_inst": "Dept Inf Dis Epi, Imperial College"
+        "author_name": "Nathan J Edwards",
+        "author_inst": "The MITRE Corporation"
       },
       {
-        "author_name": "Christl A. Donnelly",
-        "author_inst": "Imperial College London"
+        "author_name": "Rebecca Widrick",
+        "author_inst": "The MITRE Corporation"
       },
       {
-        "author_name": "Samir Bhatt",
-        "author_inst": "Imperial College London"
+        "author_name": "Richard Potember",
+        "author_inst": "The MITRE Corporation"
       },
       {
-        "author_name": "Seth Flaxman",
-        "author_inst": "Imperial College London"
+        "author_name": "Mike Gerschefske",
+        "author_inst": "The MITRE Corporation"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1270242,31 +1272887,95 @@
     "category": "pharmacology and toxicology"
   },
   {
-    "rel_doi": "10.1101/2020.07.12.199364",
-    "rel_title": "Flexibility and mobility of SARS-CoV-2-related protein structures",
-    "rel_date": "2020-07-12",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.12.199364",
-    "rel_abs": "The worldwide CoVid-19 pandemic has led to an unprecedented push across the whole of the scientific community to develop a potent antiviral drug and vaccine as soon as possible. Existing academic, governmental and industrial institutions and companies have engaged in large-scale screening of existing drugs, in vitro, in vivo and in silico. Here, we are using in silico modelling of SARS-CoV-2 drug targets, i.e. SARS-CoV-2 protein structures as deposited on the Protein Databank (PDB). We study their flexibility, rigidity and mobility, an important first step in trying to ascertain their dynamics for further drug-related docking studies. We are using a recent protein flexibility modelling approach, combining protein structural rigidity with possible motion consistent with chemical bonds and sterics. For example, for the SARS-CoV-2 spike protein in the open configuration, our method identifies a possible further opening and closing of the S1 subunit through movement of SB domain. With full structural information of this process available, docking studies with possible drug structures are then possible in silico. In our study, we present full results for the more than 200 thus far published SARS-CoV-2-related protein structures in the PDB.",
-    "rel_num_authors": 3,
+    "rel_doi": "10.1101/2020.07.10.20150045",
+    "rel_title": "Genomic epidemiology reveals multiple introductions and spread of SARS-CoV-2 in the Indian state of Karnataka",
+    "rel_date": "2020-07-11",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20150045",
+    "rel_abs": "An earlier version of this manuscript was removed owing to inclusion of confidential information relating to an individual",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Rudolf A Roemer",
-        "author_inst": "University of Warwick"
+        "author_name": "Chitra Pattabiraman",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
       },
       {
-        "author_name": "Navodya Sophie Roemer",
-        "author_inst": "University of Lincoln"
+        "author_name": "Farhat Habib",
+        "author_inst": "TruFactor-InMobi Group, Bangalore"
       },
       {
-        "author_name": "Anne Katrine Wallis",
-        "author_inst": "University of Warwick"
+        "author_name": "Harsha PK",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Risha Rasheed",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Vijayalakshmi Reddy",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Prameela Dinesh",
+        "author_inst": "Directorate of Health and Family Welfare Services, Government of Karnataka, Bangalore- 560012"
+      },
+      {
+        "author_name": "Tina Damodar",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Nakka Vijay Kiran Reddy",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Kiran Hosallimath",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Anson K George",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Banerjee John",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Amrita Pattanaik",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Narendra Kumar",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Reeta S Mani",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Manjunatha M Venkataswamy",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Shafeeq K Shahul Hameed",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Prakash Kumar B.G.",
+        "author_inst": "Directorate of Health and Family Welfare Services, Government of Karnataka, Bangalore, - 560012"
+      },
+      {
+        "author_name": "Anita Desai",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
+      },
+      {
+        "author_name": "Ravi Vasanthapuram",
+        "author_inst": "Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS)"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "molecular biology"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.07.09.20150086",
@@ -1271708,73 +1274417,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.11.20151365",
-    "rel_title": "Decreased serum levels of inflammaging marker miR-146a are associated with clinical response to tocilizumab in COVID-19 patients",
+    "rel_doi": "10.1101/2020.07.10.20150904",
+    "rel_title": "Serological Tests for SARS-CoV-2 Coronavirus by Commercially Available Point-of-Care and Laboratory Diagnostics in Pre-COVID-19 Samples in Japan",
     "rel_date": "2020-07-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.11.20151365",
-    "rel_abs": "BackgroundCurrent COVID-19 pandemic poses an unprecedented threat to global health and healthcare systems. At least in western countries, the most amount of the death toll is accounted by old people affected by age-related diseases. In this regard, we proposed that COVID-19 severity may be tightly related to inflammaging, i.e. the age-related onset of inflammation, which is responsible for age-related diseases. It has been reported that systemic hyper-inflammation may turn to be detrimental in COVID-19 patients.\n\nObjectiveHere, we exploited a recently closed clinical trial (NCT04315480) on the anti-IL-6 drug tocilizumab to assess whether microRNAs regulating inflammaging can be assessed as biomarkers of drug response and outcome.\n\nMethodsSerum levels of miR-146a-5p, -21-5p, and -126-3p were quantified by RT-PCR and Droplet Digital PCR by two independent laboratories on 30 patients with virologically confirmed COVID-19, characterized by multifocal interstitial pneumonia confirmed by CT-scan and requiring oxygen therapy, and 29 age- and gender-matched healthy control subjects. COVID-19 patients were treated with a single-dose intravenous infusion of 8 mg/kg tocilizumab and categorized into responders and non-responders.\n\nResultsWe showed that COVID-19 patients who did not respond to tocilizumab have lower serum levels of miR-146a-5p after the treatment (p=0.007). Moreover, among non-responders, those with the lowest serum levels of miR-146a-5p experienced the most adverse outcome (p=0.008).\n\nConclusionOur data show that blood-based biomarkers, such as miR-146a-5p, can provide a molecular link between inflammaging and COVID-19 clinical course, thus allowing to enlarge the drug armory against this worldwide health threat.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20150904",
+    "rel_abs": "Serological tests for SARS-CoV-2 coronavirus in pre-COVID-19 samples in Japan showed 1.5%-1.75% positives, and previous surveys might overestimate COVID-19 seroprevalence in several population of Japan. These false negatives could be excluded by combination of different diagnostics to 0.25%.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Jacopo Sabbatinelli",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
-      },
-      {
-        "author_name": "Angelica Giuliani",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
-      },
-      {
-        "author_name": "Giulia Matacchione",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
-      },
-      {
-        "author_name": "Silvia Latini",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
-      },
-      {
-        "author_name": "Noemi Laprovitera",
-        "author_inst": "University of Bologna"
-      },
-      {
-        "author_name": "Giovanni Pomponio",
-        "author_inst": "Azienda Ospedaliera \"Ospedali Riuniti\" di Ancona"
-      },
-      {
-        "author_name": "Alessia Ferrarini",
-        "author_inst": "Azienda Ospedaliera \"Ospedali Riuniti\" di Ancona"
-      },
-      {
-        "author_name": "Silvia Svegliati Baroni",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
-      },
-      {
-        "author_name": "Marianna Pavani",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
-      },
-      {
-        "author_name": "Marco Moretti",
-        "author_inst": "Azienda Ospedaliera \"Ospedali Riuniti\" di Ancona"
-      },
-      {
-        "author_name": "Armando Gabrielli",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
-      },
-      {
-        "author_name": "Antonio Domenico Procopio",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
+        "author_name": "Mariko Harada Sassa",
+        "author_inst": "Kyoto University"
       },
       {
-        "author_name": "Manuela Ferracin",
-        "author_inst": "University of Bologna"
+        "author_name": "Zhaoqing Lyu",
+        "author_inst": "Kyoto University"
       },
       {
-        "author_name": "Massimiliano Bonaf\u00e8",
-        "author_inst": "University of Bologna"
+        "author_name": "Tomoko Fujitani",
+        "author_inst": "Kyoto University"
       },
       {
-        "author_name": "Fabiola Olivieri",
-        "author_inst": "Universit\u00e0 Politecnica delle Marche"
+        "author_name": "Kouji H. Harada",
+        "author_inst": "Kyoto University"
       }
     ],
     "version": "1",
@@ -1273406,35 +1276071,67 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.11.198770",
-    "rel_title": "ACE2-expressing endothelial cells in aging mouse brain",
-    "rel_date": "2020-07-11",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.11.198770",
-    "rel_abs": "Angiotensin-converting enzyme 2 (ACE2) is a key receptor mediating the entry of SARS-CoV-2 into the host cell. Through a systematic analysis of publicly available mouse brain sc/snRNA-seq data, we found that ACE2 is specifically expressed in small sub-populations of endothelial cells and mural cells, namely pericytes and vascular smooth muscle cells. Further, functional changes in viral mRNA transcription and replication, and impaired blood-brain barrier regulation were most prominently implicated in the aged, ACE2-expressing endothelial cells, when compared to the young adult mouse brains. Concordant EC transcriptomic changes were further found in normal aged human brains. Overall, this work reveals an outline of ACE2 distribution in the mouse brain and identify putative brain host cells that may underlie the selective susceptibility of the aging brain to viral infection.",
-    "rel_num_authors": 4,
+    "rel_doi": "10.1101/2020.07.06.20147827",
+    "rel_title": "Clinical Features of Hemodialysis (HD) patients confirmed with Coronavirus Disease 2019 (COVID-19): a Retrospective Case-Control Study",
+    "rel_date": "2020-07-10",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147827",
+    "rel_abs": "BackgroundSince December 2019, Coronavirus Disease 2019(COVID-19) occurred in wuhan, China, and outbreaked rapidly into a global pandemic. This current poses great challenges to hemodialysis (HD) patients.\n\nObjectiveTo make a comprehensive evaluation and comparison between HD patients confirmed with COVID-19 and the general HD patients.\n\nMethodsHD patients confirmed with COVID-19 in Wuhan No.5 Hospital were admitted as confirmed group from Jan 10 to Mar 15, 2020. And HD patients not infected in our dialysis center were chosen as control group. General characteristics, laboratory indicators were retrospectively collected, analyzed and compared.\n\nResultsA total of 142 cases were admitted, including 43 cases in confirmed group and 99 in control group. Body mass index (BMI) was slightly lower in confirmed group than that in control group (P=0.011). The proportion of one or less underlying disease in confirmed group(51.16%) was higher than that in control group(14.14%)(P< 0.001), and the proportion of three or more underlying diseases in confirmed group(11.63%) was lower than that in control group(52.53%)(P< 0.001). Patients in confirmed group exhibited significantly lower hemoglobin, lymphocyte count, and lymphocyte percentage, but higher neutrophil percentage, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein, aspartate transaminase, and alkaline phosphatase. There was no significant difference in age, gender, dialysis age, primary disease, the using of ACEI/ARB, platelet-to-lymphocyte ratio (PLR), and other indicators between the two groups.\n\nConclusionsFaced with Severe Acute Respiratory Syndrome-CoV-2 (SARS-CoV-2), HD patients with lower BMI and hemoglobin were more susceptible to be infected, which might be related to malnutrition. Once confirmed with COVID-19, HD patients expressed obviously dis-regulated of inflammation and immune.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "SU Bin Lim",
-        "author_inst": "Johns Hopkins University, School of Medicine"
+        "author_name": "Xiaohui Wang",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
       },
       {
-        "author_name": "Valina L. Dawson",
-        "author_inst": "Johns Hopkins University, School of Medicine"
+        "author_name": "Huan Zhou",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
       },
       {
-        "author_name": "Ted M. Dawson",
-        "author_inst": "Johns Hopkins University, School of Medicine"
+        "author_name": "Xiaofen Xiao",
+        "author_inst": "Department of Nutrition, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
       },
       {
-        "author_name": "Sung-Ung Kang",
-        "author_inst": "Johns Hopkins University, School of Medicine"
+        "author_name": "Xianhua Tan",
+        "author_inst": "Department of Radiology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Xin Zhang",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Yong He",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Jing Li",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Guosheng Yang",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Mingmei Li",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Duan Liu",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Shanshan Han",
+        "author_inst": "Department of Nephrology, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
+      },
+      {
+        "author_name": "Haibo Kuang",
+        "author_inst": "Department of Nutrition, Wuhan No.5 Hospital, Wuhan, Hubei Province, 430050, China"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
-    "type": "new results",
-    "category": "neuroscience"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "nephrology"
   },
   {
     "rel_doi": "10.1101/2020.07.08.20149161",
@@ -1275284,47 +1277981,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.08.20149146",
-    "rel_title": "Recurrent Neural Reinforcement Learning for Counterfactual Evaluation of Public Health Interventions on the Spread of Covid-19 in the world",
+    "rel_doi": "10.1101/2020.07.08.20148742",
+    "rel_title": "Disproportionate incidence of COVID-19 in African Americans correlates with dynamic segregation",
     "rel_date": "2020-07-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.08.20149146",
-    "rel_abs": "As the Covid-19 pandemic soars around the world, there is urgent need to forecast the expected number of cases worldwide and the length of the pandemic before receding and implement public health interventions for significantly stopping the spread of Covid-19. Widely used statistical and computer methods for modeling and forecasting the trajectory of Covid-19 are epidemiological models. Although these epidemiological models are useful for estimating the dynamics of transmission of epidemics, their prediction accuracies are quite low. Alternative to the epidemiological models, the reinforcement learning (RL) and causal inference emerge as a powerful tool to select optimal interventions for worldwide containment of Covid-19. Therefore, we formulated real-time forecasting and evaluation of multiple public health intervention problems into off-policy evaluation (OPE) and counterfactual outcome forecasting problems and integrated RL and recurrent neural network (RNN) for exploring public health intervention strategies to slow down the spread of Covid-19 worldwide, given the historical data that may have been generated by different public health intervention policies. We applied the developed methods to real data collected from January 22, 2020 to July 30, 2020 for real-time forecasting the confirmed cases of Covid-19 across the world. We observed that the number of new cases of Covid-19 worldwide reached a peak (407,205) on July 24, 2020 and forecasted that the number of laboratory-confirmed cumulative cases of Covid-19 will pass 20 million as of August 22, 2020. The results showed that outbreak of Covid-19 worldwide has peaked and is on the decline",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.08.20148742",
+    "rel_abs": "Socio-economic disparities quite often have a central role in the unfolding of large-scale catastrophic events. One of the most concerning aspects of the ongoing COVID-19 pandemics [1] is that it disproportionately affects people from Black and African American backgrounds [2-6], creating an unexpected infection gap. Interestingly, the abnormal impact on these ethnic groups seem to be almost uncorrelated with other risk factors, including co-morbidity, poverty, level of education, access to healthcare, residential segregation, and response to cures [7-11]. A proposed explanation for the observed incidence gap is that people from African American backgrounds are more often employed in low-income service jobs, and are thus more exposed to infection through face-to-face contacts [12], but the lack of direct data has not allowed to draw strong conclusions in this sense so far. Here we introduce the concept of dynamic segregation, that is the extent to which a given group of people is internally clustered or exposed to other groups, as a result of mobility and commuting habits. By analysing census and mobility data on more than 120 major US cities, we found that the dynamic segregation of African American communities is significantly associated with the weekly excess COVID-19 incidence and mortality in those communities. The results confirm that knowing where people commute to, rather than where they live, is much more relevant for disease modelling.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Qiyang Ge",
-        "author_inst": "Fudan University"
-      },
-      {
-        "author_name": "Zixin Hu",
-        "author_inst": "fudan University"
-      },
-      {
-        "author_name": "Kai Zhang",
-        "author_inst": "University of Texas School of Public Health"
-      },
-      {
-        "author_name": "Shudi Li",
-        "author_inst": "University of Texas School of Public Health"
-      },
-      {
-        "author_name": "Wei Lin",
-        "author_inst": "Fudan University"
+        "author_name": "Aleix Bassolas",
+        "author_inst": "Queen Mary University of London"
       },
       {
-        "author_name": "Li Jin",
-        "author_inst": "Fudan University"
+        "author_name": "Sandro Sousa",
+        "author_inst": "Queen Mary University of London"
       },
       {
-        "author_name": "Momiao Xiong",
-        "author_inst": "University of Texas School of Public Health"
+        "author_name": "Vincenzo Nicosia",
+        "author_inst": "Queen mary University of London"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.07.08.20148965",
@@ -1277446,91 +1280127,107 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.09.194639",
-    "rel_title": "Decline of humoral responses against SARS-CoV-2 Spike in convalescent individuals",
+    "rel_doi": "10.1101/2020.07.08.194456",
+    "rel_title": "Human B cell clonal expansion and convergent antibody responses to SARS-CoV-2",
     "rel_date": "2020-07-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.09.194639",
-    "rel_abs": "In the absence of effective vaccines and with limited therapeutic options, convalescent plasma is being collected across the globe for potential transfusion to COVID-19 patients. The therapy has been deemed safe and several clinical trials assessing its efficacy are ongoing. While it remains to be formally proven, the presence of neutralizing antibodies is thought to play a positive role in the efficacy of this treatment. Indeed, neutralizing titers of [&ge;]1:160 have been recommended in some convalescent plasma trials for inclusion. Here we performed repeated analyses at one-month interval on 31 convalescent individuals to evaluate how the humoral responses against the SARS-CoV-2 Spike, including neutralization, evolve over time. We observed that receptor-binding domain (RBD)-specific IgG slightly decreased between six and ten weeks after symptoms onset but RBD-specific IgM decreased much more abruptly. Similarly, we observed a significant decrease in the capacity of convalescent plasma to neutralize pseudoparticles bearing SARS-CoV-2 S wild-type or its D614G variant. If neutralization activity proves to be an important factor in the clinical efficacy of convalescent plasma transfer, our results suggest that plasma from convalescent donors should be recovered rapidly after symptoms resolution.",
-    "rel_num_authors": 18,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.08.194456",
+    "rel_abs": "During virus infection B cells are critical for the production of antibodies and protective immunity. Here we show that the human B cell compartment in patients with diagnostically confirmed SARS-CoV-2 and clinical COVID-19 is rapidly altered with the early recruitment of B cells expressing a limited subset of IGHV genes, progressing to a highly polyclonal response of B cells with broader IGHV gene usage and extensive class switching to IgG and IgA subclasses with limited somatic hypermutation in the initial weeks of infection. We identify extensive convergence of antibody sequences across SARS-CoV-2 patients, highlighting stereotyped naive responses to this virus. Notably, sequence-based detection in COVID-19 patients of convergent B cell clonotypes previously reported in SARS-CoV infection predicts the presence of SARS-CoV/SARS-CoV-2 cross-reactive antibody titers specific for the receptor-binding domain. These findings offer molecular insights into shared features of human B cell responses to SARS-CoV-2 and other zoonotic spillover coronaviruses.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Guillaume Beaudoin-Bussi\u00e8res",
-        "author_inst": "CRCHUM"
+        "author_name": "Sandra Cathrine Abel Nielsen",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Annemarie Laumaea",
-        "author_inst": "Universit\u00e9 de Montr\u00e9al"
+        "author_name": "Fan Yang",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Sai Priya Anand",
-        "author_inst": "CRCHUM / McGill"
+        "author_name": "Katherine JL Jackson",
+        "author_inst": "Garvan Institute of Medical Research"
       },
       {
-        "author_name": "J\u00e9r\u00e9mie Pr\u00e9vost",
-        "author_inst": "CRCHUM / Universit\u00e9 de Montr\u00e9al"
+        "author_name": "Ramona A. Hoh",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Romain Gasser",
-        "author_inst": "Universit\u00e9 de Montr\u00e9al"
+        "author_name": "Katharina R\u00f6ltgen",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Guillaume Goyette",
-        "author_inst": "CRCHUM"
+        "author_name": "Bryan Stevens",
+        "author_inst": "Stanford University School of Medicine"
       },
       {
-        "author_name": "Halima Medjahed",
-        "author_inst": "CRCHUM"
+        "author_name": "Ji-Yeun Lee",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Jos\u00e9ee Perreault",
-        "author_inst": "H\u00e9ma-Qu\u00e9bec"
+        "author_name": "Arjun Rustagi",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Tony Tremblay",
-        "author_inst": "H\u00e9ma-Qu\u00e9bec"
+        "author_name": "Angela J. Rogers",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Antoine Lewin",
-        "author_inst": "H\u00e9ma-Qu\u00e9bec"
+        "author_name": "Abigail E. Powell",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Laurie Gokool",
-        "author_inst": "CRCHUM"
+        "author_name": "Javaria Najeeb",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Chantal Morrisseau",
-        "author_inst": "CRCHUM"
+        "author_name": "Ana Rita Otrelo-Cardoso",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Philippe B\u00e9gin",
-        "author_inst": "CHU Ste-Justine"
+        "author_name": "Kathryn E Yost",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Cecile Tremblay",
-        "author_inst": "CRCHUM"
+        "author_name": "Bence Daniel",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Val\u00e9rie Martel-Laferri\u00e8re",
-        "author_inst": "CRCHUM"
+        "author_name": "Howard Y Chang",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Jonathan Richard",
-        "author_inst": "Centre de Recherche du CHUM"
+        "author_name": "Ansuman T Satpathy",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Ren\u00e9e Bazin",
-        "author_inst": "H\u00e9ma-Qu\u00e9bec"
+        "author_name": "Theodore S. Jardetzky",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Andr\u00e9s Finzi",
-        "author_inst": "CRCHUM, Universit\u00e9 de Montr\u00e9al"
+        "author_name": "Peter S. Kim",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Taia T. Wang",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Benjamin A. Pinsky",
+        "author_inst": "Stanford University School of Medicine"
+      },
+      {
+        "author_name": "Catherine A Blish",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Scott D Boyd",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.07.08.194209",
@@ -1279351,93 +1282048,37 @@
     "category": "medical education"
   },
   {
-    "rel_doi": "10.1101/2020.07.07.20148304",
-    "rel_title": "COVID-19 Mortality Risk Assessment: An International Multi-Center Study",
+    "rel_doi": "10.1101/2020.07.07.20148213",
+    "rel_title": "No evidence of viral polymorphisms associated with Paediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2 (PIMS-TS).",
     "rel_date": "2020-07-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20148304",
-    "rel_abs": "BackgroundTimely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients.\n\nMethodsDe-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts.\n\nFindingsThe derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation ([&le;] 93%), elevated levels of C-reactive protein ([&ge;] 130 mg/L), blood urea nitrogen ([&ge;] 18 mg/dL), and blood creatinine ([&ge;] 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-of-sample AUCs of 0.90 (95% CI, 0.87-0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88-0.95) on Seville patients, 0.87 (95% CI, 0.84-0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76-0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality_calculator and is currently in clinical use.\n\nInterpretationThe CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, BioRxiv, MedRxiv, arXiv, and SSRN for peer-reviewed articles, preprints, and research reports in English from inception to March 25th, 2020 focusing on disease severity and mortality risk scores for patients that had been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Earlier investigations showed promise at predicting COVID-19 disease severity using data at admission. However, existing work was limited by its data scope, either relying on a single center with rich clinical information or broader cohort with sparse clinical information. No analysis has leveraged Electronic Health Records data from an international multi-center cohort from both Europe and the United States.\n\nAdded value of this studyWe present the first multi-center COVID-19 mortality risk study that uses Electronic Health Records data from 3,062 patients across four different countries, including Greece, Italy, Spain, and the United States, encompassing 33 hospitals. We employed state-of-the-art machine learning techniques to develop a personalized COVID-19 mortality risk (CMR) score for hospitalized patients upon admission based on clinical features including vitals, lab results, and comorbidities. The model validates clinical findings of mortality risk factors and exhibits strong performance, with AUCs ranging from 0.81 to 0.92 across external validation cohorts. The model identifies increased age as a primary mortality predictor, consistent with observed disease trends and subsequent public health guidelines. Additionally, among the vital and lab values collected at admission, decreased oxygen saturation ([&le;] 93%) and elevated levels of C-reactive protein ([&ge;] 130 mg/L), blood urea nitrogen ([&ge;] 18 mg/dL), blood creatinine ([&ge;] 1.2 mg/dL), and blood glucose ([&ge;]180 mg/dL) are highlighted as key biomarkers of mortality risk. These findings corroborate previous studies that link COVID-19 severity to hypoxemia, impaired kidney function, and diabetes. These features are also consistent with risk factors used in severity risk scores for related respiratory conditions such as community-acquired pneumonia.\n\nImplications of all the available evidenceOur work presents the development and validation of a personalized mortality risk score. We take a data-driven approach to derive insights from Electronic Health Records data spanning Europe and the United States. While many existing papers on COVID-19 clinical characteristics and risk factors are based on Chinese hospital data, the similarities in our findings suggest consistency in the disease characteristics across international cohorts. Additionally, our machine learning model offers a novel approach to understanding the disease and its risk factors. By creating a single comprehensive risk score that integrates various admission data components, the calculator offers a streamlined way of evaluating COVID-19 patients upon admission to augment clinical expertise. The CMR model provides a valuable clinical decision support tool for patient triage and care management, improving risk estimation early within admission, that can significantly affect the daily practice of physicians.",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20148213",
+    "rel_abs": "Generally, children and teenagers do not become seriously ill with COVID-19. However, in countries with high rates of coronavirus disease, children with the syndrome COVID-19 associated inflammation syndrome referred to as PIMS-TS have been reported. Similarities noted between SARS-CoV-2 Spike protein sequences and those of other super antigens has prompted the suggestion that this might be the mechanism by SARS-CoV-ST triggers PIMS-TS. It has also been suggested that the D614G variant found more commonly in the US and across European countries may explain why PIMS-TS appears to be common in these countries. Here we analysed viral sequences from 13 paediatric COVID-19 patients of whom five were diagnosed with PIMS-TS. This is the first characterisation of viruses from PIMS-TS patients. In contrast to what has been hypothesised, we found no evidence of unique sequences associated with the viruses from PIMS-TS patients.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Dimitris Bertsimas",
-        "author_inst": "Massachusetts Institute of Technology"
-      },
-      {
-        "author_name": "Galit Lukin",
-        "author_inst": "Massachusetts Institute of Technology"
-      },
-      {
-        "author_name": "Luca Mingardi",
-        "author_inst": "Massachusetts Institute of Technology"
-      },
-      {
-        "author_name": "Omid Nohadani",
-        "author_inst": "Benefits Science Technologies"
-      },
-      {
-        "author_name": "Agni Orfanoudaki",
-        "author_inst": "Massachusetts Institute of Technology"
-      },
-      {
-        "author_name": "Bartolomeo Stellato",
-        "author_inst": "Princeton University"
-      },
-      {
-        "author_name": "Holly Wiberg",
-        "author_inst": "Massachusetts Institute of Technology"
-      },
-      {
-        "author_name": "Sara Gonzalez-Garcia",
-        "author_inst": "Institute of Biomedicine of Seville (IBIS), Virgen del Rocio University Hospital, CSIC, University of Seville"
-      },
-      {
-        "author_name": "Carlos Luis Parra-Calderon",
-        "author_inst": "Institute of Biomedicine of Seville (IBIS), Virgen del Rocio University Hospital, CSIC, University of Seville"
-      },
-      {
-        "author_name": "- The Hellenic COVID-19 Study Group",
-        "author_inst": ""
-      },
-      {
-        "author_name": "Kenneth Robinson",
-        "author_inst": "Hartford HealthCare"
-      },
-      {
-        "author_name": "Michelle Schneider",
-        "author_inst": "Hartford HealthCare"
-      },
-      {
-        "author_name": "Barry Stein",
-        "author_inst": "Hartford HealthCare"
-      },
-      {
-        "author_name": "Alberto Estirado",
-        "author_inst": "HM Hospitals"
-      },
-      {
-        "author_name": "Lia a Beccara",
-        "author_inst": "Azienda Socio-Sanitaria Territoriale di Cremona"
+        "author_name": "Juanita Pang",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Rosario Canino",
-        "author_inst": "Azienda Socio-Sanitaria Territoriale di Cremona"
+        "author_name": "Florencia A.T. Boshier",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Martina Dal Bello",
-        "author_inst": "Massachusetts Institute of Technology"
+        "author_name": "Nele Alders",
+        "author_inst": "Great Ormond Street Hospital for Children NHS Foundation Trust"
       },
       {
-        "author_name": "Federica Pezzetti",
-        "author_inst": "Azienda Socio-Sanitaria Territoriale di Cremona"
+        "author_name": "Garth Dixon",
+        "author_inst": "Great Ormond Street Hospital for Children NHS Foundation Trust"
       },
       {
-        "author_name": "Angelo Pan",
-        "author_inst": "Azienda Socio-Sanitaria Territoriale di Cremona"
+        "author_name": "Judith Breuer",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1281065,27 +1283706,47 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.06.182972",
-    "rel_title": "Unique transcriptional changes in coagulation cascade genes in SARS-CoV-2-infected lung epithelial cells: A potential factor in COVID-19 coagulopathies",
+    "rel_doi": "10.1101/2020.07.07.192005",
+    "rel_title": "A Fluorescence-based High Throughput-Screening assay for the SARS-CoV RNA synthesis complex",
     "rel_date": "2020-07-07",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.06.182972",
-    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly become a global pandemic. In addition to the acute pulmonary symptoms of COVID-19 (the disease associated with SARS-CoV-2 infection), pulmonary and distal coagulopathies have caused morbidity and mortality in many patients. Currently, the molecular pathogenesis underlying COVID-19 associated coagulopathies are unknown. While there are many theories for the cause of this pathology, including hyper inflammation and excess tissue damage, the cellular and molecular underpinnings are not yet clear. By analyzing transcriptomic data sets from experimental and clinical research teams, we determined that changes in the gene expression of genes important in the extrinsic coagulation cascade in the lung epithelium may be important triggers for COVID-19 coagulopathy. This regulation of the extrinsic blood coagulation cascade is not seen with influenza A virus (IAV)-infected NHBEs suggesting that the lung epithelial derived coagulopathies are specific to SARS-Cov-2 infection. This study is the first to identify potential lung epithelial cell derived factors contributing to COVID-19 associated coagulopathy.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC=\"FIGDIR/small/182972v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (42K):\norg.highwire.dtl.DTLVardef@93cfb7org.highwire.dtl.DTLVardef@2a23c9org.highwire.dtl.DTLVardef@93623borg.highwire.dtl.DTLVardef@161e25_HPS_FORMAT_FIGEXP  M_FIG C_FIG AUTHOR SUMMARYO_ST_ABSWhy was this study done?C_ST_ABSO_LISevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly become a global pandemic.\nC_LIO_LIIn addition to the acute pulmonary symptoms of COVID-19 (the disease associated with SARS-CoV-2 infection), pulmonary and distal coagulopathies have caused morbidity and mortality in many patients.\nC_LIO_LICurrently, the molecular pathogenesis underlying COVID-19 associated coagulopathies are unknown. Understanding the molecular basis of dysregulated blood coagulation during SARS-CoV-2 infection may help promote new therapeutic strategies to mitigate these complications in COVID-19 patients.\nC_LI\n\nWhat did the researchers do and find?O_LIWe analyzed three publicly available RNA sequencing datasets to identify possible molecular etiologies of COVID-19 associated coagulopathies. These data sets include sequencing libraries from clinically isolated samples of bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells (PBMCs) from SARS-CoV-2 positive patients and healthy controls. We also analyzed a publicly available RNA sequencing dataset derived from in vitro SARS-CoV-2 infected primary normal human bronchial epithelial (NHBE) cells and mock infected samples.\nC_LIO_LIPathway analysis of both NHBE and BALF differential gene expression gene sets. We found that SARS-CoV-2 infection induces the activation of the extrinsic blood coagulation cascade and suppression of the plasminogen activation system in both NHBEs and cells isolated from the BALF. PBMCs did not differentially express genes regulating blood coagulation.\nC_LIO_LIComparison with influenza A virus (IAV)-infected NHBEs revealed that the regulation of the extrinsic blood coagulation cascade is unique to SARS-CoV-2, and not seen with IAV infection.\nC_LI\n\nWhat do these findings mean?O_LIThe hyper-activation of the extrinsic blood coagulation cascade and the suppression of the plasminogen activation system in SARS-CoV-2 infected epithelial cells may drive diverse coagulopathies in the lung and distal organ systems.\nC_LIO_LIThe gene transcription pattern in SARS-CoV-2 infected epithelial cells is distinct from IAV infected epithelial cells with regards to the regulation of blood coagulation.\nC_LI",
-    "rel_num_authors": 2,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.07.192005",
+    "rel_abs": "The Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) emergence in 2003 introduced the first serious human coronavirus pathogen to an unprepared world. To control emerging viruses, existing successful anti(retro)viral therapies can inspire antiviral strategies, as conserved viral enzymes (eg., viral proteases and RNA-dependent RNA polymerases) represent targets of choice. Since 2003, much effort has been expended in the characterization of the SARS-CoV replication/transcription machinery. Until recently, a pure and highly active preparation of SARS-CoV recombinant RNA synthesis machinery was not available, impeding target-based high throughput screening of drug candidates against this viral family. The current Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic revealed a new pathogen whose RNA synthesis machinery is highly (>96% aa identity) homologous to SARS-CoV. This phylogenetic relatedness highlights the potential use of conserved replication enzymes to discover inhibitors against this significant pathogen, which in turn, contributes to scientific preparedness against emerging viruses. Here, we report the use of a purified and highly active SARS-CoV replication/transcription complex (RTC) to set-up a high-throughput screening of Coronavirus RNA synthesis inhibitors. The screening of a small (1,520 compounds) chemical library of FDA-approved drugs demonstrates the robustness of our assay and will allow to speed-up drug repositioning or novel drug discovery against the SARS-CoV-2.\n\nPrinciple of SARS-CoV RNA synthesis detection by a fluorescence-based high throughput screening assay\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC=\"FIGDIR/small/192005v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (20K):\norg.highwire.dtl.DTLVardef@e8122dorg.highwire.dtl.DTLVardef@18557org.highwire.dtl.DTLVardef@1d95362org.highwire.dtl.DTLVardef@f15222_HPS_FORMAT_FIGEXP  M_FIG C_FIG Highlights- A new SARS-CoV non radioactive RNA polymerase assay is described\n- The robotized assay is suitable to identify RdRp inhibitors based on HTS",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Ethan S. FitzGerald",
-        "author_inst": "Brown University"
+        "author_name": "Cecilia Eydoux",
+        "author_inst": "AMU"
       },
       {
-        "author_name": "Amanda M. Jamieson",
-        "author_inst": "Brown University"
+        "author_name": "Veronique Fattorini",
+        "author_inst": "CNRS-AMU"
+      },
+      {
+        "author_name": "Ashleigh Shannon",
+        "author_inst": "CNRS-AMU"
+      },
+      {
+        "author_name": "Thi-Tuyet-Nhung Le",
+        "author_inst": "CNRS-AMU"
+      },
+      {
+        "author_name": "Bruno Didier",
+        "author_inst": "Univ. Strasbourg"
+      },
+      {
+        "author_name": "Bruno Canard",
+        "author_inst": "CNRS"
+      },
+      {
+        "author_name": "Jean-Claude Guillemot",
+        "author_inst": "AMU"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "pathology"
+    "category": "biochemistry"
   },
   {
     "rel_doi": "10.1101/2020.07.07.190546",
@@ -1282287,33 +1284948,29 @@
     "category": "genetic and genomic medicine"
   },
   {
-    "rel_doi": "10.1101/2020.07.06.20147751",
-    "rel_title": "COVID-19 presenting as anosmia and dysgeusia in New York City emergency departments, March - April, 2020",
+    "rel_doi": "10.1101/2020.07.06.20147702",
+    "rel_title": "COVID-19 screening strategies that permit the safe re-opening of college campuses",
     "rel_date": "2020-07-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147751",
-    "rel_abs": "BackgroundIncreasing evidence has been emerging of anosmia and dysgeusia as frequently reported symptoms in COVID-19. Improving our understanding of these presenting symptoms may facilitate the prompt recognition of the disease in emergency departments and prevent further transmission.\n\nMethodsWe examined a cross-sectional cohort using New York City emergency department syndromic surveillance data for March and April 2020. Emergency department visits for anosmia and/or dysgeusia were identified and subsequently matched to the Electronic Clinical Laboratory Reporting System to determine testing results for SARS-CoV-2.\n\nResultsOf the 683 patients with anosmia and/or dysgeusia included, SARS-CoV-2 testing was performed for 232 (34%) and 168 (72%) were found to be positive. Median age of all patients presenting with anosmia and/or dysgeusia symptoms was 38, and 54% were female. Anosmia and/or dysgeusia was the sole complaint of 158 (23%) patients, of whom 35 were tested for SARS-CoV-2 and 23 (66%) were positive. While the remaining patients presented with at least one other symptom, nearly half of all patients (n=334, 49%) and more than a third of those who tested positive (n=62, 37%) did not have any of the CDC-established symptoms used for screening of COVID-19 such as fever, cough, shortness of breath, or sore throat.\n\nConclusions and RelevanceAnosmia and/or dysgeusia have been frequent complaints among patients presenting to emergency departments during the COVID-19 pandemic, and, while only a small proportion of patients ultimately underwent testing for SARS-CoV-19, the majority of patients tested have been positive. Anosmia and dysgeusia likely represent underrecognized symptoms of COVID-19 but may have important future implications in disease diagnosis and surveillance.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147702",
+    "rel_abs": "ImportanceThe COVID-19 pandemic poses an existential threat to many US residential colleges: either they open their doors to students in September or they risk serious financial consequences.\n\nObjectiveTo define SARS-CoV-2 screening performance standards that would permit the safe return of students to campus for the Fall 2020 semester.\n\nDesignDecision and cost-effectiveness analysis linked to a compartmental epidemic model to evaluate campus screening using tests of varying frequency (daily-weekly), sensitivity (70%-99%), specificity (98%-99.7%), and cost ($10-$50/test). Reproductive numbers Rt = {1.5, 2.5, 3.5} defined three epidemic scenarios, with additional infections imported via exogenous shocks. We generally adhered to US government guidance for parameterization data.\n\nParticipantsA hypothetical cohort of 5000 college-age, uninfected students.\n\nMain Outcome(s) and Measure(s)Cumulative tests, infections, and costs; daily isolation dormitory census; incremental cost-effectiveness; and budget impact. All measured over an 80-day, abbreviated semester.\n\nResultsWith Rt = 2.5, daily screening with a 70% sensitive, 98% specific test produces 85 cumulative student infections and isolation dormitory daily census averaging 108 (88% false positives). Screening every 2 (7) days nets 135 (3662) cumulative infections and daily isolation census 66 (252) with 73% (4%) false positives. Across all scenarios, test frequency exerts more influence on outcomes than test sensitivity. Cost-effectiveness analysis selects screening every {2, 1, 7} days with a 70% sensitive test as the preferred strategy for Rt = {2.5, 3.5, 1.5}, implying a screening cost of {$470, $920, $120} per student per semester.\n\nConclusions & RelevanceRapid, inexpensive and frequently conducted screening - even if only 70% sensitive - would be cost-effective and produce a modest number of COVID-19 infections. While the optimal screening frequency hinges on the success of behavioral interventions to reduce the base severity of transmission (Rt), this could permit the safe return of student to campus.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSWhat SARS-CoV-2 screening and isolation program will keep U.S. residential college students safe and permit the reopening of campuses?\n\nFindingsFrequent screening (every 2 or 3 days) of all students with a low-sensitivity, high-specificity test will control outbreaks with manageable isolation dormitory utilization at a justifiable cost.\n\nMeaningCampuses can safely reopen in the Fall 2020 but success hinges on frequent screening and uncompromising, continuous attention to basic prevention and behavioral interventions to reduce the baseline severity of transmission.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Tina Z. Wang",
-        "author_inst": "Weill Cornell Medicine"
-      },
-      {
-        "author_name": "Jessica Sell",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
+        "author_name": "A David Paltiel",
+        "author_inst": "Yale School of Public Health"
       },
       {
-        "author_name": "Don Weiss",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
+        "author_name": "Amy Zheng",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Ramona Lall",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
+        "author_name": "Rochelle P Walensky",
+        "author_inst": "Medical Practice Evaluation Center, Division of Infectious Diseases, Massachusetts General Hospital and Harvard Medical School, Boston, MA"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1283713,41 +1286370,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.03.20145797",
-    "rel_title": "Dengue antibodies can cross-react with SARS-CoV-2 and vice versa-Antibody detection kits can give false-positive results for both viruses in regions where both COVID-19 and Dengue co-exist",
+    "rel_doi": "10.1101/2020.06.29.20131367",
+    "rel_title": "Evaluation of Viasure SARS-CoV-2 RT-qPCR kit (CerTest Biotec) using CDC FDA EUA RT-qPCR kit as a gold standard.",
     "rel_date": "2020-07-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20145797",
-    "rel_abs": "Five of thirteen Dengue antibody-positive serum samples, dated 2017 (pre-dating the COVID-19 outbreak) produced false-positive results in SARS-CoV-2 IgG/IgM rapid strip tests. Our results emphasize the importance of NAT and/or virus antigen tests to complement sero-surveillance for definitive diagnosis of COVID-19/Dengue in regions where both viruses are co-endemic.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20131367",
+    "rel_abs": "BackgroundSeveral RT-qPCR kits are available for SARS-CoV-2 diagnosis, some of them with Emergency Use Authorization (EUA) by FDA, but most of them lacking of proper evaluation studies due to covid19 emergency.\n\nObjectiveWe evaluated Viasure RT-qPCR kit (CerTest Biotec, Spain) for SARS-CoV-2 diagnosis using CDC FDA EUA kit as gold standard.\n\nResultsAlthough we found the lack of RNA quality control probe as the main limitation for Viasure kit, the sensitivity was up to 97.5% and specificity was 100%.\n\nConclusionsViasure RT-qPCR kit is a reliable tool for SARS-CoV-2 diagnosis but improvement of an alternative RT-qPCR reaction for RNA extraction quality control as RNaseP is recommended.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Himadri Nath",
-        "author_inst": "CSIR-Indian Institute of Chemical Biology"
-      },
-      {
-        "author_name": "Abinash Mallick",
-        "author_inst": "CSIR-Indian Institute of Chemical Biology"
+        "author_name": "Byron Freire-Paspuel",
+        "author_inst": "Universidad de las Americas"
       },
       {
-        "author_name": "Subrata Roy",
-        "author_inst": "CSIR-Indian Institute of Chemical Biology"
+        "author_name": "Patricio Alejandro Vega-Marino",
+        "author_inst": "Agencia de Regulacion y Control de la Bioseguridad y Cuarentena  para Galapagos"
       },
       {
-        "author_name": "Soumi Sukla",
-        "author_inst": "NIPER, Kolkata"
+        "author_name": "Alberto Velez",
+        "author_inst": "Agencia de Regulacion y Control de la Bioseguridad y Cuarentena para Galapagos"
       },
       {
-        "author_name": "Keya Basu",
-        "author_inst": "IPGMER, Kolkata (Department of Pathology)"
+        "author_name": "Marilyn Cruz",
+        "author_inst": "Agencia de Regulacion y Control de la Bioseguridad y Cuarentena para Galapagos"
       },
       {
-        "author_name": "Abhishek De",
-        "author_inst": "Calcutta National Medical College, Kolkata (Department of Dermatology)"
+        "author_name": "Franklin Perez",
+        "author_inst": "One Lab. Santa Elena. Ecuador"
       },
       {
-        "author_name": "Subhajit Biswas",
-        "author_inst": "CSIR-Indian Institute of Chemical Biology"
+        "author_name": "Miguel Angel Garcia Bereguiain",
+        "author_inst": "Universidad de Las Americas"
       }
     ],
     "version": "1",
@@ -1284923,151 +1287576,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.02.20143032",
-    "rel_title": "Characterization of Microbial Co-infections in the Respiratory Tract of hospitalized COVID-19 patients",
+    "rel_doi": "10.1101/2020.07.02.20145052",
+    "rel_title": "Modeling COVID-19 for lifting non-pharmaceutical interventions",
     "rel_date": "2020-07-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20143032",
-    "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, microbial composition of the respiratory tract and other infected tissues, as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear.\n\nMethodBetween January 27 and February 26, 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients (requiring ICU admission and mechanical ventilation), in the Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. Co-infection rates, the prevalence and abundance of microbial communities in these COVID-19 patients were determined.\n\nFindingsNotably, respiratory microbial co-infections were exclusively found in 84.6% of severely ill patients (11/13), among which viral and bacterial co-infections were detected by sequencing in 30.8% (4/13) and 69.2% (9/13) of the patients, respectively. In addition, for 23.1% (3/13) of the patients, bacterial co-infections with Burkholderia cepacia complex (BCC) and Staphylococcus epidermidis were also confirmed by bacterial culture. Further, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes in one severely ill patient was demonstrated, which might be the primary cause of his disease deterioration and death one month after ICU admission.\n\nInterpretationOur findings identified distinct patterns of co-infections with SARS-CoV-2 and various respiratory pathogenic microbes in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking of BCC-associated nosocomial infections are recommended to improve the pre-emptive treatment regimen and reduce fatal outcomes of hospitalized patients infected with SARS-CoV-2.\n\nFundingNational Science and Technology Major Project of China, National Major Project for Control and Prevention of Infectious Disease in China, the emergency grants for prevention and control of SARS-CoV-2 of Ministry of Science and Technology and Guangdong province, Guangdong Provincial Key Laboratory of Genome Read and Write, Guangdong Provincial Academician Workstation of BGI Synthetic Genomics, and Shenzhen Engineering Laboratory for Innovative Molecular Diagnostics.",
-    "rel_num_authors": 33,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20145052",
+    "rel_abs": "As a result of the COVID-19 worldwide pandemic, the United States instituted various non-pharmaceutical interventions (NPIs) in an effort to the slow the spread of the disease. Although necessary for public safety, these NPIs can also have deleterious effects on the economy of a nation. State and federal leaders need tools that provide insight into which combination of NPIs will have the greatest impact on slowing the disease and at what point in time it is reasonably safe to start lifting these restrictions to everyday life. In the present work, we outline a modeling process that incorporates the parameters of the disease, the effects of NPIs, and the characteristics of individual communities to offer insight into when and to what degree certain NPIs should be instituted or lifted based on the progression of a given outbreak of COVID-19.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Huanzi Zhong",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China. Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, 2100 Copenhagen, Denma"
-      },
-      {
-        "author_name": "Yanqun Wang",
-        "author_inst": "Guangzhou Institute of Respiratory Health"
-      },
-      {
-        "author_name": "Zhun Shi",
-        "author_inst": "BGI-Shenzhen,Shenzhen 518083,China"
-      },
-      {
-        "author_name": "Lu Zhang",
-        "author_inst": "Institute of Infectious disease, Guangzhou Eighth People's Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China 510060."
-      },
-      {
-        "author_name": "Huahui Ren",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Weiqun He",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
-      },
-      {
-        "author_name": "Zhaoyong Zhang",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
-      },
-      {
-        "author_name": "Airu Zhu",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
-      },
-      {
-        "author_name": "Jingxian Zhao",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
-      },
-      {
-        "author_name": "Fei Xiao",
-        "author_inst": "Department of Infectious Diseases, Guangdong Provincial Key Laboratory of Biomedical Imaging, Guangdong Provincial Engineering Research Center of Molecular Imag"
-      },
-      {
-        "author_name": "Fangming Yang",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Tianzhu Liang",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Feng Ye",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
-      },
-      {
-        "author_name": "Bei Zhong",
-        "author_inst": "The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, Guangdong, China"
-      },
-      {
-        "author_name": "Shicong Ruan",
-        "author_inst": "Yangjiang People's Hospital, Yangjiang, Guangdong, China"
-      },
-      {
-        "author_name": "Mian Gan",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
-      },
-      {
-        "author_name": "Jiahui Zhu",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Fang Li",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
-      },
-      {
-        "author_name": "Fuqiang Li",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Daxi Wang",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Jiandong Li",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Peidi Ren",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Shida Zhu",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Huanming Yang",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Jian Wang",
-        "author_inst": "BGI-Shenzhen"
-      },
-      {
-        "author_name": "Karsten Kristiansen",
-        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, China."
-      },
-      {
-        "author_name": "Hein M Tun",
-        "author_inst": "HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China."
-      },
-      {
-        "author_name": "Weijun Chen",
-        "author_inst": "BGI PathoGenesis Pharmaceutical Technology, Shenzhen, China."
-      },
-      {
-        "author_name": "Nanshan Zhong",
-        "author_inst": "State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University"
-      },
-      {
-        "author_name": "Xun Xu",
-        "author_inst": "BGI-shenzhen"
+        "author_name": "Matt Koehler",
+        "author_inst": "The MITRE Corporation"
       },
       {
-        "author_name": "Yi-min Li",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+        "author_name": "David M Slater",
+        "author_inst": "The MITRE Corporation"
       },
       {
-        "author_name": "Junhua LI",
-        "author_inst": "BGI-Shenzhen"
+        "author_name": "Garry Jacyna",
+        "author_inst": "The MITRE Corporation"
       },
       {
-        "author_name": "Jincun Zhao",
-        "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff"
+        "author_name": "James R Thompson",
+        "author_inst": "The MITRE Corporation"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.07.04.187435",
@@ -1286461,21 +1288998,45 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.07.03.20145672",
-    "rel_title": "A Novel Approach for Estimating the Final Outcome of Global Diseases Like COVID-19",
+    "rel_doi": "10.1101/2020.07.03.20146167",
+    "rel_title": "Serial interval, basic reproduction number and prediction of COVID-19 epidemic size in Jodhpur, India",
     "rel_date": "2020-07-04",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20145672",
-    "rel_abs": "The existence of a universal law which maps the bell curve of daily cases to a sigmoid curve for cumulative ones is used for making robust estimations about the final outcome of a disease. Computations of real time effective reproduction rate are presented and its limited usefulness is derived. After using methods ESE & EDE we are able to find the inflection point of the cumulative curve under consideration and study its time evolution. Since mortality processes tend to follow a Gompertz distribution, we apply the properties of it and introduce novel estimations for both the time remaining after inflection time and the capacity of the curve. Special properties of sigmoid curves are used for assessing the quality of estimation and as indices for the cycle completion. Application is presented for COVID-19 evolution for most affected countries and the World.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20146167",
+    "rel_abs": "BackgroundUnderstanding the epidemiology of COVID-19 is important for design of effective control measures at local level. We aimed to estimate the serial interval and basic reproduction number for Jodhpur, India and to use it for prediction of epidemic size for next one month.\n\nMethodsContact tracing of SARS-CoV-2 infected individuals was done to obtain the serial intervals. Aggregate and instantaneous R0 values were derived and epidemic projection was done using R software v4.0.0.\n\nResultsFrom among 79 infector-infectee pairs, the estimated median and 95 percentile values of serial interval were 5.98 days (95% CI 5.39 - 6.65) and 13.17 days (95% CI 11.27 - 15.57), respectively. The overall R0 value in the first 30 days of outbreak was 1.64 (95% CI 1.12 - 2.25) which subsequently decreased to 1.07 (95% CI 1.06 - 1.09). The instantaneous R0 value over 14 days window ranged from a peak of 3.71 (95% CI 1.85 -2.08) to 0.88 (95% CI 0.81 - 0.96) as on 24 June 2020. The projected COVID-19 case-load over next one month was 1881 individuals. Reduction of R0 from 1.17 to 1.085 could result in 23% reduction in projected epidemic size over the next one month.\n\nConclusionAggressive testing, contact-tracing and isolation of infected individuals in Jodhpur district resulted in reduction of R0. Further strengthening of control measures could lead to substantial reduction of COVID-19 epidemic size. A data-driven strategy was found useful in surge capacity planning and guiding the public health strategy at local level.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Demetris T Christopoulos",
-        "author_inst": "National and Kapodistrian University of Athens"
+        "author_name": "Suman Saurabh",
+        "author_inst": "All India Institute of Medical Sciences (AIIMS), Jodhpur"
+      },
+      {
+        "author_name": "Mahendra Kumar Verma",
+        "author_inst": "All India Institute of Medical Sciences (AIIMS), Jodhpur, India"
+      },
+      {
+        "author_name": "Vaishali Gautam",
+        "author_inst": "All India Institute of Medical Sciences (AIIMS), Jodhpur, India"
+      },
+      {
+        "author_name": "Akhil Goel",
+        "author_inst": "All India Institute of Medical Sciences (AIIMS), Jodhpur, India"
+      },
+      {
+        "author_name": "Manoj Kumar Gupta",
+        "author_inst": "All India Institute of Medical Sciences, Jodhpur, India"
+      },
+      {
+        "author_name": "Pankaj Bhardwaj",
+        "author_inst": "All India Institute of Medical Sciences (AIIMS), Jodhpur, India"
+      },
+      {
+        "author_name": "Sanjeev Misra",
+        "author_inst": "All India Institute of Medical Sciences (AIIMS), Jodhpur, India"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1288003,45 +1290564,21 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.07.01.20129882",
-    "rel_title": "Retrospective Clinical Evaluation of Four Lateral Flow Assays for the Detection of SARS-CoV-2 Antibodies",
+    "rel_doi": "10.1101/2020.07.01.20144667",
+    "rel_title": "Numerical Analysis of Disastrous Effect of Reopening Too Soon in Georgia, USA",
     "rel_date": "2020-07-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20129882",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19) is a potentially life-threatening respiratory infection caused by severe acute respiratory coronavirus 2 (SARS-CoV-2), for which numerous serologic assays are available. In a CLIA laboratory setting, we used a retrospective sample set (n = 457) to evaluate two lateral flow immunoassays (LFIAs; two iterations of Rapid Response COVID-19 Test Cassette, BTNX Inc.) and a subset of to evaluate SARS-COV-2 IgG/IgM Rapid Test, ACON Laboratories (n = 200); and Standard Q COVID-19 IgM/IgG Duo, SD BIOSENSOR (n = 155) for their capacity to detect of SARS-CoV-2 IgG. In a cohort of primarily hospitalized patients with RT-PCR confirmed COVID-19, the BTNX assays demonstrated 95% and 92% agreement with the Abbott SARS-CoV-2 IgG assay and sensitivity was highest at [&ge;] 14 days from symptom onset [BTNX kit 1, 95%; BTNX kit 2, 91%]. ACON and SD assays demonstrated 99% and 100% agreement with the Abbott assay at [&ge;] 14 days from symptom onset. Specificity was measured using 74 specimens collected prior to SARS-CoV-2 circulation in the United States and 31 \"cross-reactivity challenge\" specimens, including those from patients with a history of seasonal coronavirus infection and was 98% for BTNX kit 1 and ACON and 100% for BTNX kit 2 and SD. Taken with data from EUA assays, these results suggest that LFIAs may provide adequate results for rapid detection of SARS-CoV-2. Replicating these results in fingerstick blood in outpatient populations, would further support the possibility that LFIAs may be useful to increase access to serologic testing",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20144667",
+    "rel_abs": "Social distancing restrictions were lifted in Georgia, USA before the daily new Covid-19 cases were significantly reduced below the peak. In this paper we show through numerical analysis the disastrous consequence of this action resulting in a second peak of daily cases which caused additional fatalities.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Kathrine McAulay",
-        "author_inst": "Mayo Clinic"
-      },
-      {
-        "author_name": "Andrew Bryan",
-        "author_inst": "University of Washington School of Medicine"
-      },
-      {
-        "author_name": "Alexander L. Greninger",
-        "author_inst": "University of Washington School of Medicine"
-      },
-      {
-        "author_name": "Francisca Grill",
-        "author_inst": "Arizona State University"
-      },
-      {
-        "author_name": "Douglas F. Lake",
-        "author_inst": "Arizona State University"
-      },
-      {
-        "author_name": "Erin J. Kaleta",
-        "author_inst": "Mayo Clinic"
-      },
-      {
-        "author_name": "Thomas E Grys",
-        "author_inst": "Mayo Clinic"
+        "author_name": "Santanu Basu",
+        "author_inst": "Sparkle Optics Corporation"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1289581,57 +1292118,85 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.30.20143651",
-    "rel_title": "Identifying main and interaction effects of risk factors to predict intensive care admission in patients hospitalized with COVID-19: a retrospective cohort study in Hong Kong",
+    "rel_doi": "10.1101/2020.07.01.20144030",
+    "rel_title": "Broad phenotypic alterations and potential dysfunctions of lymphocytes in COVID-19 recovered individuals",
     "rel_date": "2020-07-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.30.20143651",
-    "rel_abs": "BackgroundThe coronavirus disease 2019 (COVID-19) has become a pandemic, placing significant burdens on the healthcare systems. In this study, we tested the hypothesis that a machine learning approach incorporating hidden nonlinear interactions can improve prediction for Intensive care unit (ICU) admission.\n\nMethodsConsecutive patients admitted to public hospitals between 1st January and 24th May 2020 in Hong Kong with COVID-19 diagnosed by RT-PCR were included. The primary endpoint was ICU admission.\n\nResultsThis study included 1043 patients (median age 35 (IQR: 32-37; 54% male). Nineteen patients were admitted to ICU (median hospital length of stay (LOS): 30 days, median ICU LOS: 16 days). ICU patients were more likely to be prescribed angiotensin converting enzyme inhibitors/angiotensin receptor blockers, anti-retroviral drugs lopinavir/ritonavir and remdesivir, ribavirin, steroids, interferon-beta and hydroxychloroquine. Significant predictors of ICU admission were older age, male sex, prior coronary artery disease, respiratory diseases, diabetes, hypertension and chronic kidney disease, and activated partial thromboplastin time, red cell count, white cell count, albumin and serum sodium. A tree-based machine learning model identified most informative characteristics and hidden interactions that can predict ICU admission. These were: low red cells with 1) male, 2) older age, 3) low albumin, 4) low sodium or 5) prolonged APTT. A five-fold cross validation confirms superior performance of this model over baseline models including XGBoost, LightGBM, random forests, and multivariate logistic regression.\n\nConclusionsA machine learning model including baseline risk factors and their hidden interactions can accurately predict ICU admission in COVID-19.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20144030",
+    "rel_abs": "BackgroundLymphopenia is a typical symptom in the COVID-19 patients. While millions of patients are clinical recovered, little is known about the immune status of lymphocytes in these individuals.\n\nMethodsA clinical recovered cohort (CR) of 55 COVID-19 individuals (discharged from hospital 4 to 11 weeks), and 55 age and sex matched healthy donors cohort (HD) were recruited. Detailed analysis on phenotype of the lymphocytes in peripheral blood mononuclear cells (PBMCs) was performed by flow cytometry.\n\nFindingsCompared with cohort HD, the CD8+ T cells in cohort CR had higher Teff and Tem, but lower Tc1 (IFN-{gamma}+), Tc2 (IL-4+) and Tc17 (IL-17A+) frequencies. The CD4+ T cells of CR had decreased frequency, especially on the Tcm subset. Moreover, CD4+ T cells of CR expressed lower PD-1 and had lower frequencies of Th1 (IFN-{gamma}+), Th2 (IL-4+), Th17 (IL-17A+) as well as circulating Tfh (CXCR5+PD-1+). Accordingly, isotype-switched memory B cell (IgM-CD20hi) in CR had significantly lower proportion in B cells, though level of activation marker CD71 elevated. For CD3-HLA-DRlo lymphocytes of CR, besides levels of IFN-{gamma}, Granzyme B and T-bet were lower, the correlation between T-bet and IFN-{gamma} became irrelevant. In addition, taken into account of discharged days, all the lowered function associated phenotypes showed no recovery tendency within whole observation period.\n\nInterpretationThe CR COVID-19 individuals still showed remarkable phenotypic alterations in lymphocytes after clinical recovery 4 to 11 weeks. This suggests SARS-CoV-2 infection imprints profoundly on lymphocytes and results in long-lasting potential dysfunctions.\n\nFundingKunming Science and Technology Department (2020-1-N-037)",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Jiandong Zhou",
-        "author_inst": "City University of Hong Kong"
+        "author_name": "Jingyi Yang",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences (CAS)"
       },
       {
-        "author_name": "Gary Tse",
-        "author_inst": "Tianjin Medical University"
+        "author_name": "Maohua Zhong",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences (CAS),"
       },
       {
-        "author_name": "Sharen Lee",
-        "author_inst": "Laboratory of Cardiovascular Physiology"
+        "author_name": "Ejuan Zhang",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences (CAS)"
       },
       {
-        "author_name": "Tong Liu",
-        "author_inst": "Tianjin Medical University"
+        "author_name": "Ke Hong",
+        "author_inst": "Wuhan Jinyintan Hospital"
       },
       {
-        "author_name": "William KK Wu",
-        "author_inst": "LKS Institute of Health Sciences"
+        "author_name": "Qingyu Yang",
+        "author_inst": "Wuhan Jinyintan Hospital"
       },
       {
-        "author_name": "zhidong cao",
-        "author_inst": "Institute of Automation, Chinese Academy of Sciences"
+        "author_name": "Dihan Zhou",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences (CAS)"
       },
       {
-        "author_name": "Dajun Zeng",
-        "author_inst": "Chinese Academy of Sciences"
+        "author_name": "Jianbo Xia",
+        "author_inst": "Maternal and Child Health Hospital of Hubei Province"
       },
       {
-        "author_name": "Ian CK Wong",
-        "author_inst": "HKU"
+        "author_name": "Yao-Qing Chen",
+        "author_inst": "School of Public Health (Shenzhen), Sun Yat-sen University"
       },
       {
-        "author_name": "Qingpeng Zhang",
-        "author_inst": "City University of Hong Kong"
+        "author_name": "Mingbo Sun",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences & Peking Union Medical College"
       },
       {
-        "author_name": "Bernard MY Cheung",
-        "author_inst": "HKU"
+        "author_name": "Bali Zhao",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences (CAS)"
+      },
+      {
+        "author_name": "Jie Xiang",
+        "author_inst": "Wuhan Jinyintan Hospital"
+      },
+      {
+        "author_name": "Ying Liu",
+        "author_inst": "Wuhan Jinyintan Hospital"
+      },
+      {
+        "author_name": "Yang Han",
+        "author_inst": "Wuhan Jinyintan Hospital"
+      },
+      {
+        "author_name": "Xi Zhou",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences (CAS)"
+      },
+      {
+        "author_name": "Chaolin Huang",
+        "author_inst": "Wuhan Jinyintan Hospital"
+      },
+      {
+        "author_name": "You Shang",
+        "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Huimin Yan",
+        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences (CAS)"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1291115,27 +1293680,27 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.06.23.20132522",
-    "rel_title": "The advantages of the simplest pandemic models",
+    "rel_doi": "10.1101/2020.06.24.20138644",
+    "rel_title": "Strong Correlation Between Prevalence of Severe Vitamin D Deficiency and Population Mortality Rate from COVID-19 in Europe",
     "rel_date": "2020-07-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20132522",
-    "rel_abs": "As a pandemic of coronavirus spreads across the globe, people debate policies to mitigate its severity. Many complex, highly detailed models have been developed to help policy setters make better decisions. However, the basis of these models is unlikely to be understood by non-experts.\n\nWe describe the advantages of simple models for covid-19. We say a model is \"simple\" if its only parameter is the rate of contact between people in the population. This contact rate can vary over time, depending on choices by policy setters. Such models can be understood by a broad audience, and thus can be helpful in explaining the policy decisions to the public. They can be used to evaluate outcomes of different policy strategies. However, simple models have a disadvantage when dealing with inhomogeneous populations.\n\nTo augment the power of a simple model to evaluate complicated situations, we add what we call \"satellite\" equations that do not change the original model. For example, with the help of a satellite equation, one could know what his/her chance is of remaining uninfected through the end of epidemic. Satellite equations can model the effect of the epidemic on high-risk individuals, or death rates, or on nursing homes, and other isolated populations.\n\nTo compare simple models with complex models, we introduce our \"slightly complex\" Model J. We find the conclusions of simple and complex models can be quite similar. But, for each added complexity, a modeler may have to choose additional parameter values describing who will infect whom under what conditions, choices for which there is often little rationale but that can have a big impact on predictions. Our simulations suggest that the added complexity offers little predictive advantage.\n\nAuthor SummaryThere is a large variety of available data about the coronavirus pandemic, but we still lack data about some important factors. Who is likely to infect whom and under what conditions and how long after becoming infected? These factors are the essence of transmission dynamics. Two groups using identical complex models can be expected to make different predictions simply because they make different choices for such transmission parameters in the model. The audience has no way to choose between their predictions. We explain how simple models can be used to answer complex questions by adding what we call satellite equations, addressing questions involving age groups, death rates, and likelihood of transmission to nursing homes and to uninfected, isolated populations. Simple models are ideal for seeing what kinds of interventions are needed to achieve goals of policy setters.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20138644",
+    "rel_abs": "BackgroundSARS-CoV-2 virus causes a very wide range of COVID-19 disease severity in humans: from completely asymptomatic to fatal, and the reasons behind it are often not understood. There is some data that Vitamin D may have protective effect, so authors decided to analyze European country-wide data to determine if Vitamin D levels are associated with COVID-19 population death rate.\n\nMethodsTo retrieve the Vitamin D levels data, authors analyzed the Vitamin D European population data compiled by 2019 ECTS Statement on Vitamin D Status published in the European Journal of Endocrinology. For the data set to used for analysis, only recently published data, that included general adult population of both genders ages 40-65 or wider, and must have included the prevalence of Vitamin D deficiency.\n\nResultsThere were 10 countries data sets that fit the criteria and were analyzed. Severe Vitamin D deficiency was defined as 25(OH)D less than 25 nmol/L (10 ng/dL). Pearson correlation analysis between death rate per million from COVID-19 and prevalence of severe Vitamin D deficiency shows a strong correlation with r = 0.76, p = 0.01, indicating significant correlation. Correlation remained significant, even after adjusting for age structure of the population. Additionally, over time, correlation strengthened, and r coefficient asymptoticaly increased.\n\nConclusionsAuthors recommend universal screening for Vitamin D deficiency, and further investigation of Vitamin D supplementation in randomized control studies, which may lead to possible treatment or prevention of COVID-19.",
     "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Sana Jahedi",
-        "author_inst": "University of New Brunswick"
+        "author_name": "Isaac Z Pugach",
+        "author_inst": "Complete Med Care"
       },
       {
-        "author_name": "James Yorke",
-        "author_inst": "University of Maryland"
+        "author_name": "Sofya Pugach",
+        "author_inst": "Complete Med Care"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.06.29.20143156",
@@ -1292917,59 +1295482,103 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.06.30.181297",
-    "rel_title": "If the link missed\uff1aCould inflammatory skin disorders with barrier dysfunction increase the risk of COVID-19?",
-    "rel_date": "2020-07-01",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.30.181297",
-    "rel_abs": "Since the end of 2019, COVID-19 pandemic caused by the SARS-CoV-2 emerged globally. The angiotensin-converting enzyme 2 (ACE2) on the cell surface is crucial for SARS-COV-2 entering into the cells. We use SARS-COV-2 pseudo virus and humanized ACE2 mice to mimic the possible transmitting of SARS-COV-2 through skin based on the data we found that skin ACE2 level is associated with skin pre-existing cutaneous conditions in human and mouse models and inflammatory skin disorders with barrier dysfunction increased the penetration of topical FITC conjugated spike protein into the skin. Our study indicated the possibility that the pre-existing cutaneous conditions could increase the risk for SARS-COV-2 infection.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR/small/181297v4_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (33K):\norg.highwire.dtl.DTLVardef@14cef60org.highwire.dtl.DTLVardef@1f78c65org.highwire.dtl.DTLVardef@1224834org.highwire.dtl.DTLVardef@1b27475_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
-    "rel_num_authors": 10,
+    "rel_doi": "10.1101/2020.06.24.20134288",
+    "rel_title": "A retrospective study evaluating efficacy and safety of compassionate use of tocilizumab in 13 patients with severe-to-critically ill COVID-19: analysis of well-responding cases and rapidly-worsening cases after tocilizumab administration",
+    "rel_date": "2020-06-30",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20134288",
+    "rel_abs": "We administered tocilizumab into 13 severe-to-critically ill patients with coronavirus disease 2019 (COVID-19) for compassionate use in combination with potential anti-viral agents in those who required an oxygen supply and showed increased laboratory inflammatory markers such as C-reactive protein (CRP) and ferritin. One injection of tocilizumab led to rapid improvements in clinical features, inflammatory findings, and oxygen supply in seven patients with severe COVID-19 and substantial amelioration in two patients who were critically ill, whereas four patients, who exhibited rapidly worsened respiratory function, required artificial ventilatory support even after tocilizumab treatment. Three of these four patients ultimately recovered from deterioration after methylprednisolone treatment. Administration of tocilizumab did not affect viral elimination nor IgG production specific for the virus. Compared with well-responding patients, rapidly-worsened patients showed a significantly higher ratio of ferritin vs. CRP. These findings suggest that tocilizumab has beneficial effects in severe-to-critically ill patients with COVID-19; however, in some cases, addition of methylprednisolone is required for disease rescue.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Qiannan Xu",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Shoji Hashimoto",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Lihong Chen",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Heita Kitajima",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Li Zhang",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Tsuyoshi Arai",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Mengyan Hu",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Yoshitaka Tamura",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Xiaopan Wang",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Takayuki Nagai",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Qi Yang",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Hiroshi Morishita",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Yunchen Le",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Hiroto Matsuoka",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Feng Xue",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Yuki Han",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Xia Li",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Seijiro Minamoto",
+        "author_inst": "Osaka Habikino Medical Center"
       },
       {
-        "author_name": "Jie Zheng",
-        "author_inst": "Shanghai Ruijin Hospital"
+        "author_name": "Tomonori Hirashima",
+        "author_inst": "Osaka Habikino Medical Center"
+      },
+      {
+        "author_name": "Tomoki Yamada",
+        "author_inst": "Osaka Habikino Medical Center"
+      },
+      {
+        "author_name": "Yozo Kashiwa",
+        "author_inst": "Osaka Habikino Medical Center"
+      },
+      {
+        "author_name": "Makoto Kameda",
+        "author_inst": "Osaka Habikino Medical Center"
+      },
+      {
+        "author_name": "Seiji Yamaguchi",
+        "author_inst": "Osaka Habikino Medical Center"
+      },
+      {
+        "author_name": "Kazuko Uno",
+        "author_inst": "Louis Pasteur Center for Medical Research"
+      },
+      {
+        "author_name": "Emi Nakayama",
+        "author_inst": "Research Institute for Microbial Diseases, Osaka University"
+      },
+      {
+        "author_name": "Tatsuo Shioda",
+        "author_inst": "Research Institute for Microbial Diseases, Osaka University"
+      },
+      {
+        "author_name": "Kazuyuki Yoshizaki",
+        "author_inst": "Institute of Scientific and Industry Research, Osaka University"
+      },
+      {
+        "author_name": "Sujin Kang",
+        "author_inst": "Immunology Frontier Research Center, Osaka University"
+      },
+      {
+        "author_name": "Tadamistu Kishimoto",
+        "author_inst": "Immunology Frontier Research Center, Osaka University"
+      },
+      {
+        "author_name": "Toshio Tanaka",
+        "author_inst": "Osaka Habikino Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "pathology"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.06.22.165936",
@@ -1294903,67 +1297512,87 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.29.20140129",
-    "rel_title": "Assessment of a Diagnostic Strategy Based on Chest Computed Tomography in Patients Hospitalized for COVID-19 Pneumonia: an observational study",
+    "rel_doi": "10.1101/2020.06.28.20141838",
+    "rel_title": "SARS-CoV-2 serological testing using electrochemiluminescence reveals arapid onset of seroconversion in severe COVID-19 patients",
     "rel_date": "2020-06-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20140129",
-    "rel_abs": "ObjectivesTo assess the relevance of a diagnostic strategy for COVID-19 based on chest computed tomography (CT) in patients with hospitalization criteria.\n\nSettingObservational study with retrospective analysis in a French emergency department (ED).\n\nParticipants and interventionFrom March 3 to April 2, 2020, 385 adult patients presenting to the ED for suspected COVID-19 underwent an evaluation that included history, physical examination, blood tests, real-time reverse transcription-polymerase chain reaction (RT-PCR) and chest CT. When the time-interval between chest CT and RT-PCR assays was longer than 7 days, patients were excluded from the study. Only patients with hospitalization criteria were included. Diagnosis accuracy was assessed using the sensitivity and specificity of RT-PCR.\n\nOutcomesSensitivity and specificity of RT-PCR, chest CT (also accompanied by lymphopenia) were measured and were also analyzed by subgroups of age and sex.\n\nResultsAmong 377 included subjects, RT-PCR was positive in 36%, while chest CT was compatible with a COVID-19 diagnosis in 59%. In the population with positive RT-PCR, there were more men (55% vs 37%, p=0.015), a higher frequency of reticular and, or, interlobular septal thickening (53% vs 31%, p=0.02) as well as a higher frequency of bilateral lesion distribution (98% vs 86%, p=0.01) compared to the population with negative RT-PCR. The proportion of lymphopenia was higher in men vs women (47% vs 39%, p=0.03) and varies between patients >80 versus 50-80 and p<0.001).\n\nUsing CT as reference, RT-PCR obtained a sensitivity of 61%, specificity of 93%. There was a significant difference between CT and RT-PCR diagnosis performance (p<0.001). When CT was accompanied by lymphopenia, sensitivity and specificity of RT-PCR were respectively 71% and 94%. CT abnormalities and lymphopenia provided diagnosis in 29% of patients with negative PCR.\n\nConclusionsChest CT had a superior yield than RT-PCR in COVID-19 hospitalized patients, especially when accompanied by lymphopenia.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.28.20141838",
+    "rel_abs": "Despite ongoing efforts to characterize the host response toward SARS-CoV-2, a major gap in our knowledge still exists regarding the magnitude and duration of the humoral response. We report the development of a rapid, highly specific and sensitive electrochemiluminescent assay for detecting IgM, IgA, and IgG antibodies toward two distinct SARS-CoV-2 antigens namely, the receptor binding domain (RBD) and the nuclear protein (NP). Whereas IgM antibodies toward RBD were detected at early stages of the disease, IgM antibodies against NP did not develop. Analysis of the antibody response in mild versus moderate/severe patients revealed a rapid onset of IgG and IgA antibodies, specifically in moderate/severe patients. Finally, we observed a marked reduction in IgM/IgA antibodies and to lesser extent, IgG, over time. We provide a comprehensive analysis of the human antibody response, and has major implications on our understanding and monitoring of SARS-CoV-2 infections, as well as finding effective vaccines.\n\nOne Sentence SummaryUsing a newly developed assay to detect anti-SARS-Cov-2 IgM, IgG and IgA antibodies we reveal a rapid onset of IgG and IgA antibodies towards distinct viral antigens, specifically in moderate/severe COVID-19 patients,",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Marine Thieux",
-        "author_inst": "Medipole Hopital Mutualiste Clinical Research Unit"
+        "author_name": "Ariel Munitz",
+        "author_inst": "Department of Clinical Microbiology and Immunology, The Sackler School of Medicine, Tel-Aviv University, Ramat Aviv 69978, Israel."
+      },
+      {
+        "author_name": "Liat Edry-Botzer",
+        "author_inst": "Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
+      },
+      {
+        "author_name": "Michal Itan",
+        "author_inst": "Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Anne Charlotte Kalenderian",
-        "author_inst": "Medipole Hopital Mutualiste Imapole"
+        "author_name": "Ran Tur-Kaspa",
+        "author_inst": "Department of Medicine D and the Liver Institute, Rabin Medical Center, Beilinson Hospital, Molecular Hepatology Research Laboratory, Felsenstein Medical Resear"
       },
       {
-        "author_name": "Aurelie Chabrol",
-        "author_inst": "Medipole Hopital Mutualiste Imapole"
+        "author_name": "Dror Dicker",
+        "author_inst": "Internal Medicine D, Hasharon Hospital-Rabin Medical Center, Petach Tikva, Israel. Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Laurent Gendt",
-        "author_inst": "Medipole Hopital Mutualiste Eurofins CBM 69"
+        "author_name": "Dana Markovitch",
+        "author_inst": "Internal Medicine D, Hasharon Hospital-Rabin Medical Center, Petach Tikva, Israel. Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Emma Giraudier",
-        "author_inst": "Lyon 2 University Masters Degree in Medical Translation and Scientific Writing"
+        "author_name": "Moran Goren",
+        "author_inst": "Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Herve Lelievre",
-        "author_inst": "Medipole Hopital Mutualiste Eurofins CBM 69"
+        "author_name": "Michael Mor",
+        "author_inst": "Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Samir Lounis",
-        "author_inst": "Medipole Hopital Mutualiste Imapole"
+        "author_name": "Shuval Lev",
+        "author_inst": "Intensive care unit, Hasharon Hospital-Rabin Medical Center, Petach Tikva, Israel. Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Yves Mataix",
-        "author_inst": "Medipole Hopital Mutualiste Department of Medicine"
+        "author_name": "Tamar Gottesman",
+        "author_inst": "Infectious diseases and infection control, Hasharon Hospital-Rabin Medical Center, Petach Tikva, Israel. Sackler School of Medicine, Tel Aviv University, 699780"
       },
       {
-        "author_name": "Emeline Moderni",
-        "author_inst": "Lyon 2 University Masters Degree in Medical Translation and Scientific Writing"
+        "author_name": "Khitam Muhsen",
+        "author_inst": "Department of Epidemiology and Preventive Medicine, School of Public Health, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Laetitia Paradisi",
-        "author_inst": "Medipole Hopital Mutualiste Clinical Research Unit"
+        "author_name": "Daniel Cohen",
+        "author_inst": "Department of Epidemiology and Preventive Medicine, School of Public Health, Tel Aviv University, 6997801 Israel"
       },
       {
-        "author_name": "Guillaume Ranchon",
-        "author_inst": "Medipole Hopital Mutualiste Emergency Department"
+        "author_name": "Miguel Stein",
+        "author_inst": "Allergy and Immunology Unit, Wolfson Medical Center, 6997801 Israel"
       },
       {
-        "author_name": "Carlos El Khoury",
-        "author_inst": "Medipole Hopital Mutualiste Clinical Research Unit"
+        "author_name": "Udi Qimron",
+        "author_inst": "Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
+      },
+      {
+        "author_name": "Natalia Freund",
+        "author_inst": "Department of Clinical Microbiology and Immunology, Sackler School of Medicine, Tel Aviv University, 6997801 Israel"
+      },
+      {
+        "author_name": "Yariv Wine",
+        "author_inst": "School of Molecular Cell Biology and Biotechnology, George S. Wise Faculty of Life Sciences, Tel Aviv University, 6997801 Israel"
+      },
+      {
+        "author_name": "Motti Gerlic",
+        "author_inst": "Department of Clinical Microbiology and Immunology, The Sackler School of Medicine, Tel-Aviv University, Ramat Aviv 69978, Israel."
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.06.28.20132498",
@@ -1296861,61 +1299490,29 @@
     "category": "emergency medicine"
   },
   {
-    "rel_doi": "10.1101/2020.06.27.20141689",
-    "rel_title": "Estimating the infection fatality risk of COVID-19 in New York City, March 1-May 16, 2020",
+    "rel_doi": "10.1101/2020.06.26.20131144",
+    "rel_title": "The scale and dynamics of COVID-19 epidemics across Europe",
     "rel_date": "2020-06-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.27.20141689",
-    "rel_abs": "During March 1-May 16, 2020, 191,392 laboratory-confirmed COVID-19 cases were diagnosed and reported and 20,141 confirmed and probable COVID-19 deaths occurred among New York City (NYC) residents. We applied a network model-inference system developed to support the Citys pandemic response to estimate underlying SARS-CoV-2 infection rates. Based on these estimates, we further estimated the infection fatality risk (IFR) for 5 age groups (i.e. <25, 25-44, 45-64, 65-74, and 75+ years) and all ages overall, during March 1-May 16, 2020. We estimated an overall IFR of 1.45% (95% Credible Interval: 1.09-1.87%) in NYC. In particular, weekly IFR was estimated as high as 6.1% for 65-74 year-olds and 17.0% for 75+ year-olds. These results are based on more complete ascertainment of COVID-19-related deaths in NYC and thus likely more accurately reflect the true, higher burden of death due to COVID-19 than previously reported elsewhere. It is thus crucial that officials account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the pandemic unfolds.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20131144",
+    "rel_abs": "The number of COVID-19 deaths reported from European countries has varied more than 100-fold. In terms of coronavirus transmission, the relatively low death rates in some countries could be due to low intrinsic (e.g. low population density) or imposed contact rates (e.g. non-pharmaceutical interventions) among individuals, or because fewer people were exposed or susceptible to infection (e.g. smaller populations). Here we develop a flexible empirical model (skew-logistic) to distinguish among these possibilities. We find that countries reporting fewer deaths did not generally have intrinsically lower rates of transmission and epidemic growth, and flatter epidemic curves. Rather, countries with fewer deaths locked down earlier, had shorter epidemics that peaked sooner, and smaller populations. Consequently, as lockdowns are eased we expect, and are starting to see, a resurgence of COVID-19 across Europe.\n\nOne Sentence SummaryA flexible empirical model shows that European countries reporting fewer COVID-19 deaths locked down earlier, had shorter epidemics that peaked sooner, and smaller populations.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Wan Yang",
-        "author_inst": "Columbia University"
-      },
-      {
-        "author_name": "Sasikiran Kandula",
-        "author_inst": "Columbia University"
-      },
-      {
-        "author_name": "Mary Huynh",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
-      },
-      {
-        "author_name": "Sharon K Greene",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
-      },
-      {
-        "author_name": "Gretchen Van Wye",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
-      },
-      {
-        "author_name": "Wenhui Li",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
-      },
-      {
-        "author_name": "Hiu Tai Chan",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
-      },
-      {
-        "author_name": "Emily McGibbon",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
-      },
-      {
-        "author_name": "Alice Yeung",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
+        "author_name": "Christopher Dye",
+        "author_inst": "Oxford University"
       },
       {
-        "author_name": "Don Olson",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
+        "author_name": "Russell C.H. Cheng",
+        "author_inst": "University of Southampton"
       },
       {
-        "author_name": "Anne Fine",
-        "author_inst": "New York City Department of Health and Mental Hygiene"
+        "author_name": "John S. Dagpunar",
+        "author_inst": "University of Southampton"
       },
       {
-        "author_name": "Jeffrey Shaman",
-        "author_inst": "Columbia University"
+        "author_name": "Brian G. Williams",
+        "author_inst": "Stellenbosch University"
       }
     ],
     "version": "1",
@@ -1298367,47 +1300964,23 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.29.20142281",
-    "rel_title": "Early Hemoglobin kinetics in response to ribavirin: Safety lesson learned from Hepatitis C to CoVID-19 therapy",
+    "rel_doi": "10.1101/2020.06.28.20141960",
+    "rel_title": "Data presented by the UK government as lockdown was eased shows the transmission of COVID-19 had already increased.",
     "rel_date": "2020-06-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20142281",
-    "rel_abs": "BackgroundRibavirin (RBV) is been used for SARS-CoV-2 infection. This drug is associated with a wide range of side effects, mainly anemia, so its use in patients with potential respiratory affectation could not be appropriate. The evidences of adverse events associated with RBV-use has mainly been derived in the context of hepatitis C (HCV) treatment, however the possible use of RBV in CoVID-19 patients could be limited to 14 days.\n\nMethodsLongitudinal study including HIV/HCV coinfected patients. We evaluate the hemoglobin dynamics and reductions as well as evaluate the development rate of anemia during the first 2 weeks of therapy in HCV infected patients.\n\nResults189 patients were included in the study. The median hemoglobin levels were 14.6 g/dL (IQR: 13.2-15.6 g/dL) and 13.5 g/dL (IQR: 12.3-14.5 g/dL) at weeks 1 and 2 of therapy, respectively. A cumulative number of 27 (14.2%) patients developed anemia (23 grade 1 [12.1%] and 4 grade 2 [2.1%]). We identify a baseline hemoglobin levels of 14 g/dL as the better cut-off to identify those patients with a high chance to develop anemia. Of the 132 patients with baseline hemoglobin level >14 g/dL, 8 developed anemia (6.1%) compared with 19 of 57 (33.3%) with hemoglobin levels lower than 14 g/dL (p < 0.001).\n\nConclusionsOur study shows valuable information about the early hemoglobin kinetic timing in patients on RBV-therapy, that could be useful to tailor CoVID-19 treatment if RBV use is considered.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.28.20141960",
+    "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) is an international emergency that has been addressed in many countries by changes in and restrictions on behaviour. These are often collectively labelled social distancing and lockdown. On the 23rd June 2020, Boris Johnson, the Prime Minister of the United Kingdom announced substantial easings of restrictions. This paper examines some of the data he presented.\n\nMethodsGeneralised additive models, with negative binomial errors and cyclic term representing day-of-week effects, were fitted to data on the daily numbers of new confirmed cases of COVID-19. Exponential rates for the epidemic were estimated for different periods, and then used to calculate R, the reproduction number, for the disease in different periods.\n\nResultsAfter an initial stabilisation, the lockdown reduced R to around 0.81 (95% CI: 0.79, 0.82). This value increased to around 0.94 (95% CI 0.89, 0.996) for the fortnight from the 9th June 2020.\n\nConclusionsOfficial UK data, presented as the easing of the lockdown was announced, shows that R was already more than half way back to 1 at that point. That suggests there was little scope for the announced changes to be implemented without restarting the spread of the disease.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Antonio Rivero-Juarez",
-        "author_inst": "IMIBIC"
-      },
-      {
-        "author_name": "Mario Frias",
-        "author_inst": "IMIBIC"
-      },
-      {
-        "author_name": "Isabel Machuca",
-        "author_inst": "IMIBIC"
-      },
-      {
-        "author_name": "Marina Gallo",
-        "author_inst": "IMIBIC"
-      },
-      {
-        "author_name": "Pedro Lopez-Lopez",
-        "author_inst": "IMIBIC"
-      },
-      {
-        "author_name": "Angela Camacho",
-        "author_inst": "IMIBIC"
-      },
-      {
-        "author_name": "Antonio Rivero",
-        "author_inst": "IMIBIC"
+        "author_name": "Mike Lonergan",
+        "author_inst": "University of Dundee"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "toxicology"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2020.06.28.20142174",
@@ -1299781,63 +1302354,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.26.20140616",
-    "rel_title": "The impact of SARS-CoV-2 transmission fear and COVID-19 pandemic on the mental health of patients with primary immunodeficiency disorders, severe asthma, and other high-risk groups",
+    "rel_doi": "10.1101/2020.06.25.20139907",
+    "rel_title": "Teach, and teach and teach: does the average citizen use masks correctly during daily activities? Results from an observational study with more than 12,000 participants",
     "rel_date": "2020-06-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20140616",
-    "rel_abs": "BackgroundThe adverse effects of COVID-19 pandemic on the mental health of high-risk group patients for morbidity and mortality and its impact on public health in the long term have not been clearly determined.\n\nObjectiveTo determine the level of COVID-19 related transmission fear and anxiety in healthcare workers and patients with primary immunodeficiency disorder (PID), severe asthma, and the ones with other comorbidities.\n\nMethodsThe healthcare workers and patients with PID, severe asthma (all patients receiving biological agent treatment), malignancy, cardiovascular disease, hypertension (90% of patients receiving ACEI or ARB therapy), diabetes mellitus (42 % of patients receiving DPP-4 inhibitor therapy) were included in the study. A total of 560 participants, 80 individuals in each group, were provided. The hospital anxiety and depression scale (HADS) and Fear of illness and virus evaluation (FIVE) scales were applied to the groups with face to face interview methods.\n\nResultsThe mean age was 49.30 {+/-} 13.74 years and 306 (55 %) were female. The FIVE Scale and HADS-A scale scores of health care workers were significantly higher than other groups scores (p = 0.001 and 0.006). The second-highest scores belonged to patients with PID. There was no significant difference between the groups for the HADS-D score (p=0.07). The lowest score in all scales was observed in patients with hypertension.\n\nConclusionsThis study demonstrated that in the pandemic process, patients with primary immunodeficiency, asthma patients, and other comorbid patients, especially healthcare workers, should be referred to the centers for the detection and treatment of mental health conditions.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.25.20139907",
+    "rel_abs": "COVID-19 is a new disease with no treatment and no vaccine so far. The pandemic is still growing in many areas. Among the core measures to prevent disease spread is the use of face masks. We observed 12,588 people in five Brazilian cities within the Baixada Santista metropolitan area. Even though this is densely populated region and heavily impacted by COVID-19 with a high risk population, only 45.1% of the observed population wore in face masks in a correct way, and another 15.5% simply did not use masks at all. The remainder used masks incorrectly, which is evidence of the worst scenario of people believing that they are protected when they are not. This is among the first studies, to the best of our knowledge, that measures real life compliance with face masks during this COVID-19 pandemic. It is our conclusion that it is paramount to first control the virus before allowing people back in the streets. We should not assume that people will wear masks properly. Equally important is to instruct and sensitize people on how to use face masks and why it is important.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Fatih Colkesen",
-        "author_inst": "Department of Clinical Immunology and Allergy, Necmettin Erbakan University Meram Faculty of Medicine,"
+        "author_name": "Evaldo Stanislau Affonso de Ara\u00fajo",
+        "author_inst": "1. Sao Judas Tadeu University, Medical School, 2. Hospital das Clinicas, University of Sao Paulo Medical School"
       },
       {
-        "author_name": "Oguzhan Kilincel",
-        "author_inst": "Department of  Psychiatry, Sakarya Yenikent State Hospital"
+        "author_name": "Fatima Maria Bernardes Henriques Amaral",
+        "author_inst": "Sao Judas Tadeu University, Medical School"
       },
       {
-        "author_name": "Mehmet Sozen",
-        "author_inst": "Department of  Endocrinology and Metabolism, Kocaeli University Faculty of  Medicine"
+        "author_name": "Dongmin Park",
+        "author_inst": "Sao Judas Tadeu University, Medical School"
       },
       {
-        "author_name": "Eray Yildiz",
-        "author_inst": "Department of Clinical Immunology and Allergy, Necmettin Erbakan University Meram Faculty of Medicine"
+        "author_name": "Ana Paola Ceraldi Cameira",
+        "author_inst": "Sao Judas Tadeu University, Medical School"
       },
       {
-        "author_name": "Sengul Beyaz",
-        "author_inst": "Division of  Clinical Immunology and Allergy, Department of Internal Medicine, Istanbul Faculty of Medicine, Istanbul University"
+        "author_name": "Murilo Augustinho Muniz da Cunha",
+        "author_inst": "Sao Judas Tadeu University, Medical School"
       },
       {
-        "author_name": "Fatma Colkesen",
-        "author_inst": "Department of  Infectious Diseases and Clinical Microbiology, University of  Health Sciences, Konya Training and Research Hospital"
+        "author_name": "Evelyn Gutierrez Karl",
+        "author_inst": "Sao Judas Tadeu University, Medical School"
       },
       {
-        "author_name": "Gokhan Aytekin",
-        "author_inst": "Department of  Clinical Immunology and Allergy, University of  Health Sciences, Konya Training and Research Hospital"
-      },
-      {
-        "author_name": "Mehmet Zahit Kocak",
-        "author_inst": "Department of  Medical Oncology, Meram Faculty of  Medicine, Necmettin Erbakan University"
-      },
-      {
-        "author_name": "Yakup Alsancak",
-        "author_inst": "Department of  Cardiology , Meram Faculty of  Medicine, Necmettin Erbakan University"
-      },
-      {
-        "author_name": "Murat Araz",
-        "author_inst": "Department of  Medical Oncology, Meram Faculty of  Medicine, Necmettin Erbakan University"
-      },
-      {
-        "author_name": "Sevket Arslan",
-        "author_inst": "Department of  Clinical Immunology and Allergy,   Necmettin Erbakan University Meram Faculty of  Medicine"
+        "author_name": "Sheila J Henderson",
+        "author_inst": "Alliant International University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "psychiatry and clinical psychology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.06.26.20140764",
@@ -1301407,41 +1303964,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.23.20138222",
-    "rel_title": "Phylogenomics and phylodynamics of SARS-CoV-2 retrieved genomes from India",
+    "rel_doi": "10.1101/2020.06.22.20134130",
+    "rel_title": "Impact of public health interventions on the COVID-19 epidemic: a stochastic model based on data from an African island",
     "rel_date": "2020-06-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20138222",
-    "rel_abs": "The ongoing SARS-CoV-2 pandemic is one of the biggest outbreaks after the Spanish flu of 1918. Understanding the epidemiology of viral outbreaks is the first step towards vaccine development programs. This is the first phylodynamics study attempted on of SARS-CoV-2 genomes from India to infer its current evolution in the context of an ongoing pandemic. Out of 286 retrieved SARS-CoV-2 whole genomes from India, 138 haplotypes were generated and analyzed. Median-joining network was built to investigate the relatedness of SARS-CoV-2 haplotypes in India. The BDSIR package of BEAST2 was used to calculate the reproduction number (R0) and the infectious rate of the virus. Past and current population trend was investigated using the stamp date method in coalescent Bayesian skyline plot, implemented in BEAST2 and by exponential growth prior in BEAST 1.10.4. Median-joining network reveals two distinct ancestral clusters A and B showing genetic affinities with Wuhan outbreak sample. The network also illustrates the autochthonous development of isolates in a few instances. High basic reproduction number of SARS-nCoV-2 in India points towards the phase of active community transmission. The Bayesian skyline plot revel exponential rise in the effective population size (Ne) of Indian isolates from the first week of January to the first week of April 2020. More genome sequencing and analyses of the virus will be required in coming days to monitor COVID19 after the upliftment of lock down in India.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20134130",
+    "rel_abs": "A stochastic model was created to simulate the impact of various healthcare measures on the COVID-19 epidemic. Travel restrictions and point of entry or exit screening help to delay the onset of the outbreak by a few weeks. Population surveillance is critical to detect the start of community transmission early and to avoid a surge in cases. Contact reduction and contact tracing are key interventions that can help to control the outbreak. To promptly curb the number of new cases, countries should diagnose patients using a highly sensitive test.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Sameera Farah",
-        "author_inst": "Department of Zoology, Laboratory of Molecular and Conservation Genetics, Govt. Vidarbha Institute of Science and Humanities, Amravati-444604-India; Department "
-      },
-      {
-        "author_name": "Ashwin Atkulwar",
-        "author_inst": "Department of Zoology, Laboratory of Molecular and Conservation Genetics, Govt. Vidarbha Institute of Science and Humanities, VMV Road, Amravati-444604-Indial; "
-      },
-      {
-        "author_name": "Manas Ranjan Praharaj",
-        "author_inst": "National Institute of Animal Biotechnology, Gowlidoddy, Hyderabad, Telangana-500032-India."
-      },
-      {
-        "author_name": "Raja Khan",
-        "author_inst": "Indian Veterinary Research Institute, Izatnagar, Bareilly, U.P - 243122, India."
-      },
-      {
-        "author_name": "Ravikumar Gandham",
-        "author_inst": "National Institute of Animal Biotechnology, Gowlidoddy, Hyderabad, Telangana-500032-India."
-      },
-      {
-        "author_name": "Mumtaz Baig",
-        "author_inst": "Department of Zoology, Laboratory of Molecular and Conservation Genetics, Govt. Vidarbha Institute of Science and Humanities, Amravati-444604-India; Department "
+        "author_name": "Dooshanveer Nuckchady",
+        "author_inst": "Dr. A. G. Jeetoo Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1302721,29 +1305258,113 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.24.20139329",
-    "rel_title": "A Decision Analytic Approach for Social Distancing Policies During the COVID-19 Pandemic",
+    "rel_doi": "10.1101/2020.06.25.20140384",
+    "rel_title": "Seroprevalence of Antibodies to SARS-CoV-2 in Six Sites in the United States, March 23-May 3, 2020",
     "rel_date": "2020-06-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139329",
-    "rel_abs": "The COVID-19 pandemic has become a crucial public health issue in many countries including the United States. In the absence of the right vaccine strain and sufficient antiviral stockpiles on hand, non-pharmaceutical interventions have become valuable public health tools at the early stages of the pandemic and they are employed by many countries across the globe. These interventions are designed to increase social distancing between individuals to reduce the transmission of the virus and eventually dampen the burden on the healthcare system. The virus transmissibility is a function of the average number of contacts individuals have in their communities and it is highly dependent on population density and daily mobility patterns, along with other social factors. These show significant variation across the United States. In this article, we study the effectiveness of social distancing measures in communities with different population density. Specifically, first we show how the empirical estimation of reproduction number differs for two completely different states, thus the experience of the COVID-19 outbreak is drastically different, suggesting different outbreak growth rates in practice. Second, we develop an age-structured compartmental model for simulating the disease spread in order to demonstrate the variation in the observed outbreak characteristics. We find that early trigger and late trigger options present a trade-off between the peak magnitude and the overall death toll of the outbreak which may also vary across different populations.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.25.20140384",
+    "rel_abs": "ImportanceReported cases of SARS-CoV-2 infection likely underestimate the prevalence of infection in affected communities. Large-scale seroprevalence studies provide better estimates of the proportion of the population previously infected.\n\nObjectiveTo estimate prevalence of SARS-CoV-2 antibodies in convenience samples from several geographic sites in the United States.\n\nDesignSerologic testing of convenience samples using residual sera obtained for routine clinical testing by two commercial laboratory companies.\n\nSettingConnecticut (CT), south Florida (FL), Missouri (MO), New York City metro region (NYC), Utah (UT), and Washington States (WA) Puget Sound region.\n\nParticipantsPersons of all ages with serum collected during intervals from March 23 through May 3, 2020.\n\nExposureSARS-CoV-2 virus infection.\n\nMain outcomes and measuresWe estimated the presence of antibodies to SARS-CoV-2 spike protein using an ELISA assay. We standardized estimates to the site populations by age and sex. Estimates were adjusted for test performance characteristics (96.0% sensitivity and 99.3% specificity). We estimated the number of infections in each site by extrapolating seroprevalence to site populations. We compared estimated infections to number of reported COVID-19 cases as of last specimen collection date.\n\nResultsWe tested sera from 11,933 persons. Adjusted estimates of the proportion of persons seroreactive to the SARS-CoV-2 spike protein ranged from 1.13% (95% confidence interval [CI] 0.70-1.94) in WA to 6.93% (95% CI 5.02-8.92) in NYC (collected March 23-April 1). For sites with later collection dates, estimates ranged from 1.85% (95% CI 1.00-3.23, collected April 6-10) for FL to 4.94% (95% CI 3.61-6.52) for CT (April 26-May 3). The estimated number of infections ranged from 6 to 24 times the number of reported cases in each site.\n\nConclusions and relevanceOur seroprevalence estimates suggest that for five of six U.S. sites, from late March to early May 2020, >10 times more SARS-CoV-2 infections occurred than the number of reported cases. Seroprevalence and under-ascertainment varied by site and specimen collection period. Most specimens from each site had no evidence of antibody to SARS-CoV-2. Tracking population seroprevalence serially, in a variety of specific geographic sites, will inform models of transmission dynamics and guide future community-wide public health measures.\n\nKey findingsO_ST_ABSQuestionC_ST_ABSWhat proportion of persons in six U.S. sites had detectable antibodies to SARS-CoV-2, March 23-May 3, 2020?\n\nFindingsWe tested 11,933 residual clinical specimens. We estimate that from 1.1% of persons in the Puget Sound to 6.9% in New York City (collected March 23-April 1) had detectable antibodies. Estimates ranged from 1.9% in south Florida to 4.9% in Connecticut with specimens collected during intervals from April 6-May 3. Six to 24 times more infections were estimated per site with seroprevalence than with case report data.\n\nMeaningFor most sites, evidence suggests >10 times more SARS-CoV-2 infections occurred than reported cases. Most persons in each site likely had no detectable SARS-CoV-2 antibodies.",
+    "rel_num_authors": 24,
     "rel_authors": [
       {
-        "author_name": "Zeynep Ertem",
-        "author_inst": "University of Southern California"
+        "author_name": "Fiona P. Havers",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Ozgur Araz",
-        "author_inst": "University of Nebraska"
+        "author_name": "Carrie Reed",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Maytee Cruz-Aponte",
-        "author_inst": "University of Puerto Rico"
+        "author_name": "Travis W. Lim",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Joel M. Montgomery",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "John D. Klena",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Aron J. Hall",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Alicia M. Fry",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Deborah L. Cannon",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Cheng-Feng Chiang",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Aridth Gibbons",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Inna Krapiunaya,",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Maria Morales-Betoulle",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Katherine Roguski",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Mohammed Rasheed",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Brandi Freeman",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Sandra Lester",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Lisa Mills",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Darin S. Carroll",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "S. Michelle Owen",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Jeffrey A. Johnson",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Vera A. Semenova",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "- State Collaborator Group",
+        "author_inst": "-"
+      },
+      {
+        "author_name": "Jarad Schiffer",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Natalie P. Thornburg",
+        "author_inst": "Centers for Disease Control and Prevention"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1304327,27 +1306948,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.24.20138982",
-    "rel_title": "Modeling the Covid-19 Pandemic Response of the US States",
+    "rel_doi": "10.1101/2020.06.24.20139196",
+    "rel_title": "How Many Lives Has Lockdown Saved in the UK?",
     "rel_date": "2020-06-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20138982",
-    "rel_abs": "BackgroundThe United States of America (USA) has been the country worst affected, in absolute terms, by the Covid-19 pandemic. The country comprises 50 states under a federal system. The impact of the pandemic has resulted in different responses at the state level, which are driven by differing intervention policies, demographics, connectedness and other factors. Understanding the dynamics of the Covid-19 pandemic at the state level is essential in predicting its future evolution.\n\nObjectiveOur objective is to identify and characterize multiple waves of the pandemic by analyzing the reported infected population curve in each of the 50 US states. Based on the intensity of the waves, characterized by declining, stationary, or increasing strengths, each states response can be inferred and quantified.\n\nMethodsWe apply a recently proposed multiple-wave model to fit the infected population data for each state in USA, and use the proposed Pandemic Response Index to quantify their response to the Covid-19 pandemic.\n\nResultsWe have analyzed reported infected cases from each one of the 50 USA states and the District of Columbia, based on the multiple-wave model, and present the relevant parameters. Multiple waves have been identified and this model is found to describe the data better. Each of the states can be classified into one of three distinct classes characterized by declining, increasing, or stationary strength of the waves following the initial one. The effectiveness of intervention measures can be inferred by the peak intensities of the waves, and states with similar population characteristics can be directly compared. We estimate how much lower the number of infections might have been, if early and strict intervention measures had been imposed to stop the disease spread at the first wave, as was the case for certain states. Based on our models results, we compute the value of the Pandemic Response Index, a recently introduced metric for quantifying in an objective manner the response to the pandemic.\n\nConclusionsOur results reveal a series of epidemic waves, characterizing USAs pandemic response at the state level, and also infer to what extent the imposition of early intervention measures could have had on the spread and impact of the disease. As of June 11, 2020, only 19 states and the District of Columbia (40% of the total) clearly exhibit declining trends in the numbers of reported infected cases, while 13 states exhibit stationary and 18 states increasing trends in the numbers of reported cases.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139196",
+    "rel_abs": "We compare the trajectory of deaths (both in hospitals and care homes) on a daily basis in Sweden and England and Wales (which constitute 90 per cent of the UK population) from 11 March to 7 August 2020, the latest date at which the relevant data is available for England and Wales.\n\nDeaths in both Sweden and England and Wales peaked on 8 April. The build up to the peak was very similar in both. Given the time lag between infection and death, the lockdown would have had little effect on the peak number of deaths.\n\nBy the first week of August, the deaths are very similar in both. However, from early May the decline in England and Wales has been much sharper.\n\nWe estimate that to 7 August, lockdown saved 17,700 lives in England and Wales, or just under 20,000 extrapolating to a UK level.",
     "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Georgios Neofotistos",
-        "author_inst": "Institute for Applied Computational Science (IACS),  John A. Paulson School of Engineering and Applied Sciences, Harvard University"
+        "author_name": "Rickard Bengt Emanuel Nyman",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Efthimios Kaxiras",
-        "author_inst": "Institute for Applied Computational Science (IACS),  John A. Paulson School of Engineering and Applied Sciences, Harvard University"
+        "author_name": "Paul Ormerod",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.06.24.20139014",
@@ -1305968,35 +1308589,27 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.06.24.168534",
-    "rel_title": "Lung expression of genes encoding SARS-CoV-2 cell entry molecules and antiviral restriction factors: interindividual differences are associated with age and germline variants",
+    "rel_doi": "10.1101/2020.06.23.167791",
+    "rel_title": "N-glycosylation network construction and analysis to modify glycans on the spike S glycoprotein of SARS-CoV-2.",
     "rel_date": "2020-06-24",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.24.168534",
-    "rel_abs": "Germline variants in genes involved in SARS-CoV-2 cell entry (i.e. ACE2 and TMPRSS2) may influence the susceptibility to infection, as may polymorphisms in genes involved in the innate host response to viruses (e.g. APOBEC3 family). We searched for polymorphisms acting, in lung tissue, as expression quantitative trait loci (eQTLs) for 15 candidate COVID-19 susceptibility genes, selected for their roles in virus cell entry and host antiviral responses. No significant eQTLs were identified for ACE2 and TMPRSS2 genes, whose expression levels did not associate with either sex or age of the 408 patients whose non-diseased lung tissue was analyzed. Instead, we identified seven cis-eQTLs (FDR<0.05) for APOBEC3D and APOBEC3G (rs139296, rs9611092, rs139331, rs8177832, rs17537581, rs61362448, and rs738469). The genetic control of the expression of APOBEC3 genes, which encode enzymes that interfere with virus replication, may explain interindividual differences in risk or severity of viral infections. Future studies should investigate the role of host genetics in COVID-19 patients using a genome-wide approach, to identify other genes whose expression levels are associated with susceptibility to SARS-CoV-2 infection or COVID-19 severity.\n\nAuthor summaryIdentification of expression quantitative trait loci (eQTLs) has become commonplace in functional studies on the role of individual genetic variants in susceptibility to diseases. In COVID-19, it has been proposed that individual variants in SARS-CoV-2 cell entry and innate host response genes may influence the susceptibility to infection. We searched for polymorphisms acting, in non-diseased lung tissue of 408 patients, as eQTLs for 15 candidate COVID-19 susceptibility genes, selected for their roles in virus cell entry and host antiviral responses. Seven cis-eQTLs were detected for APOBEC3D and APOBEC3G genes, which encode enzymes that interfere with virus replication. No significant eQTLs were identified for ACE2 and TMPRSS2 genes. Therefore, the identified eQTLs may represent candidate loci modulating interindividual differences in risk or severity of SARS-CoV-2 virus infection.",
-    "rel_num_authors": 4,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.23.167791",
+    "rel_abs": "Background The spike S-protein of SARS-CoV-2 is N-glycosylated. The N-glycan structure and composition of this glycoprotein influence how the virus interacts with host cells.Objective To identify a putative N-glycan biosynthesis pathway of SARS-CoV-2 (HEK293 cell recombinant) from previously published mass spectrometric studies, and to identify what effect blocking some enzymes has on the overall glycoprotein profile. Finally, our goal was to provide the biosynthesis network, and glycans in easy-to-use format for further glycoinformatics work.Methods We reconstructed the glycosylation network based on previously published empirical data using GNAT, a glycosylation network analysis tool. Our compilation of the network tool had 23 glycosyltransferase and glucosidase enzymes, and could infer the pathway of glycosylation machinery based on glycans identified in the virus spike protein. Once the glycan biosynthesis pathway was generated, we simulated the effect of blocking specific enzymes - Mannosidase-II and alpha-1,6-fucosyltransferase to see how they would affect the biosynthesis network.Results Of the 23 enzymes, a total of 12 were involved in glycosylation of SARS-CoV-2 - Man-Ia, MGAT1, MGAT2, MGAT4, MGAT5, B4GalT, B4GalT, Man II, SiaT, ST3GalI, ST3GalVI and FucT8. Blocking enzymes resulted in a substantially modified glycan profile of the protein.Conclusions A network analysis of N-glycan biosynthesis of SARS-CoV-2 spike protein shows an elaborate enzymatic pathway with several intermediate glycans, along with the ones identified by mass spectrometric studies. Variations in the final N-glycan profile of the virus, given its site-specific microheterogeneity, could be a factor in the host response to the infection and response to antibodies. Here we provide all the resources generated - the glycans derived from mass spectrometry and intermediate glycans in glycoCT xml format, and the biosynthesis network for future drug and vaccine development work.Competing Interest StatementThe authors have declared no competing interest.View Full Text",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Chiara E. Cotroneo",
-        "author_inst": "Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy"
-      },
-      {
-        "author_name": "Nunzia Mangano",
-        "author_inst": "Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy"
-      },
-      {
-        "author_name": "Tommaso A. Dragani",
-        "author_inst": "Fondazione IRCCS Istituto Nazionale Tumori"
+        "author_name": "Sridevi Krishnan",
+        "author_inst": "University of California Davis"
       },
       {
-        "author_name": "Francesca Colombo",
-        "author_inst": "Institute of Biomedical Technologies, National Research Council (ITB-CNR), Segrate (MI), Italy"
+        "author_name": "Giri P Krishnan",
+        "author_inst": "University of California San Diego"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "genomics"
+    "category": "physiology"
   },
   {
     "rel_doi": "10.1101/2020.06.24.169383",
@@ -1307201,131 +1309814,55 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.15.20117747",
-    "rel_title": "SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases",
+    "rel_doi": "10.1101/2020.06.22.20132910",
+    "rel_title": "Insufficient social distancing may be related to a future COVID-19 outbreak in Ijui-Brazil: Predictions of further social interventions.",
     "rel_date": "2020-06-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20117747",
-    "rel_abs": "Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we use longitudinal wastewater analysis to track SARS-CoV-2 dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. Viral titers in wastewater increased exponentially from mid-March to mid-April, after which they began to decline. Viral titers in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral titers as a convolution of back-dated new clinical cases with the viral shedding function of an individual. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. Finally, we found that wastewater viral titers at the neighborhood level correlate better with demographic variables than with population size. This work suggests that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and may shed light on infection characteristics that are difficult to capture in clinical investigations, such as early viral shedding dynamics.",
-    "rel_num_authors": 28,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20132910",
+    "rel_abs": "The coronavirus disease initiated in 2019 (COVID-19) has proven to be highly contagious and quickly became a pandemic. Nowadays, it presents higher transmission rates worldwide, chiefly in small Brazilian cities, as Ijui. Located in the northwestern of the State of Rio Grande do Sul (RS) with 83,475 inhabitants, Ijui was selected to receive a population-based survey organized in five steps, involving 2,222 subjects. Subjects were tested for the presence of antibodies against coronavirus (SARS-CoV-2) and answered questions regarding social distance adherence (SDA), daily preventive routine (DPR), comorbidities, and sociodemographic characteristics. In parallel, the local government registered the official COVID-19 cases in Ijui, and the mobile social distancing index (MSDI) was also registered. In this study, we demonstrate the decrease in the levels of SDA, DPR and MSDI before the beginning of COVID-19 community transmission in Ijui. Also, we provide predictions for cases, hospitalization, and deaths in the city. We concluded that the insufficient social distancing, evidenced by different methods, might have a strong relationship with the rapid increase of COVID-19 cases in Ijui. Our study predicts a closer outbreak of community infection of COVID-19, which could be avoided or attenuated if the levels of the social distancing in the population increase.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Fuqing Wu",
-        "author_inst": "MIT"
-      },
-      {
-        "author_name": "Amy Xiao",
-        "author_inst": "MIT"
-      },
-      {
-        "author_name": "Jianbo Zhang",
-        "author_inst": "MIT"
-      },
-      {
-        "author_name": "Katya Moniz",
-        "author_inst": "MIT"
-      },
-      {
-        "author_name": "Noriko Endo",
-        "author_inst": "Biobot Analytics, Inc."
-      },
-      {
-        "author_name": "Federica Armas",
-        "author_inst": "Singapore-MIT Alliance for Research and Technology"
-      },
-      {
-        "author_name": "Richard Bonneau",
-        "author_inst": "New York University"
-      },
-      {
-        "author_name": "Megan A Brown",
-        "author_inst": "New York University"
-      },
-      {
-        "author_name": "Mary Bushman",
-        "author_inst": "Harvard University"
-      },
-      {
-        "author_name": "Peter R Chai",
-        "author_inst": "Harvard University"
-      },
-      {
-        "author_name": "Claire Duvallet",
-        "author_inst": "Biobot Analytics, Inc."
-      },
-      {
-        "author_name": "Timothy B Erickson",
-        "author_inst": "Harvard University"
+        "author_name": "Thiago Gomes Heck",
+        "author_inst": "Universidade Regional do Noroeste do Estado do Rio Grande do Sul (Uniju\u00ed)"
       },
       {
-        "author_name": "Katelyn Foppe",
-        "author_inst": "Biobot Analytics, Inc."
+        "author_name": "Rafael Zancan Frantz",
+        "author_inst": "Regional University of Northwestern Rio Grande do Sul State (UNIJU\u00ed)"
       },
       {
-        "author_name": "Newsha Ghaeli",
-        "author_inst": "Biobot Analytics, Inc."
-      },
-      {
-        "author_name": "Xiaoqiong Gu",
-        "author_inst": "Singapore-MIT Alliance for Research and Technology"
+        "author_name": "Matias Nunes Frizzo",
+        "author_inst": "Universidade Regional do Noroeste do Estado do Rio Grande do Sul (Uniju\u00ed)"
       },
       {
-        "author_name": "William P Hanage",
-        "author_inst": "Harvard University"
+        "author_name": "Carlos Henrique Ramires Fran\u00e7ois",
+        "author_inst": "Universidade Regional do Noroeste do Estado do Rio Grande do Sul (Uniju\u00ed)"
       },
       {
-        "author_name": "Katherine H Huang",
-        "author_inst": "Broad Institute of MIT and Harvard"
+        "author_name": "Mirna Stela Ludwig",
+        "author_inst": "Universidade Regional do Noroeste do Estado do Rio Grande do Sul (Uniju\u00ed)"
       },
       {
-        "author_name": "Wei Lin Lee",
-        "author_inst": "Singapore-MIT Alliance for Research and Technology"
+        "author_name": "Marilia Arndt Mesenburg",
+        "author_inst": "Universidade Federal de Pelotas e Universidade Federal de Ci\u00eancias da Sa\u00fade de Porto Alegre"
       },
       {
-        "author_name": "Mariana Matus",
-        "author_inst": "Biobot Analytics, Inc."
+        "author_name": "Giovano Pereira Buratti",
+        "author_inst": "Universidade Regional do Noroeste do Estado do Rio Grande do Sul (Uniju\u00ed)"
       },
       {
-        "author_name": "Kyle A McElroy",
-        "author_inst": "Biobot Analytics, Inc."
+        "author_name": "L\u00edgia Beatriz Bento Franz",
+        "author_inst": "Universidade Regional do Noroeste do Estado do Rio Grande do Sul (Uniju\u00ed)"
       },
       {
-        "author_name": "Jonathan Nagler",
-        "author_inst": "Center for Data Science NYU"
-      },
-      {
-        "author_name": "Steven F Rhode",
-        "author_inst": "Massachusetts Water Resources Authority, Boston, MA"
-      },
-      {
-        "author_name": "Mauricio Santillana",
-        "author_inst": "Harvard University"
-      },
-      {
-        "author_name": "Joshua A Tucker",
-        "author_inst": "Center for Data Science NYU"
-      },
-      {
-        "author_name": "Stefan Wuertz",
-        "author_inst": "Nanyang Technological University"
-      },
-      {
-        "author_name": "Shijie Zhao",
-        "author_inst": "MIT"
-      },
-      {
-        "author_name": "Janelle Thompson",
-        "author_inst": "Nanyang Technological University"
-      },
-      {
-        "author_name": "Eric J Alm",
-        "author_inst": "Massachusetts Institute of Technology"
+        "author_name": "Evelise Moraes Berlezi",
+        "author_inst": "Universidade Regional do Noroeste do Estado do Rio Grande do Sul (Uniju\u00ed)"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.06.20.20135186",
@@ -1308643,21 +1311180,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.21.20136937",
-    "rel_title": "A Statistical and Dynamical Model for Forecasting COVID-19 Deaths based on a Hybrid Asymmetric Gaussian and SEIR Construct",
+    "rel_doi": "10.1101/2020.06.21.20136929",
+    "rel_title": "Derivation and Validation of Clinical Prediction Rule for COVID-19 Mortality in Ontario, Canada",
     "rel_date": "2020-06-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.21.20136937",
-    "rel_abs": "BackgroundThe limitations of forecasting (real-time statistical) and predictive (dynamic epidemiological) models have become apparent as COVID-19 has progressed from a rapid exponential ascent to a slower decent, which is dependent on unknowable parameters such as extent of social distancing and easing. We present a means to optimize a forecasting model by functionalizing our previously reported Asymmetric Gaussian model with SEIR-like parameters. Conversely, SEIR models can be adapted to better incorporate real-time data.\n\nMethodsOur previously reported asymmetric Gaussian model was shown to greatly improve on forecasting accuracy relative to use of symmetric functions, such as Gaussian and error functions for death rates and cumulative deaths, respectively. However, the reported asymmetric Gaussian implementation, which fitted well to the ascent and much of the recovery side of the real death rate data, was not agile enough to respond to changing social behavior that is resulting in persistence of infections and deaths in the later stage of recovery. We have introduced a time-dependent {sigma}(t) parameter to account for transmission rate variability due to the effects of behavioral changes such as social distancing and subsequent social easing. The {sigma}(t) parameter is analogous to the basic reproduction number R0 (infection factor) that is evidently not a constant during the progression of COVID-19 for a particular population. The popularly used SEIR model and its many variants are also incorporating a time dependent R0(t) to better describe the effects of social distancing and social easing to improve predictive capability when extrapolating from real-time data.\n\nResultsComparisons are given for the previously reported Asymmetric Gaussian model and to the revised, what we call, SEIR Gaussian model. We also have developed an analogous model based on R0(t) that we call SEIR Statistical model to show the correspondence that can be attained. It is shown that these two models can replicate each other and therefore provide similar forecasts based on fitting to the same real-time data. We show the results for reported U.S. death rates up to June 12, 2020 at which time the cumulative death count was 113,820. The forecasted cumulative deaths for these two models and compared to the University of Washington (UW) IHME model are 140,440, 139,272, and 149,690 (for 8/4/20) and 147,819, 148, 912, and 201,129 (for 10/1/20), respectively. We also show how the SEIR asymmetric Gaussian model can also account for various scenarios of social distancing, social easing, and even re-bound outbreaks where the death and case rates begin climbing again.\n\nConclusionsForecasting models, based on real-time data, are essential for guiding policy and human behavior to minimize the deadly impact of COVID-19 while balancing the need to socialize and energize the economy. It is becoming clear that changing social behavior from isolation to easing requires models that can adapt to the changing transmission rate in order to more accurately forecast death and case rates. We believe our asymmetric Gaussian approach has advantages over modified SEIR models in offering simpler governing equations that are dependent on fewer variables.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.21.20136929",
+    "rel_abs": "BackgroundSARS-CoV-2 is currently causing a high mortality global pandemic. However, the clinical spectrum of disease caused by this virus is broad, ranging from asymptomatic infection to cytokine storm with organ failure and death. Risk stratification of individuals with COVID-19 would be desirable for management, prioritization for trial enrollment, and risk stratification. We sought to develop a prediction rule for mortality due to COVID-19 in individuals with diagnosed infection in Ontario, Canada.\n\nMethodsData from Ontarios provincial iPHIS system were extracted for the period from January 23 to May 15, 2020. Both logistic regression-based prediction rules, and a rule derived using a Cox proportional hazards model, were developed in half the study and validated in remaining patients. Sensitivity analyses were performed with varying approaches to missing data.\n\nResults21,922 COVID-19 cases were reported. Individuals assigned to the derivation and validation sets were broadly similar. Age and comorbidities (notably diabetes, renal disease and immune compromise) were strong predictors of mortality. Four point-based prediction rules were derived (base case, smoking excluded as a predictor, long-term care excluded as a predictor, and Cox model based). All rules displayed excellent discrimination (AUC for all rules > 0.92) and calibration (both by graphical inspection and P > 0.50 by Hosmer-Lemeshow test) in the derivation set. All rules performed well in the validation set and were robust to random replacement of missing variables, and to the assumption that missing variables indicated absence of the comorbidity or characteristic in question.\n\nConclusionsWe were able to use a public health case-management data system to derive and internally validate four accurate, well-calibrated and robust clinical prediction rules for COVID-19 mortality in Ontario, Canada. While these rules need external validation, they may be a useful tool for clinical management, risk stratification, and clinical trials.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jack A. Syage",
-        "author_inst": "ImmunogenX"
+        "author_name": "David Fisman",
+        "author_inst": "University of Toronto"
+      },
+      {
+        "author_name": "Amy L. Greer",
+        "author_inst": "University of Guelph"
+      },
+      {
+        "author_name": "Ashleigh Tuite",
+        "author_inst": "University of Toronto"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1310113,95 +1312658,71 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.23.20137596",
-    "rel_title": "Platelets can contain SARS-CoV-2 RNA and are hyperactivated in COVID-19",
+    "rel_doi": "10.1101/2020.06.23.20137521",
+    "rel_title": "SARS CoV-2 Serosurvey in Addis Ababa, Ethiopia",
     "rel_date": "2020-06-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20137596",
-    "rel_abs": "RationaleIn addition to the overwhelming lung inflammation that prevails in COVID-19, hypercoagulation and thrombosis contribute to the lethality of subjects infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Platelets are chiefly implicated in thrombosis. Moreover, they can interact with viruses and are an important source of inflammatory mediators. While a lower platelet count is associated with severity and mortality, little is known about platelet function during COVID-19.\n\nObjectiveTo evaluate the contribution of platelets to inflammation and thrombosis in COVID-19 patients.\n\nMethods and ResultsWe document the presence of SARS-CoV-2 RNA in platelets of COVID-19 patients. Exhaustive assessment of cytokines in plasma and in platelets revealed the modulation of platelet-associated cytokine levels in COVID-19, pointing to a direct contribution of platelets to the plasmatic cytokine load. Moreover, we demonstrate that platelets release their alpha- and dense-granule contents and phosphatidylserine-exposing extracellular vesicles. Functionally, platelets were hyperactivated in COVID-19 subjects, with aggregation occurring at suboptimal thrombin concentrations. Furthermore, platelets adhered more efficiently onto collagen-coated surfaces under flow conditions.\n\nConclusionsThese data suggest that platelets could participate in the dissemination of SARS-CoV-2 and in the overwhelming thrombo-inflammation observed in COVID-19. Thus, blockade of platelet activation pathways may improve outcomes in this disease.\n\nKEY POINTSPlatelets are a source of inflammatory cytokines and degranulate in COVID-19 Platelets contain SARS-CoV-2 RNA molecules and are prone to activation in COVID-19\n\nSubject termsInfectious diseases/Emerging infectious diseases, SARS-CoV-2, COVID-19, Hematology, Platelets",
-    "rel_num_authors": 19,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20137521",
+    "rel_abs": "The global COVID-19 pandemic caused by SARS CoV-2 is causing both mortality/morbidity and collateral social and economic damage related to public panic and aggressive public policy measures to contain the disease worldwide.(1) The epidemic appears to have taken hold much more slowly in sub-Saharan Africa than most of the world.(2) Antibody testing to evaluate the population proportion previously infected with SARS CoV-2 has the potential to guide public policy, but has not been reported so far for sub-Saharan Africa.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Younes Zaid",
-        "author_inst": "Cheikh Zaid Hospital; Mohammed V University"
+        "author_name": "John H Kempen",
+        "author_inst": "Massachusetts Eye and Ear/Harvard Medical School"
       },
       {
-        "author_name": "Florian Puhm",
-        "author_inst": "Universite Laval"
+        "author_name": "Aida Abashawl",
+        "author_inst": "5.\tBerhan Public Health and Eye Care Consultancy"
       },
       {
-        "author_name": "Isabelle Allaeys",
-        "author_inst": "Universite Laval"
+        "author_name": "Hilkiah Kinfemichael",
+        "author_inst": "MyungSung Medical School"
       },
       {
-        "author_name": "Abdallah Naya",
-        "author_inst": "Hassan II University"
+        "author_name": "Mesfin Nigussie Difabachew",
+        "author_inst": "International Clinical Laboratories"
       },
       {
-        "author_name": "Mounia Oudghiri",
-        "author_inst": "Hassan II University"
+        "author_name": "Christopher J Kempen",
+        "author_inst": "MyungSung Christian Medical Center (MCM) Eye Unit, Addis Ababa, Ethiopia"
       },
       {
-        "author_name": "Loubna Khalki",
-        "author_inst": "Mohammed VI University of Health Sciences (UM6SS)"
+        "author_name": "Melaku Tesfaye Debele",
+        "author_inst": "International Clinical Laboratories, Addis Ababa"
       },
       {
-        "author_name": "Youness Limami",
-        "author_inst": "Cheikh Zaid Hospital"
+        "author_name": "Abel A Menkir",
+        "author_inst": "MyungSung Medical College, Addis Ababa, Ethiopia"
       },
       {
-        "author_name": "Nabil Zaid",
-        "author_inst": "Mohammed V University"
+        "author_name": "Maranatha T Assefa",
+        "author_inst": "MyungSung Medical College, Addis Ababa, Ethiopia"
       },
       {
-        "author_name": "Khalid Sadki",
-        "author_inst": "Mohammed V University"
+        "author_name": "Eyob H Asfaw",
+        "author_inst": "MyungSung Medical College, Addis Ababa, Ethiopia"
       },
       {
-        "author_name": "Rafiqua Ben El Haj",
-        "author_inst": "Cheikh Zaid Hospital"
+        "author_name": "Leul B Habtegabriel",
+        "author_inst": "MyungSung Medical College, Addis Ababa, Ethiopia"
       },
       {
-        "author_name": "Wissal Maher",
-        "author_inst": "Cheikh Zaid Hospital"
-      },
-      {
-        "author_name": "Lamiae Belayachi",
-        "author_inst": "Cheikh Zaid Hospital"
-      },
-      {
-        "author_name": "Bouchra Belefquih",
-        "author_inst": "Cheikh Zaid Hospital"
-      },
-      {
-        "author_name": "Amina Benouda",
-        "author_inst": "Cheikh Zaid Hospital"
-      },
-      {
-        "author_name": "Amine Cheikh",
-        "author_inst": "Cheikh Zaid Hospital"
-      },
-      {
-        "author_name": "Yahia Cherrah",
-        "author_inst": "Cheikh Zaid Hospital"
-      },
-      {
-        "author_name": "Louis Flamand",
-        "author_inst": "Universite Laval"
+        "author_name": "Yohannes Sitotaw Addisie",
+        "author_inst": "Ethiopia Biotechnology Institute"
       },
       {
-        "author_name": "Fadila Guessous",
-        "author_inst": "Mohammed VI University of Health Sciences (UM6SS); University of Virginia"
+        "author_name": "Eric J Nilles",
+        "author_inst": "Brigham and Women's Hospital/Harvard Medical School"
       },
       {
-        "author_name": "Eric Boilard",
-        "author_inst": "Universite Laval"
+        "author_name": "Joseph Craig Longenecker",
+        "author_inst": "Kuwait University, Health Sciences Center, Faculty of Medicine; Faculty of Public Health"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.06.16.155457",
@@ -1311715,57 +1314236,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.20.20134387",
-    "rel_title": "A systematic review and meta-analysis reveals long and dispersive incubation period of COVID-19",
+    "rel_doi": "10.1101/2020.06.18.20132571",
+    "rel_title": "Transcriptomic profiling of disease severity in patients with COVID-19 reveals role of blood clotting and vasculature related genes",
     "rel_date": "2020-06-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.20.20134387",
-    "rel_abs": "BackgroundThe incubation period of SARS-CoV-2 remains uncertain, which has important implications for estimating transmission potential, forecasting epidemic trends, and decision-making in prevention and control.\n\nPurposeTo estimate the central tendency and dispersion for incubation period of COVID-19 and, in turn, assess the effect of a certain length of quarantine for close contacts in active monitoring.\n\nData SourcesPubMed, Embase, medRxiv, bioRxiv, and arXiv, searched up to April 26, 2020\n\nStudy SelectionCOVID-19 studies that described either individual-level incubation period data or summarized statistics for central tendency and dispersion measures of incubation period were recruited.\n\nData ExtractionFrom each recruited study, either individual-level incubation period data or summarized statistics for central tendency and dispersion measures were extracted, as well as population characteristics including sample size, average age, and male proportion.\n\nData SynthesisFifty-six studies encompassing 4 095 cases were included in this meta-analysis. The estimated median incubation period for general transmissions was 5.8 days [95% confidence interval (95%CI), 5.3 to 6.2 d]. Median and dispersion were higher for SARS-CoV-2 incubation compared to other viral respiratory infections. Furthermore, about 20 in 10 000 contacts in active monitoring would develop symptoms after 14 days, or below 1 in 10 000 for young-age infections or asymptomatic transmissions.\n\nLimitationSmall sample sizes for subgroups; some data were possibly used repeatedly in different studies; limited studies for outside mainland China; non-negligible intra-study heterogeneity.\n\nConclusionThe long, dispersive incubation period of SARS-CoV-2 contributes to the global spread of COVID-19. Yet, a 14-day quarantine period is sufficient to trace and identify symptomatic infections, which while could be justified according to a better understanding of the crucial parameters.",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20132571",
+    "rel_abs": "COVID-19 caused by SARS-CoV-2 manifests as a range of symptoms. Understanding the molecular mechanisms responsible for immuno-pathogenesis of disease is important for treatment and management of COVID-19. We examined host transcriptomes in moderate and severe COVID-19 cases with a view to identifying pathways that affect its progression. RNA extracted from whole blood of COVID-19 cases was analysed by microarray analysis. Moderate and severe cases were compared with healthy controls and differentially regulated genes (DEGs) categorized into cellular pathways.\n\nDEGs in COVID-19 cases were mostly related to host immune activation and cytokine signaling, pathogen uptake, host defenses, blood and vasculature genes, and SARS-CoV-2- and other virus-affected pathways. The DEGs in these pathways were increased in severe compared with moderate cases. In a severe COVID-19 patient with an unfavourable outcome we observed dysregulation of genes in platelet homeostasis and cardiac conduction and fibrin clotting with disease progression.\n\nCOVID-19 morbidity is associated with cytokine activation, cardiovascular risk and thrombosis. We identified DEGs related to dysregulation of blood clotting and homeostasis, platelet activation pathways and to be associated with disease progression. These can be biomarkers of disease progression and also potential targets for treatment interventions in COVID-19.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Yongyue Wei",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Kiran Iqbal Masood",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Liangmin Wei",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Syed Faisal Mahmood",
+        "author_inst": "The Aga Khan University"
       },
       {
-        "author_name": "Yihan Liu",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Saba Shahid",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Lihong Huang",
-        "author_inst": "Zhongshan Hospital Fudan University"
+        "author_name": "Nosheen Nasir",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Sipeng Shen",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Najia Ghanchi",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Ruyang Zhang",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Asghar Nasir",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Jiajin Chen",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Bushra Jamil",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Yang Zhao",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Iffat Khanum",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Hongbing Shen",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Safina Razzak",
+        "author_inst": "The Aga Khan University, Pakistan"
       },
       {
-        "author_name": "Feng Chen",
-        "author_inst": "Nanjing Medical University"
+        "author_name": "Akbar Kanji",
+        "author_inst": "The Aga Khan University, Pakistan"
+      },
+      {
+        "author_name": "Zahra Hasan",
+        "author_inst": "The Aga Khan University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1313068,99 +1315593,47 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.21.162396",
-    "rel_title": "Calcitriol, the active form of vitamin D, is a promising candidate for COVID-19 prophylaxis",
+    "rel_doi": "10.1101/2020.06.22.133355",
+    "rel_title": "Companion vaccine Bioinformatic design tool reveals limited functional genomic variability of SARS-Cov-2 Spike Receptor Binding Domain",
     "rel_date": "2020-06-22",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.21.162396",
-    "rel_abs": "COVID-19, the disease caused by SARS-CoV-2 (1), was declared a pandemic by the World Health Organization (WHO) in March 2020 (2). While awaiting a vaccine, several antivirals are being used to manage the disease with limited success (3, 4). To expand this arsenal, we screened 4 compound libraries: a United States Food and Drug Administration (FDA) approved drug library, an angiotensin converting enzyme-2 (ACE2) targeted compound library, a flavonoid compound library as well as a natural product library. Of the 121 compounds identified with activity against SARS-CoV-2, 7 were shortlisted for validation. We show for the first time that the active form of Vitamin D, calcitriol, exhibits significant potent activity against SARS-CoV-2. This finding paves the way for consideration of host-directed therapies for ring prophylaxis of contacts of SARS-CoV-2 patients.",
-    "rel_num_authors": 20,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.22.133355",
+    "rel_abs": "BackgroundTracking the genetic variability of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is a crucial challenge. Mainly to identify target sequences in order to generate robust vaccines and neutralizing monoclonal antibodies, but also to track viral genetic temporal and geographic evolution and to mine for variants associated with reduced or increased disease severity. Several online tools and bioinformatic phylogenetic analyses have been released, but the main interest lies in the Spike protein, which is the pivotal element of current vaccine design, and in the Receptor Binding Domain, that accounts for most of the neutralizing the antibody activity.\n\nMethodsHere, we present an open-source bioinformatic protocol, and a web portal focused on SARS-CoV-2 single mutations and minimal consensus sequence building as a companion vaccine design tool. Furthermore, we provide immunogenomic analyses to understand the impact of the most frequent RBD variations.\n\nResultsResults on the whole GISAID sequence dataset at the time of the writing (October 2020) reveals an emerging mutation, S477N, located on the central part of the Spike protein Receptor Binding Domain, the Receptor Binding Motif. Immunogenomic analyses revealed some variation in mutated epitope MHC compatibility, T-cell recognition, and B-cell epitope probability for most frequent human HLAs.\n\nConclusionsThis work provides a framework able to track down SARS-CoV-2 genomic variability.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Chee Keng Mok",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Yan Ling Ng",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Bintou Ahmadou Ahidjo",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Regina Ching Hua Lee",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Marcus Wing Choy Loe",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Jing Liu",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Kai Sen Tan",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Parveen Kaur",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Wee Joo Chng",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "John Eu Li Wong",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "De Yun Wang",
-        "author_inst": "National University of Singapore"
-      },
-      {
-        "author_name": "Er Wei Hao",
-        "author_inst": "Guangxi University of Chinese Medicine, China"
-      },
-      {
-        "author_name": "Xiaotao Hao",
-        "author_inst": "Guangxi University of Chinese Medicine"
-      },
-      {
-        "author_name": "Yong Wah Tan",
-        "author_inst": "Agency for Science, Technology and Research, Singapore"
+        "author_name": "Alice Massacci",
+        "author_inst": "Takis srl, Rome"
       },
       {
-        "author_name": "Tze Minn Mak",
-        "author_inst": "National Public Health Laboratory, Singapore"
+        "author_name": "Eleonora Sperandio",
+        "author_inst": "Biostatistics, Bioinformatics and Clinical Trial Center, IRCCS Regina Elena National Cancer Institute"
       },
       {
-        "author_name": "Cui Lin",
-        "author_inst": "National Public Health Laboratory, Singapore"
+        "author_name": "Mariano Maffei",
+        "author_inst": "EvviVax srl"
       },
       {
-        "author_name": "Raymond V.T.P Lin",
-        "author_inst": "National Public Health Laboratory, Singapore"
+        "author_name": "Fabio Palombo",
+        "author_inst": "Neomatrix srl, Rome"
       },
       {
-        "author_name": "Paul A Tambyah",
-        "author_inst": "National University of Singapore"
+        "author_name": "Luigi Aurisicchio",
+        "author_inst": "Takis srl, Rome"
       },
       {
-        "author_name": "Jiagang Deng",
-        "author_inst": "Guangxi University of Chinese Medicine, China"
+        "author_name": "Gennaro Ciliberto",
+        "author_inst": "Scientific Direction IRCCS Regina Elena National Cancer Institute"
       },
       {
-        "author_name": "Justin Jang Hann Chu",
-        "author_inst": "National University of Singapore"
+        "author_name": "Matteo Pallocca",
+        "author_inst": "IRCSS Regina Elena National Cancer Institute"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_by_nc_nd",
+    "type": "confirmatory results",
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2020.06.17.20134262",
@@ -1314994,71 +1317467,47 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.06.20.162560",
-    "rel_title": "Multi-Omics and Integrated Network Approach to Unveil Evolutionary Patterns, Mutational Hotspots, Functional Crosstalk and Regulatory Interactions in SARS-CoV-2",
+    "rel_doi": "10.1101/2020.06.19.20135996",
+    "rel_title": "The support needs of Australian primary health care nurses during the COVID-19 pandemic",
     "rel_date": "2020-06-20",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.20.162560",
-    "rel_abs": "SARS-CoV-2 pandemic resulted in 92 million cases in a span of one year. The study focuses on understanding population specific variations attributing its high rate of infections in specific geographical regions particularly in USA. Rigorous phylogenomic network analysis of complete SARS-CoV-2 genomes (245) inferred five central clades named a (ancestral), b, c, d and e (subtype e1 & e2). The clade d & e2 were found exclusively comprising of USA. Clades were distinguished by 10 co-mutational combinations in Nsp3, ORF8, Nsp13, S, Nsp12, Nsp2 and Nsp6. Our analysis revealed that only 67.46% of SNP mutations were at amino acid level. T1103P mutation in Nsp3 was predicted to increase protein stability in 238 strains except 6 strains which were marked as ancestral type; whereas co-mutation (P409L & Y446C) in Nsp13 were found in 64 genomes from USA highlighting its 100% co-occurrence. Docking highlighted mutation (D614G) caused reduction in binding of Spike proteins with ACE2, but it also showed better interaction with TMPRSS2 receptor contributing to high transmissibility among USA strains. We also found host proteins, MYO5A, MYO5B, MYO5C had maximum interaction with viral proteins (N, S, M). Thus, blocking the internalization pathway by inhibiting MYO5 proteins which could be an effective target for COVID-19 treatment. The functional annotations of the HPI network were found to be closely associated with hypoxia and thrombotic conditions confirming the vulnerability and severity of infection. We also screened CpG islands in Nsp1 & N conferring ability of SARS-CoV-2 to enter and trigger ZAP activity inside host cell.\n\nImportanceIn the current study we presented a global view of mutational pattern observed in SARS-CoV-2 virus transmission. This provided a who-infect-whom geographical model since the early pandemic. This is hitherto the most comprehensive comparative genomics analysis of full-length genomes for co-mutations at different geographical regions specially in USA strains. Compositional structural biology results suggested that mutations have balance of contrary forces effect on pathogenicity suggesting only few mutations to effective at translation level but not all. Novel HPI analysis and CpG predictions elucidates the proof of concept of hypoxia and thrombotic conditions in several patients. Thus, the current study focuses the understanding of population specific variations attributing high rate of SARS-CoV-2 infections in specific geographical regions which may eventually be vital for the most severely affected countries and regions for sharp development of custom-made vindication strategies.",
-    "rel_num_authors": 13,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.19.20135996",
+    "rel_abs": "AimTo identify Australian primary healthcare nurses immediate support needs during the COVID-19 pandemic.\n\nBackgroundCOVID-19 has had widespread implications for primary healthcare nurses. Supporting these nurses capacity to deliver quality care ensures that ongoing health needs can be met.\n\nMethodsPrimary healthcare nurses were recruited to an online survey via social media and professional organisations in April 2020.\n\nResultsSix-hundred and thirty-seven responses were included in analysis. Participants provided 1213 statements about perceived supports required to provide quality clinical care. From these, seven key categories emerged, namely; personal protective equipment, communication, funding, industrial issues, self-care, workplace factors and valuing nurses.\n\nConclusionA number of key issues relating to personal health and safety, care quality, and job security need to be addressed to support primary healthcare nurses during the COVID-19 pandemic. Addressing these support issues can assist in retaining nurses and optimising the role of primary healthcare nurses during a pandemic.\n\nImplications for nursing managementResponding to the needs of primary healthcare nurses has the potential to facilitate their role in providing community based healthcare. This knowledge can guide the provision of support for primary healthcare nurses during the current pandemic, as well as informing planning for future health crises.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Vipin Gupta",
-        "author_inst": "PHIXGEN PVT. LTD"
-      },
-      {
-        "author_name": "Shazia Haider",
-        "author_inst": "Jaypee Institute of Information Technology, Noida"
-      },
-      {
-        "author_name": "Mansi Verma",
-        "author_inst": "Sri Venkateswara College, University of Delhi"
-      },
-      {
-        "author_name": "Nirjara Singhvi",
-        "author_inst": "University of Delhi"
-      },
-      {
-        "author_name": "Kalaiarasan Ponnusamy",
-        "author_inst": "Jawaharlal Nehru University"
-      },
-      {
-        "author_name": "Md. Zubbair Malik",
-        "author_inst": "Jawaharlal Nehru University, New Delhi, India."
-      },
-      {
-        "author_name": "Helianthous Verma",
-        "author_inst": "Ramjas College, University of Delhi"
+        "author_name": "Elizabeth Halcomb",
+        "author_inst": "University of Wollongong"
       },
       {
-        "author_name": "Roshan Kumar",
-        "author_inst": "Magadh University, Bodh Gaya, Bihar"
+        "author_name": "Anna Williams",
+        "author_inst": "University of Notre Dame, Sydney"
       },
       {
-        "author_name": "Utkarsh Sood",
-        "author_inst": "The Energy and Resources Institute"
+        "author_name": "Christine Ashley",
+        "author_inst": "University of Wollongong"
       },
       {
-        "author_name": "Princy Hira",
-        "author_inst": "Maitreyi College, University of Delhi."
+        "author_name": "Susan McInnes",
+        "author_inst": "University of Wollongong"
       },
       {
-        "author_name": "Shiva Satija",
-        "author_inst": "Sri Venkateswara College, University of Delhi"
+        "author_name": "Catherine Stephen",
+        "author_inst": "University of Wollongong"
       },
       {
-        "author_name": "Rup Lal",
-        "author_inst": "The Energy and Resources Institute"
+        "author_name": "Kaara Ray Calma",
+        "author_inst": "University of Wollongong"
       },
       {
-        "author_name": "Yogendra Singh",
-        "author_inst": "University of Delhi"
+        "author_name": "Sharon James",
+        "author_inst": "University of Wollongong"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "nursing"
   },
   {
     "rel_doi": "10.1101/2020.06.19.20134908",
@@ -1316424,25 +1318873,53 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.18.20134700",
-    "rel_title": "Predictable county-level estimates of R0 for COVID-19 needed for public health planning in the USA",
+    "rel_doi": "10.1101/2020.06.18.20134346",
+    "rel_title": "The Relationship between the Global Burden of Influenza from 2017-2019 and COVID-19",
     "rel_date": "2020-06-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20134700",
-    "rel_abs": "The basic reproduction number, R0, determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Estimated R0 values are only useful, however, if they accurately predict the future potential rate of spread. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA. Most of the high among-county variance in the rate of spread was explained by four factors: the timing of the county-level outbreak (partial R2 = 0.093), population size (partial R2 = 0.34), population density (partial R2 = 0.13), and spatial location (partial R2 = 0.42). Of these, the effect of timing is explained by early steps that people and governments took to reduce transmission, and population size is explained by the sample size of deaths that affects the statistical ability to estimate R0. For predictions of future spread, population density is important, likely because it scales the average contact rate among people. To generate support for a possible explanation for the importance of spatial location, we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread (P = 0.016). The high predictability of R0 based on population density and spatial location allowed us to extend estimates to all 3109 counties in the lower 48 States. The high variation of R0 among counties argues for public health policies that are enacted at the county level for controlling COVID-19.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20134346",
+    "rel_abs": "BackgroundSARS-CoV-2 and influenza are lipid-enveloped viruses with differential morbidity and mortality but shared modes of transmission. With a descriptive epidemiological framing, we assessed whether historical patterns of regional influenza burden are reflected in the observed heterogeneity in COVID-19 cases across regions of the world.\n\nMethodsWeekly surveillance data reported in FluNet from January 2017-December 2019 for influenza and World Health Organization for COVID-19 (to May 31, 2020) across the seven World Bank regions were used to assess the total and annual number of influenza and COVID-19 cases per country, within and across all regions, to generate comparative descending ranks from highest to lowest burden of disease.\n\nResultsAcross regions, rankings of influenza and COVID-19 were relatively consistent. Europe and Central Asia and North America ranked first and second for COVID-19 and second and first for influenza, respectively. East Asia and the Pacific traditionally ranked higher for influenza with recent increases in COVID-19 consistent with influenza season. Across regions, Sub-Saharan Africa ranked amongst the least affected by both influenza and COVID-19.\n\nConclusionConsistency in the regional distribution of the burden of COVID-19 and influenza suggest shared individual, structural, and environmental determinants of transmission. Using a descriptive epidemiological framework to assess shared regional trends for rapidly emerging respiratory pathogens with better studied respiratory infections may provide further insights into the differential impacts of non-pharmacologic interventions and intersections with environmental conditions. Ultimately, forecasting trends and informing interventions for novel respiratory pathogens like COVID-19 should leverage epidemiologic patterns in the relative burden of past respiratory pathogens as prior information.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Anthony R Ives",
-        "author_inst": "University of Wisconsin-Madison"
+        "author_name": "Stefan D Baral",
+        "author_inst": "JHSPH"
       },
       {
-        "author_name": "Claudio Bozzuto",
-        "author_inst": "Wildlife Analysis GmbH, Zurich, Switzerland"
+        "author_name": "Katherine B Rucinski",
+        "author_inst": "JHSPH"
+      },
+      {
+        "author_name": "Jean Olivier Twahirwa Rwema",
+        "author_inst": "JHSPH"
+      },
+      {
+        "author_name": "Amrita Rao",
+        "author_inst": "JHSPH"
+      },
+      {
+        "author_name": "Neia Prata Menezes",
+        "author_inst": "JHSPH"
+      },
+      {
+        "author_name": "Daouda Diouf",
+        "author_inst": "Enda Sant\u00e9"
+      },
+      {
+        "author_name": "Adeeba Kamarulzaman",
+        "author_inst": "Universiti Malaya"
+      },
+      {
+        "author_name": "Nancy Phaswana-Mafuya",
+        "author_inst": "North West University"
+      },
+      {
+        "author_name": "Sharmistha Mishra",
+        "author_inst": "University of Toronto"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1318722,35 +1321199,71 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.06.19.161687",
-    "rel_title": "Cytosine deamination in SARS-CoV-2 leads to progressive CpG depletion.",
+    "rel_doi": "10.1101/2020.06.19.158717",
+    "rel_title": "No evidence of coronaviruses or other potentially zoonotic viruses in Sunda pangolins (Manis javanica) entering the wildlife trade via Malaysia.",
     "rel_date": "2020-06-19",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.19.161687",
-    "rel_abs": "RNA viruses use CpG reduction to evade the host cell defense, but the driving mechanisms are still largely unknown. In an attempt to address this we used a rapidly growing genomic dataset of SARS-CoV-2 with relevant metadata information. Remarkably, by simply ordering SARS-CoV-2 genomes by their date of collection, we find a progressive increase of C-to-U substitutions resulting in 5'-UCG-3' motif reduction that in turn have reduced the CpG frequency over just a few months of observation. This is consistent with APOBEC-mediated RNA editing resulting in CpG reduction, thus allowing the virus to escape ZAP-mediated RNA degradation. Our results thus link the dynamics of target sequences in the viral genome for two known host molecular defense mechanisms, mediated by the APOBEC and ZAP proteins.",
-    "rel_num_authors": 4,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.19.158717",
+    "rel_abs": "The legal and illegal trade in wildlife for food, medicine and other products is a globally significant threat to biodiversity that is also responsible for the emergence of pathogens that threaten human and livestock health and our global economy. Trade in wildlife likely played a role in the origin of COVID-19, and viruses closely related to SARS-CoV-2 have been identified in bats and pangolins, both traded widely. To investigate the possible role of pangolins as a source of potential zoonoses, we collected throat and rectal swabs from 334 Sunda pangolins (Manis javanica) confiscated in Peninsular Malaysia and Sabah between August 2009 and March 2019. Total nucleic acid was extracted for viral molecular screening using conventional PCR protocols used to routinely identify known and novel viruses in extensive prior sampling (>50,000 mammals). No sample yielded a positive PCR result for any of the targeted viral families - Coronaviridae, Filoviridae, Flaviviridae, Orthomyxoviridae and Paramyxoviridae. In light of recent reports of coronaviruses including a SARS-CoV-2 related virus in Sunda pangolins in China, the lack of any coronavirus detection in our  upstream market chain samples suggests that these detections in  downstream animals more plausibly reflect exposure to infected humans, wildlife or other animals within the wildlife trade network. While confirmatory serologic studies are needed, it is likely that Sunda pangolins are incidental hosts of coronaviruses. Our findings further support the importance of ending the trade in wildlife globally.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Mukhtar Sadykov",
-        "author_inst": "King Abdullah University of Science and Technology"
+        "author_name": "Jimmy Lee",
+        "author_inst": "EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY 10001-2320"
       },
       {
-        "author_name": "Tobias Mourier",
-        "author_inst": "King Abdullah University of Science and Technology"
+        "author_name": "Tom Hughes",
+        "author_inst": "EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY 10001-2320"
       },
       {
-        "author_name": "Qingtian Guan",
-        "author_inst": "King Abdullah University of Science and Technology"
+        "author_name": "Mei-Ho Lee",
+        "author_inst": "EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY 10001-2320"
       },
       {
-        "author_name": "Arnab Pain",
-        "author_inst": "King Abdullah University of Science and Technology"
+        "author_name": "Hume Field",
+        "author_inst": "EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY 10001-2320"
+      },
+      {
+        "author_name": "Jeffrine Japning Rovie-Ryan",
+        "author_inst": "National Wildlife Forensic Laboratory, Department of Wildlife and National Parks (PERHILITAN), Peninsular Malaysia, KM 10, Jalan Cheras, 56100, Kuala Lumpur, Ma"
+      },
+      {
+        "author_name": "Frankie Thomas Sitam",
+        "author_inst": "National Wildlife Forensic Laboratory, Department of Wildlife and National Parks (PERHILITAN), Peninsular Malaysia, KM 10, Jalan Cheras, 56100, Kuala Lumpur, Ma"
+      },
+      {
+        "author_name": "Symphorosa Sipangkui",
+        "author_inst": "Sabah Wildlife Department, 5th Floor, B Block, Wisma MUIS, 88100, Kota Kinabalu, Sabah, Malaysia."
+      },
+      {
+        "author_name": "Senthilvel K.S.S. Nathan",
+        "author_inst": "Sabah Wildlife Department, 5th Floor, B Block, Wisma MUIS, 88100, Kota Kinabalu, Sabah, Malaysia."
+      },
+      {
+        "author_name": "Diana Ramirez",
+        "author_inst": "Sabah Wildlife Department, 5th Floor, B Block, Wisma MUIS, 88100, Kota Kinabalu, Sabah, Malaysia."
+      },
+      {
+        "author_name": "Subbiah Vijay Kumar",
+        "author_inst": "Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia."
+      },
+      {
+        "author_name": "Helen Lasimbang",
+        "author_inst": "Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia."
+      },
+      {
+        "author_name": "Jonathan H. Epstein",
+        "author_inst": "EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY 10001-2320"
+      },
+      {
+        "author_name": "Peter Daszak",
+        "author_inst": "EcoHealth Alliance, 460 West 34th Street, 17th Floor, New York, NY 10001-2320"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2020.06.19.161802",
@@ -1320184,61 +1322697,41 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.06.16.20132423",
-    "rel_title": "Seroprevalence and epidemiological characteristics of immunoglobulin M and G antibodies against SARS-CoV-2 in asymptomatic people in Wuhan, China",
+    "rel_doi": "10.1101/2020.06.16.20133207",
+    "rel_title": "Downsides of face masks and possible mitigation strategies: a systematic review and meta-analysis",
     "rel_date": "2020-06-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20132423",
-    "rel_abs": "ObjectivesPopulation screening for IgG and IgM against SARS-CoV-2 was initiated on March 25 and was open to all residents of Wuhan who were symptom-free. All ages with no fever, headache or other symptoms of COVID-19 among residents in Wuhan were included.\n\nMethodsThis study adopted a cross-sectional study. Pearson Chi-square test, T-test, and Mann-Whitney test were used in comparison between different groups. To correct the effects of gender and age, the seroprevalence of IgM positivity, IgG positivity, and IgM and/or IgG positivity were standardized according to the gender and age-specific population of Wuhan in 2017.\n\nResultsThe seroprevalence of IgG and IgM standardized for age and gender in Wuhan showed a downward trend. No significant correlation was observed between the seroprevalence of IgG and the different age groups. The seroprevalence was significantly higher for females than males (x2 =35.702, p < 0.001), with an odds ratio of 1.36 (95% CI: 1.24-1.48). A significant difference was seen in the seroprevalence of IgG among people from different geographic areas and different types of workplaces (respectively, x2 = 42.871, p < 0.001 and x2 = 202.43, p < 0.001). The IgG antibody-positive cases had a greater number of abnormalities in CT imaging than IgG-negative cases (30.7% vs 19.7%).\n\nConclusionsOur work found the reported number of confirmed patients in Wuhan only represents a small proportion of the total number of infections. There was a significant aggregation of asymptomatic infections in individuals from some occupations, and based on CT and laboratory findings, some damage may have occurred in asymptomatic individuals positive for IgG antibody.\n\nO_LSTStrengths and limitations of this studyC_LSTO_LIThis study has the important feature of having been designed as repeated five-day serosurveys, which allowed for the monitoring of seroprevalence progression.\nC_LIO_LIThis study applied scientific statistical methods accounting for the demographic structure of the general population and imperfect diagnostic tests to estimate seroprevalence in the overall population.\nC_LIO_LIThis study had selection bias since the analyzed medical records were based on examinees directed by their work units.\nC_LIO_LIPeople under the age of 19 and over age 65 were too few to be fully covered in analyses.\nC_LI",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20133207",
+    "rel_abs": "ObjectiveTo identify, appraise, and synthesise studies evaluating the downsides of wearing facemasks in any setting. We also discuss potential strategies to mitigate these downsides.\n\nMethodsPubMed, Embase, CENTRAL, EuropePMC were searched (inception-18/5/2020), and clinical registries were searched via CENTRAL. We also did forward-backward citation search of the included studies. We included randomised controlled trials and observational studies comparing facemask use to any active intervention or to control. Two author pairs independently screened articles for inclusion, extracted data and assessed the quality of included studies. The primary outcomes were compliance, discomforts, harms, and adverse events of wearing facemasks.\n\nFindingsWe screened 5471 articles, including 37 (40 references); 11 were meta-analysed. For mask wear adherence, 47% more people wore facemasks in the facemask group compared to control; adherence was significantly higher (26%) in the surgical/medical mask group than in N95/P2 group. The largest number of studies reported on the discomfort and irritation outcome (20-studies); fewest reported on the misuse of masks, and none reported on mask contamination or risk compensation behaviour. Risk of bias was generally high for blinding of participants and personnel and low for attrition and reporting biases.\n\nConclusionThere are insufficient data to quantify all of the adverse effects that might reduce the acceptability, adherence, and effectiveness of face masks. New research on facemasks should assess and report the harms and downsides. Urgent research is also needed on methods and designs to mitigate the downsides of facemask wearing, particularly the assessment of alternatives such as face shields.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Ruijie Ling",
-        "author_inst": "Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan, Hubei, China"
-      },
-      {
-        "author_name": "Yihan Yu",
-        "author_inst": "Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan, Hubei, China"
-      },
-      {
-        "author_name": "Jiayu He",
-        "author_inst": "National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China"
-      },
-      {
-        "author_name": "Jixian Zhang",
-        "author_inst": "Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan, Hubei, China"
-      },
-      {
-        "author_name": "Sha Xu",
-        "author_inst": "Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan, Hubei, China"
-      },
-      {
-        "author_name": "Renrong Sun",
-        "author_inst": "Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan, Hubei, China"
+        "author_name": "Mina Bakhit",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Wangcai Zhu",
-        "author_inst": "Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan, Hubei, China"
+        "author_name": "Natalia Krzyzaniak",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Mingfeng Chen",
-        "author_inst": "National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China"
+        "author_name": "Anna Mae Scott",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Tao Li",
-        "author_inst": "National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China"
+        "author_name": "Justin Clark",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Honglong Ji",
-        "author_inst": "Department of Cellular and Molecular Biology, University of Texas Health Science Centre at Tyler, Tyler, Texas, USA"
+        "author_name": "Paul Glasziou",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Huanqiang Wang",
-        "author_inst": "National Institute of Occupational Health and Poisons Control,Chinese CDC"
+        "author_name": "Chris Del Mar",
+        "author_inst": "Bond University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1321714,61 +1324207,45 @@
     "category": "cardiovascular medicine"
   },
   {
-    "rel_doi": "10.1101/2020.06.17.20133611",
-    "rel_title": "Knowledge, Attitudes, and Fear of COVID-19 during the Rapid Rise Period in Bangladesh",
+    "rel_doi": "10.1101/2020.06.16.20133215",
+    "rel_title": "The first proof of the capability of wastewater surveillance for COVID-19 in India through the detection of the genetic material of SARS-CoV-2",
     "rel_date": "2020-06-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.17.20133611",
-    "rel_abs": "ObjectivesTo determine the level of Knowledge, Attitude, and Practice (KAP) related to COVID-19 preventive health habits and perception of Fear towards COVID-19 in subjects living in Bangladesh.\n\nDesignProspective, cross-sectional survey of (n= 2157) male and female subjects, 13-90 years of age, living in Bangladesh.\n\nMethodsEthical Approval and Trial registration were obtained prior to the commencement of the study. Subjects who volunteered to participate and signed the informed consent were enrolled in the study and completed the \"Fear of COVID-19 Scale\" (FCS).\n\nResultsTwenty-eight percent (28.69%) of subjects reported one or more COVID-19 symptoms and 21.4% of subjects reported one or more comorbidities. Knowledge scores were slightly higher in males (8.75{+/-} 1.58) than females (8.66{+/-} 1.70). Knowledge was significantly correlated with age (p<.005), an education level (p<.001), Attitude (p<.001), and urban location (p=<.001). Knowledge scores showed an inverse correlation with Fear scores (p=<.001). Eighty-three percent (83.7%) of subjects with COVID-19 symptoms reported wearing a mask in public and 75.4% of subjects reported staying away from crowded places. Subjects with one or more symptoms reported higher Fear compared to subjects without (18.73{+/-} 4.6; 18.45{+/-} 5.1).\n\nConclusionsOverall, Bangladeshis reported a high prevalence of self-isolation, positive preventive health behaviors related to COVID-19, and moderate to high fear levels. Higher Knowledge and Practice were found in males, higher education levels, older age, and urban location. \"Fear\" of COVID-19 was more prevalent in female and elderly subjects. Positive \"Attitude\" was reported for the majority of subjects, reflecting the belief that COVID-19 was controllable and containable.\n\nEthical approvalEthical permission obtained from the Institutional review board (BPA-IPRR/IRB/29/03/2020/021) of Institute of Physiotherapy, Rehabilitation, and Research (IPRR), the academic organization of the Bangladesh Physiotherapy Association.\n\nWHO Trial registryThe trial registration obtained prospectively from a primary trial registry of WHO (CTRI/2020/04/024413).\n\nData AvailabilityThe data are available regarding this study and can be viewed upon request",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20133215",
+    "rel_abs": "we made the first ever successful effort from India to detect the genetic material of SARS-CoV-2 viruses to understand the capability and application of WBE surveillance in India. Sampling was carried out on 8 and 27 May, 2020 from Old Pirana Waste Water Treatment Plant (WWTP) at Ahmedabad, Gujarat with 106 million liters per day (MLD) capacity receiving effluent of Civil Hospital treating COVID-19 patient. All three i.e. ORF1ab, N and S genes of SARS-CoV-2 were discerned in the influents with no gene spotted in the effluent collected on 8 and 27 May 2020. Temporal difference between 8 and 27 May 2020 samples was of 10x in gene copy loading with corresponding change of 2x in the number active COVID-19 patient in the city. Number of gene copies was found comparable to that reported in the untreated wastewaters of Australia, China and Turkey and lower than that of the USA, France and Spain. This study, being the first from India and probably among the first ten reports in the world of gene detection of SARS-CoV-2 in the environmental samples, aims to assist concerned authorities and policymakers to formulate and/or upgrade the COVID-19 surveillance to have explicit picture of phase of the pandemic. While infectious SARS-CoV-2 has yet to be identified in the aquatic environment, the virus potentially enters the wastewater stream from patient excretions and thus can be a great tool for pandemic monitoring.\n\nHIGHLIGHTS{square} First ever report of the presence of gene of SARS-CoV-2 in the wastewater in India.\n{square}CT value is explicitly indicative of the increase of COVID-19 patient in the vicinity.\n{square}All three i.e. ORF1ab, N and S genes of SARS-CoV-2 were discerned in the influents.\n{square}None of three genes were spotted in the effluent collected on 8 and 27 May 2020.\n{square}Wastewater surveillance conclusively specified temporal difference in COVID-19 load.\n{square}Temporal difference was 10x and 2x in gene copies and COVID-19 patient, respectively.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Mohammad Anwar Hossain",
-        "author_inst": "Centre for the Rehabilitation of the Paralysed"
-      },
-      {
-        "author_name": "K M Amran Hossain",
-        "author_inst": "Bangladesh Health Professions Institute"
-      },
-      {
-        "author_name": "Lori Maria Walton",
-        "author_inst": "University of Scranton"
-      },
-      {
-        "author_name": "Zakir Uddin",
-        "author_inst": "McGill University"
-      },
-      {
-        "author_name": "Md. Obaidul Haque",
-        "author_inst": "Bangladesh Health Professions Institute"
+        "author_name": "Manish Kumar",
+        "author_inst": "Indian Institute of Technology Gandhinagar, India"
       },
       {
-        "author_name": "Md. Feroz Kabir",
-        "author_inst": "Jashore University of Science and Technology"
+        "author_name": "Arbind K Patel",
+        "author_inst": "Indian Institute of Technology Gandhinagar, Gujarat, India"
       },
       {
-        "author_name": "S. M. Yasir Arafat",
-        "author_inst": "Enam Medical College & Hospital"
+        "author_name": "Anil V Shah",
+        "author_inst": "Gujarat Pollution Control Board, Gandhinagar, India"
       },
       {
-        "author_name": "Mohamed Sakel",
-        "author_inst": "East Kent University NHS Hospital"
+        "author_name": "Janvi Raval",
+        "author_inst": "Gujarat Biotechnology Research Centre"
       },
       {
-        "author_name": "Rafey Faruqui",
-        "author_inst": "Kent & Medway NHS and Social care Partnership Trust"
+        "author_name": "Neha Rajpara",
+        "author_inst": "Gujarat Biotechnology Research Centre"
       },
       {
-        "author_name": "Ikbal Kabir Jahid",
-        "author_inst": "Jashore University of Science and Technology"
+        "author_name": "Madhvi Joshi",
+        "author_inst": "Gujarat Biotechnology Research Centre"
       },
       {
-        "author_name": "Zahid Hossain",
-        "author_inst": "Bangladesh Health Professions Institute"
+        "author_name": "Chaitanya G Joshi",
+        "author_inst": "Gujarat Biotechnology Research Centre, Gujarat"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1323604,23 +1326081,163 @@
     "category": "genetics"
   },
   {
-    "rel_doi": "10.1101/2020.06.16.154559",
-    "rel_title": "in-silica Analysis of SARS-CoV-2 viral strain using Reverse Vaccinology Approach: A Case Study for USA",
+    "rel_doi": "10.1101/2020.06.15.20130328",
+    "rel_title": "Can we trust the prediction model? Demonstrating the importance of external validation by investigating the COVID-19 Vulnerability (C-19) Index across an international network of observational healthcare datasets",
     "rel_date": "2020-06-17",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.16.154559",
-    "rel_abs": "The recent pandemic of COVID19 that has struck the world is yet to be battled by a potential cure. Countless lives have been claimed due to the existing pandemic and the societal normalcy has been damaged permanently. As a result, it becomes crucial for academic researchers in the field of bioinformatics to combat the existing pandemic. The study involved collecting the virulent strain sequence of SARS-nCoV19 for the country USA against human host through publically available bioinformatics databases. Using in-silica analysis and reverse vaccinology, two leader proteins were identified to be potential vaccine candidates for development of a multi-epitope drug. The results of this study can provide further researchers better aspects and direction on developing vaccine and immune responses against COVID19. This work also aims at promoting the use of existing bioinformatics tools to faster streamline the pipeline of vaccine development.\n\nThe Situation of COVID19A new infection respiratory disease was first observed in the month of December 2019, in Wuhan, situated in the Hubei province, China. Studies have indicated that the reason of this disease was the emergence of a genetically-novel coronavirus closely related to SARS-CoV. This coronavirus, now named as nCoV-19, is the reason behind the spread of this fatal respiratory disease, now named as COVID-19. The initial group of infections is supposedly linked with the Huanan seafood market, most likely due to animal contact. Eventually, human-to-human interaction occurred and resulted in the transmission of the virus to humans. [13].\n\nSince then, nCoV-19 has been rapidly spreading within China and other parts of World. At the time of writing this article (mid-March 2020), COVID-19 has spread across 146 countries. A count of 164,837 cases have been confirmed of being diagnosed with COVID-19, and a total of 6470 deaths have occurred. The cumulative cases have been depicting a rising trend and the numbers are just increasing. WHO has declared COVID-19 to be a \"global health emergency\". [14].\n\nCurrent Scenario and ObjectivesCurrently, research is being conducted on a massive level to understand the immunology and genetic characteristics of the disease. However, no cure or vaccine of nCoV-19 has been developed at the time of writing this article.\n\nThough, nCoV-19 and SARS-CoV are almost genetically similar, the respiratory syndrome caused by both of them, COVID-19 and SARS respectively, are completely different. Studies have indicated that -\n\n\"SARS was more deadly but much less infectious than COVID-19\".\n\n-World Health Organization",
-    "rel_num_authors": 1,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20130328",
+    "rel_abs": "BackgroundSARS-CoV-2 is straining healthcare systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate between patients requiring hospitalization and those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision making during the pandemic. However, the model is at high risk of bias according to the Prediction model Risk Of Bias ASsessment Tool and has not been externally validated.\n\nMethodsWe followed the OHDSI framework for external validation to assess the reliability of the C-19 model. We evaluated the model on two different target populations: i) 41,381 patients that have SARS-CoV-2 at an outpatient or emergency room visit and ii) 9,429,285 patients that have influenza or related symptoms during an outpatient or emergency room visit, to predict their risk of hospitalization with pneumonia during the following 0 to 30 days. In total we validated the model across a network of 14 databases spanning the US, Europe, Australia and Asia.\n\nFindingsThe internal validation performance of the C-19 index was a c-statistic of 0.73 and calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data the model obtained c-statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US and South Korean datasets respectively. The calibration was poor with the model under-estimating risk. When validated on 12 datasets containing influenza patients across the OHDSI network the c-statistics ranged between 0.40-0.68.\n\nInterpretationThe results show that the discriminative performance of the C-19 model is low for influenza cohorts, and even worse amongst COVID-19 patients in the US, Spain and South Korea. These results suggest that C-19 should not be used to aid decision making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.",
+    "rel_num_authors": 36,
     "rel_authors": [
       {
-        "author_name": "Ajay Agarwal",
-        "author_inst": "DIT University"
+        "author_name": "Jenna M Reps",
+        "author_inst": "Janssen R&D"
+      },
+      {
+        "author_name": "Chungsoo Kim",
+        "author_inst": "Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea"
+      },
+      {
+        "author_name": "Ross D. Williams",
+        "author_inst": "Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands"
+      },
+      {
+        "author_name": "Aniek F Markus",
+        "author_inst": "Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands"
+      },
+      {
+        "author_name": "Cynthia Yang",
+        "author_inst": "Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands"
+      },
+      {
+        "author_name": "Talita Duarte Salles",
+        "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol)"
+      },
+      {
+        "author_name": "Thomas Falconer",
+        "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY"
+      },
+      {
+        "author_name": "Jitendra Jonnagaddala",
+        "author_inst": "School of Public Health and Community Medicine, UNSW Sydney"
+      },
+      {
+        "author_name": "Andrew Williams",
+        "author_inst": "Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, 02111, USA"
+      },
+      {
+        "author_name": "Sergio Fernandez-Bertolin",
+        "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol)"
+      },
+      {
+        "author_name": "Scott L DuVall",
+        "author_inst": "Department of Veterans Affairs, USA; University of Utah, USA"
+      },
+      {
+        "author_name": "Kristin Kostka",
+        "author_inst": "Real World Solutions, IQVIA, Cambridge, MA, United States"
+      },
+      {
+        "author_name": "Gowtham Rao",
+        "author_inst": "Janssen Research & Development, Titusville, NJ, USA"
+      },
+      {
+        "author_name": "Azza Shoaibi",
+        "author_inst": "Janssen Research & Development, Titusville, NJ, USA"
+      },
+      {
+        "author_name": "Anna Ostropolets",
+        "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY"
+      },
+      {
+        "author_name": "Matthew E Spotnitz",
+        "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY"
+      },
+      {
+        "author_name": "Lin Zhang",
+        "author_inst": "School of Public Health, Peking Union Medical College, Beijing, China"
+      },
+      {
+        "author_name": "Paula Casajust",
+        "author_inst": "Department of Real-World Evidence, Trial Form Support, Barcelona, Spain"
+      },
+      {
+        "author_name": "Ewout Steyerberg",
+        "author_inst": "Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands"
+      },
+      {
+        "author_name": "Fredrik Nyberg",
+        "author_inst": "School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg Gothenburg, Sweden"
+      },
+      {
+        "author_name": "Benjamin Skov Kaas-Hansen",
+        "author_inst": "Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark"
+      },
+      {
+        "author_name": "Young Hwa Choi",
+        "author_inst": "Department of Infectious Diseases, Ajou University School of Medicine, Suwon, Republic of Korea"
+      },
+      {
+        "author_name": "Daniel Morales",
+        "author_inst": "ivision of Population Health and Genomics, University of Dundee, UK"
+      },
+      {
+        "author_name": "Siaw-Teng Liaw",
+        "author_inst": "School of Public Health and Community Medicine, UNSW Sydney"
+      },
+      {
+        "author_name": "Maria Tereza Fernandes Abrahao",
+        "author_inst": "Faculty of Medicine, University of Sao Paulo, Sao Paulo, Brazil"
+      },
+      {
+        "author_name": "Carlos Areia",
+        "author_inst": "Nuffield Department of Clinical Neurosciences, University of Oxford"
+      },
+      {
+        "author_name": "Michael E Matheny",
+        "author_inst": "Department of Veterans Affairs, USA; Vanderbilt University, USA"
+      },
+      {
+        "author_name": "Maria Aragon",
+        "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol)"
+      },
+      {
+        "author_name": "Rae Woong Park",
+        "author_inst": "Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea"
+      },
+      {
+        "author_name": "George Hripcsak",
+        "author_inst": "Department of Biomedical Informatics, Columbia University, New York, NY"
+      },
+      {
+        "author_name": "Christian G Reich",
+        "author_inst": "Real World Solutions, IQVIA, Cambridge, MA, United States"
+      },
+      {
+        "author_name": "Marc A Suchard",
+        "author_inst": "Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA"
+      },
+      {
+        "author_name": "Seng Chan You",
+        "author_inst": "Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea"
+      },
+      {
+        "author_name": "Patrick B Ryan",
+        "author_inst": "Janssen Research & Development, Titusville, NJ, USA"
+      },
+      {
+        "author_name": "Daniel Prieto-Alhambra",
+        "author_inst": "Centre for Statistics in Medicine, NDORMS, University of Oxford"
+      },
+      {
+        "author_name": "Peter R Rijnbeek",
+        "author_inst": "Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2020.06.15.20131672",
@@ -1325126,43 +1327743,59 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.06.16.151555",
-    "rel_title": "Decoding of persistent multiscale structures in complex biological networks",
+    "rel_doi": "10.1101/2020.06.17.157982",
+    "rel_title": "Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding",
     "rel_date": "2020-06-17",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.16.151555",
-    "rel_abs": "In any  omics study, the scale of analysis can dramatically affect the outcome. For instance, when clustering single-cell transcriptomes, is the analysis tuned to discover broad or specific cell types? Likewise, protein communities revealed from protein networks can vary widely in sizes depending on the method. Here we use the concept of \"persistent homology\", drawn from mathematical topology, to identify robust structures in data at all scales simultaneously. Application to mouse single-cell transcriptomes significantly expands the catalog of identified cell types, while analysis of SARS-COV-2 protein interactions suggests hijacking of WNT. The method, HiDeF, is available via Python and Cytoscape.",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.17.157982",
+    "rel_abs": "The receptor binding domain (RBD) of the SARS-CoV-2 spike glycoprotein mediates viral attachment to ACE2 receptor, and is a major determinant of host range and a dominant target of neutralizing antibodies. Here we experimentally measure how all amino-acid mutations to the RBD affect expression of folded protein and its affinity for ACE2. Most mutations are deleterious for RBD expression and ACE2 binding, and we identify constrained regions on the RBDs surface that may be desirable targets for vaccines and antibody-based therapeutics. But a substantial number of mutations are well tolerated or even enhance ACE2 binding, including at ACE2 interface residues that vary across SARS-related coronaviruses. However, we find no evidence that these ACE2-affinity enhancing mutations have been selected in current SARS-CoV-2 pandemic isolates. We present an interactive visualization and open analysis pipeline to facilitate use of our dataset for vaccine design and functional annotation of mutations observed during viral surveillance.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Fan Zheng",
-        "author_inst": "University of California, San Diego"
+        "author_name": "Tyler N Starr",
+        "author_inst": "Fred Hutch Cancer Research Center"
       },
       {
-        "author_name": "She Zhang",
-        "author_inst": "University of Pittsburgh"
+        "author_name": "Allison J Greaney",
+        "author_inst": "Fred Hutch Cancer Research Center"
       },
       {
-        "author_name": "Christopher Churas",
-        "author_inst": "University of California, San Diego"
+        "author_name": "Sarah K Hilton",
+        "author_inst": "Fred Hutch Cancer Research Center"
       },
       {
-        "author_name": "Dexter Pratt",
-        "author_inst": "University of California, San Diego"
+        "author_name": "Katharine HD Crawford",
+        "author_inst": "Fred Hutch Cancer Research Center"
       },
       {
-        "author_name": "Ivet Bahar",
-        "author_inst": "University of Pittsburgh"
+        "author_name": "Mary Jane Navarro",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Trey Ideker",
-        "author_inst": "University of California, San Diego"
+        "author_name": "John E Bowen",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "M Alejandra Tortorici",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "Alexandra C Walls",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "David Veesler",
+        "author_inst": "University of Washington"
+      },
+      {
+        "author_name": "Jesse D Bloom",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "new results",
-    "category": "systems biology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.06.16.155887",
@@ -1326924,27 +1329557,31 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.06.13.20130062",
-    "rel_title": "Guillain Barr e syndrome in COVID-19:A scoping review",
+    "rel_doi": "10.1101/2020.06.13.20130310",
+    "rel_title": "COVID-19: a crash test for biomedical publishing?",
     "rel_date": "2020-06-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130062",
-    "rel_abs": "IntroductionThe novel corona virus (COVID19) can result in several neurological complications. Guillain-Barre Syndrome (GBS) is one of them and has been reported from different parts of the world in this pandemic. It is an acute post infectious polyneuropathy. The review aims to summarize the demographic features, clinical presentation, diagnostics workup, and management strategies of COVID-19 associated GBS reported in literature.\n\nMaterial and methodWe searched Medline, PubMed Central, SCOPUS and Google Scholar using pre-defined keywords, with no time limits and in English language only. We aimed to include all kind of manuscripts. Last search was done on 18th May 2020.\n\nDemographics, clinical features, diagnostic workup, management, and outcomes were documented in the data sheet.\n\nResultsWe identified 24 cases of COVID-19 associated GBS. Most of the cases were reported from Italy followed by USA. Majority were males (18 /24) The age ranged from 23 -84 years. The clinical presentation was typical sensory-motor GBS in most. Nine patients had facial palsy of which five had bilateral involvement. Two patients had bilateral abducent nerve palsy while two presented as paraparetic GBS variant with autonomic dysfunction. Electrodiagnostics was performed in 17 patients only and 12 had typical features of acute inflammatory demyelinating polyneuropathy.. Intravenous immunoglobulins were the preferred mode of treatment in most of the patient. There was one death, and most were discharged to rehabilitation or home.\n\nConclusionGBS is a frequent neurological complication associated with COVID-19. There is no clear causative relationship between GBS, and COVID-19 at present and more data are needed to establish the casualty. However, most cases have a post-infectious onset with male preponderance. Most of the cases have a typical presentation but some may present in an atypical way. Prognosis is generally good.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130310",
+    "rel_abs": "The effect of COVID-19 on biomedical publishing (BP) (i.e. scientific biomedical periodicals continuously published by research communities or commercial publishers) has not been deeply explored. To estimate the immediate COVID-19 impact on BP, we have assessed PubMed-indexed articles about COVID-19 (PMIAC) from December 2019 to April 2020. PMIAC have been classified according to publication date, country, and journals for evaluation of time-, region- and scientometric-dependant impact of COVID-19 on BP and have been curated manually (i.e. each entry has been individually analyzed). PMIAC analysis reflects geographic and temporal parameters of outbreak spread. A major BP problem is related to the fact that only 40% of articles report/review/analyze data. Another BP weakness is the clusterization of \"highly-trusted\" publications according to countries of origin and \"highly impacting\" journals. Finally, a problem highlighted by COVID-19 crisis is the increased specification of biomedical research. To solve the problem, analytical reviews integrating data from different areas of biology and medicine are required. The data on PMIAC suggest priority of \"what is published\" over \"where it is published\" and \"who are the authors\". We believe that our brief analysis may help to shape forthcoming BP to become more effective in solving immediate problems resulted from global threats.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Imran Ahmad",
-        "author_inst": "Bahria University Medical and Dental College"
+        "author_name": "Ivan Y Iourov",
+        "author_inst": "Mental Health Research Center"
+      },
+      {
+        "author_name": "Maria A Zelenova",
+        "author_inst": "Mental Health Research Center"
       },
       {
-        "author_name": "Farooq Azam Rathore",
-        "author_inst": "Bahria University Medical and Dental College"
+        "author_name": "Svetlana G Vorsanova",
+        "author_inst": "Veltischev Research and Clinical Institute for Pediatrics of the Pirogov Russian National Research Medical University"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "neurology"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2020.06.13.20130252",
@@ -1328026,29 +1330663,129 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.13.20130617",
-    "rel_title": "Is tracking and modeling Covid-19 infection dynamics for Bangladesh using daily data feasible?",
+    "rel_doi": "10.1101/2020.06.13.20130088",
+    "rel_title": "Compassionate Use of Tocilizumab in Severe SARS-CoV2 Pneumonia. When late administration is too late.",
     "rel_date": "2020-06-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130617",
-    "rel_abs": "Given the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladeshs case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130088",
+    "rel_abs": "IntroductionTocilizumab is an interleukin 6 receptor antagonist which has been used for the treatment of severe SARS-CoV-2 pneumonia (SSP), aiming to ameliorate the cytokine release syndrome (CRS) -induced acute respiratory distress syndrome (ARDS). However, there is no data about the best moment for its administration along the course of the disease.\n\nMethodsWe provided tocilizumab on a compassionate-use basis to patients with SSP hospitalized (excluding intensive care and intubated cases) who required oxygen support to have a saturation >93%. Primary endpoint was intubation or death after 24 hours of its administration. Patients received at least one dose of 400 mg intravenous tocilizumab during March 8-2020, through April 20-2020.\n\nFindingsA total of 207 patients were studied and 186 analysed. The mean age was 65 years and 68% were male. A co-existing condition was present in 68 % of cases. At baseline, 114 (61%) required oxygen support with FiO2 >0.5 % and 72 (39%) [&le;]0.5%. Early administration of tocilizumab, when the need of oxygen support was still below FiO2 [&le;]0.5%, was significantly more effective than given it in advanced stages (FiO2 >0.5 %), achieving lower rates of intubation or death (13% vs 37% repectively, p<0{middle dot}001).\n\nInterpretationThe benefit of tocilizumab in severe SARS-Cov-2 pneumonia is only expected when it is administrated before the need of high oxygen support.\n\nFundingNone.",
+    "rel_num_authors": 28,
     "rel_authors": [
       {
-        "author_name": "Karar Zunaid Ahsan",
-        "author_inst": "Gillings School of Global Public Health, the University of North Carolina at Chapel Hill, NC, USA"
+        "author_name": "Miguel Gorgolas",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Alfonso Cabello",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Laura Prieto Perez",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
       },
       {
-        "author_name": "Rashida Ijdi",
-        "author_inst": "Carolina Population Center, University of North Carolina at Chapel Hill, NC, USA"
+        "author_name": "Felipe Villar Alvarez",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Beatriz Alvarez Alvarez",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
       },
       {
-        "author_name": "Peter Kim Streatfield",
-        "author_inst": "Health Systems and Population Studies Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Mohakhali, Dhaka, Bangladesh"
+        "author_name": "Maria Jesus Rodriguez Nieto",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Irene Carrillo Acosta",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Itziar Fernandez Ormaechea",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Aws Al-Hayani",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Pilar Carballosa",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Silvia Calpena Martinez",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Farah Ezzine de Blas",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Marina Castellanos Gonzalez",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Alba Naya Prieto",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Marta Lopez de las Heras",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Marcel Jose Rodriguez Guzman",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Ana Cordero Guijarro",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Antonio Broncano Lavado",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Alicia Macias Valcayo",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Marta Martin Garcia",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Javier Becares Martinez",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Ricardo Fernandez Roblas",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Miguel A Piris Pinilla",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Jose Fortes Alen",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Olga Sanchez Pernaute",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Fredeswinda Romero Bueno",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "Sarah Heili Frades",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
+      },
+      {
+        "author_name": "German Peces Barba Romero",
+        "author_inst": "Hospital Universitario Fundacion Jimenez Diaz - Universidad Autonoma de Madrid"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1329724,43 +1332461,79 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.15.153692",
-    "rel_title": "Bio-JOIE: Joint Representation Learning of Biological Knowledge Bases",
+    "rel_doi": "10.1101/2020.06.16.153403",
+    "rel_title": "Oral drug repositioning candidates and synergistic remdesivir combinations for the prophylaxis and treatment of COVID-19",
     "rel_date": "2020-06-16",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.15.153692",
-    "rel_abs": "The widespread of Coronavirus has led to a worldwide pandemic with a high mortality rate. Currently, the knowledge accumulated from different studies about this virus is very limited. Leveraging a wide-range of biological knowledge, such as gene on-tology and protein-protein interaction (PPI) networks from other closely related species presents a vital approach to infer the molecular impact of a new species. In this paper, we propose the transferred multi-relational embedding model Bio-JOIE to capture the knowledge of gene ontology and PPI networks, which demonstrates superb capability in modeling the SARS-CoV-2-human protein interactions. Bio-JOIE jointly trains two model components. The knowledge model encodes the relational facts from the protein and GO domains into separated embedding spaces, using a hierarchy-aware encoding technique employed for the GO terms. On top of that, the transfer model learns a non-linear transformation to transfer the knowledge of PPIs and gene ontology annotations across their embedding spaces. By leveraging only structured knowledge, Bio-JOIE significantly outperforms existing state-of-the-art methods in PPI type prediction on multiple species. Furthermore, we also demonstrate the potential of leveraging the learned representations on clustering proteins with enzymatic function into enzyme commission families. Finally, we show that Bio-JOIE can accurately identify PPIs between the SARS-CoV-2 proteins and human proteins, providing valuable insights for advancing research on this new disease.",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.16.153403",
+    "rel_abs": "The ongoing pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates strategies to identify prophylactic and therapeutic drug candidates for rapid clinical deployment. A high-throughput, high-content imaging assay of human HeLa cells expressing the SARS-CoV-2 receptor ACE2 was used to screen ReFRAME, a best-in-class drug repurposing library. From nearly 12,000 compounds, we identified 66 compounds capable of selectively inhibiting SARS-CoV-2 replication in human cells. Twenty-four of these drugs show additive activity in combination with the RNA-dependent RNA polymerase inhibitor remdesivir and may afford increased in vivo efficacy. We also identified synergistic interaction of the nucleoside analog riboprine and a folate antagonist 10-deazaaminopterin with remdesivir. Overall, seven clinically approved drugs (halofantrine, amiodarone, nelfinavir, simeprevir, manidipine, ozanimod, osimertinib) and 19 compounds in other stages of development may have the potential to be repurposed as SARS-CoV-2 oral therapeutics based on their potency, pharmacokinetic and human safety profiles.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Junheng Hao",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Malina A. Bakowski",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
       },
       {
-        "author_name": "Chelsea Jui-Ting Ju",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Nathan Beutler",
+        "author_inst": "The Scripps Research Institute"
       },
       {
-        "author_name": "Muhao Chen",
-        "author_inst": "University of Pennsylvania"
+        "author_name": "Emily Chen",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
       },
       {
-        "author_name": "Yizhou Sun",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Tu-Trinh H. Nguyen",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
       },
       {
-        "author_name": "Carlo Zaniolo",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Melanie G. Kirkpatrick",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
       },
       {
-        "author_name": "Wei Wang",
-        "author_inst": "University of California, Los Angeles"
+        "author_name": "Mara Parren",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "Linlin Yang",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "James Ricketts",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "Anil K. Gupta",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
+      },
+      {
+        "author_name": "Mitchell V. Hull",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
+      },
+      {
+        "author_name": "Peter G. Schultz",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
+      },
+      {
+        "author_name": "Dennis R. Burton",
+        "author_inst": "The Scripps Research Institute"
+      },
+      {
+        "author_name": "Arnab K. Chatterjee",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
+      },
+      {
+        "author_name": "Case W. McNamara",
+        "author_inst": "Calibr, a division of The Scripps Research Institute"
+      },
+      {
+        "author_name": "Thomas F. Rogers",
+        "author_inst": "Scripps Research"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.06.15.153064",
@@ -1331530,85 +1334303,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.11.20128330",
-    "rel_title": "Genome sequencing of the first SARS-CoV-2 reported from patients with COVID-19 in Ecuador.",
+    "rel_doi": "10.1101/2020.06.12.20129098",
+    "rel_title": "Laboratory Testing Implications of Risk-Stratification and Management for Improving Clinical Outcomes of COVID-19 Patients",
     "rel_date": "2020-06-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128330",
-    "rel_abs": "SARS-CoV-2, the etiological agent of COVID-19 was first described in Wuhan in December 2019 and has now spread globally. Ecuador was the second country in South America to report confirmed cases. The first case reported in Quito, the capital city of Ecuador, was a tourist who came from the Netherlands and presented symptoms on March 10th, 2020 (index case). In this work we used the MinION platform (Oxford Nanopore Technologies) to sequence the metagenome of the bronchoalveolar lavage (BAL) from this case reported, and subsequently we sequenced the whole genome of the index case and other three patients using the ARTIC network protocols. Our data from the metagenomic approach confirmed the presence of SARS-CoV-2 coexisting with pathogenic bacteria suggesting coinfection. Relevant bacteria found in the BAL metagenome were Streptococcus pneumoniae, Mycobacterium tuberculosis, Staphylococcus aureus and Chlamydia spp. Lineage assignment of the four whole genomes revealed three different origins. The variant HEE-01 was imported from the Netherlands and was assigned to B lineage, HGSQ-USFQ-018, belongs to the B.1 lineage showing nine nucleotide differences with the reference strain and grouped with sequences from the United Kingdom, and HGSQ-USFQ-007 and HGSQ-USFQ-010 belong to the B lineage and grouped with sequences from Scotland. All genomes show mutations in their genomes compared to the reference strain, which could be important to understand the virulence, severity and transmissibility of the virus. Our findings also suggest that there were at least three independent introductions of SARS-CoV-2 to Ecuador.\n\nIMPORTANCECOVID-19, an infectious disease caused by SARS-CoV-2, has spread globally including Latin American countries including Ecuador. The first strain of SARS-CoV-2 sequenced was from Wuhan, which is considered as the reference strain. There were no data about the SARS-CoV-2 lineages in Ecuador, and the purpose of this study was to find out the origin of the different lineages circulating in the population. We also were interested in the mutations present in these genomes as they can influence virulence, transmission and infectivity.",
-    "rel_num_authors": 17,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129098",
+    "rel_abs": "The high mortality rate of COVID-19 patients is mainly caused by the progression from mild to critical illness. To identify the key laboratory indicators and stratify high-risk COVID-19 patients with progression to severe/critical illness, we compared 474 moderate patients and 74 severe/critical patients. The laboratory indicators, including lactate dehydrogenase (LDH), monocytes percentage, etc. were significantly higher in the severe/critical patients (P <0.001) and showed a noticeable change at about a week before the diagnosis. Based on these indicators, we constructed a risk-stratification model, which can accurately grade the severity of patients with COVID-19 (accuracy = 0.96, 95% CI: 0.94 - 0.989, sensitivity = 0.98, specificity = 0.84). Also, compared with non-COVID-19 viral pneumonia, we found that COVID-19 had weaker dysfunction to the heart, liver, and kidney. The prognostic model based on laboratory indicators could help to diagnose, monitor, and predict severity at an early stage to those patients with COVID-19.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Sully Marquez",
-        "author_inst": "Universidad San Francisco de Quito, COCIBA, Instituto de Microbiologia"
-      },
-      {
-        "author_name": "Belen Prado-Vivar",
-        "author_inst": "Universidad San Francisco de Quito, COCIBA, Instituto de Microbiologia"
-      },
-      {
-        "author_name": "Juan Jose Guadalupe",
-        "author_inst": "Universidad San Francisco de Quito, COCIBA, Laboratorio de Biotecnologia Vegetal"
+        "author_name": "Caidong Liu",
+        "author_inst": "Department of laboratory medicine, Nanjing First Hospital, Nanjing Medical University"
       },
       {
-        "author_name": "Bernardo Gutierrez Granja",
-        "author_inst": "Department of Zoology, University of Oxford"
+        "author_name": "Ziyu Wang",
+        "author_inst": "Department of Bioinformatics, Nanjing Medical University"
       },
       {
-        "author_name": "Manuel Jibaja",
-        "author_inst": "Hospital Eugenio Espejo, Quito"
+        "author_name": "Jie Li",
+        "author_inst": "Department of Bioinformatics, Nanjing Medical University"
       },
       {
-        "author_name": "Milton Tobar",
-        "author_inst": "Hospital Eugenio Espejo, Quito"
+        "author_name": "Changgang Xiang",
+        "author_inst": "Department of laboratory medicine, First People's Hospital of Jiangxia District of Wuhan"
       },
       {
-        "author_name": "Francisco Mora",
-        "author_inst": "Hospital General Sur de Quito, IESS"
+        "author_name": "Lingxiang Wu",
+        "author_inst": "Department of Bioinformatics, Nanjing Medical University"
       },
       {
-        "author_name": "Juan Gaviria",
-        "author_inst": "Hospital General Sur de Quito, IESS"
+        "author_name": "Wei Wu",
+        "author_inst": "Department of Bioinformatics, Nanjing Medical University"
       },
       {
-        "author_name": "Maria Garcia",
-        "author_inst": "Hospital General Sur de Quito, IESS"
+        "author_name": "Weiye Hou",
+        "author_inst": "Department of laboratory medicine, Nanjing First Hospital, Nanjing Medical University"
       },
       {
-        "author_name": "Edison Ligna",
-        "author_inst": "Hospital General Sur de Quito, IESS"
+        "author_name": "Huiling Sun",
+        "author_inst": "General clinical research center, Nanjing First Hospital, Nanjing Medical University"
       },
       {
-        "author_name": "Franklin Espinosa",
-        "author_inst": "Hospital General Sur de Quito, IESS"
+        "author_name": "Youli Wang",
+        "author_inst": "Department of laboratory medicine, Nanjing First Hospital, Nanjing Medical University"
       },
       {
-        "author_name": "Jorge Reyes",
-        "author_inst": "Hospital General Sur de Quito, IESS"
+        "author_name": "Zhenling Nie",
+        "author_inst": "Department of laboratory medicine, Nanjing First Hospital, Nanjing Medical University"
       },
       {
-        "author_name": "Veronica Barragan",
-        "author_inst": "Universidad San Francisco de Quito, COCIBA, Instituto de Microbiologia"
+        "author_name": "Yingdong Gao",
+        "author_inst": "Department of laboratory medicine, Nanjing First Hospital, Nanjing Medical University"
       },
       {
-        "author_name": "Patricio Rojas-Silva",
-        "author_inst": "Universidad San Francisco de Quito, COCIBA, Instituto de Microbiologia"
+        "author_name": "Ruisheng Zhang",
+        "author_inst": "Department of laboratory medicine, Nanjing First Hospital, Nanjing Medical University"
       },
       {
-        "author_name": "Gabriel Trueba",
-        "author_inst": "Universidad San Francisco de Quito, COCIBA, Instituto de Microbiologia"
+        "author_name": "Xinyi Xia",
+        "author_inst": "COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine"
       },
       {
-        "author_name": "Michelle Grunauer",
-        "author_inst": "Universidad San Francisco de Quito, Escuela de Medicina, COCSA"
+        "author_name": "qianghu wang",
+        "author_inst": "Nanjing medical university"
       },
       {
-        "author_name": "Paul Cardenas",
-        "author_inst": "Universidad San Francisco de Quito, COCIBA, Instituto de Microbiologia"
+        "author_name": "Shukui Wang",
+        "author_inst": "Department of laboratory medicine, Nanjing First Hospital, Nanjing Medical University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1333048,47 +1335813,23 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.11.20127241",
-    "rel_title": "Critical Questions when Interpreting Coronavirus PCR Diagnostics",
+    "rel_doi": "10.1101/2020.06.11.20128991",
+    "rel_title": "Transformed time series analysis of first-wave COVID-19: universal similarities found in the Group of Twenty (G20) Countries",
     "rel_date": "2020-06-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20127241",
-    "rel_abs": "The results of PCR measurements are regarded as unquestionable. This statement must be put into perspective. This relativization is particularly important in connection with the interpretation of SARS-CoV-2 results. Members of the critical infrastructure, such as nurses, may be quarantined although this is not necessary and are therefore missing from patient care. With our small but impressive comparison of methods and transport media for SARS-CoV-2, we not only show the different sensitivity of common routine systems and media in laboratory medicine. Further, we would like to inform clinically working physicians, who are not familiar with the technical weaknesses of the PCR investigation, about gaps and present solutions for their daily work.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128991",
+    "rel_abs": "As of April 30, 2020, the number of cumulative confirmed coronavirus disease 2019 (COVID-19) cases exceeded 3 million worldwide and 1 million in the US with an estimated fatality rate of more than 7 percent. Because the patterns of the occurrence of new confirmed cases and deaths over time are complex and seemingly country-specific, estimating the long-term pandemic spread is challenging. I developed a simple transformation algorithm to investigate the characteristics of the case and death time series per nation, and described the universal similarities observed in the transformed time series of 19 nations in the Group of Twenty (G20). To investigate the universal similarities among the cumulative profiles of confirmed cases and deaths of 19 individual nations in the G20, a transformation algorithm of the time series data sets was developed with open-source software programs. The algorithm was used to extract and analyze statistical information from daily updated COVID-19 pandemic data sets from the European Centre for Disease Prevention and Control (ECDC). Two new parameters for each nation were suggested as factors for time-shifting and time-scaling to define reduced time, which was used to quantify the degree of universal similarities among nations. After the cumulative confirmed case and death profiles of a nation were transformed by using reduced time, most of the 19 nations, with few exceptions, had transformed profiles that closely converged to those of Italy after the onset of cases and deaths. The initial profiles of the cumulative confirmed cases per nation universally showed 3-4 week latency periods, during which the total number of cases remained at approximately ten. The latency period of the cumulative number of deaths was approximately half the latency number of cumulative cases, and subsequent uncontrollable increases in human deaths seemed unavoidable because the coronavirus had already widely spread. Immediate governmental actions, including responsive public-health policy-making and enforcement, are observed to be critical to minimize (and possibly stop) further infections and subsequent deaths. In the pandemic spread of infectious viral diseases, such as COVID-19 studied in this work, different nations show dissimilar and seemingly uncorrelated time series profiles of infected cases and deaths. After these statistical phenomena were viewed as identical events occurring at a distinct rate in each country, the reported algorithm of the data transformation using the reduced time revealed a nation-independent, universal profile (especially initial periods of the pandemic spread) from which a nation-specific, predictive estimation could be made and used to assist in immediate public-health policy-making.\n\nO_TEXTBOXResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe open data set were obtained from the website of the European Center for Disease Control and Prevention (ECDC). Although the data include the number of new cases and deaths per day per nation, extracting any apparent correlations between unique time-series of nations in different continents is challenging. Nevertheless, cumulative and non-cumulative statistics are, in principle, equivalent, and hence one can be obtained from the other. Because the non-cumulative profiles report instantaneous variations in the pandemic time series, estimation of future trends by extrapolating recent data is often intractable and limited to short-term extrapolations.\n\nAdded value of this studyA data transformation method for the cumulative confirmed cases (CCC) and cumulative confirmed deaths (CCD) was developed and used to directly compare the pandemic statuses of multiple nations, especially G20 nations. This model requires data for the nation with the greatest CCC and CCD (especially, during the initial burst of 90-120 days), which, in the case of the COVID-19 pandemic spread, is Italy. Two parameters for time-shifting (m) and time-scaling ({beta}) are newly introduced and used to define the reduced time{tau} . After the transformation, most nations cumulative profiles converge with those of Italy regardless of their geographical locations.\n\nImplications of all the available evidenceThe discovery of the universality of the transformed CCC and CCD profiles of multiple countries provides new insight into analyzing pandemic time series, including the current COVID-19 pandemic spread. By shifting and scaling a nations pandemic data into the reduced time frame, the nations CCC and CCD profiles can be predicted as long as the reference countrys cumulative data are available in the linear time domain. After the extraction of meaningful information from the transformed data, the overall implication is that most nations will reach the same state as Italys current state soon, depending on a specific nations population and human dynamics.\n\nC_TEXTBOX",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Juergen Durner",
-        "author_inst": "Department of Operative/Restorative Dentistry, Periodontology and Pedodontics, Ludwig- Maximilians-"
-      },
-      {
-        "author_name": "Siegfried Burggraf",
-        "author_inst": "Laboratory Becker & Colleagues"
-      },
-      {
-        "author_name": "Ludwig Czibere",
-        "author_inst": "Laboratory Becker & Colleagues"
-      },
-      {
-        "author_name": "Tobias Fleige",
-        "author_inst": "Laboratory Becker & Colleagues"
-      },
-      {
-        "author_name": "Michael Spannagl",
-        "author_inst": "Haemophilia Treatment Centre, Ludwig-Maximilians-University of Munich"
-      },
-      {
-        "author_name": "David Watts",
-        "author_inst": "School of Medical Sciences and Photon Science Institute, University of Manchester, UK"
-      },
-      {
-        "author_name": "Marc Becker",
-        "author_inst": "Laboratory Becker & Colleagues"
+        "author_name": "Albert S Kim",
+        "author_inst": "University of Hawaii at Manoa"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2020.06.11.20128793",
@@ -1334418,75 +1337159,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.11.20107086",
-    "rel_title": "COVID-19: Comparison between 8-days and extended 4-weeks outbreak periods through socioeconomic and natural factors",
+    "rel_doi": "10.1101/2020.06.09.20120139",
+    "rel_title": "Prevalence and Predictors of General Psychiatric Disorders and Loneliness during COVID-19 in the United Kingdom: Results from the Understanding Society UKHLS",
     "rel_date": "2020-06-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20107086",
-    "rel_abs": "Since mid-March 2020, global COVID-19 pandemic has experienced an exponential growth in process from sporadic to sudden outbreaks. This paper selects the 8-day surge data of daily cases, death and recovery rates (March 19-26, 2020) from 18 countries with severe pandemic situation to discuss the impact of 9 factors of both socioeconomic and natural on the pathogen outbreak. Moreover, the paper also elaborates analysis and comparison of relatively slow 4-week (February 1-29, 2020) data of Chinas surge cases to determine the relationship between social and natural factors and on the spread of pandemic, which provides an effective reference for delaying and controlling the pandemic development.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20120139",
+    "rel_abs": "Despite ample research on the prevalence of specific psychiatric disorders during COVID-19, we know little about how the pandemic affects the general wellbeing of a wider population. The study investigates the prevalence and predictors of general psychiatric disorders measured by the 12-item General Health Questionnaire (GHQ-12) and frequency of loneliness during COVID-19 in the United Kingdom, a country heavily hit by the pandemic. We analyzed 15,530 respondents of the first large-scale, nationally representative survey of COVID-19 in a developed country, the first wave of Understanding Society COVID-19 Study. Results show that 29.2% of the respondents score 4 or more, the caseness threshold, on the general psychiatric disorder measure, and 35.86% of the respondents sometimes or often feel lonely. Regression analyses show that those who have or had COVID-19-related symptoms are more likely to develop general psychiatric disorders and are lonelier. Women and people in their 20s have higher risks of general psychiatric disorders and loneliness, while having a job and living with a partner are protective factors. This study showcases the general psychiatric disorders and loneliness of broader members of the society during COVID-19 and the underlying social disparities.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Sana Ullah",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
-      },
-      {
-        "author_name": "Jianghua ZHENG",
-        "author_inst": "College of Resources and Environment Science, Xinjiang University, Urumqi, 830046, China"
-      },
-      {
-        "author_name": "Zhengkang ZUO",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
-      },
-      {
-        "author_name": "Feizhou ZHANG",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
-      },
-      {
-        "author_name": "Ke SHANG",
-        "author_inst": "School of Geophysics and Information Technology, China University of Geosciences, Beijing, 100083, China."
-      },
-      {
-        "author_name": "Wenjie YU",
-        "author_inst": "College of Resources and Environment Science, Xinjiang University, Urumqi, 830046, China."
-      },
-      {
-        "author_name": "Yu FU",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
-      },
-      {
-        "author_name": "Chuqiao HAN",
-        "author_inst": "College of Resources and Environment Science, Xinjiang University, Urumqi, 830046, China."
-      },
-      {
-        "author_name": "Yi LIN",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
-      },
-      {
-        "author_name": "Kaiwen JIANG",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
-      },
-      {
-        "author_name": "Shanlin SUN",
-        "author_inst": "College of Electronic Information and Automation, Guilin University of Aerospace Technology, Guilin 541004, Guangxi Province China."
-      },
-      {
-        "author_name": "Yiyuan SUN",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
-      },
-      {
-        "author_name": "Shoujiang ZHAO",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
+        "author_name": "Lambert Zixin Li",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Lei YAN",
-        "author_inst": "School of Earth and Space Science, Peking University, Beijing, 100871, China."
+        "author_name": "Senhu Wang",
+        "author_inst": "University of Cambridge"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.06.10.20084715",
@@ -1335816,59 +1338509,59 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.06.09.20126086",
-    "rel_title": "Private Health Sector in India: Ready and willing, yet underutilized in the Covid-19 pandemic.",
+    "rel_doi": "10.1101/2020.06.10.20127266",
+    "rel_title": "Resource requirements for reintroducing elective surgery in England during the COVID-19 pandemic: a modelling study",
     "rel_date": "2020-06-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20126086",
-    "rel_abs": "BackgroundThe private medical sector is a resource that must be estimated for efficient inclusion into public healthcare during pandemics.\n\nMethodsA survey was conducted among private healthcare workers to ascertain their views on the potential resources that can be accessed from the private sector and methods to do the same.\n\nResultsThere were 213 respondents, 80% of them being doctors. Nearly half (47.4%) felt that the contribution from the private medical sector has been suboptimal. Areas suggested for improved contributions by the private sector related to patient care (71.8%) and provision of equipment (62.4%), with fewer expectations (39.9%) on the research front. Another area of deemed support was maintaining continuity of care for non-COVID patients using virtual consultation services (77.4%), tele-consultation being the preferred option (60%). 58.2% felt that the Government had not involved the private sector adequately; and 45.1% felt they should be part of policy-making.\n\nConclusionA streamlined pathway to facilitate the private sector to join hands with the public sector for a national cause is the need of the hour. Through our study, we have identified gaps in the current contribution by the private sector and identified areas in which they could contribute, by their own admission.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127266",
+    "rel_abs": "BackgroundThe response to COVID-19 has required cancellation of all but the most urgent surgeries, including many cancer operations. We estimated the number of cancelled surgical procedures in the National Health Service (NHS) in England due to COVID-19 and how this deficit would change over time once elective surgery was reintroduced.\n\nMethodsModelling study using Hospital Episode Statistics (HES) data from 2014 to 2019. Using NHS England definitions, surgical procedures were grouped into four classes of urgency. We calculated time-weighted average numbers of surgical procedures from 1st March 2020 and extrapolated to 28th February 2021 informed by activity in previous years. We estimated the procedure deficit using multiple conservative assumptions and then modelled the reintroduction of elective surgery between 1st June 2020 and 28th February 2021, estimating the resources required to achieve this. Costs of surgery were calculated using NHS reference costs. Estimates are reported with 95% confidence intervals.\n\nFindings4,547,534 (3,318,195 - 6,250,771) patients with pooled mean age of 53.5 years were expected to undergo surgery in the NHS in England between 1st March 2020 and 28th February 2021. Due to COVID-19, 749,248 (513,565 - 1,077,448) surgical procedures were cancelled by 31st May 2020. As current guidelines require a gradual reintroduction of elective surgery, this deficit will increase further and 2,270,178 (1,453,057 - 3,363,472) patients will be awaiting surgery by 28th February 2021. The cost of these delayed procedures is {pound}4,688,318,443 ({pound}2,726,364,240 - {pound}7,070,166,056). However, the safe delivery of surgery during the pandemic will require substantial extra resources including personal protective equipment and universal preoperative screening, leading to additional costs of {pound}606,252,901 ({pound}521,159,931 - {pound}730,720,808).\n\nInterpretationReintroduction of elective surgery during the pandemic response in NHS England will be associated with substantial treatment delays for many patients, and a large increase in treatment costs.\n\nFundingNIHR (DRF-2018-11-ST2-062) to AJF.",
     "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Samira Davalbhakta",
-        "author_inst": "Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals"
+        "author_name": "Alexander J Fowler",
+        "author_inst": "William Harvey Research Institute, Queen Mary, University of London, UK"
       },
       {
-        "author_name": "Supriya Sharma",
-        "author_inst": "Department of Surgical Gastroenterology Sanjay Gandhi Postgraduate Institute of Medical Sciences Lucknow, India"
+        "author_name": "Tom D Dobbs",
+        "author_inst": "Reconstructive Surgery & Regenerative Medicine Research Group, Institute of Life Sciences, Swansea University Medical School, Swansea, UK"
       },
       {
-        "author_name": "Shefali Gupta",
-        "author_inst": "Department of Microbiology Maharishi Markandeshwar Institute of Medical Sciences and Research (MMIMSR) Haryana, India"
+        "author_name": "Yize I Wan",
+        "author_inst": "William Harvey Research Institute, Queen Mary University of London, UK."
       },
       {
-        "author_name": "Vishwesh Agarwal",
-        "author_inst": "Mahatma Gandhi Missions Medical College"
+        "author_name": "Ryan Laloo",
+        "author_inst": "Leeds Vascular Institute, Leeds General Infirmary, UK"
       },
       {
-        "author_name": "Gaurav Pandey",
-        "author_inst": "Sanjay Gandhi Postgraduate Institute of Medical Sciences Lucknow, India"
+        "author_name": "Sarah Hui",
+        "author_inst": "William Harvey Research Institute, Queen Mary University of London, UK"
       },
       {
-        "author_name": "Durga Prasanna Misra",
-        "author_inst": "Sanjay Gandhi Postgraduate Institute of Medical Sciences Lucknow, India"
+        "author_name": "Dmitri Nepogodiev",
+        "author_inst": "Academic Department of Surgery, University of Birmingham, UK"
       },
       {
-        "author_name": "Bijaya Nanda Naik",
-        "author_inst": "Dept of Community Medicine NAMO Medical Education and Research Institute, Silvassa, DNH"
+        "author_name": "Aneel Bhangu",
+        "author_inst": "Academic Department of Surgery, University of Birmingham, UK"
       },
       {
-        "author_name": "Ashish Goel",
-        "author_inst": "University College Of Medical Sciences, New Delhi"
+        "author_name": "Iain Whitaker",
+        "author_inst": "Reconstructive Surgery & Regenerative Medicine Research Group, Institute of Life Sciences, Swansea University Medical School, Swansea, UK"
       },
       {
-        "author_name": "Latika Gupta",
-        "author_inst": "Sanjay Gandhi Postgraduate Institute of Medical Sciences Lucknow, India"
+        "author_name": "Rupert M Pearse",
+        "author_inst": "William Harvey Research Institute, Queen Mary University of London, UK."
       },
       {
-        "author_name": "Vikas Agarwal",
-        "author_inst": "Sanjay Gandhi Postgraduate Institute of Medical Sciences Lucknow, India"
+        "author_name": "Tom EF Abbott",
+        "author_inst": "William Harvey Research Institute, Queen Mary University of London, UK"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "surgery"
   },
   {
     "rel_doi": "10.1101/2020.06.10.20127290",
@@ -1337342,69 +1340035,41 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.11.20127894",
-    "rel_title": "A scenario modeling pipeline for COVID-19 emergency planning",
+    "rel_doi": "10.1101/2020.06.10.20127589",
+    "rel_title": "Effect of social distancing on COVID-19 incidence and mortality in the US",
     "rel_date": "2020-06-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20127894",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, we developed a flexible scenario modeling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations. Here, we present the components and configurable features of the COVID Scenario Pipeline, with a vignette detailing its current use. We also present model limitations and active areas of development to meet ever-changing decision maker needs.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127589",
+    "rel_abs": "Social distancing policies were implemented in most US states as a containment strategy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The effectiveness of these policy interventions on morbidity and mortality remains unknown. Our analysis examined the associations between statewide policies and objective measures of social distancing, and objective social distancing and COVID-19 incidence and mortality. We used nationwide, de-identified smartphone GPS data to estimate county-level social distancing. COVID-19 incidence and mortality data were from the Johns Hopkins Coronavirus Resource Center. Generalized linear mixed models were used to estimate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for the association between objective social distancing and COVID-19 incidence and mortality. Stay-at-home orders were associated with a 35% increase in social distancing. Higher social distancing was associated with a 29% reduction in COVID-19 incidence (adjusted IRR 0.71; 95% CI 0.57-0.87) and a 35% reduction in COVID-19 mortality (adjusted IRR 0.65; 95% CI 0.55-0.76). These findings provide evidence to inform ongoing national discussions on the effectiveness of these public health measures and the potential implications of returning to normal social activity.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Joseph Chadi Lemaitre",
-        "author_inst": "EPFL"
-      },
-      {
-        "author_name": "Kyra H Grantz",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Joshua Kaminsky",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Hannah R Meredith",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Shaun A Truelove",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Stephen A Lauer",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
-      },
-      {
-        "author_name": "Lindsay T Keegan",
-        "author_inst": "University of Utah"
-      },
-      {
-        "author_name": "Sam Shah",
-        "author_inst": "Unaffiliated"
+        "author_name": "Trang VoPham",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Josh Wills",
-        "author_inst": "Unaffiliated"
+        "author_name": "Matthew D Weaver",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Kathryn Kaminsky",
-        "author_inst": "Unaffiliated"
+        "author_name": "Jaime E Hart",
+        "author_inst": "Harvard Medical School"
       },
       {
-        "author_name": "Javier Perez-Saez",
-        "author_inst": "Johns Hopkins University"
+        "author_name": "Mimi Ton",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Justin Lessler",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Emily White",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       },
       {
-        "author_name": "Elizabeth C Lee",
-        "author_inst": "Johns Hopkins Bloomberg School of Public Health"
+        "author_name": "Polly A Newcomb",
+        "author_inst": "Fred Hutchinson Cancer Research Center"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1338744,33 +1341409,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.11.20128389",
-    "rel_title": "Profiling the positive detection rate of SARS-CoV-2 using polymerase chain reaction in different types of clinical specimens: a systematic review and meta-analysis",
+    "rel_doi": "10.1101/2020.06.11.20128165",
+    "rel_title": "Easing social distancing index after COVID-19 pandemic",
     "rel_date": "2020-06-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128389",
-    "rel_abs": "BackgroundTesting is one of the commendable preventive measures against coronavirus disease (COVID-19), and needs to be done using both most appropriate specimen and an accurate diagnostic test like real time reverse transcription polymerase chain reaction (qRT-PCR). However, the detection rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA from different clinical specimens after onset of symptoms is not yet well established. For guiding the selection of specimens for clinical diagnosis of COVID-19, a systematic review aiming at profiling the positive detection rate from different clinical specimens using PCR was conducted.\n\nMethodsThe systematic search was done using PubMed/MEDLINE, Science direct, Google Scholar, among others. The search included studies on laboratory diagnosis of SARS-CoV-2 from different clinical specimens using PCR. Data extraction was done using Microsoft Excel spread sheet 2010 and reported according to PRISMA-P guidelines. Using Open Meta Analyst software, DerSimonian-Laird random effects analysis was performed to determine a summary estimate (positive rate [PR]/proportions) and their 95% confidence interval (95%CI).\n\nResultsA total of 8136 different clinical specimens were analyzed to detect SARS-CoV-2, with majority being nasopharyngeal swabs (69.6%). Lower respiratory tract (LRT) specimens had a PR of 71.3% (95%CI:60.3%-82.3%) while no virus was detected from the urinogenital specimens. Bronchoalveolar lavage fluid (BLF) specimen had the PR of 91.8% (95%CI:79.9-103.7%), followed by rectal swabs, 87.8 % (95%CI:78.6%-96.9%) then sputum, 68.1% (95%CI:56.9%-79.4%). Low PR was observed in oropharyngeal swabs, 7.6% (95%CI:5.7%-9.6%) and blood samples, 1.0% (95%CI: -0.1%-2.1%), whilst no SARS-CoV-2 was detected in urine samples. Nasopharyngeal swab, a widely used specimen had a PR of 45.5% (95%CI:31.2%-59.7%).\n\nConclusionIn this study, SARS-CoV-2 was highly detected in lower respiratory tract specimens while there was no detected virus in urinogenital specimens. Regarding the type of clinical specimens, bronchoalveolar lavage fluid had the highest positive rate followed by rectal swab then sputum. Nasopharyngeal swab which is widely used had a moderate detection rate. Low positive rate was recorded in oropharyngeal swab and blood sample while no virus was found in urine samples. More importantly, the virus was detected in feces, suggesting SARS-CoV-2 transmission by the fecal route.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128165",
+    "rel_abs": "ContextEasing social distancing (ESD) is a global public health issue in post-pandemic period of COVID-19 and requires a simple index for real time assessment.\n\nObjectiveWe aimed to develop a simple index for ESD to quantify the impacts of social distancing for reducing confirmed infected cases, optimal triage and care of patients for recovery, and critical care capacity for reducing death from COVID-19.\n\nDesign, Setting, and ParticipantsData on the retrospective cohort of 185 countries with reported numbers on confirmed cases, recovery, and death from COVID-19 were retrieved from publicity available repository. Up to May 31, a total of 5,844,136 confirmed cases, 2,639,961 recovered, and 327,487 deaths were reported globally.\n\nMain Outcome MeasuresThe ESD index measured by cumulative number of COVID-19 cases and recovery and case-fatality rate.\n\nResultsWe developed a simple index for the guidance of easing social distancing (ESD). If the ESD index is less than 1, ESD would be considered. The global ESD index declined from 3.87 at peak in March to 1.35 by the end of May, consisting of 56.76% countries/regions (105/185) with the ESD lower than one.\n\nConclusion and RelevanceThis simple ESD index provides a quantitative assessment on whether and when to ease social distancing from local to global community.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "George M. Bwire",
-        "author_inst": "School of Pharmacy, Muhimbili University of Health and Allied Sciences, P.O. Box 65001, Dar es Salaam, Tanzania."
+        "author_name": "Li-Sheng Chen",
+        "author_inst": "School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan"
+      },
+      {
+        "author_name": "Ming-Fang Yen",
+        "author_inst": "School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan"
       },
       {
-        "author_name": "Mtebe V. Majigo",
-        "author_inst": "School of Medicine, Muhimbili University of Health and Allied Sciences, P.O. Box 65001, Dar es Salaam, Tanzania"
+        "author_name": "Chao-Chih Lai",
+        "author_inst": "Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Emergency Department of Taipei City Hos"
       },
       {
-        "author_name": "Belinda J. Njiro",
-        "author_inst": "School of Medicine, Muhimbili University of Health and Allied Sciences, P.O. Box 65001, Dar es Salaam, Tanzania"
+        "author_name": "Chen-Yang Hsu",
+        "author_inst": "Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Dachung Hospital, Miaoli, Taiwan"
       },
       {
-        "author_name": "Akili Mawazo",
-        "author_inst": "Institute of Allied Health Sciences, Muhimbili University of Health and Allied Sciences, P.O. Box 65001, Dar es Salaam, Tanzania"
+        "author_name": "Hsiu-Hsi Chen",
+        "author_inst": "Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1340626,135 +1343295,51 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.06.10.20127175",
-    "rel_title": "Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic.",
+    "rel_doi": "10.1101/2020.06.10.20127258",
+    "rel_title": "Knowledge, attitudes, and practices among the general population during COVID-19 outbreak in Iran: A national cross-sectional survey",
     "rel_date": "2020-06-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127175",
-    "rel_abs": "BackgroundCardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both \"direct\", through infection, and \"indirect\", through changes in healthcare.\n\nMethodsWe used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(\"direct\" effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For \"indirect\" effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020.\n\nFindingsCVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy and England during the pandemic. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown, and is still reduced in Italy and England. Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous(peak RR 1.4). For total CVD(incident and prevalent), at 10% population COVID-19 rate, we estimated direct impact of 31,205 and 62,410 excess deaths in England at RR 1.5 and 2.0 respectively, and indirect effect of 49932 to 99865 excess deaths.\n\nInterpretationSupply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the COVID-19 pandemic.\n\nFundingNIHR, HDR UK, Astra Zeneca",
-    "rel_num_authors": 29,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127258",
+    "rel_abs": "BackgroundCOVID-19, which emerged in December 2019, is the largest pandemic ever to occur. During the early phase, little was known about public awareness relating to Coronavirus disease. This study was designed to determine knowledge, attitudes and practices (KAP) among the Iranian public towards COVID-19.\n\nMethodsA cross-sectional online survey was carried out in Iran from 2 March to 8 April 2020 using a self-administered questionnaire on 1,480 people. COVID-19-related KAP questions were adapted from other internationally validated questionnaires specific to infectious diseases.\n\nResultsAll participants were aware of COVID-19. When asked unprompted, 80% of respondents could correctly cite fever, difficulty breathing and cough as signs/symptoms of COVID-19. Most of our sample population knew that by staying at home and staying isolated (95.3%, 95 % CI: 94.2-96.3) as well as constant hand washing and using disinfectants (92.5%, 95 % CI: 91.1-93.8) could prevent COVID-19. However, there was also widespread misconceptions such as the belief that COVID-19 can be transmitted by wild animals (58%, 95 % CI: 55.5-60.5) and by air (48.3%, 95 % CI: 45.7-50.8). Unprompted, self-reported actions taken to avoid COVID-19 infection included hand washing with soap and water (95.4%, 95 % CI: 94.3-96.4), avoiding crowded places (93%, 95 % CI: 91.7-94.3), cleaning hands with other disinfectants (80.9 %, 95 % CI: 78.9-82.9), and covering mouths and noses when coughing and sneezing (76.1 %, 95 % CI: 73.9-78.2). The internet and social media (94.5%, 95 % CI: 93.3-95.6) were the main Coronavirus information sources. However, the most trusted information sources on Coronavirus were health and medical professionals (79.3%, 95 % CI: 77.2-81.3). The majority of participants (77.0%, 95 % CI: 74.8-79.1) wanted more information about Coronavirus to be available.\n\nConclusionOur findings suggest that peoples knowledge and attitude towards COVID-19 at the time of its outbreak was of a high level. Therefore, health systems should use multiple ways, such as mass media, phone applications, electronic, print, and tele-education to increase KAP related to COVID-19.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Amitava Banerjee",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Suliang Chen",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Laura Pasea",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Alvina Lai",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Michail Katsoulis",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Spiros Denaxas",
-        "author_inst": "University College London"
-      },
-      {
-        "author_name": "Vahe Nafilyan",
-        "author_inst": "Office for National Statistics"
-      },
-      {
-        "author_name": "Bryan Williams",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Wai Keong Wong",
-        "author_inst": "University College London Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Ameet Bakhai",
-        "author_inst": "Royal Free Hospitals NHS Trust"
-      },
-      {
-        "author_name": "Kamlesh Khunti",
-        "author_inst": "University of Leicester"
-      },
-      {
-        "author_name": "Deenan Pillay",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Mahdad Noursadeghi",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Honghan Wu",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Nilesh Pareek",
-        "author_inst": "King's College Hospital"
-      },
-      {
-        "author_name": "Daniel Bromage",
-        "author_inst": "Kings College London"
-      },
-      {
-        "author_name": "Theresa Mcdonagh",
-        "author_inst": "Kings College London"
-      },
-      {
-        "author_name": "Jonathan Byrne",
-        "author_inst": "Kings London NHS Trust"
-      },
-      {
-        "author_name": "James T Teo",
-        "author_inst": "Kings College Hospital NHS Foundation Trust"
-      },
-      {
-        "author_name": "Ajay Shah",
-        "author_inst": "King's College London"
-      },
-      {
-        "author_name": "Ben Humberstone",
-        "author_inst": "Office for National Statistics"
-      },
-      {
-        "author_name": "Liang V Tang",
-        "author_inst": "Huazhong University of Science and Technology, Wuhan, China"
+        "author_name": "Edris Kakemam",
+        "author_inst": "Tabriz University of Medical Sciences"
       },
       {
-        "author_name": "Anoop SV Shah",
-        "author_inst": "University of Edinburgh"
+        "author_name": "DJavad Ghoddoosi-Nejad",
+        "author_inst": "Birjand University of Medical Sciences"
       },
       {
-        "author_name": "Andrea Rubboli",
-        "author_inst": "Ospedale S. Maria delle Croci, Ravenna, Italy"
+        "author_name": "Zahra Chegini",
+        "author_inst": "Qazvin University of Medical Sciences"
       },
       {
-        "author_name": "Yutao Guo",
-        "author_inst": "PLA General Hospital, Beijing, China."
+        "author_name": "Khalil Momeni",
+        "author_inst": "Ilam University of Medical Sciences"
       },
       {
-        "author_name": "Yu Hu",
-        "author_inst": "Huazhong University of Science and Technology, Wuhan, China."
+        "author_name": "Hamid Salehinia",
+        "author_inst": "Birjand University of Medical sciences"
       },
       {
-        "author_name": "Cathie LM Sudlow",
-        "author_inst": "University of Edinburgh"
+        "author_name": "Soheil Hassanipour",
+        "author_inst": "Guilan University of Medical Sciences"
       },
       {
-        "author_name": "Gregory YH Lip",
-        "author_inst": "University of Liverpool"
+        "author_name": "Hosein Ameri",
+        "author_inst": "Shahid Sadoughi University of Medical Sciences"
       },
       {
-        "author_name": "Harry Hemingway",
-        "author_inst": "UCL"
+        "author_name": "Morteza Arab-Zozani",
+        "author_inst": "Birjand University of Medical Sciences"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "cardiovascular medicine"
+    "category": "medical education"
   },
   {
     "rel_doi": "10.1101/2020.06.09.20126722",
@@ -1342268,71 +1344853,47 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.06.10.144816",
-    "rel_title": "Remdesivir but not famotidine inhibits SARS-CoV-2 replication in human pluripotent stem cell-derived intestinal organoids",
+    "rel_doi": "10.1101/2020.06.11.140285",
+    "rel_title": "ROBOCOV: An affordable open-source robotic platform for COVID-19 testing by RT-qPCR",
     "rel_date": "2020-06-11",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.10.144816",
-    "rel_abs": "Gastrointestinal symptoms in COVID-19 are associated with prolonged symptoms and increased severity. We employed human intestinal organoids derived from pluripotent stem cells (PSC-HIOs) to analyze SARS-CoV-2 pathogenesis and to validate efficacy of specific drugs in the gut. Certain, but not all cell types in PSC-HIOs express SARS-CoV-2 entry factors ACE2 and TMPRSS2, rendering them susceptible to SARS-CoV-2 infection. Remdesivir, a promising drug to treat COVID-19, effectively suppressed SARS-CoV-2 infection of PSC-HIOs. In contrast, the histamine-2-blocker famotidine showed no effect. Thus, PSC-HIOs provide an interesting platform to study SARS-CoV-2 infection and to identify or validate drugs.",
-    "rel_num_authors": 13,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.11.140285",
+    "rel_abs": "Current global pandemic due to the SARS-CoV-2 has struggled and pushed the limits of global health systems. Supply chain disruptions and scarce availability of commercial laboratory reagents have motivated worldwide actors to search for alternative workflows to cope with the demand.\n\nWe have used the OT-2 open-source liquid-handling robots (Opentrons, NY), RNA extraction and RT-qPCR reagents to set-up a reproducible workflow for RT-qPCR SARS-CoV-2 testing. We developed a framework with a template and several functions and classes that allow the creation of customized RT-qPCR automated circuits. As a proof of concept, we provide data obtained by a fully-functional tested code using the MagMax Pathogen RNA/DNA kit and the MagMax Viral/Pathogen II kit (Thermo Fisher Scientific, MA) on the Kingfisher Flex instrument (Thermo Fisher Scientific, MA). With these codes available is easy to create new stations or circuits from scratch, adapt existing ones to changes in the experimental protocol, or perform fine adjustments to fulfil special needs.\n\nThe affordability of this platform makes it accessible for most laboratories and hospitals with a bioinformatician, democratising automated SARS-CoV-2 PCR testing and increasing, temporarily or not, the capacity of carrying out tests. It also confers flexibility, as this platform is not dependant on any particular commercial kit and can be quickly adapted to protocol changes or other special needs.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Jan Krueger",
-        "author_inst": "Ulm University"
+        "author_name": "Jos\u00e9 Luis Villanueva-Ca\u00f1as",
+        "author_inst": "Hospital Cl\u00ednic de Barcelona"
       },
       {
-        "author_name": "Ruediger Gross",
-        "author_inst": "Ulm University"
+        "author_name": "Eva Gonzalez-Roca",
+        "author_inst": "Hospital Cl\u00ednic de Barcelona"
       },
       {
-        "author_name": "Carina Conzelmann",
-        "author_inst": "Ulm University"
+        "author_name": "Aitor Gastaminza Unanue",
+        "author_inst": "Independent engineer"
       },
       {
-        "author_name": "Janis A Mueller",
-        "author_inst": "Ulm University"
-      },
-      {
-        "author_name": "Lennart Koepke",
-        "author_inst": "Ulm University"
-      },
-      {
-        "author_name": "Konstantin Sparrer",
-        "author_inst": "Ulm University"
+        "author_name": "Esther Titos",
+        "author_inst": "Hospital Cl\u00ednic de Barcelona"
       },
       {
-        "author_name": "Desiree Schuetz",
-        "author_inst": "Ulm University"
+        "author_name": "Miguel Juli\u00e1n Mart\u00ednez Yoldi",
+        "author_inst": "Hospital Cl\u00ednic de Barcelona"
       },
       {
-        "author_name": "Thomas Seufferlein",
-        "author_inst": "Ulm University"
+        "author_name": "Andrea Vergara G\u00f3mez",
+        "author_inst": "Hospital Cl\u00ednic de Barcelona"
       },
       {
-        "author_name": "Thomas F.E. Barth",
-        "author_inst": "Ulm University"
-      },
-      {
-        "author_name": "Steffen Stenger",
-        "author_inst": "Ulm University"
-      },
-      {
-        "author_name": "Sandra Heller",
-        "author_inst": "Ulm University"
-      },
-      {
-        "author_name": "Alexander Kleger",
-        "author_inst": "Ulm University"
-      },
-      {
-        "author_name": "Jan Muench",
-        "author_inst": "Ulm University"
+        "author_name": "Joan Ant\u00f3n Puig Butill\u00e9",
+        "author_inst": "Hospital Cl\u00ednic de Barcelona"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2020.06.11.146522",
@@ -1344134,21 +1346695,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.08.20125658",
-    "rel_title": "Temporal evolution of COVID-19 in the states of India using SIQR Model",
+    "rel_doi": "10.1101/2020.06.08.20125062",
+    "rel_title": "Principles and Practice of SARS-CoV-2 Decontamination of N95 Masks with UV-C",
     "rel_date": "2020-06-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125658",
-    "rel_abs": "COVID 19 entered during the last week of April 2020 in India has caused 3,546 deaths with 1,13,321 number of reported cases. Indian government has taken many proactive steps, including strict lockdown of the entire nation for more than 50 days, identification of hotspots, app-based tracking of citizens to track infected. This paper investigated the evolution of COVID 19 in five states of India (Maharashtra, UP, Gujrat, Tamil Nadu, and Delhi) from 1st April 2020 to 20th May 2020. Variation of doubling rate and reproduction number (from SIQR) with time is used to analyse the performance of the majorly affected Indian states. It has been determined that Uttar Pradesh is one of the best performers among five states with the doubling rate crossing 18 days as of 20th May. Tamil Nadu has witnessed the second wave of infections during the second week of May. Maharashtra is continuously improving at a steady rate with its doubling rate reaching to 12.67 days. Also these two states are performing below the national average in terms of infection doubling rate. Gujrat and Delhi have reported the doubling rate of 16.42 days and 15.49 days respectively. Comparison of these states has also been performed based on time-dependent reproduction number. Recovery rate of India has reached to 40 % as the day paper is written.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125062",
+    "rel_abs": "A mainstay of personal protective equipment (PPE) during the COVID-19 pandemic is the N95 filtering facepiece respirator. N95 respirators are commonly used to protect healthcare workers from respiratory pathogens, including the novel coronavirus SARS-CoV-2, and are increasingly employed by other frontline workers and the general public. Under routine circumstances, these masks are disposable, single-use items, but extended use and reuse practices have been broadly enacted to alleviate critical supply shortages during the COVID-19 pandemic. While extended-time single use presents a low risk of pathogen transfer, repeated donning and doffing of potentially contaminated masks presents increased risk of pathogen transfer. Therefore, efficient and safe decontamination methods for N95 masks are needed to reduce the risk of reuse and mitigate local supply shortages. Here we review the available literature concerning use of germicidal ultraviolet-C (UV-C) light to decontaminate N95 masks. We propose a practical method for repeated point-of-use decontamination using commercially-available UV-C crosslinker boxes from molecular biology laboratories to expose each side of the mask to 800-1200 mJ/cm2 of UV-C. We measure the dose that penetrated to the interior of the respirators and model the potential germicidal action on SARS-CoV-2. Our experimental results, in combination with modeled data, suggest that a two-minute UV-C treatment cycle should induce a >3-log-order reduction in viral bioburden on the surface of the respirators, and a 2-log order reduction throughout the interior. The resulting exposure is 100-fold less than the dose expected to damage the masks, facilitating repeated decontamination. As such, UV-C germicidal irradiation (UVGI) is a practical strategy for small-scale point-of-use decontamination of N95s.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "ALOK TIWARI",
-        "author_inst": "IIT BOMBAY"
+        "author_name": "Thomas Huber",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Olivia Goldman",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Alexander E. Epstein",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Gianna Stella",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Thomas P. Sakmar",
+        "author_inst": "Rockefeller University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1346071,67 +1348648,79 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.08.139477",
-    "rel_title": "An Inexpensive RT-PCR Endpoint Diagnostic Assay for SARS-CoV-2 Using Nested PCR: Direct Assessment of Detection Efficiency of RT-qPCR Tests and Suitability for Surveillance",
+    "rel_doi": "10.1101/2020.06.07.20121939",
+    "rel_title": "Mortality Analysis of COVID-19 Confirmed cases in Pakistan",
     "rel_date": "2020-06-09",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.08.139477",
-    "rel_abs": "With a view to extending testing capabilities for the ongoing SARS-CoV-2 pandemic we have developed a test that lowers cost and does not require real time quantitative reverse transcription polymerase chain reaction (RT-qPCR). We developed a reverse transcription nested PCR endpoint assay (RT-nPCR) and showed that RT-nPCR has comparable performance to the standard RT-qPCR test. In the course of comparing the results of both tests, we found that the standard RT-qPCR test can have low detection efficiency (less than 50%) in a real testing scenario which may be only partly explained by low viral representation in many samples. This finding points to the importance of directly monitoring detection efficiency in test environments. We also suggest measures that would improve detection efficiency.",
-    "rel_num_authors": 12,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.07.20121939",
+    "rel_abs": "IntroductionCOVID-19, a novel disease, appeared in December 2019 in China and rapidly spread across the world. Till second week of April 2020, high incidence (2.9/100,000) and cases fatality rates (1.7%)was observed in Pakistan.\n\nThis study was conducted to determine temporal and spatial distribution of first 100 deaths attributed to COVID-19 in Pakistan and their associated demographic factors.\n\nMethodWe conducted a descriptive epidemiological analysis of first 100 deaths reported among RT-PCR confirmed COVID-19 cases. Demographic, epidemiological and risk factors information was obtained associated comorbidities and clinical signs and symptoms were recorded and frequencies were determined.\n\nResultsA total of 100 mortalities with overall Case Fatality Rate 1.67% (CFR) were analysed. Median age of patients was 64.5 years (IQR: 54-70) with 75% (n = 75) Males. Among all deaths reported, 71 (71%) cases had one or more documented comorbidities at the time of diagnosis. Most frequently reported co-morbidities were; hypertension (67 %), followed by Diabetes Mellitus 945%) and Ischemic Heart Diseases (27%). First death was reported on 18 March 2020 and the most frequent presenting symptoms were shortness of breath (87%) and fever (79%). Median duration of illness was eight days (IQR: 4-11 days), median delay reaching hospital to seek health care was three days (IQR: 0-6 days) while median duration of hospital stay was also three days (IQR: 1-7 days). Among all reported deaths, 62% were attributed to local transmission as these cases had no history of international travel. The most affected age group was 60-69 years while no death reported in age group below 20 years.\n\nConclusionHigh CFR among old age group and its association with co-morbidities (chronic disease) suggests targeted interventions such as social distancing and strict quarantine measure for elderly and morbid people. Comparative studies among deaths and recovered patients are recommended to explore further disease dynamics.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Jayeshkumar Narsibhai Davda",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Ambreen Chaudhry",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Keith Frank",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Aamer Ikram",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Sivakumar Prakash",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Mirza Amir Baig",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
       },
       {
-        "author_name": "Gunjan Purohit",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Muhammad Salman",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Devi Prasad Vijayashankar",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Tamkeen Ghafoor",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
       },
       {
-        "author_name": "Dhiviya Vedagiri",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Zakir Hussain",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
       },
       {
-        "author_name": "Karthik Bharadwaj Tallapaka",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Mumtaz Ali Khan",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Krishnan Harinivas Harshan",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biollgy"
+        "author_name": "Jamil Ahmad Ansari",
+        "author_inst": "National Institute of Health"
       },
       {
-        "author_name": "Archana Bharadwaj Siva",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Asif Syed",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
       },
       {
-        "author_name": "Rakesh Kumar Mishra",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Wasif Javed",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
       },
       {
-        "author_name": "Jyotsna Dhawan",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Ehsan Larik",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
       },
       {
-        "author_name": "Imran Siddiqi",
-        "author_inst": "CSIR-Centre for Cellular and Molecular Biology"
+        "author_name": "Muhammad Mohsan Wattoo",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
+      },
+      {
+        "author_name": "Naveed Masood",
+        "author_inst": "Field Epidemiology and Laboratory Training"
+      },
+      {
+        "author_name": "zeeshan Iqbal Baig",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
+      },
+      {
+        "author_name": "Khurram Akram",
+        "author_inst": "Field Epidemiology and Laboratory Training Program"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "molecular biology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.06.05.20094482",
@@ -1347909,25 +1350498,137 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.08.20125377",
-    "rel_title": "Weather variables impact on COVID-19 incidence",
+    "rel_doi": "10.1101/2020.06.08.20124305",
+    "rel_title": "Time-series plasma cell-free DNA analysis reveals disease severity of COVID-19 patients",
     "rel_date": "2020-06-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125377",
-    "rel_abs": "We test the hypothesis of COVID-19 contagion being influenced by meteorological parameters such as temperature or humidity. We analysed data at high spatial resolution (regions in Italy and counties in the USA) and found that while at low resolution this might seem the case, at higher resolution no correlation is found. Our results are consistent with a poor outdoors transmission of the disease. However, a possible indirect correlation between good weather and a decrease in disease spread may occur, as people spend longer time outdoors.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20124305",
+    "rel_abs": "Clinical symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. Detection of individuals at high risk for critical condition is crucial for control of the disease. Herein, for the first time, we profiled and analyzed plasma cell-free DNA (cfDNA) of mild and severe COVID-19 patients. We found that in comparison between mild and severe COVID-19 patients, Interleukin-37 signaling was one of the most relevant pathways; top significantly altered genes included POTEH, FAM27C, SPATA48, which were mostly expressed in prostate and testis; adrenal glands, small intestines and liver were tissues presenting most differentially expressed genes. Our data thus revealed potential tissue involvement, provided insights into mechanism on COVID-19 progression, and highlighted utility of cfDNA as a noninvasive biomarker for disease severity inspections.\n\nOne Sentence SummaryCfDNA analysis in COVID-19 patients reveals severity-related tissue damage.",
+    "rel_num_authors": 30,
     "rel_authors": [
       {
-        "author_name": "Javier G. Corripio",
-        "author_inst": "meteoexploration.com"
+        "author_name": "Xinping Chen",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Yu Lin",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Tao Wu",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
       },
       {
-        "author_name": "Lorna Raso",
-        "author_inst": "meteoexploration.com"
+        "author_name": "Jinjin Xu",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Zhichao Ma",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Kun Sun",
+        "author_inst": "Shenzhen Bay Laboratory"
+      },
+      {
+        "author_name": "Hui Li",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Yuxue Luo",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China; School of Medicine, South China University of Technology, Guangzhou 510006, Guangdong, China"
+      },
+      {
+        "author_name": "Chen Zhang",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Fang Chen",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Jiao Wang",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Tingyu Kuo",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China; BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Xiaojuan Li",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Chunyu Geng",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Feng Lin",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Chaojie Huang",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Junjie Hu",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Jianhua Yin",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Ming Liu",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Ye Tao",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Jiye Zhang",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Rijing Ou",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
+      },
+      {
+        "author_name": "Furong Xiao",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Huanming Yang",
+        "author_inst": "BGI-Tianjin;Prince Aljawhra Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University"
+      },
+      {
+        "author_name": "Jian Wang",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China; James D. Watson Institute of Genome Sciences, Hangzhou 310058, China"
+      },
+      {
+        "author_name": "Xun Xu",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China; Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, 518120, China"
+      },
+      {
+        "author_name": "Shengmiao Fu",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Xin Jin",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China; School of Medicine, South China University of Technology, Guangzhou 510006, Guangdong, China"
+      },
+      {
+        "author_name": "Hongyan Jiang",
+        "author_inst": "Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Hainan Provincial Key Laboratory of Cell and Molecular Genetic Translational M"
+      },
+      {
+        "author_name": "Ruoyan Chen",
+        "author_inst": "BGI-Shenzhen, Shenzhen, 518083, Guangdong, China"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1349179,29 +1351880,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.06.20124149",
-    "rel_title": "Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates",
+    "rel_doi": "10.1101/2020.06.04.20122325",
+    "rel_title": "Sub-weekly cycle uncovers the hidden link of 1atmospheric pollution to Kawasaki Disease",
     "rel_date": "2020-06-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.06.20124149",
-    "rel_abs": "Hawkes processes are used in machine learning for event clustering and causal inference, while they also can be viewed as stochastic versions of popular compartmental models used in epidemiology. Here we show how to develop accurate models of COVID-19 transmission using Hawkes processes with spatial-temporal covariates. We model the conditional intensity of new COVID-19 cases and deaths in the U.S. at the county level, estimating the dynamic reproduction number of the virus within an EM algorithm through a regression on Google mobility indices and demographic covariates in the maximization step. We validate the approach on short-term forecasting tasks, showing that the Hawkes process outperforms several benchmark models currently used to track the pandemic, including an ensemble approach and a SEIR-variant. We also investigate which covariates and mobility indices are most important for building forecasts of COVID-19 in the U.S.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122325",
+    "rel_abs": "Anthropogenic pollution has frequently been linked to myriad human ailments despite clear mechanistic links are yet lacking, a fact that severely downgraded its actual relevance. Now a prominent unnoticed sub-weekly cycle (SWC) of 3.5 days is uncovered in the long-term epidemiological records of Kawasaki disease (KD) in Japan, a mysterious vasculitis of yet unknown origin. After ruling out the effect of reporting biases, the analysis of Light Detection and Ranging (LIDAR) atmospheric profiles further confirms that this variability is linked to atmospheric particles with an aerodynamic diameter less than 1 {micro}m. SWC accounts for 20% of the variance in KD and its contribution is stable throughout the entire epidemiological record dating back to 1970, both at the prefecture level and for entire Japan. KD maxima in 2010-2016 always occur in full synchrony with LIDAR particle arrival in diverse locations such as Tokyo, Toyama and Tsukuba as well as for the entire of Japan. Rapid intrusion of aerosols from heights up to 6km to the surface is observed with KD admissions co-varying with their metal chemical composition. While regional intensity of winds has not changed in the interval 1979-2015, our study instead points for the first time to increased anthropogenic pollution as a necessary co-factor in the occurrence of KD and sets the field to associate other similar human vasculitis.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Wen-Hao Chiang",
-        "author_inst": "Indiana University-Purdue University Indianapolis"
+        "author_name": "Xavier Rodo",
+        "author_inst": "ISGlobal"
       },
       {
-        "author_name": "Xueying Liu",
-        "author_inst": "Indiana University-Purdue University Indianapolis"
+        "author_name": "Albert Navarro Gallinad",
+        "author_inst": "ADAPT Centre, Trinity College Dublin, Dublin, Ireland."
+      },
+      {
+        "author_name": "Tomoko Kojima",
+        "author_inst": "Faculty of Advanced Science and Technology, Kumamoto University, Kumamoto, Japan"
+      },
+      {
+        "author_name": "Joan Ballester",
+        "author_inst": "ISGlobal, Barcelona, Spain"
       },
       {
-        "author_name": "George Mohler",
-        "author_inst": "Indiana University-Purdue University Indianapolis"
+        "author_name": "Silvia Borras",
+        "author_inst": "Climate and Health (CLIMA) Program, ISGlobal, Barcelona, Catalonia, Spain."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1350993,97 +1353702,65 @@
     "category": "health systems and quality improvement"
   },
   {
-    "rel_doi": "10.1101/2020.06.05.20123117",
-    "rel_title": "Serology confirms SARS-CoV-2 infection in PCR-negative children presenting with Paediatric Inflammatory Multi-System Syndrome",
+    "rel_doi": "10.1101/2020.06.05.20123745",
+    "rel_title": "Combined oropharyngeal/nasal swab is equivalent to nasopharyngeal sampling for SARS-CoV-2 diagnostic PCR",
     "rel_date": "2020-06-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123117",
-    "rel_abs": "BackgroundDuring the COVID-19 outbreak, reports have surfaced of children who present with features of a multisystem inflammatory syndrome with overlapping features of Kawasaki disease and toxic shock syndrome - Paediatric Inflammatory Multisystem Syndrome-temporally associated with SARS-CoV-2 pandemic (PIMS-TS). Initial reports find that many of the children are PCR-negative for SARS-CoV-2, so it is difficult to confirm whether this syndrome is a late complication of viral infection in an age group largely spared the worst consequences of this infection, or if this syndrome reflects enhanced surveillance.\n\nMethodsChildren hospitalised for symptoms consistent with PIMS-TS between 28 April and 8 May 2020, and who were PCR-negative for SARS-CoV-2, were tested for antibodies to viral spike glycoprotein using an ELISA test.\n\nResultsEight patients (age range 7-14 years, 63% male) fulfilled case-definition for PIMS-TS during the study period. Six of the eight patients required admission to intensive care. All patients exhibited significant IgG and IgA responses to viral spike glycoprotein. Further assessment showed that the IgG isotypes detected in children with PIMS-TS were of the IgGl and lgG3 subclasses, a distribution similar to that observed in samples from hospitalised adult COVID-19 patients. In contrast, lgG2 and lgG4 were not detected in children or adults. IgM was not detected in children, which contrasts with adult hospitalised adult COVID-19 patients of whom all had positive IgM responses.\n\nConclusionsStrong IgG antibody responses can be detected in PCR-negative children with PIMS-TS. The low detection rate of IgM in these patients is consistent with infection having occurred weeks previously and that the syndrome onset occurs well after the control of SARS-CoV-2 viral load. This implies that the disease is largely immune-mediated. Lastly, this indicates that serology can be an appropriate diagnostic tool in select patient groups.",
-    "rel_num_authors": 21,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123745",
+    "rel_abs": "BackgroundEarly 2020, a COVID-19 epidemic became a public health emergency of international concern. To address this pandemic broad testing with an easy, comfortable and reliable testing method is of utmost concern. The nasopharyngeal (NP) swab sampling is the reference method though hampered by international supply shortages. A new oropharyngeal/nasal (OP/N) sampling method was investigated using the more readily available throat swab.\n\nMethodsIn this prospective observational study 36 COVID-19 patients were tested with both a NP and combined OP/N swab for SARS-CoV-2 RNA by PCR. In hospitalized suspect patients, who tested negative on both swabs, extensive retesting was performed. The sensitivity of NP versus combined OP/N swab sampling on admission and the correlation between viral RNA loads recovered was investigated.\n\nResults35 patients were diagnosed with SARS-CoV-2 by means of either NP or OP/N sampling. The paired swabs were both positive in 31 patients. The one patient who tested negative on both NP and OP/N swab on admission, was ultimately diagnosed on bronchoalveolar lavage fluid. A strong correlation was found between the viral RNA loads of the paired swabs (r = 0.76; P < 0.05). The sensitivity of NP and OP/N analysis in hospitalized patients (n = 28) was 89.3% and 92.7% respectively.\n\nConclusionsThis study demonstrates equivalence of NP and OP/N sampling for detection of SARS-CoV-2 by means of rRT-PCR. Sensitivity of both NP and OP/N sampling is very high in hospitalized patients.",
+    "rel_num_authors": 13,
     "rel_authors": [
       {
-        "author_name": "Marisol Perez-Toledo",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Sian E. Faustini",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Sian E. Jossi",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Adrian Shields",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "Hari Krishnan Kanthimathinathan",
-        "author_inst": "Birmingham Women and Children's NHS Foundation Trust"
-      },
-      {
-        "author_name": "Joel D. Allen",
-        "author_inst": "University of Southampton"
-      },
-      {
-        "author_name": "Yasunori Watanabe",
-        "author_inst": "University of Southampton"
-      },
-      {
-        "author_name": "Margaret Goodall",
-        "author_inst": "University of Birmingham"
-      },
-      {
-        "author_name": "David C. Wraith",
-        "author_inst": "University of Birmingham"
+        "author_name": "Tania Desmet",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Tonny V. Veenith",
-        "author_inst": "University Hospitals Birmingham NHS Trust"
+        "author_name": "Peter De Paepe",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Mark T. Drayson",
-        "author_inst": "University of Birmingham"
+        "author_name": "Jerina Boelens",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Deepthi Jyothish",
-        "author_inst": "Birmingham Women's and Children's NHS Foundation Trust"
+        "author_name": "Liselotte Coorevits",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Eslam Al-Abadi",
-        "author_inst": "Birmingham Women's and Children's NHS Foundation Trust"
+        "author_name": "Elizaveta Padalko",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Ashish Chikermane",
-        "author_inst": "Birmingham Women's and Children's NHS Foundation Trust"
+        "author_name": "Stien Vandendriessche",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Steven Welch",
-        "author_inst": "University Hospitals Birmingham"
+        "author_name": "Isabel Leroux-Roels",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Kavitha Masilamani",
-        "author_inst": "Birmingham Women's and Children's NHS Foundation Trust"
+        "author_name": "Annelies Aerssens",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Scott Hackett",
-        "author_inst": "University Hospitals Birmingham"
+        "author_name": "Steven Callens",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Max Crispin",
-        "author_inst": "University of Southampton"
+        "author_name": "Eva Van Braeckel",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Barnaby Scholefield",
-        "author_inst": "University of Birmingham"
+        "author_name": "Thomas Malfait",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Adam F. Cunningham",
-        "author_inst": "University of Birmingham"
+        "author_name": "Frank Vermassen",
+        "author_inst": "Ghent University Hospital"
       },
       {
-        "author_name": "Alex G. Richter",
-        "author_inst": "University of Birmingham"
+        "author_name": "Bruno Verhasselt",
+        "author_inst": "Ghent University Hospital"
       }
     ],
     "version": "1",
@@ -1352203,31 +1354880,131 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.04.20122317",
-    "rel_title": "Heart Disease Deaths during the Covid-19 Pandemic",
+    "rel_doi": "10.1101/2020.06.07.137802",
+    "rel_title": "Neuropilin-1 facilitates SARS-CoV-2 cell entry and provides a possible pathway into the central nervous system",
     "rel_date": "2020-06-07",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122317",
-    "rel_abs": "The SARS-CoV-2 pandemic is associated with a reduction in hospitalization for an acute cardiovascular conditions. In a major health system in Massachusetts, there was a 43% reduction in these types of hospitalizations in March 2020 compared with March 2019.4 Whether mortality rates from heart disease have changed over this period is unknown.\n\nWe assembled information from the National Center for Health Statistics (Centers for Disease Control and Prevention) for 118,356,533 person-weeks from Week 1 (ending January 4) through Week 17 (ending April 25) of 2020 for the state of Massachusetts. We found that heart disease deaths are unchanged during the Covid-19 pandemic period as compared to the corresponding period of 2019. This is despite reports that admissions for acute myocardial infarction have fallen during this time.",
-    "rel_num_authors": 3,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.07.137802",
+    "rel_abs": "The causative agent of the current pandemic and coronavirus disease 2019 (COVID-19) is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1. Understanding how SARS-CoV-2 enters and spreads within human organs is crucial for developing strategies to prevent viral dissemination. For many viruses, tissue tropism is determined by the availability of virus receptors on the surface of host cells2. Both SARS-CoV and SARS-CoV-2 use angiotensin-converting enzyme 2 (ACE2) as a host receptor, yet, their tropisms differ3-5. Here, we found that the cellular receptor neuropilin-1 (NRP1), known to bind furin-cleaved substrates, significantly potentiates SARS-CoV-2 infectivity, which was inhibited by a monoclonal blocking antibody against the extracellular b1b2 domain of NRP1. NRP1 is abundantly expressed in the respiratory and olfactory epithelium, with highest expression in endothelial cells and in the epithelial cells facing the nasal cavity. Neuropathological analysis of human COVID-19 autopsies revealed SARS-CoV-2 infected NRP1-positive cells in the olfactory epithelium and bulb. In the olfactory bulb infection was detected particularly within NRP1-positive endothelial cells of small capillaries and medium-sized vessels. Studies in mice demonstrated, after intranasal application, NRP1-mediated transport of virus-sized particles into the central nervous system. Thus, NRP1 could explain the enhanced tropism and spreading of SARS-CoV-2.",
+    "rel_num_authors": 28,
     "rel_authors": [
       {
-        "author_name": "Jeremy Faust",
-        "author_inst": "Brigham and Women's Hospital, Harvard Medical School"
+        "author_name": "Ludovico Cantuti-Castelvetri",
+        "author_inst": "TU Munich"
       },
       {
-        "author_name": "Zhenqiu Lin",
-        "author_inst": "Yale-New Haven Hospital, Center for Outcomes Research and Evaluation"
+        "author_name": "Ravi Ohja",
+        "author_inst": "University of Helsinki"
       },
       {
-        "author_name": "Harlan Krumholz",
-        "author_inst": "Yale University"
+        "author_name": "Liliana Pedro",
+        "author_inst": "TU Munich"
+      },
+      {
+        "author_name": "Minou Djannatian",
+        "author_inst": "TU Munich"
+      },
+      {
+        "author_name": "Jonas Franz",
+        "author_inst": "University of Goettingen"
+      },
+      {
+        "author_name": "Suvi Kuivanen",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Katri Kallio",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Tugberg Kaya",
+        "author_inst": "TU Munich"
+      },
+      {
+        "author_name": "Maria Anastasina",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Teemu Smura",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Lev Levanov",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Leonora Szirovicza",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Allan Tobi",
+        "author_inst": "University of Tartu"
+      },
+      {
+        "author_name": "Hannimari Kallio-Kokko",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Pamela Osterlund",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Merja Joensuu",
+        "author_inst": "University of Queensland"
+      },
+      {
+        "author_name": "Frederic Meunier",
+        "author_inst": "University of Queensland"
+      },
+      {
+        "author_name": "Sarah Butcher",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Martin Winkler",
+        "author_inst": "University of Goettingen"
+      },
+      {
+        "author_name": "Brit Mollenhauer",
+        "author_inst": "University of Goettingen"
+      },
+      {
+        "author_name": "Ari Helenius",
+        "author_inst": "ETH Zuerich"
+      },
+      {
+        "author_name": "Ozgun Gokce",
+        "author_inst": "LMU Munich"
+      },
+      {
+        "author_name": "Tambet Teesalu",
+        "author_inst": "University of Tartu"
+      },
+      {
+        "author_name": "Jussi Hepojoki",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Olli Vapalahti",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Christine Stadelmann",
+        "author_inst": "University of Goettingen"
+      },
+      {
+        "author_name": "Giuseppe Balistreri",
+        "author_inst": "University of Helsinki"
+      },
+      {
+        "author_name": "Mikael Simons",
+        "author_inst": "TU Munich"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.06.06.138149",
@@ -1354125,27 +1356902,23 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.02.20117499",
-    "rel_title": "Emergency calls are early indicators of ICU bed requirement during the COVID-19 epidemic",
+    "rel_doi": "10.1101/2020.06.01.20119560",
+    "rel_title": "Covid-19 Epidemiological Factor Analysis: Identifying Principal Factors with Machine Learning",
     "rel_date": "2020-06-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20117499",
-    "rel_abs": "BackgroundAlthough the number of intensive care unit (ICU) beds is crucial during the COVID-19 epidemic caring for the most critically ill infected patients, there is no recognized early indicator to anticipate ICU bed requirements.\n\nMethodsIn the Ile-de-France region, from February 20 to May 5, 2020, emergency medical service (EMS) calls and the response provided (ambulances) together the percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, general practitioner (GP) and emergency department (ED) visits, and hospital admissions of COVID-19 patients were recorded daily and compared to the number of COVID-19 ICU patients. Correlation curve analysis was performed to determine the best correlation coefficient (R), depending on the number of days the indicator has been shifted. A delay [&ge;]7 days was considered as an early alert, and a delay [&ge;]14 days a very early alert.\n\nFindingsEMS calls, percentage of positive RT-PCR tests, ambulances used, ED and GP visits of COVID-19 patients were strongly associated with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipate ICU bed requirement.\n\nInterpretationThe daily number of COVID19-related telephone calls received by the EMS and corresponding dispatch ambulances, and the proportion of positive RT-PCR tests were the earliest indicators of the number of COVID19 patients requiring ICU care during the epidemic crisis in the Ile-de-France region, rapidly followed by ED and GP visits. This information may help health authorities to anticipate a future epidemic, including a second wave of COVID19 or decide additional social measures.\n\nFundingOnly institutional funding was provided.\n\nResearch in contextO_ST_ABSEvidence before the studyC_ST_ABSWe searched PubMed and preprint archives for articles published up to May 17, 2020, that contained information about the anticipation of intensive care unit (ICU) bed requirement during the COVID-19 outbreak using the terms \"coronavirus\", \"2009-nCOV\", \"COVID-19\", SARS-CoV2\", \"prediction\" \"resource\" and \"intensive care\". We also reviewed relevant references in retrieved articles and the publicly available publication list of the COVID-19 living systematic review.22 This list contains studies on covid-19 published on PubMed and Embase through Ovid, bioRxiv, and medRxiv, and is continuously updated. Although many studies estimated the number of patients who would have severe COVID-19 requiring ICU, very few contained assessment for early signals (from internet or social media), and we retrieved no study whose data came from suspected or infected patients.\n\nAdded values of this studyDuring the COVID-19 epidemic, emergency medical system (EMS) calls, percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, ambulance dispatch, emergency department (ED) and general practitioner (GP) visits of COVID-19 patients were strongly associated with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipated COVID-19 ICU bed requirement.\n\nImplication of all available evidenceEMS calls and ambulance dispatch, percent of positive RT-PCR, and ED and GP visits could be valuable tools as daily alert signals to set up plan to face the burden of ICU bed requirement during the initial wave of the COVID-19 epidemic, and may possibly also help anticipating a second wave. These results are important since mortality has been reported being correlated to health care resources.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20119560",
+    "rel_abs": "Based on a subset of Covid-19 Wave 1 cases at a time point near TZ+3m (April, 2020), we perform an analysis of the influencing factors for the epidemics impacts with several different statistical methods. The consistent conclusion of the analysis with the available data is that apart from the policy and management quality, being the dominant factor, the most influential factors among the considered were current or recent universal BCG immunization and the prevalence of smoking.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "- The COVID-19 APHP-Universities-INRIA-INSERM Group",
-        "author_inst": ""
-      },
-      {
-        "author_name": "Bruno Riou",
-        "author_inst": "Sorbonne Universite and Assistance Publique-Hopitaux de Paris, Paris, France"
+        "author_name": "Serge Dolgikh",
+        "author_inst": "National Aviation University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "emergency medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.06.02.20119859",
@@ -1355471,39 +1358244,55 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2020.06.03.20121590",
-    "rel_title": "Deep Learning and Holt-Trend Algorithms for predicting COVID-19  pandemic",
+    "rel_doi": "10.1101/2020.06.04.20121848",
+    "rel_title": "An Agent Based Model methodology for assessing spread and health systems burden for Covid-19 using a synthetic population from India",
     "rel_date": "2020-06-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.03.20121590",
-    "rel_abs": "According to WHO, more than one million individuals are infected with COVID-19, and around 20000 people have died because of this infectious disease around the world. In addition, COVID-19 epidemic poses serious public health threat to the world where people with little or no pre-existing human immunity can be more vulnerable to the effects of the effects of the coronavirus. Thus, developing surveillance systems for predicting COVID-19 pandemic in an early stage saves millions of lives. In this study, the deep learning algorithm and Holt-trend model is proposed to predict coronavirus. The Long-Short Term Memory (LSTM) algorithm and Holt-trend were applied to predict confirmed numbers and death cases. The real time data have been collected from the World Health Organization (WHO). In the proposed research, we have considered three countries to test the proposed model namely Saudi Arabia, Spain and Italy. The results suggest that the LSTM models showed better performance in predicting the cases of coronavirus patients. Standard measure performance MSE, RMSE, Mean error and correlation are employed to estimate the results of the proposed models. The empirical results of the LSTM by using correlation metric are 99.94%, 99.94% and 99.91 to predict number of confirmed cases on COVID-19 in three countries. Regarding the prediction results of LSTM model to predict the number of death on COVID-19 are 99.86%, 98.876% and 99.16 with respect to the Saudi Arabia, Italy and Spain respectively. Similarly the experimented results of Holt-Trend to predict the number of confirmed cases on COVID-19 by using correlation metrics are 99.06%, 99.96% and 99.94, whereas the results of Holt-Trend to predict the number of death cases are 99.80%, 99.96 and 99.94 with respect to the Saudi Arabia, Italy and Spain respectively. The empirical results indicate the efficient performance of the presented model in predicting the number of confirmed and death cases of COVID-19 in these countries. Such findings provide better insights about the future of COVID-19 in general. The results were obtained by applying the time series models which needs to be considered for the sake of saving the lives of many people.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20121848",
+    "rel_abs": "ObjectivesTo evaluate the transmission dynamics and health systems burden of COVID-19 with and without interventions, using an Agent Based Modeling (ABM) approach on a localized synthetic population.\n\nStudy designA synthetic population of Rangareddy district, Telangana state, India, with 5,48,323 agents and simulated using an ABM approach for three different scenarios.\n\nMethodsThe patterns and trends of the COVID-19 in terms of infected, admitted, critical cases requiring intensive care and/ or ventilator support, mortality and recovery were examined. The model was simulated over a period of 365 days for a no lockdown scenario and two Non-Pharmaceutical Intervention (NPI) scenarios i.e., 50% lockdown and 75% lockdown scenarios.\n\nResultsResults revealed that the peak values and slope of the curve declined as NPI became more stringent. The peak values could facilitate policymakers to plan the required capacity to accommodate influx of hospitalizations.\n\nConclusionsABM provides better insight into projections compared to compartmental models. The results could provide a platform for researchers and modelers to explore using ABM approach for COVID-19 projections with inclusion of interventions and health system preparedness.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Theyazn H.H Aldhyani",
-        "author_inst": "Department of Computer Science and Information at king faisal University, Kingdom of Saudi Arabia"
+        "author_name": "Narassima MS",
+        "author_inst": "Amrita Vishwa Vidyapeetham"
       },
       {
-        "author_name": "Melfi Alrasheed Sr.",
-        "author_inst": "Department of Quantitative Methods, School of Business, King Faisal University. Saudi"
+        "author_name": "Guru Rajesh Jammy",
+        "author_inst": "Society for Health, Allied Research and Education (SHARE-INDIA), Telangana, India."
+      },
+      {
+        "author_name": "Rashmi Pant",
+        "author_inst": "Society for Health Allied Research and Education (SHARE-INDIA)"
       },
       {
-        "author_name": "Ahmed i Abdullah Alqarn Sr.",
-        "author_inst": "Department of Computer Sciences and Information Technology, Albaha University,"
+        "author_name": "Lincoln Choudhury",
+        "author_inst": "Krashapana Consultancy Private limited, New Delhi, India."
       },
       {
-        "author_name": "Mohammed Y. Alzahrani",
-        "author_inst": "Department of Computer Sciences and Information Technology, Albaha University"
+        "author_name": "Aadharsh R",
+        "author_inst": "Amrita Vishwa Vidyapeetham"
       },
       {
-        "author_name": "Ahmed H., Alahmadi",
-        "author_inst": "Department of Computer Science and Information at Taibah University,"
+        "author_name": "Vijay Yeldandi",
+        "author_inst": "Society for Health, Allied Research and Education (SHARE-INDIA), Telangana, India."
+      },
+      {
+        "author_name": "Anbuudayasankar SP",
+        "author_inst": "Amrita Vishwa Vidyapeetham"
+      },
+      {
+        "author_name": "Rangasami P",
+        "author_inst": "Amrita Vishwa Vidyapeetham"
+      },
+      {
+        "author_name": "Denny John",
+        "author_inst": "Department of Public Health, Amrita Institute of Medical Sciences and Research Centre, Amrita Vishwa Vidyapeetham, Kochi, Kerala, India"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.06.04.20122028",
@@ -1357612,71 +1360401,47 @@
     "category": "neurology"
   },
   {
-    "rel_doi": "10.1101/2020.06.04.20122846",
-    "rel_title": "A tertiary center experience of multiple myeloma patients with COVID-19: lessons learned and the path forward",
+    "rel_doi": "10.1101/2020.06.04.20122564",
+    "rel_title": "Adverse effects of COVID-19 related lockdown on pain, physical activity and psychological wellbeing in people with chronic pain",
     "rel_date": "2020-06-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122846",
-    "rel_abs": "BackgroundThe COVID-19 pandemic, caused by SARS-CoV-2 virus, has resulted in over 100,000 deaths in the United States. Our institution has treated over 2,000 COVID-19 patients during the pandemic in New York City. The pandemic directly impacted cancer patients and the organization of cancer care. Mount Sinai Hospital has a large and diverse multiple myeloma (MM) population. Herein, we report the characteristics of COVID-19 infection and serological response in MM patients in a large tertiary care institution in New York.\n\nMethodsWe performed a retrospective study on a cohort of 58 patients with a plasma-cell disorder (54 MM, 4 smoldering MM) who developed COVID-19 between March 1, 2020 and April 30, 2020. We report epidemiological, clinical and laboratory characteristics including persistence of viral detection by polymerase chain reaction (PCR) and anti-SARS-CoV-2 antibody testing, treatments initiated, and outcomes.\n\nResultsOf the 58 patients diagnosed with COVID-19, 36 were hospitalized and 22 were managed at home. The median age was 67 years; 52% of patients were male and 63% were non-white. Hypertension (64%), hyperlipidemia (62%), obesity (37%), diabetes mellitus (28%), chronic kidney disease (24%) and lung disease (21%) were the most common comorbidities. In the total cohort, 14 patients (24%) died. Older age (>70 years), male sex, cardiovascular risk, and patients not in complete remission (CR) or stringent CR were significantly (p<0.05) associated with hospitalization. Among hospitalized patients, laboratory findings demonstrated elevation of traditional inflammatory markers (CRP, ferritin, D-dimer) and a significant (p<0.05) association between elevated inflammatory markers, severe hypogammaglobulinemia, non-white race, and mortality. Ninety-six percent (22/23) of patients developed antibodies to SARS-CoV-2 at a median of 32 days after initial diagnosis. Median time to PCR negativity was 43 (range 19-68) days from initial positive PCR.\n\nConclusionsDrug exposure and MM disease status at the time of contracting COVID-19 had no bearing on mortality. Mounting a severe inflammatory response to SARS-CoV-2 and severe hypogammaglobulinemia were associated with higher mortality. The majority of patients mounted an antibody response to SARS-CoV-2. These findings pave a path to identification of vulnerable MM patients who need early intervention to improve outcome in future outbreaks of COVID-19.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122564",
+    "rel_abs": "Countries across the world imposed lockdown restrictions during the COVID-19 pandemic. It has been proposed that lockdown conditions disproportionately impact those living with chronic pain, requiring adaptation to treatment and care strategies. We investigated how lockdown restrictions in the United Kingdom impacted individuals with chronic pain (N = 431) relative to a healthy control group (N = 88) using an online survey. In accordance with the fear-avoidance model, we hypothesised increases in perceived pain and psychological distress that would be mediated by pain catastrophizing. Survey questions answered during the lockdown period, probing patients self-perceived changes retrospectively, revealed that people with chronic pain perceived increases in their pain severity compared to before lockdown. They were also more adversely affected by lockdown compared to pain-free individuals, demonstrating greater increases in anxiety and depressed mood, increased loneliness and reduced levels of physical exercise. Pain catastrophizing was found to be an important factor in predicting the extent of self-perceived increases in pain, and accounted for the relationship between decreased mood and pain. Perceived decreases in levels of physical exercise also independently predicted perceptions of increased pain. Interestingly, actual changes in pain symptoms (measured at two time points at pre- and post-lockdown in a subgroup, N = 85) did not change significantly on average, but those reporting increases also demonstrated greater baseline levels of pain catastrophizing. Overall, the findings suggest that remote pain management provision to target reduction of catastrophizing and increases to physical activity could be beneficial for chronic pain patients in overcoming the adverse effects of lockdown.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Bo Wang",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
-      },
-      {
-        "author_name": "Oliver Van Oekelen",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
-      },
-      {
-        "author_name": "Tarek Mouhieddine",
-        "author_inst": "Mount Sinai Hospital"
-      },
-      {
-        "author_name": "Diane Marie Del Valle",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
-      },
-      {
-        "author_name": "Joshua Richter",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
-      },
-      {
-        "author_name": "Hearn Jay Cho",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
-      },
-      {
-        "author_name": "Shambavi Richard",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
+        "author_name": "Nicholas Fallon",
+        "author_inst": "University of Liverpool"
       },
       {
-        "author_name": "Ajai Chari",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
+        "author_name": "Christopher Brown",
+        "author_inst": "University of Liverpool"
       },
       {
-        "author_name": "Sacha Gnjatic",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Hannah Twiddy",
+        "author_inst": "Walton Centre NHS Foundation Trust"
       },
       {
-        "author_name": "Miriam Merad",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Eleanor Brian",
+        "author_inst": "University of Liverpool"
       },
       {
-        "author_name": "Sundar Jagannath",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
+        "author_name": "Bernhard Frank",
+        "author_inst": "Walton Centre NHS Foundation Trust"
       },
       {
-        "author_name": "Samir Parekh",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
+        "author_name": "Turo Nurmikko",
+        "author_inst": "Walton Centre NHS Foundation Trust"
       },
       {
-        "author_name": "Deepu Madduri",
-        "author_inst": "Icahn Mount Sinai Tisch Cancer Institute"
+        "author_name": "Andrej Stancak",
+        "author_inst": "University of Liverpool"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "oncology"
+    "category": "pain medicine"
   },
   {
     "rel_doi": "10.1101/2020.06.05.135954",
@@ -1358946,79 +1361711,135 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.03.132639",
-    "rel_title": "Human iPSC-derived alveolar and airway epithelial cells can be cultured at air-liquid interface and express SARS-CoV-2 host factors",
+    "rel_doi": "10.1101/2020.06.04.135012",
+    "rel_title": "Olfactory transmucosal SARS-CoV-2 invasion as port of Central Nervous System entry in COVID-19 patients",
     "rel_date": "2020-06-04",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.03.132639",
-    "rel_abs": "Development of an anti-SARS-CoV-2 therapeutic is hindered by the lack of physiologically relevant model systems that can recapitulate host-viral interactions in human cell types, specifically the epithelium of the lung. Here, we compare induced pluripotent stem cell (iPSC)-derived alveolar and airway epithelial cells to primary lung epithelial cell controls, focusing on expression levels of genes relevant for COVID-19 disease modeling. iPSC-derived alveolar epithelial type II-like cells (iAT2s) and iPSC-derived airway epithelial lineages express key transcripts associated with lung identity in the majority of cells produced in culture. They express ACE2 and TMPRSS2, transcripts encoding essential host factors required for SARS-CoV-2 infection, in a minor subset of each cell sub-lineage, similar to frequencies observed in primary cells. In order to prepare human culture systems that are amenable to modeling viral infection of both the proximal and distal lung epithelium, we adapt iPSC-derived alveolar and airway epithelial cells to two-dimensional air-liquid interface cultures. These engineered human lung cell systems represent sharable, physiologically relevant platforms for SARS-CoV-2 infection modeling and may therefore expedite the development of an effective pharmacologic intervention for COVID-19.",
-    "rel_num_authors": 15,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.04.135012",
+    "rel_abs": "The newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic respiratory disease presenting with fever, cough, and often pneumonia. Moreover, thromboembolic events throughout the body including the central nervous system (CNS) have been described. Given first indication for viral RNA presence in the brain and cerebrospinal fluid and in light of neurological symptoms in a large majority of COVID-19 patients, SARS-CoV-2-penetrance of the CNS is likely. By precisely investigating and anatomically mapping oro- and pharyngeal regions and brains of 32 patients dying from COVID-19, we not only describe CNS infarction due to cerebral thromboembolism, but also demonstrate SARS-CoV-2 neurotropism. SARS-CoV-2 enters the nervous system via trespassing the neuro-mucosal interface in the olfactory mucosa by exploiting the close vicinity of olfactory mucosal and nervous tissue including delicate olfactory and sensitive nerve endings. Subsequently, SARS-CoV-2 follows defined neuroanatomical structures, penetrating defined neuroanatomical areas, including the primary respiratory and cardiovascular control center in the medulla oblongata.",
+    "rel_num_authors": 29,
     "rel_authors": [
       {
-        "author_name": "Kristine M Abo",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Jenny Meinhardt",
+        "author_inst": "Charite - Universitaetsmedizin Berlin"
       },
       {
-        "author_name": "Liang Ma",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Josefine Radke",
+        "author_inst": "Charite -  Universitaetsmedizin Berlin"
       },
       {
-        "author_name": "Taylor Matte",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Carsten Dittmayer",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Jessie Huang",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Ronja Mothes",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Konstantinos D Alysandratos",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Jonas Franz",
+        "author_inst": "University Medical Center, Goettingen"
       },
       {
-        "author_name": "Rhiannon B Werder",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Michael Laue",
+        "author_inst": "Robert Koch Institute Berlin"
       },
       {
-        "author_name": "Aditya Mithal",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Julia Schneider",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Mary Lou Beermann",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Sebastian Bruenink",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Jonathan Lindstrom-Vautrin",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Olga Hassan",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Gustavo Mostoslavsky",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Werner Stenzel",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Laertis Ikonomou",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Marc Windgassen,",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Darrell N Kotton",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Larissa Roessler",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Finn Hawkins",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Hans-Hilmar Goebel",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Andrew Wilson",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Hubert Martin",
+        "author_inst": "Charite"
       },
       {
-        "author_name": "Carlos Villacorta-Martin",
-        "author_inst": "Boston University School of Medicine and Boston Medical Center"
+        "author_name": "Andreas Nitsche",
+        "author_inst": "Robert Koch Institute Berlin"
+      },
+      {
+        "author_name": "Walter Schulz-Schaeffer",
+        "author_inst": "University of the Saarland"
+      },
+      {
+        "author_name": "Samy Hakroush",
+        "author_inst": "University Medical Center Goettingen, Germany"
+      },
+      {
+        "author_name": "Martin S Winkler",
+        "author_inst": "University Medical Center Goettingen, Germany"
+      },
+      {
+        "author_name": "Bjoern Tampe",
+        "author_inst": "University Medical Center Goettingen, Germany"
+      },
+      {
+        "author_name": "Sefer Elezkurtaj",
+        "author_inst": "Charite"
+      },
+      {
+        "author_name": "David Horst",
+        "author_inst": "Charite"
+      },
+      {
+        "author_name": "Lars Oesterhelweg",
+        "author_inst": "Charite"
+      },
+      {
+        "author_name": "Michael Tsokos",
+        "author_inst": "Charite"
+      },
+      {
+        "author_name": "Barbara Ingold Heppner",
+        "author_inst": "DRK Kliniken Berlin"
+      },
+      {
+        "author_name": "Christine Stadelmann",
+        "author_inst": "University Medical Center, Goettingen"
+      },
+      {
+        "author_name": "Christian Drosten",
+        "author_inst": "Charite Universitaetsmedizin"
+      },
+      {
+        "author_name": "Victor M Corman",
+        "author_inst": "Charite - Universitaetsmedizin Berlin"
+      },
+      {
+        "author_name": "Helena Radbruch",
+        "author_inst": "Charite - Universitaetsmedizin Berlin"
+      },
+      {
+        "author_name": "Frank L Heppner",
+        "author_inst": "Charite - Universitaetsmedizin Berlin"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "molecular biology"
+    "category": "neuroscience"
   },
   {
     "rel_doi": "10.1101/2020.06.04.128751",
@@ -1360512,39 +1363333,43 @@
     "category": "pathology"
   },
   {
-    "rel_doi": "10.1101/2020.06.01.20119347",
-    "rel_title": "COVID-19 Public Sentiment Insights and MachineLearning for Tweets Classification",
+    "rel_doi": "10.1101/2020.05.29.20117143",
+    "rel_title": "Detection of lung hypoperfusion in Covid-19 patients during recovery by digital imaging quantification",
     "rel_date": "2020-06-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20119347",
-    "rel_abs": "Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fueled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better understand COVID-19s informational crisis and gauge public sentiment, so that appropriate messaging and policy decisions can be implemented. In this research article, we identify public sentiment associated with the pandemic using Coronavirus specific Tweets and R statistical software, along with its sentiment analysis packages. We demonstrate insights into the progress of fear-sentiment over time as COVID-19 approached peak levels in the United States, using descriptive textual analytics supported by necessary textual data visualizations. Furthermore, we provide a methodological overview of two essential machine learning (ML) classification methods, in the context of textual analytics, and compare their effectiveness in classifying Coronavirus Tweets of varying lengths. We observe a strong classification accuracy of 91% for short Tweets, with the Naive Bayes method. We also observe that the logistic regression classification method provides a reasonable accuracy of 74% with shorter Tweets, and both methods showed relatively weaker performance for longer Tweets. This research provides insights into Coronavirus fear sentiment progression, and outlines associated methods, implications, limitations and opportunities.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20117143",
+    "rel_abs": "PurposeA large number of patients affected by the SARS-Cov-2 virus worldwide undergo recovery of symptoms in about one month. Among these patients, the healing process is still under observation, with some patients in need of careful clinical monitoring. While the radiological findings have been shown to regress almost completely, little knowledge is available at the moment about other complications in the lung and in other organs. We then investigated the lung perfusion conditions in patients affected by COVID-19 during recovery.\n\nMethodWe retrospectively studied 20 patients, from 14 to 60 days after resolution of the COVID-19 symptoms, using chest CT. In a subgroup of 5 patients contrasted CT was used. Beside normal radiological evaluation of lung tissue, perfusion conditions were evaluated by digital image processing in the lung volume automatically segmented.\n\nResultsPulmonary lung evaluation showed that COVID-19 pneumonia almost completely regressed, with mild focal areas affected by fibrous stripes. In patients that reported dyspnea, lung CT showed complete resolution of interstitial changes. Quantification of lung perfusion condition by contrasted CT, showed that dyspnea in 3 patients was associated with areas of hypoperfusion, while in 2 patients not reporting dyspnea perfusion conditions were comparable to normal controls.\n\nConclusionsAlthough we obtained preliminary data, this is the first report on quantitative evaluation of hypoperfused lung tissue detected in recovering COVID-19 patients. These results suggest the need to further investigate these patients and to redefine the role of CT evaluation for diagnostic purposes as well as for evaluation of potential treatments.\n\nFundingThis was an academic study that received no direct funding.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Jim Samuel",
-        "author_inst": "University of Charleston, Charleston, WV"
+        "author_name": "Gianluigi Patelli",
+        "author_inst": "Bolognini Hospital - ASST Bergamo Est"
       },
       {
-        "author_name": "Ali G. G. Md. Nawaz",
-        "author_inst": "University of Charleston, Charleston, WV"
+        "author_name": "Silvia Paganoni",
+        "author_inst": "Bolognini Hospital - ASST Bergamo Est"
       },
       {
-        "author_name": "Md Mokhlesur Rahman",
-        "author_inst": "University of North Carolina at Charlotte, Charlotte, NC;  Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh"
+        "author_name": "Francesca Besana",
+        "author_inst": "Bolognini Hospital - ASST Bergamo Est"
       },
       {
-        "author_name": "Ek Esawi",
-        "author_inst": "University of Charleston, Charleston, WV"
+        "author_name": "Mattia Ronzoni",
+        "author_inst": "D/Vision Lab srl"
       },
       {
-        "author_name": "Yana Samuel",
-        "author_inst": "Northeastern University, Boston, MA"
+        "author_name": "Simone Manini",
+        "author_inst": "D/Vision Lab srl"
+      },
+      {
+        "author_name": "Andrea Remuzzi",
+        "author_inst": "University of Bergamo"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2020.06.01.20119271",
@@ -1361694,53 +1364519,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.30.20117853",
-    "rel_title": "Evaluating the Efficacy of Stay-At-Home Orders: Does Timing Matter?",
+    "rel_doi": "10.1101/2020.05.31.20118315",
+    "rel_title": "Cytokine biomarkers of COVID-19",
     "rel_date": "2020-06-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.30.20117853",
-    "rel_abs": "BACKGROUNDThe many economic, psychological, and social consequences of pandemics and social distancing measures create an urgent need to determine the efficacy of non-pharmaceutical interventions (NPIs), and especially those considered most stringent, such as stay-at-home and self-isolation mandates. This study focuses specifically on the efficacy of stay-at-home orders, both nationally and internationally, in the control of COVID-19.\n\nMETHODSWe conducted an observational analysis from April to May 2020 and included countries and US states with known stay-at-home orders. Our primary exposure was the time between the date of the first reported case of COVID-19 to an implemented stay-at-home mandate for each region. Our primary outcomes were the time from the first reported case to the highest number of daily cases and daily deaths. We conducted simple linear regression analyses, controlling for the case rate of the outbreak.\n\nRESULTSFor US states and countries, a larger number of days between the first reported case and stay-at-home mandates was associated with a longer time to reach the peak daily case and death counts. The largest effect was among regions classified as the latest 10% to implement a mandate, which in the US, predicted an extra 35.3 days to the peak number of cases (95 % CI: 18.2, 52.5), and 38.3 days to the peak number of deaths (95 % CI: 23.6, 53.0).\n\nCONCLUSIONSOur study supports the potential beneficial effect of earlier stay-at-home mandates, by shortening the time to peak case and death counts for US states and countries. Regions in which mandates were implemented late experienced a prolonged duration to reaching both peak daily case and death counts.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118315",
+    "rel_abs": "We used a new strategy to screen cytokines associated with SARS-CoV-2 infection. Cytokines that can classify populations in different states of SARS-CoV-2 infection were first screened in cross-sectional serum samples from 184 subjects by 2 statistical analyses. The resultant cytokines were then analyzed for their interrelationships and fluctuating features in sequential samples from 38 COVID-19 patients. Three cytokines, M-CSF, IL-8 and SCF, which were clustered into 3 different correlation groups and had relatively small fluctuations during SARS-CoV-2 infection, were selected for the construction of a multiclass classification model. This model discriminated healthy individuals and asymptomatic and nonsevere patients with accuracy of 77.4% but was not successful in classifying severe patients. Further searching led to a single cytokine, hepatocyte growth factor (HGF), which classified severe from nonsevere COVID-19 patients with a sensitivity of 84.6% and a specificity of 97.9% under a cutoff value of 1128 pg/ml. The level of this cytokine did not increase in nonsevere patients but was significantly elevated in severe patients. Considering its potent antiinflammatory function, we suggest that HGF might be a new candidate therapy for critical COVID-19. In addition, our new strategy provides not only a rational and effective way to focus on certain cytokine biomarkers for infectious diseases but also a new opportunity to probe the modulation of cytokines in the immune response.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Alexandra Medline, MPH",
-        "author_inst": "Emory University School of Medicine"
+        "author_name": "Hai-Jun Deng",
+        "author_inst": "Key Laboratory of Molecular Biology on Infectious Diseases, Ministry of Education, Chongqing Medical University, Chongqing, China"
       },
       {
-        "author_name": "Lamar Hayes, MPH",
-        "author_inst": "David Geffen School of Medicine"
+        "author_name": "Quan-Xin Long",
+        "author_inst": "Key Laboratory of Molecular Biology on Infectious Diseases, Ministry of Education, Chongqing Medical University, Chongqing, China"
       },
       {
-        "author_name": "Farnoosh Vahedi",
-        "author_inst": "David Geffen School of Medicine"
+        "author_name": "Bei-Zhong Liu",
+        "author_inst": "Yongchuan Hospital Affiliated to Chongqing Medical University, Chongqing, China"
       },
       {
-        "author_name": "Katia Valdez",
-        "author_inst": "Fielding School of Public Health, University of California Los Angeles"
+        "author_name": "Ji-Hua Ren",
+        "author_inst": "Key Laboratory of Molecular Biology on Infectious Diseases, Ministry of Education, Chongqing Medical University, Chongqing, China"
       },
       {
-        "author_name": "Jake Sonnenberg",
-        "author_inst": "Stanford University School of Medicine"
+        "author_name": "Pu Liao",
+        "author_inst": "Laboratory department, Chongqing People Hospital, Chongqing, China"
       },
       {
-        "author_name": "Will Capell",
-        "author_inst": "David Geffen School of Medicine"
+        "author_name": "Jing-Fu Qiu",
+        "author_inst": "School of Public Health and Management, Chongqing Medical University, Chongqing, China"
       },
       {
-        "author_name": "Ami Hayashi",
-        "author_inst": "David Geffen School of Medicine"
+        "author_name": "Xiao-Jun Tang",
+        "author_inst": "School of Public Health and Management, Chongqing Medical University, Chongqing, China"
       },
       {
-        "author_name": "Zoe Glick",
-        "author_inst": "UC Berkeley"
+        "author_name": "Yong Zhang",
+        "author_inst": "School of Public Health and Management, Chongqing Medical University, Chongqing, China"
+      },
+      {
+        "author_name": "Ni Tang",
+        "author_inst": "Key Laboratory of Molecular Biology on Infectious Diseases, Ministry of Education, Chongqing Medical University, Chongqing, China"
+      },
+      {
+        "author_name": "Yin-Yin Xu",
+        "author_inst": "Yongchuan Hospital Affiliated to Chongqing Medical University, Chongqing, China"
+      },
+      {
+        "author_name": "Zhan Mo",
+        "author_inst": "Yongchuan Hospital Affiliated to Chongqing Medical University, Chongqing, China"
+      },
+      {
+        "author_name": "Juan Chen",
+        "author_inst": "Key Laboratory of Molecular Biology on Infectious Diseases, Ministry of Education, Chongqing Medical University, Chongqing, China"
       },
       {
-        "author_name": "Jeffrey D. Klausner, MD, MPH",
-        "author_inst": "UCLA David Geffen School of Medicine and Fielding School of Public Health"
+        "author_name": "Jieli Hu",
+        "author_inst": "Chongqing Medical University"
+      },
+      {
+        "author_name": "Ai-Long Huang",
+        "author_inst": "The Key Laboratory of Molecular Biology of Infectious Diseases designated by the Chinese Ministry of"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1362956,35 +1365801,31 @@
     "category": "pathology"
   },
   {
-    "rel_doi": "10.1101/2020.06.03.129817",
-    "rel_title": "Closing coronavirus spike glycoproteins by structure-guided design",
+    "rel_doi": "10.1101/2020.06.02.130955",
+    "rel_title": "Sarbecovirus comparative genomics elucidates gene content of SARS-CoV-2 and functional impact of COVID-19 pandemic mutations",
     "rel_date": "2020-06-03",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.03.129817",
-    "rel_abs": "The recent spillover of SARS-CoV-2 in the human population resulted in the ongoing COVID-19 pandemic which has already caused 4.9 million infections and more than 326,000 fatalities. To initiate infection the SARS-CoV-2 spike (S) glycoprotein promotes attachment to the host cell surface, determining host and tissue tropism, and fusion of the viral and host membranes. Although SARS-CoV- 2 S is the main target of neutralizing antibodies and the focus of vaccine design, its stability and conformational dynamics are limiting factors for developing countermeasures against this virus. We report here the design of a prefusion SARS-CoV-2 S ectodomain trimer construct covalently stabilized in the closed conformation. Structural and antigenicity analysis showed we successfully shut S in the closed state without otherwise altering its architecture. Finally, we show that this engineering strategy is applicable to other {beta}-coronavirus S glycoproteins and might become an important tool for vaccine design, structural biology, serology and immunology studies.",
-    "rel_num_authors": 4,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.02.130955",
+    "rel_abs": "Despite its overwhelming clinical importance, the SARS-CoV-2 gene set remains unresolved, hindering dissection of COVID-19 biology. Here, we use comparative genomics to provide a high-confidence protein-coding gene set, characterize protein-level and nucleotide-level evolutionary constraint, and prioritize functional mutations from the ongoing COVID-19 pandemic. We select 44 complete Sarbecovirus genomes at evolutionary distances ideally-suited for protein-coding and non-coding element identification, create whole-genome alignments, and quantify protein-coding evolutionary signatures and overlapping constraint. We find strong protein-coding signatures for all named genes and for 3a, 6, 7a, 7b, 8, 9b, and also ORF3c, a novel alternate-frame gene. By contrast, ORF10, and overlapping-ORFs 9c, 3b, and 3d lack protein-coding signatures or convincing experimental evidence and are not protein-coding. Furthermore, we show no other protein-coding genes remain to be discovered. Cross-strain and within-strain evolutionary pressures largely agree at the gene, amino-acid, and nucleotide levels, with some notable exceptions, including fewer-than-expected mutations in nsp3 and Spike subunit S1, and more-than-expected mutations in Nucleocapsid. The latter also shows a cluster of amino-acid-changing variants in otherwise-conserved residues in a predicted B-cell epitope, which may indicate positive selection for immune avoidance. Several Spike-protein mutations, including D614G, which has been associated with increased transmission, disrupt otherwise-perfectly-conserved amino acids, and could be novel adaptations to human hosts. The resulting high-confidence gene set and evolutionary-history annotations provide valuable resources and insights on COVID-19 biology, mutations, and evolution.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Matthew McCallum",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Alexandra C Walls",
-        "author_inst": "University of Washington"
+        "author_name": "Irwin Jungreis",
+        "author_inst": "MIT; Broad Institute of MIT and Harvard, Cambridge, MA"
       },
       {
-        "author_name": "Davide Corti",
-        "author_inst": "Humabs Biomed SA, subsidiary of Vir Biotechnology"
+        "author_name": "Rachel Sealfon",
+        "author_inst": "Center for Computational Biology, Flatiron Institute, New York, NY"
       },
       {
-        "author_name": "David Veesler",
-        "author_inst": "University of Washington"
+        "author_name": "Manolis Kellis",
+        "author_inst": "MIT"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.05.31.20107862",
@@ -1364610,27 +1367451,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.06.01.20118612",
-    "rel_title": "Modeling the Covid-19 Epidemic using Time Series Econometrics",
+    "rel_doi": "10.1101/2020.06.01.20118505",
+    "rel_title": "Pulmonary Thromboembolic Disease in Patients with COVID-19 Undergoing Computed Tomography Pulmonary Angiography (CTPA): Incidence and Relationship with Pulmonary Parenchymal Abnormalities",
     "rel_date": "2020-06-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20118612",
-    "rel_abs": "The classic  logistic model has provided a realistic model of the behavior of Covid-19 in China and many East Asian countries. Once these countries passed the peak, the daily case count fell back, mirroring its initial climb in a symmetric way, just as the classic model predicts. However, in Italy and Spain, and now the UK and many other Western countries, the experience has been very different. The daily count has fallen back gradually from the peak but remained stubbornly high. The reason for the divergence from the classical model remain unclear. We take an empirical stance on this issue and develop a model that is based upon the statistical characteristics of the time series. With the possible exception of China, the workhorse logistic model is decisively rejected against more flexible alternatives.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20118505",
+    "rel_abs": "PurposeThis study aims to report the incidence, severity and extent of pulmonary thromboembolic disease (PTD) in patients with confirmed COVID-19 who have undergone CT pulmonary angiography (CTPA) in a tertiary centre.\n\nMaterials and MethodsThis is a retrospective analysis of all patients undergoing CTPA between 23rd March 2020 and 19th April 2020 in a tertiary centre. The presence of PTD, location and involved pulmonary lobes were documented. The pattern and extent of pulmonary parenchymal abnormalities including the presence of fibrosis, lymph node enlargement and pleural effusion were evaluated by two experienced observers independently and consensus was achieved for the most disparate results. Inter-observer agreement was assessed using Kappa statistics. Student t-test, Chi square and Mann-Whitney U tests were used to compare imaging features between PTD and non-PTD sub-groups.\n\nResultsDuring the study period, 2157 patients were confirmed with COVID-19, 297/2157 (13.8%) had CT imaging, 100/2157 (4.6%) were CTPA studies, 93 studies were analysed, excluding suboptimal studies. Overall incidence of PTD was 41/93 (44%) with a third of patients showing segmental and subsegmental PTD (n = 28/93, 30%,). D-dimer was elevated in 90/93 (96.8%) of cases. High Wells score did not differentiate between PE and non-PE groups (p = 0.801). The inter-observer agreement was fair (Kappa = 0.659) for parenchymal pattern and excellent (Kappa = 0.816) for severity. Lymph node enlargement was found in 34/93 of cases (36.6%) with 29/34 (85.3%) showing no additional source of infection. Fibrosis was seen in 16/93 (17.2%) of cases, mainly demonstrating fibrotic organising pneumonia.\n\nConclusionThere is a high incidence of PTD in COVID-19 patients undergoing CTPA, complicated by lack of a valid risk stratification tool. Our data indicates a much higher suspicion of PTD is needed in severe COVID-19 patients. The concomitant presence of fibrotic features on CT indicates the need for follow-up for evaluation of chronic pulmonary complications.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Peter D. Spencer",
-        "author_inst": "University of York"
+        "author_name": "Cheng Fang",
+        "author_inst": "Kings College Hospital NHS Foundation Trust"
       },
       {
-        "author_name": "Adam Golinski",
-        "author_inst": "University of York"
+        "author_name": "Giorgio Garzillo",
+        "author_inst": "Kings College Hospital NHS Foundation Trust"
+      },
+      {
+        "author_name": "Bhavna Batohi",
+        "author_inst": "Kings College Hospital NHS Foundation Trust"
+      },
+      {
+        "author_name": "James T Teo",
+        "author_inst": "Kings College Hospital NHS Foundation Trust"
+      },
+      {
+        "author_name": "Marko Berovic",
+        "author_inst": "Kings College Hospital NHS Foundation Trust"
+      },
+      {
+        "author_name": "Paul Sidhu",
+        "author_inst": "Kings College Hospital NHS Foundation Trust"
+      },
+      {
+        "author_name": "Hasti Robbie",
+        "author_inst": "Kings College Hospital NHS Foundation Trust"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2020.06.01.20119040",
@@ -1366056,83 +1368917,55 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2020.05.29.20114751",
-    "rel_title": "Syncope at SARS-CoV-2 onset due to impaired baroreflex response",
+    "rel_doi": "10.1101/2020.05.29.20114199",
+    "rel_title": "Effect of Dry Heat and Autoclave Decontamination Cycles on N95 FFRs",
     "rel_date": "2020-06-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20114751",
-    "rel_abs": "We describe clinical and laboratory findings in 35 consecutive patients tested positive for SARS-CoV-2 by reverse transcriptase-polymerase chain reaction on nasopharyngeal swab that presented one or multiple syncopal events at disease onset. Neurological examination and electrocardiographic findings were normal. Chest computed tomography showed findings consistent with interstitial pneumonia. Arterial blood gas analysis showed low pO2, pCO2, and P/F ratio indicating hypocapnic hypoxemia, while patients did not show the expected compensatory heart rate increase. Such mechanism could have led to syncope. We speculate that SARS-CoV-2 could have caused angiotensin-converting enzyme-2 (ACE2) receptor internalization in the nucleus of the solitary tract (NTS), thus altering the baroreflex response and inhibiting the compensatory tachycardia during acute hypocapnic hypoxemia.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20114199",
+    "rel_abs": "Current shortages of Filtering Facepiece Respirators (FFRs) have created a demand for effective methods for N95 decontamination and reuse. Before implementing any reuse strategy it is important to determine what effects the proposed method has on the physical functioning of the FFR. Here we investigate the effects of two potential methods for decontamination; dry heat at 95 {degrees}C, and autoclave treatments. We test both fit and filtration efficiency for each method. For the dry heat treatment we consider the 3M 1860, 3M 1870, and 3M8210+ models. After five cycles of the dry heating method, all three FFR models pass both fit and filtration tests, showing no degradation. For the autoclave tests we consider the 3M 1870, and the 3M 8210+. We find significant degradation of the FFRs following the 121 {degrees}C autoclave cycles. The molded mask tested (3M 8210+) failed fit testing after just 1 cycle in the autoclave. The pleated (3M 1870) mask passed fit testing for 5 cycles, but failed filtration testing. The 95 {degrees}C dry heat cycle is scalable to over a thousand masks per day in a hospital setting, and is above the temperature which has been shown to achieve the requisite 3 log kill of SARS-CoV-2[1], making it a promising method for N95 decontamination and reuse.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Ciro Canetta",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
-      },
-      {
-        "author_name": "Silvia Accordino",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
-      },
-      {
-        "author_name": "Elisabetta Buscarini",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
-      },
-      {
-        "author_name": "Gianpaolo Benelli",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
-      },
-      {
-        "author_name": "Giuseppe La Piana",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
-      },
-      {
-        "author_name": "Alessandro Scartabellati",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
-      },
-      {
-        "author_name": "Giovanni Vigano'",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
-      },
-      {
-        "author_name": "Roberto Assandri",
-        "author_inst": "Ospedale Maggiore di Crema, Crema, Italy"
+        "author_name": "Cole Meisenhelder",
+        "author_inst": "Harvard University"
       },
       {
-        "author_name": "Alberto Astengo",
-        "author_inst": "Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy;"
+        "author_name": "Lo\u00efc Anderegg",
+        "author_inst": "Harvard University"
       },
       {
-        "author_name": "Chiara Benzoni",
-        "author_inst": "Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy;"
+        "author_name": "Andrew Preecha",
+        "author_inst": "Harvard University"
       },
       {
-        "author_name": "Gianfranco Gaudiano",
-        "author_inst": "Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy;"
+        "author_name": "Chiu Oan Ngooi",
+        "author_inst": "Harvard University"
       },
       {
-        "author_name": "Daniele Cazzato",
-        "author_inst": "Fondazione IRCCS Istituto Neurologico \"Carlo Besta\", Milan, Italy"
+        "author_name": "Lei Liao",
+        "author_inst": "4C Air"
       },
       {
-        "author_name": "Sebastiano Davide Rossi",
-        "author_inst": "Fondazione IRCCS Istituto Neurologico \"Carlo Besta\", Milan, Italy"
+        "author_name": "Wang Xiao",
+        "author_inst": "4C Air"
       },
       {
-        "author_name": "Susanna Usai",
-        "author_inst": "Fondazione IRCCS Istituto Neurologico \"Carlo Besta\", Milan, Italy"
+        "author_name": "Steven Chu",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Irene Tramacere",
-        "author_inst": "Fondazione IRCCS Istituto Neurologico \"Carlo Besta\", Milan, Italy"
+        "author_name": "Yi Cui",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Giuseppe Lauria",
-        "author_inst": "Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy; Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy"
+        "author_name": "John M Doyle",
+        "author_inst": "Harvard University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "neurology"
+    "category": "occupational and environmental health"
   },
   {
     "rel_doi": "10.1101/2020.05.31.20114991",
@@ -1368270,45 +1371103,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.06.01.20100461",
-    "rel_title": "Determining the optimal strategy for reopening schools, work and society in the UK: balancing earlier opening and the impact of test and trace strategies with the risk of occurrence of a secondary COVID-19 pandemic wave",
+    "rel_doi": "10.1101/2020.06.01.20118885",
+    "rel_title": "Modelling testing frequencies required for early detection of a SARS-CoV-2 outbreak on a university campus",
     "rel_date": "2020-06-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20100461",
-    "rel_abs": "BackgroundIn order to slow down the spread of SARS-CoV-2, the virus causing the COVID-19 pandemic, the UK government has imposed strict physical distancing ( lockdown) measures including school  dismissals since 23 March 2020. As evidence is emerging that these measures may have slowed the spread of the pandemic, it is important to assess the impact of any changes in strategy, including scenarios for school reopening and broader relaxation of social distancing. This work uses an individual-based model to predict the impact of a suite of possible strategies to reopen schools in the UK, including that currently proposed by the UK government.\n\nMethodsWe use Covasim, a stochastic agent-based model for transmission of COVID-19, calibrated to the UK epidemic. The model describes individuals contact networks stratified as household, school, work and community layers, and uses demographic and epidemiological data from the UK. We simulate a range of different school reopening strategies with a society-wide relaxation of lockdown measures and in the presence of different non-pharmaceutical interventions, to estimate the number of new infections, cumulative cases and deaths, as well as the effective reproduction number with different strategies. To account for uncertainties within the stochastic simulation, we also simulated different levels of infectiousness of children and young adults under 20 years old compared to older ages.\n\nFindingsWe found that with increased levels of testing of people (between 25% and 72% of symptomatic people tested at some point during an active COVID-19 infection depending on scenarios) and effective contact-tracing and isolation for infected individuals, an epidemic rebound may be prevented across all reopening scenarios, with the effective reproduction number (R) remaining below one and the cumulative number of new infections and deaths significantly lower than they would be if testing did not increase. If UK schools reopen in phases from June 2020, prevention of a second wave would require testing 51% of symptomatic infections, tracing of 40% of their contacts, and isolation of symptomatic and diagnosed cases. However, without such measures, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a secondary pandemic wave, as are other scenarios for reopening. When infectiousness of <20 year olds was varied from 100% to 50% of that of older ages, our findings remained unchanged.\n\nInterpretationTo prevent a secondary COVID-19 wave, relaxation of social distancing including reopening schools in the UK must be implemented alongside an active large-scale population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of symptomatic and diagnosed individuals. Such combined measures have a greater likelihood of controlling the transmission of SARS-CoV-2 and preventing a large number of COVID-19 deaths than reopening schools and society with the current level of implementation of testing and isolation of infected individuals.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSSince the onset of COVID-19 pandemic, mathematical modelling has been at the heart of informing decision-making, including the imposing of the lockdown in the UK. As countries are now starting to plan modification of these measures, it is important to assess the impact of different lockdown exit strategies including whether and how to reopen schools and relax other social distancing measures.\n\nAdded value of this studyUsing mathematical modelling, we explored the impact of strategies to reopen schools and society in the UK, including that currently proposed by the UK government. We assessed the impact of opening all schools fully or in a phased way with only some school years going back, with a society-wide relaxation of lockdown measures and in the presence of a different levels of implementation of test-trace-isolate strategies. We projected the number of new COVID-19 infections, cumulative cases and deaths, as well as the temporal distribution in the effective reproduction number (R) across different strategies. Our study is the first to provide quantification of the amount of testing and tracing that would be needed to prevent a second wave of COVID-19 in the UK under different reopening scenarios. To account for uncertainties within the stochastic simulation, we also simulated different levels of infectiousness of children and young adults under 20 years old compared to older ages.\n\nImplications of all the available evidenceEvidence to date points to the need for additional testing, contact tracing, and isolation of individuals who have either been diagnosed with COVID-19, or who are considered to be at high risk of carrying infection due to their contact history or symptoms. Our study supports these conclusions and provides additional quantification of the amount of testing and tracing that would be needed to prevent a second wave of COVID-19 in the UK under different lockdown exit strategies. Reopening schools and society alongside active testing of the symptomatic population (between 25% and 72% of people with symptomatic COVID-19 infection depending on scenarios) and with an effective contact-tracing and rapid isolation of symptomatic and diagnosed individuals, will not only prevent a secondary pandemic wave, but is also likely to be able to control the transmission of SARS-CoV-2, via keeping the R value below 1, thus preventing a large number of COVID-19 cases and deaths. However, in the absence of fully implemented large-scale testing, contact-tracing and isolation strategy, plans for reopening schools, including those currently proposed by the UK government, and the associated increase in work and community contacts, are likely to induce a secondary pandemic wave of COVID-19.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.01.20118885",
+    "rel_abs": "BackgroundEarly detection and risk mitigation efforts are essential for averting large outbreaks of SARS-CoV-2. Active surveillance for SARS-CoV-2 can aid in early detection of outbreaks, but the testing frequency required to identify an outbreak at its earliest stage is unknown. We assess what testing frequency is required to detect an outbreak before there are 10 detectable infections.\n\nMethodsA dynamic compartmental transmission model of SARS-CoV-2 was developed to simulate spread among a university community. After introducing a single infection into a fully susceptible population, we calculate the probability of detecting at least one case on each succeeding day with various NAT testing frequencies (daily testing achieving 25%, 50%, 75%, and 100% of the population tested per month) assuming an 85% test sensitivity. A proportion of infected individuals (varied from 1-60%) are assumed to present to health services (HS) for symptomatic testing. We ascertain the expected number of detectable infections in the community when there is a > 90% probability of detecting at least 1 case. Sensitivity analyses examine impact of transmission rates (Rt = 0 = 2, 2.5,3), presentation to HS (1%/5%/30%/60%), and pre-existing immunity (0%/10%)\n\nResultsAssuming an 85% test sensitivity, identifying an outbreak with 90% probability when the expected number of detectable infections is 9 or fewer requires NAT testing of 100% of the population per month; this result holds for all transmission rates and all levels of presentation at health services we considered. If 1% of infected people present at HS and Rt=0=3, testing 75%/50%/25% per month could identify an outbreak when the expected numbers of detectable infections are 12/17/30 respectively; these numbers decline to 9/11/12 if 30% of infected people present at HS. As proportion of infected individuals present at health services increases, the marginal impact of active surveillance is reduced. Higher transmission rates result in shorter time to detection but also rapidly escalating cases without intervention. Little differences were observed with 10% pre-existing immunity.\n\nConclusionsWidespread testing of 100% of the campus population every month is required to detect an outbreak when there are fewer than 9 detectable infections for the scenarios examined, but high presentation of symptomatic people at HS can compensate in part for lower levels of testing. Early detection is necessary, but not sufficient, to curtail disease outbreaks; the proposed testing rates would need to be accompanied by case isolation, contact tracing, quarantine, and other risk mitigation and social distancing interventions.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jasmina Panovska-Griffiths",
-        "author_inst": "UCL"
-      },
-      {
-        "author_name": "Cliff Kerr",
-        "author_inst": "Institute for Disease Modeling"
-      },
-      {
-        "author_name": "Robyn Margaret Stuart",
-        "author_inst": "University of Copenhagen"
-      },
-      {
-        "author_name": "Dina Mistry",
-        "author_inst": "Institute for Disease Modelling"
-      },
-      {
-        "author_name": "Daniel Klein",
-        "author_inst": "Institute for Disease Modelling"
+        "author_name": "Natasha Martin",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "Russell M Viner",
-        "author_inst": "UCL Great Ormond St. Institute of Child Health"
+        "author_name": "Robert T Schooley",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "Chris Bonell",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Victor De Gruttola",
+        "author_inst": "Harvard University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1369707,79 +1372524,63 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.05.31.116061",
-    "rel_title": "Origin and cross-species transmission of bat coronaviruses in China",
+    "rel_doi": "10.1101/2020.05.31.126136",
+    "rel_title": "A distinct phylogenetic cluster of Indian SARS-CoV-2 isolates",
     "rel_date": "2020-05-31",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.31.116061",
-    "rel_abs": "Bats are presumed reservoirs of diverse coronaviruses (CoVs) including progenitors of Severe Acute Respiratory Syndrome (SARS)-CoV and SARS-CoV-2, the causative agent of COVID-19. However, the evolution and diversification of these coronaviruses remains poorly understood. We used a Bayesian statistical framework and sequence data from all known bat-CoVs (including 630 novel CoV sequences) to study their macroevolution, cross-species transmission, and dispersal in China. We find that host-switching was more frequent and across more distantly related host taxa in alpha-than beta-CoVs, and more highly constrained by phylogenetic distance for beta-CoVs. We show that inter-family and -genus switching is most common in Rhinolophidae and the genus Rhinolophus. Our analyses identify the host taxa and geographic regions that define hotspots of CoV evolutionary diversity in China that could help target bat-CoV discovery for proactive zoonotic disease surveillance. Finally, we present a phylogenetic analysis suggesting a likely origin for SARS-CoV-2 in Rhinolophus spp. bats.",
-    "rel_num_authors": 15,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.31.126136",
+    "rel_abs": "From an isolated epidemic, COVID-19 has now emerged as a global pandemic. The availability of genomes in the public domain following the epidemic provides a unique opportunity to understand the evolution and spread of the SARS-CoV-2 virus across the globe. The availability of whole genomes from multiple states in India prompted us to analyse the phylogenetic clusters of genomes in India. We performed whole-genome sequencing for 64 genomes making a total of 361 genomes from India, followed by phylogenetic clustering, substitution analysis, and dating of the different phylogenetic clusters of viral genomes. We describe a distinct phylogenetic cluster (Clade I / A3i) of SARS-CoV-2 genomes from India, which encompasses 41% of all genomes sequenced and deposited in the public domain from multiple states in India. Globally 3.5% of genomes, which till date could not be mapped to any distinct known cluster fall in this newly defined clade. The cluster is characterized by a core set of shared genetic variants - C6312A (T2016K), C13730T (A88V/A97V), C23929T, and C28311T (P13L). Further, the cluster is also characterized by a nucleotide substitution rate of 1.4 x 10-3 variants per site per year, lower than the prevalent A2a cluster, and predominantly driven by variants in the E and N genes and relative sparing of the S gene. Epidemiological assessments suggest that the common ancestor emerged in the month of February 2020 and possibly resulted in an outbreak followed by countrywide spread, as evidenced by the low divergence of the genomes from across the country. To the best of our knowledge, this is the first comprehensive study characterizing the distinct and predominant cluster of SARS-CoV-2 in India.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Alice Latinne",
-        "author_inst": "EcoHealth Alliance"
-      },
-      {
-        "author_name": "Ben Hu",
-        "author_inst": "Wuhan Institute of Virology"
-      },
-      {
-        "author_name": "Kevin J Olival",
-        "author_inst": "EcoHealth Alliance"
-      },
-      {
-        "author_name": "Guangjian Zhu",
-        "author_inst": "EcoHealth Alliance"
-      },
-      {
-        "author_name": "Libiao Zhang",
-        "author_inst": "Guangdong Institute of Applied Biological Resources"
+        "author_name": "Sofia Banu",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Hongying Li",
-        "author_inst": "EcoHealth Alliance"
+        "author_name": "Bani Jolly",
+        "author_inst": "CSIR Institute of Genomics and Integrative Biology"
       },
       {
-        "author_name": "Aleksei A Chmura",
-        "author_inst": "EcoHealth Alliance"
+        "author_name": "Payel Mukherjee",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Hume E Field",
-        "author_inst": "EcoHealth Alliance"
+        "author_name": "Priya Singh",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Carlos Zambrana-Torrelio",
-        "author_inst": "EcoHealth Alliance"
+        "author_name": "Shagufta Khan",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Jonathan H Epstein",
-        "author_inst": "EcoHealth Alliance"
+        "author_name": "Lamuk Zaveri",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Bei Li",
-        "author_inst": "Wuhan Institute of Virology"
+        "author_name": "Sakshi Shambhavi",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Wei Zhang",
-        "author_inst": "Wuhan Institute of Virology"
+        "author_name": "Namami Gaur",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Lin-Fa Wang",
-        "author_inst": "Duke-NUS Graduate Medical School"
+        "author_name": "Rakesh K Mishra",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       },
       {
-        "author_name": "Zhengli Shi",
-        "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences"
+        "author_name": "Vinod Scaria",
+        "author_inst": "CSIR Institute of Genomics & Integrative Biology"
       },
       {
-        "author_name": "Peter Daszak",
-        "author_inst": "EcoHealth Alliance"
+        "author_name": "Divya Tej Sowpati",
+        "author_inst": "CSIR Centre for Cellular and Molecular Biology"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "evolutionary biology"
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.05.30.125856",
@@ -1371317,55 +1374118,95 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.05.28.20115584",
-    "rel_title": "Prognostic value of visual quantification of lesion severity at initial chest CT in confirmed Covid-19 infection: a retrospective analysis on 216 patients",
+    "rel_doi": "10.1101/2020.05.29.20116376",
+    "rel_title": "Early transmission of SARS-CoV-2 in South Africa: An epidemiological and phylogenetic report",
     "rel_date": "2020-05-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20115584",
-    "rel_abs": "Rationale and ObjectivesStudies suggest an association between chest CT findings assessed with semi-quantitative CT score and gravity of Covid-19. The objective of this work is to analyze potential correlation between visual quantification of lesion severity at initial chest CT and clinical outcome in confirmed Covid-19 patients.\n\nMaterials and MethodsFrom March 5th to March 21st, 2020, all consecutive patients that underwent chest CT for clinical suspicion of Covid-19 at a single tertiary center were retrospectively evaluated for inclusion. Patients with lung parenchyma lesions compatible with Covid-19 and positive RT-PCR were included.\n\nGlobal extensiveness of abnormal lung parenchyma was visually estimated and classified independently by 2 readers, following the European Society of Thoracic Imaging Guidelines. Death and/or mechanical ventilation within 30 days following the initial chest CT was chosen as the primary hard endpoint.\n\nResults216 patients (124 men, 62 years-old {+/-} 16.5, range 22 - 94 yo) corresponding to 216 chest CT were included. Correlation between lesion severity and percentage of patients that met the primary endpoint was high, with a coefficient {rho} of 0.87 (p = 0.05).\n\nA greater than 25% involvement was significantly associated with a higher risk of mechanical ventilation or death at 30 days, with a Risk Ratio of 5.00 (95% CI [3.59-6.99]).\n\nConclusionThis retrospective cohort confirms a correlation between visual evaluation of lesions severity at initial chest CT and the 30 days clinical outcome of Covid-19 patients and suggests using a threshold of greater than 25% involvement to identify patients at risk.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20116376",
+    "rel_abs": "BackgroundThe emergence of a novel coronavirus, SARS-CoV-2, in December 2019, progressed to become a world pandemic in a few months and reached South Africa at the beginning of March. To investigate introduction and understand the early transmission dynamics of the virus, we formed the South African Network for Genomics Surveillance of COVID (SANGS_COVID), a network of ten government and university laboratories. Here, we present the first results of this effort, which is a molecular epidemiological study of the first twenty-one SARS-CoV-2 whole genomes sampled in the first port of entry, KwaZulu-Natal (KZN), during the first month of the epidemic. By combining this with calculations of the effective reproduction number (R), we aim to shed light on the patterns of infections that define the epidemic in South Africa.\n\nMethodsR was calculated using positive cases and deaths from reports provided by the four major provinces. Molecular epidemiology investigation involved sequencing viral genomes from patients in KZN using ARCTIC protocols and assembling whole genomes using meticulous alignment methods. Phylogenetic analysis was performed using maximum likelihood (ML) and Bayesian trees, lineage classification and molecular clock calculations.\n\nFindingsThe epidemic in South Africa has been very heterogeneous. Two of the largest provinces, Gauteng, home of the two large metropolis Johannesburg and Pretoria, and KwaZulu-Natal, home of the third largest city in the country Durban, had a slow growth rate on the number of detected cases. Whereas, Western Cape, home of Cape Town, and the Eastern Cape provinces the epidemic is spreading fast. Our estimates of transmission potential for South Africa suggest a decreasing transmission potential towards R=1 since the first cases and deaths have been reported. However, between 06 May and 18 May 2020, we estimate that R was on average 1.39 (1.04-2.15, 95% CI). We also demonstrate that early transmission in KZN, and most probably in all main regions of SA, was associated with multiple international introductions and dominated by lineages B1 and B. The study also provides evidence for locally acquired infections in a hospital in Durban within the first month of the epidemic, which inflated early mortality in KZN.\n\nInterpretationThis first report of SANGS_COVID consortium focuses on understanding the epidemic heterogeneity and introduction of SARS-CoV-2 strains in the first month of the epidemic in South Africa. The early introduction of SARS-CoV-2 in KZN included caused a localized outbreak in a hospital, provides potential explanations for the initially high death rates in the province. The current high rate of transmission of COVID-19 in the Western Cape and Eastern Cape highlights the crucial need to strength local genomic surveillance in South Africa.\n\nFundingUKZN Flagship Program entitled: Afrocentric Precision Approach to Control Health Epidemic, by a research Flagship grant from the South African Medical Research Council (MRC-RFA-UFSP-01- 2013/UKZN HIVEPI, by the the Technology Innovation Agency and the the Department of Science and Innovation and by National Human Genome Re- search Institute of the National Institutes of Health under Award Number U24HG006941. H3ABioNet is an initiative of the Human Health and Heredity in Africa Consortium (H3Africa).\n\nResearch in context Evidence before this studyWe searched PubMed, BioRxiv and MedRxiv for reports on epidemiology and phylogenetic analysis using whole genome sequencing (WGS) of SARS-CoV-2. We used the following keywords: SARS-CoV-2, COVID-19, 2019-nCoV or novel coronavirus and transmission genomics, epidemiology, phylogenetic or reproduction number. Our search identified an important lack of molecular epidemiology studies in the southern hemisphere, with only a few reports from Latin America and one in Africa. In other early transmission reports on SARS-CoV-2 infections in Africa, authors focused on transmission dynamics, but molecular and phylogenetic methods were missing.\n\nAdded value of this studyWith a growing sampling bias in the study of transmission genomics of the SARS-CoV-2 pandemic, it is important for us to report high-quality whole genome sequencing (WGS) of local SARS-CoV-2 samples and in-depth phylogenetic analyses of the first month of infection in South-Africa. In our molecular epidemiological investigation, we identify the early transmission routes of the infection in the KZN and report thirteen distinct introductions from many locations and a cluster of localized transmission linked to a healthcare setting that caused most of the initial deaths in South Africa. Furthermore, we formed a national consortium in South Africa, funded by the Department of Science and Innovation and the South African Medical Research Council, to capacitate ten local laboratories to produce and analyse SARS-CoV-2 data in near real time.\n\nImplications of all the available evidenceThe COVID-19 pandemic is progressing around the world and in Africa. Early transmission genomics and dynamics of SARS-CoV-2 throw light on the early stages of the epidemic in a given region. This facilitates the investigation of localized outbreaks and serves to inform public health responses in South Africa.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Elias Taieb",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Jennifer Giandhari",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
       },
       {
-        "author_name": "Aissam Labani",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Sureshnee Pillay",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
       },
       {
-        "author_name": "Yvon Ruch",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Eduan Wilkinson",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
       },
       {
-        "author_name": "Francois Danion",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Houriiyah Tegally",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
       },
       {
-        "author_name": "Mathieu Oberlin",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Ilya Sinayskiy",
+        "author_inst": "Quantum Research Group, School of Chemistry and Physics, University of KwaZulu-Natal, Durban, South Africa"
       },
       {
-        "author_name": "Pascal Bilbault",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Maria Schuld",
+        "author_inst": "Quantum Research Group, School of Chemistry and Physics, University of KwaZulu-Natal, Durban, South Africa"
       },
       {
-        "author_name": "Pierre Leyendecker",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Jos\u00e9 Louren\u00e7o",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Catherine Roy",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Benjamin Chimukangara",
+        "author_inst": "University of KwaZulu Natal"
       },
       {
-        "author_name": "Mickael Ohana",
-        "author_inst": "Hopitaux Universitaires de Strasbourg"
+        "author_name": "Richard John Lessells",
+        "author_inst": "Infectious Diseases Department, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Yunus Moosa",
+        "author_inst": "Infectious Diseases Department, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Inbal Gazy",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
+      },
+      {
+        "author_name": "Maryam Fish",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
+      },
+      {
+        "author_name": "Lavanya Singh",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
+      },
+      {
+        "author_name": "Khulekani Sedwell Khanyile",
+        "author_inst": "KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South "
+      },
+      {
+        "author_name": "Vagner Fonseca",
+        "author_inst": "Laboratorio de Genetica Celular e Molecular, Instituto de Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil"
+      },
+      {
+        "author_name": "Marta Giovanetti",
+        "author_inst": "Fundacao Oswaldo Cruz"
+      },
+      {
+        "author_name": "Luiz Carlos Junior Alcantara",
+        "author_inst": "Instituto Oswaldo Cruz"
+      },
+      {
+        "author_name": "Francesco Petruccione",
+        "author_inst": "Quantum Research Group, School of Chemistry and Physics, University of KwaZulu-Natal, Durban, South Africa"
+      },
+      {
+        "author_name": "Tulio de Oliveira",
+        "author_inst": "University of KwaZulu-Natal"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "radiology and imaging"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.05.27.120402",
@@ -1372807,35 +1375648,31 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.05.29.20116921",
-    "rel_title": "Time courses of COVID-19 infection and local variation in socioeconomic and health disparities in England",
+    "rel_doi": "10.1101/2020.05.29.20116657",
+    "rel_title": "Loneliness during lockdown: trajectories and predictors during the COVID-19 pandemic in 35,712 adults in the UK",
     "rel_date": "2020-05-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20116921",
-    "rel_abs": "ObjectiveTo identify factors associated with local variation in the time course of COVID-19 case burden in England.\n\nMethodsWe analyzed laboratory-confirmed COVID-19 case data for 150 upper tier local authorities, from the period from January 30 to May 6, 2020, as reported by Public Health England. Using methods suitable for time-series data, we identified clusters of local authorities with distinct trajectories of daily cases, after adjusting for population size. We then tested for differences in sociodemographic, economic, and health disparity factors between these clusters.\n\nResultsTwo clusters of local authorities were identified: a higher case trajectory that rose faster over time to reach higher peak infection levels, and a lower case trajectory cluster that emerged more slowly, and had a lower peak. The higher case trajectory cluster (79 local authorities) had higher population density (p<0.001), higher proportion of Black and Asian residents (p=0.03; p=0.02), higher multiple deprivation scores (p<0.001), a lower proportions of older adults (p=0.005), and higher preventable mortality rates (p=0.03). Local authorities with higher proportions of Black residents were more likely to belong to the high case trajectory cluster, even after adjusting for population density, deprivation, proportion of older adults and preventable mortality (p=0.04).\n\nConclusionAreas belonging to the trajectory with significantly higher COVID-19 case burden were more deprived, and had higher proportions of ethnic minority residents. A higher proportion of Black residents in regions belonging to the high trajectory cluster was not fully explained by differences in population density, deprivation, and other overall health disparities between the clusters.\n\nWhat is already known on this subject?Emerging evidence suggests that the burden of COVID-19 infection is falling unequally across England, with provisional data suggesting higher overall infection and mortality rates for Black, Asian, and mixed race/ethnicity individuals.\n\nWhat does this study add?We found that regions with greater socioeconomic deprivation and poorer population health measures showed a faster rise in COVID-19 cases, and reached higher peak case levels. Areas with a higher proportion of Black residents were more likely to show this kind of time course, even after adjusting for multiple co-occurring factors, including population density. This finding merits further investigation in terms of the intersecting vulnerability factors Black and other minority ethnic individuals face in England (e.g. proportion of people working in service and caring roles, and the role of structural discrimination), and has implications for the ongoing allocation of public health resources, in order to better mitigate such inequalities.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20116657",
+    "rel_abs": "There are increasing worries that lockdowns and \"stay-at-home\" orders due to the COVID-19 pandemic could lead to a rise in loneliness, which is recognised as a major public health concern. But profiles of loneliness during the pandemic and risk factors remain unclear.\n\nData from 35,712 UK adults in the UCL COVID-19 Social Study (a panel study collecting data weekly during the pandemic) were analysed from 21/03/2020-03/05/2020. The sample was well-stratified and weighted to population proportions of gender, age, ethnicity, education and geographical location. Growth mixture modelling was used to identify the latent classes of loneliness growth trajectories and their predictors.\n\nAnalyses revealed four classes, with the baseline loneliness level ranging from low to high. In the first six weeks of lockdown, loneliness levels increased in the highest loneliness group, decreased in the lowest loneliness group, and stayed relatively constant in the middle two groups. Younger adults (OR = 2.17-6.81), women (OR = 1.59), people with low income (OR = 1.3), the economically inactive (OR = 1.3-2.04) and people with mental health conditions (OR = 5.32) were more likely to be in highest loneliness class relative to the lowest. Further, living with others or in a rural area, and having more close friends or greater social support were protective.\n\nPerceived levels of loneliness in the first few weeks of lockdown during COVID-19 were relatively stable in the UK, but for many people these levels were high with no signs of improvement. Results suggest that more efforts are needed to address loneliness, especially amongst young people.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Shelley H. Liu",
-        "author_inst": "Icahn School of Medicine at Mount SInai"
-      },
-      {
-        "author_name": "Bian Liu",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Feifei Bu",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Yan Li",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Andrew Steptoe",
+        "author_inst": "University College London"
       },
       {
-        "author_name": "Agnes Norbury",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Daisy Fancourt",
+        "author_inst": "University College London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.05.29.20116889",
@@ -1373981,33 +1376818,49 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.27.20114819",
-    "rel_title": "Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea",
+    "rel_doi": "10.1101/2020.05.27.20114728",
+    "rel_title": "Lessons from movement ecology for the return to work: modeling contacts and the spread of COVID-19",
     "rel_date": "2020-05-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114819",
-    "rel_abs": "ObjectivesElderly people had suffered disproportional burden of COVID-19. We hypothesized that males and females in different age groups might have different epidemic trajectories.\n\nMethodsUsing publicly available data from South Korea, daily new COVID-19 cases were fitted with generalized additive models, assuming Poisson and negative binomial distributions. Epidemic dynamics by age and gender groups were explored with interactions between smoothed time terms and age and gender.\n\nResultsA negative binomial distribution fitted the daily case counts best. Interaction between the dynamic patterns of daily new cases and age groups was statistically significant (p<0.001), but not with gender group. People aged 20-39 years led the epidemic processes in the society with two peaks: one major peak around March 1 and a smaller peak around April 7, 2020. The epidemic process among people aged 60 or above was trailing behind that of younger people with smaller magnitude. After March 15, there was a consistent decline of daily new cases among elderly people, despite large fluctuations of case counts among young adults.\n\nConclusionsAlthough young people drove the COVID-19 epidemic in the whole society with multiple rebounds, elderly people could still be protected from virus infection after the peak of epidemic.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114728",
+    "rel_abs": "Human behavior (movement, social contacts) plays a central role in the spread of pathogens like SARS- CoV-2. The rapid spread of SARS-CoV-2 was driven by global human movement, and initial lockdown measures aimed to localize movement and contact in order to slow spread. Thus, movement and contact patterns need to be explicitly considered when making reopening decisions, especially regarding return to work. Here, as a case study, we consider the initial stages of resuming research at a large research university, using approaches from movement ecology and contact network epidemiology. First, we develop a dynamical pathogen model describing movement between home and work; we show that limiting social contact, via reduced people or reduced time in the workplace are fairly equivalent strategies to slow pathogen spread. Second, we develop a model based on spatial contact patterns within a specific office and lab building on campus; we show that restricting on-campus activities to labs (rather than labs and offices) could dramatically alter (modularize) contact network structure and thus, potentially reduce pathogen spread by providing a workplace mechanism to reduce contact. Here we argue that explicitly accounting for human movement and contact behavior in the workplace can provide additional strategies to slow pathogen spread that can be used in conjunction with ongoing public health efforts.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Xinhua Yu",
-        "author_inst": "University of Memphis"
+        "author_name": "Allison K Shaw",
+        "author_inst": "University of Minnesota"
       },
       {
-        "author_name": "Jiasong Duan",
-        "author_inst": "University of Memphis"
+        "author_name": "Lauren A White",
+        "author_inst": "University of Maryland College Park"
       },
       {
-        "author_name": "Yu Jiang",
-        "author_inst": "University of Memphis"
+        "author_name": "Matthew Michalska-Smith",
+        "author_inst": "University of Minnesota"
       },
       {
-        "author_name": "Hongmei Zhang",
-        "author_inst": "University of Memphis"
+        "author_name": "Elizabeth T Borer",
+        "author_inst": "University of Minnesota"
+      },
+      {
+        "author_name": "Meggan E Craft",
+        "author_inst": "University of Minnesota"
+      },
+      {
+        "author_name": "Eric W Seabloom",
+        "author_inst": "University of Minnesota"
+      },
+      {
+        "author_name": "Emilie Snell-Rood",
+        "author_inst": "University of Minnesota"
+      },
+      {
+        "author_name": "Michael Travisano",
+        "author_inst": "University of Minnesota"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1375239,31 +1378092,111 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.29.20117069",
-    "rel_title": "Regression Analysis of COVID-19 Spread in India and its Different States",
+    "rel_doi": "10.1101/2020.05.28.121533",
+    "rel_title": "Structures of human antibodies bound to SARS-CoV-2 spike reveal common epitopes and recurrent features of antibodies",
     "rel_date": "2020-05-29",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20117069",
-    "rel_abs": "Linear and polynomial regression model has been used to investigate the COVID-19 outbreak in India and its different states using time series epidemiological data up to 26th May 2020. The data driven analysis shows that the case fatality rate (CFR) for India (3.14% with 95% confidence interval of 3.12% to 3.16%) is half of the global fatality rate, while higher than the CFR of the immediate neighbors i.e. Bangladesh, Pakistan and Sri Lanka. Among Indian states, CFR of West Bengal (8.70%, CI: 8.21-9.18%) and Gujrat (6.05%, CI: 4.90-7.19%) is estimated to be higher than national rate, whereas CFR of Bihar, Odisha and Tamil Nadu is less than 1%. The polynomial regression model for India and its different states is trained with data from 21st March 2020 to 19th May 2020 (60 days). The performance of the model is estimated using test data of 7 days from 20th May 2020 to 26th May 2020 by calculating RMSE and % error. The model is then used to predict number of patients in India and its different states up to 16th June 2020 (21 days). Based on the polynomial regression analysis, Maharashtra, Gujrat, Delhi and Tamil Nadu are continue to remain most affected states in India.",
-    "rel_num_authors": 3,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.28.121533",
+    "rel_abs": "Neutralizing antibody responses to coronaviruses focus on the trimeric spike, with most against the receptor-binding domain (RBD). Here we characterized polyclonal IgGs and Fabs from COVID-19 convalescent individuals for recognition of coronavirus spikes. Plasma IgGs differed in their degree of focus on RBD epitopes, recognition of SARS-CoV, MERS-CoV, and mild coronaviruses, and how avidity effects contributed to increased binding/neutralization of IgGs over Fabs. Electron microscopy reconstructions of polyclonal plasma Fab-spike complexes showed recognition of both S1A and RBD epitopes. A 3.4[A] cryo-EM structure of a neutralizing monoclonal Fab-S complex revealed an epitope that blocks ACE2 receptor-binding on \"up\" RBDs. Modeling suggested that IgGs targeting these sites have different potentials for inter-spike crosslinking on viruses and would not be greatly affected by identified SARS-CoV-2 spike mutations. These studies structurally define a recurrent anti-SARS-CoV-2 antibody class derived from VH3-53/VH3-66 and similarity to a SARS-CoV VH3-30 antibody, providing criteria for evaluating vaccine-elicited antibodies.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Poonam Chauhan",
-        "author_inst": "Central University of Punjab, Bathinda"
+        "author_name": "Christopher O Barnes",
+        "author_inst": "California Institute of Technology"
       },
       {
-        "author_name": "Ashok Kumar",
-        "author_inst": "Central University of Punjab"
+        "author_name": "Anthony P West Jr.",
+        "author_inst": "California Institute Technology"
       },
       {
-        "author_name": "Pooja Jamdagni",
-        "author_inst": "Himachal Pradesh University, Shimla"
+        "author_name": "Kathryn Huey-Tubman",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Magnus A.G. Hoffmann",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Naima G. Sharaf",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Pauline R. Hoffman",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Nicholas Koranda",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Harry B. Gristick",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Christian Gaebler",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Frauke Muecksch",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Julio C Cetrulo Lorenzi",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Shlomo Finkin",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Thomas Hagglof",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Arlene Hurley",
+        "author_inst": "California Institute of Technology"
+      },
+      {
+        "author_name": "Katrina G Millard",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Yiska Weisblum",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Fabian Schmidt",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Theodora Hatziioannou",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Paul D Bieniasz",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Marina Caskey",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Davide Robbiani",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Michel C Nussenzweig",
+        "author_inst": "Rockefeller University"
+      },
+      {
+        "author_name": "Pamela J Bjorkman",
+        "author_inst": "California Institute of Technology"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.05.28.118059",
@@ -1376713,91 +1379646,91 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.24.20101238",
-    "rel_title": "Single-cell RNA-seq and V(D)J profiling of immune cells in COVID-19 patients",
+    "rel_doi": "10.1101/2020.05.26.20111120",
+    "rel_title": "THE LOW-HARM SCORE FOR PREDICTING MORTALITY IN PATIENTS DIAGNOSED WITH COVID-19: A MULTICENTRIC VALIDATION STUDY",
     "rel_date": "2020-05-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20101238",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19) has caused over 220,000 deaths so far and is still an ongoing global health problem. However, the immunopathological changes of key types of immune cells during and after virus infection remain unclear. Here, we enriched CD3+ and CD19+ lymphocytes from peripheral blood mononuclear cells of COVID-19 patients (severe patients and recovered patients at early or late stages) and healthy people (SARS-CoV-2 negative) and revealed transcriptional profiles and changes in these lymphocytes by comprehensive single-cell transcriptome and V(D)J recombination analyses. We found that although the T lymphocytes were decreased in the blood of patients with virus infection, the remaining T cells still highly expressed inflammatory genes and persisted for a while after recovery in patients. We also observed the potential transition from effector CD8 T cells to central memory T cells in recovered patients at the late stage. Among B lymphocytes, we analyzed the expansion trajectory of a subtype of plasma cells in severe COVID-19 patients and traced the source as atypical memory B cells (AMBCs). Additional BCR and TCR analyses revealed a high level of clonal expansion in patients with severe COVID-19, especially of B lymphocytes, and the clonally expanded B cells highly expressed genes related to inflammatory responses and lymphocyte activation. V-J gene usage and clonal types of higher frequency in COVID-19 patients were also summarized. Taken together, our results provide crucial insights into the immune response against patients with severe COVID-19 and recovered patients and valuable information for the development of vaccines and therapeutic strategies.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.26.20111120",
+    "rel_abs": "- ImportanceMany COVID-19 prognostic factors for disease severity have been identified and many scores have already been proposed to predict death and other outcomes. However, hospitals in developing countries often cannot measure some of the variables that have been reported as useful.\n\n- ObjectiveTo assess the sensitivity, specificity, and predictive values of the novel LOW-HARM score (Lymphopenia, Oxygen saturation, White blood cells, Hypertension, Age, Renal injury, and Myocardial injury).\n\n- DesignThe score was designed using data from already published cohorts of patients diagnosed with COVID-19. Afterwards, it was calculated it in 438 consecutive hospital admissions at twelve different institutions in ten different cities in Mexico.\n\n- SettingTwelve hospitals in ten different cities in Mexico.\n\n- ParticipantsData from 438 patients was collected. Data from 400 patients (200 deaths and 200 survivors) was included in the analysis.\n\n- ExposureAll patients had an infection with SARS-CoV-2 confirmed by PCR.\n\n- Main OutcomeThe sensitivity, specificity, and predictive values of different cut-offs of the LOW-HARM score to predict death.\n\n- ResultsMean scores at admission and their distributions were significantly lower in patients who were discharged compared to those who died during their hospitalization 10 (SD: 17) vs 70 (SD: 28). The overall AUC of the model was 95%. A cut-off > 65 points had a specificity of 98% and a positive predictive value of 96%. More than a third of the cases (36%) in the sample had a LOW-HARM score > 65 points.\n\n- Conclusions and relevanceThe LOW-HARM score measured at admission is highly specific and useful for predicting mortality. It is easy to calculate and can be updated with individual clinical progression.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSIs it possible to predict mortality in patients diagnosed with COVID-19 using easy-to-access and easy-to-measure variables?\n\nFindingsThe LOW-HARM score (Lymphopenia, Oxygen saturation, White blood cells, Hypertension, Age, Renal injury, and Myocardial injury) is a one-hundred-point score that, when measured at admission, had an overall AUC of 95% for predicting mortality. A cut-off of [&ge;] 65 points had a specificity of 98% and a positive predictive value of 96%.\n\nMeaningThe LOW-HARM score measured at admission is highly specific and useful for predicting mortality in patients diagnosed with COVID-19. In our sample, more than a third of patients met the proposed cut-off.",
     "rel_num_authors": 18,
     "rel_authors": [
       {
-        "author_name": "Xiaoying Fan",
-        "author_inst": "Guangzhou Regenerative Medicine and Health Guangdong Laboratory"
+        "author_name": "Adrian Soto-Mota",
+        "author_inst": "The University of Oxford"
       },
       {
-        "author_name": "Xiangyang Chi",
-        "author_inst": "Beijing Institute of Biotechnology, Academy of Military Medical Sciences"
+        "author_name": "Braulio A. Marfil Garza",
+        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
       },
       {
-        "author_name": "Wenji Ma",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
+        "author_name": "Erick Martinez Rodriguez",
+        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
       },
       {
-        "author_name": "Suijuan Zhong",
-        "author_inst": "State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University"
+        "author_name": "Jose Omar Barreto Rodriguez",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias."
       },
       {
-        "author_name": "Yunzhu Dong",
-        "author_inst": "Beijing Institute of Biotechnology, Academy of Military Medical Sciences"
+        "author_name": "Alicia Estela Lopez Romo",
+        "author_inst": "Sistema de Salud Christus Muguerza"
       },
       {
-        "author_name": "Wei Zhou",
-        "author_inst": "Guangzhou Regenerative Medicine and Health Guangdong Laboratory"
+        "author_name": "Paolo Alberti Minutti",
+        "author_inst": "Centro Medico Nacional Siglo XXI"
       },
       {
-        "author_name": "Wenyu Ding",
-        "author_inst": "State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University"
+        "author_name": "Juan Vicente Alejandre Loya",
+        "author_inst": "Centro Medico Nacional Occidente"
       },
       {
-        "author_name": "Hongyan Fan",
-        "author_inst": "Department of Clinical Laboratory, The 940th Hospital of PLA Joint Logistics Support Forces"
+        "author_name": "Felix Emmanuel Perez Talavera",
+        "author_inst": "Centro Medico Nacional Occidente"
       },
       {
-        "author_name": "Chonghai Yin",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
+        "author_name": "Freddy Jose Avila-Cervera",
+        "author_inst": "Hospital Regional de Alta Especialidad de la Peninsula de Yucatan"
       },
       {
-        "author_name": "Zhentao Zuo",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
+        "author_name": "Adriana Nohemi Velazquez Burciaga",
+        "author_inst": "Universidad Anahuac"
       },
       {
-        "author_name": "Yilong Yang",
-        "author_inst": "Beijing Institute of Biotechnology, Academy of Military Medical Sciences"
+        "author_name": "Oscar Morado Aramburo",
+        "author_inst": "Hospital de la Beneficencia Espanola, San Luis Potosi."
       },
       {
-        "author_name": "Mengyao Zhang",
-        "author_inst": "Beijing Institute of Biotechnology, Academy of Military Medical Sciences"
+        "author_name": "Luis Alberto Pina Olguin",
+        "author_inst": "Hospital Regional de Alta Especialidad del Bajio"
       },
       {
-        "author_name": "Qiang Ma",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
+        "author_name": "Adrian Soto-Rodriguez",
+        "author_inst": "Universidad del Valle de Mexico"
       },
       {
-        "author_name": "Jianwei Liu",
-        "author_inst": "Guangzhou Regenerative Medicine and Health Guangdong Laboratory"
+        "author_name": "Andres Castaneda Prado",
+        "author_inst": "Centro de Investigacion en Politicas, Poblacion y Salud."
       },
       {
-        "author_name": "Ting Fang",
-        "author_inst": "Beijing Institute of Biotechnology, Academy of Military Medical Sciences"
+        "author_name": "Patricio Santillan-Doherty",
+        "author_inst": "Instituto Nacional de Enfermedades Respiratorias"
       },
       {
-        "author_name": "Qian Wu",
-        "author_inst": "State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University"
+        "author_name": "Juan O Galindo Galindo",
+        "author_inst": "Sistema de Salud Christus Muguerza"
       },
       {
-        "author_name": "Wei Chen",
-        "author_inst": "Beijing Institute of Biotechnology, Academy of Military Medical Sciences"
+        "author_name": "Daniel Hernandez Gordillo",
+        "author_inst": "Centro Medico Nacional Occidente"
       },
       {
-        "author_name": "Xiaoqun Wang",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
+        "author_name": "Juan Gutierrez Mejia",
+        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "emergency medicine"
   },
   {
     "rel_doi": "10.1101/2020.05.26.20113720",
@@ -1378211,39 +1381144,55 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2020.05.27.119610",
-    "rel_title": "Assessment of ACE2, CXCL10 and Their co-expressed Genes: An In-silico Approach to Evaluate the Susceptibility and Fatality of Lung Cancer Patients towards COVID-19 Infection",
+    "rel_doi": "10.1101/2020.05.26.20109595",
+    "rel_title": "Efficacy and harms of remdesivir for the treatment of COVID-19: a systematic review and meta-analysis",
     "rel_date": "2020-05-27",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.27.119610",
-    "rel_abs": "BackgroundCOVID-19 is a recent pandemic that started to spread out worldwide from Wuhan, China. This disease is caused by a newly discovered strain of the coronavirus, namely SARS CoV-2. Lung cancer patients are reported to be more susceptible to COVID-19 infection. To evaluate the probable reasons behind the excessive susceptibility and fatality of lung cancer patients to COVID-19 infection, we targeted two most crucial biomarkers of COVID-19, ACE2 and CXCL10. ACE2 plays a vital role in the SARS CoV-2 entry into the host cell while CXCL10 is a cytokine mainly responsible for the lung cell damage involving in a cytokine storm.\n\nMethodsFirstly, we used the TIMER, UALCAN and GEPIA2 databases to analyze the expression and correlation of ACE2 and CXCL10 in LUAD and LUSC. After that, using the cBioPortal database, we performed an analytical study to determine the genetic changes in ACE2 and CXCL10 protein sequences that are responsible for lung cancer development. Finally, we analyzed different functional approaches of ACE2, CXCL10 and their co-expressed genes associated with lung cancer and COVID-19 development by using the PANTHER database.\n\nResultsInitially, we observed that ACE2 and CXCL10 are mostly overexpressed in LUAD and LUSC. We also found the functional significance of ACE2 and CXCL10 in lung cancer development by determining the genetic alteration frequency in their amino acid sequences. Lastly, by doing the functional assessment of the targeted genes, we identified that ACE2 and CXCL10 along with their commonly co-expressed genes are respectively involved in the binding activity and immune responses in case of lung cancer and COVID-19 infection.\n\nConclusionsFinally, on the basis of this systemic analysis, we came to the conclusion that ACE2 and CXCL10 are possible biomarkers responsible for the higher susceptibility and fatality of lung cancer patients towards the COVID-19.",
-    "rel_num_authors": 5,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.26.20109595",
+    "rel_abs": "BackgroundWe evaluated the efficacy and safety of remdesivir for the treatment of COVID-19.\n\nMethodsSystematic review in five engines, pre-print webpages and RCT registries until May 22, 2020 for randomized controlled trials (RCTs) and observational studies evaluating remdesivir on confirmed, COVID-19 adults with pneumonia and/or respiratory insufficiency. Primary outcomes were all-cause mortality, clinical improvement or recovery, need for invasive ventilation, and serious adverse events (SAE). Secondary outcomes included length of hospital stay, progression of pneumonia, and adverse events (AE). Inverse variance random effects meta-analyses were performed.\n\nResultsTwo placebo-controlled RCTs (n=1300) and two case series (n=88) were included. All studies used remdesivir 200mg IV the first day and 100mg IV for 9 more days, and followed up until 28 days. Wang et al. RCT was stopped early due to AEs; ACTT-1 was preliminary reported at 15-day follow up. Time to clinical improvement was not decreased in Wang et al. RCT, but median time to recovery was decreased by 4 days in ACTT-1. Remdesivir did not decrease all-cause mortality (RR 0.71, 95%CI 0.39 to 1.28) and need for invasive ventilation at 14 days (RR 0.57, 95%CI 0.23 to 1.42), but had fewer SAEs (RR 0.77, 95%CI 0.63 to 0.94). AEs were similar between remdesivir and placebo arms. Risk of bias ranged from some concerns to high risk in RCTs.\n\nInterpretationThere is paucity of adequately powered and fully reported RCTs evaluating effects of remdesivir in adult, hospitalized COVID-19 patients. Remdesivir should not be recommended for the treatment of severe COVID-19.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Tousif Bin Mahmood",
-        "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh"
+        "author_name": "Alejandro Piscoya",
+        "author_inst": "Universidad San Ignacio de Loyola"
       },
       {
-        "author_name": "Afrin Sultana Chowdhury",
-        "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh"
+        "author_name": "Luis F. Ng-Sueng",
+        "author_inst": "Universidad Peruana de Ciencias Aplicadas"
+      },
+      {
+        "author_name": "Angela Parra del Riego",
+        "author_inst": "Universidad Peruana de Ciencias Aplicadas"
       },
       {
-        "author_name": "Mehedee Hasan",
-        "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh"
+        "author_name": "Renato Cerna-Viacava",
+        "author_inst": "Universidad Peruana de Ciencias Aplicadas"
       },
       {
-        "author_name": "Md. Mezbah-Ul-Islam Aakil",
-        "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh"
+        "author_name": "Vinay Pasupuleti",
+        "author_inst": "MedErgy Health Group Inc."
       },
       {
-        "author_name": "Mohammad Imran Hossan",
-        "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh"
+        "author_name": "Yuani M Roman",
+        "author_inst": "University of Connecticut"
+      },
+      {
+        "author_name": "Priyaleela Thota",
+        "author_inst": "Hemex Health Inc."
+      },
+      {
+        "author_name": "C. Michael White",
+        "author_inst": "University of Connecticut"
+      },
+      {
+        "author_name": "Adrian V Hernandez",
+        "author_inst": "University of Connecticut"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.05.26.20111617",
@@ -1379693,137 +1382642,17 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.26.20104497",
-    "rel_title": "Knowledge and attitude towards COVID-19 in Bangladesh: Population-level estimation and a comparison of data obtained by phone and online survey methods",
+    "rel_doi": "10.1101/2020.05.19.20106492",
+    "rel_title": "A modified SEIR Model with Confinement and Lockdown of COVID-19 for Costa Rica",
     "rel_date": "2020-05-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.26.20104497",
-    "rel_abs": "Peoples adherence to the guidelines and measures suggested in fighting the ongoing COVID-19 pandemic is partly determined by the Knowledge, Attitude, and Practices (KAP) of the population. In this cross-sectional study, we primarily addressed two key issues. First, we tried to determine whether there is a significant difference in the estimated COVID-19 knowledge level from the online and phone survey methods. Second, we tried to quantify the knowledge and attitude of COVID-19 in Bangladeshi adult population. Data were collected through phone calls (April 14-23, 2020) and online survey (April 18-19, 2020) in Bangladesh. The questionnaire had 20 knowledge questions with each correct response getting one point and incorrect/dont know response getting no point (maximum total knowledge score 20). Participants scoring >17 were categorized as having good knowledge. The percentages of good knowledge holders were 57.6%, 75.1%, and 95.8% in the phone (n=1426), online non-medical (n=1097), and online medical participants (n=382), respectively. Comparison between phone and online survey showed that, overall, online survey might overestimate knowledge level than that of phone survey, although there was no difference for elderly, poor, and rural people. Male gender, higher education, living in town/urban areas, good financial condition, and use of internet were positively associated with good knowledge. However, higher knowledge was associated with having less confidence in the final control of COVID-19. Our adult population-level estimates showed that only 32.6% (95% CI 30.1-35.2%) had good knowledge. This study provides crucial information that could be useful for the researchers and policymakers to develop effective strategies.",
-    "rel_num_authors": 31,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106492",
+    "rel_abs": "The fast moving post-modern society allows for individuals to move fast in and between different countries, making it a perfect situation for the spread of emerging diseases. COVID-19 emerged with properties of a highly contagious disease, that has spread rapidly around the world. SIR/SEIR models are generally used to explain the dynamics of epidemics, however Coronavirus has shown dynamics with constant non-pharmaceutical interventions, making it difficult to model with these simple models. We extend an SEIR model to include a confinement compartment (SEICR) and use this to explain data from COVID-19 epidemic in Costa Rica. Then we discuss possible second wave of infection by adding a time varying function in the model to simulate cyclic interventions.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Anwarul Karim",
-        "author_inst": "Department of Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong"
-      },
-      {
-        "author_name": "Mastura Akter",
-        "author_inst": "Department of Biomedical Sciences, City University of Hong Kong, Hong Kong"
-      },
-      {
-        "author_name": "AHM Thafikul Mazid",
-        "author_inst": "Department of Medicine, Dhaka Medical College and Hospital, Dhaka, Bangladesh"
-      },
-      {
-        "author_name": "Orindom Shing Pulock",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Tasmiah Tahera Aziz",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Samira Hayee",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Nowrin Tamanna",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "GS Chuwdhury",
-        "author_inst": "Department of Pathology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong"
-      },
-      {
-        "author_name": "Afsana Haque",
-        "author_inst": "Department of Urban Planning and Design, University of Hong Kong, Hong Kong"
-      },
-      {
-        "author_name": "Farhana Yeasmin",
-        "author_inst": "Department of Applied Food Science and Nutrition, Chattogram Veterinary and Animal Sciences University, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Mashkura Akter Mitu",
-        "author_inst": "Faculty of Agriculture, Hajee Mohammad Danesh Science and Technology University, Dinajpur, Bangladesh"
-      },
-      {
-        "author_name": "Farjana Yeasmin",
-        "author_inst": "Department of Zoology, Government Hazi Mohammad Mohsin College, National University, Bangladesh"
-      },
-      {
-        "author_name": "Humayun Rashid",
-        "author_inst": "Chattogram International Medical College, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Ashish Kumar Kuri",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Arni Das",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Koushik Majumder",
-        "author_inst": "Chittagong Medical College and Hospital, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Dipen Barua",
-        "author_inst": "Centre of Buddhist Studies, Faculty of Arts, University of Hong Kong, Hong Kong"
-      },
-      {
-        "author_name": "Md Mahabubur Rahaman",
-        "author_inst": "Infectious Disease Division, International Centre for Diarrhoeal Disease Research, Bangladesh"
-      },
-      {
-        "author_name": "Sanjida Akter",
-        "author_inst": "Department of Social and Preventive Medicine, Faculty of Medicine, University Malaya, Malaysia"
-      },
-      {
-        "author_name": "Nashid Niaz Munia",
-        "author_inst": "Chattogram International Medical College, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Jabin Sultana",
-        "author_inst": "Department of Physiology, Biochemistry and Pharmacology, Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram, Bangl"
-      },
-      {
-        "author_name": "Faeeqa Usaila",
-        "author_inst": "Department of Biomedical Sciences, City University of Hong Kong, Hong Kong"
-      },
-      {
-        "author_name": "Sabrina Sifat",
-        "author_inst": "Shaheed Suhrawardy Medical College and Hospital, Dhaka, Bangladesh"
-      },
-      {
-        "author_name": "Nishat Anjum Nourin",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Md Forhad Uddin",
-        "author_inst": "Independent Researcher, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Mrinmoy Bhowmik",
-        "author_inst": "Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Tanvir Ahammed",
-        "author_inst": "Department of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh"
-      },
-      {
-        "author_name": "Nabil Sharik",
-        "author_inst": "Upzila Health and Family Planning Office, Sadar, Gopalganj, Bangladesh"
-      },
-      {
-        "author_name": "Quddus Mehnaz",
-        "author_inst": "School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong"
-      },
-      {
-        "author_name": "Md Nur Hossain Bhuiyan",
-        "author_inst": "Department of Surgery, Chittagong Medical College and Hospital, Chattogram, Bangladesh"
-      },
-      {
-        "author_name": "Tahmina Banu",
-        "author_inst": "Chittagong Research Institute for Children Surgery, Chattogram, Bangladesh"
+        "author_name": "Tomas de-Camino-Beck",
+        "author_inst": "Automata Innovations"
       }
     ],
     "version": "1",
@@ -1381383,35 +1384212,43 @@
     "category": "pharmacology and therapeutics"
   },
   {
-    "rel_doi": "10.1101/2020.05.19.20107532",
-    "rel_title": "COVID-19 Datasets: A Survey and Future Challenges",
+    "rel_doi": "10.1101/2020.05.24.20107193",
+    "rel_title": "Using HoloLens\u2122 to reduce staff exposure to aerosol generating procedures during a global pandemic",
     "rel_date": "2020-05-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107532",
-    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWIn December 2019, a novel virus named COVID-19 emerged in the city of Wuhan, China. In early 2020, the COVID-19 virus spread in all continents of the world except Antarctica causing widespread infections and deaths due to its contagious characteristics and no medically proven treatment. The COVID-19 pandemic has been termed as the most consequential global crisis after the World Wars. The first line of defense against the COVID-19 spread are the non-pharmaceutical measures like social distancing and personal hygiene. The great pandemic affecting billions of lives economically and socially has motivated the scientific community to come up with solutions based on computer-aided digital technologies for diagnosis, prevention, and estimation of COVID-19. Some of these efforts focus on statistical and Artificial Intelligence-based analysis of the available data concerning COVID-19. All of these scientific efforts necessitate that the data brought to service for the analysis should be open source to promote the extension, validation, and collaboration of the work in the fight against the global pandemic. Our survey is motivated by the open source efforts that can be mainly categorized as (a) COVID-19 diagnosis from CT scans, X-ray images, and cough sounds, (b) COVID-19 case reporting, transmission estimation, and prognosis from epidemiological, demographic, and mobility data, (c) COVID-19 emotional and sentiment analysis from social media, and (d) knowledge-based discovery and semantic analysis from the collection of scholarly articles covering COVID-19. We survey and compare research works in these directions that are accompanied by open source data and code. Future research directions for data-driven COVID-19 research are also debated. We hope that the article will provide the scientific community with an initiative to start open source extensible and transparent research in the collective fight against the COVID-19 pandemic.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20107193",
+    "rel_abs": "RATIONALECOVID-19 poses a unique challenge; caring for patients with a novel, infectious disease whilst protecting staff. Some interventions used to give oxygen therapy are aerosol generating procedures. Staff delivering such interventions require PPE and are exposed to a significant viral load resulting in sick days and even death. We aim to reduce this risk using an augmented-reality communication device: The HoloLens by Microsoft.\n\nOBJECTIVESIn a tertiary centre in London we aim to implement HoloLens technology, allowing other medical staff to remotely join the consulting clinician when in a high-risk patient area delivering oxygen therapy. The study primary outcome was to reduce the exposure to staff and demonstrate non-inferiority staff satisfaction when compared to not using the device. Our secondary outcome was to reduce extrapolated PPE costs when using the device.\n\nMETHODSOur study was conducted in March and April 2020, within a respiratory unit delivering aerosolising oxygen therapies (High flow nasal oxygen, Continuous positive airway pressure and non-invasive ventilation) to patients with suspected or confirmed COVID-19 infection.\n\nMEASUREMENTSSelf-reported questionnaires to assess satisfaction in key areas of patient care. An infrared people counting device was also used to assess staff in and out of the unit.\n\nMAIN RESULTSMean self-reported time in the high-risk zone was less when using HoloLens (2.69 hours) compared to usual practice (3.96 hours) although this difference was not statistically significant (p = 0.3657). HoloLens showed non-inferiority when compared to usual practice in staff satisfaction score for all domains. Furthermore, mean staff satisfaction score encouragingly improved when using HoloLens. Self-reported PPE counts from this study showed 12 staff members changing PPE 25.8 times per shift, almost double the 13.5 times in the HoloLens count.\n\nCONCLUSIONSWe have demonstrated HoloLens can reduce the number of staff exposed to aerosol generating areas in a novel infectious disease. Our results show it did not impair communication, medical staff availability or end of life care. HoloLens technology may also reduce the use of PPE, which has equipment availability and cost benefits. This study provides grounding for further use of the HoloLens device by bringing a bedside experience to experts remote to the situation.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Junaid Shuja",
-        "author_inst": "Umm Al-Qura University"
+        "author_name": "John J Cafferkey",
+        "author_inst": "Imperial College Healthcare NHS Trust"
       },
       {
-        "author_name": "Eisa Alanazi",
-        "author_inst": "Umm Al-Qura University"
+        "author_name": "Dominic OP Hampson",
+        "author_inst": "Division of Respiratory Medicine, Imperial College Healthcare NHS Trust, London UK"
       },
       {
-        "author_name": "Waleed Alasmary",
-        "author_inst": "Umm Al-Qura University"
+        "author_name": "Clare Ross",
+        "author_inst": "Division of Respiratory Medicine, Imperial College Healthcare NHS Trust, London UK"
       },
       {
-        "author_name": "Abdulaziz Alashaikh",
-        "author_inst": "University of Jeddah"
+        "author_name": "Angad S Kooner",
+        "author_inst": "Cutrale Perioperative and Ageing Research Group, Department of Bioengineering, Imperial College London"
+      },
+      {
+        "author_name": "Guy FJ Martin",
+        "author_inst": "Department of Surgery and Cancer, Imperial College London, London UK"
+      },
+      {
+        "author_name": "James M Kinross",
+        "author_inst": "Department of Surgery and Cancer, Imperial College London, London UK"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "respiratory medicine"
   },
   {
     "rel_doi": "10.1101/2020.05.19.20107102",
@@ -1382801,29 +1385638,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.20.20107755",
-    "rel_title": "BCG vaccination and socioeconomic variables vs Covid-19 global features: clearing up a controversial issue",
+    "rel_doi": "10.1101/2020.05.25.20109470",
+    "rel_title": "Seroprevalence of antibodies against SARS-CoV-2 among public community and health-care workers in Alzintan City of Libya",
     "rel_date": "2020-05-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20107755",
-    "rel_abs": "BackgroundThe Covid-19 pandemic is characterized by extreme variability in the outcome distribution and mortality rates across different countries. Some recent studies suggested an inverse correlation with BCG vaccination at population level, while others denied this hypothesis. In order to address this controversial issue, we performed a strict epidemiological study collecting data available on a global scale, considering additional variables such as cultural-political factors and adherence to other vaccination coverages.\n\nMethodsData on 121 countries, accounting for about 99% of Covid-19 cases and deaths globally, were from Johns Hopkins Coronavirus Resource Center, World Bank, International Monetary Fund, United Nations, Human Freedom Report, and BCG Atlas. Statistical models used were Ordinary Least Squares, Tobit and Fractional Probit, implemented on Stata/MP16 software.\n\nResultsBased on our results, countries where BCG vaccination is or has been mandated in the last decades have seen a drastic reduction in Covid-19 diffusion (-80% on average) and mortality (-50% on average), even controlling for relative wealth of countries and their governmental health expenditure. A significant contribution to this reduction (respectively -50% and -13% on average) was also associated to the outbreak onset during summer, suggesting a possible influence of seasonality. Other variables turned out to be associated, though to a lesser extent.\n\nConclusionsRelying on a very large dataset and a wide array of control variables, our study confirms a strong and robust association between Covid-19 diffusion and mortality with BCG vaccination and a set socio-economic factors, opening new perspectives for clinical speculations and public health policies.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.25.20109470",
+    "rel_abs": "A study was conducted to determine the seroprevalence of antibodies against SARS-CoV-2 among public community and health care workers in Alzintan City, Libya. During the period from 2/4/2020 to 18/5/2020, a total of 219 blood samples were collected and analyzed for the presence of antibodies against SARS-CoV-2. Collection of samples were divided in two categories; random samples from public community and samples from health care workers belonging to two Governmental hospitals and one private clinic. One Step Novel Coronavirus (COVID-19) IgM/IgG Antibody Test was used. Out of the 219 samples tested, 6 (2.74%) samples were seropositive for SARS-CoV-2. All health-care workers were tested negative. All positive cases were females and 5 of them aged between 44 to 75 years and one aged 32 years. The prevalence in young females ([&le;]40 years) was 1.4% in total young females tested in the study and 1.75% in young females taken from public community. The prevalence in older females aged ([&le;] 40 years), was 11.1% in total females tested and 13.9% in females taken from public community. In conclusion, the preliminary investigation of SARS-CoV-2 revealed considerable prevalence in Alzintan City although the disease seems to be in its mild form. Active surveillance studies with high number of samples using both virological and serological tests are in urgent need.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Luigi Ventura",
-        "author_inst": "Department of Economy and Law, Sapienza University of Rome,  Rome, Italy"
+        "author_name": "ABDULWAHAB M. KAMMON",
+        "author_inst": "University of Tripoli"
       },
       {
-        "author_name": "Matteo Vitali",
-        "author_inst": "Department of Public Health and Infectious Diseases, Sapienza University of Rome, Italy"
+        "author_name": "Ali A. El-Arabi",
+        "author_inst": "Al-Zintan University"
       },
       {
-        "author_name": "Vincenzo Romano Spica",
-        "author_inst": "Department of Movement, Human and Health Sciences, University of Rome \u201cForo Italico\u201d, Rome Italy"
+        "author_name": "Esadk A. Erhouma",
+        "author_inst": "Al-Zintan University"
+      },
+      {
+        "author_name": "Taha M. Mehemed",
+        "author_inst": "Al-Zintan University"
+      },
+      {
+        "author_name": "Othman A. Mohamed",
+        "author_inst": "Al-Zintan University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1384523,75 +1387368,23 @@
     "category": "emergency medicine"
   },
   {
-    "rel_doi": "10.1101/2020.05.23.20111310",
-    "rel_title": "No evidence for allelic association between Covid-19 and ACE2 genetic variants by direct exome sequencing in 99 SARS-CoV-2 positive patients",
+    "rel_doi": "10.1101/2020.05.25.20112938",
+    "rel_title": "What Can We Learn from the Time Evolution of COVID-19 Epidemic in Slovenia?",
     "rel_date": "2020-05-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20111310",
-    "rel_abs": "BackgroundCoronaviruses (CoV) are a large family of viruses that are common in people and many animal species. Animal coronaviruses rarely infect humans with the exceptions of the Middle East Respiratory Syndrome (MERS-CoV), the Severe acute respiratory syndrome coronavirus (SARS-CoV), and now SARS-CoV-2, which is the cause of the ongoing pandemic of coronavirus disease 2019 (COVID-19). Many studies suggested that genetic variants in ACE2 gene may influence the host susceptibility/resistance to SARS-CoV-2 virus according to the functional role of ACE2 in human pathophysiology. However, all these studies have been conducted in silico based on epidemiological and population data. We therefore investigated the occurrence of ACE2 variants in a cohort of 99 Italian unrelated individuals clinically diagnosed with coronavirus disease 19 (COVID-19) to experimental demonstrate allelic association with disease severity.\n\nMethodsBy whole-exome sequencing we analysed 99 DNA samples of severely and extremely severely COVID-19 patients hospitalized at the University Hospital of Rome \"Tor Vergata\" and Bambino Gesu Hospital in Rome.\n\nResultsWe identified three different germline variants, one intronic (c.439+4G>A) and two missense (c.2158A>G, p.Asn720Asp; c.1888G>C, p.Asp630His), in 26 patients with a similar frequency between male and female and a not statistically different frequency, except for c.1888G>C, (p.Asp630His) with the ethnically matched populations (EUR).\n\nConclusionsOur results suggest that there is not any ACE2 exonic allelic association with disease severity. It is possible that rare susceptibility alleles are located in the non-coding region of the gene able to control ACE2 gene activity. It is therefore of interest, to explore the existence of ACE2 susceptibility alleles to SARS-Co-V2 in these regulatory regions. In addition, we found no significant evidence that ACE2 alleles is associated with disease severity/sex bias in the Italian population.",
-    "rel_num_authors": 14,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.25.20112938",
+    "rel_abs": "A recent work (DOI 10.1101/2020.05.06.20093310) indicated that temporarily splitting larger populations into smaller groups can efficiently mitigate the spread of SARS-CoV-2 virus. The fact that, soon afterwards, on May 15, 2020, the two million people Slovenia was the first European country proclaiming the end of COVID-19 epidemic within national borders may be relevant from this perspective. Motivated by this evolution, in this paper we investigate the time dynamics of coronavirus cases in Slovenia with emphasis on how efficient various containment measures act to diminish the number of COVID-19 infections. Noteworthily, the present analysis does not rely on any speculative theoretical assumption; it is solely based on raw epidemiological data. Out of the results presented here, the most important one is perhaps the finding that, while imposing drastic curfews and travel restrictions reduce the infection rate k by a factor of four with respect to the unrestricted state, they only improve the{kappa} -value by ~ 15% as compared to the much bearable state of social and economical life wherein (justifiable) wearing face masks and social distancing rules are enforced/followed. Significantly for behavioral and social science, our analysis of the time dependence{kappa} ={kappa} (t) may reveal an interesting self-protection instinct of the population, which became manifest even before the official lockdown enforcement.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Antonio Novelli",
-        "author_inst": "Laboratory of Medical Genetics, Bambino Ges\u00f9 Children's Hospital, IRCCS, Rome, Italy"
-      },
-      {
-        "author_name": "Michela Biancolella",
-        "author_inst": "Department of Biology, Tor Vergata University of Rome, 00133 Rome, Italy"
-      },
-      {
-        "author_name": "Paola Borgiani",
-        "author_inst": "Department of Biomedicine and Prevention, Tor Vergata University of Rome, 00133 Rome, Italy"
-      },
-      {
-        "author_name": "Dario Cocciadiferro",
-        "author_inst": "Laboratory of Medical Genetics, Bambino Ges\u00f9 Children's Hospital, IRCCS, Rome, Italy"
-      },
-      {
-        "author_name": "Vito Luigi Colona",
-        "author_inst": "Medical Genetics Laboratory, Tor Vergata Hospital, Rome, Italy"
-      },
-      {
-        "author_name": "Maria Rosaria D'Apice",
-        "author_inst": "Medical Genetics Laboratory, Tor Vergata Hospital, Rome, Italy"
-      },
-      {
-        "author_name": "Paola Rogliani",
-        "author_inst": "Unit of Respiratory Medicine, Department of Experimental Medicine, University of Rome \"Tor Vergata\", Rome, Italy"
-      },
-      {
-        "author_name": "Salvatore Zaffina",
-        "author_inst": "Occupational Medicine, Bambino Ges\u00f9 Children's Hospital, IRCCS, Rome, Italy"
-      },
-      {
-        "author_name": "Francesca Leonardis",
-        "author_inst": "Intensive Care Unit, Tor Vergata University Hospital, Rome, Italy"
-      },
-      {
-        "author_name": "Andrea Campana",
-        "author_inst": "Department of Pediatrics, IRCCS Bambino Ges\u00f9 Children's Hospital, Rome, Italy"
-      },
-      {
-        "author_name": "Massimiliano Raponi",
-        "author_inst": "Medical Directorate, IRCCS Bambino Ges\u00f9 Children's Hospital, Rome, Italy"
-      },
-      {
-        "author_name": "Massimo Andreoni",
-        "author_inst": "Infectious Diseases Clinic, Policlinico Tor Vergata, Rome, Italy"
-      },
-      {
-        "author_name": "Sandro Grelli",
-        "author_inst": "Dept. of Experimental Medicine and Biochemical Sciences, University of Rome Tor Vergata, Italy"
-      },
-      {
-        "author_name": "Giuseppe Novelli",
-        "author_inst": "Tor Vergata University"
+        "author_name": "Ioan Baldea",
+        "author_inst": "Heidelberg University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "genetic and genomic medicine"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.05.23.20111211",
@@ -1385709,51 +1388502,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.23.112284",
-    "rel_title": "SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search",
+    "rel_doi": "10.1101/2020.05.23.20111443",
+    "rel_title": "COVID-19 in Latin America: Contrasting phylodynamic inference with epidemiological surveillance.",
     "rel_date": "2020-05-26",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.23.112284",
-    "rel_abs": "The COVID-19 pandemic has sparked unprecedented mobilization of scientists, generating a deluge of papers that makes it hard for researchers to keep track and explore new directions. Search engines are designed for targeted queries, not for discovery of connections across a corpus. In this paper, we present SciSight, a system for exploratory search of COVID-19 research integrating two key capabilities: first, exploring associations between biomedical facets automatically extracted from papers (e.g., genes, drugs, diseases, patient outcomes); second, combining textual and network information to search and visualize groups of researchers and their ties. SciSight1 has so far served over 15K users with over 42K page views and 13% returns.",
-    "rel_num_authors": 8,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20111443",
+    "rel_abs": "BackgroundSARS-CoV-2 revealed important gaps in infectious disease surveillance. Molecular epidemiology can help monitoring and adapting traditional surveillance to surpass those limitations. This work aims to contrast data driven from traditional surveillance with parameters inferred from molecular epidemiology in Latin America (LATAM)\n\nMethodsWe obtained epidemiological data up to 4th June, 2020. We estimated Effective Reproductive Number (Re) and epidemic curves using maximum likelihood (ML). SARS-CoV-2 genomes were obtained from GISAID up to June 4th 2020. We aligned sequences, generated a ML phylogenetic tree, and ran a coalescent model Birth Death SIR. Phylodynamic analysis was performed for inferring Re, number of infections and date of introduction.\n\nFindingsA total of 1,144,077 cases were reported up to 4th June 2020. Countries with the largest cumulative cases were Chile, Peru and Panama. We found at least 18 different lineages circulating, with a predominance of B.1 and B.1.1. We inferred an underestimation of the daily incident cases. When contrasting observed and inferred Re, we did not find statistically significant differences except for Chile and Mexico. Temporal analysis of the introduction of SARS-CoV-2 suggested a detection lag of at least 21 days.\n\nInterpretationOur results support that epidemiological and genomic surveillance are two complementary approaches. Even with a low number of genomes proper estimations of Re could be performed. We suggest that countries, especially developing countries, should consider to add genomic surveillance to their systems for monitoring and adapting epidemiological control of SARS-CoV-2.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Tom Hope",
-        "author_inst": "Allen Institute for AI"
-      },
-      {
-        "author_name": "Jason Portenoy",
-        "author_inst": "University of Washington"
+        "author_name": "Diana M. Rojas-Gallardo",
+        "author_inst": "Fundacion Universitaria Autonoma de las Americas"
       },
       {
-        "author_name": "Kishore Vasan",
-        "author_inst": "University of Washington"
+        "author_name": "Sandra C. Garzon-Castano",
+        "author_inst": "Fundacion Universitaria Autonoma de las Americas"
       },
       {
-        "author_name": "Jonathan Borchardt",
-        "author_inst": "Allen Institute for AI"
+        "author_name": "Natalia Millan",
+        "author_inst": "Fundacion Universitaria Autonoma de las Americas"
       },
       {
-        "author_name": "Eric Horvitz",
-        "author_inst": "Microsoft Research"
+        "author_name": "Erika V. Jimenez-Posada",
+        "author_inst": "Fundacion Universitaria Autonoma de las Americas"
       },
       {
-        "author_name": "Daniel S. Weld",
-        "author_inst": "Allen Institute for AI"
+        "author_name": "Marlen Martinez-Gutierrez",
+        "author_inst": "Universidad Cooperativa de Colombia"
       },
       {
-        "author_name": "Marti A. Hearst",
-        "author_inst": "University of California, Berkeley"
+        "author_name": "Julian Ruiz-Saenz",
+        "author_inst": "Universidad Cooperativa de Colombia"
       },
       {
-        "author_name": "Jevin West",
-        "author_inst": "University of Washington"
+        "author_name": "Jaime A. Cardona-Ospina",
+        "author_inst": "Fundacion Universitaria Autonoma de las Americas"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.05.25.114199",
@@ -1387147,61 +1389936,69 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.24.20104414",
-    "rel_title": "Risk of infection and hospitalization by Covid-19 in Mexico: a case-control study",
+    "rel_doi": "10.1101/2020.05.22.20102525",
+    "rel_title": "Study on the expression levels of antibodies against SARS-CoV-2 at different period of disease and its related factors in 192 cases of COVID-19 patients",
     "rel_date": "2020-05-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.24.20104414",
-    "rel_abs": "ObjectiveDuring the onset of a novel epidemic, there are public health priorities that need to be estimated, such as risk factors for infection, hospitalization, and clinical severity to allocate resources and issue health policies. In this work we calculate the risk of infection and hospitalization by Covid-19 conferred by demographic, lifestyle, and co-morbidity factors.\n\nMaterial and methodsThis is a case-control study including the tested individuals for SARS-Cov-2 by RT-PCR officially reported by the Health Secretary of Mexico from January 01 to May 8, 2020 (102,875 subjects). Demographic (sex, age, foreign and immigrant status, native speaking, place of residence), life-style (smoking), and co-morbidities [diabetes, obesity, high blood pressure (HBP), asthma, immunosuppression, chronic obstructive pulmonary disease (COPD), cardiovascular disease other than HBP, chronic kidney disease (CKD), and other not specified diseases (other diseases)] variables were included in this study. The risk of infection and hospitalization conferred by each variable was calculated with univariate (ULR) and multivariate (MLR) logistic regression models.\n\nResultsThe place of residence (OR=4.91 living in Tijuana City), followed by advanced age (OR=6.71 in 61-70 years-old), suffering from diabetes (OR=1.87) or obesity (OR=1.61), being male (OR=1.55), having HBP (OR=1.52), and notoriously being indigenous (OR=1.49) conferred a higher risk of becoming infected by SARS-CoV-2 in Mexico. Unexpectedly, we found that having asthma (OR=0.63), immunosuppression (OR=0.65) or smoking (OR=0.85) are protective factors against infection, while suffering from COPD does not increase the risk for SARS-CoV-2 infection. In contrast, advanced age (OR=11.6 in [&ge;] 70 years-old) is the main factor for hospitalization due to Covid-19, followed by some co-morbidities, mainly diabetes (OR=3.69) and HBP (OR=2.79), being indigenous (OR=1.89), male sex (OR=1.67) and the place of residence (OR=4.22 for living in Juarez City). Unlike the protective risk against infection, immunosuppression (OR=2.69) and COPD (OR=3.63), contribute to the risk of being hospitalized, while having asthma (OR=0.7) also provides protection against hospitalization.\n\nConclusionsIn addition to confirming that older age, diabetes, HBP and obesity are the main risk of infection and hospitalization by Covid-19, we found that being indigenous, immunosuppression, smoking and asthma protect against infection, and the latter also against hospitalization.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20102525",
+    "rel_abs": "BackgroundIn 2020, the current outbreak of Coronavirus Disease 2019(COVID-19) has constituted a global pandemic. But the question about the immune mechanism of patients with COVID-19 is unclear and cause particular concern to the world. Here, we launched a follow-up analysis of antibodies against SARS-CoV-2 of 192 COVID-19 patients, aiming to depict a kinetics profile of antibodies against SARS-CoV-2 and explore the related factors of antibodies expression against SARS-CoV-2 in COVID-19 patient.\n\nMethodsA total of 192 COVID-19 patients enrolled in the designated hospital of Guangzhou, Guangzhou Eighth Peoples Hospital, from January to February 2020 were selected as the study cohort. A cohort of 130 COVID-19 suspects who had been excluded from SARS-CoV-2 infected by negative RT-PCR result and 209 healthy people were enrolled in this study. Detection of IgM and IgG against SARS-CoV-2 were performed by Chemiluminescence immunoassay in different groups.\n\nResultsIt has been found that the seroconversion time of IgM against SARS-CoV-2 in most patients was 5-10 days after the symptoms onset, and then rose rapidly, reaching a peak around 2 to 3 weeks, and the median peak concentration was 2.705 AU / mL. The peak of IgM maintained within one week, and then enters the descending channel. IgG seroconverted later than or synchronously with IgM, reaching peaks around 3 to 4 weeks.The median peak concentration was 33.998AU / ml,which was higher than that of IgM. IgM titers begins to gradually decrease after reaching the peak in the 4th week, after the 8th week, a majority of IgM in patients serum started to turn negative. On the contrary, titers of IgG began to decline slightly after the fifth week, and more than 90% of results of patients were positive after 8 weeks. Additionally, the concentration of antibodies positively correlated with the severity of the disease and the duration of virus exist in host.\n\nConclusionWe depict a kinetics profile of antibodies against SARS-CoV-2 in COVID-19 patients and found out that the levels of antibodies were related to the disease severity, age, gender and virus clearance or continuous proliferation of COVID-19 patients.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Jaime Berumen",
-        "author_inst": "Unidad de Medicina Experimental, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"
+        "author_name": "Jingyi Ou",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China"
       },
       {
-        "author_name": "Max Schmulson",
-        "author_inst": "Unidad de Medicina Experimental, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"
+        "author_name": "Mingkai Tan",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China"
       },
       {
-        "author_name": "Jesus Alegre",
-        "author_inst": "Unidad de Medicina Experimental, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"
+        "author_name": "Haolan He",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China"
       },
       {
-        "author_name": "Guadalupe Guerrero",
-        "author_inst": "Hospital General de Mexico, Dr. Eduardo Liceaga, Mexico City, Mexico"
+        "author_name": "Haiyan Tan",
+        "author_inst": "Department of Laboratory Medicine, Guangzhou Baiyun District Maternal and Child Health Hospital, Guangzhou, China"
       },
       {
-        "author_name": "Gustavo Olaiz",
-        "author_inst": "Centro de Investigacion en politicas, poblacion y salud, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"
+        "author_name": "Jiewen Mai",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
       },
       {
-        "author_name": "Rosa M. Wong-Chew",
-        "author_inst": "Division de Investigacion, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"
+        "author_name": "Yaoxiang Long",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
       },
       {
-        "author_name": "Jorge Larriva-Sahd",
-        "author_inst": "Instituto de Neurobiologia, Universidad Nacional Autonoma de Mexico, Campus Juriquilla, Queretaro Mexico"
+        "author_name": "Xiaowen Jiang",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
       },
       {
-        "author_name": "Carlos Cantu-Brito",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico."
+        "author_name": "Qing He",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
       },
       {
-        "author_name": "Ana Ochoa-Guzman",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico."
+        "author_name": "Ying Huang",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
       },
       {
-        "author_name": "Adrian Garcilazo-Avila",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico."
+        "author_name": "Yan Li",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
       },
       {
-        "author_name": "Carlos Gonzalez-Carballo",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran, Mexico City, Mexico."
+        "author_name": "Renshen Chen",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
       },
       {
-        "author_name": "Erwin Chiquete",
-        "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran."
+        "author_name": "Liya Li",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
+      },
+      {
+        "author_name": "Fang Li",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China."
+      },
+      {
+        "author_name": "Yaling Shi",
+        "author_inst": "Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou,China"
       }
     ],
     "version": "1",
@@ -1388357,25 +1391154,21 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.19.20107425",
-    "rel_title": "A Modelling Analysis of Strategies for Relaxing COVID-19 Social Distancing",
+    "rel_doi": "10.1101/2020.05.20.20107573",
+    "rel_title": "Modelling information-dependent social behaviors in response to lockdowns: the case of COVID-19 epidemic in Italy",
     "rel_date": "2020-05-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107425",
-    "rel_abs": "BackgroundThe ability of countries to contain and control COVID-19 virus transmission via social distancing is critical in the absence of a vaccine. Early activation of robust measures has been shown to control the daily infection rate, and consequential pressure on the health care system. As countries begin to control COVID-19 spread an understanding of how to ease social distancing measures to prevent a rebound in cases and deaths is required.\n\nMethodsUsing COVID-19 transmission data from the outbreak source in Hubei Province, China prior to activation of containment measures, we adapted an established individual-based simulation model of the city of Newcastle, Australia. Simulation of virus transmission in this model, with and without, social distancing measures activated permitted us to quantify social distancing effectiveness. Optimal strategies for relaxing social distancing were determined under two settings: with high numbers of daily cases, as in New York; and where early social distancing activation resulted in limited ongoing transmission, as in Perth, Australia.\n\nFindingsIn countries where strong social distancing measures were activated after the COVID-19 virus had spread widely, our study found these measures are required to be maintained for significant periods before being eased, to return to a situation where daily case numbers become low. In countries where early responses to the COVID-19 pandemic have been highly successful, as in Australia, we show that a staged relaxation of social distancing prevents a rebound in cases.\n\nInterpretationModelling studies and direct observation have shown that robust and timely social distancing have the most effect in containing the spread of the COVID-19 virus. Questions arise as to the duration of strong social distancing measures, given they are highly disruptive to society and economic activity. This study demonstrates the necessity of holding robust social distancing in place until COVID-19 virus transmission has significantly decreased, and how they may then be safely eased.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20107573",
+    "rel_abs": "The COVID-19 pandemic started in January 2020 has not only threatened world public health, but severely impacted almost every facet of lives including behavioral and psychological aspects. In this paper we focus on the  human element and propose a mathematical model to investigate the effects on the COVID-19 epidemic of social behavioral changes in response to lockdowns. We consider a SEIR-like epidemic model where that contact and quarantine rates are assumed to depend on the available information and rumors about the disease status in the community. The model is applied to the case of COVID-19 epidemic in Italy. We consider the period that stretches between Bebruary 24, 2020 when the first bulletin by the Italian Civil Brotection was reported and May 18, 2020 when the lockdown restrictions have been mostly removed. The role played by the information-related parameters is determined by evaluating how they affect suitable outbreak-severity indicators. We estimated that citizens compliance with mitigation measures played a decisive role in curbing the epidemic curve by preventing a duplication of deaths and about 46% more contagions.\n\nSubject class: 92D30, 34C60",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "George J Milne",
-        "author_inst": "University of Western Australia"
-      },
-      {
-        "author_name": "Simon Xie",
-        "author_inst": "the University of Western Australia"
+        "author_name": "Bruno Buonomo",
+        "author_inst": "University of Naples Federico II"
       },
       {
-        "author_name": "Dana Poklepovich",
-        "author_inst": "University of Western Australia"
+        "author_name": "Rossella Della Marca",
+        "author_inst": "University of Parma"
       }
     ],
     "version": "1",
@@ -1390039,35 +1392832,35 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2020.05.22.20109959",
-    "rel_title": "CLINICAL CHARACTERISTICS AND PROGNOSTIC FACTORS FOR ICU ADMISSION OF PATIENTS WITH COVID-19 USING MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING",
+    "rel_doi": "10.1101/2020.05.21.20108969",
+    "rel_title": "ASSESSMENT OF WORKERS PERSONAL VULNERABILITY TO COVID-19 USING COVID-AGE",
     "rel_date": "2020-05-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20109959",
-    "rel_abs": "There remain many unknowns regarding the onset and clinical course of the ongoing COVID-19 pandemic. We used a combination of classic epidemiological methods, natural language processing (NLP), and machine learning (for predictive modeling), to analyse the electronic health records (EHRs) of patients with COVID-19.\n\nWe explored the unstructured free text in the EHRs within the SESCAM Healthcare Network (Castilla La-Mancha, Spain) from the entire population with available EHRs (1,364,924 patients) from January 1st to March 29th, 2020. We extracted related clinical information upon diagnosis, progression and outcome for all COVID-19 cases, focusing in those requiring ICU admission.\n\nA total of 10,504 patients with a clinical or PCR-confirmed diagnosis of COVID-19 were identified, 52.5% males, with age of 58.2{+/-}19.7 years. Upon admission, the most common symptoms were cough, fever, and dyspnoea, but all in less than half of cases. Overall, 6% of hospitalized patients required ICU admission. Using a machine-learning, data-driven algorithm we identified that a combination of age, fever, and tachypnoea was the most parsimonious predictor of ICU admission: those younger than 56 years, without tachypnoea, and temperature <39{degrees}C, (or >39{degrees}C without respiratory crackles), were free of ICU admission. On the contrary, COVID-19 patients aged 40 to 79 years were likely to be admitted to the ICU if they had tachypnoea and delayed their visit to the ER after being seen in primary care.\n\nOur results show that a combination of easily obtainable clinical variables (age, fever, and tachypnoea with/without respiratory crackles) predicts which COVID-19 patients require ICU admission.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20108969",
+    "rel_abs": "Decisions on fitness for employment that entails a risk of contracting Covid-19 require an assessment of the workers personal vulnerability should infection occur. Using recently published UK data, we have developed a risk model that provides estimates of personal vulnerability to Covid-19 according to sex, age, ethnicity, and various comorbidities. Vulnerability from each risk factor is quantified in terms of its equivalence to added years of age. Addition of the impact from each risk factor to an individuals true age generates their \"Covid-age\", a summary measure representing the age of a healthy UK white male with equivalent vulnerability. We discuss important limitations of the model, including current scientific uncertainties and limitations on generalisability beyond the UK setting and its use beyond informing assessments of individual vulnerability in the workplace. As new evidence becomes available, some of these limitations can be addressed. The model does not remove the need for clinical judgement or for other important considerations when managing occupational risks from Covid-19.",
     "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Jose Luis Izquierdo",
-        "author_inst": "Hospital Universitario de Guadalajara, Guadalajara, Spain"
+        "author_name": "David Coggon",
+        "author_inst": "MRC Lifecourse Epidemiology Unit, University of Southampton, UK"
       },
       {
-        "author_name": "Julio Ancochea",
-        "author_inst": "Hospital Universitario de La Princesa, Madrid, Spain"
+        "author_name": "Peter Croft",
+        "author_inst": "Keele University, UK"
       },
       {
-        "author_name": "- Savana COVID-19 Research Group",
-        "author_inst": ""
+        "author_name": "Paul Cullinan",
+        "author_inst": "Imperial College (NHLI) and Royal Brompton Hospital, UK"
       },
       {
-        "author_name": "Joan B Soriano",
-        "author_inst": "Hospital Universitario de La Princesa"
+        "author_name": "Anthony Williams",
+        "author_inst": "Working Fit Ltd, Temple Ewell, Kent UK"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "respiratory medicine"
+    "category": "occupational and environmental health"
   },
   {
     "rel_doi": "10.1101/2020.05.22.20108845",
@@ -1391477,41 +1394270,57 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.22.20110502",
-    "rel_title": "Conditions for a second wave of COVID-19 due to interactions between disease dynamics and social processes",
+    "rel_doi": "10.1101/2020.05.22.20110551",
+    "rel_title": "Anti-SARS-CoV-2 IgG antibodies are associated with reduced viral load",
     "rel_date": "2020-05-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110502",
-    "rel_abs": "In May 2020, many jurisdictions around the world began lifting physical distancing restrictions against the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), giving rise to concerns about a possible second wave of coronavirus disease 2019 (COVID-19). These restrictions were imposed as a collective population response to the presence of COVID-19 in communities. However, lifting restrictions is also a population response to their socio-economic impacts, and is expected to increase COVID-19 cases, in turn. This suggests that the COVID-19 pandemic exemplifies a coupled behaviour-disease system. Here we develop a minimal mathematical model of the interaction between social support for school and workplace closure and the transmission dynamics of SARS-CoV-2. We find that a second wave of COVID-19 occurs across a broad range of plausible model input parameters, on account of instabilities generated by behaviour-disease interactions. We conclude that second waves of COVID-19-should they materialize-can be interpreted as the outcomes of nonlinear interactions between disease dynamics and population behaviour.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110551",
+    "rel_abs": "Anti-SARS-CoV-2 antibodies have been described, but correlation with virologic outcomes is limited. Here, we find anti-SARS-CoV-2 IgG to be associated with reduced viral load. High viral loads were rare in individuals who had seroconverted. Higher viral load on admission was associated with increased 30-day mortality (OR 4.20 [95% CI: 1.62-10.86]).",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Sansao A Pedro",
-        "author_inst": "Universidade Eduardo Mondlane, Departamento de Matematica e Informatica, Maputo, Mozambique"
+        "author_name": "Andrew Bryan",
+        "author_inst": "University of Washington School of Medicine"
+      },
+      {
+        "author_name": "Susan L Fink",
+        "author_inst": "University of Washington School of Medicine"
       },
       {
-        "author_name": "Frank T Ndjomatchoua",
-        "author_inst": "International Rice Research Institute, Sustainable Impact Platform, Geospatial Science and Modelling cluster, DAPO Box 7777-1301, Metro Manila, Philippines"
+        "author_name": "Meghan A Gattuso",
+        "author_inst": "Aquaelis"
       },
       {
-        "author_name": "Peter Jentsch",
-        "author_inst": "University of Guelph, School of Environmental Sciences, Guelph, N1G 2W1, Canada and University of Waterloo, Department of Applied Mathematics, Waterloo, N2L 3G1"
+        "author_name": "Gregory Pepper",
+        "author_inst": "University of Washington"
       },
       {
-        "author_name": "Jean M Tcheunche",
-        "author_inst": "Avenir Health, Glastonbury, CT, USA"
+        "author_name": "Anu Chaudhary",
+        "author_inst": "University of Washington School of Medicine"
       },
       {
-        "author_name": "Madhur Anand",
-        "author_inst": "University of Guelph, School of Environmental Sciences, Guelph, N1G 2W1, Canada"
+        "author_name": "Mark Wener",
+        "author_inst": "University of Washington School of Medicine"
       },
       {
-        "author_name": "Chris T Bauch",
-        "author_inst": "University of Waterloo, Department of Applied Mathematics, Waterloo, N2L 3G1, Canada"
+        "author_name": "Chihiro Morishima",
+        "author_inst": "University of Washington School of Medicine"
+      },
+      {
+        "author_name": "Keith Jerome",
+        "author_inst": "University of Washington School of Medicine"
+      },
+      {
+        "author_name": "Patrick C Mathias",
+        "author_inst": "University of Washington School of Medicine"
+      },
+      {
+        "author_name": "Alexander L Greninger",
+        "author_inst": "University of Washington"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1392855,39 +1395664,59 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.05.23.107334",
-    "rel_title": "Lung epithelial stem cells express SARS-CoV-2 entry factors: implications for COVID-19",
+    "rel_doi": "10.1101/2020.05.21.109322",
+    "rel_title": "The emergence of SARS-CoV-2 in Europe and the US",
     "rel_date": "2020-05-23",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.23.107334",
-    "rel_abs": "SARS-CoV-2 can infiltrate the lower respiratory tract, resulting in severe respiratory failure and a high death rate. Normally, the airway and alveolar epithelium can be rapidly reconstituted by multipotent stem cells after episodes of infection. Here, we analyzed published RNA-seq datasets and demonstrated that cells of four different lung epithelial stem cell types express SARS-CoV-2 entry factors, including Ace2. Thus, stem cells can be potentially infected by SARS-CoV-2, which may lead to defects in regeneration capacity partially accounting for the severity of SARS-CoV-2 infection and its consequences.",
-    "rel_num_authors": 5,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.21.109322",
+    "rel_abs": "Accurate understanding of the global spread of emerging viruses is critically important for public health response and for anticipating and preventing future outbreaks. Here, we elucidate when, where and how the earliest sustained SARS-CoV-2 transmission networks became established in Europe and the United States (US). Our results refute prior findings erroneously linking cases in January 2020 with outbreaks that occurred weeks later. Instead, rapid interventions successfully prevented onward transmission of those early cases in Germany and Washington State. Other, later introductions of the virus from China to both Italy and Washington State founded the earliest sustained European and US transmission networks. Our analyses reveal an extended period of missed opportunity when intensive testing and contact tracing could have prevented SARS-CoV-2 from becoming established in the US and Europe.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Anna A. Valyaeva",
-        "author_inst": "Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University"
+        "author_name": "Michael Worobey",
+        "author_inst": "Department of Ecology and Evolutionary Biology, University of Arizona"
       },
       {
-        "author_name": "Anastasia A. Zharikova",
-        "author_inst": "Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University"
+        "author_name": "Jonathan Pekar",
+        "author_inst": "Department of Biomedical Informatics, University of California San Diego"
       },
       {
-        "author_name": "Artem S. Kasianov",
-        "author_inst": "The Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute)"
+        "author_name": "Brendan B. Larsen",
+        "author_inst": "Department of Ecology and Evolutionary Biology, University of Arizona"
       },
       {
-        "author_name": "Yegor S. Vassetzky",
-        "author_inst": "CNRS, UMR 9018, Universite Paris-Saclay, Institut Gustave Roussy"
+        "author_name": "Martha I. Nelson",
+        "author_inst": "Fogarty International Center, National Institutes of Health"
       },
       {
-        "author_name": "Eugene V. Sheval",
-        "author_inst": "Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University"
+        "author_name": "Verity Hill",
+        "author_inst": "Institute of Evolutionary Biology, University of Edinburgh"
+      },
+      {
+        "author_name": "Jeffrey B. Joy",
+        "author_inst": "Department of Medicine, University of British Columbia"
+      },
+      {
+        "author_name": "Andrew Rambaut",
+        "author_inst": "Institute of Evolutionary Biology, University of Edinburgh"
+      },
+      {
+        "author_name": "Marc A. Suchard",
+        "author_inst": "David Geffen School of Medicine at UCLA"
+      },
+      {
+        "author_name": "Joel O. Wertheim",
+        "author_inst": "Department of Medicine, University of California San Diego"
+      },
+      {
+        "author_name": "Philippe Lemey",
+        "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Evolutionary Virology"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "cell biology"
+    "category": "genetics"
   },
   {
     "rel_doi": "10.1101/2020.05.20.106401",
@@ -1394449,45 +1397278,45 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.05.18.20105874",
-    "rel_title": "Early experiences with antibody testing in a Flemish nursing home during an acute COVID-19 outbreak: a retrospective cohort study.",
+    "rel_doi": "10.1101/2020.05.18.20104703",
+    "rel_title": "COVID-19 in China: Risk Factors and R0 Revisited",
     "rel_date": "2020-05-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20105874",
-    "rel_abs": "objectivesto assess the prevalence of COVID-19 (PCR-test) in residents and staff of a nursing home. To examine the presence of IgM and IgG antibodies in the sample and the relation between PCR and antibody test results.\n\ndesigncross-sectional and (retrospective) cohort study\n\nsettinga nursing home for the elderly Bessemerberg in Lanaken (Belgium) with up to 130 beds. Lanaken is situated in the Belgian province with the highest COVID-19 prevalence.\n\nparticipantsresidents (N=108) and staff members (N=93) of the nursing home\n\noutcomesPCR, IgM and IgG\n\nresultsthe prevalence of COVID-19, based on PCR test was 34% (N=40) for residents and 13% (N=11) for staff members, respectively. Of the residents, 13% showed positive IgM results and 15% positive IgG results. In 17% of the residents, at least one of the antibodies was positive. In total 13% of the staff members had positive IgM and 16% had a positive IgG. In 20% of the staff members at least one of these antibody tests was positive. In PCR positive residents, the percentage of IgM positive, IgG positive, and at least one of both was 28%, 34%, and 41%. In PCR positive staff, we found 30%, 60%, and 60%. Additional antibody tests were performed in nine residents between day 11 and 14 after the positive PCR test. Of those, 7 (78%) tested positive on at least one antibody. When retesting three weeks later, all remaining residents also tested positive.\n\nconclusionsRecently it was reported that in Belgium antibodies are present in 3-4% of the general population. Although, the prevalence in our residents is higher, the number is largely insufficient for herd immunity. In staff members of the regional hospital the prevalence of antibodies was 6%. The higher prevalence in nursing home staff (21%) may be related to the complete absence of good quality protection in the first weeks of the outbreak.\n\nArticle summaryO_LSTStrengths and limitations of this studyC_LST- This is the first study in Belgium examining the prevalence of COVID-19 and the presence of antibodies in residents and staff members of a nursing home\n- The internal procedural control was positive -with one exception- in all tests, which suggests good quality sampling and testing.\n- Some degree of selection bias should be assumed in residents, since some residents were absent; mostly from hospitalisation or death which can be related to the presence of COVID-related disease.\n- The study was set up in one nursing home and is consequently not representative for the whole of the Flemish community",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20104703",
+    "rel_abs": "The COVID-19 epidemic had spread rapidly through China and subsequently has proliferated globally leading to a pandemic situation around the globe. Human-to-human transmissions, as well as asymptomatic transmissions of the infection, have been confirmed. As of April 3rd public health crisis in China due to COVID-19 is potentially under control. We compiled a daily dataset of case counts, mortality, recovery, temperature, population density, and demographic information for each prefecture during the period of January 11 to April 07, 2020 (excluding Wuhan from our analysis due to missing data). Understanding the characteristics of spatiotemporal clustering of the COVID-19 epidemic and R0 is critical in effectively preventing and controlling the ongoing global pandemic. The prefectures were grouped based on several relevant features using unsupervised machine learning techniques. We performed a computational analysis utilizing the reported cases in China to estimate the revised R0 among different regions for prevention planning in an ongoing global pandemic. Finally, our results indicate that the impact of temperature and demographic (different age group percentage compared to the total population) factors on virus transmission may be characterized using a stochastic transmission model. Such predictions will help prioritize segments of a given community/region for action and provide a visual aid in designing prevention strategies for a specific geographic region. Furthermore, revised estimation and our methodology will aid in improving the human health consequences of COVID-19 elsewhere.",
     "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Frank Buntinx",
-        "author_inst": "University of Leuven, Department of Public Health and Primary Care, Leuven, Belgium"
+        "author_name": "Irtesam Mahmud Khan",
+        "author_inst": "BUET"
       },
       {
-        "author_name": "Peter Claes",
-        "author_inst": "Woonzorgcentrum Bessemerberg, Lanaken, Belgium."
+        "author_name": "Wenyi Zhang",
+        "author_inst": "Center for Disease Control and Prevention of PLA"
       },
       {
-        "author_name": "Marjo Gulikers",
-        "author_inst": "Woonzorgcentrum Bessemerberg, Lanaken, Belgium."
+        "author_name": "Sumaira Zafar",
+        "author_inst": "Asian Institute of Technology"
       },
       {
-        "author_name": "Jan Y Verbakel",
-        "author_inst": "University of Leuven, Department of Public Health and Primary Care, Leuven, Belgium"
+        "author_name": "Yong Wang",
+        "author_inst": "Center for Disease Control and Prevention of PLA"
       },
       {
-        "author_name": "Jan De Lepeleire",
-        "author_inst": "University of Leuven, Department of Public Health and Primary Care, Leuven, Belgium"
+        "author_name": "Junyu He",
+        "author_inst": "Zhejiang University"
       },
       {
-        "author_name": "Michael Van der Elst",
-        "author_inst": "University of Leuven, Department of Public Health and Primary Care, Leuven, Belgium"
+        "author_name": "Hailon Sun",
+        "author_inst": "Center for Disease Control and Prevention of PLA"
       },
       {
-        "author_name": "Marc Van Ranst",
-        "author_inst": "University of Leuven, Laboratory of Clinical and Epidemiological Virology (Rega Institute), Leuven, Belgium"
+        "author_name": "Ubydul Haque",
+        "author_inst": "University of North Texas Health Science Center"
       },
       {
-        "author_name": "Pieter Vermeersch",
-        "author_inst": "Department of cardiovascular Sciences, KU Leuven, Leuven Belgium"
+        "author_name": "M. Sohel Rahman",
+        "author_inst": "BUET"
       }
     ],
     "version": "1",
@@ -1396019,51 +1398848,39 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.05.21.109280",
-    "rel_title": "A previously uncharacterized gene in SARS-CoV-2 illuminates the functional dynamics and evolutionary origins of the COVID-19 pandemic",
+    "rel_doi": "10.1101/2020.05.21.109298",
+    "rel_title": "Recombinant SARS-CoV-2 spike proteins for sero-surveillance and epitope mapping",
     "rel_date": "2020-05-22",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.21.109280",
-    "rel_abs": "Understanding the emergence of novel viruses requires an accurate and comprehensive annotation of their genomes. Overlapping genes (OLGs) are common in viruses and have been associated with pandemics, but are still widely overlooked. We identify and characterize ORF3d, a novel OLG in SARS-CoV-2 that is also present in Guangxi pangolin-CoVs but not other closely related pangolin-CoVs or bat-CoVs. We then document evidence of ORF3d translation, characterize its protein sequence, and conduct an evolutionary analysis at three levels: between taxa (21 members of Severe acute respiratory syndrome-related coronavirus), between human hosts (3978 SARS-CoV-2 consensus sequences), and within human hosts (401 deeply sequenced SARS-CoV-2 samples). ORF3d has been independently identified and shown to elicit a strong antibody response in COVID-19 patients. However, it has been misclassified as the unrelated gene ORF3b, leading to confusion. Our results liken ORF3d to other accessory genes in emerging viruses and highlight the importance of OLGs.",
-    "rel_num_authors": 8,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.21.109298",
+    "rel_abs": "The newly emergent SARS-CoV-2 coronavirus is closely related to SARS-CoV which emerged in 2002. Studies on coronaviruses in general, and SARS in particular, have identified the virus spike protein (S) as being central to virus tropism, to the generation of a protective antibody response and to the unambiguous detection of past infections. As a result of this centrality SARS-CoV-2 S protein has a role in many aspects of research from vaccines to diagnostic tests. We describe a number of recombinant forms of SARS-CoV-2 S expressed in commonly available expression systems and their preliminary use in diagnostics and epitope mapping. These sources may find use in the current and future analysis of the virus and the Covid-19 disease it causes.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Chase W. Nelson",
-        "author_inst": "American Museum of Natural History"
-      },
-      {
-        "author_name": "Zachary Ardern",
-        "author_inst": "Chair for Microbial Ecology, Technical University of Munich, Freising, Germany"
-      },
-      {
-        "author_name": "Tony L. Goldberg",
-        "author_inst": "Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI"
-      },
-      {
-        "author_name": "Chen Meng",
-        "author_inst": "Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany"
+        "author_name": "Sophie M Jegouic",
+        "author_inst": "University of Reading"
       },
       {
-        "author_name": "Chen-Hao Kuo",
-        "author_inst": "Biodiversity Research Center, Academia Sinica, Taipei, Taiwan"
+        "author_name": "Silvia Loureiro",
+        "author_inst": "University of Reading"
       },
       {
-        "author_name": "Christina Ludwig",
-        "author_inst": "Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), Technical University of Munich, Freising, Germany"
+        "author_name": "Michelle Thom",
+        "author_inst": "The Pirbright Institute"
       },
       {
-        "author_name": "Sergios-Orestis Kolokotronis",
-        "author_inst": "Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY"
+        "author_name": "Deepa Paliwal",
+        "author_inst": "University of Reading"
       },
       {
-        "author_name": "Xinzhu Wei",
-        "author_inst": "Departments of Integrative Biology and Statistics, University of California, Berkeley, CA"
+        "author_name": "Ian M Jones",
+        "author_inst": "University of Reading"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "evolutionary biology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.05.19.20095901",
@@ -1397729,29 +1400546,41 @@
     "category": "radiology and imaging"
   },
   {
-    "rel_doi": "10.1101/2020.05.17.20104687",
-    "rel_title": "A DISSYMMETRY IN THE FIGURES RELATED TO THE COVID-19 PANDEMIC IN THE WORLD: WHAT FACTORS EXPLAIN THE DIFFERENCE BETWEEN AFRICA AND THE REST OF THE WORLD?",
+    "rel_doi": "10.1101/2020.05.20.20103200",
+    "rel_title": "The Hybrid Forecasting Method SVR-ESAR forCovid-19",
     "rel_date": "2020-05-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104687",
-    "rel_abs": "Humanity has experienced outbreaks for millennia, from epidemics limited to pandemics that have claimed many victims and changed the course of civilizations. The advent of vaccines has eradicated some of the serious pathogens and reduced many others. However, pandemics are still part of our modern world, as we continue to have pandemics as devastating as HIV and as alarming as severe acute respiratory syndrome, Ebola and the Middle East respiratory syndrome. The Covid-19 epidemic with 0-exponential contamination curves reaching 3 million confirmed cases should not have come as a surprise, nor should it have been the last pandemic in the world. In this article, we try to summarize the lost opportunities as well as the lessons learned, hoping that we can do better in the future. The objective of this study is to relate the situation of Covid-19 in African countries with those of the countries most affected by the pandemic. It also allows us to verify how, according to the observed situation, the African ecosystem seems to be much more resilient compared to that of other continents where the number of deaths is in the thousands. To verify this, the diagnosed morbidity and mortality reported for different states of the world are compared to the ages of life and the average annual temperature of these states. The results show that the less dramatic balance of the African continent compared to other continents is partly linked to the relatively high temperatures on the continent but also to the relatively young character of its population.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20103200",
+    "rel_abs": "We know that SARS-Cov2 produces the new COVID-19 disease, which is one of the most dangerous pandemics of modern times. This pandemic has critical health and economic consequences, and even the health services of the large, powerful nations may be saturated. Thus, forecasting the number of infected persons in any country is essential for controlling the situation. In the literature, different forecasting methods have been published, attempting to solve the problem. However, a simple and accurate forecasting method is required for its implementation in any part of the world. This paper presents a precise and straightforward forecasting method named SVR-ESAR (Support Vector regression hybridized with the classical Exponential smoothing and ARIMA). We applied this method to the infected time series in four scenarios, which we have taken for the Github repository: the Whole World, China, the US, and Mexico. We compared our results with those of the literature showing the proposed method has the best accuracy.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Cheikh Faye Sr.",
-        "author_inst": "Assane Seck University of Ziguinchor"
+        "author_name": "Juan Frausto-Solis",
+        "author_inst": "National Technological Institute of Mexico/IT Cd Madero"
       },
       {
-        "author_name": "CheikhTidiane Wade Sr.",
-        "author_inst": "Assane Seck University of Ziguinchor"
+        "author_name": "Jose Enrique Olvera Vazquez",
+        "author_inst": "National Technological Institute of Mexico/IT Cd Madero"
       },
       {
-        "author_name": "Ibrahima Demba Dione Sr.",
-        "author_inst": "Assane Seck University of Ziguinchor"
+        "author_name": "Juan Javier Gonzalez-Barbosa",
+        "author_inst": "National Technological Institute of Mexico/IT Cd Madero"
+      },
+      {
+        "author_name": "Guadalupe Castilla-Valdez",
+        "author_inst": "National Technological Institute of Mexico/IT Cd Madero"
+      },
+      {
+        "author_name": "Juan Paulo Sanchez-Hernandez",
+        "author_inst": "Universidad Politecnica del Estado de Morelos"
+      },
+      {
+        "author_name": "Joaquin Perez-Ortega",
+        "author_inst": "National Technological Institute of Mexico/CENIDET"
       }
     ],
     "version": "1",
-    "license": "cc0",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "health informatics"
   },
@@ -1399139,41 +1401968,93 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.17.20104968",
-    "rel_title": "Fuzzy Autocatalytic analysis of Covid-19 outbreak in Malaysia",
+    "rel_doi": "10.1101/2020.05.18.20105155",
+    "rel_title": "The Dynamic Changes of Antibodies against SARS-CoV-2 during the Infection and Recovery of COVID-19",
     "rel_date": "2020-05-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104968",
-    "rel_abs": "The objective of this research is to demonstrate a mathematical technique to analyze the Covid-19 outbreak, particularly with respect to Malaysia. The technique is able to accommodate scarcity, quantity, and availability of the data set. The obtained results can offer descriptive insight for reflecting and strategizing actions in combating the pandemic.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20105155",
+    "rel_abs": "Deciphering the dynamic changes of antibodies against SARS-CoV-2 is essential for understanding the immune response in COVID-19 patients. By comprehensively analyzing the laboratory findings of 1,850 patients, we describe the dynamic changes of the total antibody, spike protein (S)-, receptor-binding domain (RBD)-, and nucleoprotein (N)- specific IgM and IgG levels during SARS-CoV-2 infection and recovery. Our results indicate that the S-, RBD-, and N- specific IgG generation of severe/critical COVID-19 patients is one week later than mild/moderate cases, while the levels of these antibodies are 1.5-fold higher in severe/critical patients during hospitalization (P<0.01). The decrease of these IgG levels indicates the poor outcome of severe/critical patients. The RBD- and S-specific IgG levels are 2-fold higher in virus-free patients (P<0.05). Notably, we found that the patients who got re-infected had a low level of protective antibody on discharge. Therefore, our evidence proves that the dynamic changes of antibodies could provide an important reference for diagnosis, monitoring, and treatment, and shed new light on the precise management of COVID-19.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Tahir Ahmad",
-        "author_inst": "Universiti Teknologi Malaysia"
+        "author_name": "Kening Li",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
       },
       {
-        "author_name": "Azmirul Ashaari",
-        "author_inst": "Universiti Teknologi Malaysia"
+        "author_name": "Min Wu",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
       },
       {
-        "author_name": "Siti Rahmah Awang",
-        "author_inst": "Universiti Teknologi Malaysia"
+        "author_name": "Bin Huang",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
       },
       {
-        "author_name": "Siti Salwana Mamat",
-        "author_inst": "Universiti Teknologi Malaysia"
+        "author_name": "Aifang Zhong",
+        "author_inst": "Medical Technical Support Division, the 904th Hospital, Changzhou, Jiangsu 213003, China"
       },
       {
-        "author_name": "Wan Munirah Wan Mohamad",
-        "author_inst": "Universiti Teknologi Malaysia"
+        "author_name": "Lu Li",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
       },
       {
-        "author_name": "Amirul Aizad Ahmad Fuad",
-        "author_inst": "Universiti Teknologi Malaysia"
+        "author_name": "Yun Cai",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
       },
       {
-        "author_name": "Nurfarhana Hassan",
-        "author_inst": "Universiti Teknologi Malaysia"
+        "author_name": "Lingxiang Wu",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Mengyan Zhu",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Jie Li",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Ziyu Wang",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Wei Wu",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Wanlin Li",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Bakwatanisa Bosco",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Zhenhua Gan",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Zhihua Wang",
+        "author_inst": "Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China"
+      },
+      {
+        "author_name": "Qinghua Qiao",
+        "author_inst": "Medical and Technical Support Department, Pingdingshan Medical District, the 989th Hospital of Joint Logistic Support Force, Pingdingshan, Henan, 467000, China"
+      },
+      {
+        "author_name": "Jian Wu",
+        "author_inst": "COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu 210002, China"
+      },
+      {
+        "author_name": "qianghu wang",
+        "author_inst": "Nanjing medical university"
+      },
+      {
+        "author_name": "Shukui Wang",
+        "author_inst": "Department of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu 210006, China"
+      },
+      {
+        "author_name": "Xinyi Xia",
+        "author_inst": "Joint Expert Group for COVID-19, Wuhan Huoshenshan Hospital, Wuhan, Hubei 430100, China"
       }
     ],
     "version": "1",
@@ -1400645,55 +1403526,55 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.18.20103283",
-    "rel_title": "Search for asymptomatic carriers of SARS-CoV-2 in healthcare workers during the pandemic: a Spanish experience",
+    "rel_doi": "10.1101/2020.05.15.20103531",
+    "rel_title": "IL6 inhibition in critically ill COVID-19 patients is associated with increased secondary infections",
     "rel_date": "2020-05-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20103283",
-    "rel_abs": "Objectivedetermine the percentage of healthcare workers (HCW) carrying SARS-CoV-2 in high exposure areas of the hospital.\n\nDesigncross-sectional study during April 15-24th in Hospital Costa del Sol (Marbella, Spain), excluding HCW with previous COVID19.\n\nSettinghospital based, focused on patient care areas COVID19.\n\nParticipants498 subjects, 80% women. Participation was offered to all the HCW of Emergencies, Intensive Care and Anesthesia, Internal Medicine and Pneumology. Other units not directly involved in the care of these patients were offered to participate.\n\nInterventionnaso and oropharyngeal PCR determination was performed together with IgG and IgM antibody determination by immunochromatography. On the day of sampling, a health questionnaire was answered, reporting symptoms on the same day and in the previous fourteen days.\n\nMain outcome measurespercentage of HCW with positive PCR for SARS-CoV-2, percentage of HCW with positive IgG for SARS-CoV-2.\n\nResultsTwo individuals were detected with PCR for SARS-CoV-2 positive (0.4%). Both were asymptomatic on the day of sampling, but one of them had had a CoVID-19 compatible picture in the previous two weeks and had positive IgG and IgM; therefore, only one subject was truly asymptomatic carrier (0.2%). 9 workers with positive IgG (1.8%) were detected.\n\nConclusionsthe prevalence of asymptomatic carriers among health workers of the services directly involved in the care of patients with CoVID-19 was very low in our center. This type of strategy can be one more tool in controlling the pandemic.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20103531",
+    "rel_abs": "BackgroundAnti-inflammatory therapies such as IL-6 inhibition have been proposed for COVID-19 in a vacuum of evidence-based treatment. However, abrogating the inflammatory response in infectious diseases may impair a desired host response and predispose to secondary infections.\n\nMethodsWe retrospectively reviewed the medical record of critically ill COVID-19 patients during an 8-week span and compared the prevalence of secondary infection and outcomes in patients who did and did not receive tocilizumab. Additionally, we included representative histopathologic post-mortem findings from several COVID-19 cases that underwent autopsy at our institution.\n\nResults111 patients were identified, of which 54 had received tocilizumab while 57 had not. Receiving tocilizumab was associated with a higher risk of secondary bacterial (48.1% vs. 28.1%, p=0.029 and fungal (5.6% vs. 0%, p=0.112) infections. Consistent with higher number of infections, patients who received tocilizumab had higher mortality (35.2% vs. 19.3%, p=0.020). Seven cases underwent autopsy. In 3 cases who received tocilizumab, there was evidence of pneumonia on pathology. Of the 4 cases that had not been given tocilizumab, 2 showed evidence of aspiration pneumonia and 2 exhibited diffuse alveolar damage.\n\nConclusionsExperimental therapies are currently being applied to COVID-19 outside of clinical trials. Anti-inflammatory therapies such as anti-IL-6 therapy have the potential to impair viral clearance, predispose to secondary infection, and cause harm. We seek to raise physician awareness of these issues and highlight the need to better understand the immune response in COVID-19.",
     "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Julian Olalla",
-        "author_inst": "Unidad de Medicina Interna. Hospital Costa del Sol"
+        "author_name": "Lucas M Kimmig",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Ana M Correa",
-        "author_inst": "Unidad de Microbiologia. Hospital Costa del Sol."
+        "author_name": "David Wu",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Maria Dolores Martin-Escalante",
-        "author_inst": "Unidad de Medicina Interna. Hospital Costa del Sol."
+        "author_name": "Matthew Gold",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Maria Luisa Hortas",
-        "author_inst": "Area de Laboratorio. Hospital Costa del Sol."
+        "author_name": "Natasha N Pettit",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Maria Jesus Martin-Sendarrubias",
-        "author_inst": "Salud Laboral. Hospital Costa del Sol."
+        "author_name": "David Pitrak",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Victor Fuentes",
-        "author_inst": "Medicina Preventiva. Hospital Costa del Sol."
+        "author_name": "Jeffrey Mueller",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Gabriel Sena",
-        "author_inst": "Unidad de Microbiologia. Hospital Costa del Sol."
+        "author_name": "Aliya N Husain",
+        "author_inst": "University of Chicago"
       },
       {
-        "author_name": "Javier Garcia-Alegria",
-        "author_inst": "Unidad de Medicina Interna. Hospital Costa del Sol."
+        "author_name": "Ece A Mutlu",
+        "author_inst": "Rush University"
       },
       {
-        "author_name": "ROBLE Group",
-        "author_inst": ""
+        "author_name": "Gokhan M Mutlu",
+        "author_inst": "University of Chicago"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "intensive care and critical care medicine"
   },
   {
     "rel_doi": "10.1101/2020.05.16.20103853",
@@ -1401923,71 +1404804,111 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.05.19.105445",
-    "rel_title": "Clinical And Analytical Performance Of An Automated Serological Test That Identifies S1/S2 Neutralizing IgG In Covid-19 Patients Semiquantitatively.",
+    "rel_doi": "10.1101/2020.05.20.105247",
+    "rel_title": "A replication-competent vesicular stomatitis virus for studies of SARS-CoV-2 spike-mediated cell entry and its inhibition",
     "rel_date": "2020-05-20",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.19.105445",
-    "rel_abs": "BACKGROUNDIn the Covid-19 pandemic, highly selective serological testing is essential to define exposure to SARS-CoV-2 virus. Many tests have been developed, yet with variable speed to first result, and of unknown quality, particularly when considering the prediction of neutralizing capacity.\n\nOBJECTIVES/METHODSThe LIAISON(R) SARS-CoV-2 S1/S2 IgG assay was designed to measure antibodies against the SARS-CoV-2 native S1/S2 proteins in a standardized automated chemiluminescent assay. Clinical and analytical performance of the test were validated in an observational study using residual samples (>1500) with positive or negative Covid-19 diagnosis.\n\nRESULTSThe LIAISON(R) SARS-CoV-2 S1/S2 IgG assay proved highly selective and specific, and offers semiquantitative measures of serum or plasma levels of anti-S1/S2 IgG with neutralizing activity. The diagnostic sensitivity was 91.3% and 95.7% at >5 or [&ge;]15 days from diagnosis respectively, and 100% when assessed against a neutralizing assay. The specificity ranged between 97% and 98.5%. The average imprecision of the assay was <5 % coefficient of variation. Assay performance at 2 different cut-offs was evaluated to optimize predictive values in settings with different % disease prevalence. CONCLUSIONS. The automated LIAISON(R) SARS-CoV-2 S1/S2 IgG assay brings efficient, sensitive, specific, and precise serological testing to the laboratory, with the capacity to test large amounts of samples per day: first results are available within 35 minutes with a throughput of 170 tests/hour. The test also provides a semiquantitative measure to identify samples with neutralizing antibodies, useful also for a large scale screening of convalescent plasma for safe therapeutic use.\n\nIMPORTANCEWith the worldwide advance of the COVID-19 pandemic, efficient, reliable and accessible diagnostic tools are needed to support public health officials and healthcare providers in their efforts to deliver optimal medical care, and articulate sound demographic policy. DiaSorin has developed an automated serology based assay for the measurement of IgG specific to SARS CoV-2 Spike protein, and tested its clinical performance in collaboration with Italian health care professionals who provided access to large numbers of samples from infected and non-infected individuals. The assay delivers excellent sensitivity and specificity, and is able to identify samples with high levels of neutralizing antibodies. This will provide guidance in assessing the true immune status of subjects, as well as meeting the pressing need to screen donors for high titer convalescent sera for subsequent therapeutic and prophylactic use.",
-    "rel_num_authors": 13,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.20.105247",
+    "rel_abs": "There is an urgent need for vaccines and therapeutics to prevent and treat COVID-19. Rapid SARS-CoV-2 countermeasure development is contingent on the availability of robust, scalable, and readily deployable surrogate viral assays to screen antiviral humoral responses, and define correlates of immune protection, and to down-select candidate antivirals. Here, we describe a highly infectious recombinant vesicular stomatitis virus bearing the SARS-CoV-2 spike glycoprotein S as its sole entry glycoprotein that closely resembles the authentic agent in its entry-related properties. We show that the neutralizing activities of a large panel of COVID-19 convalescent sera can be assessed in high-throughput fluorescent reporter assay with rVSV-SARS-CoV-2 S and that neutralization of the rVSV and authentic SARS-CoV-2 by spike-specific antibodies in these antisera is highly correlated. Our findings underscore the utility of rVSV-SARS-CoV-2 S for the development of spike-specific vaccines and therapeutics and for mechanistic studies of viral entry and its inhibition.",
+    "rel_num_authors": 23,
     "rel_authors": [
       {
-        "author_name": "Fabrizio Bonelli",
-        "author_inst": "DiaSorin"
+        "author_name": "M Eugenia Dieterle",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Antonella Sarasini",
-        "author_inst": "Fondazione IRCCS Policlinico San Matteo"
+        "author_name": "Denise Haslwanter",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Claudia Zierold",
-        "author_inst": "DiaSorin"
+        "author_name": "Robert H Bortz III",
+        "author_inst": "Albert Einstein College Of Medicine"
       },
       {
-        "author_name": "Mariella Calleri",
-        "author_inst": "DiaSorin"
+        "author_name": "Ariel S Wirchnianski",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Alice Bonetti",
-        "author_inst": "Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo"
+        "author_name": "Gorka Lasso",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Frank A Blocki",
-        "author_inst": "DiaSorin"
+        "author_name": "Olivia Vergnolle",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Luca Pallavicini",
-        "author_inst": "DiaSorin"
+        "author_name": "Shawn A Abbasi",
+        "author_inst": "U.S. Army Medical Research Institute of Infectious Diseases"
       },
       {
-        "author_name": "Alberto Chinali",
-        "author_inst": "DiaSorin"
+        "author_name": "J Maximilian Fels",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Daniela Campisi",
-        "author_inst": "ASST Niguarda Hospital"
+        "author_name": "Ethan Laudermilch",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Elena Percivalle",
-        "author_inst": "Fondazione IRCCS Policlinico San Matteo"
+        "author_name": "Catalina Florez",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Anna Pia DiNapoli",
-        "author_inst": "Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo"
+        "author_name": "Amanda Mengotto",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Carlo Federico Perno",
-        "author_inst": "University of Milan"
+        "author_name": "Duncan Kimmel",
+        "author_inst": "Albert Einstein College of Medicine"
       },
       {
-        "author_name": "Fausto Balldanti",
-        "author_inst": "Molecular Virology Unit, Fondazione IRCCS Policlinico San Matteo"
+        "author_name": "Ryan J Malonis",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "George Georgiev",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Jose Quiroz",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Jason Barnhill",
+        "author_inst": "United States Marine Academy at West Point"
+      },
+      {
+        "author_name": "Liise-Anne Pirofski",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Johanna P Daily",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "John M Dye",
+        "author_inst": "U.S. Army Medical Research Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Jonathan R Lai",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Andrew S Herbert",
+        "author_inst": "U.S. Army Medical Research Institute of Infectious Diseases"
+      },
+      {
+        "author_name": "Kartik Chandran",
+        "author_inst": "Albert Einstein College of Medicine"
+      },
+      {
+        "author_name": "Rohit K Jangra",
+        "author_inst": "Albert Einstein College of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.05.18.103184",
@@ -1403273,49 +1406194,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.18.20101501",
-    "rel_title": "The impact of physical distancing measures against COVID-19 transmission on contacts and mixing patterns in the Netherlands: repeated cross-sectional surveys",
+    "rel_doi": "10.1101/2020.05.15.20103077",
+    "rel_title": "Mathematical Modeling and Simulation of SIR Model for COVID-2019 Epidemic Outbreak: A Case Study of India",
     "rel_date": "2020-05-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20101501",
-    "rel_abs": "BackgroundDuring the current pandemic of coronavirus (COVID-19) many countries have taken drastic measures to reduce transmission of SARS-CoV2. The measures often include physical distancing that aims to reduce the number of contacts in the population. Little is known about the actual reduction in number of contacts as a consequence of physical distancing measures.\n\nMethodsIn the Netherlands, a cross-sectional survey was carried out in 2016/2017 in which 8179 participants retrospectively reported the number, age and gender of different persons they had contacted (spoken to in person or touched) during the previous day. The survey was repeated among 2830 of the original participants, using the same questionnaire, in March and April 2020 after physical distancing measures had been implemented.\n\nResultsThe average number of contacts in the community was reduced from on average 12.5 (interquartile range: 2-17) to 3.7 (interquartile range: 0-4) different persons per participant, a reduction of 71% (95% confidence interval: 71-71). The reduction in the number of community contacts was highest for children and adolescents (between 5 and 20 years) and smallest for elderly persons of 80 years and older. The reduction in the effective number of total contacts, measured as the largest eigenvalue of the matrix with community and household contacts, was 62% (95% confidence interval: 48 - 72).\n\nConclusionThe substantial reduction in contacts has contributed greatly in halting the COVID-19 epidemic. This reduction was unevenly distributed over age groups, household sizes and occupations. These findings offer guidance for the lifting of age-group targeted measures.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.15.20103077",
+    "rel_abs": "The present study discusses the spread of COVID-2019 epidemic of India and its end by using SIR model. Here we have discussed about the spread of COVID-2019 epidemic in great detail using Euler's method. The Eulers method is a method for solving the ordinary differential equations. The SIR model has the combination of three ordinary differential equations. In this study, we have used the data of COVID-2019 Outbreak of India on 8 May, 2020. In this data, we have used 135710 susceptible cases, 54340 infectious cases and 1830 reward/removed cases for the initial level of experimental purpose. Data about a wide variety of infectious diseases has been analyzed with the help of SIR model. Therefore, this model has been already well tested for infectious diseases by various scientists and researchers. Using the data to the number of COVID-2019 outbreak cases in India the results obtained from the analysis and simulation of this proposed SIR model showing that the COVID-2019 epidemic cases increase for some time and there after this outbreak decrease. The results obtained from the SIR model also suggest that the Eulers method can be used to predict transmission and prevent the COVID-2019 epidemic in India. Finally, from this study, we have found that the outbreak of COVID-2019 epidemic in India will be at its peak on 25 May 2020 and after that it will work slowly and on the verge of ending in the first or second week of August 2020.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Jantien A. Backer",
-        "author_inst": "National Institute for Public Health and the Environment"
-      },
-      {
-        "author_name": "Liesbeth Mollema",
-        "author_inst": "National Institute for Public Health and the Environment"
-      },
-      {
-        "author_name": "Eric R. A. Vos",
-        "author_inst": "National Institute for Public Health and the Environment"
-      },
-      {
-        "author_name": "Don Klinkenberg",
-        "author_inst": "National Institute for Public Health and the Environment"
-      },
-      {
-        "author_name": "Fiona R.M. van der Klis",
-        "author_inst": "National Institute for Public Health and the Environment"
-      },
-      {
-        "author_name": "Hester E. de Melker",
-        "author_inst": "National Institute for Public Health and the Environment"
-      },
-      {
-        "author_name": "Susan van den Hof",
-        "author_inst": "National Institute for Public Health and the Environment"
-      },
-      {
-        "author_name": "Jacco Wallinga",
-        "author_inst": "National Institute for Public Health and the Environment"
+        "author_name": "Dr. Ramjeet Singh Yadav",
+        "author_inst": "Ashoka Institute of Technology and Management, Varanasi, UP, India"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1404795,29 +1407688,73 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.13.20100495",
-    "rel_title": "Risk factors for adverse clinical outcomes in patients with COVID-19: A systematic review and meta-analysis",
+    "rel_doi": "10.1101/2020.05.13.20100404",
+    "rel_title": "Clinical characteristics and early outcomes in patients with COVID-19 treated with tocilizumab at a United States academic center",
     "rel_date": "2020-05-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20100495",
-    "rel_abs": "ImportanceCOVID-19 is a clinically heterogeneous disease of varying severity and prognosis. Clinical characteristics that impact disease course could offer guidance for clinical decision making and future research endeavors and unveil disease pathways.\n\nObjectiveTo examine risk factors associated with adverse clinical outcomes in patients with COVID-19.\n\nData sourcesWe performed a systematic review in PubMed from January 1 until April 19, 2020.\n\nStudy selectionObservational studies that examined the association of any clinical characteristic with an adverse clinical outcome were considered eligible. We scrutinized studies for potential overlap.\n\nData extraction and synthesisInformation on the effect of clinical factors on clinical endpoints of patients with COVID-19 was independently extracted by two researchers. When an effect size was not reported, crude odds ratios were calculated based on the available information from the eligible articles. Study-specific effect sizes from non-overlapping studies were synthesized applying the random-effects model.\n\nMain outcome and measureThe examined outcomes were severity and progression of disease, admission to ICU, need for mechanical ventilation, mortality, or a composite outcome.\n\nResultsWe identified 88 eligible articles, and we performed a total of 256 meta-analyses on the association of 98 unique risk factors with five clinical outcomes. Seven meta-analyses presented the strongest epidemiological evidence in terms of statistical significance (P-value <0.005), between-study heterogeneity (I2 <50%), sample size (more than 1000 COVID-19 patients), 95% prediction interval excluded the null value, and absence of small-study effects. Elevated C-reactive protein (OR, 6.46; 95% CI, 4.85 - 8.60), decreased lymphocyte count (OR, 4.16; 95% CI, 3.17 - 5.45), cerebrovascular disease (OR, 2.84; 95% CI, 1.55 - 5.20), chronic obstructive pulmonary disease (OR, 4.44; 95% CI, 2.46 - 8.02), diabetes mellitus (OR, 2.04; 95% CI, 1.54 - 2.70), hemoptysis (OR, 7.03; 95% CI, 4.57 - 10.81), and male sex (OR, 1.51; 95% CI, 1.30 - 1.75) were associated with risk of severe COVID-19.\n\nConclusions and relevanceOur results highlight factors that could be useful for prognostic model building, help guide patients selection for randomized clinical trials, as well as provide alternative treatment targets by shedding light to disease pathophysiology.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20100404",
+    "rel_abs": "We describe early outcomes in 11 COVID-19 patients treated with the IL-6 receptor inhibitor tocilizumab. While C-reactive protein decreased, neither clinical improvement nor reduced temperature or oxygen requirements was observed in most patients. Our findings contrast with prior reports and raise questions about tocilizumab use in severe COVID-19.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Vanesa Bellou",
-        "author_inst": "University of Ioannina Medical School"
+        "author_name": "Casey Allison Rimland",
+        "author_inst": "Medical Scientist Training Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, NC"
       },
       {
-        "author_name": "Ioanna Tzoulaki",
-        "author_inst": "University of Ioannina Medical School"
+        "author_name": "Camille E Morgan",
+        "author_inst": "Medical Scientist Training Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, NC; \tDepartment of Epidemiology, UNC Gillings School of Glob"
       },
       {
-        "author_name": "Evangelos Evangelou",
-        "author_inst": "University of Ioannina Medical School"
+        "author_name": "Griffin J Bell",
+        "author_inst": "Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Min K Kim",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, UNC School of Medicine, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Tanner Hedrick",
+        "author_inst": "Department of Pharmacy, UNC Medical Center, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Ashley Marx",
+        "author_inst": "Department of Pharmacy, UNC Medical Center, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Brian Bramson",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, UNC School of Medicine, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Heidi Swygard",
+        "author_inst": "Division of Infectious Diseases, UNC School of Medicine, Chapel Hill, NC, USA"
+      },
+      {
+        "author_name": "Sonia Napravnik",
+        "author_inst": "Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC; Division of Infectious Diseases, Department of Medicine, UNC School of"
       },
       {
-        "author_name": "Lazaros Belbasis",
-        "author_inst": "University of Ioannina Medical School"
+        "author_name": "John L Schmitz",
+        "author_inst": "Department of Pathology and Laboratory Medicine, UNC School of Medicine, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Shannon S Carson",
+        "author_inst": "Division of Pulmonary Diseases and Critical Care Medicine, Department of Medicine, UNC School of Medicine, Chapel Hill, NC"
+      },
+      {
+        "author_name": "William A Fischer",
+        "author_inst": "Division of Pulmonary Diseases and Critical Care Medicine, Department of Medicine, UNC School of Medicine, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Joseph J Eron",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, UNC School of Medicine, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Cynthia L Gay",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, UNC School of Medicine, Chapel Hill, NC"
+      },
+      {
+        "author_name": "Jonathan B Parr",
+        "author_inst": "Division of Infectious Diseases, Department of Medicine, UNC School of Medicine, Chapel Hill, NC"
       }
     ],
     "version": "1",
@@ -1405913,51 +1408850,35 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.05.14.20101824",
-    "rel_title": "Changing travel patterns in China during the early stages of the COVID-19 pandemic",
+    "rel_doi": "10.1101/2020.05.14.20101873",
+    "rel_title": "COVID Faster R-CNN: A Novel Framework to Diagnose Novel Coronavirus Disease (COVID-19) in X-Ray Images",
     "rel_date": "2020-05-19",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101824",
-    "rel_abs": "Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigated the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020 and discussed their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower access to care. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and have not yet led to structural reorganisation of the transportation network at the time of this study.\n\nOne sentence summaryUnderstanding travel before, during, and after the introduction of travel restrictions in China in response to the COVID-19 Pandemic.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101873",
+    "rel_abs": "COVID-19 or novel coronavirus disease, which has already been declared as a worldwide pandemic, at first had an outbreak in a small town of China, named Wuhan. More than two hundred countries around the world have already been affected by this severe virus as it spreads by human interaction. Moreover, the symptoms of novel coronavirus are quite similar to the general flu. Screening of infected patients is considered as a critical step in the fight against COVID-19. Therefore, it is highly relevant to recognize positive cases as early as possible to avoid further spreading of this epidemic. However, there are several methods to detect COVID-19 positive patients, which are typically performed based on respiratory samples and among them one of the critical approach which is treated as radiology imaging or X-Ray imaging. Recent findings from X-Ray imaging techniques suggest that such images contain relevant information about the SARS-CoV-2 virus. In this article, we have introduced a Deep Neural Network (DNN) based Faster Regions with Convolutional Neural Networks (Faster R-CNN) framework to detect COVID-19 patients from chest X-Ray images using available open-source dataset. Our proposed approach provides a classification accuracy of 97.36%, 97.65% of sensitivity, and a precision of 99.28%. Therefore, we believe this proposed method might be of assistance for health professionals to validate their initial assessment towards COVID-19 patients.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Hamish Gibbs",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Yang Liu",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Carl AB Pearson",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Christopher I Jarvis",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Chris Grundy",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Kabid Hassan Shibly",
+        "author_inst": "Dhaka International University (DIU)"
       },
       {
-        "author_name": "Billy J Quilty",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Samrat Kumar Dey",
+        "author_inst": "Dhaka International University (DIU)"
       },
       {
-        "author_name": "Charlie Diamond",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Md. Tahzib Ul Islam",
+        "author_inst": "Dhaka International University (DIU)"
       },
       {
-        "author_name": "Rosalind M Eggo",
-        "author_inst": "London School of Hygiene and Tropical Medicine"
+        "author_name": "Md. Mahbubur Rahman",
+        "author_inst": "Military Institute of Science and Technology (MIST)"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2020.05.14.20101758",
@@ -1407607,93 +1410528,117 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.05.18.101493",
-    "rel_title": "SARS-CoV2 infection in farmed mink, Netherlands, April 2020",
+    "rel_doi": "10.1101/2020.05.18.102038",
+    "rel_title": "Neutralizing antibody and soluble ACE2 inhibition of a replication-competent VSV-SARS-CoV-2 and a clinical isolate of SARS-CoV-2.",
     "rel_date": "2020-05-18",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.18.101493",
-    "rel_abs": "In April 2020, respiratory disease and increased mortality were observed in farmed mink on two farms in the Netherlands. In both farms, at least one worker had been found positive for SARS-CoV-2. Necropsies of the mink revealed interstitial pneumonia, and organ and swab samples tested positive for SARS-CoV-2 RNA by qPCR. Variations in viral genomes point at between-mink transmission on the farms and lack of infection link between the farms. Inhalable dust in the mink houses contained viral RNA, indicating possible exposure of workers.",
-    "rel_num_authors": 19,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.18.102038",
+    "rel_abs": "Antibody-based interventions against SARS-CoV-2 could limit morbidity, mortality, and possibly disrupt epidemic transmission. An anticipated correlate of such countermeasures is the level of neutralizing antibodies against the SARS-CoV-2 spike protein, yet there is no consensus as to which assay should be used for such measurements. Using an infectious molecular clone of vesicular stomatitis virus (VSV) that expresses eGFP as a marker of infection, we replaced the glycoprotein gene (G) with the spike protein of SARS-CoV-2 (VSV-eGFP-SARS-CoV-2) and developed a high-throughput imaging-based neutralization assay at biosafety level 2. We also developed a focus reduction neutralization test with a clinical isolate of SARS-CoV-2 at biosafety level 3. We compared the neutralizing activities of monoclonal and polyclonal antibody preparations, as well as ACE2-Fc soluble decoy protein in both assays and find an exceptionally high degree of concordance. The two assays will help define correlates of protection for antibody-based countermeasures including therapeutic antibodies, immune {gamma}-globulin or plasma preparations, and vaccines against SARS-CoV-2. Replication-competent VSV-eGFP-SARS-CoV-2 provides a rapid assay for testing inhibitors of SARS-CoV-2 mediated entry that can be performed in 7.5 hours under reduced biosafety containment.",
+    "rel_num_authors": 25,
     "rel_authors": [
       {
-        "author_name": "Nadia Oreshkova",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "James Brett Case",
+        "author_inst": "Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Robert-Jan Molenaar",
-        "author_inst": "GD Animal Health, Deventer, The Netherlands"
+        "author_name": "Paul W Rothlauf",
+        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA; Program in Virology, Harvard Medical School, Boston, MA, USA"
       },
       {
-        "author_name": "Sandra Vreman",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "Rita E Chen",
+        "author_inst": "Departments of Medicine, Pathology & Immunology, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Frank Harders",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands WBVR"
+        "author_name": "Zhuoming Liu",
+        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Bas B. Oude Munnink",
-        "author_inst": "Department of Viroscience,  Erasmus University Medical Center, Rotterdam, The Netherlands"
+        "author_name": "Haiyan Zhao",
+        "author_inst": "Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Renate W. Hakze-vd Honing",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "Arthur S Kim",
+        "author_inst": "Departments of Medicine, Pathology & Immunology, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Nora Gerhards",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "Louis-Marie Bloyet",
+        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Paulien Tolsma",
-        "author_inst": "Regional Public Health Service Brabant-Zuid-Oost, Eindhoven, The Netherlands"
+        "author_name": "Qiru Zeng",
+        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Ruth Bouwstra",
-        "author_inst": "GD Animal Health, Deventer, The Netherlands"
+        "author_name": "Stephen Tahan",
+        "author_inst": "Washington University in St. Louis School of Medicine"
       },
       {
-        "author_name": "Reina Sikkema",
-        "author_inst": "Department of Viroscience, Erasmus University Medical Center, Rotterdam, The Netherlands"
+        "author_name": "Lindsay Droit",
+        "author_inst": "Departments of Molecular Microbiology, Pathology & Immunology, Washington University School of Medicine, St. Louis, MO, USA."
       },
       {
-        "author_name": "Mirriam Tacken",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "Ma. Xenia G. Ilagan",
+        "author_inst": "Washington University School of Medicine"
       },
       {
-        "author_name": "Myrna M.T. de Rooij",
-        "author_inst": "Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands"
+        "author_name": "Michael A Tartell",
+        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA; Program in Virology, Harvard Medical School, Boston, MA, USA"
       },
       {
-        "author_name": "Eefke Weesendorp",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "Gaya K Amarasinghe",
+        "author_inst": "Departments of Molecular Microbiology, Pathology & Immunology, Biochemistry & Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA"
       },
       {
-        "author_name": "Marc Engelsma",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "Jeffrey P Henderson",
+        "author_inst": "Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA."
+      },
+      {
+        "author_name": "Shane Miersch",
+        "author_inst": "The Donnelly Centre, University of Toronto, Toronto, Canada."
       },
       {
-        "author_name": "Christianne Bruschke",
-        "author_inst": "Ministry of Agriculture, Nature and Food Quality, The Hague, The Netherlands"
+        "author_name": "Mart Ustav",
+        "author_inst": "The Donnelly Centre, University of Toronto, Toronto, Canada."
       },
       {
-        "author_name": "Lidwien A.M. Smit",
-        "author_inst": "Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands"
+        "author_name": "Sachdev Sidhu",
+        "author_inst": "The Donnelly Centre, University of Toronto, Toronto, Canada."
       },
       {
-        "author_name": "Marion Koopmans",
-        "author_inst": "Department of Viroscience,  Erasmus University Medical Center, Rotterdam, The Netherlands"
+        "author_name": "Herbert W Virgin",
+        "author_inst": "Vir Biotechnology, San Francisco, CA, USA."
       },
       {
-        "author_name": "Wim H.M. van der Poel",
-        "author_inst": "Wageningen Bioveterinary Research, Wageningen University and Research, Lelystad, The Netherlands"
+        "author_name": "David Wang",
+        "author_inst": "Washington University School of Medicine"
+      },
+      {
+        "author_name": "Siyuan Ding",
+        "author_inst": "Washington University in St. Louis School of Medicine"
       },
       {
-        "author_name": "JA Stegeman",
-        "author_inst": "Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, The Netherlands"
+        "author_name": "Davide Corti",
+        "author_inst": "Humabs Biomed SA, subsidiary of Vir Biotechnology"
+      },
+      {
+        "author_name": "Elitza S Theel",
+        "author_inst": "Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA."
+      },
+      {
+        "author_name": "Daved H Fremont",
+        "author_inst": "Departments of Molecular Microbiology, Pathology & Immunology, Biochemistry & Molecular Biophysics, and The Andrew M. and Jane M. Bursky Center for Human Immuno"
+      },
+      {
+        "author_name": "Michael S Diamond",
+        "author_inst": "Departments of Medicine, Molecular Microbiology, Biochemistry & Molecular Biophysics, and The Andrew M. and Jane M. Bursky Center for Human Immunology & Immunot"
+      },
+      {
+        "author_name": "Sean P. J. Whelan",
+        "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "new results",
     "category": "microbiology"
   },
@@ -1409533,63 +1412478,55 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2020.05.14.20096602",
-    "rel_title": "Decline in Emergent and Urgent Care during the COVID-19 Pandemic",
+    "rel_doi": "10.1101/2020.05.11.20098053",
+    "rel_title": "Parasites and their protection against COVID-19- Ecology or Immunology?",
     "rel_date": "2020-05-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20096602",
-    "rel_abs": "Due to the ongoing coronavirus disease (COVID-19) pandemic, there are concerns that patients may be avoiding care for emergent and urgent health conditions due to fear of contagion or as an unintentional consequence of government orders to postpone \"non-essential\" services. We therefore sought to evaluate the effect of the COVID-19 pandemic on the number of patient encounters for select emergent or urgent diagnoses at a large tertiary-care academic medical center in Boston. Inpatient diagnoses included acute myocardial infarction (MI) and stroke, and outpatient but urgent diagnoses included new referrals for breast and hematologic malignancies. For each condition, we used a \"difference-in-differences\" approach to estimate the proportional change in number of encounters during the pandemic (March - April 2020) compared with earlier in the same year (January - February 2020), using equivalent periods in 2019 as a control. After the onset of the pandemic, we observed significant reductions in hospitalizations for MI (difference-in-differences estimate, 0.67; 95%CI, 0.46-0.96; P=0.04) and stroke (difference-in-differences estimate, 0.42; 95%CI, 0.28-0.65; P<0.001) (Table). In the ambulatory setting, there was a reduction in referrals for breast cancer and hematologic cancers, but this did not reach statistical significance until the month after the onset of the pandemic. Our findings suggest an urgent need for public health messaging to ensure that patients continue to seek care for acute emergencies. In addition, decisions by health systems regarding when to reinitiate non-emergent care should carefully factor in the harms of delayed diagnosis and treatment occurring during the COVID-19 pandemic.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20098053",
+    "rel_abs": "BackgroundDespite the high infectivity of SARS-CoV-2, the incidence of COVID-19 in Africa has been slower than predicted. We aimed to investigate a possible association between parasitic infections and COVID-19.\n\nMethodsAn ecological study in which we analysed WHO data on COVID-19 cases in comparison to WHO data on helminths and malaria cases using correlation, regression, and Geographical Information Services analyses.\n\nResultsOf the global 3.34 million COVID-19 cases and 238,628 deaths as at May 4th 2020, Africa reported 0.029/3.3 million (0.88%) cases and 1,064/238,628 (0.45%) deaths. In 2018, Africa reported 213/229 million (93%) of all malaria cases, 204/229 million (89%) of schistosomiasis cases, and 271/1068 million (25%) of soil-transmitted helminth cases globally. In contrast, Europe reported 1.5/3.3 million (45%) of global COVID-19 cases and 142,667/238,628 (59%) deaths. Europe had 5.8/1068 million (0.55%) soil-transmitted helminths cases and no malaria/schistosomiasis cases in 2018. We found an inverse correlation between the incidence of COVID-19 and malaria (r -0.17, p =0.002) and COVID-19 and soil-transmitted helminths (r -0.25, p <0.001). Malaria-endemic countries were less likely to have COVID-19 (OR 0.51, 95% CI 0.29-0.90; p =0.02). Similarly, countries endemic for soil-transmitted helminths were less likely to have COVID-19 (OR 0.24, 95% CI 0.13-0.44; p <0.001), as were countries endemic for schistosomiasis (OR 0.22, 95% CI 0.11-0.45; p<0.001).\n\nConclusionsOne plausible hypothesis for the comparatively low COVID-19 cases/deaths in parasite-endemic areas is immunomodulation induced by parasites. Studies to elucidate the relationship between parasitic infections and susceptibility to COVID-19 at an individual level are warranted.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Dhruv S Kazi",
-        "author_inst": "Beth Israel Deaconess Medical Center"
-      },
-      {
-        "author_name": "Rishi K Wadhera",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
-      },
-      {
-        "author_name": "Changyu Shen",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "Kenneth Ssebambulidde",
+        "author_inst": "Infectious Diseases Institute, College of Health Sciences, Makerere University"
       },
       {
-        "author_name": "Kalon K.L. Ho",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "Ivan Segawa",
+        "author_inst": "Makerere Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda"
       },
       {
-        "author_name": "Rushad Patell",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "Kelvin M Abuga",
+        "author_inst": "Kenya Medical Research Institute Centre for Geographic Medicine Research-Coast, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya"
       },
       {
-        "author_name": "Magdy H. Selim",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "Vivian Nakate",
+        "author_inst": "Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda"
       },
       {
-        "author_name": "John H. Urwin",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "Anthony Kayiira",
+        "author_inst": "St Francis Hospital Nsambya, Kampala, Uganda"
       },
       {
-        "author_name": "Mark L. Zeidel",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "Jayne Ellis",
+        "author_inst": "London School of Hygiene and Tropical Medicine, London, UK"
       },
       {
-        "author_name": "Peter Zimetbaum",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "Lillian Tugume",
+        "author_inst": "Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda"
       },
       {
-        "author_name": "Kevin Tabb",
-        "author_inst": "Beth Israel Lahey Health, Cambridge, MA"
+        "author_name": "Agnes N Kiragga",
+        "author_inst": "Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda"
       },
       {
-        "author_name": "Robert W. Yeh",
-        "author_inst": "Beth Israel Deaconess Medical Center, Boston, MA"
+        "author_name": "David B Meya",
+        "author_inst": "Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health systems and quality improvement"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.05.14.20102533",
@@ -1410743,43 +1413680,151 @@
     "category": "geriatric medicine"
   },
   {
-    "rel_doi": "10.1101/2020.05.11.20098392",
-    "rel_title": "Forecasting Covid-19 dynamics in Brazil: a data driven approach",
+    "rel_doi": "10.1101/2020.05.11.20098459",
+    "rel_title": "Distinct systems serology features in children, elderly and COVID patients",
     "rel_date": "2020-05-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20098392",
-    "rel_abs": "This paper has a twofold contribution. The first is a data driven approach for predicting the Covid-19 pandemic dynamics, based on data from more advanced countries. The second is to report and discuss the results obtained with this approach for Brazilian states, as of May 4th, 2020. We start by presenting preliminary results obtained by training an LSTM-SAE network, which are somewhat disappointing. Then, our main approach consists in an initial clustering of the world regions for which data is available and where the pandemic is at an advanced stage, based on a set of manually engineered features representing a countrys response to the early spread of the pandemic. A Modified Auto-Encoder network is then trained from these clusters and learns to predict future data for Brazilian states. These predictions are used to estimate important statistics about the disease, such as peaks. Finally, curve fitting is carried out on the predictions in order to find the distribution that best fits the outputs of the MAE, and to refine the estimates of the peaks of the pandemic. Results indicate that the pandemic is still growing in Brazil, with most states peaks of infection estimated between the 25th of April and the 19th of May 2020. Predicted numbers reach a total of 240 thousand infected Brazilians, distributed among the different states, with Sao Paulo leading with almost 65 thousand estimated, confirmed cases. The estimated end of the pandemics (with 97% of cases reaching an outcome) starts as of May 28th for some states and rests through August 14th, 2020.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20098459",
+    "rel_abs": "SARS-CoV-2, the pandemic coronavirus that causes COVID-19, has infected millions worldwide, causing unparalleled social and economic disruptions. COVID-19 results in higher pathogenicity and mortality in the elderly compared to children. Examining baseline SARS-CoV-2 cross-reactive coronavirus immunological responses, induced by circulating human coronaviruses, is critical to understand such divergent clinical outcomes. The cross-reactivity of coronavirus antibody responses of healthy children (n=89), adults (n=98), elderly (n=57), and COVID-19 patients (n=19) were analysed by systems serology. While moderate levels of cross-reactive SARS-CoV-2 IgG, IgM, and IgA were detected in healthy individuals, we identified serological signatures associated with SARS-CoV-2 antigen-specific Fc{gamma} receptor binding, which accurately distinguished COVID-19 patients from healthy individuals and suggested that SARS-CoV-2 induces qualitative changes to antibody Fc upon infection, enhancing Fc{gamma} receptor engagement. Vastly different serological signatures were observed between healthy children and elderly, with markedly higher cross-reactive SARS-CoV-2 IgA and IgG observed in elderly, whereas children displayed elevated SARS-CoV-2 IgM, including receptor binding domain-specific IgM with higher avidity. These results suggest that less-experienced humoral immunity associated with higher IgM, as observed in children, may have the potential to induce more potent antibodies upon SARS-CoV-2 infection. These key insights will inform COVID-19 vaccination strategies, improved serological diagnostics and therapeutics.",
+    "rel_num_authors": 33,
     "rel_authors": [
       {
-        "author_name": "Igor Gadelha Pereira",
-        "author_inst": "Universidade Federal do Rio Grande do Norte"
+        "author_name": "Kevin J. Selva",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Joris M Guerin",
-        "author_inst": "Universidade Federal do Rio Grande do Norte"
+        "author_name": "Carolien E. van de Sandt",
+        "author_inst": "University of Melbourne"
       },
       {
-        "author_name": "Andouglas Goncalves Silva Jr.",
-        "author_inst": "Instituto Federal do Rio Grande do Norte"
+        "author_name": "Melissa M. Lemke",
+        "author_inst": "University of Michigan"
       },
       {
-        "author_name": "Cosimo Distante",
-        "author_inst": "CNR"
+        "author_name": "Christina Y. Lee",
+        "author_inst": "University of Michigan"
       },
       {
-        "author_name": "Gabriel Santos Garcia",
-        "author_inst": "Universidade de Brasilia"
+        "author_name": "Suzanne K. Shoffner",
+        "author_inst": "University of Michigan"
       },
       {
-        "author_name": "Luiz M.G. Goncalves",
-        "author_inst": "Universidade Federal do Rio Grande do Norte"
+        "author_name": "Brendon Y. Chua",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Thi H.O. Nguyen",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Louise C. Rowntree",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Luca Hensen",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Marios Koutsakos",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Chinn Yi Wong",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "David C. Jackson",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Katie L. Flanagan",
+        "author_inst": "Launceston General Hospital, Launceston"
+      },
+      {
+        "author_name": "Jane Crowe",
+        "author_inst": "Deepdene Surgery"
+      },
+      {
+        "author_name": "Allen C. Cheng",
+        "author_inst": "Monash University"
+      },
+      {
+        "author_name": "Denise L. Doolan",
+        "author_inst": "James Cook University"
+      },
+      {
+        "author_name": "Fatima Amanat",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Florian Krammer",
+        "author_inst": "Icahn School of Medicine at Mount Sinai"
+      },
+      {
+        "author_name": "Keith Chappell",
+        "author_inst": "University of Queensland"
+      },
+      {
+        "author_name": "Naphak Modhiran",
+        "author_inst": "University of Queensland"
+      },
+      {
+        "author_name": "Daniel Watterson",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Paul Young",
+        "author_inst": "University of Queensland"
+      },
+      {
+        "author_name": "Bruce Wines",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "P. Mark Hogarth",
+        "author_inst": "Burnet Institute"
+      },
+      {
+        "author_name": "Robyn Esterbauer",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Hannah G. Kelly",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Hyon-Xhi Tan",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Jennifer A. Juno",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Adam K. Wheatley",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Stephen J. Kent",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Kelly B. Arnold",
+        "author_inst": "University of Michigan"
+      },
+      {
+        "author_name": "Katherine Kedzierska",
+        "author_inst": "University of Melbourne"
+      },
+      {
+        "author_name": "Amy W. Chung",
+        "author_inst": "University of Melbourne"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.05.14.20102061",
@@ -1411933,119 +1414978,31 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2020.05.18.099507",
-    "rel_title": "Afucosylated immunoglobulin G responses are a hallmark of enveloped virus infections and show an exacerbated phenotype in COVID-19",
-    "rel_date": "2020-05-18",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.18.099507",
-    "rel_abs": "IgG antibodies are crucial for protection against invading pathogens. A highly conserved N-linked glycan within the IgG-Fc-tail, essential for IgG function, shows variable composition in humans. Afucosylated IgG variants are already used in anti-cancer therapeutic antibodies for their elevated binding and killing activity through Fc receptors (Fc{gamma}RIIIa). Here, we report that afucosylated IgG which are of minor abundance in humans ([~]6% of total IgG) are specifically formed against surface epitopes of enveloped viruses after natural infections or immunization with attenuated viruses, while protein subunit immunization does not elicit this low fucose response. This can give beneficial strong responses, but can also go awry, resulting in a cytokine-storm and immune-mediated pathologies. In the case of COVID-19, the critically ill show aggravated afucosylated-IgG responses against the viral spike protein. In contrast, those clearing the infection unaided show higher fucosylation levels of the anti-spike protein IgG. Our findings indicate antibody glycosylation as a potential factor in inflammation and protection in enveloped virus infections including COVID-19.",
-    "rel_num_authors": 25,
+    "rel_doi": "10.1101/2020.05.12.20099085",
+    "rel_title": "Understanding the indoor pre-symptomatic transmission mechanism of COVID-19",
+    "rel_date": "2020-05-17",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099085",
+    "rel_abs": "Discovering the mechanism that enables pre-symptomatic individuals to transmit the SARS-CoV-2 virus has a significant impact on the possibility of controlling COVID-19 pandemic. To this end, we have developed an evidence based quantitative mechanistic mathematical model. The model explicitly tracks the dynamics of contact and airborne transmission between individuals indoors, and was validated against the observed fundamental attributes of the epidemic, the secondary attack rate (SAR) and serial interval distribution. Using the model we identified the dominant driver of pre-symptomatic transmission, which was found to be contact route, while the contribution of the airborne route is negligible. We provide evidence that a combination of rather easy to implement measures of frequent hand washing, cleaning fomites and avoiding physical contact decreases the risk of infection by an order of magnitude, similarly to wearing masks and gloves.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Mads D. Larsen",
-        "author_inst": "Sanquin Reseach"
-      },
-      {
-        "author_name": "Erik L de Graaf",
-        "author_inst": "Sanquin Reseach"
-      },
-      {
-        "author_name": "Myrthe E. Sonneveld",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "H. Rosina Plomp",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Federica Linty",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "Remco Visser",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "Maximilian Brinkhaus",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "Tonci Sustic",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "Steven W. deTaeye",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "Arthur E.H. Bentlage",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "Jan Nouta",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Suvi Natunen",
-        "author_inst": "Finnish Red Cross Blood Service"
-      },
-      {
-        "author_name": "Carolien A.M. Koeleman",
-        "author_inst": "Leiden University Medical Center"
-      },
-      {
-        "author_name": "Susanna Sainio",
-        "author_inst": "Finnish Red Cross Blood Service"
-      },
-      {
-        "author_name": "Neeltje A. Kootstra",
-        "author_inst": "University of Amsterdam"
-      },
-      {
-        "author_name": "Philip J.M. Brouwer",
-        "author_inst": "Amsterdam University Medical Centers"
-      },
-      {
-        "author_name": "Rogier W. Sanders",
-        "author_inst": "Amsterdam University Medical Centers"
-      },
-      {
-        "author_name": "Marit J. van Gils",
-        "author_inst": "Amsterdam University Medical Centers"
-      },
-      {
-        "author_name": "Sanne de Bruin",
-        "author_inst": "Amsterdam University Medical Centers"
-      },
-      {
-        "author_name": "Alexander P.J. Vlaar",
-        "author_inst": "Amsterdam University Medical Centers"
-      },
-      {
-        "author_name": "Amsterdam UMC COVID-19 biobank study group",
-        "author_inst": ""
-      },
-      {
-        "author_name": "Hans L. Zaaijer",
-        "author_inst": "Sanquin Research"
-      },
-      {
-        "author_name": "Manfred Wuhrer",
-        "author_inst": "Leiden University Medical Center,"
+        "author_name": "Yehuda Arav",
+        "author_inst": "Israel Institute for Biological Research"
       },
       {
-        "author_name": "C. Ellen van der Schoot",
-        "author_inst": "Sanquin Research"
+        "author_name": "Ziv Klausner",
+        "author_inst": "Israel Institute for Biological Research"
       },
       {
-        "author_name": "Gestur Vidarsson",
-        "author_inst": "Sanquin Research"
+        "author_name": "Eyal Fattal",
+        "author_inst": "Israeli Institute for Biological Research"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "new results",
-    "category": "immunology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.05.14.096107",
@@ -1413215,47 +1416172,43 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.14.20102483",
-    "rel_title": "Early and massive testing saves lives: COVID-19 related infections and deaths in the United States during March of 2020",
+    "rel_doi": "10.1101/2020.05.13.20099614",
+    "rel_title": "Dynamic liver function indexes monitoring and clinical characteristics in three types of COVID-19 patients",
     "rel_date": "2020-05-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20102483",
-    "rel_abs": "To optimize epidemiologic interventions, predictors of mortality should be identified. The US COVID-19 epidemic data -reported up to 3-31-2020- were analyzed using kernel regularized least squares regression. Six potential predictors of mortality were investigated: (i) the number of diagnostic tests performed in testing week I; (ii) the proportion of all tests conducted during week I of testing; (iii) the cumulative number of (test-positive) cases through 3-31-2020, (iv) the number of tests performed/million citizens; (v) the cumulative number of citizens tested; and (vi) the apparent prevalence rate, defined as the number of cases/million citizens. Two metrics estimated mortality: the number of deaths and the number of deaths/million citizens. While both expressions of mortality were predicted by the case count and the apparent prevalence rate, the number of deaths/million citizens was {approx}3.5 times better predicted by the apparent prevalence rate than the number of cases. In eighteen states, early testing/million citizens/population density was inversely associated with the cumulative mortality reported by 31 March, 2020. Findings support the hypothesis that early and massive testing saves lives. Other factors -e.g., population density-may also influence outcomes. To optimize national and local policies, the creation and dissemination of high-resolution geo-referenced, epidemic data is recommended.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20099614",
+    "rel_abs": "Background & AimsThe abnormal liver function and even liver failure related death were reported in the COVID-19 patients, but less of studies focus on the dynamic liver function changes. We analysed the liver function indexes of COVID-19 patients to explore the characteristics of liver function changes in patients with different severity.\n\nMethodsThis study included 54 moderate, 50 severe, and 31 death nucleic acid-confirmed COVID-19 patients hospitalized at the central hospital of Wuhan, China. Epidemiological histories, clinical features, imaging materials, medications and especially major liver function laboratory tests were collected for analysis.\n\nResultsThe clinical symptoms did not present any significant difference in the patients at admission, but the older male patients had pronounced mortality risk. The normal ratio of ALT, TB, and DBIL of moderate patients was 96.3%, 94.44%, and 98.15% separately at the first test, but 59.26% of patients showed declined ALB levels. The normal ratio of all liver function indexes declined after admission, but most abnormalities were mild (1-2 times of upper limit unit) and went back normal before discharge. In severe patients, the normal ratio of ALB dropped down to 30.61% at admission along with the dramatic impaired normal ratio of bilirubin at the second test. The severe patients liver function dysfunction was worse than the moderate patients but without a significant difference. The dead patients showed a significantly higher level of DBIL, AST, GGT and CRP than other groups patients in the final test, along with the hypoalbuminemia. What is worse, 16.13% of non-survivors were diagnosed with liver failure. No medication was found to be related to ALT, AST, and GGT abnormality in our study.\n\nConclusionIn moderate and severe patients, liver dysfunction was mild. Patients widely presented lower level of ALB. The higher level of bilirubin, AST, and GGT was likely to indicate the worse outcome. Dynamic monitoring of liver function indexes could be considered and liver failure related death should be noticed and prevented in the early stage.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "James B. Hittner",
-        "author_inst": "Department of Psychology, College of Charleston, Charleston, South Carolina, United States of America"
-      },
-      {
-        "author_name": "Folorunso O. Fasina",
-        "author_inst": "Food and Agriculture Organization, Dar es Salam, Tanzania"
+        "author_name": "Cheng Chen",
+        "author_inst": "Institute of Liver Diseases, Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China"
       },
       {
-        "author_name": "Almira L. Hoogesteijn",
-        "author_inst": "Human Ecology, Centro de Investigacion y de Estudios Avanzados (CINVESTAV), Merida, Mexico"
+        "author_name": "Jie Jiang",
+        "author_inst": "1.\tDepartment of Respiratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China"
       },
       {
-        "author_name": "Renata Piccinini",
-        "author_inst": "Department of Veterinary Medicine, University of Milan, Milan, Italy"
+        "author_name": "Xiaoxiao Xu",
+        "author_inst": "1.\tDepartment of Respiratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China"
       },
       {
-        "author_name": "Prakasha Kempaiah",
-        "author_inst": "Loyola University Chicaco Stritch School of Medicine, Chicago, USA"
+        "author_name": "Yiyang Hu",
+        "author_inst": "1.\tInstitute of Liver Diseases, Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China"
       },
       {
-        "author_name": "Stephen D. Smith",
-        "author_inst": "Institute for Resource Information Science, College of Agriculture, Cornell University, Ithaca, United States of America"
+        "author_name": "Yi Hu",
+        "author_inst": "1.\tDepartment of Respiratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China"
       },
       {
-        "author_name": "Ariel L. Rivas",
-        "author_inst": "Center for Global Health, Department of Internal Medicine, Medical School, University of New Mexico, Albuquerque, New Mexico, United States of America"
+        "author_name": "Yu Zhao",
+        "author_inst": "1.\tInstitute of Liver Diseases, Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "gastroenterology"
   },
   {
     "rel_doi": "10.1101/2020.05.13.20100636",
@@ -1414617,65 +1417570,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.13.20100370",
-    "rel_title": "Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19 in Wuhan, China: the PLANS (Platelet Lymphocyte Age Neutrophil Sex) model",
+    "rel_doi": "10.1101/2020.05.13.20101006",
+    "rel_title": "Loss of Taste and Smell as Distinguishing Symptoms of COVID-19",
     "rel_date": "2020-05-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20100370",
-    "rel_abs": "OBJECTIVETo develop and validate a prognostic model for in-hospital mortality in COVID-19 patients using routinely collected demographic and clinical characteristics.\n\nDESIGNMulticenter, retrospective cohort study.\n\nSETTINGJinyintan Hospital, Union Hospital, and Tongji Hosptial in Wuhan, China.\n\nPARTICIPANTSA pooled derivation cohort of 1008 COVID-19 patients from Jinyintan Hospital, Union Hospital in Wuhan and an external validation cohort of 1031 patients from Tongji Hospital in Wuhan, China.\n\nMAIN OUTCOME MEASURESOutcome of interest was in-hospital mortality, treating discharged alive from hospital as the competing event. Fine-Gray models, using backward elimination for inclusion of predictor variables and allowing non-linear effects of continuous variables, were used to derive a prognostic model for predicting in-hospital mortality among COVID-19 patients. Internal validation was implemented to check model overfitting using bootstrap approach. External validation to a separate hospital was implemented to evaluate the generalizability of the model.\n\nRESULTSThe derivation cohort was a case-mix of mild-to-severe hospitalized COVID-19 patients (n=1008, 43.6% females, median age 55). The final model (PLANS), including five predictor variables of platelet count, lymphocyte count, age, neutrophil count, and sex, had an excellent predictive performance (optimism-adjusted C-index: 0.85, 95% CI: 0.83 to 0.87; averaged calibration slope: 0.95, 95% CI: 0.82 to 1.08). Internal validation showed little overfitting. External validation using an independent cohort (n=1031, 47.8% female, median age 63) demonstrated excellent predictive performance (C-index: 0.87, 95% CI: 0.85 to 0.89; calibration slope: 1.02, 95% CI: 0.92 to 1.12). The averaged predicted survival curves were close to the observed survival curves across patients with different risk profiles.\n\nCONCLUSIONSThe PLANS model based on the five routinely collected demographic and clinical characteristics (platelet count, lymphocyte count, age, neutrophil count, and sex) showed excellent discriminative and calibration accuracy in predicting in-hospital mortality in COVID-19 patients. This prognostic model would assist clinicians in better triaging patients and allocating healthcare resources to reduce COVID-19 fatality.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20101006",
+    "rel_abs": "Olfactory and taste dysfunctions have emerged as symptoms of COVID-19. Among individuals with COVID-19 enrolled in a household study, loss of taste and/or smell was the fourth most commonly reported symptom (26/42; 62%), and among household contacts, it had the highest positive predictive value (83%; 95% CI: 55-95%) for COVID-19. These findings support consideration of loss of taste and/or smell in possible case identification and testing prioritization for COVID-19.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Jiong Li",
-        "author_inst": "Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine"
+        "author_name": "Patrick Dawson",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Yuntao Chen",
-        "author_inst": "Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands"
+        "author_name": "Elizabeth M. Rabold",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Shujing Chen",
-        "author_inst": "Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"
+        "author_name": "Rebecca L. Laws",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Sihua Wang",
-        "author_inst": "Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China"
+        "author_name": "Erin E. Conners",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Dingyu Zhang",
-        "author_inst": "Department of Tuberculosis and Respiratory Disease, Jinyintan Hospital, Wuhan, China"
+        "author_name": "Radhika Gharpure",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Junfeng Wang",
-        "author_inst": "Julius Center for Health Science and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands"
+        "author_name": "Sherry Yin",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Douwe Postmus",
-        "author_inst": "Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands"
+        "author_name": "Sean Buono",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Hesong Zeng",
-        "author_inst": "Department of Cardiology, Tongji Hospital, School of Medicine, Huazhong University of Science and Technology, Wuhan, China."
+        "author_name": "Trivikram Dasu",
+        "author_inst": "City of Milwaukee Health Department Laboratory"
       },
       {
-        "author_name": "Guoyou Qin",
-        "author_inst": "Department of Biostatistics, School of Public Health, and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China"
+        "author_name": "Sanjib Bhattacharyya",
+        "author_inst": "City of Milwaukee Health Department Laboratory"
       },
       {
-        "author_name": "Yin Shen",
-        "author_inst": "Eye Center, Medical Research Institute, Wuhan University Renmin Hospital, Wuhan University, Wuhan, China"
+        "author_name": "Ryan P. Westergaard",
+        "author_inst": "Wisconsin Department of Health Services"
       },
       {
-        "author_name": "Jinjun Jiang",
-        "author_inst": "Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China"
+        "author_name": "Ian W. Pray",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Dongni Ye",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Scott A. Nabity",
+        "author_inst": "Centers for Disease Control and Prevention"
       },
       {
-        "author_name": "Yongfu Yu",
-        "author_inst": "Department of Biostatistics, School of Public Health, and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China"
+        "author_name": "Jacqueline E. Tate",
+        "author_inst": "Centers for Disease Control and Prevention"
+      },
+      {
+        "author_name": "Hannah L. Kirking",
+        "author_inst": "Centers for Disease Control and Prevention"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc0",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1416351,49 +1419316,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.11.20095158",
-    "rel_title": "SARS-CoV-2 antibody seroprevalence in industry workers in Split-Dalmatia and Sibenik-Knin County, Croatia",
+    "rel_doi": "10.1101/2020.05.10.20097543",
+    "rel_title": "Estimating the extent of true asymptomatic COVID-19 and its potential for community transmission: systematic review and meta-analysis",
     "rel_date": "2020-05-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20095158",
-    "rel_abs": "BACKGROUNDAs a result of global spread, COVID-19 has also affected the Republic of Croatia in the last week of February. Although official data show that the number of newly infected is declining, it is still unknown what proportion of the population has been affected by the disease.\n\nAIMTo examine seroprevalence of SARS-CoV-2 antibodies in industry workers population sample.\n\nMETHODSFrom 23 to 28 April 2020, we conducted serological testing for antibodies (IgG and IgM) on 1494 factory employees living in the Split-Dalmatia and [S]ibenik-Knin County (Croatia). We analysed antibody seroprevalence on the level of the company, county, and separately for employees living at the factory premises with limited mobility during the lockdown measures.\n\nRESULTSIn a total sample of tested company employees, we detected antibodies in 1.27% of participants (95% CI 0.77-1.98%). In Split facility 13/1316 (0.99%, 95% CI 0.53-1.68%) of participants were tested positive, of which 13/1079 (1.20%, 95% CI 0.64-2.05%) of those living outside the facility and 0/237 (0%, 95% CI 0-1.26%) of those living inside the facility. In Knin facility, 6/178 (3.37%, 95% CI 1.25-7.19%) participants were tested positive for antibodies. The difference between Split (no mobility restrictions) and Knin, was not statistically significant ({chi}2 = 3.47, P = 0.062).\n\nCONCLUSIONSThe study showed relatively small SARS-CoV-2 antibody seroprevalence in the DIV Group population sample. When the study findings are interpreted on the county levels, they could indicate that most of the counties population was not exposed to the virus.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.10.20097543",
+    "rel_abs": "BackgroundThe prevalence of true asymptomatic COVID-19 cases is critical to policy makers considering the effectiveness of mitigation measures against the SARS-CoV-2 pandemic. We aimed to synthesize all available research on the asymptomatic rates and transmission rates where possible.\n\nMethodsWe searched PubMed, Embase, Cochrane COVID-19 trials, and Europe PMC (which covers pre-print platforms such as MedRxiv). We included primary studies reporting on asymptomatic prevalence where: (a) the sample frame includes at-risk population, and (b) there was sufficiently long follow up to identify pre-symptomatic cases. Meta-analysis used fixed effect and random effects models. We assessed risk of bias by combination of questions adapted from risk of bias tools for prevalence and diagnostic accuracy studies.\n\nResultsWe screened 998 articles and included nine low risk-of-bias studies from six countries that tested 21,035 at-risk people, of which 559 were positive and 83 were asymptomatic. Diagnosis in all studies was confirmed using a RT-qPCR test. The proportion of asymptomatic cases ranged from 4% to 41%. Meta-analysis (fixed effect) found that the proportion of asymptomatic cases was 15% (95% CI: 12% - 18%) overall; higher in non-aged care 16% (13% - 19%), and lower in long-term aged care 8% (3% - 18%). Four studies provided direct evidence of forward transmission of the infection by asymptomatic cases but suggested considerably lower rates than symptomatic cases.\n\nDiscussionOur estimates of the prevalence of asymptomatic COVID-19 cases and asymptomatic transmission rates are lower than many highly publicized studies, but still sufficient to warrant policy attention. Further robust epidemiological evidence is urgently needed, including in sub-populations such as children, to better understand the importance of asymptomatic cases for driving spread of the pandemic.\n\nFundingOB is supported by NHMRC Grant APP1106452. PG is supported by NHMRC Australian Fellowship grant 1080042. KB was supported by NHMRC Fellowship grant 1174523. All authors had full access to all data and agreed to final manuscript to be submitted for publication. There was no funding source for this study.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Ivan Jerkovic",
-        "author_inst": "University Department of Forensic Sciences University of Split"
-      },
-      {
-        "author_name": "Toni Ljubic",
-        "author_inst": "University Department of Forensic Sciences University of Split"
-      },
-      {
-        "author_name": "Zeljana Basic",
-        "author_inst": "University Department of Forensic Sciences"
-      },
-      {
-        "author_name": "Ivana Kruzic",
-        "author_inst": "University Deparment ofForensic Sciences"
+        "author_name": "Oyungerel Byambasuren",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Nenad Kunac",
-        "author_inst": "Clinical Department for Pathology, Forensic Medicine and Cytology, University Hospital Center Split"
+        "author_name": "Magnolia Cardona",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Josko Bezic",
-        "author_inst": "Clinical Department for Pathology, Forensic Medicine and Cytology, University Hospital Center Split"
+        "author_name": "Katy Bell",
+        "author_inst": "University of Sydney"
       },
       {
-        "author_name": "Arijana Vuko",
-        "author_inst": "Clinical Department for Pathology, Forensic Medicine and Cytology, University Hospital Center Split"
+        "author_name": "Justin Clark",
+        "author_inst": "Bond University"
       },
       {
-        "author_name": "Alemka Markotic",
-        "author_inst": "Dr. Fran Mihaljevic University Hospital for Infectious Diseases, Zagreb, Croatia; Catholic University of Croatia, Zagreb, Croatia; University of Rijeka School o"
+        "author_name": "Mary-Louise McLaws",
+        "author_inst": "UNSW Sydney"
       },
       {
-        "author_name": "Simun Andjelinovic",
-        "author_inst": "Clinical Department for Pathology, Forensic Medicine and Cytology, University Hospital Center Split, Split, Croatia; University of Split, School of Medicine, Sp"
+        "author_name": "Paul Glasziou",
+        "author_inst": "Bond University"
       }
     ],
     "version": "1",
@@ -1417960,43 +1420913,35 @@
     "category": "molecular biology"
   },
   {
-    "rel_doi": "10.1101/2020.05.14.097204",
-    "rel_title": "Expression of ACE2 and TMPRSS2 proteins in the upper and lower aerodigestive tracts of rats",
+    "rel_doi": "10.1101/2020.05.15.097501",
+    "rel_title": "Traffic-derived particulate matter and angiotensin-converting enzyme 2 expression in human airway epithelial cells",
     "rel_date": "2020-05-15",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.097204",
-    "rel_abs": "Objective Patients with coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), exhibit not only respiratory symptoms but also symptoms of chemo-sensitive disorders and kidney failure. Cellular entry of SARS-CoV-2 depends on the binding of its spike protein to a cellular receptor named angiotensin-converting enzyme 2 (ACE2), and the subsequent spike protein-priming by host cell proteases, including transmembrane protease serine 2 (TMPRSS2). Thus, high expression of ACE2 and TMPRSS2 are considered to enhance the invading capacity of SARS-CoV-2.Methods To elucidate the underlying histological mechanisms of the aerodigestive disorders caused by SARS-CoV-2, we investigated the expression of ACE2 and TMPRSS2 proteins in the aerodigestive tracts of the tongue, hard palate with partial nasal tissue, larynx with hypopharynx, trachea, esophagus, lung, and kidney of rats through immunohistochemistry.Results Strong co-expression of ACE2 and TMPRSS2 proteins was observed in the nasal respiratory epithelium, trachea, bronchioles, alveoli, kidney, and taste buds of the tongue. Remarkably, TMPRSS2 expression was much stronger in the peripheral alveoli than in the central alveoli. These results coincide with the reported clinical symptoms of COVID-19, such as the loss of taste, loss of olfaction, respiratory dysfunction, and acute nephropathy.Conclusions A wide range of organs have been speculated to be affected by SARS-CoV-2 depending on the expression levels of ACE2 and TMPRSS2. Differential distribution of TMPRSS2 in the lung indicated the COVID-19 symptoms to possibly be exacerbated by TMPRSS2 expression. This study might provide potential clues for further investigation of the pathogenesis of COVID-19.Level of Evidence NACompeting Interest StatementThe authors have declared no competing interest.View Full Text",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.15.097501",
+    "rel_abs": "Background The mechanism for the association between traffic-derived particulate matter less than 10 microns (PM10) and cases of COVID-19 disease reported in epidemiological studies is unknown. To infect cells, the spike protein of SARS-CoV-2 interacts with angiotensin-converting enzyme 2 (ACE2) on host airway cells. Increased ACE2 expression in lower airway cells in active smokers, suggests a potential mechanism whereby PM10 increases vulnerability to COVID-19 disease.Objective To assess the effect of traffic-derived PM10 on human airway epithelial cell ACE2 expression in vitro.Methods PM10 was collected from Marylebone Road (London) using a kerbside impactor. A549 and human primary nasal epithelial cells were cultured with PM10 for 2 h, and ACE2 expression (median fluorescent intensity; MFI) assessed by flow cytometry. We included cigarette smoke extract as a putative positive control. Data were analysed by either Mann-Whitney test, or Kruskal-Wallis with Dunn\u2019s multiple comparisons test.Results PM10 at 10 \u03bcg/mL, and 20 \u03bcg/mL increased ACE2 expression in A549 cells (P&lt;0.05, 0.01 vs. medium control, respectively). Experiments using a single PM10 concentration (10 \u03bcg/mL), found increased ACE2 expression in both A549 cells (control vs. PM10, median (IQR) MFI; 470 (0.1 to 1114) vs 6217 (5071 to 8506), P&lt;0.01), and in human primary epithelial cells (0 (0 to 591) vs. 4000 (2610 to 7853), P&lt;0.05). Culture of A549 cells with 5% cigarette smoke extract increased ACE2 expression (n=4, 0 (0 to 28) vs. 9088 (7557 to 15831, P&lt;0.05).Conclusion Traffic-related PM10 increases the expression of the receptor for SARS-CoV-2 in human respiratory epithelial cells.Competing Interest StatementThe authors have declared no competing interest.View Full Text",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Rumi Ueha",
-        "author_inst": "The University of Tokyo"
-      },
-      {
-        "author_name": "Taku Sato",
-        "author_inst": "Department of Otolaryngology and Head and Neck Surgery, the University of Tokyo"
-      },
-      {
-        "author_name": "Takao Goto",
-        "author_inst": "Department of Otolaryngology and Head and Neck Surgery, the University of Tokyo"
+        "author_name": "Lisa Miyashita",
+        "author_inst": "Queen Mary University of London"
       },
       {
-        "author_name": "Akihito Yamauchi",
-        "author_inst": "Department of Otolaryngology and Head and Neck Surgery, the University of Tokyo"
+        "author_name": "Gary Foley",
+        "author_inst": "Queen Mary University of London"
       },
       {
-        "author_name": "Kenji Kondo",
-        "author_inst": "Department of Otolaryngology and Head and Neck Surgery, the University of Tokyo"
+        "author_name": "Sean Semple",
+        "author_inst": "University of Sterling, UK"
       },
       {
-        "author_name": "Tatsuya Yamasoba",
-        "author_inst": "Department of Otolaryngology and Head and Neck Surgery, the University of Tokyo"
+        "author_name": "Jonathan Grigg",
+        "author_inst": "Queen Mary University of London"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "pathology"
+    "category": "pharmacology and toxicology"
   },
   {
     "rel_doi": "10.1101/2020.05.15.095794",
@@ -1419946,47 +1422891,43 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.14.096081",
-    "rel_title": "Crystal structures of SARS-CoV-2 ADP-ribose phosphatase (ADRP): from the apo form to ligand complexes",
+    "rel_doi": "10.1101/2020.05.14.092767",
+    "rel_title": "ACE2-Variants Indicate Potential SARS-CoV-2-Susceptibility in Animals: An Extensive Molecular Dynamics Study",
     "rel_date": "2020-05-14",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.096081",
-    "rel_abs": "Among 15 nonstructural proteins (Nsps), the newly emerging SARS-CoV-2 encodes a large, multidomain Nsp3. One of its units is ADP-ribose phosphatase domain (ADRP, also known as macrodomain) which is believed to interfere with the host immune response. Such a function appears to be linked to the proteins ability to remove ADP-ribose from ADP-ribosylated proteins and RNA, yet the precise role and molecular targets of the enzyme remains unknown. Here, we have determined five, high resolution (1.07 - 2.01 [A]) crystal structures corresponding to the apo form of the protein and complexes with 2-(N-morpholino)ethanesulfonic acid (MES), AMP and ADPr. We show that the protein undergoes conformational changes to adapt to the ligand in a manner previously observed before for in close homologs from other viruses. We also identify a conserved water molecule that may participate in hydrolysis. This work builds foundations for future structure-based research of the ADRP, including search for potential antiviral therapeutics.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.092767",
+    "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) emerged in late 2019 and since evolved into a global threat with nearly 4.4 million infected people and over 290,000 confirmed deaths worldwide.1 SARS-CoV-2 is an enveloped virus presenting spike (S) glycoproteins on its outer surface. Binding of S to host cell angiotensin converting enzyme 2 (ACE2) is thought to be critical for cellular entry. The host range of the virus extends far beyond humans and non-human primates. Natural and experimental infections have confirmed high susceptibility of cats, ferrets, and hamsters, whereas dogs, mice, rats, pigs, and chickens seem refractory to SARS-CoV-2 infection. To investigate the reason for the variable susceptibility observed in different species, we have developed molecular descriptors to efficiently analyze our dynamic simulation models of complexes between SARS-CoV-2 S and ACE2. Based on our analyses we predict that: (i) the red squirrel is likely susceptible to SARS-CoV-2 infection and (ii) specific mutations in ACE2 of dogs, rats, and mice render them susceptible to SARS-CoV-2 infection.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Karolina Michalska",
-        "author_inst": "Argonne National Laboratory/University of Chicago"
-      },
-      {
-        "author_name": "Youngchang Kim",
-        "author_inst": "Argonne National Laboratory/University of Chicago"
+        "author_name": "Szymon Pach",
+        "author_inst": "Institute of Pharmacy, Molecular Drug Design, Freie Universitaet Berlin, Germany"
       },
       {
-        "author_name": "Robert Jedrzejczak",
-        "author_inst": "Argonne National Laboratory/University of Chicago"
+        "author_name": "Trung Ngoc Nguyen",
+        "author_inst": "Institute of Pharmacy, Molecular Drug Design, Freie Universitaet Berlin, Germany"
       },
       {
-        "author_name": "Natalia I. Maltseva",
-        "author_inst": "Argonne National Laboratory/University of Chicago"
+        "author_name": "Jakob Trimpert",
+        "author_inst": "Institut fuer Virologie, Freie Universitaet Berlin, Germany"
       },
       {
-        "author_name": "Lucy Stols",
-        "author_inst": "University of Chicago"
+        "author_name": "Dusan Kunec",
+        "author_inst": "Institut fuer Virologie, Freie Universitaet Berlin, Germany"
       },
       {
-        "author_name": "Michael Endres",
-        "author_inst": "Argonne National Laboratory"
+        "author_name": "Nikolaus Osterrieder",
+        "author_inst": "Institut fuer Virologie, Freie Universitaet Berlin, Germany"
       },
       {
-        "author_name": "Andrzej Joachimiak",
-        "author_inst": "Argonne National Laboratory"
+        "author_name": "Gerhard Wolber",
+        "author_inst": "Institute of Pharmacy, Molecular Drug Design, Freie Universitaet Berlin, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "new results",
-    "category": "molecular biology"
+    "category": "pharmacology and toxicology"
   },
   {
     "rel_doi": "10.1101/2020.05.11.20098061",
@@ -1421328,23 +1424269,27 @@
     "category": "health informatics"
   },
   {
-    "rel_doi": "10.1101/2020.05.10.20097154",
-    "rel_title": "The Estimated Time-Varying Reproduction Numbers during the Ongoing Pandemic of the Coronavirus Disease 2019 (COVID-19) in 12 Selected Countries outside China",
-    "rel_date": "2020-05-14",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.10.20097154",
-    "rel_abs": "BackgroundHow can we anticipate the progression of the ongoing pandemic of the coronavirus disease 2019 (COVID-19)? As a measure of transmissibility, we aimed to estimate concurrently the time-varying reproduction number, R0(t), over time during the COVID-19 pandemic for each of the following 12 heavily-attacked countries: Singapore, South Korea, Japan, Iran, Italy, Spain, Germany, France, Belgium, United Kingdom, the United States of America, and South Africa.\n\nMethodsWe downloaded the publicly available COVID-19 pandemic data from the WHO COVID-19 Dashboard website (https://covid19.who.int/) for the duration of January 11, 2020 and May 1, 2020. Then, we specified two plausible distributions of serial interval to apply the novel estimation method implemented in the incidence and EpiEstim packages to the data of daily new confirmed cases for robustly estimating R0(t) in the R software.\n\nResultsWe plotted the epidemic curves of daily new confirmed cases for the 12 selected countries. A clear peak of the epidemic curve appeared in 10 of the 12 selected countries at various time points, and then the epidemic curve declined gradually. However, the United States of America and South Africa happened to have two or more peaks and their epidemic curves either reached a plateau or still climbed up. Almost all curves of the estimated R0(t) monotonically went down to be less than or close to 1.0 up to April 30, 2020 except Singapore, South Korea, Japan, Iran, and South Africa, of which the curves surprisingly went up and down at various time periods during the COVID-19 pandemic. Finally, the United States of America and South Africa were the two countries with the approximate R0(t) [&ge;] 1.0 at the end of April, and thus they were now facing the harshest battles against the coronavirus among the 12 selected countries. By contrast, Spain, Germany, and France with smaller values of the estimated R0(t) were relatively better than the other 9 countries.\n\nConclusionSeeing the estimated R0(t) going downhill speedily is more informative than looking for the drops in the daily number of new confirmed cases during an ongoing epidemic of infectious disease. We urge public health authorities and scientists to estimate R0(t) routinely during an epidemic of infectious disease and to report R0(t) daily to the public until the end of the epidemic.",
-    "rel_num_authors": 1,
+    "rel_doi": "10.1101/2020.05.12.091314",
+    "rel_title": "Meta-analysis of transcriptomes of SARS-Cov2 infected human lung epithelial cells identifies transmembrane serine proteases co-expressed with ACE2 and biological processes related to viral entry, immunity, inflammation and cellular stress.",
+    "rel_date": "2020-05-13",
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.12.091314",
+    "rel_abs": "The COVID-19 pandemic resulting from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged in December 2019 in the Chinese city of Wuhan in the province Hubei has placed immense burden on national economies and global health. At present neither vaccination nor therapies are available although several antiviral agents such as remdesivir, originally an Ebola drug, nelfinavir, an HIV-1 protease inhibitor and other drugs such as lopinavir have been evaluated. Here, we performed a meta-analysis of RNA-sequencing data from three studies employing human lung epithelial cells. Of these one focused on lung epithelial cells infected with SARS-CoV-2. We aimed at identifying genes co-expressed with angiotensin I converting enzyme 2 (ACE2) the human cell entry receptor of SARS-CoV-2, and unveiled several genes correlated or inversely correlated with high significance, among the most significant of these was the transmembrane serine protease 4 (TMPRSS4). Serine proteases are known to be involved in the infection process by priming the virus spike protein. Pathway analysis revealed papilloma virus infection amongst the most significantly correlated pathways. Gene Ontologies revealed regulation of viral life cycle, immune responses, pro-inflammatory responses-several interleukins such as IL6, IL1, IL20 and IL33, IFI16 regulating the interferon response to a virus, chemo-attraction of macrophages, last and not least cellular stress resulting from activated Reactive Oxygen Species. We believe that this dataset will aid in a better understanding of the molecular mechanism(s) underlying COVID-19.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Fu-Chang Hu",
-        "author_inst": "National Taiwan University, College of Medicine"
+        "author_name": "Wasco Wruck",
+        "author_inst": "Heinrich-Heine-University"
+      },
+      {
+        "author_name": "James Adjaye",
+        "author_inst": "Heinrich Heine University Duesseldorf"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_no",
+    "type": "new results",
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2020.05.11.089409",
@@ -1422762,25 +1425707,41 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.09.20096420",
-    "rel_title": "Timing of non-pharmaceutical interventions to mitigate COVID-19 transmission and their effects on mobility: A cross-country analysis",
+    "rel_doi": "10.1101/2020.05.09.20096099",
+    "rel_title": "Healthcare workers preparedness for COVID-19 pandemic in the occupied Palestinian territory: a cross-sectional survey",
     "rel_date": "2020-05-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.09.20096420",
-    "rel_abs": "Non-pharmaceutical interventions (NPIs) that encourage physical distancing can decrease and delay the transmission of COVID-19. They have been implemented globally during the pandemic, however, the specific NPIs implemented and the timing of interventions has varied widely. We validated two published datasets on the implementation of NPIs globally. The health and socioeconomic factors associated with delay in implementation of NPIs was analyzed using fractional logit and probit models, and beta regression models. The probability of timely NPI implementation by a country was analyzed using a probit model. The effects of these interventions on mobility changes using Google social mobility reports, were analyzed with propensity score matching methods. Three NPIs were analyzed: national school closure, national lockdown, and global travel ban. Countries with higher incomes, larger populations, and better health preparedness measures had greater delays in implementation. Countries with greater population density, more democratic political systems, lower case detection capacity, and later arrival of first cases were more likely to implement NPIs. Implementation of lockdowns significantly reduced physical mobility. Mobility was further reduced when lockdowns were enforced with curfews or fines, or were more strictly defined. National school closures did not significantly change mobility. The implementation of NPIs is a global public good during pandemics, and the international community needs to address constraints and design incentives so countries implement NPIs in a timely manner. Further analysis is needed on the effect of NPI variations on mobility and transmission, and their associated costs.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.09.20096099",
+    "rel_abs": "BackgroundThe coronavirus disease 19 (COVID-19) pandemic threatens to overwhelm the capacity of the vulnerable healthcare system in the occupied Palestinian territory (oPt). Sufficient training of healthcare workers (HCWs) in how to manage COVID-19 and the provision of personal protective equipment (PPE) to enable them to do so will be key tools in allowing oPt to mount a credible response to the crisis.\n\nMethodsA cross-sectional study was conducted using a validated online questionnaire. Data collection occurred between March 30, 2020 and April 12, 2020. The primary outcomes were availability of PPE and HCWs preparedness in oPt for COVID-19 pandemic. The secondary outcome was the regional and hospital differences in oPt in terms of availability of PPE and HCWs preparedness.\n\nResultsOf 138 respondents, only 38 HCWs (27.5%) always had access to facemasks when needed and 15 (10.9%) for isolation gowns. The vast majority of HCWs did not find eye protection (n=128, 92.8%), N95 respirators (n=132, 95.7%), and face shields (n=127, 92%) always available. Compared to HCWs in West Bank, those in the Gaza Strip were significantly less likely to have access to alcohol sanitizers (p=0.026) and gloves (p <0.001). On average, governmental hospitals were significantly less likely to have all appropriate PPE measures than non-governmental institutions (p = 0.001). As for preparedness, only 16 (11.6%) surveyed felt confident in dealing with a potential COVID-19 case. With 57 (41.3%) having received any COVID-19 related training and 57 (41.3%) not having a local hospital protocol.\n\nConclusionHCWs in oPt are underprepared and severely lacking adequate PPE provision. The lack of local protocols, and training has left HCWs confidence exceedingly low. The lack of PPE provision will exacerbate spread of COVID-19 and deepen the crisis, whilst putting HCWs at risk.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Amit Summan",
-        "author_inst": "Center for Disease Dynamics, Economics, and Policy"
+        "author_name": "Osaid Alser",
+        "author_inst": "Ministry of Health, Gaza, occupied Palestinian territory and OxPal Medlink, UK."
       },
       {
-        "author_name": "Arindam Nandi",
-        "author_inst": "The Center for Disease Dynamics, Economics & Policy"
+        "author_name": "Heba Alghoul",
+        "author_inst": "Faculty of Medicine, Islamic University of Gaza, occupied Palestinian territory."
+      },
+      {
+        "author_name": "Zahra Alkhateeb",
+        "author_inst": "Vertex Pharmaceuticals, Boston, USA."
+      },
+      {
+        "author_name": "Ayah Hamdan",
+        "author_inst": "Harvard T.H. Chan School of Public Health, Boston, USA."
+      },
+      {
+        "author_name": "Loai Albarqouni",
+        "author_inst": "Institute for Evidence-Based Healthcare, Faculty of Health Sciences & Medicine, Bond University, Australia."
+      },
+      {
+        "author_name": "Kiran Saini",
+        "author_inst": "Medical Sciences Division, University of Oxford and OxPal Medlink, UK."
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1424364,39 +1427325,23 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.05.12.092163",
-    "rel_title": "A Computational Toolset for Rapid Identification of SARS-CoV-2, other Viruses, and Microorganisms from Sequencing Data",
+    "rel_doi": "10.1101/2020.05.13.092577",
+    "rel_title": "Lung Disease Network Reveals the Impact of Comorbidity on SARS-CoV-2 infection",
     "rel_date": "2020-05-13",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.12.092163",
-    "rel_abs": "In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms, and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input, and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction, and other pre-processing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid SARS-CoV-2 identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, MERS, and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.",
-    "rel_num_authors": 5,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.13.092577",
+    "rel_abs": "Higher mortality of COVID19 patients with comorbidity is the formidable challenge faced by the health care system. In response to the present crisis, understanding the molecular basis of comorbidity is essential to accelerate the development of potential drugs. To address this, we have measured the genetic association between COVID19 and various lung disorders and observed a remarkable resemblance. 141 lung disorders directly or indirectly linked to COVID19 result in a high-density disease-disease association network that shows a small-world property. The clustering of many lung diseases with COVID19 demonstrates a greater complexity and severity of SARS-CoV-2 infection. Furthermore, our results show that the functional protein-protein interaction modules involved RNA and protein metabolism, substantially hijacked by SARS-CoV-2, are connected to several lung disorders. Therefore we recommend targeting the components of these modules to inhibit the viral growth and improve the clinical conditions in comorbidity.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Shifu Chen",
-        "author_inst": "HaploX Biotechnology"
-      },
-      {
-        "author_name": "Changshou He",
-        "author_inst": "HaploX Biotechnology"
-      },
-      {
-        "author_name": "Yingqiang Li",
-        "author_inst": "HaploX Biotechnology"
-      },
-      {
-        "author_name": "Zhicheng Li",
-        "author_inst": "Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Charles E Melancon III",
-        "author_inst": "HaploX Biotechnology"
+        "author_name": "Asim Bikas Das",
+        "author_inst": "National Institute of Technology Warangal"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "systems biology"
   },
   {
     "rel_doi": "10.1101/2020.05.12.092379",
@@ -1425674,31 +1428619,43 @@
     "category": "allergy and immunology"
   },
   {
-    "rel_doi": "10.1101/2020.05.08.20095463",
-    "rel_title": "Using epidemic simulators for monitoring an ongoing epidemic",
+    "rel_doi": "10.1101/2020.05.08.20093229",
+    "rel_title": "Placental pathology in COVID-19",
     "rel_date": "2020-05-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095463",
-    "rel_abs": "Prediction of infection trends, estimating the efficacy of contact tracing, testing or impact of influx of infected are of vital importance for administration during an ongoing epidemic. Most effective methods currently are empirical in nature and their relation to parameters of interest to administrators are not evident. We thus propose a modified SEIRD model that is capable of modeling effect of interventions and in migrations on the progress of an epidemic. The tunable parameters of this model bear relevance to monitoring of an epidemic. This model was used to show that some of the commonly seen features of cumulative infections in real data can be explained by piece wise constant changes in interventions and population influx. We also show that the data of cumulative infections from twelve Indian states between mid March and mid April 2020 can be generated from the model by applying interventions according to a set of heuristic rules. Prediction for the next ten days based on this model, reproduced real data very well. In addition, our model also reproduced the time series of recoveries and deaths. Our work constitutes an important first step towards an effective dashboard for the monitoring of epidemic by the administration, especially in an Indian context.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20093229",
+    "rel_abs": "ObjectivesTo describe histopathologic findings in the placentas of women with COVID-19 during pregnancy.\n\nMethodsPregnant women with COVID-19 delivering between March 18, 2020 and May 5, 2020 were identified. Placentas were examined and compared to historical controls and women with placental evaluation for a history of melanoma.\n\nResults16 placentas from patients with SARS-CoV-2 were examined (15 with live birth in the 3rd trimester 1 delivered in the 2nd trimester after intrauterine fetal demise). Compared to controls, third trimester placentas were significantly more likely to show at least one feature of maternal vascular malperfusion (MVM), including abnormal or injured maternal vessels, as well as delayed villous maturation, chorangiosis, and intervillous thrombi. Rates of acute and chronic inflammation were not increased.\n\nThe placenta from the patient with intrauterine fetal demise showed villous edema and a retroplacental hematoma.\n\nConclusionsRelative to controls, COVID-19 placentas show increased prevalence of features of maternal vascular malperfusion (MVM), a pattern of placental injury reflecting abnormalities in oxygenation within the intervillous space associated with adverse perinatal outcomes. Only 1 COVID-19 patient was hypertensive despite the association of MVM with hypertensive disorders and preeclampsia. These changes may reflect a systemic inflammatory or hypercoagulable state influencing placental physiology.\n\nKey PointsO_LIThe placentas of women infected with SARS-CoV2 have higher rates maternal vascular malperfusion features compared to controls.\nC_LIO_LIMaternal vascular malperfusion has been associated with adverse perinatal outcomes, such as preeclampsia, fetal growth restriction, preterm birth, and stillbirth.\nC_LIO_LIAs the placentas of women with SARS-CoV2 show reproducible histopathologic abnormalities, these findings suggest increased antenatal surveillance for women with COVID-19 may be warranted.\nC_LI",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Mohan Raghavan",
-        "author_inst": "Indian Institute of Technology Hyderabad"
+        "author_name": "Elisheva D Shanes",
+        "author_inst": "Northwestern University"
       },
       {
-        "author_name": "Kousik Sarathy Sridharan",
-        "author_inst": "Indian Institute of Technology Hyderabad"
+        "author_name": "Leena B Mithal",
+        "author_inst": "Ann and Robert H. Lurie Children's Hospital of Chicago and Northwestern University"
       },
       {
-        "author_name": "Yashaswini M R",
-        "author_inst": "Indian Institute of Technology Hyderabad"
+        "author_name": "Sebastian Otero",
+        "author_inst": "Ann and Robert H. Lurie Children's Hospital of Chicago"
+      },
+      {
+        "author_name": "Hooman A Azad",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Emily S Miller",
+        "author_inst": "Northwestern University"
+      },
+      {
+        "author_name": "Jeffery A Goldstein",
+        "author_inst": "Northwestern University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pathology"
   },
   {
     "rel_doi": "10.1101/2020.05.11.088500",
@@ -1427251,31 +1430208,67 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.06.20093419",
-    "rel_title": "Evidence of Protective Role of Ultraviolet-B (UVB) Radiation in Reducing COVID-19 Deaths",
+    "rel_doi": "10.1101/2020.05.07.20094888",
+    "rel_title": "SARS-CoV-2 Infection Associated Hemophagocytic Lymphohistiocytosis: An autopsy series with clinical and laboratory correlation.",
     "rel_date": "2020-05-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20093419",
-    "rel_abs": "BackgroundResearch is ongoing to identify an effective way to prevent or treat COVID-19, but thus far these efforts have not yet identified a possible solution. Prior studies indicate the protective role of Ultraviolet-B (UVB) radiation in human health, mediated by vitamin D synthesis. In this study, we empirically outline a negative association of UVB radiation as measured by ultraviolet index (UVI) with the number of deaths attributed to COVID-19 (COVID- 19 deaths).\n\nMethodsWe carry out an observational study, applying a fixed-effect log-linear regression model to a panel dataset of 152 countries over a period of 108 days (n=6524). We use the cumulative number of COVID-19 deaths and case-fatality rate (CFR) as the main dependent variables to test our hypothesis and isolate UVI effect from potential confounding factors such as underlying time trends, country-specific time-constant and time-varying factors such as weather.\n\nFindingsAfter controlling for time-constant and time-varying factors, we find that a permanent unit increase in UVI is associated with a 1.2 percentage points decline in daily growth rates of cumulative COVID-19 deaths [p < 0.01] as well as a 1.0 percentage points decline in the daily growth rates of CFR [p < 0.05]. These results represent a significant percentage reduction in terms of the daily growth rates of cumulative COVID-19 deaths (-11.88%) and CFR (-38.46%). Our results are consistent across different model specifications.\n\nInterpretationWe find a significant negative association between UVI and COVID-19 deaths, indicating evidence of the protective role of UVB in mitigating COVID-19 deaths. If confirmed via clinical studies, then the possibility of mitigating COVID-19 deaths via sensible sunlight exposure or vitamin D intervention will be very attractive because it is cost-effective and widely available.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094888",
+    "rel_abs": "BackgroundA subset of COVID-19 patients exhibit clinical features of cytokine storm. However, clinicopathologic features diagnostic of hemophagocytic lymphohistiocytosis (HLH) have not been reported. Pathologic studies to date have largely focused on the pulmonary finding of diffuse alveolar damage (DAD). To this aim, we study the reticuloendothelial organs of four consecutive patients dying of COVID-19 and correlate with clinical and laboratory parameters to detect HLH.\n\nMethodsAutopsies restricted to chest and abdomen were performed on four patients who succumbed to COVID-19. Spleen, liver, and multiple pulmonary hilar/mediastinal lymph nodes were sampled in all cases. Bone marrow was obtained by rib squeeze in a subset of cases. Routine H&E staining as well as immunohistochemical staining for CD163 was performed to detect hemophagocytosis. Clinical and laboratory results from pre-mortem blood samples were used to calculate H-scores.\n\nFindingsAll four cases demonstrated DAD within the lungs. Three of the four cases had histologic evidence of hemophagocytosis within pulmonary hilar/mediastinal lymph nodes. One case showed hemophagocytosis in the spleen but none showed hemophagocytosis in liver or bone marrow. Lymphophagocytosis was the predominant form of hemophagocytosis observed. One patient showed diagnostic features of HLH with an H-score of 217 while a second patient was likely HLH with a partial H-score of 145 due to missing triglyceride level. Both patients exhibited high fever and early onset rise in serum ferritin; however, neither bicytopenia, pancytopenia, nor hypofibrinogenemia were observed in either. The remaining two patients had H-scores of 131 and 96.\n\nInterpretationThis is the first report of SARS-CoV-2 associated HLH. Identification of HLH in a subset of patients with severe COVID-19 will inform clinical trials of therapeutic strategies.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Rahul Kalippurayil Moozhipurath",
-        "author_inst": "Goethe University Frankfurt am Main"
+        "author_name": "Andrey Prilutskiy",
+        "author_inst": "Boston Medical Center"
       },
       {
-        "author_name": "Lennart Kraft",
-        "author_inst": "Goethe University Frankfurt am Main"
+        "author_name": "Michael Kritselis",
+        "author_inst": "Boston Medical Center"
       },
       {
-        "author_name": "Bernd Skiera",
-        "author_inst": "Goethe University Frankfurt am Main"
+        "author_name": "Artem Shevtsov",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Ilyas Yambayev",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Charitha Vadlamudi",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Qing Zhao",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Yachana Kataria",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Shayna Sarosiek",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Adam Lerner",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "John Mark Sloan",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Karen Quillen",
+        "author_inst": "Boston Medical Center"
+      },
+      {
+        "author_name": "Eric Burks",
+        "author_inst": "Boston Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pathology"
   },
   {
     "rel_doi": "10.1101/2020.05.08.20093708",
@@ -1428889,29 +1431882,53 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.05.20092445",
-    "rel_title": "Smoking and the risk of COVID-19 infection in the UK Biobank Prospective Study",
+    "rel_doi": "10.1101/2020.05.06.20092957",
+    "rel_title": "Associations with covid-19 hospitalisation amongst 406,793 adults: the UK Biobank prospective cohort study",
     "rel_date": "2020-05-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092445",
-    "rel_abs": "Several studies suggest a lower prevalence of smoking than expected among adults with coronavirus disease (COVID-19). We conducted logistic regression analyses of the UK Biobank prospective study of 0.5 million adults followed for an average of 11 years. Compared to women, men were more likely to be tested and to test positive. In sex-stratified analyses, current smokers had higher adjusted Odds Ratios (OR) for being tested (male OR 1.60, 95%CI 1.32-1.95 and female OR 1.50,1.21-.1.86). Current smokers were more slightly more likely than never smokers to test positive for COVID-19. Further examination of smoking as a risk factor for COVID-19 is required. These must take into account reverse causality, where smokers quit to avoid disease as well as prior diseases.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20092957",
+    "rel_abs": "OBJECTIVESTo identify the sociodemographic, lifestyle, comorbidity and antihypertensive medication associations with the development of hospitalisation with covid-19 in an English population.\n\nDESIGNProspective cohort study\n\nSETTINGThe population-based UK Biobank study was linked to English covid-19 test results.\n\nPARTICIPANTSIndividuals resident in England and alive in 2020.\n\nMAIN OUTCOME MEASURESCases (n=605) were defined by a positive covid-19 test result conducted between 16th March and 16th April 2020, during a restricted testing policy for hospitalised individuals with severe disease.\n\nRESULTSA total of 406,793 participants were included. Mean age on 1st January 2020 was 68 years (range 48 to 85 years). 55% were women. In multivariable models, major independent risk factors for hospitalisation with covid-19 were male sex (odds ratio 1.52; 95% confidence interval 1.28 to 1.81; P<0.001), South Asian ethnicity (2.02; 1.28 to 3.17; P=0.002) or black ethnicity (3.09; 2.18 to 4.38; P<0.001) compared to white ethnicity, greater residential deprivation (1.92 for most deprived quartile compared to least deprived quartile; 1.50 to 2.47; P<0.001), higher BMI (2.04 for BMI >35 compared to <25 Kg/m2; 1.50 to 2.77; P<0.001), former smoking (1.39 compared to never smoked; 1.16 to 1.66; P<0.001), and comorbidities hypertension (1.28; 1.06 to 1.53; P=0.009) and chronic obstructive pulmonary disease (1.81; 1.34 to 2.44; P<0.001). Increased risk was observed with increasing number of antihypertensive medications used rather than any individual class.\n\nCONCLUSIONUnderstanding why these factors confer increased risk of severe covid-19 in the population may help elucidate the underlying mechanisms as well as inform strategy and policy to prevent this disease and its consequences. We found no evidence of increased risk with specific classes of antihypertensive medication.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Eo Rin Cho",
-        "author_inst": "Centre for Global Health Research, St. Michael's Hospital, University of Toronto"
+        "author_name": "Anthony P Khawaja",
+        "author_inst": "Moorfields Eye Hospital and UCL Institute of Ophthalmology"
       },
       {
-        "author_name": "Arthur S Slutsky",
-        "author_inst": "Centre for Global Health Research, St. Michael's Hospital, University of Toronto"
+        "author_name": "Alasdair N Warwick",
+        "author_inst": "Institute of Cardiovascular Science, University College London"
       },
       {
-        "author_name": "Prabhat Jha",
-        "author_inst": "University of Toronto"
+        "author_name": "Pirro G Hysi",
+        "author_inst": "Department of Twin Research & Genetic Epidemiology, King's College London, St. Thomas' Hospital, London"
+      },
+      {
+        "author_name": "Alan Kastner",
+        "author_inst": "NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London"
+      },
+      {
+        "author_name": "Andrew Dick",
+        "author_inst": "NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London"
+      },
+      {
+        "author_name": "Peng T Khaw",
+        "author_inst": "NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London"
+      },
+      {
+        "author_name": "Adnan Tufail",
+        "author_inst": "NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London"
+      },
+      {
+        "author_name": "Paul J Foster",
+        "author_inst": "NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London"
+      },
+      {
+        "author_name": "Kay-Tee Khaw",
+        "author_inst": "Department of Public Health and Primary Care, University of Cambridge"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1430495,49 +1433512,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.07.20094177",
-    "rel_title": "Clinical and behavioural characteristics of self-isolating healthcare workers during the COVID-19 pandemic: a single-centre observational study",
+    "rel_doi": "10.1101/2020.05.07.20094276",
+    "rel_title": "Characteristics of 1,573 healthcare workers who underwent nasopharyngeal swab for SARS-CoV-2 in Milano, Lombardy, Italy",
     "rel_date": "2020-05-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094177",
-    "rel_abs": "ObjectivesTo describe a cohort of self-isolating healthcare workers (HCWs) with presumed COVID-19.\n\nDesignA cross-sectional, single-centre study.\n\nSettingA large, teaching hospital based in Central London with tertiary infection services.\n\nParticipants236 HCWs completed a survey distributed by internal staff email bulletin. 167 were female and 65\n\nMeasuresInformation on symptomatology, exposures and health-seeking behaviour were collected from participants by self-report.\n\nResultsThe 236 respondents reported illness compatible with COVID-19 and there was an increase in illness reporting during March 2020. Diagnostic swabs were not routinely performed.. Cough (n=179, 75.8%), fever (n=138, 58.5%), breathlessness (n=84, 35.6%) were reported. Anosmia was reported in 42.2%. Fever generally settled within 1 week (n=110, 88%). Several respondents remained at home and did not seek formal medical attention despite reporting severe breathlessness and measuring hypoxia (n=5/9, 55.6%). 2 patients required hospital admission but recovered following oxygen therapy. 84 respondents (41.2%) required greater than the obligated 7 days off work and 9 required greater than 3 weeks off.\n\nConclusionThere was a significant increase in staff reporting illness compatible with possible COVID-19 during March 2020. Conclusions cannot be drawn about exact numbers of confirmed cases due to lack of diagnostic swabbing. There were significant numbers of respondents reporting anosmia; as well as early non-specific illness prior to onset of cough and fever. This may represent pre-symptomatic HCWs who are likely to be infectious and thus criteria for isolation and swabbing should be broadened. The study also revealed concerning lack of healthcare seeking in respondents with significant red flag symptoms (severe breathlessness, hypoxia). This should be addressed urgently to reduce risk of severe disease being detected late. Finally, this study should inform trusts that HCWs may require longer than 7 days off work to recover from illness.\n\nO_LSTStrengths and limitations of this studyC_LSTO_LITo the authors knowledge, this study presents one of the first descriptive data analysis of self-reported healthcare worker (HCW) COVID-19 exposures and symptomatology in the UK.\nC_LIO_LIStudy respondents represented a broad range of job roles, including both frontline clinical and non-patient facing staff.\nC_LIO_LIThe inclusion of questions focusing on health-seeking behaviour allows results to be used to inform human resource management in the developing pandemic, and provides concerning but important data around late healthcare seeking in HCWs\nC_LIO_LIData were self-reported, cross-sectional and retrospective, which may be subject to recall bias, and the lack of diagnostic swabbing in the majority of respondents limits interpretation of the data\nC_LIO_LIFull demographic data were not collected on participants and certain staff groups may have been over-represented in the sample, which may introduce sampling bias.\nC_LI",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094276",
+    "rel_abs": "BackgroundThe management of healthcare workers (HCWs) exposed to confirmed cases of COVID-19 is still a matter of debate. It is unclear whether these subjects should be tested in the absence of symptoms and if those can guide diagnosis.\n\nMethodsOccupational and clinical characteristics of all the consecutive HCWs who performed a nasopharyngeal swab for the detection of SARS-CoV-2 in a University Hospital from February 24, 2020, to March 31, 2020, were collected. Frequencies of positive tests were compared according to selected variables. Multivariable logistic regression analyses were then applied.\n\nFindingsPositive tests were 138 among 1,573 HCWs (8.8%, 95% confidence interval [CI]: 7.4-10.3), with a marked difference between symptomatic (20.2%, 95% CI: 16.7-24.1) and asymptomatic (3.7%, 95% CI: 2.7-5.1) subjects (p<0.001). Physicians were the group with the highest frequency of positive tests (10.6%, 95% CI: 8.3-13.4) whereas clerical workers and technicians displayed the lowest frequency (2.9%, 95% CI: 0.8-7.3). The likelihood of being positive increased with the number of reported symptoms and the strongest predictors of a positive test were taste and smell alterations (odds ratio [OR] = 29.7) and fever (OR = 7.21). The median time from first positive test to a negative test was 23 days (95% CI: 19-24).\n\nInterpretationIn this Italian group of HCWs exposed to confirmed cases of COVID-19 the presence of symptoms, especially taste and smell alterations and fever, was associated with SARS-CoV-2 infection. The median time to clear the virus from nasopharynx was 23 days.\n\nFundingnone related to the content of this manuscript.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for articles published in English up to April 25, 2020, using the keywords \"SARS-CoV-2\", \"COVID-19\", \"2019-nCoV\", AND \"healthcare workers\",\"HCW\", AND \"testing\", \"nasopharyngeal swab\". We found one article: Roll-out of SARS-CoV-2 testing for healthcare workers at a large NHS Foundation Trust in the United Kingdom, March 2020 published in Euro Surveillance. Reviewing the pre-print website medRxiv with the same keywords we identified two additional studies: SARS-CoV-2 infection in Health Care Workers in a large public hospital in Madrid, Spain, during March 2020, and SARS-CoV-2 infection in 86 healthcare workers in two Dutch hospitals in March.\n\nAdded value of this studyWe showed that, even if symptomatic healthcare workers had a much higher probability of positive test, almost one third of those infected were asymptomatic. Specific symptoms, namely taste and smell alterations and fever, were strongly associated with the infection. Finally, the median time to clear the virus from nasopharynx was 23 days.\n\nImplications of all the available evidenceScreening strategies for healthcare workers exposed to COVID-19 patients should take in account the significant proportion of asymptomatic carriers and the predictive role of specific symptoms. Moreover, healthcare workers coming back to work after a positive test should be aware of the long-time of viral shedding from nasopharynx.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Angus de Wilton",
-        "author_inst": "COVID-19 Response Team, University College London Hospitals NHS Foundation Trust; Hospital of Tropical Diseases, London"
+        "author_name": "ANDREA LOMBARDI",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       },
       {
-        "author_name": "Eliz Kilich",
-        "author_inst": "COVID-19 Response Team, University College London Hospitals NHS Foundation Trust; Hospital of Tropical Diseases, London"
+        "author_name": "Dario Consonni",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       },
       {
-        "author_name": "Zain Chaudhry",
-        "author_inst": "COVID-19 Response Team, University College London Hospitals NHS Foundation Trust; Hospital of Tropical Diseases, London"
+        "author_name": "Michele Carugno",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       },
       {
-        "author_name": "Lucy CK Bell",
-        "author_inst": "COVID-19 Response Team, University College London Hospitals NHS Foundation Trust; Hospital of Tropical Diseases, London"
+        "author_name": "Giorgio Bozzi",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       },
       {
-        "author_name": "Joshua Gahir",
-        "author_inst": "COVID-19 Response Team, University College London Hospitals NHS Foundation Trust; Hospital of Tropical Diseases, London"
+        "author_name": "Davide Mangioni",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       },
       {
-        "author_name": "Jane Cadman",
-        "author_inst": "COVID-19 Response Team, University College London Hospitals NHS Foundation Trust"
+        "author_name": "Antonio Muscatello",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       },
       {
-        "author_name": "Robert A Lever",
-        "author_inst": "Hospital of Tropical Diseases, London; University College London"
+        "author_name": "Valeria Castelli",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       },
       {
-        "author_name": "Sarah Logan",
-        "author_inst": "Hospital of Tropical Diseases, London; COVID-19 Response Team, University College London Hospitals NHS Foundation Trust;"
+        "author_name": "Emanuele Palomba",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
+      },
+      {
+        "author_name": "Anna Paola Cantu'",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
+      },
+      {
+        "author_name": "Ferruccio Ceriotti",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
+      },
+      {
+        "author_name": "Basilio Tiso",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
+      },
+      {
+        "author_name": "Angela Cecilia Pesatori",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
+      },
+      {
+        "author_name": "Luciano Riboldi",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
+      },
+      {
+        "author_name": "Alessandra Bandera",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
+      },
+      {
+        "author_name": "Andrea Gori",
+        "author_inst": "IRCCS Ca' Granda Ospedale Maggiore Policlinico Foundation"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1431893,25 +1434938,53 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.06.20093492",
-    "rel_title": "Metapopulation modeling of COVID-19 advancing into the countryside: an analysis of mitigation strategies for Brazil",
+    "rel_doi": "10.1101/2020.05.06.20093476",
+    "rel_title": "Sensitivity and specificity of a rapid test for assessment of exposure to SARS-CoV-2 in a community-based setting in Brazil",
     "rel_date": "2020-05-10",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20093492",
-    "rel_abs": "Since the first case of COVID-19 was confirmed in Brazil on 19 February 2020, this epidemic has spread throughout all states and at least 2142 of 5570 municipalities up to 30 April 2020. In order to understand this spreading, we investigate a stochastic epidemic model using a metapopulation approach. Simulations are supplied with real data for mobility, demography, and confirmed cases of COVID-19 extracted from public sources. Contagion follows a compartmental epidemic model for each municipality; the latter, in turn, interact with each other through recurrent mobility. Considering the number of municipalities with confirmed COVID-19 cases, simulations can infer the level of mitigation (strong, moderate, or none) that each state is effectively adopting. Properties of the epidemic curves such as time and value of epidemic peak and outbreak duration have very broad distributions across different geographical locations. This outbreak variability is observed on several scales from state, passing through intermediate, immediate down to municipality levels. The epidemic waves start from several foci concentrated in highly populated regions and propagate towards the countryside. Correlations between delay of the epidemic outbreak and distance from the respective capital cities are strong in several states, showing propagation towards the countryside, and weak in others, signaling strong influences of multiple centers, not necessarily within the same state. Our take home message is that the responses of different regions to the same mitigation protocol can vary enormously such that the policies of combating COVID-19, such as quarantine or lockdown, must be engineered according to the region specificity but integrated with the overall situation. Even though we restricted our study to Brazil, we believe that these ideas can be generalized to other countries with continental scales and heterogeneous demographic distributions.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20093476",
+    "rel_abs": "BackgroundWhile the recommended laboratory diagnosis of COVID-19 is a molecular based assay, population-based studies to determine the prevalence of COVID-19 usually use serological assays.\n\nObjectiveTo evaluate the sensitivity and specificity of a rapid diagnostic test for COVID-19 compared to quantitative reverse transcription polymerase chain reaction (qRT-PCR).\n\nMethodsWe evaluated the sensitivity using a panel of finger prick blood samples from participants >18 years of age that had been tested for COVID-19 by qRT-PCR. For assessing specificity, we used serum samples from the 1982 Pelotas (Brazil) Birth Cohort participants collected in 2012 with no exposure to SARS-CoV-2.\n\nResultsThe sensitivity of the test was 77.1% (95% CI 66.6 - 85.6), based upon 83 subjects who had tested positive for qRT-PCR at least 10 days before the rapid diagnostic test (RDT). Based upon 100 sera samples, specificity was 98.0% (95% CI 92.9 - 99.8). There was substantial agreement (Kappa score 0.76) between the qRT-PCR results and the RDT.\n\nInterpretationThe validation results are well in line with previous assessments of the test, and confirm that it is sufficiently precise for epidemiological studies aimed at monitoring levels and trends of the COVID-19 pandemic.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Guilherme S Costa",
-        "author_inst": "Departamento de Fisica, Universidade Federal de Vicosa, Vicosa, Minas Gerais, Brazil"
+        "author_name": "Lucia C Pellanda",
+        "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre"
       },
       {
-        "author_name": "Wesley Cota",
-        "author_inst": "Departamento de Fisica, Universidade Federal de Vicosa, Vicosa, Minas Gerais, Brazil"
+        "author_name": "Eliana M Wendland",
+        "author_inst": "Universidade Federal de Ciencias da Saude de Porto Alegre"
+      },
+      {
+        "author_name": "Alan JA McBride",
+        "author_inst": "Biotechnology Department, Centre for Technological Development, Federal University of Pelotas, Brazil"
+      },
+      {
+        "author_name": "Luciana Tovo-Rodrigues",
+        "author_inst": "Post-graduate Program in Epidemiology, Federal University of Pelotas"
       },
       {
-        "author_name": "Silvio C Ferreira",
-        "author_inst": "Departamento de Fisica, Universidade Federal de Vicosa, Vicosa, Minas Gerais, Brazil and National Institute of Science and Technology for Complex Systems, Rio d"
+        "author_name": "Marcos RA Ferreira",
+        "author_inst": "Biotechnology Department, Centre for Technological Development, Federal University of Pelotas"
+      },
+      {
+        "author_name": "Odir A Dellagostin",
+        "author_inst": "Biotechnology Department, Centre for Technological Development, Federal University of Pelotas"
+      },
+      {
+        "author_name": "Mariangela F Silveira",
+        "author_inst": "Post-graduate Program in Epidemiology, Federal University of Pelotas"
+      },
+      {
+        "author_name": "Aluisio JD Barros",
+        "author_inst": "Post-graduate Program in Epidemiology, Federal University of Pelotas"
+      },
+      {
+        "author_name": "Pedro C Hallal",
+        "author_inst": "Post-graduate Program in Epidemiology, Federal University of Pelotas"
+      },
+      {
+        "author_name": "Cesar G Victora",
+        "author_inst": "Post-graduate Program in Epidemiology, Federal University of Pelotas"
       }
     ],
     "version": "1",
@@ -1433651,41 +1436724,21 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.05.05.20092122",
-    "rel_title": "Indian communitys Knowledge, Attitude & Practice towards COVID-19",
+    "rel_doi": "10.1101/2020.05.05.20092254",
+    "rel_title": "County-level factors influence the trajectory of Covid-19 incidence",
     "rel_date": "2020-05-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092122",
-    "rel_abs": "As COVID-19 pandemic has caused unprecedented human health consequences. Knowledge, attitude, perception of general population of India towards the transmission and prevention plays vital role for effective control measures. The study was conducted to assess the knowledge, attitude and practice of the general public of India on COVID-19. In this study, a web-based cross-sectional survey was conducted between 10th March to 18th April 2020. A 19-item questionnaire was generated, Cronbachs alpha was used to measure the internal consistency of the questionnaire & randomly distributed among the public using Google forms through social media networks. The chi-square test or Fischer exact test was used to compare categorical data and multiple linear regression was used to identify factor influencing KAP. Among 7978 participants, the overall knowledge, attitude and practice score was 80.64%, 97.33% and 93.8% consecutively. Majority of Indian population demonstrated preceded good knowledge, positive attitude and good practice regarding COVID-19 pandemic.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092254",
+    "rel_abs": "With new cases of Covid-19 surging in the United States, we need to better understand how the spread of novel coronavirus varies across all segments of the population. We use hierarchical exponential growth curve modeling techniques to examine whether community social and economic characteristics uniquely influence the incidence of Covid-19 cases in the urban built environment. We show that, as of May 3, 2020, confirmed coronavirus infections are concentrated along demographic and socioeconomic lines in New York City and surrounding areas, the epicenter of the Covid-19 pandemic in the United States. Furthermore, we see evidence that, after the onset of the pandemic, timely enactment of physical distancing measures such as school closures is imperative in order to limit the extent of the coronavirus spread in the population. Public health authorities must impose nonpharmaceutical measures early on in the pandemic and consider community-level factors that associate with a greater risk of viral transmission.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Balvir Singh Tomar",
-        "author_inst": "Institute of Gastroenterology Hepatology & Transplant"
-      },
-      {
-        "author_name": "Pratima Singh",
-        "author_inst": "Department of Pharmacy Practice, Nims University Rajasthan, Jaipur India"
-      },
-      {
-        "author_name": "Deepak Nathiya",
-        "author_inst": "Department of Pharmacy Practice, Nims University Rajasthan Jaipur India"
-      },
-      {
-        "author_name": "Supriya Suman",
-        "author_inst": "Department of Pharmacy Practice, Nims University Rajasthan, Jaipur India"
-      },
-      {
-        "author_name": "Preeti Raj",
-        "author_inst": "Department of Pharmacy Practice, Nims University Rajasthan, Jaipur, India"
-      },
-      {
-        "author_name": "Sandeep Tripathi",
-        "author_inst": "National Institute of Medical Sciences & Research, Nims University Rajasthan, Jaipur, India"
+        "author_name": "Ashley Wendell Kranjac",
+        "author_inst": "Chapman University"
       },
       {
-        "author_name": "Dushyant Singh Chauhan",
-        "author_inst": "Institute of Advance Sciences, Nims University Rajasthan, Jaipur, India"
+        "author_name": "Dinko Kranjac",
+        "author_inst": "University of La Verne"
       }
     ],
     "version": "1",
@@ -1435153,23 +1438206,39 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.05.05.20091637",
-    "rel_title": "Application-oriented mathematical algorithms for group testing",
+    "rel_doi": "10.1101/2020.05.08.083816",
+    "rel_title": "Intra-genome variability in the dinucleotide composition of SARS-CoV-2",
     "rel_date": "2020-05-09",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20091637",
-    "rel_abs": "Group testing is a widely used protocol which aims to test a small group of people to identify whether at least one of them is infected. It is particularly efficient if the infection rate is low, because it only requires a single test if everybody in the group is negative. The most efficient use of group testing is a complex mathematical question. However, the answer highly depends on practical parameters and restrictions, which are partially ignored by the mathematical literature. This paper aims to offer practically efficient group testing algorithms, focusing on the current COVID-19 epidemic.",
-    "rel_num_authors": 1,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.08.083816",
+    "rel_abs": "CpG dinucleotides are under-represented in the genomes of single stranded RNA viruses, and coronaviruses, including SARS-CoV-2, are no exception to this. Artificial modification of CpG frequency is a valid approach for live attenuated vaccine development, and if this is to be applied to SARS-CoV-2, we must first understand the role CpG motifs play in regulating SARS-CoV-2 replication. Accordingly, the CpG composition of the newly emerged SARS-CoV-2 genome was characterised in the context of other coronaviruses. CpG suppression amongst coronaviruses does not significantly differ according to genera of virus, but does vary according to host species and primary replication site (a proxy for tissue tropism), supporting the hypothesis that viral CpG content may influence cross-species transmission. Although SARS-CoV-2 exhibits overall strong CpG suppression, this varies considerably across the genome, and the Envelope (E) open reading frame (ORF) and ORF10 demonstrate an absence of CpG suppression. While ORF10 is only present in the genomes of a subset of coronaviruses, E is essential for virus replication. Across the Coronaviridae, E genes display remarkably high variation in CpG composition, with those of SARS and SARS-CoV-2 having much higher CpG content than other coronaviruses isolated from humans. Phylogeny indicates that this is an ancestrally-derived trait reflecting their origin in bats, rather than something selected for after zoonotic transfer. Conservation of CpG motifs in these regions suggests that they have a functionality which over-rides the need to suppress CpG; an observation relevant to future strategies towards a rationally attenuated SARS-CoV-2 vaccine.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Endre Csoka",
-        "author_inst": "Alfred Renyi Institute of Mathematics"
+        "author_name": "Paul Digard",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Hui-Min Lee",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Colin Sharp",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Finn Grey",
+        "author_inst": "University of Edinburgh"
+      },
+      {
+        "author_name": "Eleanor R Gaunt",
+        "author_inst": "University of Edinburgh"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "evolutionary biology"
   },
   {
     "rel_doi": "10.1101/2020.05.08.085308",
@@ -1436859,71 +1439928,23 @@
     "category": "nephrology"
   },
   {
-    "rel_doi": "10.1101/2020.05.04.20090316",
-    "rel_title": "Early postmortem brain MRI findings in COVID-19 non-survivors",
+    "rel_doi": "10.1101/2020.05.04.20091041",
+    "rel_title": "The Social and Economic Factors Underlying the Impact of COVID-19 Cases and Deaths in US Counties",
     "rel_date": "2020-05-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090316",
-    "rel_abs": "ImportanceThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is considered to have potential neuro-invasiveness that might lead to acute brain disorders or contribute to respiratory distress in patients with coronavirus disease 2019 (COVID-19). Brain magnetic resonance imaging (MRI) data in COVID-19 patients are scarce due to difficulties to obtain such examination in infected unstable patients during the COVID-19 outbreak.\n\nObjectiveTo investigate the occurrence of structural brain abnormalities in non-survivors of COVID-19 in a virtopsy framework.\n\nDesignProspective, case series study with postmortem brain MRI obtained early (<24h) after death.\n\nSettingMonocentric study.\n\nParticipantsFrom 31/03/2020 to 24/04/2020, consecutive decedents who fulfilled the following inclusion criteria were included: death <24 hours, SARS-CoV-2 detection on nasopharyngeal swab specimen, chest computerized tomographic (CT) scan suggestive of COVID-19, absence of known focal brain lesion, and MRI compatibility.\n\nMain Outcome(s) andMeasure(s)Signs of acute brain injury and MRI signal abnormalities along the olfactory tract and brainstem were searched independently by 3 neuroradiologists, then reviewed with neurologists and clinicians.\n\nResultsAmong the 62 patients who died from COVID-19 during the inclusion period, 19 decedents fulfilled inclusion criteria. Subcortical micro- and macro-bleeds (2 decedents), cortico-subcortical edematous changes evocative of posterior reversible encephalopathy syndrome (PRES, one decedent), and nonspecific deep white matter changes (one decedent) were observed. Asymmetric olfactory bulbs were found in 4 other decedents without downstream olfactory tract abnormalities. No brainstem MRI signal abnormality.\n\nConclusions and RelevancePostmortem brain MRI demonstrates hemorrhagic and PRES-related brain lesions in non-survivors of COVID-19 that might be triggered by the virus-induced endothelial disturbances. SARS-CoV-2-related olfactory impairment seems to be limited to olfactory bulbs. The absence of brainstem MRI abnormalities does not support a brain-related contribution to respiratory distress in COVID-19.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSIs there common brain MRI abnormalities patterns in non-survivors of coronavirus disease 2019 ?\n\nFindingsIn a case series of 19 non-survivors of severe COVID-19 disease, early postmortem brain MRI demonstrated patterns evocative of intracranial vasculopathy in 4 decedents: subcortical micro- and macro-bleeds (2 decedents), cortico-subcortical edematous changes evocative of posterior reversible encephalopathy syndrome (PRES, one decedent), and nonspecific deep white matter changes (one decedent). Asymmetric olfactory bulbs were found in 4 other decedents but without downstream olfactory tract abnormalities.\n\nMeaningPostmortem brain MRI demonstrates hemorrhagic and PRES-related brain lesions in non-survivors of COVID-19 that might be triggered by virus-induced endothelial disturbances.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20091041",
+    "rel_abs": "This paper uncovers the socioeconomic and health/lifestyle factors that can explain the differential impact of the coronavirus pandemic on different parts of the United States. Using a dynamic panel representation of an epidemiological model of disease spread, the paper develops a Vulnerability Index for US counties from daily reported number of cases over a 20-day period of rapid disease growth. County-level economic, demographic, and health factors are used to explain the differences in the values of this index and thereby the transmission and concentration of the disease across the country. These factors are also used to examine the number of reported deaths. The paper finds that counties with high median income have a high incidence of cases but reported lower deaths. Income inequality as measured by the Gini coefficient, is found to be associated with more deaths and more cases. The remarkable similarity in the distribution of cases across the country and the distribution of distance-weighted international passengers served by the top international airports is evidence of the spread of the virus by way of international travel. The distributions of age, race, and health risk factors such as obesity and diabetes are found to be particularly significant factors in explaining the differences in mortality across counties. Counties with better access to health care as measured by the number of primary care physicians per capita have lower deaths, and so do places with more health awareness as measured by flu vaccination prevalence. Environmental health conditions such as the amount of air pollution is found to be associated with counties with higher deaths from the virus. It is hoped that research such as these will help policymakers to develop risk factors for each region of the country to better contain the spread of infectious diseases in the future.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Tim Coolen",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Valentina Lolli",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Niloufar Sadeghi",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Antonin Rovai",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Nicola Trotta",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Fabio S Taccone",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Jacques Creteur",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Sophie Henrard",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Jean-Christophe Goffard",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Olivier Dewitte",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Gilles Naeije",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Serge Goldman",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
-      },
-      {
-        "author_name": "Xavier De Tiege",
-        "author_inst": "CUB Hopital Erasme, Universite libre de Bruxelles, Brussels, Belgium"
+        "author_name": "Nivedita Mukherji",
+        "author_inst": "Oakland University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "neurology"
+    "category": "health economics"
   },
   {
     "rel_doi": "10.1101/2020.05.04.20090993",
@@ -1438765,59 +1441786,35 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2020.05.08.084061",
-    "rel_title": "Comparison of SARS-CoV-2 spike protein binding to human, pet, farm animals, and putative intermediate hosts ACE2 and ACE2 receptors",
+    "rel_doi": "10.1101/2020.05.08.084384",
+    "rel_title": "ACE2 coding variants in different populations and their potential impact on SARS-CoV-2 binding affinity",
     "rel_date": "2020-05-08",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.08.084061",
-    "rel_abs": "The emergence of a novel coronavirus, SARS-CoV-2, resulted in a pandemic. Here, we used recently released X-ray structures of human ACE2 bound to the receptor-binding domain (RBD) of the spike protein (S) from SARS-CoV-2 to predict its binding to ACE2 proteins from different animals, including pets, farm animals, and putative intermediate hosts of SARS-CoV-2. Comparing the interaction sites of ACE2 proteins known to serve or not serve as receptor allows to define residues important for binding. From the 20 amino acids in ACE2 that contact S up to seven can be replaced and ACE2 can still function as the SARS-CoV-2 receptor. These variable amino acids are clustered at certain positions, mostly at the periphery of the binding site, while changes of the invariable residues prevent S-binding or infection of the respective animal. Some ACE2 proteins even tolerate the loss or the acquisition of N-glycosylation sites located near the S-interface. Of note, pigs and dogs which are not or not effectively infected, respectively, have only a few changes in the binding site have relatively low levels of ACE2 in the respiratory tract. Comparison of the RBD of S of SARS-CoV-2 with viruses from bat and pangolin revealed that the latter contains only one substitution, whereas the bat virus exhibits five. However, ACE2 of pangolin exhibit seven changes relative to human ACE2, a similar number of substitutions is present in ACE2 of bats, raccoon, and civet suggesting that SARS-CoV-2 may not especially adapted to ACE2 of any of its putative intermediate hosts. These analyses provide new insight into the receptor usage and animal source/origin of SARS-COV-2.\n\nIMPORTANCESARS-CoV-2 is threatening people worldwide and there are no drugs or vaccines available to mitigate its spread. The origin of the virus is still unclear and whether pets and livestock can be infected and transmit SARS-CoV-2 are important and unknown scientific questions. Effective binding to the host receptor ACE2 is the first prerequisite for infection of cells and determines the host range. Our analysis provides a framework for the prediction of potential hosts of SARS-CoV-2. We found that ACE2 from species known to support SARS-CoV-2 infection tolerate many amino acid changes indicating that the species barrier might be low. However, the lower expression of ACE2 in the upper respiratory tract of some pets and livestock means more research and monitoring should be done to explore the animal source of infection and the risk of potential cross-species transmission. Finally, the analysis also showed that SARS-CoV-2 may not specifically adapted to any of its putative intermediate hosts.",
-    "rel_num_authors": 10,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.08.084384",
+    "rel_abs": "The susceptibility of different populations to the SARS-CoV-2 infection is not yet understood. A deeper analysis of the genomes of individuals from different populations might explain their risk for infection. In this study, a combined analysis of ACE2 coding variants in different populations and computational chemistry calculations are conducted in order to probe the potential effects of ACE2 coding variants on SARS-CoV-2/ACE2 binding affinity. Our study reveals novel interaction data on the variants and SARS-CoV-2. We could show that ACE2-K26R; which is more frequent in the Ashkenazi Jewish population decrease the electrostatic attraction between SARS-CoV-2 and ACE2. On the contrary, ACE2-I468V, R219C, K341R, D206G, G211R were found to increase the electrostatic attraction and increase the binding to SARS-CoV-2; ordered by the strength of binding from weakest to strongest. I468V, R219C, K341R, D206G and G211R were more frequent in East Asian, South Asian, African and African American, European and European and South Asian populations, respectively. SARS-CoV-2/ACE2 interface in the WT protein and corresponding variants is showed to be a dominated by van der Waals (vdW) interactions. All the mutations except K341R induce an increase in the vdW attractions between the ACE2 and the SARS-CoV-2. The largest increase of is observed for the R219C mutant.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Xiaofeng Zhai",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
+        "author_name": "Fedaa Ali",
+        "author_inst": "Zewail City of Science and Technology"
       },
       {
-        "author_name": "Jiumeng Sun",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
-      },
-      {
-        "author_name": "Ziqing Yan",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
-      },
-      {
-        "author_name": "Jie Zhang",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
-      },
-      {
-        "author_name": "Jin Zhao",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
-      },
-      {
-        "author_name": "Zongzheng Zhao",
-        "author_inst": "Institute of Military Veterinary, Academy of Military Medical Sciences, Changchun, China."
-      },
-      {
-        "author_name": "Qi Gao",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
-      },
-      {
-        "author_name": "Wan-Ting He",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
+        "author_name": "Menattallah Elserafy",
+        "author_inst": "Zewail City of Science and Technology"
       },
       {
-        "author_name": "Michael Veit",
-        "author_inst": "Institute for Virology, Center for Infection Medicine, Veterinary Faculty, Free University Berlin, Berlin, Germany."
+        "author_name": "Mohamed Alkordi",
+        "author_inst": "Zewail City of Science and Technology"
       },
       {
-        "author_name": "Shuo Su",
-        "author_inst": "MOE Joint International Research Laboratory of Animal Health and Food Safety, Engineering Laboratory of Animal Immunity of Jiangsu Province, College of Veterina"
+        "author_name": "Muhamed Amin",
+        "author_inst": "University of Groningen"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "bioinformatics"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2020.05.05.078758",
@@ -1440263,101 +1443260,29 @@
     "category": "hiv aids"
   },
   {
-    "rel_doi": "10.1101/2020.05.04.20090076",
-    "rel_title": "Infection fatality rate of SARS-CoV-2 infection in a German community with a super-spreading event",
+    "rel_doi": "10.1101/2020.05.04.20090555",
+    "rel_title": "Laboratory findings associated with mechanical ventilation requirement and mortality among hospitalized individuals with Covid-19 in Eastern Massachusetts",
     "rel_date": "2020-05-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090076",
-    "rel_abs": "The world faces an unprecedented SARS-CoV2 pandemic where many critical factors still remain unknown. The case fatality rates (CFR) reported in the context of the SARS-CoV-2 pandemic substantially differ between countries. For SARS-CoV-2 infection with its broad clinical spectrum from asymptomatic to severe disease courses, the infection fatality rate (IFR) is the more reliable parameter to predict the consequences of the pandemic. Here we combined virus RT-PCR testing and assessment for SARS-CoV2 antibodies to determine the total number of individuals with SARS-CoV-2 infections in a given population.\n\nMethodsA sero-epidemiological GCP- and GEP-compliant study was performed in a small German town which was exposed to a super-spreading event (carnival festivities) followed by strict social distancing measures causing a transient wave of infections. Questionnaire-based information and biomaterials were collected from a random, household-based study population within a seven-day period, six weeks after the outbreak. The number of present and past infections was determined by integrating results from anti-SARS-CoV-2 IgG analyses in blood, PCR testing for viral RNA in pharyngeal swabs and reported previous positive PCR tests.\n\nResultsOf the 919 individuals with evaluable infection status (out of 1,007; 405 households) 15.5% (95% CI: [12.3%; 19.0%]) were infected. This is 5-fold higher than the number of officially reported cases for this community (3.1%). Infection was associated with characteristic symptoms such as loss of smell and taste. 22.2% of all infected individuals were asymptomatic. With the seven SARS-CoV-2-associated reported deaths the estimated IFR was 0.36% [0.29%; 0.45%]. Age and sex were not found to be associated with the infection rate. Participation in carnival festivities increased both the infection rate (21.3% vs. 9.5%, p<0.001) and the number of symptoms in the infected (estimated relative mean increase 1.6, p=0.007). The risk of a person being infected was not found to be associated with the number of study participants in the household this person lived in. The secondary infection risk for study participants living in the same household increased from 15.5% to 43.6%, to 35.5% and to 18.3% for households with two, three or four people respectively (p<0.001).\n\nConclusionsWhile the number of infections in this high prevalence community is not representative for other parts of the world, the IFR calculated on the basis of the infection rate in this community can be utilized to estimate the percentage of infected based on the number of reported fatalities in other places with similar population characteristics. Whether the specific circumstances of a super-spreading event not only have an impact on the infection rate and number of symptoms but also on the IFR requires further investigation. The unexpectedly low secondary infection risk among persons living in the same household has important implications for measures installed to contain the SARS-CoV-2 virus pandemic.",
-    "rel_num_authors": 21,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090555",
+    "rel_abs": "ImportanceThe coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented stress on health systems across the world, and reliable estimates of risk for adverse hospital outcomes are needed.\n\nObjectiveTo quantify admission laboratory and comorbidity features associated with critical illness and mortality risk across 6 Eastern Massachusetts hospitals.\n\nDesignRetrospective cohort study using hospital course, prior diagnoses, and laboratory values.\n\nSettingEmergency department and inpatient settings from 2 academic medical centers and 4 community hospitals.\n\nParticipantsAll individuals with hospital admission and positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by PCR testing across these 6 hospitals through June 5, 2020.\n\nExposureCoronavirus 2 (SARS-CoV-2).\n\nMain Outcome MeasuresSevere illness defined by ICU admission, mechanical ventilation, or death.\n\nResultsAmong 2,511 hospitalized individuals who tested positive for SARS-CoV-2 (of whom 50.9% were male, 53.9% white, and 27.0% Hispanic, with mean age 62.6 years), 215 (8.6%) were admitted to the ICU, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. L1-regression models developed in 3 of these hospitals yielded area under ROC curve (AUC) of 0.807 for severe illness and 0.847 for mortality in the 3 held-out hospitals. In total, 212/292 (78%) of the deaths occurred in the highest-risk mortality quintile.\n\nConclusions and RelevanceIn this cohort, specific admission laboratory studies in concert with sociodemographic features and prior diagnosis facilitated risk stratification among individuals hospitalized for COVID-19.\n\nFunding1R56MH115187-01\n\nTrial RegistrationNone\n\nKey PointsO_ST_ABSQuestionC_ST_ABSHow well can sociodemographic features, laboratory values, and comorbidities of individuals hospitalized with coronavirus disease 2019 (COVID-19) in Eastern Massachusetts through June 5, 2020 predict severe illness course?\n\nFindingsIn this cohort study of 2,511 hospitalized individuals positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by PCR who were admitted to one of six hospitals, 215 (8.6%) were admitted to the ICU, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. In a risk prediction model, 212 (78%) deaths occurred in the top mortality-risk quintile.\n\nMeaningSimple prediction models may assist in risk stratification among hospitalized COVID-19 patients.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Hendrik Streeck",
-        "author_inst": "Institute of Virology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Bianca Schulte",
-        "author_inst": "Institute of Virology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Beate Kuemmerer",
-        "author_inst": "Institute of Virology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Enrico Richter",
-        "author_inst": "Institute of Virology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Tobias Hoeller",
-        "author_inst": "Clinical Study Core Unit, Study Centre Bonn (SZB), University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Christine Fuhrmann",
-        "author_inst": "Clinical Study Core Unit, Study Centre Bonn (SZB), University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Eva Bartok",
-        "author_inst": "Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Ramona Dolscheid",
-        "author_inst": "Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Moritz Berger",
-        "author_inst": "Institute for Medical Biometry, Informatics and Epidemiology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Lukas Wessendorf",
-        "author_inst": "Institute of Virology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Monika Eschbach-Bludau",
-        "author_inst": "Institute of Virology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Angelika Kellings",
-        "author_inst": "Clinical Study Core Unit, Study Centre Bonn (SZB), University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Astrid Schwaiger",
-        "author_inst": "Biobank Core Unit, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Martin Coenen",
-        "author_inst": "Clinical Study Core Unit, Study Centre Bonn (SZB), University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Per Hoffmann",
-        "author_inst": "Institute of Human Genetics, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Markus Noethen",
-        "author_inst": "Institute of Human Genetics, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Anna-Maria Eis-Huebinger",
-        "author_inst": "Institute of Virology, University Hospital, University of Bonn, Germany"
-      },
-      {
-        "author_name": "Martin Exner",
-        "author_inst": "Institute for Hygiene and Public Health, University Hospital, University of Bonn"
-      },
-      {
-        "author_name": "Ricarda Schmithausen",
-        "author_inst": "Institute for Hygiene and Public Health, University Hospital, University of Bonn"
+        "author_name": "Victor M Castro",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Matthias Schmid",
-        "author_inst": "Institute for Medical Biometry, Informatics and Epidemiology, University Hospital, University of Bonn, Germany"
+        "author_name": "Thomas H McCoy Jr.",
+        "author_inst": "Massachusetts General Hospital"
       },
       {
-        "author_name": "Gunther Hartmann",
-        "author_inst": "Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital, University of Bonn, Germany; German Center for Infection Research (DZIF), partne"
+        "author_name": "Roy H Perlis",
+        "author_inst": "Massachusetts General Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1442085,31 +1445010,47 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.05.06.20092858",
-    "rel_title": "Spatial Network based model forecasting transmission and control of COVID-19",
+    "rel_doi": "10.1101/2020.05.03.20089938",
+    "rel_title": "Protocol for a systematic review of qualitative and quantitative effects of cardiovascular disease risk communication using heart age concepts",
     "rel_date": "2020-05-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20092858",
-    "rel_abs": "The SARS-CoV-2 driven infectious novel coronavirus disease (COVID-19) has been declared a pandemic by virtue of its brutal impact on the world in terms of loss on human life, health, economy, and other crucial resources. With the aim to explore more about its aspects, we adopted the SEIQRD (Susceptible-Exposed-Infected-Quarantine-Recovered-Death) pandemic spread with a time delay on the heterogeneous population and geography in this work. Focusing on the spatial heterogeneity, the entire population of interest in a region is divided into small distinct geographical sub regions, which interact by means of migration networks across boundaries. Utilizing the estimations of the time delay differential equations based model, we analyzed the spread dynamics of disease in a region and its sub regions. The model based numerical outcomes are validated from real time available data for India. We computed the approximate peak infection in forward time and relative timespan when disease outspread halts. To further evaluate the influence of the delay on the long term system dynamics, the sensitivity analysis is performed on time delay. The most crucial parameter, basic reproduction number R0 and its time-dependent generalization, has been estimated at both regional and sub regional levels. The impact of the most significant lockdown measure that has been implemented in India to contain the pandemic spread has been extensively studied by considering no lockdown scenario. A suggestion based on outcomes, for a bit relaxed lockdown, followed by an extended period of strict social distancing as one of the most effective control measures to manage COVID-19 spread is provided for India.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20089938",
+    "rel_abs": "IntroductionThe concept of  heart age is increasingly used for health promotion and alongside clinical guidelines for cardiovascular disease (CVD) prevention. These tools have been used by millions of consumers around the world, and many health organisations promote them as a way of encouraging lifestyle change. However, heart age tools vary widely in terms of their underlying risk models and display formats, the effectiveness of these tools compared to other CVD risk communication formats remains unclear, and doctors have raised concerns over their use to expand testing of healthy low risk adults.\n\nMethods and analysisWe aim to systematically review both qualitative and quantitative evidence of the effects of heart age when presented to patients or consumers for the purpose of CVD risk communication. Four electronic databases will be search until April 2020 and reference lists from similar review articles will be searched. Studies will be considered eligible if they meet the following criteria: (1) published from the inception of the database to April 2020, in peer-reviewed journals, (2) used an adult population (over 18 years of age) or, if not explicit regarding age, are clear that participants were not children, (3) present the concept of  heart age to patients or consumers for the purpose of CVD risk communication, (4) report qualitative themes or quantitative outcomes relating to psychological and/or behavioural responses to heart age. Two reviewers will perform study selection, data extraction and quality assessment. Reporting of the review will be informed by Preferred Reporting Items for Systematic Review and Meta-Analysis guidance.\n\nEthics and disseminationEthical approval is not required as it is a protocol for a systematic review. Findings will be disseminated through peer-reviewed publications and conference presentations.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Arvind Kumar Gupta",
-        "author_inst": "Indian Institute of Technology Ropar"
+        "author_name": "Carissa Bonner",
+        "author_inst": "University of Sydney"
       },
       {
-        "author_name": "Natasha Sharma",
-        "author_inst": "Kanya Maha Vidyalaya, Jalandhar"
+        "author_name": "Samuel Cornell",
+        "author_inst": "University of Sydney"
+      },
+      {
+        "author_name": "Carys Batcup",
+        "author_inst": "University of Sydney"
       },
       {
-        "author_name": "Atul Kumar Verma",
-        "author_inst": "Indian Institute of Technology, Ropar"
+        "author_name": "Michael Fajardo",
+        "author_inst": "University of Sydney"
+      },
+      {
+        "author_name": "Jenny Doust",
+        "author_inst": "University of Queensland"
+      },
+      {
+        "author_name": "Kevin McGeechan",
+        "author_inst": "University of Sydney"
+      },
+      {
+        "author_name": "Lyndal Trevena",
+        "author_inst": "University of Sydney"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "cardiovascular medicine"
   },
   {
     "rel_doi": "10.1101/2020.05.03.20089375",
@@ -1443542,43 +1446483,67 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.05.06.074039",
-    "rel_title": "The heterogeneous landscape and early evolution of pathogen-associated CpG and UpA dinucleotides in SARS CoV-2",
+    "rel_doi": "10.1101/2020.05.07.082487",
+    "rel_title": "COVID-19: Viral-host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection.",
     "rel_date": "2020-05-07",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.06.074039",
-    "rel_abs": "COVID-19 can lead to acute respiratory syndrome, which can be due to dysregulated immune signaling. We analyze the distribution of CpG dinucleotides, a pathogen-associated molecular pattern, in the SARS-CoV-2 genome. We find that the CpG content, which we characterize by a force parameter that accounts for statistical constraints acting on the genome at the nucleotidic and amino-acid levels, is, on average, low compared to other pathogenic betacoronaviruses. However, the CpG force widely fluctuates along the genome, with a particularly low value, comparable to the circulating seasonal HKU1, in the spike coding region and a greater value, comparable to SARS and MERS, in the highly expressed nucleocapside coding region (N ORF), whose transcripts are relatively abundant in the cytoplasm of infected cells and present in the 3UTRs of all subgenomic RNA. This dual nature of CpG content could confer to SARS-CoV-2 the ability to avoid triggering pattern recognition receptors upon entry, while eliciting a stronger response during replication. We then investigate the evolution of synonymous mutations since the outbreak of the COVID-19 pandemic, finding a signature of CpG loss in regions with a greater CpG force. Sequence motifs preceding the CpG-loss-associated loci in the N ORF match recently identified binding patterns of the Zinc finger Anti-viral Protein. Using a model of the viral gene evolution under human host pressure, we find that synonymous mutations seem driven in the SARS-CoV-2 genome, and particularly in the N ORF, by the viral codon bias, the transition-transversion bias and the pressure to lower CpG content.",
-    "rel_num_authors": 6,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.07.082487",
+    "rel_abs": "BackgroundEpidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and proteomic data on the host response against SARS-CoV-2 still have anecdotic character; currently available data from other coronavirus infections are therefore a key source of information.\n\nMethodsWe investigated selected molecular aspects of three human coronavirus (HCoV) infections, namely SARS-CoV, MERS-CoV and HCoV-229E, through a network based-approach. A functional analysis of HCoV-host interactome was carried out in order to provide a theoretic host-pathogen interaction model for HCoV infections and in order to translate the results in prediction for SARS-CoV-2 pathogenesis.\n\nThe 3D model of S-glycoprotein of SARS-CoV-2 was compared to the structure of the corresponding SARS-CoV, HCoV-229E and MERS-CoV S-glycoprotein. SARS-CoV, MERS-CoV, HCoV-229E and the host interactome were inferred through published protein-protein interactions (PPI) as well as gene co-expression, triggered by HCoV S-glycoprotein in host cells.\n\nResultsAlthough the amino acid sequences of the S-glycoprotein were found to be different between the various HCoV, the structures showed high similarity, but the best 3D structural overlap shared by SARS-CoV and SARS-CoV-2, consistent with the shared ACE2 predicted receptor. The host interactome, linked to the S-glycoprotein of SARS-CoV and MERS-CoV, mainly highlighted innate immunity pathway components, such as Toll Like receptors, cytokines and chemokines.\n\nConclusionsIn this paper, we developed a network-based model with the aim to define molecular aspects of pathogenic phenotypes in HCoV infections. The resulting pattern may facilitate the process of structure-guided pharmaceutical and diagnostic research with the prospect to identify potential new biological targets.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Andrea Di Gioacchino",
-        "author_inst": "Ecole Normale Superieure, PSL and CNRS"
+        "author_name": "Francesco Messina",
+        "author_inst": "National Instritute for Infectious Diseases \"L. Spallanzani\" - IRCCS"
       },
       {
-        "author_name": "Petr Sulc",
-        "author_inst": "Arizona State University"
+        "author_name": "Emanuela Giombini",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
       },
       {
-        "author_name": "Anastassia V Komarova",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Chiara Agrati",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
       },
       {
-        "author_name": "Benjamin D Greenbaum",
-        "author_inst": "Memorial Sloan Kettering Cancer Center"
+        "author_name": "Francesco Vairo",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
       },
       {
-        "author_name": "Remi Monasson",
-        "author_inst": "Ecole Normale Superieure, PSL and CNRS"
+        "author_name": "Tommaso Ascoli Bartoli",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
       },
       {
-        "author_name": "Simona Cocco",
-        "author_inst": "Ecole Normale Superieure, PSL and CNRS"
+        "author_name": "Samir Al Moghazi",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
+      },
+      {
+        "author_name": "Mauro Piancentini",
+        "author_inst": "Department of Biology, University of Rome \"Tor Vergata,\" Rome, Italy."
+      },
+      {
+        "author_name": "Markus Maeurer",
+        "author_inst": "Champalimaud Centre for the Unknown, Lisbon, Portugal; I. Medizinische Klinik Johannes Gutenberg-Universitat, University of Mainz, 55131 Mainz, Germany."
+      },
+      {
+        "author_name": "Alimuddin Zumla",
+        "author_inst": "Department of Infection, Division of Infection and Immunity, University College London, and National Institutes of Health and Research Biomedical Research Centr"
+      },
+      {
+        "author_name": "Maria R. Capobianchi",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
+      },
+      {
+        "author_name": "Francesco Nicola Lauria",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
+      },
+      {
+        "author_name": "Giuseppe Ippolito",
+        "author_inst": "National Institute for Infectious Diseases \"Lazzaro Spallanzani\" IRCCS, Rome, Italy."
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "genomics"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2020.05.07.082909",
@@ -1444888,105 +1447853,113 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.06.080119",
-    "rel_title": "Multiple SARS-CoV-2 introductions shaped the early outbreak in Central Eastern Europe: comparing Hungarian data to a worldwide sequence data-matrix",
+    "rel_doi": "10.1101/2020.05.05.079202",
+    "rel_title": "Neutralization of SARS-CoV-2 by destruction of the prefusion Spike",
     "rel_date": "2020-05-06",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.06.080119",
-    "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 is the third highly pathogenic human coronavirus in history. Since the emergence in Hubei province, China, during late 2019 the situation evolved to pandemic level. Following China, Europe was the second epicenter of the pandemic. To better comprehend the detailed founder mechanisms of the epidemic evolution in Central-Eastern Europe, particularly in Hungary, we determined the full-length SARS-CoV-2 genomes from 32 clinical samples collected from laboratory confirmed COVID-19 patients over the first month of disease in Hungary. We applied a haplotype network analysis on all available complete genomic sequences of SARS-CoV-2 from GISAID database as of the 21th of April, 2020. We performed additional phylogenetic and phylogeographic analyses to achieve the recognition of multiple and parallel introductory events into our region. Here we present a publicly available network imaging of the worldwide haplotype relations of SARS-CoV-2 sequences and conclude the founder mechanisms of the outbreak in Central-Eastern Europe.",
-    "rel_num_authors": 22,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.05.079202",
+    "rel_abs": "There are as yet no licenced therapeutics for the COVID-19 pandemic. The causal coronavirus (SARS-CoV-2) binds host cells via a trimeric Spike whose receptor binding domain (RBD) recognizes angiotensin-converting enzyme 2 (ACE2), initiating conformational changes that drive membrane fusion. We find that monoclonal antibody CR3022 binds the RBD tightly, neutralising SARS-CoV-2 and report the crystal structure at 2.4 [A] of the Fab/RBD complex. Some crystals are suitable for screening for entry-blocking inhibitors. The highly conserved, structure-stabilising, CR3022 epitope is inaccessible in the prefusion Spike, suggesting that CR3022 binding would facilitate conversion to the fusion-incompetent post-fusion state. Cryo-EM analysis confirms that incubation of Spike with CR3022 Fab leads to destruction of the prefusion trimer. Presentation of this cryptic epitope in an RBD-based vaccine might advantageously focus immune responses. Binders at this epitope may be useful therapeutically, possibly in synergy with an antibody blocking receptor attachment.\n\nHighlightsO_LICR3022 neutralises SARS-CoV-2\nC_LIO_LINeutralisation is by destroying the prefusion SPIKE conformation\nC_LIO_LIThis antibody may have therapeutic potential alone or with one blocking receptor attachment\nC_LI",
+    "rel_num_authors": 24,
     "rel_authors": [
       {
-        "author_name": "Gabor Kemenesi",
-        "author_inst": "University of Pecs"
+        "author_name": "Jiandong Huo",
+        "author_inst": "University of Oxford and The Rosalind Franklin Institute"
       },
       {
-        "author_name": "Safia Zeghbib",
-        "author_inst": "University of Pecs"
+        "author_name": "Yuguang Zhao",
+        "author_inst": "University of Oxford."
       },
       {
-        "author_name": "Balazs Somogyi",
-        "author_inst": "University of Pecs"
+        "author_name": "Jingshan Ren",
+        "author_inst": "University of Oxford."
       },
       {
-        "author_name": "Gabor E Toth",
-        "author_inst": "University of Pecs"
+        "author_name": "Daming Zhou",
+        "author_inst": "University of Oxford."
       },
       {
-        "author_name": "Krisztian Banyai",
-        "author_inst": "Centre for Agricultural Research, Hungary"
+        "author_name": "Helen M E Duyvesteyn",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Norbert Solymosi",
-        "author_inst": "University of Veterinary Medicine Budapest"
+        "author_name": "Helen M Ginn",
+        "author_inst": "Diamond Light Source Ltd"
       },
       {
-        "author_name": "Peter M Szabo",
-        "author_inst": "Stromal Biology, Bristol-Myers Squibb, Princeton"
+        "author_name": "Loic Carrique",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Istvan Szabo",
-        "author_inst": "National Food Safety Office, Budapest"
+        "author_name": "Tomas Malinauskas",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Adam Balint",
-        "author_inst": "National Food Safety Office, Budapest"
+        "author_name": "Reinis R Ruza",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Peter Urban",
-        "author_inst": "Szentagothai Research Centre, Bioinformatics Research Group"
+        "author_name": "Pranav NM Shah",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Robert Herczeg",
-        "author_inst": "Szentagothai Research Centre, Bioinformatics Research Group"
+        "author_name": "Tiong Kit Tan",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Attila Gyenesei",
-        "author_inst": "Szentagothai Research Centre, Bioinformatics Research Group"
+        "author_name": "Pramila Rijal",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Naomi Coombes",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Agnes Nagy",
-        "author_inst": "Hungarian Defense Forces, Military Medical Centre"
+        "author_name": "Kevin Bewley",
+        "author_inst": "Public Health England"
       },
       {
-        "author_name": "Csaba I Pereszlenyi",
-        "author_inst": "Hungarian Defense Forces, Military Medical Centre"
+        "author_name": "Julika Radecke",
+        "author_inst": "Diamond Light Source Ltd"
       },
       {
-        "author_name": "Gergely Babinszky",
-        "author_inst": "Hungarian Defense Forces, Military Medical Centre"
+        "author_name": "Neil G Paterson",
+        "author_inst": "Diamond Light Source Ltd"
       },
       {
-        "author_name": "Gabor Dudas",
-        "author_inst": "Hungarian Defense Forces, Military Medical Centre"
+        "author_name": "Piyasa Supasa",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Gabriella Terhes",
-        "author_inst": "Institute of Clinical Microbiology, University of Szeged"
+        "author_name": "Juthathip Mongkolsapaya",
+        "author_inst": "University of Oxford and Mahidol University"
       },
       {
-        "author_name": "Viktor Zoldi",
-        "author_inst": "Independent researcher, Vantaa, Finland"
+        "author_name": "Gavin R Screaton",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Robert Lovas",
-        "author_inst": "Institute for Computer Science and Control, Hungarian Academy of Sciences"
+        "author_name": "Miles Carroll",
+        "author_inst": "Public Health England and University of Oxford"
       },
       {
-        "author_name": "Szabolcs Tenczer",
-        "author_inst": "Institute for Computer Science and Control, Hungarian Academy of Sciences"
+        "author_name": "Alain Townsend",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Laszlo Kornya",
-        "author_inst": "Central Hospital of Southern Pest, Budapest"
+        "author_name": "Elizabeth E Fry",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Ferenc Jakab",
-        "author_inst": "University of Pecs"
+        "author_name": "Raymond J Owens",
+        "author_inst": "University of Oxford and The Rosalind Franklin Institute"
+      },
+      {
+        "author_name": "David I Stuart",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
     "category": "microbiology"
   },
@@ -1446450,69 +1449423,21 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.05.01.20086801",
-    "rel_title": "Efficient prevalence estimation and infected sample identification with group testing for SARS-CoV-2",
+    "rel_doi": "10.1101/2020.05.02.20084947",
+    "rel_title": "Voluntary Cyclical Distancing: A potential alternative to constant level mandatory social distancing, relying on an 'infection weather report'",
     "rel_date": "2020-05-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20086801",
-    "rel_abs": "Extensive virological testing is central to SARS-CoV-2 containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combine a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence, and to ratify losses in sensitivity against the time course of individual infections. Using this framework, we show that prevalence can be accurately estimated across four orders of magnitude using only a few dozen pooled tests without the need for individual identification. We then exhaustively evaluate the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many positives compared to individual testing with a given budget. We illustrate how pooling affects sensitivity and overall detection capacity during an epidemic and on each day post infection, finding that sensitivity loss is mainly attributed to individuals sampled at the end of infection when detection for public health containment has minimal benefit. Crucially, we confirm that our theoretical results can be accurately translated into practice using pooled human nasopharyngeal specimens. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect epidemiologically relevant infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20084947",
+    "rel_abs": "1COVID-19 has significantly changed our daily lives. Stay-at-home orders and forced closings of all non-essential businesses has had a significant impact on our economy. While it is important to ensure that the healthcare system is not overwhelmed, there are many questions that remain about the efficacy of extreme social distancing, and whether there are alternatives to mandatory lockdowns. This paper analyzes the utility of various levels of social distancing, and suggests an alternative approach using voluntary distancing informed by an infectious load index or  infection weather report.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Brian Cleary",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "James A Hay",
-        "author_inst": "Harvard T H Chan School of Public Health"
-      },
-      {
-        "author_name": "Brendan Blumenstiel",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "Maegan Harden",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "Michelle Cipicchio",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "Jon Bezney",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "Brooke Simonton",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "David Hong",
-        "author_inst": "Wharton Statistics, University of Pennsylvania"
-      },
-      {
-        "author_name": "Madikay Senghore",
-        "author_inst": "Harvard School of Public Health"
-      },
-      {
-        "author_name": "Abdul K Sesay",
-        "author_inst": "MRC Unit The Gambia at London School of Hygiene and Tropical Medicine"
-      },
-      {
-        "author_name": "Stacey Gabriel",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "Aviv Regev",
-        "author_inst": "Broad Institute of MIT and Harvard"
-      },
-      {
-        "author_name": "Michael J Mina",
-        "author_inst": "Harvard School of Public Health"
+        "author_name": "Daniel Goldman",
+        "author_inst": "Promote.Health"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1447700,33 +1450625,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.05.01.20087833",
-    "rel_title": "Early Evidence of Disparities in COVID-19 Testing in US Cities",
+    "rel_doi": "10.1101/2020.05.01.20087460",
+    "rel_title": "Prediction of Spreads of COVID-19 in India from Current Trend",
     "rel_date": "2020-05-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087833",
-    "rel_abs": "BackgroundPreliminary evidence has shown inequities in COVID-19 related cases and deaths in the US.\n\nObjectiveWe explored the emergence of spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in New York City, Philadelphia, and Chicago during the first six months of the pandemic.\n\nDesignEcological, observational study at the zip code tabulation area (ZCTA) level from March to September 2020.\n\nSettingChicago, New York City and Philadelphia.\n\nParticipantsAll populated ZCTAs in the three cities.\n\nMeasuresOutcomes were ZCTA-level COVID-19 testing, positivity, confirmed cases, and mortality cumulatively through the end of September. Predictors were the CDC social vulnerability index and its four domains, obtained from the 2014-2018 American Community Survey. We examined the spatial autocorrelation of COVID-19 outcomes using global and local Morans I and estimated associations using spatial conditional autoregressive negative binomial models.\n\nResultsWe found spatial clusters of high and low positivity, confirmed cases and mortality, co-located with clusters of low and high social vulnerability. We also found evidence for the existence of spatial inequities in testing, positivity, confirmed cases and mortality for the three cities. Specifically, neighborhoods with higher social vulnerability had lower testing rates, higher positivity ratios, confirmed case rates and mortality rates.\n\nLimitationsZCTAs are imperfect and heterogeneous geographical units of analysis. We rely on surveillance data, which may be incomplete.\n\nConclusionWe found spatial inequities in COVID-19 testing, positivity, confirmed cases, and mortality in three large cities of the US.\n\nRegistrationN/A\n\nFunding sourceNIH (DP5OD26429) and RWJF (77644)",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087460",
+    "rel_abs": "The article describe modelling efforts for evaluating the current level of COVID-19 infections in India, using exponential model. The Data from 15 march 2020 to 30 April 2020 are used for validating the model, where intrinsic rise rate is kept constant. It is observed that some states of India, like MAharastra, Gujarat and Delhi have a much higher daily infection cases. This is modelled by assuming an initial higher infections, keeping rise rate same. The sudden outbursts are captured using offset of values for these three states. Data from other states like Madhya Pradesh, Uttar Pradesh and Rajasthan are also analysed and they are found to be following the same constants as India is following. Worldwide, many attempts are made to predict outburst of COVID-19 and in the model, described in this paper, turning point is not predicted, as cases in India are still rising. The developed model is based on daily confirmed infections and not on cumulative infections and rationalization is carried out for the population of various regions, while predicting infections for various states. Assigning a decay constant at this stage will be a premature exercise and keeping that in mind, exponential model predicts that India will attain 1 lakh case by 15 May 2020. The figure of 2 lakh and 3 lakh will be attained on 22 May 2020 and 26 May 2020, respectively.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Usama Bilal",
-        "author_inst": "Drexel University"
-      },
-      {
-        "author_name": "Loni P Tabb",
-        "author_inst": "Drexel University"
-      },
-      {
-        "author_name": "Sharrelle Barber",
-        "author_inst": "Drexel University"
-      },
-      {
-        "author_name": "Ana V Diez-Roux",
-        "author_inst": "Drexel University"
+        "author_name": "Himanshu Shekhar",
+        "author_inst": "O/o DG(ACE)"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1449254,31 +1452167,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.29.20084376",
-    "rel_title": "A novel deterministic forecast model for COVID-19 epidemic based on a single ordinary integro-differential equation",
+    "rel_doi": "10.1101/2020.05.01.20084384",
+    "rel_title": "A Susceptible-Infected-Removed (SIR) model of COVID-19 epidemic trend in Malaysia under Movement Control Order (MCO) using a data fitting approach",
     "rel_date": "2020-05-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20084376",
-    "rel_abs": "In this paper we present a new approach to deterministic modelling of COVID-19 epidemic. Our model dynamics is expressed by a single prognostic variable which satisfies an integro-differential equation. All unknown parameters are described with a single, time-dependent variable R(t). We show that our model has similarities to classic compartmental models, such as SIR, and that the variable R(t) can be interpreted as a generalized effective reproduction number. The advantages of our approach are the simplicity of having only one equation, the numerical stability due to an integral formulation and the reliability since the model is formulated in terms of the most trustable statistical data variable: the number of cumulative diagnosed positive cases of COVID-19. Once this dynamic variable is calculated, other non-dynamic variables, such as the number of heavy cases (hospital beds), the number of intensive-care cases (ICUs) and the fatalities, can be derived from it using a similarly stable, integral approach. The formulation with a single equation allows us to calculate from real data the values of the sample effective reproduction number, which can then be fitted. Extrapolated values of R(t) can be used in the model to make reliable forecasts, though under the assumption that measures for reducing infections are maintained. We have applied our model to more than 15 countries and the ongoing results are available on a web-based platform [1]. In this paper, we focus on the data for two exemplary countries, Italy and Germany, and show that the model is capable of reproducing the course of the epidemic in the past and forecasting its course for a period of four to five weeks with a reasonable numerical stability.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20084384",
+    "rel_abs": "BackgroundIn this work, we presented a Susceptible-Infected-Removed (SIR) epidemiological model of COVID-19 epidemic in Malaysia post- and pre-Movement Control Order (MCO). The proposed SIR model was fitted to confirmed COVID-19 cases from the official press statements to closely reflect the observed epidemic trend in Malaysia. The proposed model is aimed to provide an accurate predictive information for decision makers in assessing the public health and social measures related to COVID-19 epidemic.\n\nMethodsThe SIR model was fitted to the data by minimizing a weighted loss function; the sum of the residual sum of squares (RSS) of infected, removed and total cases. Optimized beta ({beta}),), gamma ({gamma}) parameter values) parameter values and the starting value of susceptible individuals (N) were obtained.\n\nResultsThe SIR model post-MCO indicates the peak of infection on 10 April 2020, less than 100 active cases by 8 July 2020, less than 10 active cases by 29 August 2020, and close to zero daily new case by 22 July 2020, with a total of 6562 infected cases. In the absence of MCO, the model predicts the peak of infection on 1 May 2020, less than 100 active cases by 14 February 2021, less than 10 active cases by 26 April 2021 and close to zero daily new case by 6 October 2020, with a total of 1.6 million infected cases. Conclusion: The results suggest that the present MCO has significantly reduced the number of susceptible population and the total number of infected cases. The method to fit the SIR model used in this study was found to be accurate in reflecting the observed data. The method can be used to predict the epidemic trend of COVID-19 in other countries.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Felix Koehler-Rieper",
-        "author_inst": "Goethe-Universtitaet Frankfurt, Germany"
+        "author_name": "Wan Nor Arifin",
+        "author_inst": "Universiti Sains Malaysia"
       },
       {
-        "author_name": "Claudius H. F. Roehl",
-        "author_inst": "Universitaet Leipzig, Germany"
+        "author_name": "Weng Howe Chan",
+        "author_inst": "Universiti Teknologi Malaysia"
+      },
+      {
+        "author_name": "Safiya Amaran",
+        "author_inst": "Universiti Sultan Zainal Abidin"
       },
       {
-        "author_name": "Enrico De Micheli",
-        "author_inst": "IBF - Consiglio Nazionale Delle Ricerche, Genova, Italy"
+        "author_name": "Kamarul Imran Musa",
+        "author_inst": "Universiti Sains Malaysia"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "forensic medicine"
   },
   {
     "rel_doi": "10.1101/2020.04.30.20085290",
@@ -1450808,79 +1453725,51 @@
     "category": "rheumatology"
   },
   {
-    "rel_doi": "10.1101/2020.04.30.20086462",
-    "rel_title": "Kidney Allograft Recipients Diagnosed with Coronavirus Disease-2019: A Single Center Report",
+    "rel_doi": "10.1101/2020.04.30.20086447",
+    "rel_title": "Evaluation of effects of public health interventions on COVID-19 transmission for Pakistan: A mathematical simulation study",
     "rel_date": "2020-05-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20086462",
-    "rel_abs": "BackgroundOrgan graft recipients receiving immunosuppressive therapy are likely to be at heightened risk for the Coronavirus Disease 2019 (Covid-19) and adverse outcomes including death. It is therefore important to characterize the clinical course and outcome of Covid-19 in this vulnerable population and identify therapeutic strategies that are safe.\n\nMethodsWe performed a retrospective chart review of 54 adult kidney transplant patients diagnosed with Covid-19 and all managed in New York State, the epicenter of Covid-19 pandemic. All 54 patients were evaluated by video visits, or phone interviews, and referred to our Fever Clinic or Emergency Room for respiratory illness symptoms consistent with Covid-19 and admitted if deemed necessary from March 13, 2020 to April 20, 2020. Characteristics of the patients were stratified by hospitalization status and disease severity. Clinical course including alterations in immunosuppressive therapy were retrieved from their electronic medical records. Primary outcomes included recovery from Covid-19 symptoms, acute kidney injury, graft failure, and case fatality rate.\n\nResultsOf the 54 SARS-Cov-2 positive kidney transplant recipients, 39 with moderate to severe symptoms were admitted and 15 with mild symptoms were managed at home. Hospitalized patients compared to non-hospitalized patients were more likely to be male, of Hispanic ethnicity, and to have cardiovascular disease. At baseline, all but 2 were receiving tacrolimus, mycophenolate mofetil (MMF) and 32 were on a steroid free immunosuppression regimen. Tacrolimus dosage was reduced in 46% of hospitalized patients and maintained at baseline level in the non-hospitalized cohort. Mycophenolate mofetil (MMF) dosage was maintained at the baseline dosage in 11% of hospitalized patients and 64% of non-hospitalized patients and was stopped in 61% hospitalized patients and 0% in the non-hospitalized cohort. Azithromycin or doxycycline were prescribed at a similar rate among hospitalized and non-hospitalized patients (38% vs. 40%). In addition, 50% of hospitalized patients were treated for concurrent bacterial infections including pneumonia, urinary tract infections and sepsis. Hydroxychloroquine was prescribed in 79% of hospitalized patients and only one of 15 non-hospitalized patients. Acute kidney injury occurred in 51% of hospitalized patients. Patients with severe disease were more likely to have elevations in inflammatory biomarkers at presentation. At a median of 21 days follow up, 67% of patients have had their symptoms resolved or improved and 33% have persistent symptoms. Graft failure requiring hemodialysis occurred in 3 of 39 hospitalized patients (8%). Three of 39 (8%) hospitalized patients expired and none of the 15 non-hospitalized patients expired.\n\nConclusionsClinical presentation of Covid-19 in kidney transplant recipients was similar to what has been described in the general population. The case fatality rate in our entire cohort of 54 kidney transplant recipients was reassuringly low and patients with mild symptomology could be successfully managed at home. Data from the our study suggest that a strategy of systematic screening and triage to outpatient or inpatient care, close monitoring, early management of concurrent bacterial infections and judicious use of immunosuppressive drugs rather than cessation is beneficial.",
-    "rel_num_authors": 15,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20086447",
+    "rel_abs": "BackgroundIn an effort to contain the COVID-19 epidemic, many governments across the world have enforced lockdown or social distancing measures. Several outbreak models have been developed to investigate the effects of different public health strategies for COVID-19, but they have not been developed for Pakistan and other South East Asian countries, where a large proportion of global population resides.\n\nMethodsWe developed a stochastic individual contact model by extending the widely-used Susceptible-Infectious-Recovered (SIR) compartment model with additional compartments to model both anticipated mitigating effects of public health intervention strategies for Pakistan. We estimated the projected spread, number of hospitalizations, and case fatalities under no intervention and four increasingly stringent public health strategies of social distancing and self-isolation at the national and provincial levels of Pakistan.\n\nResultsOur analysis shows that without any public health interventions the expected number of cumulative case fatalities is 671,596 in Pakistan with the virus is expected to peak in terms of the number of required ICU-hospitalizations at 198,593 persons by the end of the June 2020. The estimated total numbers of cumulative case fatalities are lower for other public health strategies with strict social distancing showing the lowest number of deaths at 1,588 (Self-isolation: n=341,359; Flexible social distancing strategy: n=3,995; and Exit strategy: n=28,214). The lowest number of required ICU-hospitalization is also estimated for strict social distancing strategy (n=266 persons at the end of May 2020). Generally, the simulated effects of the different public health strategies at the provincial-level were similar to the national-level with strict social distancing showing the fewest number of case fatalities and ICU-hospitalizations.\n\nConclusionOur results indicate that case fatalities and ICU-hospitalizations for Pakistan will be high without any public health interventions. While strict social distancing can potentially prevent a large number of deaths and ICU-hospitalizations, the government faces an important dilemma of potentially severe economic downfall. Consideration of a temporary strict social distancing strategy with gradual return of the lower-risk Pakistani population, as simulated in our exit strategy scenario, may an effective compromise between public health and economy of Pakistani population.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Michelle Lubetzky",
-        "author_inst": "New York Presbyterian, Weill Cornell"
-      },
-      {
-        "author_name": "Meredith Aull",
-        "author_inst": "New York Presbyterian-Weill Cornell"
-      },
-      {
-        "author_name": "Rebecca Craig-Shapiro",
-        "author_inst": "New York Presbyterian-Weill Cornell"
-      },
-      {
-        "author_name": "Jun Lee",
-        "author_inst": "New York Presbyterian"
-      },
-      {
-        "author_name": "John Lee",
-        "author_inst": "New York Presbyterian-Weill Cornell"
-      },
-      {
-        "author_name": "Samuel Sultan",
-        "author_inst": "New York Presbyterian-Weill Cornell"
-      },
-      {
-        "author_name": "Jehon Marku-Podvorica",
-        "author_inst": "New York Presbyterian-Weill Cornell"
-      },
-      {
-        "author_name": "Laura Gingras",
-        "author_inst": "New York Presbyterian-Weill Cornell"
+        "author_name": "Zulfiqar A Bhutta",
+        "author_inst": "Aga Khan University"
       },
       {
-        "author_name": "Rosy Priya Kodiyanplakkal",
-        "author_inst": "New York Presbyterian-Weill Cornell"
+        "author_name": "Ofir Harari",
+        "author_inst": "Cytel Inc"
       },
       {
-        "author_name": "Choli Hartono",
-        "author_inst": "New York Presbyterian"
+        "author_name": "Jay JH Park",
+        "author_inst": "University of British Columbia"
       },
       {
-        "author_name": "Stuart Saal",
-        "author_inst": "New York Presbyterian"
+        "author_name": "Noor Zannat",
+        "author_inst": "Cytel Inc"
       },
       {
-        "author_name": "Thangamani Muthukumar",
-        "author_inst": "New York Presbyterian-Weill Cornell"
+        "author_name": "Michael Zoratti",
+        "author_inst": "McMaster University"
       },
       {
-        "author_name": "Sandip Kapur",
-        "author_inst": "New York Presbyterian-Weill Cornell"
+        "author_name": "Timothy Churches",
+        "author_inst": "South Western Sydney Clinical School, UNSW Medicine"
       },
       {
-        "author_name": "Manikkam Suthanthiran",
-        "author_inst": "New York Presbyterian-Weill Cornell"
+        "author_name": "Kristian Thorlund",
+        "author_inst": "Cytel Inc"
       },
       {
-        "author_name": "Darshana Dadhania",
-        "author_inst": "New York Presbyterian-Weill Cornell"
+        "author_name": "Edward J Mills",
+        "author_inst": "Cytel Inc"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "transplantation"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2020.04.30.20086553",
@@ -1452018,29 +1454907,61 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.30.20081828",
-    "rel_title": "Modeling COVID-19 on a network: super-spreaders, testing and containment",
+    "rel_doi": "10.1101/2020.04.30.20077594",
+    "rel_title": "Early transmission dynamics and control of COVID-19 in a southern hemisphere setting: Lima-Peru, February 29th-March 30th, 2020 .",
     "rel_date": "2020-05-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20081828",
-    "rel_abs": "To model COVID-19 spread, we use an SEIR agent-based model on a graph, which takes into account several important real-life attributes of COVID-19: super-spreaders, realistic epidemiological parameters of the disease, testing and quarantine policies. We find that mass-testing is much less effective than testing the symptomatic and contact tracing, and some blend of these with social distancing is required to achieve suppression. We also find that the fat tail of the degree distribution matters a lot for epidemic growth, and many standard models do not account for this. Additionally, the average reproduction number for individuals, equivalent in many models to R0, is not an upper bound for the effective reproduction number, R. Even with an expectation of less than one new case per person, our model shows that exponential spread is possible. The parameter which closely predicts growth rate is the ratio between 2nd to 1st moments of the degree distribution. We provide mathematical arguments to argue that certain results of our simulations hold in more general settings.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20077594",
+    "rel_abs": "The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th, 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru.\n\nWe estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place.\n\nPrior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.9 (95%CI: 0.9,1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government.\n\nWhile the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.\n\nPeru COVID-19 working group\n\n\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@113464dorg.highwire.dtl.DTLVardef@6c8ba2org.highwire.dtl.DTLVardef@434c63org.highwire.dtl.DTLVardef@4c0821org.highwire.dtl.DTLVardef@1a9c01e_HPS_FORMAT_FIGEXP  M_TBL C_TBL",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Ofir Reich",
-        "author_inst": "Google"
+        "author_name": "Cesar V. Munayco",
+        "author_inst": "Centro Nacional de Epidemiologia, Prevencion y Control de Enfermedades, Peruvian Ministry of Health, Lima, Peru"
       },
       {
-        "author_name": "Guy Shalev",
-        "author_inst": "Google"
+        "author_name": "Amna Tariq",
+        "author_inst": "Georgia State University"
       },
       {
-        "author_name": "Tom Kalvari",
-        "author_inst": "Tel Aviv University"
+        "author_name": "Richard Rothenberg",
+        "author_inst": "Georgia State University"
+      },
+      {
+        "author_name": "Gabriela G Soto-Cabezas",
+        "author_inst": "Centro Nacional de Epidemiologia, Prevencion y Control de Enfermedades, Peruvian Ministry of Health, Lima, Peru"
+      },
+      {
+        "author_name": "Mary F. Reyes",
+        "author_inst": "Centro Nacional de Epidemiologia, Prevencion y Control de Enfermedades, Peruvian Ministry of Health, Lima, Peru"
+      },
+      {
+        "author_name": "Andree Valle",
+        "author_inst": "Centro Nacional de Epidemiologia, Prevencion y Control de Enfermedades, Peruvian Ministry of Health, Lima, Peru"
+      },
+      {
+        "author_name": "Leonardo Rojas-Mezarina",
+        "author_inst": "Instituto Nacional de Salud, Peruvian Ministry of Health, Lima, Peru"
+      },
+      {
+        "author_name": "Cesar Cabezas",
+        "author_inst": "Instituto Nacional de Salud, Peruvian Ministry of Health, Lima, Peru"
+      },
+      {
+        "author_name": "Manuel Loayza",
+        "author_inst": "Centro Nacional de Epidemiologia, Prevencion y Control de Enfermedades, Peruvian Ministry of Health, Lima, Peru."
+      },
+      {
+        "author_name": "- COVID-19 Peru COVID-19 working group",
+        "author_inst": ""
+      },
+      {
+        "author_name": "Gerardo Chowell",
+        "author_inst": "Georgia State University"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1453648,107 +1456569,47 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.29.20084244",
-    "rel_title": "Are COVID-19 infected children with gastrointestinal symptoms different from those without symptoms? A comparative study of the clinical characteristics and epidemiological trend of 244 pediatric cases from Wuhan",
+    "rel_doi": "10.1101/2020.04.30.20083881",
+    "rel_title": "Associations between psychiatric disorders, COVID-19 testing probability and COVID-19 testing results: Findings from a population-based study",
     "rel_date": "2020-05-05",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20084244",
-    "rel_abs": "ObjectiveCOVID-19 patients presenting with gastrointestinal (GI) symptoms occur in both adults and children. To date, however, no large sample size study focusing on gastrointestinal symptoms in pediatric cases has been published. We analyzed COVID-19 infected children in Wuhan who presented with initial GI symptoms to determine the GI characteristics and epidemiological trend of the disease.\n\nDesignWe retrospectively analyzed 244 children patients confirmed with COVID-19 at Wuhan Childrens Hospital from 21 Jan to 20 Mar 2020. Symptomatic cases were divided into two groups according to whether the patients presented with or without GI symptoms on admission. Demographic, epidemiological, symptoms, and laboratory data were compared. We also analyzed the respective trends of case number changes of GI cases and asymptomatic cases.\n\nResults34 out of 193 symptomatic children had GI symptoms. They had lower median age and weight, a higher rate of fever, a longer length of stay and more hematological and biochemical abnormalities than patients without GI symptoms. There was no significant difference in chest CT findings or stool SARS-CoV-2 test positive percentages between the two groups. The number of patients admitted with GI symptoms showed an overall downward trend with time. At the time of writing, 242 patients were discharged, one died, and one critically ill patient was still in the intensive care unit.\n\nConclusionCOVID-19 infected children with GI symptoms are prone to presenting with more clinical and laboratory abnormalities than patients without GI symptoms. More attention and timely hospital admission are needed for these patients.\n\nSignificance of this studyO_LSTWhat is already known on this subject?C_LSTO_LICOVID-19 is now a pandemic with more than 1.6 million people infected worldwide\nC_LIO_LIAlthough attacking the respiratory tract mostly, both adult and children infected with COVID-19 can present with GI symptoms\nC_LI\n\nO_LSTWhat are the new findings?C_LSTO_LIInfants younger than two years old and presence of fever are the two risk factors of presenting with GI symptoms\nC_LIO_LIA high proportion of patients without GI symptoms and asymptomatic patients will have positive RT-PCR for the virus in stool\nC_LIO_LIEarlier testing through contact screening of family members means more COVID-19 infected children are diagnosed when completely asymptomatic\nC_LI\n\nO_LSTHow might it impact on clinical practice in the foreseeable future?C_LSTO_LIThe presence of COVID-19 in stool in infected children will have a major implication for parents and carers of young infants\nC_LIO_LIIncreasing number of asymptomatic COVID-19 patients who are detected through screening could provide a useful lesson for other countries still experiencing the rise and peak of the pandemic\nC_LI",
-    "rel_num_authors": 22,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20083881",
+    "rel_abs": "ObjectiveTo compare prevalence of COVID-19 testing and test outcomes among individuals with psychiatric disorders to those without such diagnoses, and to examine the associations of testing probability and outcome with psychiatric diagnosis categories.\n\nDesignLarge population-based study to perform association analyses of psychiatric disorder diagnoses with COVID-19 testing probability and such test results, by using two-sided Fisher exact tests and logistic regressions.\n\nSettingUK Biobank.\n\nParticipants1 474 men and women of British ancestry that had been tested for COVID-19, with a mean age of 58.2 years.\n\nMain outcome measuresCOVID-19 testing probability and COVID-19 test results.\n\nResultsIndividuals with psychiatric disorders were overrepresented among the 1 474 UKB participants with test data: 23% of the COVID-19 test sample had a psychiatric diagnosis compared to 10% in the full cohort (p<0.0001). This overrepresentation persisted for each of the specific psychiatric disorders tested. Furthermore, individuals with a psychiatric disorder (p=0.01), particularly with substance use disorder (p<0.005), had negative test results significantly more often than individuals without psychiatric disorders. Sensitivity analyses confirmed our results.\n\nConclusionsIn contrast with our hypotheses, UKB participants with psychiatric disorders have been tested for COVID-19 more frequently than individuals without a psychiatric history, pleading against the notion that limited health care access is preventing them from undergoing testing. Among those tested, test outcomes were more frequently negative for UKB participants with psychiatric disorders than in others, countering arguments that people with psychiatric disorders are particularly prone to contract the virus.\n\nSUMMARY BOXO_ST_ABSWhat is already known on this topic (2-3 sentences)C_ST_ABSWe searched PubMed using the terms \"COVID-19\" combined with \"mental health\", \"psychiatric disorder\" or \"mental illness\" for all articles published in any language before April 21st, 2020. Two hundred articles were retrieved, most of which related to the Chinese experience when dealing with the pandemic, including the mental health impact of the COVID-19 pandemic on general population mental health and healthcare workers; and on advancing mental healthcare resources in times of crisis. No evidence was found on testing patterns for severe acute respiratory syndromes (e.g. COVID-19, SARS, MERS) or Ebola virus on people with psychiatric disorders.\n\nWhat this study adds (2-3 sentences)We highlight a positive association between psychiatric disorders and the likelihood of being tested for COVID-19, as well as an association between psychiatric disorders and negative results. The results thus counter arguments that patients with psychiatric disorders are suffering from limited health care access preventing them from undergoing testing. Additionally, these are important findings as they carry the potential to reduce stigma: while people in the general population may be concerned that patients with psychiatric disorders do not comply with containment measures and are susceptible to contract COVID-19, our findings may help counter such concerns.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Xiaoli Xiong",
-        "author_inst": "Wuhan Children's Hospital"
-      },
-      {
-        "author_name": "Kenenth Kak-Yuen Wong",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Shuiqing Chi",
-        "author_inst": "Union Hospital, Wuhan"
-      },
-      {
-        "author_name": "Aifen Zhou",
-        "author_inst": "Wuhan Children's Hospital"
-      },
-      {
-        "author_name": "Jianqiao Tang",
-        "author_inst": "Wuhan Children's Hospital"
-      },
-      {
-        "author_name": "Lishan Zhou",
-        "author_inst": "Wuhan Children's Hospital"
-      },
-      {
-        "author_name": "Patrick Ho-yu Chung",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Gilbert Chua",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Keith TS Tung",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Ian CK Wong",
-        "author_inst": "The Univeristy of Hong Kong"
-      },
-      {
-        "author_name": "Celine SL Chui",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Xue Li",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Mike Yat-wah Kwan",
-        "author_inst": "Princess Margaret Hospital, Hong Kong"
-      },
-      {
-        "author_name": "Wilfred HS Wong",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Marco Hok-kung Ho",
-        "author_inst": "The University of Hong Kong"
-      },
-      {
-        "author_name": "Godfrey CF Chan",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Dennis van der Meer",
+        "author_inst": "NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway"
       },
       {
-        "author_name": "Guoqing Cao",
-        "author_inst": "Union Hospital, Wuhan"
+        "author_name": "Justo Emilio Pinzon-Espinosa",
+        "author_inst": "Department of Psychiatry and Psychology, Institute of Neuroscience, Hospital Clinic of Barcelona, Spain"
       },
       {
-        "author_name": "Kang Li",
-        "author_inst": "Union Hospital, Wuhan"
+        "author_name": "Bochao Danae Lin",
+        "author_inst": "Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands"
       },
       {
-        "author_name": "Patrick Ip",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Joeri K. Tijdink",
+        "author_inst": "Department of Medical Humanities, Amsterdam University Medical Center, Amsterdam, the Netherlands"
       },
       {
-        "author_name": "Peng Chen",
-        "author_inst": "Wuhan Children's Hospital"
+        "author_name": "Christiaan H. Vinkers",
+        "author_inst": "Amsterdam University Medical Center"
       },
       {
-        "author_name": "Shaotao Tang",
-        "author_inst": "Union Hospital, Wuhan"
+        "author_name": "Sinan Guloksuz",
+        "author_inst": "Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands"
       },
       {
-        "author_name": "Paul KH Tam",
-        "author_inst": "The University of Hong Kong"
+        "author_name": "Jurjen J. Luykx",
+        "author_inst": "Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "pediatrics"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.04.29.20084335",
@@ -1455454,75 +1458315,355 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.05.03.073080",
-    "rel_title": "Feline coronavirus drug inhibits the main protease of SARS-CoV-2 and blocks virus replication",
+    "rel_doi": "10.1101/2020.05.02.043554",
+    "rel_title": "Catalytic cleavage of HEAT and subsequent covalent binding of the tetralone moiety by the SARS-CoV-2 main protease",
     "rel_date": "2020-05-04",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.03.073080",
-    "rel_abs": "The COVID-19 pandemic, attributed to the SARS-CoV-2 coronavirus infection, resulted in millions infected worldwide and an immediate need for antiviral treatments. The main protease (Mpro) in SARS-CoV-2 is a viable drug target because of its essential role in the cleavage of the virus polypeptide and subsequent viral replication. Feline infectious peritonitis, a fatal infection in cats caused by a coronavirus, was successfully treated previously with a dipeptide-based protease inhibitor. Here we show this drug, GC376, and its analog GC373, are effective inhibitors of the Mpro from both SARS-CoV and SARS-CoV-2 with IC50 values in the nanomolar range. Crystal structures of the SARS-CoV and SARS-CoV-2 Mpro with these inhibitors have a covalent modification of the nucleophilic Cys145. NMR analysis reveals that inhibition proceeds via reversible formation of a hemithioacetal. GC373 and GC376 are potent inhibitors of SARS-CoV-2 in cell culture, with EC50 values near one micromolar and little to no toxicity. These protease inhibitors are soluble, non-toxic, and bind reversibly. They are strong drug candidates for the treatment of human coronavirus infections because they have already been successful in animals (cats). The work here lays the framework for their use in human trials for the treatment of COVID-19.",
-    "rel_num_authors": 14,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.02.043554",
+    "rel_abs": "Here we present the crystal structure of SARS-CoV-2 main protease (Mpro) covalently bound to 2-methyl-1-tetralone. This complex was obtained by co-crystallization of Mpro with HEAT (2-(((4-hydroxyphenethyl)amino)methyl)-3,4-dihydronaphthalen-1(2H)-one) in the framework of a large X-ray crystallographic screening project of Mpro against a drug repurposing library, consisting of 5632 approved drugs or compounds in clinical phase trials. Further investigations showed that HEAT is cleaved by Mpro in an E1cB-like reaction mechanism into 2-methylene-1-tetralone and tyramine. The catalytic Cys145 subsequently binds covalently in a Michael addition to the methylene carbon atom of 2-methylene-1-tetralone. According to this postulated model HEAT is acting in a pro-drug-like fashion. It is metabolized by Mpro, followed by covalent binding of one metabolite to the active site. The structure of the covalent adduct elucidated in this study opens up a new path for developing non-peptidic inhibitors.",
+    "rel_num_authors": 84,
     "rel_authors": [
       {
-        "author_name": "Wayne Vuong",
-        "author_inst": "University of Alberta"
+        "author_name": "Sebastian G\u00fcnther",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       },
       {
-        "author_name": "Muhammad Bashir Khan",
-        "author_inst": "University of Alberta"
+        "author_name": "Patrick Y. A. Reinke",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       },
       {
-        "author_name": "Conrad Fischer",
-        "author_inst": "University of Alberta"
+        "author_name": "Dominik Oberthuer",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       },
       {
-        "author_name": "Elena Arutyunova",
-        "author_inst": "University of Alberta"
+        "author_name": "Oleksandr Yefanov",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       },
       {
-        "author_name": "Tess Lamer",
-        "author_inst": "University of Alberta"
+        "author_name": "Helen Ginn",
+        "author_inst": "Diamond Light Source Ltd. Diamond House, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK"
       },
       {
-        "author_name": "Justin Shields",
-        "author_inst": "University of Alberta"
+        "author_name": "Susanne Meier",
+        "author_inst": "Universitaet Hamburg, Institut fuer Nanostruktur- und Festkoerperphysik and Hamburg Centre for Ultrafast Imaging, Universitaet Hamburg, Luruper Chaussee 149, 22"
       },
       {
-        "author_name": "Holly A Saffran",
-        "author_inst": "University of Alberta"
+        "author_name": "Thomas J. Lane",
+        "author_inst": "Linac Coherent Light Source, SLAC National Accelerator Laboratory, Menlo Park, California, USA"
       },
       {
-        "author_name": "Ryan T McKay",
-        "author_inst": "University of Alberta"
+        "author_name": "Kristina Lorenzen",
+        "author_inst": "European XFEL GmbH. Holzkoppel 4, 22869 Schenefeld, Germany"
       },
       {
-        "author_name": "Marco J van Belkum",
-        "author_inst": "University of Alberta"
+        "author_name": "Luca Gelisio",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       },
       {
-        "author_name": "Michael Joyce",
-        "author_inst": "University of Alberta"
+        "author_name": "Wolfgang Brehm",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       },
       {
-        "author_name": "Howard S Young",
-        "author_inst": "University of Alberta"
+        "author_name": "Ilona Dunkel",
+        "author_inst": "Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany"
       },
       {
-        "author_name": "D. Lorne Tyrrell",
-        "author_inst": "University of Alberta"
+        "author_name": "Martin Domaracky",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       },
       {
-        "author_name": "John C Vederas",
-        "author_inst": "University of Alberta"
+        "author_name": "Sofiane Saouane",
+        "author_inst": "Deutsches Elektronen Synchrotron (DESY), Photon Science, Notkestrasse 85, 22607, Hamburg, Germany"
       },
       {
-        "author_name": "M Joanne Lemieux",
-        "author_inst": "University of Alberta"
+        "author_name": "Julia Lieske",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Christiane Ehrt",
+        "author_inst": "Universitaet Hamburg, Center for Bioinformatics, Bundesstr. 43, 20146 Hamburg, Germany"
+      },
+      {
+        "author_name": "Faisal Koua",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Alexandra Tolstikova",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Thomas A. White",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Michael Groessler",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Holger Fleckenstein",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Fabian Trost",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Marina Galchenkova",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Yaroslav Gevorkov",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg and Vision Systems, Hamburg University of Technology, 21071 Hamburg, Germany"
+      },
+      {
+        "author_name": "Chufeng Li",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Salah Awel",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Ariana Peck",
+        "author_inst": "Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA"
+      },
+      {
+        "author_name": "P. Lourdu Xavier",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg and Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee"
+      },
+      {
+        "author_name": "Miriam Barthelmess",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Frank Schl\u00fcnzen",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Nadine Werner",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology and Laboratory for Structural Biology of Infection and Inflammati"
+      },
+      {
+        "author_name": "Hina Andaleeb",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology and Laboratory for Structural Biology of Infection and Inflammati"
+      },
+      {
+        "author_name": "Najeeb Ullah",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology and Laboratory for Structural Biology of Infection and Inflammati"
+      },
+      {
+        "author_name": "Sven Falke",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology and Laboratory for Structural Biology of Infection and Inflammati"
+      },
+      {
+        "author_name": "Bruno Alves Franca",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology and Laboratory for Structural Biology of Infection and Inflammati"
+      },
+      {
+        "author_name": "Martin Schwinzer",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology and Laboratory for Structural Biology of Infection and Inflammati"
+      },
+      {
+        "author_name": "Hevila Brognaro",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology and Laboratory for Structural Biology of Infection and Inflammati"
+      },
+      {
+        "author_name": "Brandon Seychell",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Physical Chemistry, Grindelallee 117, 20146 Hamburg, Germany"
+      },
+      {
+        "author_name": "Henry Gieseler",
+        "author_inst": "Universitaet Hamburg, Institut fuer Nanostruktur- und Festkoerperphysik and Hamburg Centre for Ultrafast Imaging, Universitaet Hamburg, Luruper Chaussee 149, 22"
+      },
+      {
+        "author_name": "Diogo Melo",
+        "author_inst": "Universitaet Hamburg, Institut fuer Nanostruktur- und Festkoerperphysik and Hamburg Centre for Ultrafast Imaging, Universitaet Hamburg, Luruper Chaussee 149, 22"
+      },
+      {
+        "author_name": "Jo J. Zaitsev-Doyle",
+        "author_inst": "Universitaet Hamburg, Institut fuer Nanostruktur- und Festkoerperphysik and Hamburg Centre for Ultrafast Imaging, Universitaet Hamburg, Luruper Chaussee 149, 22"
+      },
+      {
+        "author_name": "Brenna Norton-Baker",
+        "author_inst": "Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761 Hamburg, Germany"
+      },
+      {
+        "author_name": "Juraj Knoska",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Gisel Esperanza",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Aida Rahmani Mashhour",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Filip Guicking",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Vincent Hennicke",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Pontus Fischer",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
+      },
+      {
+        "author_name": "Cromarte Rogers",
+        "author_inst": "Universitaet Hamburg, Institut fuer Nanostruktur- und Festkoerperphysik, Luruper Chaussee 149, 22761 Hamburg, Germany"
+      },
+      {
+        "author_name": "Diana C. F. Monteiro",
+        "author_inst": "Hauptmann Woodward Medical Research Institute, 700 Ellicott Street, Buffalo, NY, 14203, USA"
+      },
+      {
+        "author_name": "Johanna Hakanp\u00e4\u00e4",
+        "author_inst": "Deutsches Elektronen Synchrotron (DESY), Photon Science, Notkestrasse 85, 22607, Hamburg, Germany"
+      },
+      {
+        "author_name": "Jan Meyer",
+        "author_inst": "Deutsches Elektronen Synchrotron (DESY), Photon Science, Notkestrasse 85, 22607, Hamburg, Germany"
+      },
+      {
+        "author_name": "Heshmat Noei",
+        "author_inst": "Deutsches Elektronen Synchrotron (DESY), Photon Science, Notkestrasse 85, 22607, Hamburg, Germany"
+      },
+      {
+        "author_name": "Phil Gribbon",
+        "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), screening port, Schnackenburgallee 114, 22525 Hamburg, Germany"
+      },
+      {
+        "author_name": "Bernhard Ellinger",
+        "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), screening port, Schnackenburgallee 114, 22525 Hamburg, Germany"
+      },
+      {
+        "author_name": "Maria Kuzikov",
+        "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), screening port, Schnackenburgallee 114, 22525 Hamburg, Germany"
+      },
+      {
+        "author_name": "Markus Wolf",
+        "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), screening port, Schnackenburgallee 114, 22525 Hamburg, Germany"
+      },
+      {
+        "author_name": "Linlin Zhang",
+        "author_inst": "Institute of Biochemistry, Center for Structural and Cell Biology in Medicine and German Center for Infection Research (DZIF), Hamburg-Luebeck-Borstel-Riems Sit"
+      },
+      {
+        "author_name": "Xinyuanyuan Sun",
+        "author_inst": "Institute of Biochemistry, Center for Structural and Cell Biology in Medicine and German Center for Infection Research (DZIF), Hamburg-Luebeck-Borstel-Riems Sit"
+      },
+      {
+        "author_name": "Jonathan Pletzer-Zelgert",
+        "author_inst": "Universitaet Hamburg, Center for Bioinformatics, Bundesstr. 43, 20146 Hamburg, Germany"
+      },
+      {
+        "author_name": "Jan Wollenhaupt",
+        "author_inst": "Helmholtz Zentrum Berlin, Hahn-Meitner-Platz 1, 14109 Berlin, Germany"
+      },
+      {
+        "author_name": "Christian Feiler",
+        "author_inst": "Helmholtz Zentrum Berlin, Hahn-Meitner-Platz 1, 14109 Berlin, Germany"
+      },
+      {
+        "author_name": "Manfred Weiss",
+        "author_inst": "Helmholtz Zentrum Berlin, Hahn-Meitner-Platz 1, 14109 Berlin, Germany"
+      },
+      {
+        "author_name": "Eike-Christian Schulz",
+        "author_inst": "Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761 Hamburg, Germany"
+      },
+      {
+        "author_name": "Pedram Mehrabi",
+        "author_inst": "Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761 Hamburg, Germany"
+      },
+      {
+        "author_name": "Christina Schmidt",
+        "author_inst": "European XFEL GmbH. Holzkoppel 4, 22869 Schenefeld, Germany"
+      },
+      {
+        "author_name": "Robin Schubert",
+        "author_inst": "European XFEL GmbH. Holzkoppel 4, 22869 Schenefeld, Germany"
+      },
+      {
+        "author_name": "Huijong Han",
+        "author_inst": "European XFEL GmbH. Holzkoppel 4, 22869 Schenefeld, Germany"
+      },
+      {
+        "author_name": "Boris Krichel",
+        "author_inst": "Dynamics of Viral Structures, Heinrich-Pette-Institut, Leibniz-Institut f\u00fcr Experimentelle Virologie, Martinistrasse 52, 20251 Hamburg, Germany"
+      },
+      {
+        "author_name": "Yaiza Fern\u00e1ndez-Garc\u00eda",
+        "author_inst": "Bernhard Nocht Institute for Tropical Medicine, Bernhard-Nocht-Strasse 74, 20359 Hamburg, Germany"
+      },
+      {
+        "author_name": "Beatriz Escudero-P\u00e9rez",
+        "author_inst": "Bernhard Nocht Institute for Tropical Medicine, Bernhard-Nocht-Strasse 74, 20359 Hamburg, Germany"
+      },
+      {
+        "author_name": "Stephan G\u00fcnther",
+        "author_inst": "Bernhard Nocht Institute for Tropical Medicine, Bernhard-Nocht-Strasse 74, 20359 Hamburg, Germany"
+      },
+      {
+        "author_name": "Dusan Turk",
+        "author_inst": "Department of Biochemistry & Molecular & Structural Biology, Jozef Stefan Institute, Jamova 39, 1 000 Ljubljana, Slovenia"
+      },
+      {
+        "author_name": "Charlotte Uetrecht",
+        "author_inst": "Dynamics of Viral Structures, Heinrich-Pette-Institut, Leibniz-Institut f\u00fcr Experimentelle Virologie, Martinistrasse 52, 20251 Hamburg, Germany"
+      },
+      {
+        "author_name": "Tobias Beck",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Physical Chemistry, Grindelallee 117, 20146 Hamburg and Hamburg Centre for Ultrafast Imaging, Univer"
+      },
+      {
+        "author_name": "Henning Tidow",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology, Martin-Luther-King-Platz 6, 20146 Hamburg, and Hamburg Centre fo"
+      },
+      {
+        "author_name": "Aschwin Chari",
+        "author_inst": "Department of Structural Dynamics, Max Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Goettingen, Germany"
+      },
+      {
+        "author_name": "Andrea Zaliani",
+        "author_inst": "Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), screening port, Schnackenburgallee 114, 22525 Hamburg, Germany"
+      },
+      {
+        "author_name": "Matthias Rarey",
+        "author_inst": "Universitaet Hamburg, Center for Bioinformatics, Bundesstr. 43, 20146 Hamburg, Germany"
+      },
+      {
+        "author_name": "Russel Cox",
+        "author_inst": "Institute for Organic Chemistry and BMWZ, Leibniz University of Hannover, Schneiderberg 38, 30167 Hannover, Germany"
+      },
+      {
+        "author_name": "Rolf Hilgenfeld",
+        "author_inst": "German Center for Infection Research (DZIF), Hamburg-Luebeck-Borstel, Laboratory for Antiviral Chemotherapy, Institute of Chemistry & Metabolomics and Institute"
+      },
+      {
+        "author_name": "Henry N Chapman",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg and Hamburg Centre for Ultrafast Imaging, Universitaet Hamburg, Luruper Chaussee 14"
+      },
+      {
+        "author_name": "Arwen R. Pearson",
+        "author_inst": "Universitaet Hamburg, Institut fuer Nanostruktur- und Festkoerperphysik and Hamburg Centre for Ultrafast Imaging, Universitaet Hamburg, Luruper Chaussee 149, 22"
+      },
+      {
+        "author_name": "Christian Betzel",
+        "author_inst": "Universitaet Hamburg, Department of Chemistry, Institute of Biochemistry and Molecular Biology, Martin-Luther-King-Platz 6, 20146 Hamburg, and Hamburg Centre fo"
+      },
+      {
+        "author_name": "Alke Meents",
+        "author_inst": "Center for Free-Electron Laser Science, DESY, Notkestrasse 85, 22607 Hamburg, Germany"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "biophysics"
   },
   {
     "rel_doi": "10.1101/2020.05.03.074781",
@@ -1456888,31 +1460029,23 @@
     "category": "oncology"
   },
   {
-    "rel_doi": "10.1101/2020.04.27.20081794",
-    "rel_title": "Predicting community mortality risk due to CoVID-19 using machine learning and development of a prediction tool",
+    "rel_doi": "10.1101/2020.04.27.20081539",
+    "rel_title": "An ARIMA Model to Forecast the Spread and the Final Size of COVID-2019 Epidemic in Italy",
     "rel_date": "2020-05-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20081794",
-    "rel_abs": "BackgroundThe recent pandemic of CoVID-19 has emerged as a threat to global health security. There are a very few prognostic models on CoVID-19 using machine learning.\n\nObjectivesTo predict mortality among confirmed CoVID-19 patients in South Korea using machine learning and deploy the best performing algorithm as an open-source online prediction tool for decision-making.\n\nMaterials and methodsMortality for confirmed CoVID-19 patients (n=3,299) between January 20, 2020 and April 30, 2020 was predicted using five machine learning algorithms (logistic regression, support vector machine, K nearest neighbor, random forest and gradient boosting). Performance of the algorithms was compared, and the best performing algorithm was deployed as an online prediction tool.\n\nResultsThe random forest algorithm was the best performer in terms of predictive ability (accuracy=0.981), discrimination (area under ROC curve=0.886), calibration (Matthews Correlation Coefficient=0.459; Brier Score=0.063) and. The best performer algorithm (random forest) was deployed as the online CoVID-19 Community Mortality Risk Prediction tool named CoCoMoRP (https://ashis-das.shinyapps.io/CoCoMoRP/).\n\nConclusionsWe describe the development and deployment of an open-source machine learning tool to predict mortality risk among CoVID-19 confirmed patients using publicly available surveillance data. This tool can be utilized by potential stakeholders such as health providers and policy makers to triage patients at the community level in addition to other approaches.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20081539",
+    "rel_abs": "Coronavirus disease (COVID-2019) is a severe ongoing novel pandemic that is spreading quickly across the world. Italy, that is widely considered one of the main epicenters of the pandemic, has registered the highest COVID-2019 death rates and death toll in the world, to the present day. In this article I estimate an autoregressive integrated moving average (ARIMA) model to forecast the epidemic trend over the period after April 4, 2020, by using the Italian epidemiological data at national and regional level. The data refer to the number of daily confirmed cases officially registered by the Italian Ministry of Health (www.salute.gov.it) for the period February 20 to April 4, 2020. The main advantage of this model is that it is easy to manage and fit. Moreover, it may give a first understanding of the basic trends, by suggesting the hypothetic epidemics inflection point and final size.\n\nHighlights ARIMA models allow in an easy way to investigate COVID-2019 trends, which are nowadays of huge economic and social impact.\nThese data may be used by the health authority to continuously monitor the epidemic and to better allocate the available resources.\nThe results suggest that the epidemic spread inflection point, in term of cumulative cases, will be reached at the end of May.\nFurther useful and more precise forecasting may be provided by updating these data or applying the model to other regions and countries.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "ASHIS DAS",
-        "author_inst": "The World Bank"
-      },
-      {
-        "author_name": "Shiba Mishra",
-        "author_inst": "Credit Suisse Private Limited"
-      },
-      {
-        "author_name": "Saji Saraswathy Gopalan",
-        "author_inst": "The World Bank Group"
+        "author_name": "Gaetano Perone",
+        "author_inst": "University of Bergamo"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2020.04.28.20081687",
@@ -1458770,59 +1461903,39 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.27.20081893",
-    "rel_title": "Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold",
+    "rel_doi": "10.1101/2020.04.27.20074849",
+    "rel_title": "Performance verification of detecting COVID-19 specific antibody by using four chemiluminescence immunoassay systems",
     "rel_date": "2020-05-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20081893",
-    "rel_abs": "Individual variation in susceptibility and exposure is subject to selection by natural infection, accelerating the acquisition of immunity, and reducing herd immunity thresholds and epidemic final sizes. This is a manifestation of a wider population phenomenon known as \"frailty variation\". Despite theoretical understanding, public health policies continue to be guided by mathematical models that leave out considerable variation and as a result inflate projected disease burdens and overestimate the impact of interventions. Here we focus on trajectories of the coronavirus disease (COVID-19) pandemic in England and Scotland until November 2021. We fit models to series of daily deaths and infer relevant epidemiological parameters, including coefficients of variation and effects of non-pharmaceutical interventions which we find in agreement with independent empirical estimates based on contact surveys. Our estimates are robust to whether the analysed data series encompass one or two pandemic waves and enable projections compatible with subsequent dynamics. We conclude that vaccination programmes may have contributed modestly to the acquisition of herd immunity in populations with high levels of pre-existing naturally acquired immunity, while being critical to protect vulnerable individuals from severe outcomes as the virus becomes endemic.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC=\"FIGDIR/small/20081893v5_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (19K):\norg.highwire.dtl.DTLVardef@aeb87forg.highwire.dtl.DTLVardef@d2c441org.highwire.dtl.DTLVardef@152aeceorg.highwire.dtl.DTLVardef@1526779_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIVariation in susceptibility/exposure responds to selection by natural infection\nC_LIO_LISelection on susceptibility/exposure flattens epidemic curves\nC_LIO_LIModels with incomplete heterogeneity overestimate intervention impacts\nC_LIO_LIIndividual variation lowered the natural herd immunity threshold for SARS-CoV-2\nC_LI",
-    "rel_num_authors": 10,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20074849",
+    "rel_abs": "BackgroundThe purpose of current study is to evaluate the analytical performance of seven kits for detecting IgM/IgG antibody of corona virus (2019-nCoV) by using four chemiluminescence immunoassay systems.\n\nMethods50 patients diagnosed with 2019-nCoV infection and 130 controls without corona virus infection from the General Hospital of Chongqing were enrolled in current retrospective study. Four chemiluminescence immunoassay systems including seven IgM/IgG antibody detection Kits for 2019-nCoV (A_IgM, A_IgG, B_IgM, B_IgG, C_IgM, C_IgG, D_Ab) were employed to detecting antibody concentration. Chi-square test, receiver operating characteristic (ROC) curve and Youdens index were demonstrated to verify the cutoff value of each detection system.\n\nResultsThe repeatability verification results of the A, B, C, and D system are all qualified. D-Ab performances best (92% sensitivity and 99.23% specificity), and B_IgM worse than other systems. Except for the system of A_IgM and C_IgG, the optimal diagnostic thresholds and cutoff value of other kits from recommendations are inconsistent with each other. B_IgM got the worst AUC and C_IgG had the best diagnostic accuracy. More importantly, B_IgG system have the highest false positive rate for testing patients with AIDS, tumor and pregnant. A_IgM system test showed highest false positive rates among elder over 90 years old.\n\nConclusionsSystems for CoVID-2019 IgM/IgG antibody test performance difference. Serum diagnosis kit of D-Ab is the most reliable detecting system for 2019-nCoV antibody, which can be used as an alternative method for nucleic acid testing.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "M. Gabriela M. Gomes",
-        "author_inst": "Liverpool School of Tropical Medicine"
+        "author_name": "Yafang Wan",
+        "author_inst": "Chongqing General Hospital"
       },
       {
-        "author_name": "Marcelo U. Ferreira",
-        "author_inst": "Universidade de Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Rodrigo M. Corder",
-        "author_inst": "Universidade de Sao Paulo, Brazil"
-      },
-      {
-        "author_name": "Jessica G. King",
-        "author_inst": "University of Edinburgh, UK"
-      },
-      {
-        "author_name": "Caetano Souto-Maior",
-        "author_inst": "National Institutes of Health, USA"
-      },
-      {
-        "author_name": "Carlos Penha-Goncalves",
-        "author_inst": "Instituto Gulbenkian de Ciencia, Portugal"
-      },
-      {
-        "author_name": "Guilherme Goncalves",
-        "author_inst": "Universidade do Porto, Portugal"
+        "author_name": "Zhijie Li",
+        "author_inst": "The General Hospital of Chongqing"
       },
       {
-        "author_name": "Maria Chikina",
-        "author_inst": "University of Pittsburgh, USA"
+        "author_name": "Kun Wang",
+        "author_inst": "The General Hospital of Chongqing"
       },
       {
-        "author_name": "Wesley Pegden",
-        "author_inst": "Carnegie Mellon University, USA"
+        "author_name": "Tian Li",
+        "author_inst": "The General Hospital of Chongqing"
       },
       {
-        "author_name": "Ricardo Aguas",
-        "author_inst": "University of Oxford, UK"
+        "author_name": "Pu Liao",
+        "author_inst": "The General Hospital of Chongqing"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.05.01.071688",
@@ -1460368,119 +1463481,43 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.04.28.20083089",
-    "rel_title": "A possible role of immunopathogenesis in COVID-19 progression",
-    "rel_date": "2020-05-02",
+    "rel_doi": "10.1101/2020.04.26.20080341",
+    "rel_title": "How the COVID-19 pandemic is favoring the adoption of digital technologies in healthcare: a rapid literature review",
+    "rel_date": "2020-05-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083089",
-    "rel_abs": "BackgroundThe role of cellular immunity in pathogenesis of COVID-19 is unclear and conflicting data points to insufficient or pathogenic immunity as drivers of COVID-19 progression. Here we aimed to delineate the phenotype and function of the immune system in patients with moderate, severe, and critical COVID-19.\n\nMethodsIn this prospective study, we included 53 patients with moderate (n=21), severe (n=18), and critical (n=14) COVID-19 manifestations. Using multiparametric flow cytometry we compared quantitative, phenotypic, and functional characteristics of circulating immune cells, SARS-CoV-2 antigen-reactive T-cells, and humoral immunity.\n\nResultsDeep phenotypic profiling revealed a depletion of circulating bulk CD8+ T-cells, CD4+ and CD8+ T-cell subsets with activated memory/effector T-cells expressing CD57+, HLA-DR+, and the key activation and migration molecule CD11a++ in critical COVID-19. Importantly, survival from acute respiratory distress syndrome was accompanied by a recovery of the depleted CD11++ T-cell subsets including T-cells expressing CD28, CD57, HLA-DR activation/effector molecules. We further observed a stronger response of S-protein specific T-cells producing inflammatory cytokines in critical COVID-19 cases. This seemingly contradictory observation is in fact confirmation of the underlying immunopathogenesis in patients with critical COVID-19.\n\nConclusionOur findings suggest a CD11a-based immune signature as a possible prognostic marker for disease development. Our data further reveal that increased rather than decreased SARS-CoV-2 specific T cell immunity is associated with adverse outcome in COVID-19. Tissue migration of activated effectors T-cells may constitute a crucial cornerstone in the immunopathogenesis of SARS-CoV-2 associated tissue injury.\n\nTrial registrationThis is a prospective observational study without a trial registration number.\n\nFundingThis work was supported by grants from Mercator Foundation, the BMBF e:KID (01ZX1612A), and BMBF NoChro (FKZ 13GW0338B).\n\n25 Word summaryStronger S-protein reactivity and decreased frequency of activated memory/effector T-cells expressing CD11a++ suggests immunopathogenesis in critical COVID-19 mediated by tissue migration of activated effector T-cells.",
-    "rel_num_authors": 25,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20080341",
+    "rel_abs": "BackgroundHealthcare is responding to the COVID-19 pandemic through the fast adoption of digital solutions and advanced technology tools. The aim of this study is to describe which digital solutions have been reported in the scientific literature and to investigate their potential impact in the fight against the COVID-19 pandemic.\n\nMethodsWe conducted a literature review searching PubMed and MedrXiv with terms considered adequate to find relevant literature on the use of digital technologies in response to COVID-19. We developed an impact score to evaluate the potential impact on COVID-19 pandemic of all the digital solutions addressed in the selected papers.\n\nResultsThe search identified 269 articles, of which 145 full-text articles were assessed and 124 included in the review after screening and impact evaluation. Of selected articles, most of them addressed the use of digital technologies for diagnosis, surveillance and prevention. We report that digital solutions and innovative technologies have mainly been proposed for the diagnosis of COVID-19. In particular, within the reviewed articles we identified numerous suggestions on the use of artificial-intelligence-powered tools for the diagnosis and screening of COVID-19. Digital technologies are useful also for prevention and surveillance measures, for example through contact-tracing apps or monitoring of internet searches and social media usage.\n\nDiscussionIt is worth taking advantage of the push given by the crisis, and mandatory to keep track of the digital solutions proposed today to implement tomorrows best practices and models of care, and to be ready for any new moments of emergency.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Moritz Anft",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Krystallenia Paniskaki",
-        "author_inst": "Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Germany"
-      },
-      {
-        "author_name": "Arturo Blazquez-Navarro",
-        "author_inst": "Charite Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute of Health, Berlin-Bran"
-      },
-      {
-        "author_name": "Adrian Atila Nicolas Doevelaar",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Felix Seibert",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Bodo Hoelzer",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Sarah Skrzypczyk",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Eva Kohut",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Julia Kurek",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Jan Zapka",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
-      },
-      {
-        "author_name": "Patrizia Wehler",
-        "author_inst": "Charite Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute of Health, Berlin-Bran"
-      },
-      {
-        "author_name": "Sviatlana Kaliszczyk",
-        "author_inst": "Charite Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute of Health, Berlin-Bran"
-      },
-      {
-        "author_name": "Sharon Bajda",
-        "author_inst": "Charite Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute of Health, Berlin-Bran"
-      },
-      {
-        "author_name": "Constantin Thieme",
-        "author_inst": "Charite Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute of Health, Berlin-Bran"
-      },
-      {
-        "author_name": "Toralf Roch",
-        "author_inst": "Charite Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute of Health, Berlin-Bran"
-      },
-      {
-        "author_name": "Margarethe Justine Konik",
-        "author_inst": "Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Germany"
-      },
-      {
-        "author_name": "Thorsten Brenner",
-        "author_inst": "Department of Anesthesiology, University Hospital Essen, University Duisburg-Essen, Germany"
-      },
-      {
-        "author_name": "Clemens Tempfer",
-        "author_inst": "Department of Gynecology and Obstetrics, Marien Hospital Herne, University Hospital of the Ruhr-University Bochum, Hoelkeskampring 40, 44625 Herne, Germany"
-      },
-      {
-        "author_name": "Carsten Watzl",
-        "author_inst": "Department of Immunology, Leibniz Research Centre for Working Environment and Human Factors at the Technical University Dortmund (IfADo), Ardeystrasse 67, 44139"
-      },
-      {
-        "author_name": "Sebastian Dolff",
-        "author_inst": "Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Germany"
+        "author_name": "Davide Golinelli",
+        "author_inst": "DIBINEM, University of Bologna"
       },
       {
-        "author_name": "Ulf Dittmer",
-        "author_inst": "Germany Institute for Virology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany"
+        "author_name": "Erik Boetto",
+        "author_inst": "University of Bologna"
       },
       {
-        "author_name": "Timm Westhoff",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
+        "author_name": "Gherardo Carullo",
+        "author_inst": "Department of Italian and Supranational Public Law, University of Milan, Italy"
       },
       {
-        "author_name": "Oliver Witzke",
-        "author_inst": "Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Germany"
+        "author_name": "Andrea Giovanni Nuzzolese",
+        "author_inst": "STLab, ISTC-CNR"
       },
       {
-        "author_name": "Ulrik Stervbo",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
+        "author_name": "Maria Paola Landini",
+        "author_inst": "IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy"
       },
       {
-        "author_name": "Nina Babel",
-        "author_inst": "Center for Translational Medicine and Immune Diagnostics Laboratory, Medical Department I, Marien Hospital Herne, University Hospital of the Ruhr-University Boc"
+        "author_name": "Maria Pia Fantini",
+        "author_inst": "DIBINEM, University of Bologna"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "allergy and immunology"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2020.04.26.20080143",
@@ -1462014,27 +1465051,115 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.26.20080770",
-    "rel_title": "A first study on the impact of containment measure on COVID-19 spread in Morocco",
+    "rel_doi": "10.1101/2020.04.27.20076000",
+    "rel_title": "The effect of a national lockdown in response to COVID-19 pandemic on the prevalence of clinical symptoms in the population",
     "rel_date": "2020-05-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20080770",
-    "rel_abs": "BackgroundSince the appearance of the first case of COVID-19 in Morocco, the cumulative number of reported infectious cases continues to increase and, consequently, the government imposed the containment measure within the country. Our aim is to predict the impact of the compulsory containment on COVID-19 spread. Earlier knowledge of the epidemic characteristics of COVID-19 transmission related to Morocco will be of great interest to establish an optimal plan-of-action to control the epidemic.\n\nMethodUsing a Susceptible-Asymptomatic-Infectious model and the data of reported cumulative confirmed cases in Morocco from March 2nd to April 9, 2020, we determined the basic and control reproduction numbers and we estimated the model parameter values. Furthermore, simulations of different scenarios of containment are performed.\n\nResultsEpidemic characteristics are predicted according to different rates of containment. The basic reproduction number is estimated to be 2.9949, with CI(2.6729-3.1485). Furthermore, a threshold value of containment rate, below which the epidemic duration is postponed, is determined.\n\nConclusionOur findings show that the basic reproduction number reflects a high speed of spread of the epidemic. Furthermore, the compulsory containment can be efficient if more than 73% of population are confined. However, even with 90% of containment, the end-time is estimated to happen on July 4th which can be harmful and lead to consequent social-economic damages. Thus, containment need to be accompanied by other measures such as mass testing to reduce the size of asymptomatic population. Indeed, our sensitivity analysis investigation shows that the COVID-19 dynamics depends strongly on the asymptomatic duration as well as the contact and containment rates. Our results can help the Moroccan government to anticipate the spread of COVID-19 and avoid human loses and consequent social-economic damages as well.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20076000",
+    "rel_abs": "The vast and rapid spread of COVID-19 calls for immediate action from policy-makers, and indeed, many countries have implemented lockdown measures to varying degrees. Here, we utilized nationwide surveys that assess COVID-19 associated symptoms to analyse the effect of the lockdown policy in Israel on the prevalence of clinical symptoms in the population. Daily symptom surveys were distributed online and included questions regarding fever, respiratory symptoms, gastrointestinal symptoms, anosmia and ageusia. A total of 2,071,349 survey responses were analysed. We defined a single measure of symptoms, Symptoms Average (SA), as the mean number of symptoms reported by responders. Data were collected between March 15th to June 3rd, 2020. Notably, on the population level, following severe lockdown measures between March 15 th and April 20th, SA sharply declined by 83.8% (p < 0.05), as did every single symptom, including the most common symptoms reported by our responders, cough and rhinorrhea and\\or nasal congestion, which decreased by 74.1% (p < 0.05) and 69.6% (p < 0.05), respectively. Similarly, on the individual level, analysis of repeated responses from the same individuals (N = 208,637) over time also showed a decrease in symptoms during this time period. Moreover, the reduction in symptoms was observed in all cities in Israel, and in several stratifications of demographic characteristics. Different symptoms exhibit different reduction dynamics, suggesting differences in the nature of the symptoms or in the underlying medical conditions. Between May 13th and June 3rd, following several subsequent lockdown relief measures, we observed an increase in individual symptoms and in SA, which increased by 31.42%. Overall, these results demonstrate a profound decrease in a variety of clinical symptoms following the implementation of a lockdown in Israel, and an increase in the prevalence of symptoms following the loosening of lockdown restrictions. As our survey symptoms are not specific to COVID-19 infection, this effect likely represents an overall nationwide reduction in the prevalence of infectious diseases, including COVID-19. This quantification may be of major interest for COVID-19 pandemic, as many countries consider implementation of lockdown strategies.",
+    "rel_num_authors": 24,
     "rel_authors": [
       {
-        "author_name": "Aayah Hammoumi",
-        "author_inst": "Cadi Ayyad University"
+        "author_name": "Ayya Keshet",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Redouane Qesmi",
-        "author_inst": "USMBA University"
+        "author_name": "Amir Gavrieli",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Hagai Rossman",
+        "author_inst": "Weizmann institute of science"
+      },
+      {
+        "author_name": "Smadar Shilo",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Tomer Meir",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Tal Karady",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Amit Lavon",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Dmitry Kolobkov",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Iris Kalka",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Saar Shoer",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Anastasia Godneva",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Ori Cohen",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Adam Kariv",
+        "author_inst": "The public knowledge workshop"
+      },
+      {
+        "author_name": "Ori Hoch",
+        "author_inst": "The public knowledge workshop"
+      },
+      {
+        "author_name": "Mushon Zer-Aviv",
+        "author_inst": "The public knowledge workshop"
+      },
+      {
+        "author_name": "Noam Castel",
+        "author_inst": "The public knowledge workshop"
+      },
+      {
+        "author_name": "Anat Ekka Zohar",
+        "author_inst": "Maccabi Healthcare Services"
+      },
+      {
+        "author_name": "Angela Irony",
+        "author_inst": "Maccabi Healthcare Services"
+      },
+      {
+        "author_name": "Benjamin Geiger",
+        "author_inst": "Weizmann Institute of Science"
+      },
+      {
+        "author_name": "Yuval Dor",
+        "author_inst": "Hebrew University of Jerusalem"
+      },
+      {
+        "author_name": "Dorit Hizi",
+        "author_inst": "The public knowledge workshop"
+      },
+      {
+        "author_name": "Ran Balicer",
+        "author_inst": "Clalit Health Services"
+      },
+      {
+        "author_name": "Varda Shalev",
+        "author_inst": "Maccabi Healthcare Services"
+      },
+      {
+        "author_name": "Eran Segal",
+        "author_inst": "Weizmann Institute of Science"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.26.20080788",
@@ -1463172,67 +1466297,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.30.069922",
-    "rel_title": "Broad-spectrum antiviral activity of naproxen: from Influenza A to SARS-CoV-2 Coronavirus",
+    "rel_doi": "10.1101/2020.04.30.071175",
+    "rel_title": "Electrostatic Characteristics of SARS-CoV-2 Spike and Human ACE2 Protein Variations Predict Mutable Binding Efficacy",
     "rel_date": "2020-05-01",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.30.069922",
-    "rel_abs": "There is an urgent need for specific antiviral drugs directed against SARS-CoV-2 both to prevent the most severe forms of COVID-19 and to reduce viral excretion and subsequent virus dissemination; in the present pandemic context, drug repurposing is a priority. Targeting the nucleoprotein N of the SARS-CoV-2 coronavirus in order to inhibit its association with viral RNA could be a strategy to impeding viral replication and possibly other essential functions associated with viral N. The antiviral properties of naproxen, belonging to the NSAID family, previously demonstrated against Influenza A virus, were evaluated against SARS-CoV-2. Naproxen binding to the nucleoprotein of SARS-CoV2 was shown by molecular modeling. In VeroE6 cells and reconstituted human primary respiratory epithelium models of SARS-CoV-2 infection, naproxen inhibited viral replication and protected the bronchial epithelia against SARS-CoV-2 induced-damage. The benefit of naproxen addition to the standard of care is tested in an on-going clinical study.",
-    "rel_num_authors": 12,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.30.071175",
+    "rel_abs": "SARS-CoV-2 is a novel virus that is presumed to have emerged from bats to crossover into humans in late 2019. As the global pandemic ensues, scientist are working to evaluate the virus and develop a vaccine to counteract the deadly disease that has impacted lives across the entire globe. We perform computational electrostatic simulations on multiple variants of SARS-CoV-2 spike protein s1 in complex with human angiotensin-converting enzyme 2 (ACE2) variants to examine differences in electrostatic interactions across the various complexes. Calculations are performed across the physiological pH range to also examine the impact of pH on these interactions. Two of six spike protein s1 variations having greater electric forces at pH levels consistent with nasal secretions and significant variations in force across all five variants of ACE2. Five out of six spike protein s1 variations have relatively consistent forces at pH levels of the lung, and one spike protein s1 variant that has low potential across a wide range of pH. These predictions indicate that variants of SARS-CoV-2 spike proteins and human ACE2 in certain combinations could potentially play a role in increased binding efficacy of SARS-CoV-2 in vivo.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Olivier Terrier",
-        "author_inst": "Centre International de Recherche en Infectiologie"
-      },
-      {
-        "author_name": "Sebastien Dilly",
-        "author_inst": "INSERM  and Sorbonne University, CRSA UMR S_938"
-      },
-      {
-        "author_name": "Mario-Andres Pizzorno",
-        "author_inst": "Lyon I University, CIRI, INSERM 1111, CNRS UMR 5308, Ens de Lyon"
-      },
-      {
-        "author_name": "Julien Henri",
-        "author_inst": "Institut de Biologie Physico-Chimique CNRS UMR 8226"
-      },
-      {
-        "author_name": "Francis Berenbaum",
-        "author_inst": "Sorbonne University, INSERM, CRSA UMR S_938, AP-HP"
-      },
-      {
-        "author_name": "Bruno Lina",
-        "author_inst": "Lyon I University, CIRI, INSERM U 1111, CNRS UMR 5308, Ens de Lyon"
-      },
-      {
-        "author_name": "Bruno Feve",
-        "author_inst": "INSERM and Sorbonne Universitu CRSA UMR S_938, AP-HP, ICAN"
-      },
-      {
-        "author_name": "Frederic Adnet",
-        "author_inst": "AP-HP, SAMU, Avicenne Hospital"
-      },
-      {
-        "author_name": "Michele Sabbah",
-        "author_inst": "INSERM and Sorbonne University, CRSA UMR S_938"
-      },
-      {
-        "author_name": "Manuel Rosa-Calavatra",
-        "author_inst": "University Lyon I, CIRI, INSERM U1111, CNRS UMR 5308, Ens de Lyon"
-      },
-      {
-        "author_name": "Vincent Marechal",
-        "author_inst": "INSERM and Sorbonne University, CRSA UMR S_938"
+        "author_name": "Scott P Morton",
+        "author_inst": "Middle Tennessee State University"
       },
       {
-        "author_name": "Anny Slama-Schwok",
-        "author_inst": "INSERM  and Sorbonne University, CRSA UMR S_938"
+        "author_name": "Joshua L Phillips",
+        "author_inst": "Middle Tennessee State University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "molecular biology"
   },
   {
     "rel_doi": "10.1101/2020.04.30.070383",
@@ -1464710,29 +1467795,21 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.27.20078329",
-    "rel_title": "Population-scale testing can suppress the spread of COVID-19",
+    "rel_doi": "10.1101/2020.04.24.20078717",
+    "rel_title": "Full lockdown policies in Western Europe countries have no evident impacts on the COVID-19 epidemic.",
     "rel_date": "2020-05-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20078329",
-    "rel_abs": "We propose an additional intervention that would contribute to the control of the COVID-19 pandemic, offer more protection for people working in essential jobs, and help guide an eventual reopening of society. The intervention is based on: (1) testing every individual (2) repeatedly, and (3) self-quarantine of infected individuals. Using a standard epidemiological model (SIR), we show here that by identification and isolation of the majority of infectious individuals, including those who may be asymptomatic, the reproduction number R0 of SARS-CoV-2 would be reduced well below 1.0, and the epidemic would collapse. We replicate these observations in a more complex stochastic dynamic model on a social network graph. We also find that the testing regime would be additive to other interventions, and be effective at any level of prevalence. If adopted as a policy, any industrial society could sustain the regime for as long as it takes to find a safe and effective cure or vaccine. Our model also indicates that unlike sampling-based tests, population-scale testing does not need to be very accurate: false negative rates up to 15% could be tolerated if 80% comply with testing every ten days, and false positives can be almost arbitrarily high when a high fraction of the population is already effectively quarantined. Testing at the required scale would be feasible if existing qPCR-based methods are scaled up and multiplexed. A mass produced, low throughput field test kit could also be carried out at home. Economic analysis also supports the feasibility of the approach: current reagent costs for tests are in the range of a dollar or less, and the estimated benefits for population-scale testing are so large that the policy would be cost-effective even if the costs were larger by more than two orders of magnitude. To identify both active and previous infections, both viral RNA and antibodies could be tested. All technologies to build such test kits, and to produce them in the scale required to test the entire worlds population exist already. Integrating them, scaling up production, and implementing the testing regime will require resources and planning, but at a scale that is very small compared to the effort that every nation would devote to defending itself against a more traditional foe.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078717",
+    "rel_abs": "This phenomenological study assesses the impacts of full lockdown strategies applied in Italy, France, Spain and United Kingdom, on the slowdown of the 2020 COVID-19 outbreak. Comparing the trajectory of the epidemic before and after the lockdown, we find no evidence of any discontinuity in the growth rate, doubling time, and reproduction number trends. Extrapolating pre-lockdown growth rate trends, we provide estimates of the death toll in the absence of any lockdown policies, and show that these strategies might not have saved any life in western Europe. We also show that neighboring countries applying less restrictive social distancing measures (as opposed to police-enforced home containment) experience a very similar time evolution of the epidemic.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Jussi Taipale",
-        "author_inst": "University  of Cambridge"
-      },
-      {
-        "author_name": "Paul Romer",
-        "author_inst": "New York University"
-      },
-      {
-        "author_name": "Sten Linnarsson",
-        "author_inst": "Karolinska Institutet"
+        "author_name": "Thomas A. J. Meunier",
+        "author_inst": "Woods Hole Oceanographic Institution"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1465920,83 +1468997,107 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.04.29.069054",
-    "rel_title": "Spike mutation pipeline reveals the emergence of a more transmissible form of SARS-CoV-2",
+    "rel_doi": "10.1101/2020.04.30.029736",
+    "rel_title": "Susceptibility of tree shrew to SARS-CoV-2 infection",
     "rel_date": "2020-04-30",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.29.069054",
-    "rel_abs": "We have developed an analysis pipeline to facilitate real-time mutation tracking in SARS-CoV-2, focusing initially on the Spike (S) protein because it mediates infection of human cells and is the target of most vaccine strategies and antibody-based therapeutics. To date we have identified thirteen mutations in Spike that are accumulating. Mutations are considered in a broader phylogenetic context, geographically, and over time, to provide an early warning system to reveal mutations that may confer selective advantages in transmission or resistance to interventions. Each one is evaluated for evidence of positive selection, and the implications of the mutation are explored through structural modeling. The mutation Spike D614G is of urgent concern; it began spreading in Europe in early February, and when introduced to new regions it rapidly becomes the dominant form. Also, we present evidence of recombination between locally circulating strains, indicative of multiple strain infections. These finding have important implications for SARS-CoV-2 transmission, pathogenesis and immune interventions.",
-    "rel_num_authors": 16,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.30.029736",
+    "rel_abs": "Since SARS-CoV-2 became a pandemic event in the world, it has not only caused huge economic losses, but also a serious threat to global public health. Many scientific questions about SARS-CoV-2 and COVID-19 were raised and urgently need to be answered, including the susceptibility of animals to SARS-CoV-2 infection. Here we tested whether tree shrew, an emerging experimental animal domesticated from wild animal, is susceptible to SARS-CoV-2 infection. No clinical signs were observed in SARS-CoV-2 inoculated tree shrews during this experiment except the increasing body temperature (above 39{degrees} C) particular in female animals during infection. Low levels of virus shedding and replication in tissues occurred in all three age groups, each of which showed his own characteristics. Histopathological examine revealed that pulmonary abnormalities were mild but the main changes although slight lesions were also observed in other tissues. In summary, tree shrew is not susceptible to SARS-CoV-2 infection and may not be a suitable animal for COVID-19 related researches.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Bette Korber",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Yuan Zhao",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Will Fischer",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Junbin Wang",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical Collegeof"
       },
       {
-        "author_name": "S. Gnana Gnanakaran",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Dexuan Kuang",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Heyjin Yoon",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Jingwen Xu",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "James Theiler",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Mengli Yang",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Werner Abfalterer",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Chunxia Ma",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Brian Foley",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Siwen Zhao",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Elena E Giorgi",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Jingmei Li",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Tanmoy Bhattacharya",
-        "author_inst": "Los Alamos National Laboratory"
+        "author_name": "Haiting Long",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Matthew D Parker",
-        "author_inst": "The University of Sheffield"
+        "author_name": "Kaiyun Ding",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "David G Partridge",
-        "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust"
+        "author_name": "Jiahong Gao",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Cariad M Evans",
-        "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust"
+        "author_name": "Jiansheng Liu",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Thushan de Silva",
-        "author_inst": "University of Sheffield"
+        "author_name": "Haixuan Wang",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "Celia C LaBranche",
-        "author_inst": "Duke Univerisity"
+        "author_name": "Haiyan Li",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "David C Montefiori",
-        "author_inst": "Duke University"
+        "author_name": "Yun Yang",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       },
       {
-        "author_name": "- Sheffield COVID-19 Genomics Group",
-        "author_inst": "-"
+        "author_name": "Wenhai Yu",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
+      },
+      {
+        "author_name": "Jing Yang",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
+      },
+      {
+        "author_name": "Yinqiu Zheng",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
+      },
+      {
+        "author_name": "Daoju Wu",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
+      },
+      {
+        "author_name": "Shuaiyao Lu",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
+      },
+      {
+        "author_name": "Hongqi Liu",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
+      },
+      {
+        "author_name": "Xiaozhong Peng",
+        "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "new results",
-    "category": "evolutionary biology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.04.29.069476",
@@ -1467238,21 +1470339,25 @@
     "category": "genetics"
   },
   {
-    "rel_doi": "10.1101/2020.04.24.20078824",
-    "rel_title": "Estimating COVID-19 Antibody Seroprevalence in Santa Clara County, California. A re-analysis of Bendavid et al.",
+    "rel_doi": "10.1101/2020.04.24.20078808",
+    "rel_title": "Reacting to outbreaks at neighboring localities",
     "rel_date": "2020-04-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078824",
-    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWA recent study by Bendavid et al. claimed that the rate of infection of COVID-19 in Santa Clara county was between 2.49% and 4.16%, 50-85 times higher than the number of officially confirmed cases. The statistical methodology used in that study overestimates of rate of infection given the available data. We jointly estimate the sensitivity and specificity of the test kit along with rate of infection with a simple Bayesian model, arriving at lower estimates of the rate of COVID-19 in Santa Clara county. Re-analyzing their data, we find that the rate of infection was likely between 0.27% and 3.21%.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078808",
+    "rel_abs": "We study the dynamics of epidemics in a networked metapopulation model. In each subpopulation, representing a locality, the disease propagates according to a modified susceptible-exposed-infected-recovered (SEIR) dynamics. In the modified SEIR dynamics, individuals reduce their number of contacts as a function of the weighted sum of cumulative number of cases within the locality and in neighboring localities. We consider a scenario with two localities where disease originates in one locality and is exported to the neighboring locality via travel of exposed (latently infected) individuals. We establish a lower bound on the outbreak size at the origin as a function of the speed of spread. Using the lower bound on the outbreak size at the origin, we establish an upper bound on the outbreak size at the importing locality as a function of the speed of spread and the level of preparedness for the low mobility regime. We evaluate the critical levels of preparedness that stop the disease from spreading at the importing locality. Finally, we show how the benefit of preparedness diminishes under high mobility rates. Our results highlight the importance of preparedness at localities where cases are beginning to rise such that localities can help stop local outbreaks when they respond to the severity of outbreaks in neighboring localities.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Stephen T Bennett",
-        "author_inst": "University of California, Irvine"
+        "author_name": "Ceyhun Eksin",
+        "author_inst": "Texas A&M"
       },
       {
-        "author_name": "Mark Steyvers",
-        "author_inst": "University of California, Irvine"
+        "author_name": "Martial Ndeffo-Mbah",
+        "author_inst": "Texas A&M"
+      },
+      {
+        "author_name": "Joshua S Weitz",
+        "author_inst": "Georgia Institute of Technology"
       }
     ],
     "version": "1",
@@ -1468672,71 +1471777,43 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.24.20078774",
-    "rel_title": "State-by-State prediction of likely COVID-19 scenarios in the United States and assessment of the role of testing and control measures",
+    "rel_doi": "10.1101/2020.04.28.066977",
+    "rel_title": "Controlling the SARS-CoV-2 outbreak, insights from large scale whole genome sequences generated across the world",
     "rel_date": "2020-04-29",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078774",
-    "rel_abs": "Due to the heterogeneity among the States in the US, predicting COVID-19 trends and quantitatively assessing the effects of government testing capability and control measures need to be done via a State-by-State approach. We develop a comprehensive model for COVID-19 incorporating time delays and population movements. With key parameter values determined by empirical data, the model enables the most likely epidemic scenarios to be predicted for each State, which are indicative of whether testing services and control measures are vigorous enough to contain the disease. We find that government control measures play a more important role than testing in suppressing the epidemic. The vast disparities in the epidemic trends among the States imply the need for long-term placement of control measures to fully contain COVID-19.",
-    "rel_num_authors": 13,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.28.066977",
+    "rel_abs": "BackgroundSARS-CoV-2 most likely evolved from a bat beta-coronavirus and started infecting humans in December 2019. Since then it has rapidly infected people around the world, with more than 4.5 million confirmed cases by the middle of May 2020. Early genome sequencing of the virus has enabled the development of molecular diagnostics and the commencement of therapy and vaccine development. The analysis of the early sequences showed relatively few evolutionary selection pressures. However, with the rapid worldwide expansion into diverse human populations, significant genetic variations are becoming increasingly likely. The current limitations on social movement between countries also offers the opportunity for these viral variants to become distinct strains with potential implications for diagnostics, therapies and vaccines.\n\nMethodsWe used the current sequencing archives (NCBI and GISAID) to investigate 15,487 whole genomes, looking for evidence of strain diversification and selective pressure.\n\nResultsWe used 6,294 SNPs to build a phylogenetic tree of SARS-CoV-2 diversity and noted strong evidence for the existence of two major clades and six sub-clades, unevenly distributed across the world. We also noted that convergent evolution has potentially occurred across several locations in the genome, showing selection pressures, including on the spike glycoprotein where we noted a potentially critical mutation that could affect its binding to the ACE2 receptor. We also report on mutations that could prevent current molecular diagnostics from detecting some of the sub-clades.\n\nConclusionThe worldwide whole genome sequencing effort is revealing the challenge of developing SARS-CoV-2 containment tools suitable for everyone and the need for data to be continually evaluated to ensure accuracy in outbreak estimations.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Zheng-Meng Zhai",
-        "author_inst": "East China Normal University"
-      },
-      {
-        "author_name": "Yong-Shang Long",
-        "author_inst": "East China Normal University"
-      },
-      {
-        "author_name": "Jie Kang",
-        "author_inst": "East China Normal University"
-      },
-      {
-        "author_name": "Yi-Lin Li",
-        "author_inst": "East China Normal University"
-      },
-      {
-        "author_name": "Lang Zeng",
-        "author_inst": "East China Normal University"
-      },
-      {
-        "author_name": "Li-Lei Han",
-        "author_inst": "East China Normal University"
-      },
-      {
-        "author_name": "Zhao-Hua Lin",
-        "author_inst": "East China Normal University"
-      },
-      {
-        "author_name": "Yin-Qi Zeng",
-        "author_inst": "East China Normal University"
+        "author_name": "Jody Phelan",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Da-Yu Wu",
-        "author_inst": "East China Normal University"
+        "author_name": "Wouter Deelder",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Ming Tang",
-        "author_inst": "East China Normal University"
+        "author_name": "Daniel Ward",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Di Xu",
-        "author_inst": "Fudan University"
+        "author_name": "Susana Campino",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Zonghua Liu",
-        "author_inst": "East China Normal University"
+        "author_name": "Martin L Hibberd",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       },
       {
-        "author_name": "Ying-Cheng Lai",
-        "author_inst": "Arizona State University - Tempe Campus"
+        "author_name": "Taane G Clark",
+        "author_inst": "London School of Hygiene and Tropical Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nd",
+    "type": "new results",
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.04.29.067983",
@@ -1470158,41 +1473235,301 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.23.20077230",
-    "rel_title": "Analysis of national and international guidelines on respiratory protection equipment for COVID-19 in healthcare settings.",
+    "rel_doi": "10.1101/2020.04.25.20074856",
+    "rel_title": "Test performance evaluation of SARS-CoV-2 serological assays",
     "rel_date": "2020-04-29",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20077230",
-    "rel_abs": "BackgroundConsistent guidelines on respiratory protection for healthcare professionals combined with improved global supply chains are critical to prevent COVID-19. We analysed the guidelines published by national and international societies/organizations on facemasks and respirators to prevent COVID-19 in healthcare settings.\n\nMethodsFrom the 1st January to the 2nd April 2020, guidelines published in four countries (France, Germany, United States, United Kingdom), and two international organizations (US and European Centre for Diseases Control, and World Health Organization) were reviewed to analyse the mask and respirators recommended for healthcare settings during the COVID-19 outbreak. The aerosol generating procedures (AGP) definitions and the strategy recommended for optimizing supplies and overcoming shortages were collected.\n\nFindingsThe recommendation of respirator was universally recommended for AGP across countries, although the type of respirators and what constituted an AGP was variable. Some guidance maintained the use of N95/99 for all contact with confirmed COVID-19 cases (i.e. Germany) whereas others, recommended a surgical mask (i.e. WHO, UK, France). Most guidelines were published in March with either downgraded (US and European CDC), relatively stable (WHO, Germany, and UK), or a mixing of high and low level equipment (France). The strategies to overcome shortage of respiratory protection equipment were based on minimizing the need and rationalizing the use, but also prolonging their use, reusing them after cleaning/sterilization, or using cloth masks.\n\nInterpretationsIn a crisis context, stable and consistent guidelines clearly detailing the respiratory protection type, and their indications, may prevent the confusion and anxiety among frontline staff, and avoid shortage.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.25.20074856",
+    "rel_abs": "BackgroundSerological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data.\n\nMethodWe conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system.\n\nResultsAmong specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8-100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3-100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7-94.8%. No consistent cross-reactivity was observed.\n\nConclusionOur evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies.",
+    "rel_num_authors": 72,
     "rel_authors": [
       {
-        "author_name": "Gabriel Birgand",
-        "author_inst": "Imperial College London"
+        "author_name": "Jeffrey D. Whitman",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Nico T. Mutters",
-        "author_inst": "Heidelberg University Hospital"
+        "author_name": "Joseph Hiatt",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Jonathan Otter",
-        "author_inst": "Imperial College London"
+        "author_name": "Cody T. Mowery",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Vanessa M. Eichel",
-        "author_inst": "Heidelberg University Hospital"
+        "author_name": "Brian R. Shy",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Didier Lepelletier",
-        "author_inst": "CHU de Nantes"
+        "author_name": "Ruby Yu",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Daniel J. Morgan",
-        "author_inst": "University of Maryland School of Medicine"
+        "author_name": "Tori N. Yamamoto",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Ujjwal Rathore",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Gregory M. Goldgof",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Caroline Whitty",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jonathan M Woo",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Antonia E. Gallman",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Tyler E. Miller",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Andrew G. Levine",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "David N. Nguyen",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Sagar P. Bapat",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Joanna Balcerek",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Sophia Bylsma",
+        "author_inst": "University of California, Berkeley"
+      },
+      {
+        "author_name": "Ana M. Lyons",
+        "author_inst": "University of California, Berkeley"
+      },
+      {
+        "author_name": "Stacy Li",
+        "author_inst": "University of California, Berkeley"
+      },
+      {
+        "author_name": "Allison Wai-yi Wong",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Eva Mae Gillis-Buck",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Zachary B. Steinhart",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Youjin Lee",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Ryan Apathy",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Mitchell J. Lipke",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jennifer A. Smith",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Tina Zheng",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Ian C. Boothby",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Erin Isaza",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jackie Chan",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Dante D Acenas II",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jinwoo Lee",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Trisha A. Macrae",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Than S. Kyaw",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "David Wu",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Dianna L. Ng",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Wei Gu",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Vanessa A. York",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Haig A. Eskandarian",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Perri C. Callaway",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Lakshmi Warrier",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Mary E. Moreno",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Justine Levan",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Leonel Torres",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Lila Farrington",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Rita Loudermilk",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Kanishka Koshal",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Kelsey C. Zorn",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Wilfredo F. Garcia-Beltran",
+        "author_inst": "Massachusetts General Hospital"
+      },
+      {
+        "author_name": "Diane Yang",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Michael G. Astudillo",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Bradley E. Bernstein",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Jeffrey A. Gelfand",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Edward T. Ryan",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Richelle C. Charles",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "A. John Iafrate",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Jochen K. Lennerz",
+        "author_inst": "Massachusetts General Hospital/Harvard Medical School"
+      },
+      {
+        "author_name": "Steve Miller",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Charles Y Chiu",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Susan L. Stramer",
+        "author_inst": "American Red Cross"
+      },
+      {
+        "author_name": "Michael R. Wilson",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Aashish Manglik",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Chun Jimmie Ye",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Nevan J. Krogan",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Mark S. Anderson",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Jason G. Cyster",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Joel D. Ernst",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Alan H.B. Wu",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Kara L. Lynch",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Caryn Bern",
+        "author_inst": "University of California, San Francisco"
       },
       {
-        "author_name": "Jean Christophe Lucet",
-        "author_inst": "AP-HP, Hopital Bichat  Claude Bernard"
+        "author_name": "Patrick D. Hsu",
+        "author_inst": "University of California, Berkeley"
+      },
+      {
+        "author_name": "Alexander Marson",
+        "author_inst": "University of California, San Francisco"
       }
     ],
     "version": "1",
@@ -1471264,215 +1474601,163 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.26.20073411",
-    "rel_title": "Machine Learning to Predict Mortality and Critical Events in COVID-19 Positive New York City Patients",
+    "rel_doi": "10.1101/2020.04.22.20074351",
+    "rel_title": "Resilient SARS-CoV-2 diagnostics workflows including viral heat inactivation",
     "rel_date": "2020-04-28",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20073411",
-    "rel_abs": "Coronavirus 2019 (COVID-19), caused by the SARS-CoV-2 virus, has become the deadliest pandemic in modern history, reaching nearly every country worldwide and overwhelming healthcare institutions. As of April 20, there have been more than 2.4 million confirmed cases with over 160,000 deaths. Extreme case surges coupled with challenges in forecasting the clinical course of affected patients have necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods for achieving this are lacking. In this paper, we use electronic health records from over 3,055 New York City confirmed COVID-19 positive patients across five hospitals in the Mount Sinai Health System and present a decision tree-based machine learning model for predicting in-hospital mortality and critical events. This model is first trained on patients from a single hospital and then externally validated on patients from four other hospitals. We achieve strong performance, notably predicting mortality at 1 week with an AUC-ROC of 0.84. Finally, we establish model interpretability by calculating SHAP scores to identify decisive features, including age, inflammatory markers (procalcitonin and LDH), and coagulation parameters (PT, PTT, D-Dimer). To our knowledge, this is one of the first models with external validation to both predict outcomes in COVID-19 patients with strong validation performance and identify key contributors in outcome prediction that may assist clinicians in making effective patient management decisions.\n\nOne-Sentence SummaryWe identify clinical features that robustly predict mortality and critical events in a large cohort of COVID-19 positive patients in New York City.",
-    "rel_num_authors": 49,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20074351",
+    "rel_abs": "There is a worldwide need for reagents to perform SARS-CoV-2 detection. Some laboratories have implemented kit-free protocols, but many others do not have the capacity to develop these and/or perform manual processing. We provide multiple workflows for SARS-CoV-2 nucleic acid detection in clinical samples by comparing several commercially available RNA extraction methods: QIAamp Viral RNA Mini Kit (QIAgen), RNAdvance Blood/Viral (Beckman) and Mag-Bind Viral DNA/RNA 96 Kit (Omega Bio-tek). We also compared One-step RT-qPCR reagents: TaqMan Fast Virus 1-Step Master Mix (FastVirus, ThermoFisher Scientific), qPCRBIO Probe 1-Step Go Lo-ROX (PCR Biosystems) and Luna(R) Universal Probe One-Step RT-qPCR Kit (Luna, NEB). We used primer-probes that detect viral N (EUA CDC) and RdRP (PHE guidelines). All RNA extraction methods provided similar results. FastVirus and Luna proved most sensitive. N detection was more reliable than that of RdRP, particularly in samples with low viral titres. Importantly, we demonstrate that treatment of nasopharyngeal swabs with 70 degrees for 10 or 30 min, or 90 degrees for 10 or 30 min (both original variant and B 1.1.7) inactivates SARS-CoV-2 employing plaque assays, and that it has minimal impact on the sensitivity of the qPCR in clinical samples. These findings make SARS-CoV-2 testing portable to settings that do not have CL-3 facilities. In summary, we provide several testing pipelines that can be easily implemented in other laboratories and have made all our protocols and SOPs freely available at https://osf.io/uebvj/.",
+    "rel_num_authors": 36,
     "rel_authors": [
       {
-        "author_name": "Akhil Vaid",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Sulaiman Somani",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Adam J Russak",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Jessica K De Freitas",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Fayzan F Chaudhry",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Ishan Paranjpe",
-        "author_inst": "Ican School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Kipp W Johnson",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Samuel J Lee",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Riccardo Miotto",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Shan Zhao",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Noam Beckmann",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Nidhi Naik",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Kodi Arfer",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
-      },
-      {
-        "author_name": "Arash Kia",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Maria Jose Lista",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Prem Timsina",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Pedro Matos",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Anuradha Lala",
-        "author_inst": "Icahn School of Medicine Mount Sinai"
+        "author_name": "Thomas J.A. Maguire",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Manish Paranjpe",
-        "author_inst": "Harvard Medical School"
+        "author_name": "Kate Poulton",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Patricia Glowe",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Elena Ortiz-Zapater",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Eddye Golden",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Robert Page",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Matteo Danieletto",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Helin Sertkaya",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Manbir Singh",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Ana Maria Ortega-Prieto",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Dara Meyer",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Aoife O'Byrne",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Paul F O'Reilly",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Clement Bouton",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Laura H Huckins",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Ruth E Dickenson",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Patricia Kovatch",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Mattia Ficarelli",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Joseph Finkelstein",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Jose M Jimenez-Guardeno",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Robert M Freeman",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Mark Howard",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Edgar Argulian",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Gilberto Betancor",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Andrew Kasarskis",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Rui Pedro Galao",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Bethany Percha",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Suzanne Pickering",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Judith A Aberg",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Adrian W Signell",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Emilia Bagiella",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Harry Wilson",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Carol R Horowitz",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Penny Cliff",
+        "author_inst": "Viapath St Thomas'"
       },
       {
-        "author_name": "Barbara Murphy",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Mark Tan Kia Ik",
+        "author_inst": "St Thomas' Hospital"
       },
       {
-        "author_name": "Eric J Nestler",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Amita Patel",
+        "author_inst": "St Thomas' Hospital"
       },
       {
-        "author_name": "Eric E Schadt",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Eithne MacMahon",
+        "author_inst": "St Thomas' Hospital"
       },
       {
-        "author_name": "Judy H Cho",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Emma Cunningham",
+        "author_inst": "St Thomas' Hospital"
       },
       {
-        "author_name": "Carlos Cordon-Cardo",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Katie Doores",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Valentin Fuster",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Monica Agromayor",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Dennis S Charney",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Juan Martin-Serrano",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "David L Reich",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Esperanza Perucha",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Erwin P Bottinger",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Hannah E Mischo",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Matthew A Levin",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Manu Shankar-Hari",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Jagat Narula",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Rahul Batra",
+        "author_inst": "St Thomas' Hospital"
       },
       {
-        "author_name": "Zahi A Fayad",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Jonathan Edgeworth",
+        "author_inst": "St Thomas' Hospital"
       },
       {
-        "author_name": "Allan Just",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Mark Zuckerman",
+        "author_inst": "King's College Hospital"
       },
       {
-        "author_name": "Alexander W Charney",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Michael H Malim",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Girish N Nadkarni",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Stuart Neil",
+        "author_inst": "King's College London"
       },
       {
-        "author_name": "Benjamin S Glicksberg",
-        "author_inst": "Icahn School of Medicine at Mount Sinai"
+        "author_name": "Rocio Teresa Martinez-Nunez",
+        "author_inst": "King's College London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.24.20072611",
@@ -1472946,111 +1476231,63 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.28.066761",
-    "rel_title": "Heparin inhibits cellular invasion by SARS-CoV-2: structural dependence of the interaction of the surface protein (spike) S1 receptor binding domain with heparin.",
+    "rel_doi": "10.1101/2020.04.27.064139",
+    "rel_title": "A Modular Framework for Multiscale Spatial Modeling of Viral Infection and Immune Response in Epithelial Tissue",
     "rel_date": "2020-04-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.28.066761",
-    "rel_abs": "The dependence of the host on the interaction of hundreds of extracellular proteins with the cell surface glycosaminoglycan heparan sulphate (HS) for the regulation of homeostasis is exploited by many microbial pathogens as a means of adherence and invasion. The closely related polysaccharide heparin, the widely used anticoagulant drug, which is structurally similar to HS and is a common experimental proxy, can be expected to mimic the properties of HS. Heparin prevents infection by a range of viruses if added exogenously, including S-associated coronavirus strain HSR1. Heparin prevents infection by a range of viruses if added exogenously, including S-associated coronavirus strain HSR1. Here, we show that the addition of heparin to Vero cells between 6.25 - 200 g.ml-1, which spans the concentration of heparin in therapeutic use, and inhibits invasion by SARS-CoV-2 at between 44 and 80%. We also demonstrate that heparin binds to the Spike (S1) protein receptor binding domain and induces a conformational change, illustrated by surface plasmon resonance and circular dichroism spectroscopy studies. The structural features of heparin on which this interaction depends were investigated using a library of heparin derivatives and size-defined fragments. Binding is more strongly dependent on the presence of 2-O or 6-O sulphation, and the consequent conformational consequences in the heparin structure, than on N-sulphation. A hexasaccharide is required for conformational changes to be induced in the secondary structure that are comparable to those that arise from heparin binding. Enoxaparin, a low molecular weight clinical anticoagulant, also binds the S1 RBD protein and induces conformational change. These findings have implications for the rapid development of a first-line therapeutic by repurposing heparin as well as for next-generation, tailor-made, GAG-based antiviral agents against SARS-CoV-2 and other members of the Coronaviridae.",
-    "rel_num_authors": 23,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.27.064139",
+    "rel_abs": "Simulations of tissue-specific effects of primary acute viral infections like COVID-19 are essential for understanding disease outcomes and optimizing therapies. Such simulations need to support continuous updating in response to rapid advances in understanding of infection mechanisms, and parallel development of components by multiple groups. We present an open-source platform for multiscale spatiotemporal simulation of an epithelial tissue, viral infection, cellular immune response and tissue damage, specifically designed to be modular and extensible to support continuous updating and parallel development. The base simulation of a simplified patch of epithelial tissue and immune response exhibits distinct patterns of infection dynamics from widespread infection, to recurrence, to clearance. Slower viral internalization and faster immune-cell recruitment slow infection and promote containment. Because antiviral drugs can have side effects and show reduced clinical effectiveness when given later during infection, we studied the effects on progression of treatment potency and time-of-first treatment after infection. In simulations, even a low potency therapy with a drug which reduces the replication rate of viral RNA greatly decreases the total tissue damage and virus burden when given near the beginning of infection. Many combinations of dosage and treatment time lead to stochastic outcomes, with some simulation replicas showing clearance or control (treatment success), while others show rapid infection of all epithelial cells (treatment failure). Thus, while a high potency therapy usually is less effective when given later, treatments at late times are occasionally effective. We illustrate how to extend the platform to model specific virus types (e.g., hepatitis C) and add additional cellular mechanisms (tissue recovery and variable cell susceptibility to infection), using our software modules and publicly-available software repository.\n\nAuthor summaryThis study presents an open-source, extensible, multiscale platform for simulating viral immune interactions in epithelial tissues, which enables the rapid development and deployment of sophisticated models of viruses, infection mechanisms and tissue types. The model is used to investigate how potential treatments influence disease progression. Simulation results suggest that drugs which interfere with virus replication (e.g., remdesivir) yield substantially better infection outcomes when administered prophylactically even at very low doses than when used at high doses as treatment for an infection that has already begun.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Courtney Mycroft-West",
-        "author_inst": "Keele University"
-      },
-      {
-        "author_name": "Dunhao Su",
-        "author_inst": "University of Liverpool"
-      },
-      {
-        "author_name": "Isabel Pagani",
-        "author_inst": "IRCCS San Raffaele Scientific Institute"
-      },
-      {
-        "author_name": "Timothy Rudd",
-        "author_inst": "National Institute for Biological Standards and Control"
-      },
-      {
-        "author_name": "Stefano Elli",
-        "author_inst": "Istituto di Ricerche Chimiche e Biochimiche G. Ronzoni"
-      },
-      {
-        "author_name": "Scott Guimond",
-        "author_inst": "Keele University"
-      },
-      {
-        "author_name": "Gavin Miller",
-        "author_inst": "Keele University"
-      },
-      {
-        "author_name": "Maria Meneghetti",
-        "author_inst": "Universidade Federal de Sao Paulo"
-      },
-      {
-        "author_name": "Helena Nader",
-        "author_inst": "Universidade Federal de Sao Paulo"
-      },
-      {
-        "author_name": "Yong Li",
-        "author_inst": "University of Liverpool"
-      },
-      {
-        "author_name": "Quentin Nunes",
-        "author_inst": "University of Liverpool"
-      },
-      {
-        "author_name": "Patricia Procter",
-        "author_inst": "Keele University"
-      },
-      {
-        "author_name": "Nicasio Mancini",
-        "author_inst": "Universita Vita-Salute San Raffaele"
+        "author_name": "T.J. Sego",
+        "author_inst": "Indiana University"
       },
       {
-        "author_name": "Massimo Clementi",
-        "author_inst": "Universita Vita-Salute San Raffaele"
+        "author_name": "Josua O. Aponte-Serrano",
+        "author_inst": "Indiana University"
       },
       {
-        "author_name": "Antonella Bisio",
-        "author_inst": "Istituto di Ricerche Chimiche e Biochimiche G. Ronzoni"
+        "author_name": "Juliano Ferrari Gianlupi",
+        "author_inst": "Indiana University"
       },
       {
-        "author_name": "Nicholas Forsyth",
-        "author_inst": "Keele University"
+        "author_name": "Samuel Heaps",
+        "author_inst": "Indiana University"
       },
       {
-        "author_name": "Jeremy Turnbull",
-        "author_inst": "University of Liverpool"
+        "author_name": "Kira Breithaupt",
+        "author_inst": "Cognitive Science Program, Indiana University, Bloomington, IN"
       },
       {
-        "author_name": "Marco Guerrini",
-        "author_inst": "Istituto di Ricerche Chimiche e Biochimiche G. Ronzoni"
+        "author_name": "Lutz Brusch",
+        "author_inst": "Center for Information Services and High Performance Computing (ZIH), Technische Universitat Dresden"
       },
       {
-        "author_name": "David Fernig",
-        "author_inst": "University of Liverpool"
+        "author_name": "Jessica Crawshaw",
+        "author_inst": "School of Mathematics and Statistics, University of Melbourne"
       },
       {
-        "author_name": "Elisa Vicenzi",
-        "author_inst": "San Raffaele Scientific Institute"
+        "author_name": "James M. Osborne",
+        "author_inst": "School of Mathematics and Statistics, University of Melbourne"
       },
       {
-        "author_name": "Edwin Yates",
-        "author_inst": "University of Liverpool"
+        "author_name": "Ellen M. Quardokus",
+        "author_inst": "Indiana University"
       },
       {
-        "author_name": "Marcelo Lima",
-        "author_inst": "Keele University"
+        "author_name": "Richard K. Plemper",
+        "author_inst": "Institute for Biomedical Sciences, Georgia State University"
       },
       {
-        "author_name": "Mark A Skidmore",
-        "author_inst": "Keele University"
+        "author_name": "James A. Glazier",
+        "author_inst": "Indiana University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "bioengineering"
   },
   {
     "rel_doi": "10.1101/2020.04.28.065201",
@@ -1474408,17 +1477645,41 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.21.20074450",
-    "rel_title": "The dynamics of Covid-19: weather, demographics and infection timeline",
+    "rel_doi": "10.1101/2020.04.22.20075762",
+    "rel_title": "Proactive social distancing mitigates COVID-19 outbreaks within a month across 58 mainland China cities",
     "rel_date": "2020-04-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20074450",
-    "rel_abs": "We study the effects of temperature, absolute humidity, population density and when country/U.S. state reached 100 cases on early pace of Covid-19 expansion, for all 50 U.S. states and 110 countries with enough data. For U.S. states, weather variables show opposite effects when compared to the case of countries: higher temperature or absolute humidity imply faster early outbreak. The higher the population density or the earlier the date when state reached 100th case, the faster the pace of outbreak. When all variables are considered, only population density and the timeline variable show statistical significance. Discounting the effect of the timeline variable, we obtain an estimate for the initial growth rate of Covid-19, which can be also used to estimate the basic reproduction number for a region, in terms of population density. This has policy implications regarding how to control the pace of Covid-10 outbreak in a particular area, and we discuss some of them. In the case of countries, for which we did not have demographic information, weather variables lose statistical significance once the timeline variable is added. Relaxing CI requirements, absolute humidity contributes mildly to the reduction of growth rate of cases for the countries studied. Our results suggest that population density should be employed as a control variable and that analysis should have a local character, for subregions and countries separately, in studies involving the dynamics of Covid-19 and similar infectious diseases.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20075762",
+    "rel_abs": "In early 2020, cities across China enacted strict social distancing measures to contain emerging coronavirus (COVID-19) outbreaks. We estimated the speed with which these measures contained community transmission in each of 58 Chinese cities. On average, containment was achieved 7.83 days (SD 6.79 days) after the implementation of social distancing interventions, with an average reduction in the reproduction number (Rt) of 54.3% (SD 17.6%) over that time period. A single day delay in the implementation of social distancing led to a 2.41 (95% CI: 0.97, 3.86) day delay in containment. Swift social distancing interventions may thus achieve rapid containment of newly emerging COVID-19 outbreaks.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Renato H.L. Pedrosa",
-        "author_inst": "Unicamp"
+        "author_name": "Zhanwei Du",
+        "author_inst": "University of Texas at Austin"
+      },
+      {
+        "author_name": "xiaoke Xu",
+        "author_inst": "Dalian Minzu university"
+      },
+      {
+        "author_name": "Lin Wang",
+        "author_inst": "University of Cambridge"
+      },
+      {
+        "author_name": "Spencer J. Fox",
+        "author_inst": "The University of Texas at Austin"
+      },
+      {
+        "author_name": "Benjamin J Cowling",
+        "author_inst": "The University of Hong Kong"
+      },
+      {
+        "author_name": "Alison P. Galvani",
+        "author_inst": "Yale School of Public Health"
+      },
+      {
+        "author_name": "Lauren Ancel Meyers",
+        "author_inst": "The University of Texas at Austin"
       }
     ],
     "version": "1",
@@ -1475402,51 +1478663,47 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2020.04.26.062406",
-    "rel_title": "How did SARS-CoV-19 spread in India from Italy, Iran and China? Genetic surveillance of early cases and virus demography",
+    "rel_doi": "10.1101/2020.04.23.20076612",
+    "rel_title": "A systematic review of Anakinra, Tocilizumab, Sarilumab and Siltuximab for coronavirus-related infections",
     "rel_date": "2020-04-26",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.26.062406",
-    "rel_abs": "SARS-CoV-19 after emerging from Wuhan, drastically devastated all sectors of human life by crushing down the global economy and increased psychological burden on public, government, and healthcare professionals. We manifested by analyzing 35 early coronavirus cases of India, that virus introduction in India, occurred from Italy, Iran and China and population demography apparently revealed a rapid population expansion after the outbreak with a present steady growth. We depicted nucleotide substitutions in structural genes, drove for the adaptive selection and plead for sequencing more genomes to facilitate identification of new emerged mutants, genetic evolution and disease transmission caused by coronavirus.",
-    "rel_num_authors": 8,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20076612",
+    "rel_abs": "BackgroundThere is accumulating evidence for an overly activated immune response in severe Covid-19, with several studies exploring the therapeutic role of immunomodulation. Through systematic review and meta-analysis, we assess the effectiveness of specific interleukin inhibitors for the treatment of Covid-19.\n\nMethodsElectronic databases were searched on 7th January 2021 to identify studies of immunomodulatory agents (anakinra, sarilumab, siltuximab and tocilizumab) for the treatment of Covid-19. The primary outcomes were severity on an ordinal scale measured at day 15 from intervention and days to hospital discharge. Key secondary endpoints included overall mortality.\n\nResults71 studies totalling 22,058 patients were included, six were randomised trials. Most explored outcomes in patients who received tocilizumab (59/71). In prospective studies, tocilizumab was associated with improved unadjusted survival (RR 0.83 95%CI 0.72;0.96 I2 = 0.0%), but conclusive benefit was not demonstrated for other outcomes. In retrospective studies, tocilizumab was associated with less severe outcomes on an ordinal scale (Generalised odds ratio 1.34 95%CI 1.10;1.64, I2=98%) and adjusted mortality risk (HR 0.52 95%CI 0.41;0.66, I2 =76.6%). The mean difference in duration of hospitalisation was 0.36 days (95%CI -0.07;0.80, I2 =93.8%). There was substantial heterogeneity in retrospective studies, and estimates should be interpreted cautiously. Other immunomodulatory agents showed similar effects to tocilizumab, but insufficient data precluded meta-analysis by agent.\n\nConclusionTocilizumab was associated with a lower relative risk of mortality in prospective studies, but effects were inconclusive for other outcomes. Current evidence for the efficacy of anakinra, siltuximab or sarilumab in Covid-19 is insufficient, with further studies urgently needed for conclusive findings.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Mukesh Thakur",
-        "author_inst": "Zoological Survey of India, Kolkata"
-      },
-      {
-        "author_name": "Abhishek Singh",
-        "author_inst": "Zoological Survey of India, Kolkata"
+        "author_name": "Fasihul Khan",
+        "author_inst": "University of Nottingham"
       },
       {
-        "author_name": "Bheem Dutt Joshi",
-        "author_inst": "Zoological Survey of India, Kolkata"
+        "author_name": "Iain Stewart",
+        "author_inst": "University of Nottingham"
       },
       {
-        "author_name": "Avijit Ghosh",
-        "author_inst": "Zoological Survey of India, Kolkata"
+        "author_name": "Laura Fabbri",
+        "author_inst": "University of Nottingham"
       },
       {
-        "author_name": "Sujeet Kumar Singh",
-        "author_inst": "Zoological Survey of India, Kolkata"
+        "author_name": "Samuel Moss",
+        "author_inst": "University of Nottingham"
       },
       {
-        "author_name": "Neha Singh",
-        "author_inst": "University of Zurich, Zurich, Switzerland"
+        "author_name": "Karen Robinson",
+        "author_inst": "John Hopkins University"
       },
       {
-        "author_name": "Lalit Kumar Sharma",
-        "author_inst": "Zoological Survey of India, Kolkata"
+        "author_name": "Alan R Smyth",
+        "author_inst": "University of Nottingham"
       },
       {
-        "author_name": "Kailash Chandra",
-        "author_inst": "Zoological Survey of India, Kolkata"
+        "author_name": "Gisli Jenkins",
+        "author_inst": "University of Nottingham"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "new results",
-    "category": "genomics"
+    "license": "cc_by",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.23.20076737",
@@ -1477092,49 +1480349,41 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.21.20074641",
-    "rel_title": "Association between rRT-PCR test results upon admission and outcome in hospitalized chest CT-Positive COVID-19 patients; a provincial retrospective cohort with active follow-up",
+    "rel_doi": "10.1101/2020.04.21.20074757",
+    "rel_title": "Knowledge, attitude, practice and perception regarding COVID-19 among students in Bangladesh: Survey in Rajshahi University",
     "rel_date": "2020-04-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20074641",
-    "rel_abs": "BackgroundThe Covid-19 pandemic imposed the most devastating challenge on healthcare systems worldwide. Iran was among the first countries that had to confront serious shortages in RT-PCR testing for SARS-CoV-2 and ventilators availabilities throughout the COVID-19 outbreak. This study aimed to investigate the clinical course of hospitalized COVID-19 patients with different rRT-PCR test results during the first 3 weeks of the outbreak in Qazvin province, Iran.\n\nMethodsFor this retrospective cohort study, data of hospitalized patients primarily diagnosed as having COVID-19 in all 12 centers across the whole Qazvin province during Feb 20-Mar 11, 2020 was analyzed. A multivariate logistic regression model was applied to assess the independent associates of death among COVID-19 patients.\n\nResults998 patients (57% male, median age 54 years) with positive chest CT-scan changes were included in this study. Among them, 558 patients were examined with rRT-PCR test and 73{middle dot}8% tested positive. Case fatality rate was 20{middle dot}68% and 7{middle dot}53% among test-positive and test negative hospitalized patients, respectively. While only 5{middle dot}2% of patients were ICU admitted, case fatality rates outside ICU were 17{middle dot}70% and 4{middle dot}65% in test-positive and test-negative non-ICU admitted patients, correspondingly. The independent associates of death were age [&ge;] 70 years, testing positive with rRT-PCR test, having immunodeficiency disorders and ICU admission.\n\nConclusionsHospitalized COVID-19 patients with mild symptoms despite positive chest CT changes and major comorbidities were more probable to have negative rRT-PCR test result, hence lower case fatality rate and a more favorable outcome.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20074757",
+    "rel_abs": "BackgroundThe number of infection and death by COVID-19 has been rapidly increasing since December 2019 in all over the world. Until now, there is no specific treatment or vaccine for this disease; WHO suggests only some protective measures like maintaining social distance, staying home, washing hands with soap or sanitizer, wearing mask etc. The objective of this study was to survey knowledge, attitude, practice and perception regarding COVID-19 among students in Rajshahi University, Bangladesh.\n\nMethodsWe collected data from 305 students of Rajshahi University for this cross-sectional study using mixed sampling from March 11 to March 19, 2020. Frequency distribution, Mann-Whitney and Kruskal-Wallis tests were used in this study.\n\nResultsOut of 305 participants, 224 (73.4%) and 81 (26.6%) were male and female students respectively. The study revealed that Rajshahi university students had average knowledge on symptoms, protective way and transmission of COVID-19. Female students were more knowledgeable than male. More than one third of the students had negative attitude to avoiding public transport and going out to public places with friends and family. The practice of students practice during our data collection period and in future was not satisfactory. More than one third of students were not keen to stay at home and avoid going to crowded places. The perception towards COVID-19 was not good; they had no idea whether the outbreak would affect their daily routine, study and financial matters, study field work and restrict leisure time of meeting family and relatives.\n\nConclusionsWe found that general knowledge, attitude, practice and perception of the university students regarding COVID-19 were not satisfactory. This indicated that the situation was worse among common people. In Bangladesh, the number of healthcare providers is insufficient. University students can be employed as potential workforce to create awareness among mass people on prevention of COVID-19.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Saeed Nemati",
-        "author_inst": "Cancer Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran"
-      },
-      {
-        "author_name": "Hamid Reza Najari",
-        "author_inst": "1. Department of Internal Medicine, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran; 2. Deputy of health, Qazvin University of Medical S"
-      },
-      {
-        "author_name": "Anita Eftekharzadeh",
-        "author_inst": "Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti Universiy School of Medicine, Tehran, Iran"
+        "author_name": "Md. Abdul Wadood",
+        "author_inst": "University of Rajshahi"
       },
       {
-        "author_name": "Amir Mohammad Kazemifar",
-        "author_inst": "Department of Internal Medicine, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran"
+        "author_name": "ASMA Mamun",
+        "author_inst": "University of Rajshahi"
       },
       {
-        "author_name": "Ali Qandian",
-        "author_inst": "Office of Communicable Disease, Deputy of health, Qazvin University of Medical Sciences, Qazvin, Iran"
+        "author_name": "Md. Abdur Rafi",
+        "author_inst": "Rajshahi Medical College"
       },
       {
-        "author_name": "Pedram Fattahi",
-        "author_inst": "Cancer Research Center, Cancer Research Institute, Tehran University of Medical Sciences, Tehran, Iran"
+        "author_name": "Md. kamrul Islam",
+        "author_inst": "University of Rajshahi"
       },
       {
-        "author_name": "Maedeh Zokaei Nikoo",
-        "author_inst": "Student Research Committee, Qazvin University of Medical Sciences, Qazvin, Iran"
+        "author_name": "Suhaili Mohd",
+        "author_inst": "University of Malaya"
       },
       {
-        "author_name": "Shiva Leghaei",
-        "author_inst": "Office of Communicable Disease, Deputy of health, Qazvin University of Medical Sciences, Qazvin, Iran"
+        "author_name": "Lai Lee Lee",
+        "author_inst": "University of Malaya"
       },
       {
-        "author_name": "Mohammad Reza Rouhollahi",
-        "author_inst": "1. Cancer Research Center, Cancer Research Institute, Tehran University of Medical Sciences, Tehran, Iran; 2. Clinical Cancer Research Center (CCRC), Milad Hosp"
+        "author_name": "Md. Golam Hossain",
+        "author_inst": "University of Rajshahi"
       }
     ],
     "version": "1",
@@ -1478498,75 +1481747,67 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.24.059576",
-    "rel_title": "Introductions and early spread of SARS-CoV-2 in France",
+    "rel_doi": "10.1101/2020.04.20.20064899",
+    "rel_title": "Epidemiological characteristics of COVID-19 in medical staff members of neurosurgery departments in Hubei province: A multicentre descriptive study",
     "rel_date": "2020-04-24",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.24.059576",
-    "rel_abs": "Following the emergence of coronavirus disease (COVID-19) in Wuhan, China in December 2019, specific COVID-19 surveillance was launched in France on January 10, 2020. Two weeks later, the first three imported cases of COVID-19 into Europe were diagnosed in France. We sequenced 97 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from samples collected between January 24 and March 24, 2020 from infected patients in France. Phylogenetic analysis identified several early independent SARS-CoV-2 introductions without local transmission, highlighting the efficacy of the measures taken to prevent virus spread from symptomatic cases. In parallel, our genomic data reveals the later predominant circulation of a major clade in many French regions, and implies local circulation of the virus in undocumented infections prior to the wave of COVID-19 cases. This study emphasizes the importance of continuous and geographically broad genomic sequencing and calls for further efforts with inclusion of asymptomatic infections.",
-    "rel_num_authors": 14,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20064899",
+    "rel_abs": "BackgroundThe novel coronavirus (SARS-CoV-2) has infected a large number of healthcare workers in Hubei province, China. In addition to infectious and respiratory disease physicians, many doctors in other medical fields have been infected.\n\nMethodsWe prospectively collected epidemiological data on medical staff members who are working in neurosurgery departments in 107 hospitals in Hubei province through self-reported questionnaires or telephone interviews. Data of medical staff members with laboratory-confirmed coronavirus disease 2019 (COVID-19) were analysed. The final follow-up date was 1 March 2020.\n\nFindingsA total of 5,442 neurosurgery department medical staff members were surveyed. One hundred and twenty cases, involving 54 doctors and 66 nurses, were found to have been infected with SARS-CoV-2. The overall incidence was 2.2%. These cases were concentrated in 26 centres, 16 of which had admitted a total of 59 patients with COVID-19 complicated by craniocerebral disease. Medical staff members in centres receiving COVID-19 patients had a higher risk of contracting infection than those in centres not receiving COVID-19 patients (relative risk: 19.6; 95% confidence interval: 12.6-30.6). Contact with either COVID-19 patients (62.5%, 75/120) or infected colleagues (30.8%, 37/120) was the most common mode of transmission. About 78.3% (94/120) of the infected cases wore surgical masks, whereas 20.8% (25/120) failed to use protection when exposed to the source of infection. Severe infections were observed in 11.7% (14/120) of the cases, with one death (0.8%, 1/120). All the infected medical staff members had been discharged from the hospital. A total of 1,287 medical staff members were dispatched to participate in the frontline response to COVID-19 under level 2 protection of whom one was infected. Medical staff members who took inadequate protection had a higher risk of contracting infection than those using level 2 protection (relative risk: 36.9; 95% confidence interval: 5.2-263.6).\n\nConclusionsNeurosurgical staff members in Hubei province were seriously affected by COVID-19. Level 2 protection and strengthening of protective measures are likely to be effective in preventing medical workers from being infected.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Fabiana Gambaro",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Qiangping Wang",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022"
       },
       {
-        "author_name": "Artem Baidaliuk",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Xing Huang",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       },
       {
-        "author_name": "Sylvie Behillil",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Yansen Bai",
+        "author_inst": "Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong"
       },
       {
-        "author_name": "Flora Donati",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Melanie Albert",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Xuan Wang",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       },
       {
-        "author_name": "Andreea Alexandru",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Haijun Wang",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       },
       {
-        "author_name": "Maud Vanpeene",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Xuebin Hu",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       },
       {
-        "author_name": "Meline Bizard",
-        "author_inst": "Institut Pasteur"
-      },
-      {
-        "author_name": "Angela Brisebarre",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Feng Wang",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       },
       {
-        "author_name": "Marion Barbet",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Xianke Wang",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       },
       {
-        "author_name": "Fawzi Derrar",
-        "author_inst": "Institut Pasteur of Algiers"
+        "author_name": "Jincao Chen",
+        "author_inst": "Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, China, 430071."
       },
       {
-        "author_name": "Sylvie van der Werf",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Qianxue Chen",
+        "author_inst": "Department of Neurosurgery, Hubei Provincial People's Hospital of Wuhan University, Wuhan, China, 430060."
       },
       {
-        "author_name": "Vincent Enouf",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Xiaobing Jiang Sr.",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       },
       {
-        "author_name": "Etienne Simon-Loriere",
-        "author_inst": "Institut Pasteur"
+        "author_name": "Hongyang Zhao",
+        "author_inst": "Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 430022."
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "genomics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.24.059667",
@@ -1480424,35 +1483665,47 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.20.20072157",
-    "rel_title": "Multiple drivers of the COVID-19 spread: role of climate, international mobility, and region-specific conditions",
+    "rel_doi": "10.1101/2020.04.22.20076141",
+    "rel_title": "COVID-19: Public Compliance with and Public Support for Stay-at-Home Mitigation Strategies",
     "rel_date": "2020-04-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072157",
-    "rel_abs": "The novel Coronavirus Disease 2019 (COVID-19) has spread quickly across the globe. Here, we evaluated the role of climate (temperature and precipitation), region-specific susceptibility (BCG vaccination, malaria infection, and elderly population) and international traveller population (human mobility) in shaping the geographical patterns of COVID-19 cases across 1,055 countries/regions, and examined the sequential shift of multiple drivers of the accumulated cases from December, 2019 to April 12, 2020. The accumulated numbers of COVID-19 cases (per 1 million population) were well explained by a simple regression model. The explanatory power (R2) of the model increased up to > 70% in April 2020 as the COVID-19 spread progressed. Climate, host mobility, and host susceptibility largely explained the variance of the COVID-19 cases (per 1 million population), and their explanatory power improved as the pandemic progressed; the relative importance of host mobility and host susceptibility have been greater than that of climate. The number of days from outbreak onset showed greater explanatory power in the earlier stages of COVID-19 spread but rapidly lost its influence. Our findings demonstrate that the COVID-19 pandemic is deterministically driven by climate suitability, cross-border human mobility, and region-specific susceptibility. The present distribution of COVID-19 cases has not reached an equilibrium and is changing daily, especially in the Southern Hemisphere. Nevertheless, the present results, based on mapping the spread of COVID-19 and identifying multiple drivers of this outbreak trajectory, may contribute to a better understanding of the COVID-19 disease transmission risk and the measures against long-term epidemic.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20076141",
+    "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSObjectivesC_ST_ABSGovernments worldwide have recommended unprecedented measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic. As pressure mounts to scale back these measures, understanding public compliance with and priorities for COVID-19 mitigation is critical. The main aim of this study was to assess public compliance with and support for government-imposed stay-at-home orders in nations and cities with different COVID-19 infection and death rates.\n\nDesignIn this cross-sectional study, questionnaires were administered to nationally representative respondents from April 2-8, 2020.\n\nSettingRegions with different disease prevalence included two nations [the United States (US--high) and Australia (AU--low)] and two cities [New York (NY--high) and Los Angeles (LA--low)].\n\nParticipantsFor adults 18 years or older residing in specified regions, eligible respondents were empaneled until representative quotas were reached for age, gender, and either race and ethnicity (US, NY, LA) or ancestry (AU), matching the 2010 US or 2016 AU census. Of 8718 eligible potential respondents, 5573 (response rate, 63.9%) completed surveys (US: 3010; NY: 507; LA: 525; AU: 1531). The median age was 47 years (range, 18-89); 3039 (54.5%) were female.\n\nExposureThe prevalence of COVID-19 in each region (cumulative infections, deaths) as of April 8, 2020: US (458610, 15659), AU (5956, 45),1 NY (81803, 4571), LA (7530, 198).2\n\nMain Outcomes MeasuresPublic compliance with and attitudes regarding government-imposed stay-at-home orders were evaluated and compared between regions.\n\nResultsOf 5573 total respondents, 4560 (81.8%) reported compliance with recommended quarantine or stay-at-home policies (range of samples, 75.5%-88.2%). Despite significant disruptions of social and work life, health, and behavior, 5022 respondents (90.1%) supported government-imposed stay-at-home orders (range of samples, 88.9%-93.1%). Of these, 90.8% believe orders should last at least three more weeks or until public health or government officials recommend, with such support spanning the political spectrum.\n\nConclusionsPublic compliance with stringent quarantine and stay-at-home policies was very high, in both highly-affected (US, NY) and minimally-affected regions (AU, LA). Despite extensive disruption of respondents lives, the vast majority supported continuation of long-term government-imposed stay-at-home orders. These findings have important implications for policymakers grappling with the decision as to when to lift restrictions.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Yasuhiro Kubota",
-        "author_inst": "University of the Ryukyus"
+        "author_name": "Mark \u00c9 Czeisler",
+        "author_inst": "School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria 3800 Australia"
       },
       {
-        "author_name": "Takayuki Shiono",
-        "author_inst": "University of the Ryukyus"
+        "author_name": "Mark E Howard",
+        "author_inst": "Institute for Breathing and Sleep, Austin Health, Melbourne, Victoria 3084 Australia"
       },
       {
-        "author_name": "Buntarou Kusumoto",
-        "author_inst": "University of the Ryukyus"
+        "author_name": "Rebecca Robbins",
+        "author_inst": "Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, Massachusetts 02115 USA"
       },
       {
-        "author_name": "Junichi Fujinuma",
-        "author_inst": "University of the Ryukyus"
+        "author_name": "Laura K Barger",
+        "author_inst": "Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, Massachusetts 02115 USA"
+      },
+      {
+        "author_name": "Elise R Facer-Childs",
+        "author_inst": "School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria 3800 Australia"
+      },
+      {
+        "author_name": "Shantha MW Rajaratnam",
+        "author_inst": "School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria 3800 Australia"
+      },
+      {
+        "author_name": "Charles A Czeisler",
+        "author_inst": "Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women's Hospital, Boston, Massachusetts 02115 USA"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.19.20071779",
@@ -1481714,25 +1484967,65 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.20.20072892",
-    "rel_title": "Estimation of Undetected Covid-19 Infections in India",
+    "rel_doi": "10.1101/2020.04.20.20072462",
+    "rel_title": "ESTIMATING R0 OF SARS-COV-2 IN HEALTHCARE SETTINGS",
     "rel_date": "2020-04-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072892",
-    "rel_abs": "Background and ObjectivesWhile the number of detected COVID-19 infections are widely available, an understanding of the extent of undetected COVID-19 cases is urgently needed for an effective tackling of the pandemic and as a guide to lifting the lockdown. The aim of this work is to estimate and predict the true number of COVID-19 (detected and undetected) infections in India for short to medium forecast horizons. In particular, using publicly available COVID-19 infection data upto 16th April 2020, we predict the true number of infections in India during and upto the end of the formal lockdown period (21st April 2020).\n\nMethodsThe high death rate observed in most COVID-19 hit countries is suspected to be a function of the undetected infections existing in the population. An estimate of the age weighted infection fatality rate (IFR) of the disease of 0.41%, specifically calculated by taking into account the age structure of Indian population, is already available in the literature. In addition, the recorded case fatality rate (CFR= 0.70%) of Kerala, the only state in India to report single digit new infections over the second week of April, is used as a second estimate of the IFR. These estimates are used to formulate a relationship between deaths recorded and the true number of infections. The estimated undetected and detected cases time series based on these two IFR estimates are then used to fit a discrete time multivariate infection model to predict the total infections at the end of the formal lockdown period.\n\nResultsIn two consecutive fortnights during the lockdown, it was noted that the rise in detected infections has decreased by 2.7 times. For an IFR of 0.41%, the rise in undetected infections decreased by 3.2 times and the predicted number of total infections in India is 3.14 lakhs. While for an IFR of 0.70%, the rise in undetected cases decreased by 3.3 times and the total number of infections predicted on 21st April is 1.75 lakhs.\n\nInterpretation and ConclusionsThe behaviour of the undetected cases over time effectively illustrates the effects of lockdown and increased testing. From our estimates, it is found that the lockdown has brought down the undetected to detected cases ratio, and has consequently dampened the increase in the number of total cases. However, even though the rate of rise in total infections has fallen, the lifting of the lockdown should be done keeping in mind that 1.75 to 3 lakhs undetected cases will already exist in the population on 21st April.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072462",
+    "rel_abs": "To date, no specific estimate of R0 for SARS-CoV-2 is available for healthcare settings. Using inter-individual contact data, we highlight that R0 estimates from the community cannot translate directly to healthcare settings, with pre-pandemic R0 values ranging 1.3-7.7 in three illustrative healthcare institutions. This has implications for nosocomial Covid-19 control.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Siuli Mukhopadhyay",
-        "author_inst": "Department of Mathematics, Indian Institute of Technology Bombay"
+        "author_name": "Laura TEMIME",
+        "author_inst": "Cnam"
+      },
+      {
+        "author_name": "Marie-Paule Gustin",
+        "author_inst": "University Claude Bernard Lyon 1, Inserm"
       },
       {
-        "author_name": "Debraj Chakraborty",
-        "author_inst": "Indian Institute of Technology Bombay"
+        "author_name": "Audrey Duval",
+        "author_inst": "Institut Pasteur"
+      },
+      {
+        "author_name": "Niccolo Buetti",
+        "author_inst": "Inserm"
+      },
+      {
+        "author_name": "Pascal Crepey",
+        "author_inst": "EHESP"
+      },
+      {
+        "author_name": "Didier Guillemot",
+        "author_inst": "Paris-Saclay University , Inserm, Institut Pasteur, AP-HP"
+      },
+      {
+        "author_name": "Rodolphe Thiebaut",
+        "author_inst": "University of Bordeaux, Inria"
+      },
+      {
+        "author_name": "Philippe Vanhems",
+        "author_inst": "Lyon University Hospitals"
+      },
+      {
+        "author_name": "Jean-Ralph Zahar",
+        "author_inst": "AP-HP, Inserm"
+      },
+      {
+        "author_name": "David RM Smith",
+        "author_inst": "Paris-Saclay University, Institut Pasteur, Cnam"
+      },
+      {
+        "author_name": "Lulla Opatowski",
+        "author_inst": "Paris Saclay university, Inserm, Institut Pasteur"
+      },
+      {
+        "author_name": "Modelling COVID-19 in hospitals REACTinG AVIESAN working group",
+        "author_inst": ""
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1483244,51 +1486537,87 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.23.057810",
-    "rel_title": "TARGETED PROTEOMICS FOR THE DETECTION OF SARS-COV-2 PROTEINS.",
+    "rel_doi": "10.1101/2020.04.22.046565",
+    "rel_title": "Functional and Genetic Analysis of Viral Receptor ACE2 Orthologs Reveals Broad Potential Host Range of SARS-CoV-2",
     "rel_date": "2020-04-23",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.23.057810",
-    "rel_abs": "The rapid, sensitive and specific detection of SARS-CoV-2 is critical in responding to the current COVID-19 outbreak. In this proof-of-concept study, we explored the potential of targeted mass spectrometry based (MS) proteomics for the detection of SARS-CoV-2 proteins in both research samples and clinical specimens. First, we assessed the limit of detection for several SARS-CoV-2 proteins by parallel reaction monitoring (PRM) MS in infected Vero E6 cells. For tryptic peptides of Nucleocapsid protein, the limit of detection was in the mid-attomole range (9E-13 g). Next, this PRM methodology was applied to the detection of viral proteins in various COVID-19 patient clinical specimens, such as sputum and nasopharyngeal swabs. SARS-CoV-2 proteins were detected in these samples with high sensitivity in all specimens with PCR Ct values <24 and in several samples with higher CT values. A clear relationship was observed between summed MS peak intensities for SARS-CoV-2 proteins and Ct values reflecting the abundance of viral RNA. Taken together, these results suggest that targeted MS based proteomics may have the potential to be used as an additional tool in COVID-19 diagnostics.",
-    "rel_num_authors": 8,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.22.046565",
+    "rel_abs": "The pandemic of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major global health threat. Epidemiological studies suggest that bats are the natural zoonotic reservoir for SARS-CoV-2. However, the host range of SARS-CoV-2 and intermediate hosts that facilitate its transmission to humans remain unknown. The interaction of coronavirus with its host receptor is a key genetic determinant of host range and cross-species transmission. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) as the receptor to enter host cells in a species-dependent manner. It has been shown that human, palm civet, pig and bat ACE2 can support virus entry, while the murine ortholog cannot. In this study, we characterized the ability of ACE2 from diverse species to support viral entry. We found that ACE2 is expressed in a wide range of species, with especially high conservation in mammals. By analyzing amino acid residues of ACE2 critical for virus entry, based on structure of SARS-CoV spike protein interaction with human, bat, palm civet, pig and ferret ACE2, we identified approximately eighty ACE2 proteins from mammals that could potentially mediate SARS-CoV-2 entry. We chose 48 representative ACE2 orthologs among eighty orthologs for functional analysis and it showed that 44 of these mammalian ACE2 orthologs, including those of domestic animals, pets, livestock, and animals commonly found in zoos and aquaria, could bind SARS-CoV-2 spike protein and support viral entry. In contrast, New World monkey ACE2 orthologs could not bind SARS-CoV-2 spike protein and support viral entry. We further identified the genetic determinant of New World monkey ACE2 that restricts viral entry using genetic and functional analyses. In summary, our study demonstrates that ACE2 from a remarkably broad range of species can facilitate SARS-CoV-2 entry. These findings highlight a potentially broad host tropism of SARS-CoV-2 and suggest that SARS-CoV-2 might be distributed much more widely than previously recognized, underscoring the necessity to monitor susceptible hosts to prevent future outbreaks.",
+    "rel_num_authors": 17,
     "rel_authors": [
       {
-        "author_name": "Karel Bezstarosti",
-        "author_inst": "Erasmus University Medical Center"
+        "author_name": "Yinghui Liu",
+        "author_inst": "Tsinghua University"
       },
       {
-        "author_name": "Mart M Lamers",
-        "author_inst": "Erasmus University Medical Center"
+        "author_name": "Gaowei Hu",
+        "author_inst": "Fudan University"
       },
       {
-        "author_name": "Wouter AS Doff",
-        "author_inst": "Erasmus MC"
+        "author_name": "Yuyan Wang",
+        "author_inst": "Fudan University"
       },
       {
-        "author_name": "Peter C Wever",
-        "author_inst": "Jeroen Bosch Hospital"
+        "author_name": "Xiaomin Zhao",
+        "author_inst": "Tsinghua University"
       },
       {
-        "author_name": "Khoa TD Thai",
-        "author_inst": "Star-shl diagnostic laboratories"
+        "author_name": "Fansen Ji",
+        "author_inst": "Tsinghua University"
       },
       {
-        "author_name": "Jeroen JA van Kampen",
-        "author_inst": "Erasmus Medical Center"
+        "author_name": "Wenlin Ren",
+        "author_inst": "Tsinghua University"
       },
       {
-        "author_name": "Bart L Haagmans",
-        "author_inst": "Erasmus University Medical Center"
+        "author_name": "Mingli Gong",
+        "author_inst": "Tsinghua University"
       },
       {
-        "author_name": "Jeroen AA Demmers",
-        "author_inst": "Erasmus University Medical Center"
+        "author_name": "Xiaohui Ju",
+        "author_inst": "Tsinghua University"
+      },
+      {
+        "author_name": "Yuanfei Zhu",
+        "author_inst": "Fudan University"
+      },
+      {
+        "author_name": "Xia Cai",
+        "author_inst": "Fudan University"
+      },
+      {
+        "author_name": "Jianping Wu",
+        "author_inst": "Westlake University"
+      },
+      {
+        "author_name": "Xun Lan",
+        "author_inst": "Tsinghua University"
+      },
+      {
+        "author_name": "Youhua Xie",
+        "author_inst": "Fudan University"
+      },
+      {
+        "author_name": "Xinquan Wang",
+        "author_inst": "Tsinghua University"
+      },
+      {
+        "author_name": "Zhenghong Yuan",
+        "author_inst": "Fudan University"
+      },
+      {
+        "author_name": "Rong Zhang",
+        "author_inst": "Fudan University"
+      },
+      {
+        "author_name": "Qiang Ding",
+        "author_inst": "Tsinghua University"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.04.23.057265",
@@ -1485098,27 +1488427,55 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.19.20071654",
-    "rel_title": "A study on control of novel corona-virus (2019-nCoV) disease process by using PID controller",
+    "rel_doi": "10.1101/2020.04.18.20070821",
+    "rel_title": "Estimating the Prevalence of COVID-19 in the United States: Three Complementary Approaches",
     "rel_date": "2020-04-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071654",
-    "rel_abs": "BackgroundIn this paper, the SEIR dynamic model will be used to model the epidemic of coronvirus (2019-nCoV)disease. The SEIR model has been used to model infectious diseases in Malaysia.Then, the spread and control of the disease is simulated applying a PID controller. The results of this study show that the implementation of strict restrictions such as quarantine, social distancing and closure of gathering centers is effective in controlling the disease. Using the results and analyzing them, it was found that early and strict implementation of strict restrictions such as quarantine, social distance and closure of centers with a high percentage of community is very important to control this disease and prevent irreparable economic losses and depreciation of medical staff.\n\nObjectiveModeling the prevalence and control of corona-virus (2019-nCoV)and the impact of government actions using control engineering methods.\n\nMethodIn this study, the SEIR dynamic model was used and the common data on the prevalence of the virus in Wuhan, China and Malaysia were used. As an example, the use of control target schemes is simulated in this paper.\n\nResultsThe findings of this study use control methods and forecasting in control engineering to provide a clear picture of macro-decisions for different governments in the field of infectious diseases.\n\nConclusionManagement and control schemes such as travel restrictions, quarantine, social distance and closure of offices, higher education institutions must be implemented immediately to prevent major economic and social losses. The implementation of these restrictions should not be delayed during the outbreak of corona-virus(2019-nCoV) infectious diseases.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.18.20070821",
+    "rel_abs": "Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the prevalence of COVID-19 across the United States (US). Equipment shortages and varying testing capabilities have however hindered the usefulness of the official reported positive COVID-19 case counts. We introduce four complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 in each state in the US as well as Puerto Rico and the District of Columbia, using a combination of excess influenza-like illness reports, COVID-19 test statistics, COVID-19 mortality reports, and a spatially structured epidemic model. Instead of relying on the estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our four approaches emerges the consistent conclusion that on April 4, 2020, the estimated case count was 5 to 50 times higher than the official positive test counts across the different states. Nationally, our estimates of COVID-19 symptomatic cases as of April 4 have a likely range of 2.2 to 4.9 million, with possibly as many as 8.1 million cases, up to 26 times greater than the cumulative confirmed cases of about 311,000. Extending our method to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 6.0 to 10.3 million, as opposed to 1.5 million positive test counts. The proposed combination of approaches may prove useful in assessing the burden of COVID-19 during resurgences in the US and other countries with comparable surveillance systems.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "habibollah arasteh rad",
-        "author_inst": "Institute of applied Inteligent Systems Of University of Tehran"
+        "author_name": "Fred S Lu",
+        "author_inst": "Stanford"
+      },
+      {
+        "author_name": "Andre T Nguyen",
+        "author_inst": "University of Maryland, Baltimore County"
+      },
+      {
+        "author_name": "Nicholas B Link",
+        "author_inst": "Boston Children's Hospital"
+      },
+      {
+        "author_name": "Jessica T Davis",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Matteo Chinazzi",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Xinyue Xiong",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Alessandro Vespignani",
+        "author_inst": "Northeastern University"
+      },
+      {
+        "author_name": "Marc Lipsitch",
+        "author_inst": "Harvard T.H. Chan School of Public Health"
       },
       {
-        "author_name": "arshia badi",
-        "author_inst": "Institute of applied Inteligent Systems Of University of Tehran"
+        "author_name": "Mauricio Santillana",
+        "author_inst": "Harvard Medical School"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.04.20.20064873",
@@ -1486848,23 +1490205,35 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.04.17.20068601",
-    "rel_title": "The effect of BCG vaccination on COVID-19 examined by a statistical approach: no positive results from the Diamond Princess and cross-national differences previously reported by world-wide comparisons are flawed in several ways",
+    "rel_doi": "10.1101/2020.04.17.20069716",
+    "rel_title": "Years of life lost due to the psychosocial consequences of COVID19 mitigation strategies based on Swiss data",
     "rel_date": "2020-04-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20068601",
-    "rel_abs": "Recently, the controversial hypothesis that past BCG (Bacillus Calmette-Guerin) vaccination reduces infection or severity of COVID-19 has been proposed. The present study examined this hypothesis using statistical approaches based on the public data. Three approaches were utilized: 1) comparing the infection and mortality ratio of people on the cruise ship Diamond Princess, 2) comparing the number of mortalities among nations, and 3) comparing the maximum daily increase rate of total mortalities among nations. The result of 1) showed that there is no significant difference in infection per person onboard or mortality-infection between Japanese citizens vs. US citizens and BCG obligatory nations vs. non-BCG obligatory nations on the Diamond Princess. The result of 2) showed that the number of mortalities among nations is similar to the previous studies, but this analysis also considered the timing of COVID-19 arrival in each nation. After correcting for arrival time, previously reported effect of BCG vaccination on decreasing total mortality disappeared. This is because nations that lack BCG vaccination are concentrated in Western Europe, which is near an epicenter of COVID-19. Therefore some previous reports are now considered to be affected by this artifact; the result may have been flawed by dispersal from an epicenter. However, some results showed weakly significant differences in the number of deaths at a particular time among BCG obligatory and non-BCG nations (especially the use of Japanese BCG strain Tokyo 172). However, these results are affected by the results of three countries and the effect of BCG vaccination remains inconclusive. The result of 3) showed that the maximum daily increasing rate in death among nations showed no significant difference among BCG vaccination policies. In the present study, although some results showed statistically significant differences among BCG vaccination policies, they may be affected by the impact of various other factors, such as national infection-control policies, social distancing, behavioral changes of people, possible previous local epidemics of closely related viruses, or inter-population differences in ACE2 or other genetic polymorphism. Further research is needed to better understand the underlying cause of the observed differences in infection and mortality of the disease among nations. Nevertheless, our results show that the effect of past BCG vaccination, if any, can be masked by many other factors. Therefore, the possible effect might be relatively small. In fact, in Japan, where almost all citizens have been vaccinated, COVID-19 cases are constantly increasing. Given the importance of peoples behavior in preventing viral propagation, the spread of optimism triggered by this hypothesis would be harmful to BCG vaccination nations.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20069716",
+    "rel_abs": "BackgroundThe pandemic caused by COVID-19 has forced governments to implement strict social mitigation strategies to reduce the morbidity and mortality from acute infections. These strategies however carry a significant risk for mental health which can lead to increased short-term and long-term mortality and is currently not included in modelling the impact of the pandemic.\n\nMethodsWe used years of life lost (YLL) as the main outcome measure as applied to Switzerland as an exemplar. We focused on suicide, depression, alcohol use disorder, childhood trauma due to domestic violence, changes in marital status and social isolation as these are known to increase YLL in the context of imposed restriction in social contact and freedom of movement. We stipulated a minimum duration of mitigation of 3 months based on current public health plans.\n\nResultsThe study projects that the average person would suffer 0.205 YLL due to psychosocial consequence of COVID-19 mitigation measures. However, this loss would be entirely borne by 2.1% of the population, who will suffer an average 9.79 YLL.\n\nConclusionsThe results presented here are likely to underestimate the true impact of the mitigation strategies on YLL. However, they highlight the need for public health models to expand their scope in order to provide better estimates of the risks and benefits of mitigation.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Masakazu Asahara",
-        "author_inst": "Aichi Gakuin University"
+        "author_name": "Dominik Andreas Moser",
+        "author_inst": "University of Berne, Institute of Psychology, Switzerland; Centre Hospitalier Universitaire Vaudois, Child and Adolescent Psychiatry Service, Department of Psyc"
+      },
+      {
+        "author_name": "Jennifer Glaus",
+        "author_inst": "Centre Hospitalier Universitaire Vaudois, Child and Adolescent Psychiatry Service, Department of Psychiatry, Switzerland"
+      },
+      {
+        "author_name": "Sophia Frangou",
+        "author_inst": "Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Canada; Department of Psychiatry, Icahn School of Medicine"
+      },
+      {
+        "author_name": "Daniel Scott Schechter",
+        "author_inst": "Centre Hospitalier Universitaire Vaudois, Child and Adolescent Psychiatry Service, Switzerland; Universite de Geneve Faculte de medecine, Switzerland; New York "
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.04.17.20068908",
@@ -1488206,23 +1491575,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.20.052290",
-    "rel_title": "Dynamical asymmetry exposes 2019-nCoV prefusion spike",
+    "rel_doi": "10.1101/2020.04.16.20068163",
+    "rel_title": "Projections for first-wave COVID-19 deaths across the US using social-distancing measures derived from mobile phones",
     "rel_date": "2020-04-22",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.20.052290",
-    "rel_abs": "The novel coronavirus (2019-nCoV) spike protein is a smart molecular machine that instigates the entry of coronavirus to the host cell causing the COVID-19 pandemic. In this study, a structural-topology based model Hamiltonian of C3 symmetric trimeric spike is developed to explore its complete conformational energy landscape using molecular dynamic simulations. The study finds 2019-nCoV to adopt a unique strategy by undertaking a dynamic conformational asymmetry induced by a few unique inter-chain interactions. This results in two prevalent asymmetric structures of spike where one or two spike heads lifted up undergoing a dynamic transition likely to enhance rapid recognition of the host-cell receptor turning on its high-infectivity. The crucial interactions identified in this study are anticipated to potentially affect the efficacy of therapeutic targets.\n\nOne Sentence SummaryInter-chain-interaction driven rapid symmetry breaking strategy adopted by the prefusion trimeric spike protein likely to make 2019-nCoV highly infective.",
-    "rel_num_authors": 1,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20068163",
+    "rel_abs": "We propose a Bayesian model for projecting first-wave COVID-19 deaths in all 50 U.S. states. Our models projections are based on data derived from mobile-phone GPS traces, which allows us to estimate how social-distancing behavior is \"flattening the curve\" in each state. In a two-week look-ahead test of out-of-sample forecasting accuracy, our model significantly outperforms the widely used model from the Institute for Health Metrics and Evaluation (IHME), achieving 42% lower prediction error: 13.2 deaths per day average error across all U.S. states, versus 22.8 deaths per day average error for the IHME model. Our model also provides an accurate, if slightly conservative, assessment of forecasting accuracy: in the same look-ahead test, 98% of data points fell within the models 95% credible intervals. Our models projections are updated daily at https://covid-19.tacc.utexas.edu/projections/.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Susmita Roy",
-        "author_inst": "Indian Institute of Science Education and Research Kolkata"
+        "author_name": "Spencer Woody",
+        "author_inst": "University of Texas at Austin"
+      },
+      {
+        "author_name": "Mauricio Garcia Tec",
+        "author_inst": "University of Texas at Austin"
+      },
+      {
+        "author_name": "Maytal Dahan",
+        "author_inst": "University of Texas at Austin"
+      },
+      {
+        "author_name": "Kelly Gaither",
+        "author_inst": "University of Texas at Austin"
+      },
+      {
+        "author_name": "Michael Lachmann",
+        "author_inst": "Santa Fe Institute"
+      },
+      {
+        "author_name": "Spencer Fox",
+        "author_inst": "University of Texas at Austin"
+      },
+      {
+        "author_name": "Lauren Ancel Meyers",
+        "author_inst": "The University of Texas at Austin"
+      },
+      {
+        "author_name": "James G Scott",
+        "author_inst": "University of Texas at Austin"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "new results",
-    "category": "biophysics"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.20.052233",
@@ -1489628,29 +1493025,41 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.19.20071605",
-    "rel_title": "Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level",
+    "rel_doi": "10.1101/2020.04.19.20071712",
+    "rel_title": "Potential magnitude of COVID-19-induced healthcare resource depletion in Ontario, Canada",
     "rel_date": "2020-04-22",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071605",
-    "rel_abs": "The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths at the date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. In the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how the socioeconomic features of Iranian provinces might predict the number of cases. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran, which indicated that the spread of COVID-19 within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases. Interestingly, literacy is a protective factor that might be directly related to health literacy and compliance with public health measures. These features indicate that policies related to social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be targeted to reduce SARS-CoV2 spread in Iran. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071712",
+    "rel_abs": "BackgroundThe global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing significant strain to healthcare systems. The purpose of our study is to predict the impact of the COVID-19 pandemic on patient outcomes and the healthcare system in Ontario, Canada.\n\nMethodsWe developed an individual-level simulation to model the flow of COVID-19 patients through the Ontario healthcare system. We simulated different combined scenarios of epidemic trajectory and healthcare capacity. Outcomes include numbers of patients needing admission to the ward, Intensive Care Unit (ICU), and requiring ventilation; days to resource depletion; and numbers of patients awaiting resources and deaths associated with limited access to resources.\n\nFindingsWe demonstrate that with effective early public health measures system resources need not be depleted. For scenarios considering late or ineffective implementation of physical distancing, health system resources would be depleted within 14-26 days. Resource depletion was also avoided or delayed with aggressive measures to rapidly increase ICU, ventilator, and acute care hospital capacity.\n\nInterpretationWe found that without aggressive physical distancing measures the Ontario healthcare system would have been inadequately equipped to manage the expected number of patients with COVID-19, despite the rapid capacity increase. This overall lack of resources would have led to an increase in mortality. By slowing the spread of the disease via ongoing public health measures and having increased healthcare capacity, Ontario may have avoided catastrophic stresses to its health care system.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Ricardo Ram\u00edrez-Aldana",
-        "author_inst": "Research Division, Instituto Nacional de Geriatr\u00eda (INGER), Anillo Perif. 2767, San Jeronimo Lidice, La Magdalena Contreras, 10200, Mexico City, Mexico."
+        "author_name": "Kali Barrett",
+        "author_inst": "University Health Network"
       },
       {
-        "author_name": "Juan Carlos Gomez-Verjan",
-        "author_inst": "Instituto Nacional de Geriatria"
+        "author_name": "Yasin A Khan",
+        "author_inst": "University Health Network"
       },
       {
-        "author_name": "Omar Yaxmehen Bello-Chavolla",
-        "author_inst": "Instituto Nacional de Geriatria"
+        "author_name": "Stephen Mac",
+        "author_inst": "Institute of Health Policy, Management and Evaluation, University of Toronto"
+      },
+      {
+        "author_name": "Raphael Ximenes",
+        "author_inst": "Toronto Health Economics and Technology Assessment (THETA) Collaborative, University Health Network"
+      },
+      {
+        "author_name": "David MJ Naimark",
+        "author_inst": "Sunnybrook Health Sciences Centre"
+      },
+      {
+        "author_name": "Beate Sander",
+        "author_inst": "Toronto Health Economics and Technology Assessment (THETA) Collaborative, University Health Network"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1490938,137 +1494347,197 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.17.20064691",
-    "rel_title": "Development and validation of an early warning score (EWAS) for predicting clinical deterioration in patients with coronavirus disease 2019",
+    "rel_doi": "10.1101/2020.04.15.20064931",
+    "rel_title": "Sequencing analysis of the spread of SARS-CoV2 in the Greater New York City region",
     "rel_date": "2020-04-21",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20064691",
-    "rel_abs": "BackgroundSince the pandemic outbreak of coronavirus disease 2019 (COVID-19), the health system capacity in highly endemic areas has been overwhelmed. Approaches to efficient management are urgently needed. We aimed to develop and validate a score for early prediction of clinical deterioration of COVID-19 patients.\n\nMethodsIn this retrospective multicenter cohort study, we included 1138 mild to moderate COVID-19 patients admitted to 33 hospitals in Guangdong Province from December 27, 2019 to March 4, 2020 (N =818; training cohort), as well as two hospitals in Hubei Province from January 21 to February 22, 2020 (N =320; validation cohort) in the analysis.\n\nResultsThe 14-day cumulative incidences of clinical deterioration were 7.9% and 12.1% in the training and validation cohorts, respectively. An Early WArning Score (EWAS) (ranging from 0 to 4.5), comprising of age, underlying chronic disease, neutrophil to lymphocyte ratio, C-reactive protein, and D-dimer levels, was developed (AUROC: 0.857). By applying the EWAS, patients were categorized into low-, medium-, and high risk groups (cut-off values: two and three). The 14-day cumulative incidence of clinical deterioration in the low-risk group was 1.8%, which was significantly lower than the incidence rates in the medium-(14.4%) and high-risk (40.9%) groups (P <.001). The predictability of EWAS was similar in the validation cohort (AUROC =0.781), patients in the low-, medium-, and high-risk groups had 14-day cumulative incidences of 2.6%, 10.0%, and 25.7%, respectively (P <.001).\n\nConclusionThe EWAS, which is based on five common parameters, can predict COVID-19-related clinical deterioration and may be a useful tool for a rapid triage and establishing a COVID-19 hierarchical management system that will greatly focus clinical management and medical resources to reduce mortality in highly endemic areas.",
-    "rel_num_authors": 30,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20064931",
+    "rel_abs": "Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in Spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.",
+    "rel_num_authors": 45,
     "rel_authors": [
       {
-        "author_name": "Yabing Guo",
-        "author_inst": "Nanfang Hospital, Southern Medical University"
+        "author_name": "Matthew T Maurano",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Yingxia Liu",
-        "author_inst": "National Clinical Research Centre for Infectious Disease, Shenzhen Third People's Hospital, Second Affiliated Hospital of Southern University of Science and Tec"
+        "author_name": "Sitharam Ramaswami",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Jiatao Lu",
-        "author_inst": "Wuhan Hankou Hospital"
+        "author_name": "Paul Zappile",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Rong Fan",
-        "author_inst": "Nanfang Hospital, Southern Medical University"
+        "author_name": "Dacia Dimartino",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Fuchun Zhang",
-        "author_inst": "Guangzhou Eighth People's Hospital"
+        "author_name": "Ludovic Boytard",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Xueru Yin",
-        "author_inst": "Nanfang Hospital, Southern Medical University"
+        "author_name": "Andre M Ribeiro-dos-Santos",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Zhihong Liu",
-        "author_inst": "Nanfang Hospital, Southern Medical University"
+        "author_name": "Nicholas A Vulpescu",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Qinglang Zeng",
-        "author_inst": "Honghu People's Hospital"
+        "author_name": "Gael Westby",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Jing Yuan",
-        "author_inst": "National Clinical Research Centre for Infectious Disease, Shenzhen Third People's Hospital, Second Affiliated Hospital of Southern University of Science and Tec"
+        "author_name": "Guomiao Shen",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Shufang Hu",
-        "author_inst": "Wuhan Hankou Hospital"
+        "author_name": "Xiaojun Feng",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Qiongya Wang",
-        "author_inst": "Wuhan Hankou Hospital"
+        "author_name": "Megan S Hogan",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Baolin Liao",
-        "author_inst": "Guangzhou Eighth People's Hospital"
+        "author_name": "Manon Ragonnet-Cronin",
+        "author_inst": "MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Imperial College London"
       },
       {
-        "author_name": "Mingxing Huang",
-        "author_inst": "The Fifth Affiliated Hospital, Sun Yat-sen University"
+        "author_name": "Lily Geidelberg",
+        "author_inst": "MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Imperial College London"
       },
       {
-        "author_name": "Sichun Yin",
-        "author_inst": "The Ninth Dongguan People's Hospital"
+        "author_name": "Christian Marier",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Xilin Zhang",
-        "author_inst": "The Fourth Foshan People's Hospital"
+        "author_name": "Peter Meyn",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Rui Xin",
-        "author_inst": "Guangdong Second Provincial General Hospital"
+        "author_name": "Yutong Zhang",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Zhanzhou Lin",
-        "author_inst": "Huizhou Central People's Hospital"
+        "author_name": "John Cadley",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Changzheng Hu",
-        "author_inst": "Jiangmen Central Hospital"
+        "author_name": "Raquel Ordonez",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Boliang Zhao",
-        "author_inst": "The First Zhaoqing People's Hospital"
+        "author_name": "Raven Luther",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Ridong He",
-        "author_inst": "Zhanjiang Central People's Hospital"
+        "author_name": "Emily Huang",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Minfeng Liang",
-        "author_inst": "The First Foshan People's Hospital"
+        "author_name": "Emily Guzman",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Zheng Zhang",
-        "author_inst": "National Clinical Research Centre for Infectious Disease, Shenzhen Third People's Hospital, Second Affiliated Hospital of Southern University of Science and Tec"
+        "author_name": "Carolina Arguelles-Grande",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Li Liu",
-        "author_inst": "Nanfang Hospital, Southern Medical University"
+        "author_name": "Kimon V Argyropoulos",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Jian Sun",
-        "author_inst": "Nanfang Hospital, Southern Medical University"
+        "author_name": "Margaret Black",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Lu Tang",
-        "author_inst": "University of Pittsburgh"
+        "author_name": "Antonio Serrano",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Lisi Deng",
-        "author_inst": "The Fifth Affiliated Hospital, Sun Yat-sen University"
+        "author_name": "Melissa E Call",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Jinyu Xia",
-        "author_inst": "The Fifth Affiliated Hospital, Sun Yat-sen University"
+        "author_name": "Min Jae Kim",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Xiaoping Tang",
-        "author_inst": "Guangzhou Eighth People's Hospital"
+        "author_name": "Brendan Belovarac",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Lei Liu",
-        "author_inst": "National Clinical Research Centre for Infectious Disease, Shenzhen Third People's Hospital, Second Affiliated Hospital of Southern University of Science and Tec"
+        "author_name": "Tatyana Gindin",
+        "author_inst": "NYU School of Medicine"
       },
       {
-        "author_name": "Jinlin Hou",
-        "author_inst": "Nanfang Hospital, Southern Medical University"
+        "author_name": "Andrew Lytle",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Jared Pinnell",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Theodore Vougiouklakis",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "John Chen",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Lawrence H Lin",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Amy Rapkiewicz",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Vanessa Raabe",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Marie I Samanovic",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "George Jour",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Iman Osman",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Maria Aguero-Rosenfeld",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Mark J Mulligan",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Erik M Volz",
+        "author_inst": "MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Imperial College London"
+      },
+      {
+        "author_name": "Paolo Cotzia",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Matija Snuderl",
+        "author_inst": "NYU School of Medicine"
+      },
+      {
+        "author_name": "Adriana Heguy",
+        "author_inst": "NYU School of Medicine"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1493028,75 +1496497,63 @@
     "category": "immunology"
   },
   {
-    "rel_doi": "10.1101/2020.04.20.051219",
-    "rel_title": "Protocol and reagents for pseudotyping lentiviral particles with SARS-CoV-2 Spike protein for neutralization assays",
+    "rel_doi": "10.1101/2020.04.20.051581",
+    "rel_title": "Boceprevir, GC-376, and calpain inhibitors II, XII inhibit SARS-CoV-2 viral replication by targeting the viral main protease",
     "rel_date": "2020-04-20",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.20.051219",
-    "rel_abs": "SARS-CoV-2 enters cells using its Spike protein, which is also the main target of neutralizing antibodies. Therefore, assays to measure how antibodies and sera affect Spike-mediated viral infection are important for studying immunity. Because SARS-CoV-2 is a biosafety-level-3 virus, one way to simplify such assays is to pseudotype biosafety-level-2 viral particles with Spike. Such pseudotyping has now been described for single-cycle lentiviral, retroviral and VSV particles, but the reagents and protocols are not widely available. Here we detail how to effectively pseudotype lentiviral particles with SARS-CoV-2 Spike and infect 293T cells engineered to express the SARS-CoV-2 receptor, ACE2. We also make all the key experimental reagents available in the BEI Resources repository of ATCC and the NIH. Furthermore, we demonstrate how these pseudotyped lentiviral particles can be used to measure the neutralizing activity of human sera or plasma against SARS-CoV-2 in convenient luciferase-based assays, thereby providing a valuable complement to ELISA-based methods that measure antibody binding rather than neutralization.",
-    "rel_num_authors": 14,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.20.051581",
+    "rel_abs": "A novel coronavirus SARS-CoV-2, also called novel coronavirus 2019 (nCoV-19), started to circulate among humans around December 2019, and it is now widespread as a global pandemic. The disease caused by SARS-CoV-2 virus is called COVID-19, which is highly contagious and has an overall mortality rate of 6.96% as of May 4, 2020. There is no vaccine or antiviral available for SARS-CoV-2. In this study, we report our discovery of inhibitors targeting the SARS-CoV-2 main protease (Mpro). Using the FRET-based enzymatic assay, several inhibitors including boceprevir, GC-376, and calpain inhibitors II, and XII were identified to have potent activity with single-digit to submicromolar IC50 values in the enzymatic assay. The mechanism of action of the hits was further characterized using enzyme kinetic studies, thermal shift binding assays, and native mass spectrometry. Significantly, four compounds (boceprevir, GC-376, calpain inhibitors II and XII) inhibit SARS-CoV-2 viral replication in cell culture with EC50 values ranging from 0.49 to 3.37 M. Notably, boceprevir, calpain inhibitors II and XII represent novel chemotypes that are distinct from known Mpro inhibitors. A complex crystal structure of SARS-CoV-2 Mpro with GC-376, determined at 2.15 [A] resolution with three monomers per asymmetric unit, revealed two unique binding configurations, shedding light on the molecular interactions and protein conformational flexibility underlying substrate and inhibitor binding by Mpro. Overall, the compounds identified herein provide promising starting points for the further development of SARS-CoV-2 therapeutics.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Kate H.D. Crawford",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Rachel Eguia",
-        "author_inst": "Fred Hutchinson Cancer Research Center"
-      },
-      {
-        "author_name": "Adam S Dingens",
-        "author_inst": "Fred Hutchinson Cancer Research Center"
-      },
-      {
-        "author_name": "Andrea N Loes",
-        "author_inst": "Fred Hutchinson Cancer Research Center"
+        "author_name": "Chunlong Ma",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Keara D Malone",
-        "author_inst": "Fred Hutchinson Cancer Research Center"
+        "author_name": "Michael D Sacco",
+        "author_inst": "University of South Florida"
       },
       {
-        "author_name": "Caitlin R Wolf",
-        "author_inst": "University of Washington"
+        "author_name": "Brett Hurst",
+        "author_inst": "Utah State University"
       },
       {
-        "author_name": "Helen Y Chu",
-        "author_inst": "University of Washington"
+        "author_name": "Julia A Townsend",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "M. Alejandra Tortorici",
-        "author_inst": "University of Washington"
+        "author_name": "Yanmei Hu",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "David Veesler",
-        "author_inst": "University of Washington"
+        "author_name": "Tommy Szeto",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Michael Murphy",
-        "author_inst": "University of Washington"
+        "author_name": "Xiujun Zhang",
+        "author_inst": "University of South Florida"
       },
       {
-        "author_name": "Deleah Pettie",
-        "author_inst": "University of Washington"
+        "author_name": "Bart Tarbet",
+        "author_inst": "Utah State University"
       },
       {
-        "author_name": "Neil P King",
-        "author_inst": "University of Washington"
+        "author_name": "Michael T Marty",
+        "author_inst": "University of Arizona"
       },
       {
-        "author_name": "Alejandro B Balazs",
-        "author_inst": "Ragon Institute"
+        "author_name": "Yu Chen",
+        "author_inst": "University of South Florida"
       },
       {
-        "author_name": "Jesse D Bloom",
-        "author_inst": "Fred Hutchinson Cancer Research Center"
+        "author_name": "Jun Wang",
+        "author_inst": "University of Arizona"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "microbiology"
+    "category": "pharmacology and toxicology"
   },
   {
     "rel_doi": "10.1101/2020.04.20.050138",
@@ -1494634,155 +1498091,75 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2020.04.17.046375",
-    "rel_title": "Rapid development of an inactivated vaccine for SARS-CoV-2",
+    "rel_doi": "10.1101/2020.04.14.20060160",
+    "rel_title": "Patient-derived mutations impact pathogenicity of SARS-CoV-2",
     "rel_date": "2020-04-19",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.17.046375",
-    "rel_abs": "The COVID-19 pandemic caused by SARS-CoV-2 has brought about an unprecedented crisis, taking a heavy toll on human health, lives as well as the global economy. There are no SARS-CoV-2-specific treatments or vaccines available due to the novelty of this virus. Hence, rapid development of effective vaccines against SARS-CoV-2 is urgently needed. Here we developed a pilot-scale production of a purified inactivated SARS-CoV-2 virus vaccine candidate (PiCoVacc), which induced SARS-CoV-2-specific neutralizing antibodies in mice, rats and non-human primates. These antibodies potently neutralized 10 representative SARS-CoV-2 strains, indicative of a possible broader neutralizing ability against SARS-CoV-2 strains circulating worldwide. Immunization with two different doses (3g or 6 g per dose) provided partial or complete protection in macaques against SARS-CoV-2 challenge, respectively, without any antibody-dependent enhancement of infection. Systematic evaluation of PiCoVacc via monitoring clinical signs, hematological and biochemical index, and histophathological analysis in macaques suggests that it is safe. These data support the rapid clinical development of SARS-CoV-2 vaccines for humans.\n\nOne Sentence SummaryA purified inactivated SARS-CoV-2 virus vaccine candidate (PiCoVacc) confers complete protection in non-human primates against SARS-CoV-2 strains circulating worldwide by eliciting potent humoral responses devoid of immunopathology",
-    "rel_num_authors": 34,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20060160",
+    "rel_abs": "The sudden outbreak of the severe acute respiratory syndrome-coronavirus (SARS-CoV-2) has spread globally with more than 1,300,000 patients diagnosed and a death toll of 70,000. Current genomic survey data suggest that single nucleotide variants (SNVs) are abundant. However, no mutation has been directly linked with functional changes in viral pathogenicity. We report functional characterizations of 11 patient-derived viral isolates. We observed diverse mutations in these viral isolates, including 6 different mutations in the spike glycoprotein (S protein), and 2 of which are different SNVs that led to the same missense mutation. Importantly, these viral isolates show significant variation in cytopathic effects and viral load, up to 270-fold differences, when infecting Vero-E6 cells. Therefore, we provide direct evidence that the SARS-CoV-2 has acquired mutations capable of substantially changing its pathogenicity.",
+    "rel_num_authors": 14,
     "rel_authors": [
       {
-        "author_name": "Qiang Gao",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Linlin Bao",
-        "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College"
-      },
-      {
-        "author_name": "Haiyan Mao",
-        "author_inst": "Department of Microbiology, Zhejiang Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Lin Wang",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Kangwei Xu",
-        "author_inst": "Division of Respiratory Virus Vaccines, National Institute for Food and Drug Control"
-      },
-      {
-        "author_name": "minnan Yang",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Yajing Li",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Ling Zhu",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Nan Wang",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Zhe Lv",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Hong Gao",
-        "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College"
-      },
-      {
-        "author_name": "Xiaoqin Ge",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Biao Kan",
-        "author_inst": "National Institute for Communicable Disease Control and Prevention, China CDC"
-      },
-      {
-        "author_name": "Yaling Hu",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Jiangning Liu",
-        "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College"
-      },
-      {
-        "author_name": "Fang Cai",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Deyu Jiang",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Yanhui Yin",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Chengfeng Qin",
-        "author_inst": "Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences"
-      },
-      {
-        "author_name": "Jing Li",
-        "author_inst": "Sinovac Biotech Ltd"
-      },
-      {
-        "author_name": "Xuejie Gong",
-        "author_inst": "Sinovac Biotech Ltd"
+        "author_name": "Hangping Yao",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Xiuyu Lou",
-        "author_inst": "Department of Microbiology, Zhejiang Provincial Center for Disease Control and Prevention"
+        "author_name": "Xiangyun Lu",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Wen Shi",
-        "author_inst": "Department of Microbiology, Zhejiang Provincial Center for Disease Control and Prevention"
+        "author_name": "Qiong Chen",
+        "author_inst": "Life Sciences Institute, Zhejiang University"
       },
       {
-        "author_name": "Dongdong Wu",
-        "author_inst": "Sinovac Biotech Ltd"
+        "author_name": "Kaijin Xu",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Hengming Zhang",
-        "author_inst": "Sinovac Biotech Ltd"
+        "author_name": "Yu Chen",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Lang Zhu",
-        "author_inst": "Sinovac Biotech Ltd"
+        "author_name": "Linfang Cheng",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Wei Deng",
-        "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College"
+        "author_name": "Fumin Liu",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Yurong Li",
-        "author_inst": "Sinovac Biotech Ltd"
+        "author_name": "Zhigang Wu",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Jinxing Lu",
-        "author_inst": "National Institute for Communicable Diseases"
+        "author_name": "Haibo Wu",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Changgui Li",
-        "author_inst": "Division of Respiratory Virus Vaccines, National Institute for Food and Drug Control"
+        "author_name": "Changzhong Jin",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Xiangxi Wang",
-        "author_inst": "Institute of Biophysics, Chinese Academy of Sciences"
+        "author_name": "Min Zheng",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Weidong Yin",
-        "author_inst": "Sinovac Biotech Ltd"
+        "author_name": "Nanping Wu",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Z"
       },
       {
-        "author_name": "Yanjun Zhang",
-        "author_inst": "Zhejiang Center for Disease Control and Prevention"
+        "author_name": "Chao Jiang",
+        "author_inst": "Life Sciences Institute, Zhejiang University"
       },
       {
-        "author_name": "Chuan Qin",
-        "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences"
+        "author_name": "Lanjuan Li",
+        "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease, The First Affiliated Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.16.20067611",
@@ -1496688,27 +1500065,23 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.04.14.20065466",
-    "rel_title": "Modelling strategies to predict hospital demand during the COVID-19 outbreak in Bogota, Colombia",
+    "rel_doi": "10.1101/2020.04.14.20065706",
+    "rel_title": "Has mortality due to other causes increased during the Covid-19 pandemic? Early evidence from England and Wales",
     "rel_date": "2020-04-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065466",
-    "rel_abs": "Colombia, like many developing nations, does not have a strong health system able to respond to a pandemic of the magnitude of Covid-19. There is an increasing need to create a model that allows particular clinics and hospitals to estimate the number of patients that require Intensive Care Units-ICU care (critical), and the number of patients that require hospital care (severe), but not ICU care, in order to manage their limited resources.\n\nThis paper presents a prediction of the total number of ICU and regular beds that will be needed during the pandemic COVID-19 for Bogota-Colombia. We use a SEIR model that includes three different compartments of infection: those who can stay at home, those in regular hospital beds and those in need of ICU treatment. The model allows for a time varying transmission rate which we use to incorporate the measures introduced by the government over the period of one semester. The model predicts that by mid October 2020, the city will need 4 524 prevalent ICUs needed and 16 738 regular hospital beds needed. By the third week of July 2020, the number of patients that need ICUs will overpass the capacity set at 1 200 beds for ICU hospital beds in the city. The model predicts that the death toll by the same date will reach 1 752 people and the number of cases will be 30 216 inhabitants by then. We provide a Shiny app available in https://claudia-rivera-rodriguez.shinyapps.io/shinyappcovidclinic/. The original values in the app reproduce the results of this paper, but the parameters and starting values can be changed according to the users needs. COVID-19 has posed too many challenges to health systems around the globe, this model is an useful tool for cities, hospitals and clinics in Colombia that need to prepare for the excess demand of services that a pandemic like this one generates. Unfortunately, the model predicts that by the third week of July the projected capacity of the system in Bogota will not be enough. We expect the lockdown rules strength in the future days, so the death toll is not as bad as predicted by this model.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065706",
+    "rel_abs": "BackgroundThe Covid-19 pandemic has claimed many lives in the UK and globally. The objective of this paper is to study whether the number of deaths not registered as covid-19-related has increased compared to what would have been expected in the absence of the pandemic. This may be a result of some covid-19 deaths being unreported or spillover effects on other causes of death (or both). Reasons behind this might include covid-19 underreporting, avoiding visits to hospitals or GPs, and the effects of the lockdown.\n\nMethodsI used weekly ONS data on the number of deaths in England and Wales that did not officially involve covid-19 over the period 2015-2020. Simply observing trends is not sufficient as spikes in deaths may occasionally occur. I thus followed a differences-in-differences econometric approach to study whether there was a relative increase in deaths not registered as covid-19-related during the pandemic, compared to a control. As an additional approach, an interrupted time series model was also used.\n\nResultsResults suggest that there are an additional 968 weekly deaths that officially did not involve covid-19, compared to what would have otherwise been expected. This increase is also confirmed by the interrupted time series analysis.\n\nDiscussionThe number of deaths not officially involving covid-19 has demonstrated an absolute and relative increase during the pandemic. It is possible that some people are dying from covid-19 without being diagnosed, and that there are excess deaths due to other causes as a result of the pandemic. Analysing the cause of death for any excess non-covid-19 deaths will shed light upon the reasons for the increase in such deaths and will help design appropriate policy responses to save lives.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Claudia Rivera-Rodriguez",
-        "author_inst": "The University of Auckland"
-      },
-      {
-        "author_name": "Beatriz Piedad Urdinola",
-        "author_inst": "National University of Colombia"
+        "author_name": "Sotiris Vandoros",
+        "author_inst": "King's College London"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "public and global health"
   },
   {
     "rel_doi": "10.1101/2020.04.15.20067207",
@@ -1498050,67 +1501423,99 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.16.044503",
-    "rel_title": "SARS-CoV-2 is transmitted via contact and via the air between ferrets.",
+    "rel_doi": "10.1101/2020.04.14.20064733",
+    "rel_title": "Chest Computed Tomography for the Diagnosis of Patients with Coronavirus Disease 2019 (COVID-19): A Rapid Review and Meta-Analysis",
     "rel_date": "2020-04-17",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.16.044503",
-    "rel_abs": "SARS-CoV-2, a coronavirus that newly emerged in China in late 2019 1,2 and spread rapidly worldwide, caused the first witnessed pandemic sparked by a coronavirus. As the pandemic progresses, information about the modes of transmission of SARS-CoV-2 among humans is critical to apply appropriate infection control measures and to slow its spread. Here we show that SARS-CoV-2 is transmitted efficiently via direct contact and via the air (via respiratory droplets and/or aerosols) between ferrets. Intranasal inoculation of donor ferrets resulted in a productive upper respiratory tract infection and long-term shedding, up to 11 to 19 days post-inoculation. SARS-CoV-2 transmitted to four out of four direct contact ferrets between 1 and 3 days after exposure and via the air to three out of four independent indirect recipient ferrets between 3 and 7 days after exposure. The pattern of virus shedding in the direct contact and indirect recipient ferrets was similar to that of the inoculated ferrets and infectious virus was isolated from all positive animals, showing that ferrets were productively infected via either route. This study provides experimental evidence of robust transmission of SARS-CoV-2 via the air, supporting the implementation of community-level social distancing measures currently applied in many countries in the world and informing decisions on infection control measures in healthcare settings 3.",
-    "rel_num_authors": 12,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20064733",
+    "rel_abs": "BackgroundThe outbreak of the coronavirus disease 2019 (COVID-19) has had a massive impact on the whole world. Computed tomography (CT) has been widely used in the diagnosis of this novel pneumonia. This study aims to understand the role of CT for the diagnosis and the main imaging manifestations of patients with COVID-19.\n\nMethodsWe conducted a rapid review and meta-analysis on studies about the use of chest CT for the diagnosis of COVID-19. We comprehensively searched databases and preprint servers on chest CT for patients with COVID-19 between 1 January 2020 and 31 March 2020. The primary outcome was the sensitivity of chest CT imaging. We also conducted subgroup analyses and evaluated the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.\n\nResultsA total of 104 studies with 5694 patients were included. Using RT-PCR results as reference, a meta-analysis based on 64 studies estimated the sensitivity of chest CT imaging in COVID-19 was 99% (95% CI, 0.97-1.00). If case reports were excluded, the sensitivity in case series was 96% (95% CI, 0.93-0.99). The sensitivity of CT scan in confirmed patients under 18 years old was only 66% (95% CI, 0.11-1.00). The most common imaging manifestation was ground-glass opacities (GGO) which was found in 75% (95% CI, 0.68-0.82) of the patients. The pooled probability of bilateral involvement was 84% (95% CI, 0.81-0.88). The most commonly involved lobes were the right lower lobe (84%, 95% CI, 0.78-0.90) and left lower lobe (81%, 95% CI, 0.74-0.87). The quality of evidence was low across all outcomes.\n\nConclusionsIn conclusion, this meta-analysis indicated that chest CT scan had a high sensitivity in diagnosis of patients with COVID-19. Therefore, CT can potentially be used to assist in the diagnosis of COVID-19.",
+    "rel_num_authors": 20,
     "rel_authors": [
       {
-        "author_name": "Mathilde Richard",
-        "author_inst": "ErasmusMC"
+        "author_name": "Meng Lv",
+        "author_inst": "Lanzhou University"
       },
       {
-        "author_name": "Adinda Kok",
-        "author_inst": "ErasmusMC"
+        "author_name": "Mengshu Wang",
+        "author_inst": "Department of Radiology, The First Affiliated Hospital, Lanzhou University"
       },
       {
-        "author_name": "Dennis de Meulder",
-        "author_inst": "ErasmusMC"
+        "author_name": "Nan Yang",
+        "author_inst": "Department of Respiratory Medicine; Children's Hospital of Chongqing Medical University"
       },
       {
-        "author_name": "Theo M. Bestebroer",
-        "author_inst": "ErasmusMC"
+        "author_name": "Xufei Luo",
+        "author_inst": "School of Public Health of Lanzhou University, Lanzhou"
       },
       {
-        "author_name": "Mart M. Lamers",
-        "author_inst": "ErasmusMC"
+        "author_name": "Wei Li",
+        "author_inst": "Department of Radiology; Children's Hospital of Chongqing Medical University"
       },
       {
-        "author_name": "Nisreen M.A. Okba",
-        "author_inst": "ErasmusMC"
+        "author_name": "Xin Chen",
+        "author_inst": "Department of Radiology; Children's Hospital of Chongqing Medical University"
       },
       {
-        "author_name": "Martje Fentener van Vlissingen",
-        "author_inst": "ErasmusMC"
+        "author_name": "Yunlan Liu",
+        "author_inst": "School of Public Health, Lanzhou University"
       },
       {
-        "author_name": "Barry Rockx",
-        "author_inst": "ErasmusMC"
+        "author_name": "Mengjuan Ren",
+        "author_inst": "School of Public Health, Lanzhou University"
       },
       {
-        "author_name": "Bart L. Haagmans",
-        "author_inst": "ErasmusMC"
+        "author_name": "Xianzhuo Zhang",
+        "author_inst": "The First School of Clinical Medicine, Lanzhou University"
       },
       {
-        "author_name": "Marion P.G. Koopmans",
-        "author_inst": "ErasmusMC"
+        "author_name": "Ling Wang",
+        "author_inst": "School of Public Health, Lanzhou University"
       },
       {
-        "author_name": "Ron A.M. Fouchier",
-        "author_inst": "ErasmusMC"
+        "author_name": "Yanfang Ma",
+        "author_inst": "Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University"
       },
       {
-        "author_name": "Sander Herfst",
-        "author_inst": "ErasmusMC"
+        "author_name": "Junqiang Lei",
+        "author_inst": "Department of Radiology, The First Affiliated Hospital, Lanzhou University"
+      },
+      {
+        "author_name": "Toshio Fukuoka",
+        "author_inst": "Emergency and Critical Care Center, the Department of General Medicine, Department of Research and Medical Education at Kurashiki Central Hospital"
+      },
+      {
+        "author_name": "Hyeong Sik Ahn",
+        "author_inst": "Department of Preventive Medicine, Korea University College of Medicine"
+      },
+      {
+        "author_name": "Myeong Soo Lee",
+        "author_inst": "Korea Institute of Oriental Medicine, Daejeon, Korea"
+      },
+      {
+        "author_name": "Zhengxiu Luo",
+        "author_inst": "Department of Respiratory Medicine; Children's Hospital of Chongqing Medical University"
+      },
+      {
+        "author_name": "Yaolong Chen",
+        "author_inst": "Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University"
+      },
+      {
+        "author_name": "Enmei Liu",
+        "author_inst": "Department of Respiratory Medicine; Children's Hospital of Chongqing Medical University"
+      },
+      {
+        "author_name": "Jinhui Tian",
+        "author_inst": "Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University"
+      },
+      {
+        "author_name": "Xiaohui Wang",
+        "author_inst": "School of Public Health, Lanzhou University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "microbiology"
+    "license": "",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "radiology and imaging"
   },
   {
     "rel_doi": "10.1101/2020.04.16.044016",
@@ -1499660,71 +1503065,31 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.17.20067348",
-    "rel_title": "Massive and rapid COVID-19 testing is feasible by extraction-free SARS-CoV-2 RT-qPCR",
+    "rel_doi": "10.1101/2020.04.14.20064501",
+    "rel_title": "What influences COVID-19 infection rates: A statistical approach to identify promising factors applied to infection data from Germany",
     "rel_date": "2020-04-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20067348",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The most widely used method of COVID-19 diagnostics is a reverse transcription polymerase chain reaction (RT-PCR) assay, to detect the presence of SARS-CoV-2 RNA in patient samples, typically from nasopharyngeal swabs. RNA extraction is a major bottleneck in current COVID-19 testing, in terms of turn-around, logistics, component availability and cost, which delays or completely precludes COVID-19 diagnostics in many settings. Efforts to simplify the current methods are critical, as increased diagnostic availability and efficiency would benefit patient care and infection control. Here, we describe methods to circumvent RNA extraction in COVID-19 testing by performing RT-PCR directly on heat-inactivated subject samples as well as samples lysed with readily available detergents. Our data, including benchmarking with 597 clinically diagnosed patient samples against a standardised and sensitive diagnostic system, show that direct RT-PCR is a viable option to extraction-based COVID-19 diagnostics. Furthermore, using controlled amounts of active SARS-CoV-2, we evaluated performance of generic buffers as sample medium for the direct RT-PCR assay, identifying several suitable formulations. We also confirmed the effectiveness of heat inactivation of SARS-CoV-2 by plaque assay. Significant savings in terms of time and cost can be achieved by embracing RNA-extraction-free protocols, that feed directly into the established PCR-based testing pipeline. This could aid the expansion of COVID-19 testing.",
-    "rel_num_authors": 13,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20064501",
+    "rel_abs": "The recent COVID-19 pandemic is of big and world-wide concern. There is an intense discussion and uncertainty which factors and sanctions can reduce infection rates. The overall aim is to prevent an overload of the medical system. Even within one country, there is frequently a strong local variability in both - political sanctions as well as other local factors - which may influence infection rates. The main focus of study is analysis and interpretation of recent temporal developments (infection rates). We present a statistical framework designed to identify local factors which reduce infection rates. The approach is robust with respect to the number of undetected infection cases. We apply the framework to spatio-temporal infection data from Germany. In particular, we demonstrate that (1) infection rates are in average significantly decreasing in Germany; (2) there is a high spatial variability of these rates, and (3) both, early emergence of first infections and high local infection densities has led to strong recent decays in infection rates, suggesting that psychological effects (such as awareness of danger) lead to behaviour changes that reduce infection rates. However, the full potential of the presented method cannot yet be exploited, since more precise spatio-temporal data, such as local cell phone-based mobility data, are not yet available. In the nearest future, the presented framework could be applied to data from other countries at any state of infection, even during the exponential phase of the growth of infection rates.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Ioanna Smyrlaki",
-        "author_inst": "Karolinska Institute"
+        "author_name": "Moritz Mercker",
+        "author_inst": "BIONUM -  Consultants in biological and biomedical statistics, Hamburg, Germany"
       },
       {
-        "author_name": "Martin Ekman",
-        "author_inst": "Karolinska University Hospital"
+        "author_name": "Uwe Betzin",
+        "author_inst": "User Experience Consultant, Schriesheim, Germany"
       },
       {
-        "author_name": "Antonio Lentini",
-        "author_inst": "Karolinska Institute"
-      },
-      {
-        "author_name": "Nuno Rufino de Sousa",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Natali Papanicoloau",
-        "author_inst": "Karolinska Institute"
-      },
-      {
-        "author_name": "Martin Vondracek",
-        "author_inst": "Karolinska University Hospital"
-      },
-      {
-        "author_name": "Johan Aarum",
-        "author_inst": "Karolinska University Hospital"
-      },
-      {
-        "author_name": "Hamzah Safari",
-        "author_inst": "Karolinska University Hospital"
-      },
-      {
-        "author_name": "Shaman Muradrasoli",
-        "author_inst": "Public Health Agency of Sweden"
-      },
-      {
-        "author_name": "Antonio Gigliotti Rothfuchs",
-        "author_inst": "Karolinska Institutet"
-      },
-      {
-        "author_name": "Jan Albert",
-        "author_inst": "Karolinska Institute"
-      },
-      {
-        "author_name": "Bj\u00f6rn H\u00f6gberg",
-        "author_inst": "Karolinska Institute"
-      },
-      {
-        "author_name": "Bj\u00f6rn Reinius",
-        "author_inst": "Karolinska Institute"
+        "author_name": "Dennis Wilken",
+        "author_inst": "Institute of Geosciences, Kiel University, Kiel, Germany"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.04.14.20064840",
@@ -1500790,63 +1504155,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.16.20061044",
-    "rel_title": "EFFECTIVENESS OF BASELINE AND POST-PROCESSED CHEST X-RAY IN NONEARLY COVID-19 PATIENTS",
+    "rel_doi": "10.1101/2020.04.12.20062695",
+    "rel_title": "Shut it down: a cross country panel analysis on the efficacy of lockdown measures",
     "rel_date": "2020-04-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20061044",
-    "rel_abs": "BackgroundCT is a very sensitive technique to detect pneumonia in COVID-19 patients. However, it is impaired by high costs, logistic issues and high risk of exposure.\n\nChest x-ray (CXR) is a low-cost, low-risk, not time consuming technique and is emerging as the recommended imaging modality to use in COVID-19 pandemic.\n\nThis technique, although less sensitive than CT-scan, can provide useful information about pulmonary involvement.\n\nPurposeTo describe chest x-ray features of COVID-19 pneumonia and to evaluate the sensitivity of this technique in detecting pneumonia. A further scope is to assess the effectiveness of a post-processing algorithm in improving lung lesions detectability.\n\nMaterials and Methods72 patients with laboratory-confirmed COVID-19 underwent bedside chest X-ray.\n\nTwo radiologists were asked to express their opinion about: (i) presence of pneumonia (negative or positive); (ii) localization (unilateral or bilateral); (iii) topography (according to pulmonary fields); (iv) density (non consolidative ground-glass or inhomogeneous opacities; consolidative nodular-type or triangular; mixed consolidative e non-consolidative); and (v) presence of pleural effusion. The point (i) was evaluated separately, while the other points in consensus.\n\nA quality assessment of post-processed x-ray images was performed by two different readers.\n\nResultsThe agreement about presence of pneumonia was almost perfect with K value of 0.933 and p < 0.001.\n\nSensitivity was 69%.\n\nThe following findings were seen: unilateral lung involvement in 50%; lower lung lesions in 54%; peripheral distribution in 48%; and non-consolidative pattern in 44%.\n\nPost-processed images improved the detection of lesions in 7 out 72 patients ({cong}10%)\n\nConclusionCXR owns a good sensitivity in detecting COVID-19 lung involvement. Use of post-processing algorithm can improve detection of lesions. Our data support recommendations of the Radiological Society of North America (RSNA) to consider chest x-ray as first step imaging examination in Covid-19 patients.\n\nSUMMARYBedside CXR has a good sensitivity in evaluating COVID-19 lung involvement in hospitalized patients and should be considered as the first step imaging technique according to RSNA recommendations.\n\nKEY RESULTSO_LIBedside CXR has a good sensitivity in evaluating COVID-19 lung involvement in non-early clinical cases.\nC_LIO_LIThe most common findings of lung involvement were slight different from the well-described CT-ones, with less common patterns of bilateral and peripheral distribution.\nC_LIO_LIPost-processing algorithm enhances detection of pulmonary lesions.\nC_LI",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20062695",
+    "rel_abs": "Coronavirus pandemic outbreak from China in the December 2019 and since then has quickly spread all over the world. National governments introduced policies aimed to reduce the probability to contract the virus, such as lockdown measures, in order to limit the outbreak. Lockdown fostered a debate about the effective need and the optimal duration of such measures. Indeed, these policies have a high price, being characterized by the alt of many productive activities. The aim of this note is to provide preliminary evidences about the efficacy of lockdown measures all over the world, by the means of a panel data quantitative analysis. Our results confirm the efficacy of such measures, and that the average time to have effects in terms of a reduction of cases is of about ten days. Furthermore the beneficial effects of a lockdown keep reducing the new cases with a linear trend for at least the ten successive days.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Michele Gaeta",
-        "author_inst": "University of Messina"
-      },
-      {
-        "author_name": "Giuseppe Cicero",
-        "author_inst": "University of Messina"
-      },
-      {
-        "author_name": "Maria Adele Marino",
-        "author_inst": "University of Messina"
-      },
-      {
-        "author_name": "Tommaso D'Angelo",
-        "author_inst": "University of Messina"
-      },
-      {
-        "author_name": "Enrico Maria Mormina",
-        "author_inst": "University of Messina"
-      },
-      {
-        "author_name": "Silvio Mazziotti",
-        "author_inst": "University of Messina"
-      },
-      {
-        "author_name": "Alfredo Blandino",
-        "author_inst": "University of Messina"
-      },
-      {
-        "author_name": "Giulio Siracusano",
-        "author_inst": "University of Catania"
-      },
-      {
-        "author_name": "Aurelio La Corte",
-        "author_inst": "University of Catania"
-      },
-      {
-        "author_name": "Massimo Chiappini",
-        "author_inst": "Instituto Nazionale di Geofisica e Vulcanologia"
+        "author_name": "Vincenzo Alfano",
+        "author_inst": "University of Napoli Federico II"
       },
       {
-        "author_name": "Giovanni Finocchio",
-        "author_inst": "University of Messina"
+        "author_name": "Salvatore Ercolano",
+        "author_inst": "University of Basilicata"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "radiology and imaging"
+    "category": "health economics"
   },
   {
     "rel_doi": "10.1101/2020.04.11.20062125",
@@ -1502056,25 +1505385,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.13.20063644",
-    "rel_title": "Estimating the impact of mobility patterns on COVID-19 infection rates in 11 European countries",
+    "rel_doi": "10.1101/2020.04.13.20063610",
+    "rel_title": "The December 2019 New Corona Virus Disease (SARS-CoV-2) Outbreak: A Behavioral Infectious Disease Policy Model",
     "rel_date": "2020-04-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20063644",
-    "rel_abs": "BackgroundAs governments across Europe have issued non-pharmaceutical interventions (NPIs) such as social distancing and school closing, the mobility patterns in these countries have changed. It is likely different countries and populations respond differently to the same NPIs and that these differences are reflected in the epidemic development.\n\nMethodsWe build a Bayesian model that estimates the number of deaths on a given day dependent on changes in the basic reproductive number, R0, due to changes in mobility patterns. We utilize mobility data from Google mobility reports using five different categories: retail and recreation, grocery and pharmacy, transit stations, workplace and residential. The importance of each mobility category for predicting changes in R0 is estimated through the model.\n\nFindingsThe changes in mobility have a large overlap with the introduction of governmental NPIs, highlighting the importance of government action for population behavioural change. The grocery and pharmacy sector is estimated to account for 97 % of the reduction in R0 (95% confidence interval [0{middle dot}79,0{middle dot}99]).\n\nInterpretationOur model predicts three-week epidemic forecasts, using real-time observations of changes in mobility patterns, which can provide governments with direct feedback on the effects of their NPIs. The model predicts the changes in a majority of the countries accurately but overestimates the impact of NPIs in Sweden and Denmark and underestimates them in France and Belgium.\n\nFundingFinancial support: Swedish Research Council for Natural Science, grant No. VR-2016-06301 and Swedish E-science Research Center. Computational resources: Swedish National Infrastructure for Computing, grant No. SNIC-2019/3-319.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20063610",
+    "rel_abs": "It is critical to understand the impact of distinct policy interventions to the ongoing coronavirus disease pandemic. I develop a flexible behavioral, dynamic, and sectorial epidemic policy model comprising both endogenous virus transmission and public health and citizen responses. Applicable to the full epidemic cycle including confinement, deconfinement, and resurgence, the model allows exploring the multivariate impact of distinct policy interventions, including general and targeted testing and social contact reduction efforts. Using a cross-sectional calibration to data on the ongoing coronavirus disease outbreak about reported cases and deaths, tests performed, and social interactions from six countries (South Korea, Germany, Italy, France, Sweden, and the United States), I demonstrate how early, rapid, and extensive buildup of testing and social contact reduction efforts interplay to suppress the outbreak. I then use the model to show and quantify limits to the extent of deconfinement and illustrate the critical role of targeted approaches for managing post peak deconfinement and resurgence. To aid necessary public and expert understanding of outbreak control strategies the model is accessible in the form of a web-based management flight simulator.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Patrick Bryant",
-        "author_inst": "Stockholm University/Science for Life Laboratory"
-      },
-      {
-        "author_name": "Arne Elofsson",
-        "author_inst": "Stockholm University/Science for Life Laboratory"
+        "author_name": "Jeroen Struben",
+        "author_inst": "emlyon business school"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1503078,41 +1506403,61 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.11.20061721",
-    "rel_title": "COVID-19-related mortality by age groups in Europe: A meta-analysis",
+    "rel_doi": "10.1101/2020.04.12.20062869",
+    "rel_title": "Cardiovascular Diseases and COVID-19 Mortality and Intensive Care Unit Admission: A Systematic Review and Meta-analysis",
     "rel_date": "2020-04-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20061721",
-    "rel_abs": "Background and ObjectivesTo date, more than 1,000,000 confirmed cases and 65,000 deaths due to coronavirus disease 2019 (COVID-19) have been reported globally. Early data have indicated that older patients are at higher risk of dying from COVID-19 than younger ones, but precise international estimates of the age-breakdown of COVID-19-related deaths are lacking.\n\nMaterials and MethodsWe evaluated the distribution of COVID-19-related fatalities by age groups in Europe. On April 6, 2020, we systematically reviewed COVID-19-related mortality data from 32 European countries (European Union/European Economic Area and the United Kingdom). We collated official reports provided by local Public Health or Ministry of Health websites. We included countries if they provided data regarding more than 10 COVID-19-related deaths stratified by age according to pre-specified groups (i.e., < 40, 40-69, [&ge;] 70 years). We used random-effects meta-analysis to estimate the proportion of age groups among all COVID-19-related fatalities.\n\nResultsThirteen European countries were included in the review, for a total of 31,864 COVID-19-related deaths (range: 27-14,381 per country). In the main meta-analysis (including data from Germany, Hungary, Italy, Netherlands, Portugal, Spain, Switzerland; 21,522 COVID-19-related fatalities), the summary proportions of persons < 40, 40-69, and [&ge;] 70 years of age among all COVID-19-related deaths were 0.1% (0.0-0.2%; I2 24%), 12.8% (10.3-15.6%; I2 94%), and 84.8% (81.3-88.1%; I2 96%), respectively.\n\nConclusionsPeople under 40 years of age represent a small fraction of the total number of COVID-19-related deaths in Europe. These results may help health authorities respond to public concerns and guide future physical distancing and mitigation strategies.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20062869",
+    "rel_abs": "BackgroundHigh rate of cardiovascular disease (CVD) have been reported among patients with novel coronavirus disease (COVID-19). Meanwhile there were controversies among different studies about CVD burden in COVID-19 patients. Hence, we aimed to study CVD burden among COVID-19 patients, using a systematic review and meta-analysis.\n\nMethodsWe have systematically searched databases including PubMed, Embase, Cochrane Library, Scopus, Web of Science as well as medRxiv pre-print database. Hand searched was also conducted in journal websites and Google Scholar. Meta-analyses were carried out for Odds Ratio (OR) of mortality and Intensive Care Unit (ICU) admission for different CVDs. We have also performed a descriptive meta-analysis on different CVDs.\n\nResultsFifty-six studies entered into meta-analysis for ICU admission and mortality outcome and 198 papers for descriptive outcomes, including 159,698 COVID-19 patients. Results of meta-analysis indicated that acute cardiac injury, (OR: 13.29, 95% CI 7.35-24.03), hypertension (OR: 2.60, 95% CI 2.11-3.19), heart Failure (OR: 6.72, 95% CI 3.34-13.52), arrhythmia (OR: 2.75, 95% CI 1.43-5.25), coronary artery disease (OR: 3.78, 95% CI 2.42-5.90), and cardiovascular disease (OR: 2.61, 95% CI 1.89-3.62) were significantly associated with mortality. Arrhythmia (OR: 7.03, 95% CI 2.79-17.69), acute cardiac injury (OR: 15.58, 95% CI 5.15-47.12), coronary heart disease (OR: 2.61, 95% CI 1.09-6.26), cardiovascular disease (OR: 3.11, 95% CI 1.59-6.09), and hypertension (OR: 1.95, 95% CI 1.41-2.68) were also significantly associated with ICU admission in COVID-19 patients.\n\nConclusionFindings of this study revealed a high burden of CVDs among COVID-19 patients, which was significantly associated with mortality and ICU admission. Proper management of CVD patients with COVID-19 and monitoring COVID-19 patients for acute cardiac conditions is highly recommended to prevent mortality and critical situations.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC=\"FIGDIR/small/20062869v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (22K):\norg.highwire.dtl.DTLVardef@21e53corg.highwire.dtl.DTLVardef@150dcc6org.highwire.dtl.DTLVardef@1ce7f21org.highwire.dtl.DTLVardef@1fc5fd7_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "J\u00e9r\u00e9mie F. Cohen",
-        "author_inst": "Inserm UMR 1153, Universite de Paris"
+        "author_name": "Amirhossein Hessami",
+        "author_inst": "Mazandaran University of Medical Sciences"
       },
       {
-        "author_name": "Dani\u00ebl A. Korevaar",
-        "author_inst": "Department of Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, PO Box 22700, 1100 DE, Amsterdam, The Netherlands"
+        "author_name": "Amir Shamshirian",
+        "author_inst": "Mazandaran University of Medical Sciences"
       },
       {
-        "author_name": "Soraya Matczak",
-        "author_inst": "Department of General Pediatrics and Pediatric Infectious Diseases, AP-HP, Necker Hospital for Sick Children, Universite de Paris, 75015, Paris, France"
+        "author_name": "Keyvan Heydari",
+        "author_inst": "Mazandaran University of Medical Sciences"
       },
       {
-        "author_name": "Jos\u00e9phine Brice",
-        "author_inst": "Department of General Pediatrics and Pediatric Infectious Diseases, AP-HP, Necker Hospital for Sick Children, Universite de Paris, 75015, Paris, France"
+        "author_name": "Fatemeh Pourali",
+        "author_inst": "Mazandaran University of Medical Sciences"
       },
       {
-        "author_name": "Martin Chalumeau",
-        "author_inst": "Department of General Pediatrics and Pediatric Infectious Diseases, AP-HP, Necker Hospital for Sick Children, Universite de Paris, 75015, Paris, France"
+        "author_name": "Reza Alizadeh-Navaei",
+        "author_inst": "Mazandaran University of Medical Sciences"
       },
       {
-        "author_name": "Julie Toubiana",
-        "author_inst": "Department of General Pediatrics and Pediatric Infectious Diseases, AP-HP, Necker Hospital for Sick Children, Universite de Paris, 75015, Paris, France"
+        "author_name": "Mahmood Moosazadeh",
+        "author_inst": "Mazandaran University of Medical Sciences"
+      },
+      {
+        "author_name": "Saeed Abrotan",
+        "author_inst": "Mazandaran University of Medical Sciences"
+      },
+      {
+        "author_name": "Layla Shojaei",
+        "author_inst": "University of Southern California"
+      },
+      {
+        "author_name": "Sogol Sedighi",
+        "author_inst": "Shiraz University of Medical Sciences"
+      },
+      {
+        "author_name": "Danial Shamshirian",
+        "author_inst": "Shahid Beheshti University of Medical Sciences"
+      },
+      {
+        "author_name": "Nima Rezaei",
+        "author_inst": "Tehran University of Medical Sciences"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1504331,53 +1507676,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.10.20060905",
-    "rel_title": "COVID-19: A model correlating BCG vaccination to protection from mortality implicates trained immunity",
+    "rel_doi": "10.1101/2020.04.11.20062372",
+    "rel_title": "Self-Collected Oral Fluid and Nasal Swabs Demonstrate Comparable Sensitivity to Clinician Collected Nasopharyngeal Swabs for Covid-19 Detection",
     "rel_date": "2020-04-15",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20060905",
-    "rel_abs": "O_LIWe use a data quality model to demonstrate that BCG vaccination is correlated with protection from death from COVID19\nC_LIO_LIFrom a mechanistic perspective, BCG is well described to elicit its protective non-specific effects through the process of trained immunity.\nC_LIO_LITherapeutically enhancing trained immunity may therefore be an important mechanism in protection from the lethal effects of COVID19\nC_LI",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20062372",
+    "rel_abs": "BackgroundCurrently, there is a pandemic caused by the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes Covid-19. We wanted to compare specimen types and collection methods to explore if a simpler to collect specimen type could expand access to testing.\n\nMethodsWe recruited individuals recently tested for SARS-CoV-2 infection through a \"drive-through\" testing program. In participants homes, we assessed the performance of self-collected oral fluid swab specimens with and without clinician supervision, clinician-supervised self-collected mid-turbinate (nasal) swab specimens, and clinician-collected nasopharyngeal swab specimens. We tested specimens with a validated reverse transcription-quantitative polymerase chain reaction assay for the detection of SARS-CoV-2 and measured cycle threshold values. Symptom status and date of onset of symptoms was also recorded for each participant.\n\nResultsWe recruited 45 participants. The median age of study participant was 42 years old (Interquartile range, 31 to 52 years). Of the participants, 29 had at least one specimen test positive for SARS-CoV-2. Of those, 21 (73%) of 29 reported active symptoms. By specimen type and home-based collection method, clinician-supervised self-collected oral fluid swab specimens detected 26 (90%) of 29 infected individuals, clinician-supervised self-collected nasal swab specimens detected 23 (85%) of 27, clinician-collected posterior nasopharyngeal swab specimens detected 23 (79%) of 29, and unmonitored self-collected oral fluid swab specimens detected 19 (66%) of 29. Despite nasopharyngeal swabs being considered the gold standard, 4 participants tested negative by clinician-collected nasopharyngeal swab and positive by the 3 other specimen types. Additionally, false negative results by each sample type were seen to generally not overlap.\n\nConclusionsSupervised self-collected oral fluid and nasal swab specimens performed similarly to, if not better than clinician-collected nasopharyngeal swab specimens for the detection of SARS-CoV-2 infection. No sample type captured all SARS-CoV-2 infections, suggesting potential heterogeneity in the distribution of viral load in different parts of the respiratory tract between individuals. Supervised self-collection performed comparably to clinician collection and would allow for rapid expansion of testing capacity in the United States by reducing the need for trained healthcare workers, reducing exposure of healthcare workers, and reducing the amount of PPE (personal protective equipment) being used for testing during a critical shortage.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Cameron M. Green",
-        "author_inst": "Fresh Software A.G."
-      },
-      {
-        "author_name": "Stephanie Fanucchi",
-        "author_inst": "Division of Chemical, Systems & Synthetic Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Cape Town"
-      },
-      {
-        "author_name": "Ezio T. Fok",
-        "author_inst": "Epigenomics & Single Cell Biophysics Group, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University, Nijmegen, The Netherlands"
+        "author_name": "Noah Kojima",
+        "author_inst": "UCLA"
       },
       {
-        "author_name": "Simone J.C.F.M. Moorlag",
-        "author_inst": "Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands"
+        "author_name": "Fred Turner",
+        "author_inst": "Curative Inc"
       },
       {
-        "author_name": "Jorge Dominguez-Andres",
-        "author_inst": "Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands"
+        "author_name": "Vlad Slepnev",
+        "author_inst": "Curative Inc"
       },
       {
-        "author_name": "Yutaka Negishi",
-        "author_inst": "Epigenomics & Single Cell Biophysics Group, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University, Nijmegen, The Netherlands"
+        "author_name": "Agatha Bacelar",
+        "author_inst": "Curative Inc"
       },
       {
-        "author_name": "Leo A.B. Joosten",
-        "author_inst": "Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands"
+        "author_name": "Laura Deming",
+        "author_inst": "Curative Inc"
       },
       {
-        "author_name": "Mihai G. Netea",
-        "author_inst": "Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands"
+        "author_name": "Siri Kodeboyina",
+        "author_inst": "Curative Inc"
       },
       {
-        "author_name": "Musa M. Mhlanga",
-        "author_inst": "Radboud University, Radboud Institute for Molecular Life Sciences"
+        "author_name": "Jeffrey D Klausner",
+        "author_inst": "UCLA Health"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1505889,55 +1509226,43 @@
     "category": "pathology"
   },
   {
-    "rel_doi": "10.1101/2020.04.14.041962",
-    "rel_title": "De novo 3D models of SARS-CoV-2 RNA elements and small-molecule-binding RNAs to guide drug discovery",
-    "rel_date": "2020-04-15",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.14.041962",
-    "rel_abs": "The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosettas FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5 UTR; the reverse complement of the 5 UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3 UTR. For eleven of these elements (the stems in SL1-8, reverse complement of SL1-4, FSE, s2m, and 3 UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets ( FARFAR2-SARS-CoV-2, https://github.com/DasLab/FARFAR2-SARS-CoV-2; and  FARFAR2-Apo-Riboswitch, at https://github.com/DasLab/FARFAR2-Apo-Riboswitch) include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules.",
-    "rel_num_authors": 9,
+    "rel_doi": "10.1101/2020.04.08.20058180",
+    "rel_title": "Impact of COVID-19 pandemic on severity of illness and resources required during intensive care in the greater New York City area",
+    "rel_date": "2020-04-14",
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20058180",
+    "rel_abs": "ObjectiveDescribe the changes in patient population, bed occupancy, severity of illness and ventilator requirements across a large health system in the greater New York City area during the pandemic response in comparison with the 2019 baseline.\n\nDesignObservational, descriptive study of ICUs monitored by a tele-ICU system across Northwell Health. Inclusion criteria: All patients admitted to Northwell Health tele-ICUs during 2019 and between March 23, 2020 and April 6, 2020.\n\nExposureA data extract was developed to collect data every hour for each ICU bed in the Northwell tele-critical care program as a quality reporting initiative to understand ICU capacity and resource utilization. A similar extract was developed for each hour of 2019.\n\nMain Outcomes and MeasuresAverage of any given hour during the pre-COVID-19 and pandemic periods for the following metrics: proportion of beds occupied, proportion of ventilated patients, severity of illness (measured by the ICU Discharge Readiness Score (DRS)), and length of stay (LOS).\n\nResultsHourly analysis of data from 186 ICU beds from 14 ICUs and 9 hospitals were included, representing 10,714 patients in 2019 and 465 patients between March 23 and April 6, 2020. Average hourly occupancy increased from 64% to 78%, while the proportion of patients invasively ventilated increased from 33.9% to 84.2%. Median DRS (severity of illness score) increased from 1.08 (IQR: 0.24-6.98) to 39.38 (IQR: 12.00-71.28). Proportion of patients with Hispanic ethnicity doubled (7.8% to 16.6%; p<0.01) and proportion of female patients decreased from 46.3% to 32.9% (p<0.01).\n\nConclusions and RelevanceIn addition to the expected increase in ICU occupancy and ventilator requirements, this large group of ICUs in midst of the COVID-19 epidemic are faced with managing a cohort of ICU patients with a dramatically higher severity of illness than their typical census.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Ramya Rangan",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Andrew M. Watkins",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Jose Chacon",
-        "author_inst": "Stanford University"
-      },
-      {
-        "author_name": "Wipapat Kladwang",
-        "author_inst": "Stanford University"
+        "author_name": "Omar Badawi",
+        "author_inst": "Philips Healthcare"
       },
       {
-        "author_name": "Ivan N. Zheludev",
-        "author_inst": "Stanford University"
+        "author_name": "Xinggang Liu",
+        "author_inst": "Philips Healthcare"
       },
       {
-        "author_name": "Jill Townley",
-        "author_inst": "Eterna Massive Open Laboratory"
+        "author_name": "Iris Berman",
+        "author_inst": "Northwell Health"
       },
       {
-        "author_name": "Mats Rynge",
-        "author_inst": "University of Southern California"
+        "author_name": "Pamela J Amelung",
+        "author_inst": "Philips Healthcare"
       },
       {
-        "author_name": "Gregory Thain",
-        "author_inst": "University of Wisconsin-Madison"
+        "author_name": "Martin Doerfler",
+        "author_inst": "Northwell Health"
       },
       {
-        "author_name": "Rhiju Das",
-        "author_inst": "Stanford University"
+        "author_name": "Saurabh Chandra",
+        "author_inst": "Northwell Health"
       }
     ],
     "version": "1",
-    "license": "cc_by",
-    "type": "new results",
-    "category": "biochemistry"
+    "license": "cc_by_nc_nd",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "intensive care and critical care medicine"
   },
   {
     "rel_doi": "10.1101/2020.04.09.20059634",
@@ -1507031,31 +1510356,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.10.20060616",
-    "rel_title": "Chaos, Percolation and the Coronavirus Spread: the Italian case",
+    "rel_doi": "10.1101/2020.04.10.20060673",
+    "rel_title": "COVID-19 lockdowns cause global air pollution declines with implications for public health risk",
     "rel_date": "2020-04-14",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20060616",
-    "rel_abs": "A model based on chaotic maps and turbulent flows is applied to the spread of Coronavirus for each Italian region in order to obtain useful information and help to contrast it. We divide the regions into different risk categories and discuss anomalies. The worst cases are confined between the Appenine and the Alps mountain ranges but the situation seem to improve closer to the sea. The Veneto region gave the most efficient response so far and some of their resources could be diverted to other regions, in particular more tests to the Lombardia, Liguria, Piemonte, Marche and V. Aosta regions, which seem to be worst affected. We noticed worrying anomalies in the Lazio, Campania and Sicilia regions to be monitored. We stress that the number of fatalities we predicted on March 12 has been confirmed daily by the bulletins. This suggests a change of strategy in order to reduce such number maybe moving the weaker population (and negative to the virus test) to beach resorts, which should be empty presently. The ratio deceased/positives on April 4, 2020 is 5.4% worldwide, 12.3% in Italy, 1.4% in Germany, 2.7% in the USA, 10.3% in the UK and 4.1% in China. These large fluctuations should be investigated starting from the Italian regions, which show similar large fluctuations.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20060673",
+    "rel_abs": "The lockdown response to COVID-19 has caused an unprecedented reduction in global economic activity. We test the hypothesis that this has reduced tropospheric and ground-level air pollution concentrations using satellite data and a network of >10,000 air quality stations. After accounting for the effects of meteorological variability, we find remarkable declines in ground-level nitrogen dioxide (NO2: -29 % with 95% confidence interval -44% to -13%), ozone (O3: -11%; -20% to -2%) and fine particulate matter (PM2.5: -9%; -28% to 10%) during the first two weeks of lockdown (n = 27 countries). These results are largely mirrored by satellite measures of the troposphere although long-distance transport of PM2.5 resulted in more heterogeneous changes relative to NO2. Pollutant anomalies were related to short-term health outcomes using empirical exposure-response functions. We estimate that there was a net total of 7400 (340 to 14600) premature deaths and 6600 (4900 to 7900) pediatric asthma cases avoided during two weeks post-lockdown. In China and India alone, the PM2.5-related avoided premature mortality was 1400 (1100 to 1700) and 5300 (1000 to 11700), respectively. Assuming that the lockdown-induced deviations in pollutant concentrations are maintained for the duration of 2020, we estimate 0.78 (0.09 to 1.5) million premature deaths and 1.6 (0.8 to 2) million pediatric asthma cases could be avoided globally. While the state of global lockdown is not sustainable, these findings illustrate the potential health benefits gained from reducing \"business as usual\" air pollutant emissions from economic activities. Explore trends here: www.covid-19-pollution.zsv.co.za\n\nSignificance statementThe global response to the COVID-19 pandemic has resulted in unprecedented reductions in economic activity. We find that lockdown events have reduced air pollution levels by approximately 20% across 27 countries. The reduced air pollution levels come with a substantial health co-benefit in terms of avoided premature deaths and pediatric asthma cases that accompanied the COVID-19 containment measures.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Aldo Bonasera",
-        "author_inst": "Texas A&M University"
+        "author_name": "Zander S Venter",
+        "author_inst": "Norwegian Institute for Nature Research"
       },
       {
-        "author_name": "Giacomo Bonasera",
-        "author_inst": "Texas A&M University"
+        "author_name": "Kristin Aunan",
+        "author_inst": "CICERO Center for International Climate Research"
       },
       {
-        "author_name": "Suylatu Zhang",
-        "author_inst": "Inner Mongolia University"
+        "author_name": "Sourangsu Chowdhury",
+        "author_inst": "Max Planck Institute for Chemistry"
+      },
+      {
+        "author_name": "Jos Lelieveld",
+        "author_inst": "Max Planck Institute for Chemistry"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.04.10.20060681",
@@ -1508441,23 +1511770,107 @@
     "category": "evolutionary biology"
   },
   {
-    "rel_doi": "10.1101/2020.04.11.20061432",
-    "rel_title": "Application of COVID-19 pneumonia diffusion data to predict epidemic situation",
+    "rel_doi": "10.1101/2020.04.12.037580",
+    "rel_title": "Single Nucleus Multiomic Profiling Reveals Age-Dynamic Regulation of Host Genes Associated with SARS-CoV-2 Infection",
     "rel_date": "2020-04-14",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20061432",
-    "rel_abs": "ObjectiveTo evaluate novel coronavirus pneumonia cases by establishing the mathematical model of the number of confirmed cases daily, and to assess the current situation and development of the epidemic situation, so as to provide a digital basis for decision-making.\n\nMethodsThe number of newly confirmed covid-19 cases per day was taken as the research object, and the seven-day average value (M) and the sequential value (R) of M were calculated to study the occurrence and development of covid-19 epidemic through the analysis of charts and data.\n\nResultsM reflected the current situation of epidemic development; R reflected the current level of infection and the trend of epidemic development.\n\nConclusionThe current data can be used to evaluate the number of people who have been infected, and when R < 1, the peak of epidemic can be predicted.\n\nPrefaceIn December 2019, a number of cases of pneumonia with unknown causes were found in some hospitals in Wuhan, Hubei province, China. On 11 March 2020, the director-general of the world health organization (WHO), Tedros Adhanom Ghebreyesus, announced that based on the assessment, WHO believes that the current outbreak of COVID-19 can be called a global pandemic. By early April 2020, there were more than one million confirmed cases worldwide.\n\nCOVID-19 has developed from sporadic cases to pandemic in a short period of 3 months. The analysis and research of its infectious data will help to prevent and control the next stage of epidemic prevention and other infectious diseases in the future.\n\nIn this paper, COVID-19 rounded average of seven days (M), and Ms ring ratio (R) are used to predict the current potential patients data, and the relative state of epidemic prevention and control is judged through the graphic features and characteristic data, so as to provide evidence for the prevention and control decisions.",
-    "rel_num_authors": 1,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.12.037580",
+    "rel_abs": "Respiratory failure is the leading cause of COVID-19 death and disproportionately impacts adults more than children. Here, we present a large-scale snATAC-seq dataset (90,980 nuclei) of the human lung, generated in parallel with snRNA-seq (46,500 nuclei), from healthy donors of ~30 weeks, ~3 years and ~30 years of age. Focusing on genes implicated in SARS-CoV-2 cell entry, we observed an increase in the proportion of alveolar epithelial cells expressing ACE2 and TMPRSS2 in adult compared to young lungs. Consistent with expression dynamics, 10 chromatin peaks linked to TMPRSS2 exhibited significantly increased activity with age and harbored IRF and STAT binding sites. Furthermore, we identified 14 common sequence variants in age-increasing peaks with predicted regulatory function, including several associated with respiratory traits and TMPRSS2 expression. Our findings reveal a plausible contributor to why children are more resistant to COVID-19 and provide an epigenomic basis for transferring this resistance to older populations.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Zhenguo Wu",
-        "author_inst": "Xi'an Jioatong University"
+        "author_name": "Allen Wang",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Joshua A Chiou",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Olivier B Poirion",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Justin Buchanan",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Michael J Valdez",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Jamie M Verheyden",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Xiaomeng Hou",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Jacklyn M Newsome",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Parul Kudtarkar",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Dina A Faddah",
+        "author_inst": "Vertex Phamaceuticals"
+      },
+      {
+        "author_name": "Kai Zhang",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Randee E Young",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Justinn Barr",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Ravi Misra",
+        "author_inst": "University of Rochester Medical Center"
+      },
+      {
+        "author_name": "Heidie Huyck",
+        "author_inst": "University of Rochester Medical Center"
+      },
+      {
+        "author_name": "Lisa Rogers",
+        "author_inst": "University of Rochester Medical Center"
+      },
+      {
+        "author_name": "Cory Poole",
+        "author_inst": "University of Rochester Medical Center"
+      },
+      {
+        "author_name": "Gloria Pryhuber",
+        "author_inst": "University of Rochester Medical Center"
+      },
+      {
+        "author_name": "Kyle J Gaulton",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Sebastian Preissl",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "Xin Sun",
+        "author_inst": "University of California San Diego"
+      },
+      {
+        "author_name": "- NHLBI LungMap Consortium",
+        "author_inst": "-"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "genomics"
   },
   {
     "rel_doi": "10.1101/2020.04.10.20060442",
@@ -1509827,23 +1513240,23 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.04.10.036533",
-    "rel_title": "Structural interactions between pandemic SARS-CoV-2 spike glycoprotein and human Furin protease",
+    "rel_doi": "10.1101/2020.04.10.036020",
+    "rel_title": "Analysis of Ten Microsecond simulation data of SARS-CoV-2 dimeric main protease",
     "rel_date": "2020-04-12",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.10.036533",
-    "rel_abs": "The SARS-CoV-2 pandemic is an urgent global public health emergency and warrants investigating molecular and structural studies addressing the dynamics of viral proteins involved in host cell adhesion. The recent comparative genomic studies highlight the insertion of Furin protease site in the SARS-CoV-2 spike glycoprotein alerting possible modification in the viral spike protein and its eventual entry to host cell and presence of Furin site implicated to virulence. Here we structurally show how Furin interacts with the SARS-CoV-2 spike glycoprotein homotrimer at S1/S2 region, which underlined the mechanism and mode of action, which is a key for host cell entry. Unravelling the structural features of biding site opens the arena in rising bonafide antibodies targeting to block the Furin cleavage and have great implications in the development of Furin inhibitors or therapeutics.",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.10.036020",
+    "rel_abs": "The dimeric main protease of SARS-CoV-2, has become a crucial target for inhibiting/modulating its catalytic activity. However, understanding of its conformational change, and atomistic flexibility, is very much lucrative for designing/developing small molecules. Fortunately, huge data has been revealed by a research group, performed about ten-microsecond molecular dynamics to paving the way for understanding the structural complexity of protease. Herein, we have done the basic structural analysis, advanced flexibility and conformational analysis like PCA, for revealing out the regions and residues, which are mostly flexible and likely to be responsible for different conformation of protease protein.",
     "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Naveen Vankadari",
-        "author_inst": "Monash University"
+        "author_name": "Rimon Parves",
+        "author_inst": "University of Science and Technology, Chittagong"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "bioinformatics"
   },
   {
     "rel_doi": "10.1101/2020.04.10.036418",
@@ -1511233,21 +1514646,25 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.04.08.20054023",
-    "rel_title": "There are asymptomatic and pre-symptomatic patients infected with COVID-19. So what? Pandemic response implications",
+    "rel_doi": "10.1101/2020.04.09.20059014",
+    "rel_title": "How much India detecting SARS-CoV-2 Infections? A model-based estimation",
     "rel_date": "2020-04-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20054023",
-    "rel_abs": "Asymptomatic but infectious people have been reported in many infectious diseases. Asymptomatic and pre-symptomatic carriers would be a hidden reservoir of COVID-19.\n\nAimThis review identifies primary empirical evidence about the ability of asymptomatic carriers to infect others with COVID-19 pandemic and reflects on the implications for control measures.\n\nMethodsA systematic review is followed by a narrative report and commentary inclusion criteria were: studies reporting primary data on asymptomatic or pre-symptomatic patients, who were considered to have passed on COVID-19 infection; and published in indexed journals or in peer review between January 1 and March 31, 2020.\n\nResultsNine articles reported on 83 asymptomatic or pre-symptomatic persons.\n\nConclusionsThe evidence confirms COVID-19 transmission from people who were asymptomatic at the time. A series of implications for health service response are laid out.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059014",
+    "rel_abs": "Background and RationaleAmid SARS-CoV-2 outbreak, the low number of infections for a population size of 1.38 billion is widely discussed, but with no definite answers.\n\nMethodsWe used the model proposed by Bommer and Vollmer to assess the quality of official case records. The infection fatality rates were taken from Verity et al (2020). Age distribution of the population for India and states are taken from the Census of India (2011). Reported number of deaths and SARS-CoV-2 confirmed cases from https://www.covid19india.org. The reported numbers of samples tests were collected from the reports of the Indian Council for Medical Research (ICMR).\n\nResultsThe findings suggest that India is detecting just 3.6% of the total number of infections with a huge variation across its states. Among 13 states which have more than 100 COVID-19 cases, the detection rate varies from 81.9% (of 410 estimated infections) in Kerala to 0.8% (of 35487 estimated infections) in Madhya Pradesh and 2.4% (of 7431 estimated infections) in Gujarat.\n\nConclusionAs the study reports a lower number of deaths and higher recovery rates in the states with a high detection rate, thus suggest that India must enhance its testing capacity and go for widespread testing. Late detection puts patients in greater need of mechanical ventilation and ICU care, which imposes greater costs on the health system. The country should also adopt population-level random testing to assess the prevalence of the infection.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Nelson Aguirre-Duarte",
-        "author_inst": "The University of Auckland"
+        "author_name": "Srinivas Goli",
+        "author_inst": "The University of Western Australia"
+      },
+      {
+        "author_name": "K.S. James",
+        "author_inst": "International Institute for Population Sciences (IIPS)"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1512499,35 +1515916,55 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.08.20057851",
-    "rel_title": "Age-stratified Infection Probabilities Combined with Quarantine-Modified SEIR Model in the Needs Assessments for COVID-19",
+    "rel_doi": "10.1101/2020.04.08.20058040",
+    "rel_title": "Blood glucose is a representative of the clustered indicators of multi-organ injury for predicting mortality of COVID-19 in Wuhan, China",
     "rel_date": "2020-04-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20057851",
-    "rel_abs": "We use the age-stratified COVID-19 infection and death distributions from China (more than 44,672 infectious as of February 11, 2020) as an estimate for a study areas infection and morbidity probabilities at each age group. We then apply these probabilities into the actual age-stratified population to predict infectious individuals and deaths at peak. Testing with different countries shows the predicted infectious skewing with the countrys median age and age stratification, as expected. We added a Q parameter to the classic SEIR compartmental model to include the effect of quarantine (Q-SEIR). The projections from the age-stratified probabilities give much lower predicted incidences of infection than the Q-SEIR model. As expected, quarantine tends to delay the peaks for both Exposed and Infectious, and to  flatten the curve or lower the predicted values for each compartment. These two estimates were used as a range to inform planning and response to the COVID-19 threat.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20058040",
+    "rel_abs": "BackgroundConcomitance with diabetes is associated with high mortality in critical conditions. Patients with previous diabetes are more vulnerable to COVID-19. However, new-onset COVID-19-related diabetes (CRD) and its relevance have scarcely been reported. This study investigates new-onset CRD and its correlation with poor outcomes or death in patients with COVID-19.\n\nMethodsWe performed a single center, retrospective case series study in 120 patients with laboratory confirmed COVID-19 at a university hospital. Fasting blood glucose (FBG) [&ge;]7.0 mmol/L for two times during hospitalization and without a history of diabetes were defined as CRD. The Critical status was defined as admitted to intensive care unit (ICU) or death.\n\nResultsAfter excluding patients with a history of diabetes, chronic heart, kidney, and liver disease, 69 patients with COVID-19 were included in the final analysis. Of the 69 patients, 23 were Moderate, 20 were Severe, and 26 were Critical (including 16 deceased patients). The prevalence of CRD in Critical and Moderate+Severe patients was 53.85% and 13.95%, respectively. Kaplan-Meier survival analysis revealed a significantly higher mortality rate in patients with CRD (P=0.0019). Multivariable analysis indicated that CRD was an independent predictor for death (HR = 3.75, 95% CI 1.26-11.15). Cluster analysis suggested that indicators for multi-organ injury were interdependent, and more proximities of FBG with indicators for multi-organ injury was present.\n\nConclusionOur results suggest that new onset COVID-19-related diabetes is an indicator of multi-organ injury and predictor for poor outcomes and death in COVID- 19 patients. As it is easy to perform for clinical practices and even self-monitoring, glucose testing will be much helpful for predicting poor outcomes to facilitate appropriate intensive care in patients with COVID-19.\n\nFundingNational Key Research and Development Program of China; The Beijing Science and Technology Project.\n\nSignificance of this studyO_ST_ABSEvidence before this studyC_ST_ABSConcomitance with diabetes is associated with high mortality in critical conditions. Patients with previous diabetes are more vulnerable to COVID-19. However, new-onset COVID-19-related diabetes (CRD) and its relevance have scarcely been reported. Recently, an international group of leading diabetes researchers participating in the CoviDIAB Project have established a global registry of patients with Covid-19-related diabetes (covidiab.e-dendrite.com).\n\nAdded value of this study?New-onset diabetes in COVID-19 defined as CRD was investigated. Correlation between CRD and poor outcomes or death in patients with COVID-19 was found. About half of the Critical patients have new onset CRD. CRD is the representative of the clustered indicators of multi-organ injury and is the predictor for poor outcomes and death.\n\nHow might these results change the focus of research or clinical practice?Our results suggest that new onset diabetes is an indicator of multi-organ injury and predictor for poor outcomes and death in COVID-19 patients. The study of CRD may also uncover novel mechanisms of disease.",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Vena Pearl Bongolan",
-        "author_inst": "Department of Computer Science, UP Diliman, Philippines"
+        "author_name": "Jin-Kui Yang",
+        "author_inst": "Beijing Tongren Hospital, Capital Medical University"
       },
       {
-        "author_name": "Jose Marie Antonio Minoza",
-        "author_inst": "Department of Computer Science, UP Diliman, Philippines"
+        "author_name": "Jian-Min Jin",
+        "author_inst": "Beijing Tongren Hospital"
       },
       {
-        "author_name": "Romulo de Castro",
-        "author_inst": "Center for Informatics, University of San Agustin, Iloilo City, Philippines"
+        "author_name": "Shi Liu",
+        "author_inst": "Wuhan Union Hospital"
       },
       {
-        "author_name": "Jesus Emmanuel Sevilleja",
-        "author_inst": "National Center for Mental Health, Mandaluyong City, Philippines"
+        "author_name": "Peng Bai",
+        "author_inst": "Beijing Tongren Hospital"
+      },
+      {
+        "author_name": "Wei He",
+        "author_inst": "Beijing Tongren Hospital"
+      },
+      {
+        "author_name": "Fei Wu",
+        "author_inst": "Wuhan Union Hospital"
+      },
+      {
+        "author_name": "Xiao-Fang Liu",
+        "author_inst": "Beijing Tongren Hospital"
+      },
+      {
+        "author_name": "Zhong-Lin Chai",
+        "author_inst": "Monash University"
+      },
+      {
+        "author_name": "De-Min Han",
+        "author_inst": "Beijing Tongren Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.04.09.034967",
@@ -1513688,31 +1517125,43 @@
     "category": "occupational and environmental health"
   },
   {
-    "rel_doi": "10.1101/2020.04.08.20057679",
-    "rel_title": "COVID-19 Epidemic Analysis using Machine Learning and Deep Learning Algorithms",
+    "rel_doi": "10.1101/2020.04.07.20057224",
+    "rel_title": "UV light dosage distribution over irregular respirator surfaces. Methods and implications for safety",
     "rel_date": "2020-04-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20057679",
-    "rel_abs": "The catastrophic outbreak of Severe Acute Respiratory Syndrome - Coronavirus (SARS-CoV-2) also known as COVID-2019 has brought the worldwide threat to the living society. The whole world is putting incredible efforts to fight against the spread of this deadly disease in terms of infrastructure, finance, data sources, protective gears, life-risk treatments and several other resources. The artificial intelligence researchers are focusing their expertise knowledge to develop mathematical models for analyzing this epidemic situation using nationwide shared data. To contribute towards the well-being of living society, this article proposes to utilize the machine learning and deep learning models with the aim for understanding its everyday exponential behaviour along with the prediction of future reachability of the COVID-2019 across the nations by utilizing the real-time information from the Johns Hopkins dashboard.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20057224",
+    "rel_abs": "Background and ObjectivesThe SARS-CoV-2 pandemic has led to a global decrease in personal protective equipment (PPE), especially filtering facepiece respirators (FFRs). Ultraviolet-C wavelength is a promising way of decontamination, however adequate dosimetry is needed to ensure balance between over and underexposed areas and provide reliable results. Our study demonstrates that UVGI light irradiance varies significantly on different respirator angles and propose a method to decontaminate several masks at once ensuring appropriate dosage in shaded zones.\n\nMethodsAn UVGI irradiator was built with internal dimensions of 69.5 x 55 x 33 cm with three 15W UV lamps. Inside, a grating of 58 x 41 x 15 cm was placed to hold the masks. Two different flat fold respirator models were used to assess irradiance, four of model Aura 9322 3M of dimensions 17 x 9 x 4cm (tri-fold), and two of model SAFE 231FFP3NR (bi-fold) with dimensions 17 x 6 x 5 cm. A spectrometer STN-SilverNova was employed to verify wavelength spectrum and surface irradiance. A simulation was performed to find the irradiance pattern inside the box and the six masks placed inside. These simulations were carried out using the software DIALUX EVO 8.2.\n\nResultsThe data obtained reveal that the irradiance received inside the manufactured UVGI-irradiator depends not only on the distance between the lamps plane and the base of the respirators but also on the orientation and shape of the masks. This point becomes relevant in order to assure that all the respirators inside the chamber receive the correct dosage.\n\nConclusionIrradiance over FFR surfaces depend on several factors such as distance and angle of incidence of the light source. Careful irradiance measurement and simulation can ensure reliable dosage in the whole mask surface, balancing overexposure. Closed box systems might provide a more reliable, reproducible UVGI dosage than open settings.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Narinder Singh Punn",
-        "author_inst": "Indian Institute of Information Technology Allahabad"
+        "author_name": "Aurora Baluja",
+        "author_inst": "Department of Anesthesiology and Critical Care. FIDIS Health Research Institute. Hospital Clinico Universitario de Santiago de Compostela"
       },
       {
-        "author_name": "Sanjay Kumar Sonbhadra",
-        "author_inst": "Indian Institute of Information Technology Allahabad"
+        "author_name": "Justo Arines",
+        "author_inst": "Photonics4Life research group, Optics Area, Department of Applied Physics, Universidade de Santiago de Compostela"
       },
       {
-        "author_name": "Sonali Agarwal",
-        "author_inst": "Indian Institute of Information Technology Allahabad"
+        "author_name": "Ramon Vilanova",
+        "author_inst": "Iberman Group. University Hospital. Santiago de Compostela. Spain"
+      },
+      {
+        "author_name": "Julio Corti\u00f1as",
+        "author_inst": "Department of Anaesthesiology and Critical Care. Hospital Clinico Universitario. FIDIS Health Research Institute. Santiago de Compostela, Spain"
+      },
+      {
+        "author_name": "Carmen Bao-Varela",
+        "author_inst": "Photonics4Life research group, Optics Area, Department of Applied Physics, Universidade de Santiago de Compostela"
+      },
+      {
+        "author_name": "Maria Teresa Flores-Arias",
+        "author_inst": "Photonics4Life research group, Optics Area, Department of Applied Physics, Universidade de Santiago de Compostela"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health informatics"
+    "category": "health policy"
   },
   {
     "rel_doi": "10.1101/2020.04.08.20057984",
@@ -1514858,37 +1518307,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.09.20056291",
-    "rel_title": "Risk factors for mortality of adult inpatients with Coronavirus disease 2019 (COVID-19): a systematic review and meta-analysis of retrospective studies",
+    "rel_doi": "10.1101/2020.04.07.20055723",
+    "rel_title": "SARS-CoV-2 infection in Health Care Workers in a large public hospital in Madrid, Spain, during March 2020",
     "rel_date": "2020-04-11",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20056291",
-    "rel_abs": "PurposeCoronavirus disease 2019 (COVID-19) is an emerging disease that was first reported in Wuhan city, the capital of Hubei province in China, and has subsequently spread worldwide. Risk factors for mortality have not been well summarized. Current meta-analysis of retrospective cohort studies was done to summarize available findings on the association between age, gender, comorbidities and risk of death from COVID-19 infection.\n\nMethodsOnline databases including Web of Science, PubMed, Scopus, Cochrane Library and Google scholar were searched to detect relevant publications up to 1 May 2020, using relevant keywords. To pool data, random-effects model was used. Furthermore, sensitivity analysis and publication bias test were also done.\n\nResultsIn total, 14 studies with 29,909 COVID-19 infected patients and 1,445 cases of death were included in the current meta-analysis. Significant associations were found between older age ([&ge;]65 vs <65 years old) (pooled ORs=4.59, 95% CIs=2.61-8.04, p<0.001), gender (male vs female) (pooled ORs=1.50, 95% CIs=1.06-2.12, p=0.021) and risk of death from COVID-19 infection. In addition, hypertension (pooled ORs=2.70, 95% CIs= 1.40-5.24, p=0.003), cardiovascular diseases (CVDs) (pooled ORs=3.72, 95% CIs=1.77-7.83, p=0.001), diabetes (pooled ORs=2.41, 95% CIs=1.05-5.51, p=0.037), chronic obstructive pulmonary disease (COPD) (pooled ORs=3.53, 95% CIs=1.79-6.96, p<0.001) and cancer (pooled ORs=3.04, 95% CIs=1.80-5.14, p<0.001), were associated with higher risk of mortality.\n\nConclusionOlder age ([&ge;]65 years old), male gender, hypertension, CVDs, diabetes, COPD and malignancies were associated with greater risk of death from COVID-19 infection. These findings could help clinicians to identify patients with poor prognosis at an early stage.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20055723",
+    "rel_abs": "BackgroundOn January 31st the first case of COVID-19 was detected in Spain, an imported case from Germany in Canary Islands, and thereafter on February 25th the first case was detected in Madrid. The first case of COVID-19 was confirmed at the Hospital Universitario 12 de Octubre on March 1st, a large public hospital with 1200 beds, covering an area over 400000 inhabitants in southern Madrid. During March 2020 highly active circulation of SARS-CoV-2 was experienced in Madrid with 24090 cases officially reported by March 29th.\n\nMethodsSince the beginning of the epidemics the Occupational Health and Safety Service (OHSS) organized the consulting and testing of the hospital personnel with confirmed exposure and also those presenting symptoms suggestive of viral respiratory infection. For molecular diagnosis of SARS-CoV-2 infection both nasopharyngeal and oropharyngeal swabs were obtained from suspected cases and processed at the Microbiology Laboratory by automatized specific PCR methods that was operative from February 25th as part of the preparedness.\n\nResultsFrom a total of 6800 employees of the hospital, 2085 (30,6 %) were tested during the period 1-29 March 2020, some of them repeatedly (2286 total samples). The first HCW infected was confirmed on March 9th. A total of 791 HCW and personnel were confirmed to be infected by March 29th, representing 38% of those tested and 11,6 % of all the hospital workers. The proportion of infected individuals was estimated among the different groups of occupational exposure and the evolution of the cases during the expansive epidemic wave was compared between HCW and those patients attending at the Emergency Department (ER) during the same period and adjusted by the same age range. There were no statistically significant differences in the proportion of SARS- CoV-2 positive PCR detection between HCW from high risk areas involved in close contact with COVID-19 patients in comparison with clerical, administrative or laboratory personnel without direct contact with patients. The curves of evolution of accumulated cases between patients and HCW during March 2020 showed an almost parallel shape.\n\nDiscussionThe recommendation from our OHSS did not include testing of asymptomatic cases but was highly proactive in testing even patients with minor symptoms therefore, a high proportion of HCW and non-sanitary personnel was tested in March 2020 during the rapid period of expansion of the epidemics in Madrid, accounting for a total of 30,6 % of the hospital employees. Most of the COVID-19 cases among the hospital HCW and personnel were mild and managed at home under self-isolation measures, however 23 (3%) required hospitalization mostly due to severe bilateral interstitial pneumonia, two of those cases required mechanical ventilation at the ICU. No fatalities occurred during the study period.\n\nAlthough there were some cases of highly probable transmission from COVID-19 patients to HCWs, mainly at the first phase of the epidemics, there were no significant differences on the infection rates of HCW and hospital personnel that can be related to working in areas of high exposure risk. Furthermore, the evolution of cases during the same time period (March 2020) between patients attending the ER and hospital staff suggests that both groups were driven by the same dynamics. This experience is similar to the communicated from Wuhan verified by the WHO Joint Mission and also from recent experiences at hospital in the Netherlands, where most of the infections of HCW were related to household or community contacts.\n\nSignificanceSince the collective of hospital HCW are exhaustively screened in specific centers, their rate of infection for SARS-CoV-2 could be an indicator of the epidemic dynamics in the community. There appears to be a close connection between HCW infection and the driving forces of transmission in the community. Although we cannot exclude an additional risk factor of infection by SARS-CoV-2 due to the fact of the hospital environment, the similar proportions of positive cases among all the areas of the hospital and the evolutive wave of infection, as compared with the community, are clear arguments against a major factor of occupational risk. Exhaustive testing, such as the one carried out in our institution, covering over one third of all the workers, could be used as a reference of the population infected in the community. Since a significant proportion of COVID-19 cases can be asymptomatic and not all the hospital employees were actually tested, it is highly likely that this 11,6 % is a minimum estimation of the impact of SARS-CoV-2 circulation in Madrid during the first 4 weeks of the epidemics. This is in high and clear contrast with the official figures circulating at national and international levels. This has important implications to more precisely estimate the actual number of cases in the community and to develop public health policies for containment, treatment and recovery.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Mohammad Parohan",
-        "author_inst": "Tehran University of Medical Sciences"
-      },
-      {
-        "author_name": "Sajad Yaghoubi",
-        "author_inst": "Iranshahr University of Medical Sciences"
-      },
-      {
-        "author_name": "Asal Seraji",
-        "author_inst": "Islamic Azad University, Damavand Branch"
+        "author_name": "Maria Dolores Folgueira",
+        "author_inst": "Hospital Universitario 12 de Octubre, Madrid, Spain"
       },
       {
-        "author_name": "Mohammad Hassan Javanbakht",
-        "author_inst": "Tehran University of Medical Sciences"
+        "author_name": "Carmen Munoz-Ruiperez",
+        "author_inst": "Hospital Universitario 12 de Octubre, Madrid, Spain"
       },
       {
-        "author_name": "Payam Sarraf",
-        "author_inst": "Tehran University of Medical Sciences"
+        "author_name": "Miguel Angel Alonso-Lopez",
+        "author_inst": "Hospital Universitario 12 de Octubre, Madrid, Spain"
       },
       {
-        "author_name": "Mahmoud Djalali",
-        "author_inst": "Tehran University of Medical Sciences"
+        "author_name": "Rafael Delgado",
+        "author_inst": "Hospital Universitario 12 de Octubre, Madrid, Spain"
       }
     ],
     "version": "1",
@@ -1516160,35 +1519601,39 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.09.033522",
-    "rel_title": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) envelope (E) protein harbors a conserved BH3-like motif",
+    "rel_doi": "10.1101/2020.04.07.20057315",
+    "rel_title": "Clinical analysis and early differential diagnosis of suspected pediatric patients with 2019 novel coronavirus infection",
     "rel_date": "2020-04-10",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.09.033522",
-    "rel_abs": "Disclaimer textThe authors have withdrawn their manuscript whilst they perform additional experiments to test some of their conclusions further. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.",
-    "rel_num_authors": 4,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20057315",
+    "rel_abs": "BackgroundWe aimed to identify clinical features of coronavirus disease 2019 (COVID-19) in children and evaluate the role of procalcitonin in early differential diagnosis.\n\nMethodsA retrospective analysis was performed on all suspected pediatric cases.\n\nResults39 (50.6%) of 77 suspected cases were comfirmed, 4 (5.2%) of them had viral coinfection. Compared with non-COVID-19 group (n=33), COVID-19 confirmed group (n=39) had fewer fever(OR[95% CI]0.467[0.314-0.694]; P=.000) and symptoms of acute respiratory infection (0.533[0.36-0.788]; P=.001), more asymptomatic (13.568[1.895-96.729]; P=.000), and more family cluster infections (5.077[2.224-11.591]; P=.000), while computed tomography had more positive findings of viral pneumonia (1.822[1.143-2.906]; P=.008). Age (6.9[3.6-10.5] vs 5[2.1-7.6]; P=. 088) and gender were statistically insignificant. Procalcitonin (0.05[0.029-0.076] vs 0.103[0.053-0.21]; P= 000) of COVID-19 alone group (n=35) was significantly reduced. While compared with coinfection group (n=4), procalcitonin (0.05[0.029-0.076] vs 0.144[0.109-2.26]; P=.010) was also reduced. The area under curve of model is 0.834 ([95% CI][0.741-0.926]; P=.000). Procalcitonin as a differential indicator of COVID-19 alone, its area under curve is 0.809 ([0.710-0.909]; P=.000). The optimal cut-off value is 0.1 ng/mL, the sensitivity, specificity, positive and negative predictive value of differentiating are 65.9%, 78.6%, 82.9%, and 59.2%, respectively.\n\nConclusionsAsymptoms or mild symptoms, positive computed tomography findings and family cluster infection are the main clinical features of COVID-19 in children. With good performance, procalcitonin can provide an important basis for differentiating COVID-19 alone and other viral infection or viral coinfection.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Vincent Navratil",
-        "author_inst": "PRABI, Rhone Alpes Bioinformatics Center, UCBL, Lyon1, Universite de Lyon, Lyon, France"
+        "author_name": "Denggao Peng",
+        "author_inst": "The Third People's Hospital of Shenzhen"
+      },
+      {
+        "author_name": "Jing Zhang",
+        "author_inst": "The Third People's Hospital of Shenzhen"
       },
       {
-        "author_name": "Sonia Longhi",
-        "author_inst": "AFMB lab, CNRS & Aix-Marseille University"
+        "author_name": "Yingqi Xu",
+        "author_inst": "The Third People's Hospital of Shenzhen"
       },
       {
-        "author_name": "Marie Hardwick",
-        "author_inst": "W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland 21205, U"
+        "author_name": "Zhichao Liu",
+        "author_inst": "The Third People's Hospital of Shenzhen"
       },
       {
-        "author_name": "Christophe Combet",
-        "author_inst": "Centre de Recherche en Cancerologie de Lyon, UMR Inserm U1052, CNRS 5286, Universite Claude Bernard Lyon 1, Centre Leon Berard, Lyon, France"
+        "author_name": "Pengyao Wu",
+        "author_inst": "The Third People's Hospital of Shenzhen"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "new results",
-    "category": "microbiology"
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "pediatrics"
   },
   {
     "rel_doi": "10.1101/2020.04.08.013516",
@@ -1517786,119 +1521231,43 @@
     "category": "biophysics"
   },
   {
-    "rel_doi": "10.1101/2020.04.07.023903",
-    "rel_title": "Structural and functional analysis of a potent sarbecovirus neutralizing antibody",
+    "rel_doi": "10.1101/2020.04.07.028589",
+    "rel_title": "The IMPDH inhibitor merimepodib suppresses SARS-CoV-2 replication in vitro.",
     "rel_date": "2020-04-09",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.07.023903",
-    "rel_abs": "SARS-CoV-2 is a newly emerged coronavirus responsible for the current COVID-19 pandemic that has resulted in more than one million infections and 73,000 deaths1,2. Vaccine and therapeutic discovery efforts are paramount to curb the pandemic spread of this zoonotic virus. The SARS-CoV-2 spike (S) glycoprotein promotes entry into host cells and is the main target of neutralizing antibodies. Here we describe multiple monoclonal antibodies targeting SARS-CoV-2 S identified from memory B cells of a SARS survivor infected in 2003. One antibody, named S309, potently neutralizes SARS-CoV-2 and SARS-CoV pseudoviruses as well as authentic SARS-CoV-2 by engaging the S receptor-binding domain. Using cryo-electron microscopy and binding assays, we show that S309 recognizes a glycan-containing epitope that is conserved within the sarbecovirus subgenus, without competing with receptor attachment. Antibody cocktails including S309 along with other antibodies identified here further enhanced SARS-CoV-2 neutralization and may limit the emergence of neutralization-escape mutants. These results pave the way for using S309 and S309-containing antibody cocktails for prophylaxis in individuals at high risk of exposure or as a post-exposure therapy to limit or treat severe disease.",
-    "rel_num_authors": 25,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.07.028589",
+    "rel_abs": "The ongoing COVID-19 pandemic continues to pose a major public health burden around the world. The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected over one million people worldwide as of April, 2020, and has led to the deaths of nearly 300,000 people. No approved vaccines or treatments in the USA currently exist for COVID-19, so there is an urgent need to develop effective countermeasures. The IMPDH inhibitor merimepodib (MMPD) is an investigational antiviral drug that acts as a noncompetitive inhibitor of IMPDH. It has been demonstrated to suppress replication of a variety of emerging RNA viruses. We report here that MMPD suppresses SARS-CoV-2 replication in vitro. After overnight pretreatment of Vero cells with 10 M of MMPD, viral titers were reduced by 4 logs of magnitude, while pretreatment for 4 hours resulted in a 3-log drop. The effect is dose-dependent, and concentrations as low as 3.3 M significantly reduced viral titers when the cells were pretreated prior to infection. The results of this study provide evidence that MMPD may be a viable treatment option for COVID-19.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Dora Pinto",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Young-Jun Park",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Martina Beltramello",
-        "author_inst": "Humabs BioMed SA"
-      },
-      {
-        "author_name": "Alexandra C. Walls",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "M. Alejandra Tortorici",
-        "author_inst": "University of Washington"
-      },
-      {
-        "author_name": "Siro Bianchi",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Stefano Jaconi",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Katja Culap",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Fabrizia Zatta",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Anna De Marco",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Alessia Peter",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Barbara Guarino",
-        "author_inst": "Humabs Biomed SA"
-      },
-      {
-        "author_name": "Roberto Spreafico",
-        "author_inst": "Vir Biotechnology"
-      },
-      {
-        "author_name": "Elisabetta Cameroni",
-        "author_inst": "Humabs Biomed"
-      },
-      {
-        "author_name": "James Brett Case",
-        "author_inst": "Washington University School of Medicine"
-      },
-      {
-        "author_name": "Rita E. Chen",
-        "author_inst": "Washington University School of Medicine"
-      },
-      {
-        "author_name": "Colin Havenar-Daughton",
-        "author_inst": "Vir Biotehcnology"
-      },
-      {
-        "author_name": "Gyorgy Snell",
-        "author_inst": "Vir Biotechnology"
-      },
-      {
-        "author_name": "Amalio Telenti",
-        "author_inst": "Vir Biotechnology"
-      },
-      {
-        "author_name": "Herbert W. Virgin",
-        "author_inst": "Vir Biotechnology"
+        "author_name": "Natalya Bukreyeva",
+        "author_inst": "University of Texas Medical Branch"
       },
       {
-        "author_name": "Antonio Lanzavecchia",
-        "author_inst": "Institute for Research in Biomedicine"
+        "author_name": "Emily K Mantlo",
+        "author_inst": "University of Texas Medical Branch"
       },
       {
-        "author_name": "Michael S. Diamond",
-        "author_inst": "Washington University School of Medicine"
+        "author_name": "Rachel A Sattler",
+        "author_inst": "University of Texas Medical Branch"
       },
       {
-        "author_name": "Katja Fink",
-        "author_inst": "Humabs Biomed"
+        "author_name": "Cheng Huang",
+        "author_inst": "University of Texas Medical Branch"
       },
       {
-        "author_name": "David Veesler",
-        "author_inst": "University of Washington"
+        "author_name": "Slobodan Paessler",
+        "author_inst": "University of Texas Medical Branch"
       },
       {
-        "author_name": "Davide Corti",
-        "author_inst": "Humabs Biomed SA, subsidiary of Vir Biotechnology"
+        "author_name": "Jerry Zeldis",
+        "author_inst": "ViralClear, a subsidiary of BioSig, Inc."
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "immunology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.04.07.029090",
@@ -1519455,41 +1522824,21 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.04.20052308",
-    "rel_title": "The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran",
+    "rel_doi": "10.1101/2020.04.03.20052845",
+    "rel_title": "Use Crow-AMSAA Method to predict the cases of the Coronavirus 19 in Michigan and U.S.A",
     "rel_date": "2020-04-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.04.20052308",
-    "rel_abs": "ObjectivesTo estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud, Northeast of Iran.\n\nMethodsThe R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The serial interval was fit with a gamma distribution. The probable incidence and cumulative incidence in the next 30 days were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using \"earlyR\" and \"projections\" packages in R software.\n\nResultsThe maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1 to 3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI: 1.03 to 1.25) by the end of the day 41. The expected average number of new cases in Shahroud is 9.0{+/-}3.8 case/day, which means an estimated total of 271 (95% CI: 178-383) new cases in the next 30 days.\n\nConclusionsIt is essential to reduce the R0 to values below one. Therefore, we strongly recommend enforcing and continuing the current preventive measures, restricting travel, and providing screening tests for a larger proportion of the population.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052845",
+    "rel_abs": "The Crow-AMSAA method is used in engineering reliability world to predict the failures and evaluate the reliability growth. The author intents to use this model in the prediction of the Coronavirus 19 (COVID19) cases by using the daily reported data from Michigan, New York City, U.S.A and other countries. The piece wise Crow-AMSAA (CA) model fits the data very well for the infected cases and deaths at different phases while the COVID19 outbreak starting. The slope {beta} of the Crow-AMSAA line indicates the speed of the transmission or death rate. The traditional epidemiological model is based on the exponential distribution, but the Crow-AMSAA is the Non Homogeneous Poisson Process (NHPP) which can be used to modeling the complex problem like COVID19, especially when the various mitigation strategies such as social distance, isolation and locking down were implemented by the government at different places.\n\nSummaryThis paper is to use piece wise Crow-AMSAA method to fit the COVID19 confirmed cases in Michigan, New York City, U.S.A and other countries.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Ahmad Khosravi",
-        "author_inst": "Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran"
-      },
-      {
-        "author_name": "Reza Chaman",
-        "author_inst": "Department of Epidemiology, School of Public Health, Shahroud University of Medical Sciences, Shahroud, Iran"
-      },
-      {
-        "author_name": "Marzieh Rohani-Rasaf",
-        "author_inst": "Department of Epidemiology, School of Public Health, Shahroud University of Medical Sciences, Shahroud, Iran"
-      },
-      {
-        "author_name": "Fariba Zare",
-        "author_inst": "Center for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran."
-      },
-      {
-        "author_name": "Shiva Mehravaran",
-        "author_inst": "ASCEND Center for Biomedical Research, Morgan State University, Baltimore, USA"
-      },
-      {
-        "author_name": "Mohammad Hassan Emamian",
-        "author_inst": "Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran"
+        "author_name": "Yanshuo Wang",
+        "author_inst": "LLLW LLC"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1520825,21 +1524174,33 @@
     "category": "psychiatry and clinical psychology"
   },
   {
-    "rel_doi": "10.1101/2020.04.04.20052696",
-    "rel_title": "Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic",
+    "rel_doi": "10.1101/2020.04.03.20052720",
+    "rel_title": "Mitigating COVID-19 outbreak via high testing capacity and strong transmission-intervention in the United States",
     "rel_date": "2020-04-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.04.20052696",
-    "rel_abs": "The ongoing novel coronavirus disease (COVID-19) pandemic has rapidly spread in early 2020, causing tens of thousands of deaths, over a million cases and widespread socioeconomic disruption. With no vaccine available and numerous national healthcare systems reaching or exceeding capacity, interventions to limit transmission are urgently needed. While there is broad agreement that travel restrictions and closure of non-essential businesses and schools are beneficial in limiting local and regional spread, recommendations around the use of face masks for the general population are less consistent internationally. In this study, we examined the role of face masks in mitigating the spread of COVID-19 in the general population, using epidemic models to estimate the total reduction of infections and deaths under various scenarios. In particular, we examined the optimal deployment of face masks when resources are limited, and explored a range of supply and demand dynamics. We found that face masks, even with a limited protective effect, can reduce infections and deaths, and can delay the peak time of the epidemic. We consistently found that a random distribution of masks in the population was a suboptimal strategy when resources were limited. Prioritizing coverage among the elderly was more beneficial, while allocating a proportion of available resources for diagnosed infected cases provided further mitigation under a range of scenarios. In summary, face mask use, particularly for a pathogen with relatively common asymptomatic carriage, can effectively provide some mitigation of transmission, while balancing provision between vulnerable healthy persons and symptomatic persons can optimize mitigation efforts when resources are limited.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052720",
+    "rel_abs": "Most models of the COVID-19 pandemic in the United States do not consider geographic variation and spatial interaction. In this research, we developed a travel-network-based susceptible-exposed-infectious-removed (SEIR) mathematical compartmental model system that characterizes infections by state and incorporates inflows and outflows of interstate travelers. Modeling reveals that curbing interstate travel when the disease is already widespread will make little difference. Meanwhile, increased testing capacity (facilitating early identification of infected people and quick isolation) and strict social-distancing and self-quarantine rules are most effective in abating the outbreak. The modeling has also produced state-specific information. For example, for New York and Michigan, isolation of persons exposed to the virus needs to be imposed within 2 days to prevent a broad outbreak, whereas for other states this period can be 3.6 days. This model could be used to determine resources needed before safely lifting state policies on social distancing.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Colin J Worby",
-        "author_inst": "Broad Institute"
+        "author_name": "Shi Chen",
+        "author_inst": "University of Wisconsin-Madison"
       },
       {
-        "author_name": "Hsiao-Han Chang",
-        "author_inst": "National Tsing Hua University"
+        "author_name": "Qin Li",
+        "author_inst": "University of Wisconsin-Madisons"
+      },
+      {
+        "author_name": "Song Gao",
+        "author_inst": "University of Wisconsin-Madison"
+      },
+      {
+        "author_name": "Yuhao Kang",
+        "author_inst": "University of Wisconsin-Madison"
+      },
+      {
+        "author_name": "Xun Shi",
+        "author_inst": "Dartmouth College"
       }
     ],
     "version": "1",
@@ -1521979,63 +1525340,39 @@
     "category": "public and global health"
   },
   {
-    "rel_doi": "10.1101/2020.04.06.20053918",
-    "rel_title": "Thoughts on Higher Medical Education Under Major Public Health Emergencies: Thinking Ahead After COVID-19 Outbreak",
+    "rel_doi": "10.1101/2020.04.03.20052936",
+    "rel_title": "An \"Infodemic\": Leveraging High-Volume Twitter Data to Understand Public Sentiment for the COVID-19 Outbreak",
     "rel_date": "2020-04-07",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20053918",
-    "rel_abs": "ImportanceThe spread of coronavirus disease 2019 (COVID-19) has posed great threat to peoples health and several medical schools in the world suspended classes as a precaution against the virus. China has also adopted precautionary measures to keep medical schools running without suspending classes. Thinking ahead after COVID-19 Outbreak is important.\n\nObjectiveTo explore the most suitable teaching and learning pattern in medical school during COVID-19 Outbreak.\n\nDesignThis study is a case-control study. We had tried to apply a new blended teaching model based on 5G network that combined team-based learning (TBL) and online interaction to the students before the outbreak and then universities responded to the COVID-19 outbreak by closing campuses and shifting to other forms of distance learning. In other word, the courses started using blended teaching model before COVID-19 outbreak and might last using other forms of distance learning throughout the pandemic. Five Point Likert Scale Questionnaires which contains 20 items were used, and the effect of the two kinds of teaching patterns was compared by evaluating the indicators of core competencies of students including professionalism, attitude towards learning, knowledge and learning skills, teamwork skills, motivation in learning, adaptability and acceptance of the courses and network environment.\n\nSettingOur study based on a single center.\n\nParticipantsFifty fourth-year medical students receiving the \"5+3\" pattern courses regarding internal medicine were enrolled in the study.\n\nExposure(s) (for observational studies)The teaching and learning patter started using blended teaching model before COVID-19 outbreak and might last using other forms of distance learning throughout the pandemic.\n\nMain Outcome(s)According to the descriptive statistical analysis of the first part of the questionnaire (question 1-16), the average score of adaptability and acceptance of the courses is 2.60 lower than 3, indicating that students are more adapted to other forms of distance learning during COVID-19 outbreak; the average score of the rest of the questions is higher than 3, indicating that blended teaching model based on 5G network is superior to other forms of distance learning. The number of male students who are inclined to the blended teaching model based on 5G network is 0.13 times as much as that of female students (95%CI:0.028[~]0.602, p=0.009).\n\nResultsOnline forms of distance learning were accepted by the students. Female students had higher expectations on the course and were more likely to adapt well to the change during the COVID-19 outbreak. However, all students preferred the blended teaching model based on 5G network that combined team-based learning (TBL) and online interaction before the pandemic.\n\nConclusionIt indicates that medical education based on 5G network that combined team-based learning (TBL) and online interaction is a more suitable option to teach medical students online. Chinas experience in online higher medical education may serve as a reference to other countries during the pandemic.\n\nKey pointO_ST_ABSQuestionsC_ST_ABSWhat are the reflections on approaches to teaching and learning during COVID-19 Outbreak?\n\nFindingsFifty fourth-year medical students receiving the \"5+3\" pattern courses regarding internal medicine were enrolled. Five Point Likert Scale Questionnaires which contains 20 items were used. This study indicates that medical education based on 5G network that combined team-based learning (TBL) and online interaction is a more suitable option to teach medical students online during COVID-19 outbreak.\n\nMeaningChinas experience in online higher medical education may serve as a reference to other countries during the pandemic.",
-    "rel_num_authors": 11,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052936",
+    "rel_abs": "BackgroundTwitter has been used to track trends and disseminate health information during viral epidemics. On January 21, 2020, the CDC activated its Emergency Operations Center and the WHO released its first situation report about Coronavirus disease 2019 (COVID-19), sparking significant media attention. How Twitter content and sentiment has evolved in the early stages of any outbreak, including the COVID-19 epidemic, has not been described.\n\nObjectiveTo quantify and understand early changes in Twitter activity, content, and sentiment about the COVID-19 epidemic.\n\nDesignObservational study.\n\nSettingTwitter platform.\n\nParticipantsAll Twitter users who created or sent a message from January 14th to 28th, 2020.\n\nMeasurementsWe extracted tweets matching hashtags related to COVID-19 and measured frequency of keywords related to infection prevention practices, vaccination, and racial prejudice. We performed a sentiment analysis to identify emotional valence and predominant emotions. We conducted topic modeling to identify and explore discussion topics over time.\n\nResultsWe evaluated 126,049 tweets from 53,196 unique users. The hourly number of COVID-19-related tweets starkly increased from January 21, 2020 onward. Nearly half (49.5%) of all tweets expressed fear and nearly 30% expressed surprise. The frequency of racially charged tweets closely paralleled the number of newly diagnosed cases of COVID-19. The economic and political impact of the COVID-19 was the most commonly discussed topic, while public health risk and prevention were among the least discussed.\n\nConclusionTweets with negative sentiment and emotion parallel the incidence of cases for the COVID-19 outbreak. Twitter is a rich medium that can be leveraged to understand public sentiment in real-time and target public health messages based on user interest and emotion.\n\nFundingNone.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Wei Lin",
-        "author_inst": "Fujian Provincial Hospital"
-      },
-      {
-        "author_name": "Yan Chen",
-        "author_inst": "Fujian Provincial Hospital"
-      },
-      {
-        "author_name": "Songchang Shi",
-        "author_inst": "Fujian Provincial Hospital South Branch"
-      },
-      {
-        "author_name": "Jixing Liang",
-        "author_inst": "Fujian Provincial Hospital"
-      },
-      {
-        "author_name": "Huibin Huang",
-        "author_inst": "Fujian Provincial Hospital"
-      },
-      {
-        "author_name": "Liantao Li",
-        "author_inst": "Fujian Provincial Hospital"
-      },
-      {
-        "author_name": "Liangchun Cai",
-        "author_inst": "Fujian Provincial Hospital"
+        "author_name": "Richard J. Medford",
+        "author_inst": "University of Texas Southwestern Medical Center"
       },
       {
-        "author_name": "Liyao Zong",
-        "author_inst": "Fujian Provincial Hospital"
+        "author_name": "Sameh N. Saleh",
+        "author_inst": "University of Texas Southwestern Medical Center"
       },
       {
-        "author_name": "Nengying Wang",
-        "author_inst": "Fujian Provincial Hospital"
+        "author_name": "Andrew Sumarsono",
+        "author_inst": "University of Texas Southwestern Medical Center"
       },
       {
-        "author_name": "Junping Wen",
-        "author_inst": "Fujian Provincial Hospital"
+        "author_name": "Trish M. Perl",
+        "author_inst": "University of Texas Southwestern Medical Center"
       },
       {
-        "author_name": "Gang Chen",
-        "author_inst": "Fujian Provincial Hospital"
+        "author_name": "Christoph U. Lehmann",
+        "author_inst": "University of Texas Southwestern Medical Center"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "medical education"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2020.04.05.20054254",
@@ -1523357,21 +1526694,33 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.03.31.20048652",
-    "rel_title": "Widespread use of face masks in public may slow the spread of SARS CoV-2: an ecological study",
+    "rel_doi": "10.1101/2020.03.30.20048165",
+    "rel_title": "Association of BCG vaccination policy with prevalence and mortality of COVID-19",
     "rel_date": "2020-04-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20048652",
-    "rel_abs": "BackgroundThe reasons for the large differences between countries in the sizes of their SARS CoV-2 epidemics is unknown. Individual level studies have found that the use of face masks was protective for the acquisition and transmission of a range of respiratory viruses including SARS CoV-1. We hypothesized that population level usage of face masks may be negatively associated SARS CoV-2 spread.\n\nMethodsAt a country level, linear regression was used to assess the association between COVID-19 diagnoses per inhabitant and the national promotion of face masks in public (coded as a binary variable), controlling for the age of the COVID-19 epidemic and testing intensity.\n\nResultsEight of the 49 countries with available data advocated wearing face masks in public - China, Czechia, Hong Kong, Japan, Singapore, South Korea, Thailand and Malaysia. In multivariate analysis face mask use was negatively associated with number of COVID-19 cases/inhabitant (coef. -326, 95% CI -601- -51, P=0.021). Testing intensity was positively associated with COVID-19 cases (coef. 0.07, 95% CI 0.05-0.08, P<0.001).\n\nConclusionWhilst these results are susceptible to residual confounding, they do provide ecological level support to the individual level studies that found face mask usage to reduce the transmission and acquisition of respiratory viral infections.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20048165",
+    "rel_abs": "BackgroundEvidence suggests non-specific benefits of the tuberculosis vaccine bacillus Calmette-Guerin (BCG) against non-related infections. Recent studies propose such protection may extend to the novel COVID-19 as well. This is a contested hypothesis.\n\nMethodsOur ecological study confronts this hypothesis. We examine the effects of BCG vaccination on countries COVID-19 (a) cases and deaths (per million) and (b) exponential growth factors over specific periods of the pandemic. Since the BCG vaccine was derived from Mycobacterium bovis, a bacterium causing tuberculosis in cattle, having suffered from tuberculosis also may exert a non-specific protection against the COVID-19 as well. Along with BCG vaccination, we test the effect of the prevalence of tuberculosis.\n\nWe employ multiple regression and principal component analysis (PCA) to control for potentially confounding variables (n = 16).\n\nResultsBCG vaccination policy and incidence of tuberculosis is associated with a reduction in both COVID-19 cases and deaths, and the effects of these two variables are additive ({approx} 5% to 15% of total unique variance explained). The study of exponential growth factors in the initial stages of the pandemic further shows that BCG vaccination exerts a significant effect (up to 35% of unique variance explained).\n\nConclusionsOverall, these findings corroborate the hypothesis that BCG vaccination and exposure to tuberculosis may induce a non-specific protection against the novel SARS-CoV-2 infection, even after accounting for a large number of confounding influences. However, given the potential public-health benefits, our results indicate that the hypothesis deserves further attention and should not be hastily dismissed.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Chris Kenyon",
-        "author_inst": "Institute of Tropical Medicine, Antwerp"
+        "author_name": "Giovanni Sala",
+        "author_inst": "Fujita Health University"
+      },
+      {
+        "author_name": "Rik Chakraborti",
+        "author_inst": "Department of Economics, Christopher Newport University"
+      },
+      {
+        "author_name": "Atsuhiko Ota",
+        "author_inst": "Department of Public Health, Fujita Health University School of Medicine"
+      },
+      {
+        "author_name": "Tsuyoshi Miyakawa",
+        "author_inst": "Fujita Health University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1524715,33 +1528064,29 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.31.20049387",
-    "rel_title": "The impacts of diagnostic capability and prevention measures on transmission dynamics of COVID-19 in Wuhan",
+    "rel_doi": "10.1101/2020.03.31.20049452",
+    "rel_title": "A Covid-19 case mortality rate without time delay systematics",
     "rel_date": "2020-04-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20049387",
-    "rel_abs": "BackgroundAlthough by late February 2020 the COVID-19 epidemic was effectively controlled in Wuhan, China, the virus has since spread around the world and been declared a pandemic on March 11. Estimating the effects of interventions, such as transportation restrictions and quarantine measures, on the early COVID-19 transmission dynamics in Wuhan is critical for guiding future virus containment strategies. Since the exact number of COVID-19 infected cases is unknown, the number of documented cases was used by many disease transmission models to infer epidemiological parameters. However, this means that it would not be possible to adequately estimate epidemiological parameters and the effects of intervention measures, because the percentage of all infected cases that were documented changed during the first 2 months of the epidemic as a consequence of a gradually increasing diagnostic capability.\n\nMethodsTo overcome the limitations, we constructed a stochastic susceptible-exposed-infected-quarantined-recovered (SEIQR) model, accounting for intervention measures and temporal changes in the proportion of new documented infections out of total new infections, to characterize the transmission dynamics of COVID-19 in Wuhan across different stages of the outbreak. Pre-symptomatic transmission was taken into account in our model, and all epidemiological parameters were estimated using Particle Markov-chain Monte Carlo (PMCMC) method.\n\nResultsOur model captured the local Wuhan epidemic pattern as a two-peak transmission dynamics, with one peak on February 4 and the other on February 12, 2020. The impact of intervention measures determined the timing of the first peak, leading to an 86% drop in the Re from 3.23 (95% CI, 2.22 to 4.20) to 0.45 (95% CI, 0.20 to 0.69). An improved diagnostic capability led to the second peak and a higher proportion of documented infections. Our estimated proportion of new documented infections out of the total new infections increased from 11% (95% CI 1% - 43%) to 28% (95% CI 4% - 62%) after January 26 when more detection kits were released. After the introduction of a new diagnostic criterion (case definition) on February 12, a higher proportion of daily infected cases were documented (49% (95% CI 7% - 79%)).",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20049452",
+    "rel_abs": "Concerning the two approaches to the Covid-19 case mortality rate published in the literature, namely computing the ratio of (a) the daily number of deaths to a time delayed daily number of confirmed infections; and (b) the cumulative number of deaths to confirmed infections up to a certain time, both numbers having been acquired in the middle of an outbreak, it is shown that each suffers from systematic error of a different source. We further show that in the absence of detailed knowledge of the time delay distribution of (a), the true case mortality rate is obtained by pursuing method (b) at the end of the outbreak when the fate of every case has decisively been rendered. The approach is then employed to calculate the mean case mortality rate of 13 regions of China where every case has already been resolved. This leads to a mean rate of 0.527 {+/-} 0.001 %.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jingbo LIANG",
-        "author_inst": "Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China"
-      },
-      {
-        "author_name": "Hsiang-Yu Yuan",
-        "author_inst": "Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, China"
+        "author_name": "Richard Lieu",
+        "author_inst": "University of Alabama"
       },
       {
-        "author_name": "Lindsey Wu",
-        "author_inst": "Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, United Kingdom"
+        "author_name": "Siobhan Quenby",
+        "author_inst": "Division of Reproductive Health, Warwick Medical School, The University of Warwick, UK"
       },
       {
-        "author_name": "Dirk Udo Pfeiffer",
-        "author_inst": "Centre for Applied One Health Research and Policy Advice, City University of Hong Kong, Hong Kong, China"
+        "author_name": "Ally Bi-zhu Jiang",
+        "author_inst": "Shenzhen RAK wireless Technology Co., Ltd., China"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1525813,49 +1529158,45 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.04.02.20050773",
-    "rel_title": "Exponential phase of covid19 expansion is not driven by climate at global scale",
+    "rel_doi": "10.1101/2020.04.02.20050922",
+    "rel_title": "Inferring COVID-19 spreading rates and potential change points for case number forecasts",
     "rel_date": "2020-04-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20050773",
-    "rel_abs": "The pandemic state of COVID-19 caused by the SARS CoV-2 put the world in quarantine, led to hundreds of thousands of deaths and is causing an unprecedented economic crisis. However, COVID-19 is spreading in different rates at different countries. Here, we tested the effect of three classes of predictors, i.e., socioeconomic, climatic and transport, on the rate of daily increase of COVID-19. We found that global connections, represented by countries importance in the global air transportation network, is the main explanation for the growth rate of COVID-19 in different countries. Climate, geographic distance and socioeconomics had a milder effect in this big picture analysis. Geographic distance and climate were significant barriers in the past but were surpassed by the human engine that allowed us to colonize most of our planet land surface. Our results indicate that the current claims that the growth rate of COVID-19 may be lower in warmer and humid tropical countries should be taken very carefully, at risk to disturb well-established and effective policy of social isolation that may help to avoid higher mortality rates due to the collapse of national health systems.",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20050922",
+    "rel_abs": "As COVID-19 is rapidly spreading across the globe, short-term modeling forecasts provide time-critical information for decisions on containment and mitigation strategies. A main challenge for short-term forecasts is the assessment of key epidemiological parameters and how they change when first interventions show an effect. By combining an established epidemiological model with Bayesian inference, we analyze the time dependence of the effective growth rate of new infections. Focusing on the COVID-19 spread in Germany, we detect change points in the effective growth rate that correlate well with the times of publicly announced interventions. Thereby, we can quantify the effect of interventions, and we can incorporate the corresponding change points into forecasts of future scenarios and case numbers. Our code is freely available and can be readily adapted to any country or region.\n\nIntroductionWhen faced with the outbreak of a novel epidemic like COVID-19, rapid response measures are required by individuals as well as by society as a whole to mitigate the spread of the virus. During this initial, time-critical period, neither the central epidemiological parameters, nor the effectiveness of interventions like cancellation of public events, school closings, and social distancing are known.\n\nRationaleAs one of the key epidemiological parameters, we infer the spreading rate{lambda} from confirmed COVID-19 case numbers at the example of Germany by combining Bayesian inference based on Markov-Chain Monte-Carlo sampling with a class of SIR (Susceptible-Infected-Recovered) compartmental models from epidemiology. Our analysis characterizes the temporal change of the spreading rate and, importantly, allows us to identify potential change points and to provide short-term forecast scenarios based on various degrees of social distancing. A detailed description is provided in the accompanying paper, and the models, inference, and predictions are available on github. While we apply it to Germany, our approach can be readily adapted to other countries or regions.\n\nResultsIn Germany, interventions to contain the outbreak were implemented in three steps over three weeks: Around March 9, large public events like soccer matches were cancelled. On March 16, schools and childcare facilities as well as many non-essential stores were closed. One week later, on March 23, a far-reaching contact ban (\"Kontaktsperre\"), which included the prohibition of even small public gatherings as well as the further closing of restaurants and non-essential stores, was imposed by the government authorities.\n\nFrom the observed case numbers of COVID-19, we can quantify the impact of these measures on the disease spread (Fig. 0). Based on our analysis, which includes data until April 21, we have evidence of three change points: the first changed the spreading rate from{lambda} 0 = 0.43 (95 % credible interval (CI: [0.35, 0.51])) to{lambda} 1 = 0.25 (CI: [0.20, 0.30]), and occurred around March 6 (CI: March 2 to March 9); the second change point resulted in{lambda} 2 = 0.15 (CI: [0.12, 0.20]), and occurred around March 15 (CI: March 13 to March 17). Both changes in{lambda} slowed the spread of the virus, but still implied exponential growth (Fig. 0, red and orange traces). To contain the disease spread, and turn from exponential growth to a decline of new cases, a further decrease in{lambda} was necessary. Our analysis shows that this transition has been reached by the third change point that resulted in{lambda} 3 = 0.09 (CI: [0.06, 0.12]) around March 23 (CI: March 20 to March 25).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC=\"FIGDIR/small/20050922v3_fig0.gif\" ALT=\"Figure 0\">\nView larger version (39K):\norg.highwire.dtl.DTLVardef@1176ccorg.highwire.dtl.DTLVardef@8e7739org.highwire.dtl.DTLVardef@13549baorg.highwire.dtl.DTLVardef@17b5d36_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFig. 0.C_FLOATNO Bayesian analysis of the German COVID-19 data (blue diamonds) reveals three change points that match the timing of publicly announced interventions. A: The inferred effective growth rate (difference between spreading and recovery rate,{lambda} * ={lambda} - ) for an SIR model with weekly reporting modulation and reporting delay that includes scenarios with one, two or three change points (red, orange, green; fitted to case reports until March 25, April 1 and April 9, respectively). The timing of the inferred change points in growth rate is consistent with the timing of German governmental interventions (depicted as *, **, and * * *). B: Comparing inferred models with the actual new reported cases per day reveals the effectiveness of governmental interventions. After the first two interventions, the number of new cases still grew exponentially (red, orange); only after the third intervention did the number of new cases start to saturate (green) or even to decline (gray, data until April 21). This illustrates that the future development strongly depends on our distancing behavior. Note the delay between a change point and the observation of changes in the number of new cases of almost two weeks  a combination of reporting delay and a minimal period of evidence accumulation.\n\nC_FIG With this third change point,{lambda} transitioned below the critical value where the spreading rate{lambda} balances the recovery rate , i.e. the effective growth rate{lambda} * ={lambda} -  {approx} 0 (Fig. 0, gray traces). Importantly,{lambda} * = 0 presents the watershed between exponential growth or decay. Given the delay of approximately two weeks between an intervention and first inference of the induced changes in{lambda} *, future interventions such as lifting restrictions warrant careful consideration.\n\nOur detailed analysis shows that, in the current phase, reliable short- and long-term forecasts are very difficult as they critically hinge on how the epidemiological parameters change in response to interventions: In Fig. 0 already the three example scenarios quickly diverge from each other, and consequently span a considerable range of future case numbers. Thus, any uncertainty on the magnitude of our social distancing in the past two weeks can have a major impact on the case numbers in the next two weeks. Beyond two weeks, the case numbers depend on our future behavior, for which we have to make explicit assumptions. In the main paper we illustrate how the precise magnitude and timing of potential change points impact the forecast of case numbers (Fig. 2).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC=\"FIGDIR/small/20050922v3_fig2.gif\" ALT=\"Figure 2\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@24b42corg.highwire.dtl.DTLVardef@1b0dcc8org.highwire.dtl.DTLVardef@6ef54aorg.highwire.dtl.DTLVardef@a9f26c_HPS_FORMAT_FIGEXP  M_FIG O_FLOATNOFig. 2.C_FLOATNO The timing and effectiveness of interventions strongly impact future COVID-19 cases. A: We assume three different scenarios for interventions starting on March 16: (I, red) no social distancing, (II, orange) mild social distancing, or (III, green) strict social distancing. B: Delaying the restrictions has a major impact on case numbers: strict restrictions starting on March 16 (green), five days later (magenta) or five days earlier (gray). C: Comparison of the time span over which interventions ramp up to full effect. For all ramps that are centered around the same day, the resulting case numbers are fairly similar. However, a sudden change of the spreading rate can cause a temporary decrease of daily new cases, although{lambda} >  at all times (brown).\n\nC_FIG ConclusionsWe developed a Bayesian framework to infer central epidemiological parameters and the timing and magnitude of intervention effects. Thereby, the efficiency of political and individual intervention measures for social distancing and containment can be assessed in a timely manner. We find evidence for a successive decrease of the spreading rate in Germany around March 6 and around March 15, which significantly reduced the magnitude of exponential growth, but was not sufficient to turn growth into decay. Our analysis also shows that a further decrease of the spreading rate occurred around March 23, turning exponential growth into decay. Future interventions and lifting of restrictions can be modeled as additional change points, enabling short-term forecasts for case numbers. In general, our analysis code may help to infer the efficiency of measures taken in other countries and inform policy makers about tightening, loosening and selecting appropriate rules for containment.",
+    "rel_num_authors": 7,
     "rel_authors": [
       {
-        "author_name": "Marco Tulio Pacheco Coelho",
-        "author_inst": "Universidade Federal de Goias"
-      },
-      {
-        "author_name": "Joao Fabricio Mota Rodrigues",
-        "author_inst": "Universidade Federal de Goias"
+        "author_name": "Jonas Dehning",
+        "author_inst": "Max Planck Institute for Dynamics and Self-Organization"
       },
       {
-        "author_name": "Anderson Matos Medina",
-        "author_inst": "Universidade Federal da Bahia"
+        "author_name": "Johannes Zierenberg",
+        "author_inst": "Max Planck Institute for Dynamics and Self-Organization"
       },
       {
-        "author_name": "Paulo Scalco",
-        "author_inst": "Universidade Federal de Goias"
+        "author_name": "Frank Paul Spitzner",
+        "author_inst": "Max Planck Institute for Dynamics and Self-Organization"
       },
       {
-        "author_name": "Levi Carina Terribile",
-        "author_inst": "Universidade Federal de Jatai"
+        "author_name": "Michael Wibral",
+        "author_inst": "Georg August University Goettingen"
       },
       {
-        "author_name": "Bruno Vilela",
-        "author_inst": "Universidade Federal da Bahia"
+        "author_name": "Joao Pinheiro Neto",
+        "author_inst": "Max Planck Institute for Dynamics and Self-Organization"
       },
       {
-        "author_name": "Jose Alexandre Felizola Diniz-Filho",
-        "author_inst": "Universidade Federal de Goias"
+        "author_name": "Michael Wilczek",
+        "author_inst": "Max Planck Institute for Dynamics and Self-Organization"
       },
       {
-        "author_name": "Ricardo Dobrovolski",
-        "author_inst": "Universidade Federal da Bahia"
+        "author_name": "Viola Priesemann",
+        "author_inst": "Max Planck Institute for Dynamics and Self-Organization"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1527083,31 +1530424,159 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.04.02.022384",
-    "rel_title": "One-step RNA extraction for RT-qPCR detection of 2019-nCoV",
+    "rel_doi": "10.1101/2020.04.02.019075",
+    "rel_title": "Rapid community-driven development of a SARS-CoV-2 tissue simulator",
     "rel_date": "2020-04-05",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.02.022384",
-    "rel_abs": "The global outbreak of coronavirus disease 2019 (COVID-19) has placed an unprecedented burden on healthcare systems as the virus spread from the initial 27 reported cases in the city of Wuhan, China to a global pandemic in under three month[1]. Resources essential to monitoring virus transmission have been challenged with a demand for expanded surveillance. The CDC 2019-nCoV Real-Time Diagnostic Panel uses a real-time reverse transcription polymerase chain reaction (RT-PCR) consisting of two TaqMan probe and primer sets specific for the 2019-nCoV N gene, which codes for the nucleocapsid structural protein that encapsulates viral RNA, for the qualitative detection of 2019-nCoV viral RNA in respiratory samples. To isolate RNA from respiratory samples, the CDC lists RNA extraction kits from four manufacturers. In anticipation of a limited supply chain of RNA extraction kits and the need for test scalability, we sought to identify alternative RNA extraction methods. Here we show that direct lysis of respiratory samples can be used in place of RNA extraction kits to run the CDC 2019-nCoV Real-Time Diagnostic assay with the additional benefits of higher throughput, lower cost, faster turnaround and possibly higher sensitivity and improved safety.",
-    "rel_num_authors": 3,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.02.019075",
+    "rel_abs": "The 2019 novel coronavirus, SARS-CoV-2, is a pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable \"choke points\" for pharmacologic interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving regular refinements. In a sustained community effort, this consortium is integrating data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health. More broadly, this effort is creating a reusable, modular framework for studying viral replication and immune response in tissues, which can also potentially be adapted to related problems in immunology and immunotherapy.",
+    "rel_num_authors": 35,
     "rel_authors": [
       {
-        "author_name": "Monica Sentmanat",
-        "author_inst": "Washington University in St. Louis"
+        "author_name": "Michael Getz",
+        "author_inst": "Indiana University"
       },
       {
-        "author_name": "Evguenia Kouranova",
-        "author_inst": "Washington University in St. Louis"
+        "author_name": "Yafei Wang",
+        "author_inst": "Indiana University"
       },
       {
-        "author_name": "Xiaoxia Cui",
-        "author_inst": "Washington University in St. Louis"
+        "author_name": "Gary An",
+        "author_inst": "University of Vermont Medical Center"
+      },
+      {
+        "author_name": "Maansi Asthana",
+        "author_inst": "Purdue University"
+      },
+      {
+        "author_name": "Andrew Becker",
+        "author_inst": "University of Vermont Medical Center"
+      },
+      {
+        "author_name": "Chase Cockrell",
+        "author_inst": "University of Vermont Medical Center"
+      },
+      {
+        "author_name": "Nicholson Collier",
+        "author_inst": "Argonne National Laboratory, University of Chicago"
+      },
+      {
+        "author_name": "Morgan Craig",
+        "author_inst": "University of Montreal, CHU Sainte-Justine Research Centre"
+      },
+      {
+        "author_name": "Courtney L. Davis",
+        "author_inst": "Pepperdine University"
+      },
+      {
+        "author_name": "James R Faeder",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Ashlee N Ford Versypt",
+        "author_inst": "Oklahoma State University"
+      },
+      {
+        "author_name": "Tarunendu Mapder",
+        "author_inst": "Indiana University School of Medicine"
+      },
+      {
+        "author_name": "Juliano F Gianlupi",
+        "author_inst": "Indiana University"
+      },
+      {
+        "author_name": "James A. Glazier",
+        "author_inst": "Indiana University"
+      },
+      {
+        "author_name": "Sara Hamis",
+        "author_inst": "University of Saint Andrews"
+      },
+      {
+        "author_name": "Randy Heiland",
+        "author_inst": "Indiana University"
+      },
+      {
+        "author_name": "Thomas Hillen",
+        "author_inst": "University of Alberta"
+      },
+      {
+        "author_name": "Dennis Hou",
+        "author_inst": "Rutgers University"
+      },
+      {
+        "author_name": "Mohammad Aminul Islam",
+        "author_inst": "Oklahoma State University"
+      },
+      {
+        "author_name": "Adrianne L Jenner",
+        "author_inst": "University of Montreal, CHU Sainte-Justine Research Centre"
+      },
+      {
+        "author_name": "Furkan Kurtoglu",
+        "author_inst": "Indiana University"
+      },
+      {
+        "author_name": "Caroline I Larkin",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Bing Liu",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Fiona Macfarlane",
+        "author_inst": "University of Saint Andrews"
+      },
+      {
+        "author_name": "Pablo Maygrundter",
+        "author_inst": "Citizen Scientist"
+      },
+      {
+        "author_name": "Penelope A Morel",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Aarthi Narayanan",
+        "author_inst": "George Mason University"
+      },
+      {
+        "author_name": "Jonathan Ozik",
+        "author_inst": "Argonne National Laboratory, University of Chicago"
+      },
+      {
+        "author_name": "Elsje Pienaar",
+        "author_inst": "Purdue University"
+      },
+      {
+        "author_name": "Padmini Rangamani",
+        "author_inst": "University of California, San Diego"
+      },
+      {
+        "author_name": "Ali Sinan Saglam",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Jason E Shoemaker",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Amber M Smith",
+        "author_inst": "University of Tennessee Health Science Center"
+      },
+      {
+        "author_name": "Jordan J A Weaver",
+        "author_inst": "University of Pittsburgh"
+      },
+      {
+        "author_name": "Paul Macklin",
+        "author_inst": "Indiana University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "new results",
-    "category": "molecular biology"
+    "category": "systems biology"
   },
   {
     "rel_doi": "10.1101/2020.04.03.024216",
@@ -1528441,29 +1531910,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.04.01.20049668",
-    "rel_title": "Spatial variability in the risk of death from COVID-19 in Italy, 2020",
+    "rel_doi": "10.1101/2020.03.31.20049007",
+    "rel_title": "Harmonizing heterogeneous endpoints in COVID-19 trials without loss of information - an essential step to facilitate decision making",
     "rel_date": "2020-04-03",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.01.20049668",
-    "rel_abs": "ObjectivesItaly has been disproportionately affected by the COVID-19 pandemic, becoming the nation with the third highest death toll in the world as of May 10th, 2020. We analyzed the severity of COVID-19 pandemic across 20 Italian regions.\n\nMethodWe manually retrieved the daily cumulative numbers of laboratory-confirmed cases and deaths attributed to COVID-19 across 20 Italian regions. For each region, we estimated the crude case fatality ratio and time-delay adjusted case fatality ratio (aCFR). We then assessed the association between aCFR and sociodemographic, health care and transmission factors using multivariate regression analysis.\n\nResultsThe overall aCFR in Italy was estimated at 17.4%. Lombardia exhibited the highest aCFR (24.7%) followed by Marche (19.3%), Emilia Romagna (17.7%) and Liguria (17.6%). Our aCFR estimate was greater than 10% for 12 regions. Our aCFR estimates were statistically associated with population density and cumulative morbidity rate in a multivariate analysis.\n\nConclusionOur aCFR estimates for overall Italy and for 7 out of 20 regions exceeded those reported for the most affected region in China. Our findings highlight the importance of social distancing to suppress incidence and reduce the death risk by preventing saturating the health care system.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20049007",
+    "rel_abs": "BackgroundMany trials are now underway to inform decision-makers on potential effects of treatments for COVID-19. To provide sufficient information for all involved decision-makers (clinicians, public health authorities, drug regulatory agencies) a multiplicity of endpoints must be considered. It is a challenge to generate detailed high quality evidence from data while ensuring fast availability and evaluation of the results.\n\nMethodsWe reviewed all interventional COVID-19 trials on Remdesivir, Lopinavir/ritonavir and Hydroxychloroquine registered in the National Library of Medicine (NLM) at the National Institutes of Health (NIH) and summarized the endpoints used to assess treatment effects. We propose a multistate model that harmonizes heterogeneous endpoints and differing lengths of follow-up within and between trials.\n\nResultsThere are currently, March 27, 2020, 23 registered interventional trials investigating the potential benefits of Remdesivir, Lopinavir/ritonavir and Hydroxychloroquine. The endpoints are highly heterogeneous. Follow-up for the primary endpoints ranges from four to 168 days.\n\nA detailed precisely defined endpoint has been proposed by the global network REMAP-CAP, which is specialized on community-acquired pneumonia. Their seven-category endpoint accounts for major clinical events informative for all decision-makers. Moreover, the Core Outcome Measures in Effectiveness Trials (COMET) Initiative is currently working on a core outcome set. We propose a multistate model that accommodates analysis of these recommended endpoints. The model allows for a detailed investigation of treatment effects for various endpoints over the course of time thereby harmonizing differing endpoints and lengths of follow-up.\n\nConclusionMultistate model analysis is a powerful tool to study clinically heterogeneous endpoints (mortality, discharge) as well as endpoints influencing hospital capacities (duration of hospitalization and ventilation) simultaneously over time. Our proposed model extracts all information available in the data and is - by harmonizing endpoints within and between trials - a step towards faster decision making. All ongoing clinical trials, especially those with severe cases, should accommodate primary analysis with a stacked probability plot of the major events mechanical ventilation, discharge alive and death.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Kenji Mizumoto",
-        "author_inst": "Kyoto University"
+        "author_name": "Maja von Cube",
+        "author_inst": "Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of"
       },
       {
-        "author_name": "Sushma Dahal",
-        "author_inst": "Georgia State University School of Public Health"
+        "author_name": "Marlon Grodd",
+        "author_inst": "Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Germany"
       },
       {
-        "author_name": "Gerardo Chowell",
-        "author_inst": "Georgia State University School of Public Health"
+        "author_name": "Martin Wolkewitz",
+        "author_inst": "Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Germany"
+      },
+      {
+        "author_name": "Derek Hazard",
+        "author_inst": "Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Germany"
+      },
+      {
+        "author_name": "Jerome Lambert",
+        "author_inst": "University of Paris, Paris, France; ECSTRA Team, Epidemiology and Biostatistics Sorbonne Paris Cite Research Centre UMR 1153, Inserm, Paris, France"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1529523,43 +1533000,55 @@
     "category": "genetic and genomic medicine"
   },
   {
-    "rel_doi": "10.1101/2020.03.31.20048439",
-    "rel_title": "Research on the Influence of Information Diffusion on the Transmission of the Novel Coronavirus (COVID-19)",
+    "rel_doi": "10.1101/2020.03.31.20047142",
+    "rel_title": "Clinical features and outcomes of 2019 novel coronavirus-infected patients with high plasma BNP levels",
     "rel_date": "2020-04-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20048439",
-    "rel_abs": "With the rapid development of mobile Internet in China, the information of the epidemic is full-time and holographic, and the role of information diffusion in epidemic control is increasingly prominent. At the same time, the publicity of all kinds of big data also provides the possibility to explore the impact of media information diffusion on disease transmission. This paper explores the mechanism of the influence of information diffusion on the spread of the novel coronavirus, develops a model of the interaction between information diffusion and disease transmission based on the SIR model, and empirically tests the role and mechanism of information diffusion in the spread of COCID-19 by using econometric method. The result shows that there was a significant negative correlation between the information diffusion and the spread of the novel coronavirus; The result of robust test shows that the spread of both epidemic information and protection information hindered the further spread of the epidemic.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.31.20047142",
+    "rel_abs": "AimsTo explore clinical features and outcome of 2019 novel coronavirus(2019-nCoV)-infected patients with high BNP levels\n\nMethods and resultsData were collected from patients medical records, and we defined high BNP according to the plasma BNP was above > 100 pg/mL. In total,34 patients with corona virus disease 2019(COVID-19)were included in the analysis. Ten patients had high plasma BNP level. The median age for these patients was 60.5 years(interquartile range, 40-80y), and 6/10 (60%) were men. Underlying comorbidities in some patients were coronary heart disease (n=2, 20%), hypertesion (n=3,30%), heart failure (n=1,10%)and diabetes (n=2, 20%). Six (60%) patients had a history of Wuhan exposure. The most common symptoms at illness onset in patients were fever (n=7, 70%), cough (n=3, 30%), headache or fatigue(n=4,40%). These patients had higher aspartate aminotransferase(AST), troponin I, C reactive protein and lower hemoglobin, and platelet count,compared with patients with normal BNP, respectively. Compared with patients with normal BNP, patients with high BNP were more likely to develop severe pneumonia, and receive tracheal cannula, invasive mechanical ventilation, continuous renal replacement therapy, extracorporeal membrane oxygenation, and be admitted to the intensive care unit. One patient with high BNP died during the study.\n\nConclusionHigh BNP is a common condition among patients infected with 2019-nCoV. Patients with high BNP showed poor clinical outcomes",
+    "rel_num_authors": 9,
     "rel_authors": [
       {
-        "author_name": "Lin Shanlang",
-        "author_inst": "School of Economics and Management, Tongji University, China"
+        "author_name": "youbin liu",
+        "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital"
+      },
+      {
+        "author_name": "Dehui Liu",
+        "author_inst": "Guangzhou Eighth People's Hospital"
       },
       {
-        "author_name": "Ma Chao",
-        "author_inst": "School of Economics and Management, Tongji University, China"
+        "author_name": "Huafeng Song",
+        "author_inst": "Guangzhou Eighth People's Hospital"
       },
       {
-        "author_name": "Lin Ruofei",
-        "author_inst": "School of Economics and Management, Tongji University, China"
+        "author_name": "Chunlin chen",
+        "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital"
       },
       {
-        "author_name": "Huang Junpei",
-        "author_inst": "School of Economics and Management, Tongji University, China"
+        "author_name": "Mingfang lv",
+        "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital"
       },
       {
-        "author_name": "Xu Ruohan",
-        "author_inst": "School of Economics and Management, Tongji University, China"
+        "author_name": "Xing pei",
+        "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospita"
       },
       {
-        "author_name": "Yuan Aini",
-        "author_inst": "School of Economics and Management, Tongji University, China"
+        "author_name": "Zhongwei Hu",
+        "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital"
+      },
+      {
+        "author_name": "Zhihui Qin",
+        "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital"
+      },
+      {
+        "author_name": "Jinglong Li",
+        "author_inst": "Department of Cardiology, Guangzhou Eighth People's Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "health economics"
+    "category": "cardiovascular medicine"
   },
   {
     "rel_doi": "10.1101/2020.03.30.20047803",
@@ -1530817,21 +1534306,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.30.20047589",
-    "rel_title": "The Institutional and Cultural Context of Cross-National Variation in COVID-19 Outbreaks",
+    "rel_doi": "10.1101/2020.03.30.20047894",
+    "rel_title": "Forecasting the CoViD19 Diffusion in Italy and the Related Occupancy of Intensive Care Units",
     "rel_date": "2020-04-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20047589",
-    "rel_abs": "BackgroundThe COVID-19 pandemic poses an unprecedented and cascading threat to the health and economic prosperity of the worlds population.\n\nObjectivesTo understand whether the institutional and cultural context influences the COVID-19 outbreak.\n\nMethodsAt the ecological level, regression coefficients are examined to figure out contextual variables influencing the pandemics exponential growth rate across 96 countries.\n\nResultsWhile a strong institutional context is negatively associated with the outbreak (B = -0.55 ... -0.64, p < 0.001), the pandemics growth rate is steeper in countries with a quality education system (B = 0.33, p < 0.001). Countries with an older population are more affected (B = 0.46, p < 0.001). Societies with individualistic (rather than collectivistic) values experience a flatter rate of pathogen proliferation (B = -0.31, p < 0.001), similarly for higher levels of power distance (B = -0.32, p < 0.001). Hedonistic values, that is seeking indulgence and not enduring restraints, are positively related to the outbreak (B = 0.23, p = 0.001).\n\nConclusionsThe results emphasize the need for public policy makers to pay close attention to the institutional and cultural context in their respective countries when instigating measures aimed at constricting the pandemics growth.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20047894",
+    "rel_abs": "This paper provides a model-based method for the forecast of the total number of currently CoVoD-19 positive individuals and of the occupancy of the available Intensive Care Units in Italy. The predictions obtained - for a time horizon of 10 days starting from March 29th - will be provided at a national as well as at a more disaggregate levels, following a criterion based on the magnitude of the phenomenon. While the Regions which have been hit the most by the pandemic have been kept separated, the less affected ones have been aggregated into homogeneous macro-areas. Results show that - within the forecast period considered (March 29th - April 7th) - all of the Italian regions will show a decreasing number of CoViD-19 positive people. Same for the number of people who will need to be hospitalized in a Intensive Care Unit (ICU). These estimates are valid under constancy of the Governments current containment policies. In this scenario, Northern Regions will remain the most affected ones and no significant outbreak are foreseen in the southern regions.",
     "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Wolfgang Messner",
-        "author_inst": "University of South Carolina"
+        "author_name": "Livio Fenga",
+        "author_inst": "ISTAT"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1531887,65 +1535376,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.29.20043547",
-    "rel_title": "Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: A Digital Topic Modeling Approach",
+    "rel_doi": "10.1101/2020.03.29.20046565",
+    "rel_title": "Eco-epidemiological assessment of the COVID-19 epidemic in China, January-February 2020",
     "rel_date": "2020-03-31",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.29.20043547",
-    "rel_abs": "BackgroundIn December 2019, some COVID-19 cases were first reported and soon the disease broke out. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus.\n\nMethodsWe adopted the Huike database to extract news articles about coronavirus from major press media, between January 1st, 2020, to February 20th, 2020. The data were sorted and analyzed by Python software and Python package Jieba. We sought a suitable topic number using the coherence number. We operated Latent Dirichlet Allocation (LDA) topic modeling with the suitable topic number and generated corresponding keywords and topic names. We divided these topics into different themes by plotting them into two-dimensional plane via multidimensional scaling.\n\nFindingsAfter removing duplicates, 7791 relevant news reports were identified. We listed the number of articles published per day. According to the coherence value, we chose 20 as our number of topics and obtained their names and keywords. These topics were categorized into nine primary themes based on the topic visualization figure. The top three popular themes were prevention and control procedures, medical treatment and research, global/local social/economic influences, accounting for 32{middle dot}6%, 16{middle dot}6%, 11{middle dot}8% of the collected reports respectively.\n\nInterpretationThe Chinese mass media news reports lag behind the COVID-19 outbreak development. The major themes accounted for around half the content and tended to focus on the larger society than on individuals. The COVID-19 crisis has become a global issue, and society has also become concerned about donation and support as well as mental health. We recommend that future work should address the mass medias actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.\n\nFundingNational Social Science Foundation of China (18CXW021)\n\nEvidence before this studyThe novel coronavirus related news reports have engaged public attention in China during the COVID-19 crisis. Topic modeling of these news articles can produce useful information about the significance of mass media for early health communication. We searched the Huike database, the most professional Chinese media content database, using the search term \"coronavirus\" for related news articles published from January 1st, 2020, to February 20th, 2020. We found that these articles can be classified into different themes according to their emphasis, however, we found no other studies apply topic modeling method to study them.\n\nAdded value of this studyTo our knowledge, this study is the first to investigate the patterns of health communications through media and the role the media have played and are still playing in the light of the current COVID-19 crisis in China with topic modeling method. We compared the number of articles each day with the outbreak development and identified theres a delay in reporting COVID-19 outbreak progression for Chinese mass media. We identify nine main themes for 7791 collected news reports and detail their emphasis respectively.\n\nImplications of all the available evidenceOur results show that the mass media news reports play a significant role in health communication during the COVID-19 crisis, government can strengthen the report dynamics and enlarge the news coverage next time another disease strikes. Sentiment analysis of news data are needed to assess the actual effect of the news reports.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.29.20046565",
+    "rel_abs": "BackgroundThe outbreak of COVID-19 in China in early 2020 provides a rich data source for exploring the ecological determinants of this new infection, which may be of relevance elsewhere.\n\nObjectivesAssessing the spread of the COVID-19 across China, in relation to associations between cases and ecological factors including population density, temperature, solar radiation and precipitation.\n\nMethodsOpen-access COVID-19 case data include 18,069 geo-located cases in China during January and February 2020, which were mapped onto a 0.25{degrees} latitude/longitude grid together with population and weather data (temperature, solar radiation and precipitation). Of 15,539 grid cells, 559 (3.6%) contained at least one case, and these were used to construct a Poisson regression model of cell-weeks. Weather parameters were taken for the preceding week given the established 5-7 day incubation period for COVID-19. The dependent variable in the Poisson model was incident cases per cell-week and exposure was cell population, allowing for clustering of cells over weeks, to give incidence rate ratios.\n\nResultsThe overall COVID-19 incidence rate in cells with confirmed cases was 0.12 per 1,000. There was a single case in 113/559 (20.2%) of cells, while two grid cells recorded over 1,000 cases. Weekly means of maximum daily temperature varied from -28.0 to 30.1 {degrees}C, minimum daily temperature from -42.4 to 23.0 {degrees}C, maximum solar radiation from 0.04 to 2.74 MJm-2 and total precipitation from 0 to 72.6 mm. Adjusted incidence rate ratios suggested brighter, warmer and drier conditions were associated with lower incidence.\n\nConclusionThough not demonstrating cause and effect, there were appreciable associations between weather and COVID-19 incidence during the epidemic in China. This does not mean the pandemic will go away with summer weather but demonstrates the importance of using weather conditions in understanding and forecasting the spread of COVID-19.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Qian Liu",
-        "author_inst": "School of Journalism and Communication, National Media Experimental Teaching Demonstration Center, Jinan University, Guangzhou, China; Department of Communicati"
-      },
-      {
-        "author_name": "Zequan Zheng",
-        "author_inst": "International School, Jinan University, China; Faculty of Medicine, Jinan University, China"
-      },
-      {
-        "author_name": "Jiabin Zheng",
-        "author_inst": "International School, Jinan University, China; Faculty of Medicine, Jinan University, China"
-      },
-      {
-        "author_name": "Qiuyi Chen",
-        "author_inst": "School of Journalism and Communication, National Media Experimental Teaching Demonstration Center, Jinan University, Guangzhou, China"
-      },
-      {
-        "author_name": "Guan Liu",
-        "author_inst": "Faculty of Computer Centre, Jinan University, China"
-      },
-      {
-        "author_name": "Sihan Chen",
-        "author_inst": "International School, Jinan University, China"
-      },
-      {
-        "author_name": "Bojia Chu",
-        "author_inst": "International School, Jinan University, China"
-      },
-      {
-        "author_name": "Hongyu Zhu",
-        "author_inst": "International School, Jinan University, China"
-      },
-      {
-        "author_name": "Babatunde Akinwunmi",
-        "author_inst": "Pulmonary and Critical Care Medicine Unit, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard University, Boston, Massachuset"
-      },
-      {
-        "author_name": "Jian Huang",
-        "author_inst": "MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk"
-      },
-      {
-        "author_name": "Casper J. P. Zhang",
-        "author_inst": "School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China"
-      },
-      {
-        "author_name": "Wai-kit Ming",
-        "author_inst": "Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China"
+        "author_name": "Peter Byass",
+        "author_inst": "Umea University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "public and global health"
   },
@@ -1533452,41 +1536897,25 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.27.20043299",
-    "rel_title": "Failed detection of the full-length genome of SARS-CoV-2 by ultra-deep sequencing from the recovered and discharged patients retested viral PCR positive",
+    "rel_doi": "10.1101/2020.03.25.20043505",
+    "rel_title": "Machine Learning Approach for Confirmation of COVID-19 Cases: Positive, Negative, Death and Release",
     "rel_date": "2020-03-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20043299",
-    "rel_abs": "Over 10 percent of recovered and discharged patients retested positive for SARS-CoV-2, raising a public health concern whether they could be potential origins of infection. In this study, we found that detectable viral genome in discharged patients might only mean the presence of viral fragments, and could hardly form an infection origin for its extremely low concentration.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043505",
+    "rel_abs": "In recent days, Covid-19 coronavirus has been an immense impact on social, economic fields in the world. The objective of this study determines if it is feasible to use machine learning method to evaluate how much prediction results are close to original data related to Confirmed-Negative-Released-Death cases of Covid-19. For this purpose, a verification method is proposed in this paper that uses the concept of Deep-learning Neural Network. In this framework, Long short-term memory (LSTM) and Gated Recurrent Unit (GRU) are also assimilated finally for training the dataset and the prediction results are tally with the results predicted by clinical doctors. The prediction results are validated against the original data based on some predefined metric. The experimental results showcase that the proposed approach is useful in generating suitable results based on the critical disease outbreak. It also helps doctors to recheck further verification of virus by the proposed method. The outbreak of Coronavirus has the nature of exponential growth and so it is difficult to control with limited clinical persons for handling a huge number of patients with in a reasonable time. So it is necessary to build an automated model, based on machine learning approach, for corrective measure after the decision of clinical doctors. It could be a promising supplementary confirmation method for frontline clinical doctors. The proposed method has a high prediction rate and works fast for probable accurate identification of the disease. The performance analysis shows that a high rate of accuracy is obtained by the proposed method.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Fengyu Hu",
-        "author_inst": "Guangzhou Eighth People Hospital"
-      },
-      {
-        "author_name": "Fengjuan Chen",
-        "author_inst": "Guangzhou Eighth People Hospital"
-      },
-      {
-        "author_name": "Yaping Wang",
-        "author_inst": "Guangzhou Eighth People Hospital"
-      },
-      {
-        "author_name": "Teng Xu",
-        "author_inst": "Vision Medicals"
-      },
-      {
-        "author_name": "Xiaoping Tang",
-        "author_inst": "Guangzhou Eighth People Hospital"
+        "author_name": "Samir Kumar Bandyopadhyay Sr.",
+        "author_inst": "The Bhawanipur Education Society College, Kolkata, India"
       },
       {
-        "author_name": "Feng Li",
-        "author_inst": "Guangzhou Eighth People Hospital"
+        "author_name": "Shawni Dutta Jr.",
+        "author_inst": "The Bhawanipur Education Society College, Kolkata, India"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc0_ng",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1534794,35 +1538223,35 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.27.20045252",
-    "rel_title": "Estimation of protection for COVID-19 in children from epidemiological information and estimate effect of policy in Japan",
+    "rel_doi": "10.1101/2020.03.27.20044958",
+    "rel_title": "Research on the Influence of Effective Distance Between Cities on the Cross-regional Transmission of COVID-19",
     "rel_date": "2020-03-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20045252",
-    "rel_abs": "BackgroundIncidence in children was much less than in adults during the COVID-19 outbreak. Sports and entertainment events were canceled (VEC) in Japan for two weeks during 26 February - 13 March. Most schools were closed (SC).\n\nObjectWe construct a susceptible-infected-recovered model using three age classes and estimate the basic reproduction number (R0) and protection level among children simultaneously. Then we simulate SC and VEC effects.\n\nMethodWe used data of patients with symptoms in Japan during 14 January to assess SC and VEC introduction. Effects of SC and VEC were incorporated into the model through change in the contact pattern or frequencies among age classes.\n\nResultsResults suggest R0 as 2.86 [95%CI of 2.73, 2.97]. The protection level was estimated as 0.4 [0.2, 0.7]. SC and VEC can reduce the total number of patients significantly, by 6-7%.\n\nDiscussion and ConclusionThe estimated R0 was similar to that found from other studies in China and Japan. We found a significant protection level among children, and by effects of SC and VEC. Introduction",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20044958",
+    "rel_abs": "The COVID-19 epidemic in China has been effectively controlled. It is of great significance to study the law of cross-regional spread of the epidemic, for the prevention and control of the COVID-19 in the future in China and other countries or regions. In this study, the cross-regional connection intensity between cities was characterized based on the probability and the effective distance of the shortest path tree, and the empirical analysis was carried out based on the high-frequency data such as the cases of COVID 19 outbreaks. It is concluded that the higher the intensity of inter-city connection, the larger scale the cross-regional spread of the epidemic.",
     "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Junko Kurita",
-        "author_inst": "Center for Medical Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan"
+        "author_name": "Shanlang Lin",
+        "author_inst": "School of Economics and Management,Tongji University"
       },
       {
-        "author_name": "Yoshiyuki Sugishita",
-        "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan"
+        "author_name": "Yanning Qiao",
+        "author_inst": "School of economics and management, tongji university"
       },
       {
-        "author_name": "Tamie Sugawara",
-        "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan"
+        "author_name": "Junpei Huang",
+        "author_inst": "School of economics and management, tongji university"
       },
       {
-        "author_name": "Yasushi Ohkusa",
-        "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan"
+        "author_name": "Na Yan",
+        "author_inst": "School of economics and management, tongji university"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "health economics"
   },
   {
     "rel_doi": "10.1101/2020.03.26.20044842",
@@ -1536212,17 +1539641,29 @@
     "category": "health economics"
   },
   {
-    "rel_doi": "10.1101/2020.03.26.20044388",
-    "rel_title": "The more I fear about COVID-19, the more I wear medical masks: A survey on risk perception and medical masks uses",
+    "rel_doi": "10.1101/2020.03.28.20046110",
+    "rel_title": "Which Measures are Effective in Containing COVID-19?Empirical Research Based on Prevention and Control Cases in China",
     "rel_date": "2020-03-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044388",
-    "rel_abs": "The legal behaviors in using medical masks in public have been finally promulgated by the Vietnamese Government after 47 days since the WHO declared the Public Health Emergency of International Concern (PHEIC) due to the COVID-19 pandemic. From a sample of 345 Vietnamese respondents aged from 15 to 47 years, this brief note found that the risk perception of COVID-19 danger significantly increases the likelihood of wearing the medical masks. In addition, there is a weak evidence about the differences in age under the COVID-19 outbreaks. More noticeably, those who use masks before COVID-19 pandemic tend to maintain their behaviors. Our results offer the insightful into Vietnamese citizens responses in terms of using medical masks; even the uses of this method are still controversial. Our results are robust by performing Exploratory Factor Analysis for five features and further regressions.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.28.20046110",
+    "rel_abs": "Various epidemic prevention and control measures aimed at reducing person-to-person contact has paid a certain cost while controlling the epidemic. So accurate evaluation of these measures helps to maximize the effectiveness of prevention and control while minimizing social costs. In this paper, we develop the model in Dirk Brockmann and Dirk Helbing (2013) to theoretically explain the impact mechanism of traffic control and social distancing measures on the spread of the epidemic, and empirically tests the effect of the two measures in China at the present stage using econometric approach. We found that both traffic control and social distancing measures have played a very good role in controlling the development of the epidemic. Nationally, social distancing measures are better than traffic control measures; the two measures are complementary and their combined action will play a better epidemic prevention effect; Traffic control and social distancing do not work everywhere. Traffic control only works in cities with higher GDP per capita and population size, while fails in cities with lower GDP per capita and population size. In cities with lower population size, social distancing becomes inoperative; the rapid and accurate transmission of information, a higher protection awareness of the public, and a stronger confidence of residents in epidemic prevention can promote the realization of the measure effects. The findings above verify the effectiveness and correctness of the measures implemented in China at present, at the same time, we propose that it is necessary to fully consider the respective characteristics of the two measures, cooperating and complementing each other; whats more, measures should be formulated according to the citys own situation, achieving precise epidemic prevention; Finally, we should increase the transparency of information, improve protection awareness of the public, guide emotions of the public in a proper way, enhancing public confidence.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Toan D Huynh",
-        "author_inst": "University of Economics HCMC"
+        "author_name": "Shanlang Lin",
+        "author_inst": "Tongji University"
+      },
+      {
+        "author_name": "Junpei Huang",
+        "author_inst": "Tongji University"
+      },
+      {
+        "author_name": "Ziwen He",
+        "author_inst": "School of economics and management, tongji university"
+      },
+      {
+        "author_name": "Dandan Zhan",
+        "author_inst": "251227468@qq.com"
       }
     ],
     "version": "1",
@@ -1537526,27 +1540967,27 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.26.20044651",
-    "rel_title": "A deductive approach to modeling the spread of COVID-19",
+    "rel_doi": "10.1101/2020.03.25.20043927",
+    "rel_title": "Dangers of ACE inhibitor and ARB usage in COVID-19: evaluating the evidence",
     "rel_date": "2020-03-30",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044651",
-    "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), previously known as 2019-nCoV, is responsible for the atypical pneumonia pandemic designated as Coronavirus Disease 2019 (COVID-19). The number of cases continues to grow exponentially reaching 492,000 people in 175 countries as of March 25, 2020. 22,169 people ([~]4.5%) infected with SARS-COV-2 virus have died. We have developed an exponential regression model using the COVID-19 case data (Jan 22 - Mar 22, 2020). Our primary model uses designated Phase 1 countries, who exceed 2500 cases on Mar 22. The model is then applied to Phase 2 countries: those that escaped the initial Phase 1 global expansion of COVID-19. With the exception of stabilizing countries (South Korea, Japan, and Iran) all Phase 1 countries are growing exponentially, as per I2500(t) = 120.4 x e0.238t, with a rate, r = 0.238 {+/-} 0.068. Excluding China, the BRICS developing nations and Australia are in Phase 2. Case data from Phase 2 countries are following the model derived from Phase 1 countries. In the absence of measures employed to flatten the curve including social distancing, quarantine, and healthcare expansion, our model projects over 274,000 cases and 12,300 deaths in the US by Mar 31. India can expect 123,000 cases by April 16. By flattening the curve to the growth rate of stabilizing countries (r = 0.044 {+/-} 0.062), the US would prevent 8,500 deaths by Mar 31, and India would prevent 5,500 deaths by April 16.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043927",
+    "rel_abs": "BackgroundConcerns have been raised regarding the safety of Angiotensin Converting Enzyme Inhibitors (ACEIs) and Angiotensin Receptor Blockers (ARBs) in patients with COVID-19, based on the hypothesis that such medications may raise expression of ACE2, the receptor for SARS-CoV-2.\n\nMethodsWe conducted a literature review of studies (n=12) in experimental animals and human subjects (n=12) and evaluated the evidence regarding the impact of administration of ACEIs and ARBs on ACE2 expression. We prioritized studies that assessed ACE2 protein expression data, measured directly or inferred from ACE2 activity assays.\n\nResultsThe findings in animals are inconsistent with respect to an increase in ACE2 expression in response to treatment with ACEIs or ARBs. Control/sham animals show little to no effect in the plurality of studies. Those studies that report increases in ACE2 expression tend to involve acute injury models and/or higher doses of ACEIs or ARBS than are typically administered to patients. Data from human studies overwhelmingly imply that administration of ACEIs/ARBs does not increase ACE2 expression.\n\nConclusionAvailable evidence, in particular, data from human studies, does not support the hypothesis that ACEI/ARB use increases ACE2 expression and the risk of complications from COVID-19. We conclude that patients being treated with ACEIs and ARBs should continue their use for approved indications.",
     "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Pranav Kumar Mishra",
-        "author_inst": "Kasturba Medical College, Manipal; Manipal Academy of Higher Education"
+        "author_name": "Krishna Sriram",
+        "author_inst": "University of California San Diego"
       },
       {
-        "author_name": "Shekhar Mishra",
-        "author_inst": "Discovery Science and Innovation Management"
+        "author_name": "Paul A. Insel",
+        "author_inst": "University of California San Diego"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "pharmacology and therapeutics"
   },
   {
     "rel_doi": "10.1101/2020.03.26.20044511",
@@ -1538864,27 +1542305,31 @@
     "category": "cell biology"
   },
   {
-    "rel_doi": "10.1101/2020.03.26.009605",
-    "rel_title": "Re-analysis of SARS-CoV-2 infected host cell proteomics time-course data by impact pathway analysis and network analysis. A potential link with inflammatory response.",
+    "rel_doi": "10.1101/2020.03.27.012906",
+    "rel_title": "RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses",
     "rel_date": "2020-03-28",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.26.009605",
-    "rel_abs": "The disease known as coronavirus disease 19 (COVID-19), potentially caused by an outbreak of the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) in Wuhan, China, has hit the world hard, and has led to an unprecedent health and economic crisis. In order to develop treatment options able to stop or ameliorate SARS-CoV-2 effects, we need to understand the biology of the virus inside cells, but this kind of studies are still scarce. A recent study investigated translatome and proteome host cell changes induced in vitro by SARS-CoV-2. In the present study, we use the publicly available proteomics data from this study to re-analyze the mechanisms altered by the virus infection by impact pathways analysis and network analysis. Proteins linked to inflammatory response, but also proteins related to chromosome segregation during mitosis, were found to be regulated. The up-regulation of the inflammatory-related proteins observed could be linked to the propagation of inflammatory reaction and lung injury that is observed in advanced stages of COVID-19 patients.",
-    "rel_num_authors": 2,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.27.012906",
+    "rel_abs": "As the COVID-19 outbreak spreads, there is a growing need for a compilation of conserved RNA genome regions in the SARS-CoV-2 virus along with their structural propensities to guide development of antivirals and diagnostics. Using sequence alignments spanning a range of betacoronaviruses, we rank genomic regions by RNA sequence conservation, identifying 79 regions of length at least 15 nucleotides as exactly conserved over SARS-related complete genome sequences available near the beginning of the COVID-19 outbreak. We then confirm the conservation of the majority of these genome regions across 739 SARS-CoV-2 sequences reported to date from the current COVID-19 outbreak, and we present a curated list of 30  SARS-related-conserved regions. We find that known RNA structured elements curated as Rfam families and in prior literature are enriched in these conserved genome regions, and we predict additional conserved, stable secondary structures across the viral genome. We provide 106  SARS-CoV-2-conserved-structured regions as potential targets for antivirals that bind to structured RNA. We further provide detailed secondary structure models for the 5 UTR, frame-shifting element, and 3 UTR. Last, we predict regions of the SARS-CoV-2 viral genome have low propensity for RNA secondary structure and are conserved within SARS-CoV-2 strains. These 59  SARS-CoV-2-conserved-unstructured genomic regions may be most easily targeted in primer-based diagnostic and oligonucleotide-based therapeutic strategies.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Ignacio Ortea",
-        "author_inst": "Instituto de Investigacion e Innovacion Biomedica de Cadiz (INiBICA)"
+        "author_name": "Ramya Rangan",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Jens-Ole Bock",
-        "author_inst": "Cobo Technologies Aps"
+        "author_name": "Ivan N. Zheludev",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Rhiju Das",
+        "author_inst": "Stanford University"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "new results",
-    "category": "molecular biology"
+    "category": "genetics"
   },
   {
     "rel_doi": "10.1101/2020.03.24.20042598",
@@ -1540358,123 +1543803,27 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.24.20042234",
-    "rel_title": "Mechanical Ventilator Milano (MVM):A Novel Mechanical Ventilator Designed for Mass Scale Production in response to the COVID-19 Pandemics",
+    "rel_doi": "10.1101/2020.03.23.004176",
+    "rel_title": "Structure-based modeling of SARS-CoV-2 peptide/HLA-A02 antigens",
     "rel_date": "2020-03-27",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042234",
-    "rel_abs": "We present here the design of the Mechanical Ventilator Milano (MVM), a novel mechanical ventilator designed for mass scale production in response to the COVID-19 pandemics, to compensate for the dramatic shortage of such ventilators in many countries. This ventilator is an electro-mechanical equivalent of the old, reliable Manley Ventilator. Our design is optimized to permit large sale production in short time and at a limited cost, relying on off-the-shelf components, readily available worldwide from hardware suppliers. Operation of the MVM requires only a source of compressed oxygen (or compressed medical air) and electrical power. The MVM control and monitoring unit can be connected and networked via WiFi so that no additional electrical connections are necessary other than the connection to the electrical power.\n\nAt this stage the MVM is not a certified medical device. Construction of the first prototypes is starting with a team of engineers, scientists and computing experts. The purpose of this paper is to disseminate the conceptual design of the MVM broadly and to solicit feed-back from the scientific and medical community to speed the process of review, improvement and possible implementation.",
-    "rel_num_authors": 26,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.23.004176",
+    "rel_abs": "As a first step toward the development of diagnostic and therapeutic tools to fight the Coronavirus disease (COVID-19), it is important to characterize CD8+ T cell epitopes in the SARS-CoV-2 peptidome that can trigger adaptive immune responses. Here, we use RosettaMHC, a comparative modeling approach which leverages existing high-resolution X-ray structures from peptide/MHC complexes available in the Protein Data Bank, to derive physically realistic 3D models for high-affinity SARS-CoV-2 epitopes. We outline an application of our method to model 439 9mer and 279 10mer predicted epitopes displayed by the common allele HLA-A*02:01, and we make our models publicly available through an online database (https://rosettamhc.chemistry.ucsc.edu). As more detailed studies on antigen-specific T cell recognition become available, RosettaMHC models of antigens from different strains and HLA alleles can be used as a basis to understand the link between peptide/HLA complex structure and surface chemistry with immunogenicity, in the context of SARS-CoV-2 infection.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Galbiati Cristiano",
-        "author_inst": "Physics Department, Princeton University, Princeton, NJ 08544, USA"
-      },
-      {
-        "author_name": "Walter Bonivento",
-        "author_inst": "INFN Cagliari, Cagliari 09042, Italy"
-      },
-      {
-        "author_name": "Mauro Caravati",
-        "author_inst": "INFN Cagliari, Cagliari 09042, Italy"
-      },
-      {
-        "author_name": "Marco Razeti",
-        "author_inst": "INFN Cagliari, Cagliari 09042, Italy"
-      },
-      {
-        "author_name": "Sandro DeCecco",
-        "author_inst": "Physics Department, Sapienza Universit`a di Roma, Roma 00185, Italy and INFN Sezione di Roma, Roma 00185, Italy"
-      },
-      {
-        "author_name": "Giuliana Fiorillo",
-        "author_inst": "Physics Department, Universita degli Studi Federico II di Napoli, Napoli 80126, Italy and INFN Napoli, Napoli 80126, Italy"
-      },
-      {
-        "author_name": "Federico Gabriele",
-        "author_inst": "INFN Laboratori Nazionali del Gran Sasso, Assergi (AQ) 67100, Italy"
-      },
-      {
-        "author_name": "Roberto Tartaglia",
-        "author_inst": "INFN Laboratori Nazionali del Gran Sasso, Assergi (AQ) 67100, Italy"
-      },
-      {
-        "author_name": "Alessandro Razeto",
-        "author_inst": "INFN Laboratori Nazionali del Gran Sasso, Assergi (AQ) 67100, Italy"
-      },
-      {
-        "author_name": "Davide Sablone",
-        "author_inst": "INFN Laboratori Nazionali del Gran Sasso, Assergi (AQ) 67100, Italy"
-      },
-      {
-        "author_name": "Eugenio Scapparone",
-        "author_inst": "INFN Bologna, Bologna 40126, Italy"
-      },
-      {
-        "author_name": "Gemma Testera",
-        "author_inst": "INFN Genova, Genova 16146, Italy"
-      },
-      {
-        "author_name": "Marco Rescigno",
-        "author_inst": "INFN Sezione di Roma, Roma 00185, Italy"
-      },
-      {
-        "author_name": "Davide Franco",
-        "author_inst": "APC, Universite Paris Diderot, CNRS/IN2P3, CEA/Irfu, Obs de Paris, USPC, Paris 75205, France"
-      },
-      {
-        "author_name": "Iza Kochanek",
-        "author_inst": "INFN Laboratori Nazionali del Gran Sasso, Assergi (AQ) 67100, Italy"
-      },
-      {
-        "author_name": "Cary Kendziora",
-        "author_inst": "Fermi National Accelerator Laboratory, Batavia, IL 60510, USA"
-      },
-      {
-        "author_name": "Stephen H. Pordes",
-        "author_inst": "Fermi National Accelerator Laboratory, Batavia, IL 60510, USA"
-      },
-      {
-        "author_name": "Hanguo Wang",
-        "author_inst": "Physics and Astronomy Department, University of California, Los Angeles, CA 90095, USA"
-      },
-      {
-        "author_name": "Andrea Ianni",
-        "author_inst": "Physics Department, Princeton University, Princeton, NJ 08544, USA"
-      },
-      {
-        "author_name": "Art McDonald",
-        "author_inst": "Department of Physics, Engineering Physics and Astronomy, Queen s University, Kingston, ON K7L 3N6, Canada"
-      },
-      {
-        "author_name": "L. Molinari Tosatti",
-        "author_inst": "CNR STIIMA, Milano 20133, Italy"
-      },
-      {
-        "author_name": "T. Dinon",
-        "author_inst": "CNR STIIMA, Milano 20133, Italy"
-      },
-      {
-        "author_name": "M. Malosio",
-        "author_inst": "CNR STIIMA, Milano 20133, Italy"
-      },
-      {
-        "author_name": "D. Minuzzo",
-        "author_inst": "AZ Pneumatica S.r.l., Misinto (MB) 20826, Italy"
-      },
-      {
-        "author_name": "A. Zardoni",
-        "author_inst": "AZ Pneumatica S.r.l., Misinto (MB) 20826, Italy"
+        "author_name": "Santrupti Nerli",
+        "author_inst": "University of California, Santa Cruz"
       },
       {
-        "author_name": "A. Prini",
-        "author_inst": "CNR STIIMA, Milano 20133, Italy"
+        "author_name": "Nikolaos G Sgourakis",
+        "author_inst": "University of California, Santa Cruz"
       }
     ],
     "version": "1",
     "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "intensive care and critical care medicine"
+    "type": "new results",
+    "category": "immunology"
   },
   {
     "rel_doi": "10.1101/2020.03.24.005561",
@@ -1541804,67 +1545153,39 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2020.03.23.20041889",
-    "rel_title": "Coincidence of COVID-19 epidemic and olfactory dysfunction outbreak",
+    "rel_doi": "10.1101/2020.03.24.20042796",
+    "rel_title": "Reproducibility and reporting practices in COVID-19 preprint manuscripts",
     "rel_date": "2020-03-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.23.20041889",
-    "rel_abs": "BackgroundRecent surge of olfactory dysfunction in patients who were referred to ENT clinics and concurrent COVID-19epidemic in Iran motivated us to evaluate anosmic/hyposmic patients to find any relation between these two events.\n\nMethodsThis is a cross-sectional study with an online checklist on voluntary cases in all provinces of Iran between the 12th and 17th March, 2020. Cases was defined as self-reported anosmia/hyposmia in responders fewer than 4 weeks later (from start the of COVID-19 epidemic in Iran). Variables consist of clinical presentations, related past medical history, family history of recent respiratory tract infection and hospitalization.\n\nResultsIn this study 10069 participants aged 32.5{+/-}8.6 (7-78) years, 71.13% female and 81.68% non-smoker completed online checklist. They reported 10.55% a history of a trip out of home town and 1.1% hospitalization due to respiratory problems recently. From family members 12.17% had a history of severe respiratory disease in recent days and 48.23% had anosmia/hyposmia.\n\nCorrelation between the number of olfactory disorder and reported COVID-19 patients in all 31 provinces till 16th March 2020 was highly significant (Spearman correlation coefficient=0.87, p-Value<0.001). The onset of anosmia was sudden in 76.24% and till the time of filling the questionnaire in 60.90% of patients decreased sense of smell was constant. Also 83.38 of this patients had decreased taste sensation in association with anosmia.\n\nConclusionsIt seems that we have a surge in outbreak of olfactory dysfunction happened in Iran during the COVID-19 epidemic. The exact mechanism of anosmia/hyposmia in COVID-19 patients needs further investigations.",
-    "rel_num_authors": 12,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042796",
+    "rel_abs": "The novel coronavirus, COVID-19, has sparked an outflow of scientific research seeking to understand the virus, its spread, and best practices in prevention and treatment. If this international research effort is going to be as swift and effective as possible, it will need to rely on a principle of open science. When researchers share data, code, and software and generally make their work as transparent as possible, it allows other researchers to verify and expand upon their work. Furthermore, it allows public officials to make informed decisions. In this study, we analyzed 535 preprint articles related to COVID-19 for eight transparency criteria and recorded study location and funding information. We found that individual researchers have lined up to help during this crisis, quickly tackling important public health questions, often without funding or support from outside organizations. However, most authors could improve their data sharing and scientific reporting practices. The contrast between researchers commitment to doing important research and their reporting practices reveals underlying weaknesses in the research communitys reporting habits, but not necessarily their science.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Seyed Hamid Reza Bagheri",
-        "author_inst": "ENT and Head & Neck Research center and department, The five senses Institute, Iran University of Medical Sciences"
+        "author_name": "Josh Q Sumner",
+        "author_inst": "Ripeta, LLC"
       },
       {
-        "author_name": "Ali Mohammad Asghari",
-        "author_inst": "Skull base research center, The five senses institute, Iran University of Medical Sciences"
+        "author_name": "Leah Haynes",
+        "author_inst": "Ripeta, LLC"
       },
       {
-        "author_name": "Mohammad Farhadi",
-        "author_inst": "ENT and Head & Neck Research center and department, The five senses Institute, Iran University of Medical Sciences"
+        "author_name": "Sarah Nathan",
+        "author_inst": "Ripeta, LLC"
       },
       {
-        "author_name": "Ahmad Reza Shamshiri",
-        "author_inst": "Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences"
+        "author_name": "Cynthia Hudson-Vitale",
+        "author_inst": "Ripeta, LLC"
       },
       {
-        "author_name": "Ali Kabir",
-        "author_inst": "Minimally Invasive Surgery Research Center, Iran University of Medical Sciences"
-      },
-      {
-        "author_name": "Seyed Kamran Kamrava",
-        "author_inst": "ENT and Head & Neck Research center and department, The five senses Institute, Iran University of Medical Sciences"
-      },
-      {
-        "author_name": "Maryam Jalessi",
-        "author_inst": "Skull base research center, The five senses institute, Iran University of Medical Sciences"
-      },
-      {
-        "author_name": "Alireza Mohebbi",
-        "author_inst": "ENT and Head & Neck Research center and department, The five senses Institute, Iran University of Medical Sciences"
-      },
-      {
-        "author_name": "Rafieh Alizadeh",
-        "author_inst": "ENT and Head & Neck Research center and department, The five senses Institute, Iran University of Medical Sciences, Tehran"
-      },
-      {
-        "author_name": "Ali Asghar Honarmand",
-        "author_inst": "Electronic learning Committee, Iran Medical Council"
-      },
-      {
-        "author_name": "Babak Ghalehbaghi",
-        "author_inst": "Iran University of Medical Sciences"
-      },
-      {
-        "author_name": "Alireza Salimi",
-        "author_inst": "Department of anesthesiology, Shahid Beheshti University of Medical Sciences"
+        "author_name": "Leslie D McIntosh",
+        "author_inst": "Ripeta"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "otolaryngology"
+    "category": "health informatics"
   },
   {
     "rel_doi": "10.1101/2020.03.25.20042713",
@@ -1543406,37 +1546727,29 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.24.20042291",
-    "rel_title": "Fundamental principles of epidemic spread highlight the immediate need forlarge-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic",
+    "rel_doi": "10.1101/2020.03.24.20042705",
+    "rel_title": "Mathematical modeling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada",
     "rel_date": "2020-03-26",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042291",
-    "rel_abs": "The spread of a novel pathogenic infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the (first) epidemic wave. Before the implementation of control measures (e.g. social distancing, travel bans, etc) and under the assumption that infection elicits protective immunity, epidemiological theory indicates that the ongoing epidemic of SARS-CoV-2 will conform to this pattern.\n\nHere, we calibrate a susceptible-infected-recovered (SIR) model to data on cumulative reported SARS-CoV-2 associated deaths from the United Kingdom (UK) and Italy under the assumption that such deaths are well reported events that occur only in a vulnerable fraction of the population. We focus on model solutions which take into consideration previous estimates of critical epidemiological parameters such as the basic reproduction number (R0), probability of death in the vulnerable fraction of the population, infectious period and time from infection to death, with the intention of exploring the sensitivity of the system to the actual fraction of the population vulnerable to severe disease and death.\n\nOur simulations are in agreement with other studies that the current epidemic wave in the UK and Italy in the absence of interventions should have an approximate duration of 2-3 months, with numbers of deaths lagging behind in time relative to overall infections. Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries. There is an inverse relationship between the proportion currently immune and the fraction of the population vulnerable to severe disease.\n\nThis relationship can be used to determine how many people will require hospitalisation (and possibly die) in the coming weeks if we are able to accurately determine current levels of herd immunity. There is thus an urgent need for investment in technologies such as virus (or viral pseudotype) neutralization assays and other robust assays which provide reliable read-outs of protective immunity, and for the provision of open access to valuable data sources such as blood banks and paired samples of acute and convalescent sera from confirmed cases of SARS-CoV-2 to validate these. Urgent development and assessment of such tests should be followed by rapid implementation at scale to provide real-time data. These data will be critical to the proper assessment of the effects of social distancing and other measures currently being adopted to slow down the case incidence and for informing future policy direction.\n\nDisclaimer(a) This material is not final and is subject to be updated any time. (b) Code used will be made available as soon as possible. (c) Contact for press enquiries: Cairbre Sugrue, cairbre@sugruecomms.com, +44 (0)7502 203 769.",
-    "rel_num_authors": 5,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042705",
+    "rel_abs": "BackgroundWe evaluated how non-pharmaceutical interventions could be used to control the COVID-19 pandemic and reduce the burden on the healthcare system.\n\nMethodsUsing an age-structured compartmental model of COVID-19 transmission in the population of Ontario, Canada, we compared a base case with limited testing, isolation, and quarantine to scenarios with: enhanced case finding; restrictive social distancing measures; or a combination of enhanced case finding and less restrictive social distancing. Interventions were either implemented for fixed durations or dynamically cycled on and off, based on projected ICU bed occupancy. We present median and credible intervals (CrI) from 100 replicates per scenario using a two-year time horizon.\n\nResultsWe estimated that 56% (95% CrI: 42-63%) of the Ontario population would be infected over the course of the epidemic in the base case. At the epidemic peak, we projected 107,000 (95% CrI: 60,760-149,000) cases in hospital and 55,500 (95% CrI: 32,700-75,200) cases in ICU. For fixed duration scenarios, all interventions were projected to delay and reduce the height of the epidemic peak relative to the base case, with restrictive social distancing estimated to have the greatest effect. Longer duration interventions were more effective. Dynamic interventions were projected to reduce the proportion of the population infected at the end of the two-year period. Dynamic social distancing interventions could reduce the median number of cases in ICU below current estimates of Ontarios ICU capacity.\n\nInterpretationWithout significant social distancing or a combination of moderate social distancing with enhanced case finding, we project that ICU resources would be overwhelmed. Dynamic social distancing could maintain health system capacity and also allow periodic psychological and economic respite for populations.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Jose Lourenco",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Robert Paton",
-        "author_inst": "University of Oxford"
-      },
-      {
-        "author_name": "Craig Thompson",
-        "author_inst": "University of Oxford"
+        "author_name": "Ashleigh Tuite",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Paul Klenerman",
-        "author_inst": "University of Oxford"
+        "author_name": "David N Fisman",
+        "author_inst": "University of Toronto"
       },
       {
-        "author_name": "Sunetra Gupta",
-        "author_inst": "University of Oxford"
+        "author_name": "Amy L Greer",
+        "author_inst": "University of Guelph"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1545096,35 +1548409,67 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.21.20040139",
-    "rel_title": "Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19",
+    "rel_doi": "10.1101/2020.03.22.20034504",
+    "rel_title": "High risk of infection caused posttraumatic stress symptoms in individuals with poor sleep quality: A study on influence of coronavirus disease (COVID-19) in China",
     "rel_date": "2020-03-24",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.21.20040139",
-    "rel_abs": "BackgroundThe outbreak of the 2019 novel coronavirus (COVID-19) has attracted global attention. In the early stage of the outbreak, the most important question concerns some meaningful milepost moments, including (1) the time when the number of daily confirmed cases decreases, (2) the time when the number of daily confirmed cases becomes smaller than that of the daily removed (recovered and death), (3) the time when the number of daily confirmed cases becomes zero, and (4) the time when the number of patients treated in hospital is zero, which indicates the end of the epidemic. Intuitively, the former two can be regarded as two important turning points which indicate the alleviation of epidemic to some extent, while the latter two as two \"zero\" points, respectively. Unfortunately, it is extremely difficult to make right and precise prediction due to the limited amount of available data at a early stage of the outbreak.\n\nMethodTo address it, in this paper, we propose a flexible framework incorporating the effectiveness of the government control to forecast the whole process of a new unknown infectious disease in its early-outbreak. Specially, we first establish the iconic indicators to characterize the extent of epidemic spread, yielding four periods of the whole process corresponding to the four meaningful milepost moments: two turning points and two \"zero\" points. Then we develop the tracking and forecasting procedure with mild and reasonable assumption. Finally we apply it to analyze and evaluate the COVID-19 using the public available data for mainland China beyond Hubei Province from the China Centers for Disease Control (CDC) during the period of Jan 29th, 2020, to Feb 29th, 2020, which shows the effectiveness of the proposed procedure.\n\nResultsResults show that our model can clearly outline the development of the epidemic at a very early stage. The first prediction results on Jan 29th reveal that the first and second milepost moments for mainland China beyond Hubei Province would appear on Jan 31st and Feb 14th respectively, which are only one day and three days behind the real world situations. Forecasting results indicate that the number of newly confirmed cases will become zero in the mid-late March, and the number of patients treated in the hospital will become zero between mid-March and mid-April in mainland China beyond Hubei Province. The framework proposed in this paper can help people get a general understanding of the epidemic trends in counties where COVID-19 are raging as well as any other outbreaks of new and unknown infectious diseases in the future.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.22.20034504",
+    "rel_abs": "The influence of the outbreak of coronavirus disease (COVID-19) on mental health was poorly understood. The present study aimed to exam sleep problems and posttraumatic stress symptoms (PTSS) in Chinese immediately after the massive outbreak of COVID-19. A total of 2027 Chinese participated in the present study. Wuhan-expose history, sleep quality and PTSS were measured with self-rating scales. Results showed that there were significant differences of PCL-5 and of sleep quality scores in different data-collection dates (ps<0.05). There were significant differences of PCL-5 scores (t=-2.93, p<0.05) and latency onset of sleep ({chi}2=9.77, p<0.05) between participants with and without Wuhan-expose history. The interaction effect of Wuhan exposure historyx sleep quality significantly influenced PCL-5 (ps<0.05). These results indicate that keeping good sleep quality in individuals with high infectious risk is a way to prevent PTSS.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Huiwen Wang",
-        "author_inst": "School of Economics and Management, Beihang University, Beijing, China"
+        "author_name": "Fan Zhang",
+        "author_inst": "Naval Medical University"
       },
       {
-        "author_name": "Yanwen Zhang",
-        "author_inst": "School of Economics and Management, Beihang University, Beijing, China"
+        "author_name": "Zhilei Shang",
+        "author_inst": "Naval Medical University"
       },
       {
-        "author_name": "Shan Lu",
-        "author_inst": "School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, China"
+        "author_name": "Haiying Ma",
+        "author_inst": "Naval Medical University"
       },
       {
-        "author_name": "Shanshan Wang",
-        "author_inst": "School of Economics and Management, Beihang University"
+        "author_name": "Yanpu Jia",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Luna Sun",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Xin Guo",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Lili Wu",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Zhuoer Sun",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Yaoguang Zhou",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Yan Wang",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Nianqi Liu",
+        "author_inst": "Naval Medical University"
+      },
+      {
+        "author_name": "Weizhi Liu",
+        "author_inst": "Naval Medical University"
       }
     ],
     "version": "1",
     "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "psychiatry and clinical psychology"
   },
   {
     "rel_doi": "10.1101/2020.03.22.20040899",
@@ -1546722,29 +1550067,37 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.19.20032532",
-    "rel_title": "Geo temporal distribution of 1,688 Chinese healthcare workers infected with COVID-19 in severe conditions, a secondary data analysis",
+    "rel_doi": "10.1101/2020.03.19.20039404",
+    "rel_title": "Healthcare worker absenteeism, child care costs, and COVID-19 school closures: a simulation analysis",
     "rel_date": "2020-03-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20032532",
-    "rel_abs": "IntroductionThe COVID-19 outbreak is posing an unprecedented challenge to healthcare workers. This study analyzes the geo-temporal effects on disease severity for the 1,688 Chinese healthcare workers infected with COVID-19.\n\nMethodUsing the descriptive results recently reported by the Chinese CDC, we compare the percentage of infected healthcare workers in severe conditions over time and across three areas in China, and the fatality rate of infected healthcare workers with all the infected individuals in China aged 22-59 years.\n\nResultsAmong the infected Chinese healthcare workers whose symptoms onset appeared during the same ten-day period, the percentage of those in severe conditions decreased statistical significantly from 19.7% (Jan 11 - 20) to 14.4% (Jan 21 - 31) to 8.7% (Feb 1 - 11). Across the country, there was also a significant difference in the disease severity among patients symptoms onset during the same period, with Wuhan being the most severe (17%), followed by Hubei Province (10.4%), and the rest of China (7.0%). The case fatality rate for the 1,688 infected Chinese healthcare workers was significantly lower than that for the 29,798 infected patients aged 20-59 years--0.3% (5/1,688) vs. 0.65% (193/29,798), respectively.\n\nConclusionThe disease severity improved considerably over a short period of time in China. The more severe conditions in Wuhan compared to the rest of the country may be attributable to the draconian lockdown. The clinical outcomes of infected Chinese healthcare workers may represent a more accurate estimation of the severity of COVID-19 for those who have access to quality healthcare.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20039404",
+    "rel_abs": "BackgroundSchool closures have been enacted as a measure of mitigation during the ongoing COVID-19 pandemic. It has been shown that school closures could cause absenteeism amongst healthcare workers with dependent children, but there remains a need for spatially granular analyses of the relationship between school closures and healthcare worker absenteeism to inform local community preparedness.\n\nMethodsWe provide national- and county-level simulations of school closures and unmet child care needs across the United States. We develop individual simulations using county-level demographic and occupational data, and model school closure effectiveness with age-structured compartmental models. We perform multivariate quasi-Poisson ecological regressions to find associations between unmet child care needs and COVID-19 vulnerability factors.\n\nResultsAt the national level, we estimate the projected rate of unmet child care needs for healthcare worker households to range from 7.5% to 8.6%, and the effectiveness of school closures to range from 3.2% (R0 = 4) to 7.2% (R0 = 2) reduction in fewer ICU beds at peak demand. At the county-level, we find substantial variations of projected unmet child care needs and school closure effects, ranging from 1.9% to 18.3% of healthcare worker households and 5.7% to 8.8% reduction in fewer ICU beds at peak demand (R0 = 2). We find significant positive associations between estimated levels of unmet child care needs and diabetes prevalence, county rurality, and race (p < 0.05). We estimate costs of absenteeism and child care and observe from our models that an estimated 71.1% to 98.8% of counties would find it less expensive to provide child care to all healthcare workers with children than to bear the costs of healthcare worker absenteeism during school closures.\n\nConclusionsSchool closures are projected to reduce peak ICU bed demand, but could disrupt healthcare systems through absenteeism, especially in counties that are already particularly vulnerable to COVID-19. Child care subsidies could help circumvent the ostensible tradeoff between school closures and healthcare worker absenteeism.",
+    "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Wayne Gao",
-        "author_inst": "Taipei Medical University"
+        "author_name": "Elizabeth T Chin",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Mattia Sanna",
-        "author_inst": "Taipei Medical University"
+        "author_name": "Benjamin Q Huynh",
+        "author_inst": "Stanford University"
+      },
+      {
+        "author_name": "Nathan C Lo",
+        "author_inst": "University of California, San Francisco"
+      },
+      {
+        "author_name": "Trevor Hastie",
+        "author_inst": "Stanford University"
       },
       {
-        "author_name": "Chi Pang Wen",
-        "author_inst": "National Health Research Institute; China Medical University"
+        "author_name": "Sanjay Basu",
+        "author_inst": "Harvard Medical School"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1548136,71 +1551489,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.20.20039818",
-    "rel_title": "Potential Factors for Prediction of Disease Severity of COVID-19 Patients",
+    "rel_doi": "10.1101/2020.03.21.001933",
+    "rel_title": "SARS-CoV-2, an evolutionary perspective of interaction with human ACE2 reveals undiscovered amino acids necessary for complex stability",
     "rel_date": "2020-03-23",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.20.20039818",
-    "rel_abs": "ObjectiveCoronavirus disease 2019 (COVID-19) is an escalating global epidemic caused by SARS-CoV-2, with a high mortality in critical patients. Effective indicators for predicting disease severity in SARS-CoV-2 infected patients are urgently needed.\n\nMethodsIn this study, 43 COVID-19 patients admitted in Chongqing Public Health Medical Center were involved. Demographic data, clinical features, and laboratory examinations were obtained through electronic medical records. Peripheral blood specimens were collected from COVID-19 patients and examined for lymphocyte subsets and cytokine profiles by flow cytometry. Potential contributing factors for prediction of disease severity were further analyzed.\n\nResultsA total of 43 COVID-19 patients were included in this study, including 29 mild patients and 14 sever patients. Severe patients were significantly older (61.9{+/-}9.4 vs 44.4{+/-}15.9) and had higher incidence in co-infection with bacteria compared to mild group (85.7%vs27.6%). Significantly more severe patients had the clinical symptoms of anhelation (78.6%) and asthma (71.4%). For laboratory examination, 57.1% severe cases showed significant reduction in lymphocyte count. The levels of Interluekin-6 (IL6), IL10, erythrocyte sedimentation rate (ESR) and D-Dimer (D-D) were significantly higher in severe patients than mild patients, while the level of albumin (ALB) was remarkably lower in severe patients. Further analysis demonstrated that ESR, D-D, age, ALB and IL6 were the major contributing factors for distinguishing severe patients from mild patients. Moreover, ESR was identified as the most powerful factor to predict disease progression of COVID-19 patients.\n\nConclusionAge and the levels of ESR, D-D, ALB and IL6 are closely related to the disease severity of COVID-19 patients. ESR can be used as a valuable indicator for distinguishing severe COVID-19 patients in early stage, so as to increase the survival of severe patients.",
-    "rel_num_authors": 13,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.21.001933",
+    "rel_abs": "The emergence of SARS-CoV-2 has resulted in more than 200,000 infections and nearly 9,000 deaths globally so far. This novel virus is thought to have originated from an animal reservoir, and acquired the ability to infect human cells using the SARS-CoV cell receptor hACE2. In the wake of a global pandemic it is essential to improve our understanding of the evolutionary dynamics surrounding the origin and spread of a novel infectious disease. One way theory predicts selection pressures should shape viral evolution is to enhance binding with host cells. We first assessed evolutionary dynamics in select betacoronavirus spike protein genes to predict where these genomic regions are under directional or purifying selection between divergent viral lineages at various scales of relatedness. With this analysis, we determine a region inside the receptor-binding domain with putative sites under positive selection interspersed among highly conserved sites, which are implicated in structural stability of the viral spike protein and its union with human receptor hACE2. Next, to gain further insights into factors associated with coronaviruses recognition of the human host receptor, we performed modeling studies of five different coronaviruses and their potential binding to hACE2. Modeling results indicate that interfering with the salt bridges at hot spot 353 could be an effective strategy for inhibiting binding, and hence for the prevention of coronavirus infections. We also propose that a glycine residue at the receptor binding domain of the spike glycoprotein can have a critical role in permitting bat variants of the coronaviruses to infect human cells.",
+    "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "huizheng zhang",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "xiaoying wang",
-        "author_inst": "Chongqing Medical and Pharmaceutical College"
-      },
-      {
-        "author_name": "zongqiang fu",
-        "author_inst": "Henan Province hospital of traditional chinese"
+        "author_name": "Vinicio Armijos-Jaramillo",
+        "author_inst": "Universidad de Las Americas-Quito"
       },
       {
-        "author_name": "ming luo",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "zhen zhang",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "ke zhang",
-        "author_inst": "Chongqing emergency center"
+        "author_name": "Justin Yeager",
+        "author_inst": "Universidad de Las Americas-Quito"
       },
       {
-        "author_name": "ying he",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "dongyong wan",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "liwen zhang",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "jing wang",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "xiaofeng yan",
-        "author_inst": "Chongqing Public Health Medical Center"
+        "author_name": "Claire Muslin",
+        "author_inst": "Universidad de Las Americas-Quito"
       },
       {
-        "author_name": "mei han",
-        "author_inst": "Chongqing Public Health Medical Center"
-      },
-      {
-        "author_name": "yaokai chen",
-        "author_inst": "Chongqing Public Health Medical Center"
+        "author_name": "Yunierkis Perez-Castillo",
+        "author_inst": "Universidad de Las Americas-Quito"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.03.20.000885",
@@ -1550090,29 +1553407,21 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.16.20036939",
-    "rel_title": "COVID-19: Forecasting short term hospital needs in France",
+    "rel_doi": "10.1101/2020.03.14.20035659",
+    "rel_title": "Maximum entropy method for estimating the reproduction number: An investigation for COVID-19 in China",
     "rel_date": "2020-03-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.16.20036939",
-    "rel_abs": "1Europe is now considered as the epicenter of the SARS-CoV-2 pandemic, France being among the most impacted country. In France, there is an increasing concern regarding the capacity of the healthcare system to sustain the outbreak, especially regarding intensive care units (ICU). The aim of this study was to estimate the dynamics of the epidemic in France, and to assess its impact on healthcare resources for each French metropolitan Region. We developed a deterministic, age-structured, Susceptible-Exposed-Infectious-Removed (SEIR) model based on catchment areas of each COVID-19 referral hospitals. We performed one month ahead predictions (up to April 14, 2020) for three different scenarios (R0 = 1.5, R0 = 2.25, R0 = 3), where we estimated the daily number of COVID-19 cases, hospitalizations and deaths, the needs in ICU beds per Region and the reaching date of ICU capacity limits. At the national level, the total number of infected cases is expected to range from 22,872 in the best case (R0 = 1.5) to 161,832 in the worst case (R0 = 3), while the total number of deaths would vary from 1,021 to 11,032, respectively. At the regional level, all ICU capacities may be overrun in the worst scenario. Only seven Regions may lack ICU beds in the mild scenario (R0 = 2.25) and only one in the best case. In the three scenarios, Corse may be the first Region to see its ICU capacities overrun. The two other Regions, whose capacity will be overrun shortly after are Grand-Est and Bourgogne-Franche-Comte. Our analysis shows that, even in the best case scenario, the French healthcare system will very soon be overwhelmed. While drastic social distancing measures may temper our results, a massive reorganization leading to an expansion of French ICU capacities seems to be necessary to manage the coming wave of critically affected COVID-19 patients.",
-    "rel_num_authors": 3,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.14.20035659",
+    "rel_abs": "The key parameter that characterizes the transmissibility of a disease is the reproduction number R. If it exceeds 1, the number of incident cases will inevitably grow over time, and a large epidemic is possible. To prevent the expansion of an epidemic, R must be reduced to a level below 1. To estimate the reproduction number, the probability distribution function of the generation interval of an infectious disease is required to be available; however, this distribution is often unknown. In this letter, given the incomplete information for the generation interval, we propose a maximum entropy method to estimate the reproduction number. Based on this method, given the mean value and variance of the generation interval, we first determine its probability distribution function and in turn estimate the real-time values of reproduction number of COVID-19 in China. By applying these estimated reproduction numbers into the susceptible-infectious-removed epidemic model, we simulate the evolutionary track of the epidemic in China, which is well in accordance with that of the real incident cases. The simulation results predict that Chinas epidemic will gradually tend to disappear by May 2020 if the quarantine measures can continue to be executed.",
+    "rel_num_authors": 1,
     "rel_authors": [
       {
-        "author_name": "Cl\u00e9ment Massonnaud",
-        "author_inst": "Univ Rennes, EHESP, REPERES - EA 7449; Rouen University Hospital, Department of Biostatistics"
-      },
-      {
-        "author_name": "Jonathan Roux",
-        "author_inst": "Univ Rennes, EHESP, REPERES - EA 7449"
-      },
-      {
-        "author_name": "Pascal Cr\u00e9pey",
-        "author_inst": "Univ Rennes, EHESP, REPERES - EA 7449"
+        "author_name": "Yong Tao",
+        "author_inst": "Southwest University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1551360,89 +1554669,57 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.16.20037135",
-    "rel_title": "Hydroxychloroquine and Azithromycin as a treatment of COVID-19: preliminary results of an open-label non-randomized clinical trial",
+    "rel_doi": "10.1101/2020.03.19.20038844",
+    "rel_title": "A framework for identifying regional outbreak and spread of COVID-19 from one-minute population-wide surveys",
     "rel_date": "2020-03-20",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.16.20037135",
-    "rel_abs": "BackgroundChloroquine and hydroxychloroquine have been found to be efficient on SARS-CoV-2, and reported to be efficient in Chinese COV-19 patients. We evaluate the role of hydroxychloroquine on respiratory viral loads.\n\nPatients and methodsPatients were included in a single arm protocol to receive 600mg of hydroxychloroquine daily and their viral load in nasal swabs was tested daily. Depending on their clinical presentation, azithromycin was added to the treatment. Untreated patients from another center and cases refusing the protocol were included as negative controls. Presence and absence of virus at Day6-post inclusion was considered the end point.\n\nResultsTwenty cases were treated in this study and showed a significant reduction of the viral carriage at D6-post inclusion compared to controls, and much lower average carrying duration than reported of untreated patients in the literature. Azithromycin added to hydroxychloroquine was significantly more efficient for virus elimination.\n\nConclusionHydroxychloroquine is significantly associated with viral load reduction/disappearance in COVID-19 patients and its effect is reinforced by azithromycin.",
-    "rel_num_authors": 18,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20038844",
+    "rel_abs": "Coronavirus infection spreads in clusters and therefore early identification of these clusters is critical for slowing down the spread of the virus. Here, we propose that daily population-wide surveys that assess the development of symptoms caused by the virus could serve as a strategic and valuable tool for identifying such clusters to inform epidemiologists, public health officials, and policy makers. We show preliminary results from a survey of over 58,000 Israelis and call for an international consortium to extend this concept in order to develop predictive models. We expect such data to allow: Faster detection of spreading zones and patients; Obtaining a current snapshot of the number of people in each area who have developed symptoms; Predicting future spreading zones several days before an outbreak occurs; Evaluating the effectiveness of the various social distancing measures taken, and their contribution to reduce the number of symptomatic people. Such information can provide a valuable tool for decision makers to decide which areas need strengthening of social distancing measures and which areas can be relieved. Preliminary analysis shows that in neighborhoods with confirmed COVID-19 patient history, more responders report on COVID-19 associated symptoms, demonstrating the potential utility of our approach for detection of outbreaks. Researchers from other countries including the U.S, India, Italy, Spain, Germany, Mexico, Finland, Sweden, Norway and several others have adopted our approach and we are collaborating to further improve it. We call with urgency for other countries to join this international consortium, and to share methods and data collected from these daily, simple, one-minute surveys.",
+    "rel_num_authors": 10,
     "rel_authors": [
       {
-        "author_name": "Philippe GAUTRET",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
-      },
-      {
-        "author_name": "Jean Christophe LAGIER",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
-      },
-      {
-        "author_name": "Philippe PAROLA",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
-      },
-      {
-        "author_name": "Van Thuan HOANG",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
-      },
-      {
-        "author_name": "Line MEDDED",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
-      },
-      {
-        "author_name": "Morgan MAILHE",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
-      },
-      {
-        "author_name": "Barbara DOUDIER",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
-      },
-      {
-        "author_name": "Johan COURJON",
-        "author_inst": "Centre Hospitalier Universitaire de Nice"
-      },
-      {
-        "author_name": "Valerie GIORDANENGO",
-        "author_inst": "Centre Hospitalier Universitaire de Nice"
+        "author_name": "Hagai Rossman",
+        "author_inst": "Weizmann institute of science"
       },
       {
-        "author_name": "Vera ESTEVES VIEIRA",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
+        "author_name": "Ayya Keshet",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Herve TISSOT DUPONT",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
+        "author_name": "Smadar Shilo",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Stephane HONORE",
-        "author_inst": "Aix Marseille University"
+        "author_name": "Amir Gavrieli",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Philippe COLSON",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
+        "author_name": "Tal Bauman",
+        "author_inst": "Technion"
       },
       {
-        "author_name": "Eric CHABRIERE",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
+        "author_name": "Ori Cohen",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Bernard LA SCOLA",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
+        "author_name": "Ran Balicer",
+        "author_inst": "Clalit Research Institute"
       },
       {
-        "author_name": "Jean Marc ROLAIN",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
+        "author_name": "Benjamin Geiger",
+        "author_inst": "Weizmann Institute of Science"
       },
       {
-        "author_name": "Philippe BROUQUI",
-        "author_inst": "Aix Marseille University IHU Mediterranee Infection"
+        "author_name": "Yuval Dor",
+        "author_inst": "The Hebrew University of Jerusalem"
       },
       {
-        "author_name": "Didier RAOULT Sr.",
-        "author_inst": "IHU Mediterrane Infection, Aix Marseille University"
+        "author_name": "Eran Segal",
+        "author_inst": "Weizmann Institute of Science"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1553030,16 +1556307,16 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.15.20036368",
-    "rel_title": "Coronavirus disease-19: The First 7,755 Cases in the Republic of Korea",
+    "rel_doi": "10.1101/2020.03.15.20036350",
+    "rel_title": "Coronavirus disease-19: Summary of 2,370 Contact Investigations of the First 30 Cases in the Republic of Korea",
     "rel_date": "2020-03-18",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.15.20036368",
-    "rel_abs": "We report the first 7,755 patients with confirmed COVID-19 in Korea as of March 13, 2020. A total of 66 deaths were identified, resulting case fatality proportion of 0.9%. Older people, and those with coexisting medical conditions were at risk for fatal outcomes. The highest number of cases were from Daegu, followed by Gyeongbuk, with elevated age-stratified case fatality. This summary may help to understand the disease dynamics in the early phase of COVID-19 outbreak, therefore, to guide future public health measures.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.15.20036350",
+    "rel_abs": "Between January 24 and March 10, of a total of 2,370 individuals who had contacted the first 30 cases of COVID-19, 13 were found to have COVID-19, resulting secondary attack rate of 0.55% (95% CI 0.31 - 0.96). Of 119 household contacts, 9 had infections resulting secondary attack rate of 7.56 (95% CI 3.73 - 14.26).",
     "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "- COVID-19 National Emergency Response Center Korea Centers for Disease Control and Prevention",
+        "author_name": "- Korea Centers for Disease Control and Prevention COVID-19 National Emergency Response Center",
         "author_inst": "-"
       },
       {
@@ -1554604,55 +1557881,79 @@
     "category": "genomics"
   },
   {
-    "rel_doi": "10.1101/2020.03.15.20035204",
-    "rel_title": "International expansion of a novel SARS-CoV-2 mutant",
+    "rel_doi": "10.1101/2020.03.10.986711",
+    "rel_title": "Efficient inactivation of SARS-CoV-2 by WHO-recommended hand rub formulations and alcohols",
     "rel_date": "2020-03-17",
-    "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.15.20035204",
-    "rel_abs": "Letter to the editor. There is no abstract. The summary was showed: SARS-CoV-2 has inevitably mutated during its pandemic spread to cause unpredictable effects on COVID-19 and complicate epidemic control efforts. Here we report that a novel SARS-CoV-2 mutation (ORF3a) appears to be spreading worldwide, which deserves close attention.",
-    "rel_num_authors": 9,
+    "rel_site": "bioRxiv",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.10.986711",
+    "rel_abs": "The recent emergence of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19 is a major burden for health care systems worldwide. It is important to address if the current infection control instructions based on active ingredients are sufficient. We therefore determined the virucidal activity of two alcohol-based hand rub solutions for hand disinfection recommended by the World Health Organization (WHO), as well as commercially available alcohols. Efficient SARS-CoV-2 inactivation was demonstrated for all tested alcohol-based disinfectants. These findings show the successful inactivation of SARS-CoV-2 for the first time and provide confidence in its use for the control of COVID-19.\n\nImportanceThe current COVID-19 outbreak puts a huge burden on the worlds health care systems. Without effective therapeutics or vaccines being available, effective hygiene measure are of utmost importance to prevent viral spreading. It is therefore crucial to evaluate current infection control strategies against SARS-CoV-2. We show the inactivation of the novel coronavirus for the first time and endorse the importance of disinfectant-based hand hygiene to reduce SARS-CoV-2 transmission.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Minjin Wang",
-        "author_inst": "Department of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, China"
+        "author_name": "Annika Kratzel",
+        "author_inst": "Institute of Virology and Immunology, Bern and Mittelh\u00e4usern, Switzerland"
       },
       {
-        "author_name": "Mengjiao Li",
-        "author_inst": "Department of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, China"
+        "author_name": "Daniel Todt",
+        "author_inst": "Department of Molecular and Medical Virology, Ruhr-University Bochum"
       },
       {
-        "author_name": "Ruotong Ren",
-        "author_inst": "1. Genskey Biotechnology Co., Ltd.    2. Department of Hematology, The First Hospital of Lanzhou University"
+        "author_name": "Silvio Steiner",
+        "author_inst": "Institute of Virology and Immunology, Bern and Mittelh\u00e4usern, Switzerland"
       },
       {
-        "author_name": "Andreas Brave",
-        "author_inst": "Department of microbiology,Public Health Agency of Sweden"
+        "author_name": "Mitra L Gultom",
+        "author_inst": "Institute of Virology and Immunology, Bern and Mittelh\u00e4usern, Switzerland"
       },
       {
-        "author_name": "Sylvie van der Werf",
-        "author_inst": "Department of Virology,Molecular Genetics of RNA Viruses unit,CNRS UMR-3569, University of Paris, National Reference Center for Respiratory Viruses Institut Pas"
+        "author_name": "Tran Thi Nhu Thao",
+        "author_inst": "Institute of Virology and Immunology, Bern and Mittelh\u00e4usern, Switzerland"
       },
       {
-        "author_name": "En-Qiang Chen",
-        "author_inst": "Center of Infectious Diseases, West China Hospital of Sichuan University"
+        "author_name": "Nadine Ebert",
+        "author_inst": "Institute of Virology and Immunology"
       },
       {
-        "author_name": "Zhiyong Zong",
-        "author_inst": "Department of Infection Control and Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu, China"
+        "author_name": "Melle Holwerda",
+        "author_inst": "Institute of Virology and Immunology, Bern and Mittelh\u00e4usern, Switzerland"
       },
       {
-        "author_name": "Weimin Li",
-        "author_inst": "Department of Respiratory and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China"
+        "author_name": "Joerg Steinmann",
+        "author_inst": "University Hospital Essen"
       },
       {
-        "author_name": "Binwu Ying",
-        "author_inst": "Department of Laboratory Medicine, West China Hospital of Sichuan University, Chengdu, China"
+        "author_name": "Daniela Niemeyer",
+        "author_inst": "Charit\u00e9"
+      },
+      {
+        "author_name": "Ronald Dijkman",
+        "author_inst": "Institute of Virology and Immunology"
+      },
+      {
+        "author_name": "G\u00fcnter Kampf",
+        "author_inst": "University Medicine Greifswald, Institute for Hygiene and Environmental Medicine, Greifswald, Germany"
+      },
+      {
+        "author_name": "Christian Drosten",
+        "author_inst": "Charit\u00e9"
+      },
+      {
+        "author_name": "Eike Steinmann",
+        "author_inst": "Ruhr University Bochum"
+      },
+      {
+        "author_name": "Volker Thiel",
+        "author_inst": "University of Bern"
+      },
+      {
+        "author_name": "Stephanie Pfaender",
+        "author_inst": "Department for Molecular & Medical Virology, Ruhr-Universit\u00e4t Bochum, Germany"
       }
     ],
     "version": "1",
-    "license": "cc_no",
-    "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "license": "cc_by_nc_nd",
+    "type": "new results",
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.03.14.20035980",
@@ -1556030,23 +1559331,95 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.11.20034512",
-    "rel_title": "A Method to Model Outbreaks of New Infectious Diseases with Pandemic Potential such as COVID-19",
+    "rel_doi": "10.1101/2020.03.11.20031096",
+    "rel_title": "Relationship between the ABO Blood Group and the COVID-19 Susceptibility",
     "rel_date": "2020-03-16",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.11.20034512",
-    "rel_abs": "The emergence of the novel coronavirus (a.k.a. COVID-19, SARS-CoV-2) out of Wuhan, Hubei Province, China caught the world by surprise. As the outbreak began to spread outside of China, too little was known about the virus to model its transmission with any acceptable accuracy. World governments responded to rampant misinformation about the virus leading to collateral disasters, such as plunging financial markets, that could have been avoided if better models of the outbreak had been available. This is an engineering approach to model the spread of a new infectious disease from sparse data when little is known about the infectious agent itself. The paper is not so much about the model itself - because there are many good scientific approaches to model an epidemic - as it is about crunching numbers when there are barely any numbers to crunch. The coronavirus outbreak in USA is used to illustrate the implementation of this modeling approach. A Monte Carlo approach is implemented by using incubation period and testing efficiency as variables. Among others it is demonstrated that imposing early travel restrictions from infected countries slowed down the outbreak in the USA by about 26 days.",
-    "rel_num_authors": 1,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.11.20031096",
+    "rel_abs": "The novel coronavirus disease-2019 (COVID-19) has been spreading around the world rapidly and declared as a pandemic by WHO. Here, we compared the ABO blood group distribution in 2,173 patients with COVID-19 confirmed by SARS-CoV-2 test from three hospitals in Wuhan and Shenzhen, China with that in normal people from the corresponding regions. The results showed that blood group A was associated with a higher risk for acquiring COVID-19 compared with non-A blood groups, whereas blood group O was associated with a lower risk for the infection compared with non-O blood groups. This is the first observation of an association between the ABO blood type and COVID-19. It should be emphasized, however, that this is an early study with limitations. It would be premature to use this study to guide clinical practice at this time, but it should encourage further investigation of the relationship between the ABO blood group and the COVID-19 susceptibility.",
+    "rel_num_authors": 19,
     "rel_authors": [
       {
-        "author_name": "Willem G Odendaal",
-        "author_inst": "Virginia Tech"
+        "author_name": "Jiao Zhao",
+        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+      },
+      {
+        "author_name": "Yan Yang",
+        "author_inst": "National Clinical Research Center for Infectious Diseases, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen Third Peopl"
+      },
+      {
+        "author_name": "Hanping Huang",
+        "author_inst": "Infection Disease Department, Wuhan Jinyintan Hospital, Wuhan, China"
+      },
+      {
+        "author_name": "Dong Li",
+        "author_inst": "Renmin Hospital of Wuhan University, Wuhan 430060, China"
+      },
+      {
+        "author_name": "Dongfeng Gu",
+        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+      },
+      {
+        "author_name": "Xiangfeng Lu",
+        "author_inst": "Department of Epidemiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"
+      },
+      {
+        "author_name": "Zheng Zhang",
+        "author_inst": "National Clinical Research Center for Infectious Diseases, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen Third Peopl"
+      },
+      {
+        "author_name": "Lei Liu",
+        "author_inst": "National Clinical Research Center for Infectious Diseases, The Second Affiliated Hospital of Southern University of Science and Technology, Shenzhen Third Peopl"
+      },
+      {
+        "author_name": "Ting Liu",
+        "author_inst": "Infection Disease Department, Wuhan Jinyintan Hospital, Wuhan, China"
+      },
+      {
+        "author_name": "Yukun Liu",
+        "author_inst": "School of Statistics, East China Normal University, Shanghai, China"
+      },
+      {
+        "author_name": "Yunjiao He",
+        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+      },
+      {
+        "author_name": "Bin Sun",
+        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+      },
+      {
+        "author_name": "Meilan Wei",
+        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+      },
+      {
+        "author_name": "Guangyu Yang",
+        "author_inst": "School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China"
+      },
+      {
+        "author_name": "Xinghuan Wang",
+        "author_inst": "Zhongnan Hospital of Wuhan University"
+      },
+      {
+        "author_name": "Li Zhang",
+        "author_inst": "Infection Disease Department, Wuhan Jinyintan Hospital, Wuhan, China"
+      },
+      {
+        "author_name": "Xiaoyang Zhou",
+        "author_inst": "Renmin Hospital of Wuhan University, Wuhan 430060, China"
+      },
+      {
+        "author_name": "Mingzhao Xing",
+        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
+      },
+      {
+        "author_name": "Peng George Wang",
+        "author_inst": "School of Medicine, Southern University of Science and Technology, Shenzhen, China"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.03.11.20024901",
@@ -1557841,37 +1561214,45 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.09.20033126",
-    "rel_title": "Clinical features of imported cases of coronavirus disease 2019 in Tibetan patients in the Plateau area",
+    "rel_doi": "10.1101/2020.03.11.20033159",
+    "rel_title": "Prolonged presence of SARS-CoV-2 in feces of pediatric patients during the convalescent phase",
     "rel_date": "2020-03-13",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.09.20033126",
-    "rel_abs": "Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has rapidly spread throughout China, but the clinical characteristics of Tibetan patients living in the Qinghai-Tibetan plateau are unknown. We aimed to investigate the epidemiological, clinical, laboratory and radiological characteristics of these patients. We included 67 Tibetan patients with confirmed SARS-CoV-2 infection. The patients were divided into two groups based on the presence of clinical symptoms at admission, with 31 and 36 patients in the symptomatic and asymptomatic groups, respectively. The epidemiological, clinical, laboratory and radiological characteristics were extracted and analysed. No patient had a history of exposure to COVID-19 patients from Wuhan or had travelled to Wuhan. The mean age of Tibetan patients was 39.3 years and 59% of the patients were male. Seven patients presented with fever on admission and lymphocytopenia was present in 20 patients. 47 patients had abnormal chest CTs at admission instead of stating that 20 were unchanged. Lactate dehydrogenase levels were increased in 31 patients. Seven patients progressed to severe COVID-19; however, after treatment, their condition was stable. No patients died. Of the 36 asymptomatic patients, the mean age was younger than the symptomatic group (34.4{+/-}17.3vs 44.9{+/-}18.1 years, P=0.02). Lymphocyte count and prealbumin levels were higher in the asymptomatic group than the group with clinical symptoms (1.6{+/-}0.5 vs 1.3{+/-}0.6 and 241.8{+/-}68.2 vs 191.9{+/-}60.3, respectively; P<0.05). Imported cases of COVID-19 in Tibetan patients were generally mild in this high-altitude area. Absence of fever or radiologic abnormalities on initial presentation were common.",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.11.20033159",
+    "rel_abs": "BackgroundSevere acute respiratory coronavirus 2 (SARS-CoV-2) is a newly identified virus which mainly spreads from person-to-person. Presence of SARS-CoV-2 has been constantly reported in stools of patients with coronavirus disease 2019 (COVID-19). However, there is a paucity of data concerning fecal shedding of the virus in pediatric patients.\n\nObjectiveTo investigate dynamic changes of SARS-CoV-2 in respiratory and fecal specimens in children with COVID-19.\n\nMethodsFrom January 17, 2020 to February 23, 2020, three pediatric cases of COVID-19 were reported in Qingdao, Shandong Province, China. Epidemiological, clinical, laboratory, and radiological characteristics and treatment data of these children were collected. Real-time fluorescence reverse-transcriptase-polymerase-chain reaction (RT-PCR) was performed to detect SARS-CoV-2 RNA in throat swabs and fecal specimens. Patients were followed up to March 10, 2020, the final date of follow-up, and dynamic profiles of RT-PCR results were closely monitored.\n\nResultsAll the three pediatric cases were household contacts of adults whose symptoms developed earlier. Severity of disease was mild to moderate and fever was the most consistent and predominant symptom at onset of illness of these children (two cases had body temperature higher than 38.5{degrees}C). All children showed increased lymphocytes (>4.4x109 /L) with normal white blood cell counts on admission. Radiological changes were not typical for COVID-19. All children showed good response to supportive treatment. Clearance of SARS-CoV-2 in respiratory tract occurred within two weeks after abatement of fever, whereas viral RNA remained positive in stools of pediatric patients for longer than 4 weeks. Two children had fecal SARS-CoV-2 turned negative 20 days after throat swabs showing negative, while that of another child lagged behind for 8 days.\n\nInterpretationSARS-CoV-2 may exist in gastrointestinal tract for a longer time than respiratory system. Persistent shedding of SARS-CoV-2 in stools of infected children indicates the potential for the virus to be transmitted through fecal excretion. Massive efforts should be made at all levels to prevent spreading of the infection among children after reopening of kindergartens and schools.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Yu Lei",
-        "author_inst": "sichuan academy of medical sciences&sichuan provincial people's hospital"
+        "author_name": "Yuhan Xing",
+        "author_inst": "The Chinese University of Hong Kong"
       },
       {
-        "author_name": "yunping lan",
-        "author_inst": "sichuan academy of medical sciences&sichuan provincial people's hospital"
+        "author_name": "Wei Ni",
+        "author_inst": "Qingdao Women and Childrens Hospital"
       },
       {
-        "author_name": "jianli lu",
-        "author_inst": "363 hospital of  chengdu"
+        "author_name": "Qin Wu",
+        "author_inst": "Qingdao Women and Childrens Hospital"
       },
       {
-        "author_name": "xiaobo huang",
-        "author_inst": "sichuan academy of medical sciences&sichuan provincial people's hospital"
+        "author_name": "Wenjie Li",
+        "author_inst": "Qingdao Women and Childrens Hospital"
+      },
+      {
+        "author_name": "Guoju Li",
+        "author_inst": "Qingdao Women and Childrens Hospital"
+      },
+      {
+        "author_name": "Jianning Tong",
+        "author_inst": "Qingdao Women and Childrens Hospital"
       },
       {
-        "author_name": "bamu silang",
-        "author_inst": "daofu people's hospital"
+        "author_name": "Xiufeng Song",
+        "author_inst": "Qingdao Women and Childrens Hospital"
       },
       {
-        "author_name": "fan zeng",
-        "author_inst": "sichuan academy of medical sciences&sichuan provincial people's hospital"
+        "author_name": "Quansheng Xing",
+        "author_inst": "Qingdao Women and Children's Hospital"
       }
     ],
     "version": "1",
@@ -1560066,39 +1563447,39 @@
     "category": "intensive care and critical care medicine"
   },
   {
-    "rel_doi": "10.1101/2020.03.08.980383",
-    "rel_title": "In silico approach to accelerate the development of mass spectrometry-based proteomics methods for detection of viral proteins: Application to COVID-19",
+    "rel_doi": "10.1101/2020.03.10.985150",
+    "rel_title": "A proposal of an alternative primer for the ARTIC Network's multiplex PCR to improve coverage of SARS-CoV-2 genome sequencing",
     "rel_date": "2020-03-10",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.08.980383",
-    "rel_abs": "We describe a method for rapid in silico selection of diagnostic peptides from newly described viral pathogens and applied this approach to SARS-CoV-2/COVID-19. This approach is multi-tiered, beginning with compiling the theoretical protein sequences from genomic derived data. In the case of SARS-CoV-2 we begin with 496 peptides that would be produced by proteolytic digestion of the viral proteins. To eliminate peptides that would cause cross-reactivity and false positives we remove peptides from consideration that have sequence homology or similar chemical characteristics using a progressively larger database of background peptides. Using this pipeline, we can remove 47 peptides from consideration as diagnostic due to the presence of peptides derived from the human proteome. To address the complexity of the human microbiome, we describe a method to create a database of all proteins of relevant abundance in the saliva microbiome. By utilizing a protein-based approach to the microbiome we can more accurately identify peptides that will be problematic in COVID-19 studies which removes 12 peptides from consideration. To identify diagnostic peptides, another 7 peptides are flagged for removal following comparison to the proteome backgrounds of viral and bacterial pathogens of similar clinical presentation. By aligning the protein sequences of SARS-CoV-2 field isolates deposited to date we can identify peptides for removal due to their presence in highly variable regions that may lead to false negatives as the pathogen evolves. We provide maps of these regions and highlight 3 peptides that should be avoided as potential diagnostic or vaccine targets. Finally, we leverage publicly deposited proteomics data from human cells infected with SARS-CoV-2, as well as a second study with the closely related MERS-CoV to identify the two proteins of highest abundance in human infections. The resulting final list contains the 24 peptides most unique and diagnostic of SARS-CoV-2 infections. These peptides represent the best targets for the development of antibodies are clinical diagnostics. To demonstrate one application of this we model peptide fragmentation using a deep learning tool to rapidly generate targeted LCMS assays and data processing method for detecting CoVID-19 infected patient samples.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=156 HEIGHT=200 SRC=\"FIGDIR/small/980383v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (37K):\norg.highwire.dtl.DTLVardef@1d7fd4borg.highwire.dtl.DTLVardef@136563borg.highwire.dtl.DTLVardef@57641dorg.highwire.dtl.DTLVardef@16de9a4_HPS_FORMAT_FIGEXP  M_FIG C_FIG",
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.10.985150",
+    "rel_abs": "Since December 2019, the coronavirus disease 2019 (COVID-19) caused by a novel coronavirus SARS-CoV-2 has rapidly spread to almost every nation in the world. Soon after the pandemic was recognized by epidemiologists, a group of biologists comprising the ARTIC Network, has devised a multiplexed polymerase chain reaction (PCR) protocol and primer set for targeted whole-genome amplification of SARS-CoV-2. The ARTIC primer set amplifies 98 amplicons, which are separated only in two PCRs, across a nearly entire viral genome. The original primer set and protocol showed a fairly small amplification bias when clinical samples with relatively high viral loads were used. However, when samples viral load was low, several amplicons, especially amplicons 18 and 76, exhibited low coverage or complete dropout. We have determined that these dropouts were due to a dimer formation between the forward primer for amplicon 18, 18_LEFT, and the reverse primer for amplicon 76, 76_RIGHT. Replacement of 76_RIGHT with an alternatively designed primer was sufficient to produce a drastic improvement in coverage of both amplicons. Based on this result, we replaced 12 primers in total in the ARTIC primer set that were predicted to be involved in 14 primer interactions. The resulting primer set, version N1 (NIID-1), exhibits improved overall coverage compared to the ARTIC Networks original (V1) and modified (V3) primer set.",
     "rel_num_authors": 5,
     "rel_authors": [
       {
-        "author_name": "Ben Orsburn",
-        "author_inst": "UVA School of Medicine"
+        "author_name": "Kentaro Itokawa",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Conor Jenkins",
-        "author_inst": "Hood College Biology Department"
+        "author_name": "Tsuyoshi Sekizuka",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Sierra D Miller",
-        "author_inst": "Millersville University"
+        "author_name": "Masanori Hashino",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Benjamin A Neely",
-        "author_inst": "Proteomic und Genomic Sciences"
+        "author_name": "Rina Tanaka",
+        "author_inst": "National Institute of Infectious Diseases"
       },
       {
-        "author_name": "Namandje M Bumpus",
-        "author_inst": "Johns Hopkins University"
+        "author_name": "Makoto Kuroda",
+        "author_inst": "National Institute of Infectious Diseases"
       }
     ],
     "version": "1",
     "license": "cc_by",
     "type": "new results",
-    "category": "biochemistry"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.03.08.982637",
@@ -1561556,35 +1564937,151 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.05.20031906",
-    "rel_title": "COVID-19 early warning score: a multi-parameter screening tool to identify highly suspected patients",
+    "rel_doi": "10.1101/2020.03.06.20031955",
+    "rel_title": "Transmission of corona virus disease 2019 during the incubation period may lead to a quarantine loophole",
     "rel_date": "2020-03-08",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.05.20031906",
-    "rel_abs": "BACKGROUNDCorona Virus Disease 2019 (COVID-19) is spreading worldwide. Effective screening for patients is important to limit the epidemic. However, some defects make the currently applied diagnosis methods are still not very ideal for early warning of patients. We aimed to develop a diagnostic model that allows for the quick screening of highly suspected patients using easy-to-get variables.\n\nMETHODSA total of 1,311 patients receiving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleicacid detection were included, whom with a positive result were classified into COVID-19 group. Multivariate logistic regression analyses were performed to construct the diagnostic model. Receiver operating characteristic (ROC) curve analysis were used for model validation.\n\nRESULTSAfter analysis, signs of pneumonia on CT, history of close contact, fever, neutrophil-to-lymphocyte ratio (NLR), Tmax and sex were included in the diagnostic model. Age and meaningful respiratory symptoms were enrolled into COVID-19 early warning score (COVID-19 EWS). The areas under the ROC curve (AUROC) indicated that both of the diagnostic model (training dataset 0.956 [95%CI 0.935-0.977, P < 0.001]; validation dataset 0.960 [95%CI 0.919-1.0, P < 0.001]) and COVID-19 EWS (training dataset 0.956 [95%CI 0.934-0.978, P < 0.001]; validate dataset 0.966 [95%CI 0.929-1, P < 0.001]) had good discrimination capacity. In addition, we also obtained the cut-off values of disease severity predictors, such as CT score, CD8+ T cell count, CD4+ T cell count, and so on.\n\nCONCLUSIONSThe new developed COVID-19 EWS was a considerable tool for early and relatively accurately warning of SARS-CoV-2 infected patients.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.06.20031955",
+    "rel_abs": "BackgroundThe ongoing outbreak of novel corona virus disease 2019 (COVID-19) in Wuhan, China, is arousing international concern. This study evaluated whether and when the infected but asymptomatic cases during the incubation period could infect others.\n\nMethodsWe collected data on demographic characteristics, exposure history, and symptom onset day of the confirmed cases, which had been announced by the Chinese local authorities. We evaluated the potential of transmission during the incubation period in 50 infection clusters, including 124 cases. All the secondary cases had a history of contact with their first-generation cases prior to symptom onset.\n\nResultsThe estimated mean incubation period for COVID-19 was 4.9 days (95% confidence interval [CI], 4.4 to 5.4) days, ranging from 0.8 to 11.1 days (2.5th to 97.5th percentile). The observed mean and standard deviation (SD) of serial interval was 4.1{+/-}3.3 days, with the 2.5th and 97.5th percentiles at -1 and 13 days. The infectious curve showed that in 73.0% of the secondary cases, their date of getting infected was before symptom onset of the first-generation cases, particularly in the last three days of the incubation period.\n\nConclusionsThe results indicated the transmission of COVID-9 occurs among close contacts during the incubation period, which may lead to a quarantine loophole. Strong and effective countermeasures should be implemented to prevent or mitigate asymptomatic transmission during the incubation period in populations at high risk.",
+    "rel_num_authors": 33,
     "rel_authors": [
       {
-        "author_name": "Cong-Ying Song",
-        "author_inst": "The First Affiliated Hospital, School of Medicine, Zhejiang University"
+        "author_name": "Wei Xia",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Jia Xu",
-        "author_inst": "The First Affiliated Hospital, School of Medicine, Zhejiang University"
+        "author_name": "Jiaqiang Liao",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Jian-Qin He",
-        "author_inst": "The First Affiliated Hospital, School of Medicine, Zhejiang University"
+        "author_name": "Chunhui Li",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Yuan-Qiang Lu",
-        "author_inst": "The First Affiliated Hospital, School of Medicine, Zhejiang University"
+        "author_name": "Yuanyuan Li",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xi Qian",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xiaojie Sun",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Hongbo Xu",
+        "author_inst": "Tongji School of Pharmacy, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Gaga Mahai",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xin Zhao",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Lisha Shi",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Juan Liu",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Ling Yu",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Meng Wang",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Qianqian Wang",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Asmagvl Namat",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Ying Li",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Jingyu Qu",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Qi Liu",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xiaofang Lin",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Shuting Cao",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Shu Huan",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Jiying Xiao",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Fengyu Ruan",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Hanjin Wang",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Qing Xu",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xingjuan Ding",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Xingjie Fang",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Feng Qiu",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Jiaolong Ma",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Yu Zhang",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Aizhen Wang",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Yuling Xing",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Shunqing Xu",
+        "author_inst": "School of Public Health, Tongji Medical College, Huazhong University of Science and Technology"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "infectious diseases"
+    "category": "epidemiology"
   },
   {
     "rel_doi": "10.1101/2020.03.06.20032177",
@@ -1563045,55 +1566542,107 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.02.20030148",
-    "rel_title": "Validity of Wrist and Forehead Temperature in Temperature Screening in the General Population During the Outbreak of 2019 Novel Coronavirus: a prospective real-world study",
+    "rel_doi": "10.1101/2020.03.04.20031005",
+    "rel_title": "Case fatality risk of novel coronavirus diseases 2019 in China",
     "rel_date": "2020-03-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.02.20030148",
-    "rel_abs": "AimsTemperature screening is important in the population during the outbreak of 2019 Novel Coronavirus (COVID-19). This study aimed to compare the accuracy and precision of wrist and forehead temperature with tympanic temperature under different circumstances.\n\nMethodsWe performed a prospective observational study in a real-life population. We consecutively collected wrist and forehead temperatures in Celsius ({degrees}C) using a non-contact infrared thermometer (NCIT). We also measured the tympanic temperature using a tympanic thermometers (IRTT) and defined fever as a tympanic temperature [&ge;]37.3{degrees}C.\n\nResultsWe enrolled a total of 528 participants including 261 indoor and 267 outdoor participants. We divided outdoor participants into four types according to their means of transportation to the hospital as walk, bicycle, electric vehicle, car, and inside the car. Under different circumstance, the mean difference ranged from -1.72 to -0.56{degrees}C in different groups for the forehead measurements, and -0.96 to -0.61{degrees}C for the wrist measurements. Both measurements had high fever screening abilities in inpatients (wrist: AUC 0.790; 95% CI: 0.725-0.854, P <0.001; forehead: AUC 0.816; 95% CI: 0.757-0.876, P <0.001). The cut-off value of wrist measurement for detecting tympanic temperature [&ge;]37.3{degrees}C was 36.2{degrees}C with a 86.4% sensitivity and a 67.0% specificity, and the best threshold of forehead measurement was also 36.2{degrees}C with a 93.2% sensitivity and a 60.0% specificity.\n\nConclusionsWrist measurement is more stable than forehead measurement under different circumstance. Both measurements have great fever screening abilities for indoor patients. The cut-off value of both measurements was 36.2{degrees}C. (ClinicalTrials.gov number: NCT04274621)",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.04.20031005",
+    "rel_abs": "ObjectiveThe outbreak of novel coronavirus disease 2019 (COVID-19) imposed a substantial health burden in mainland China and remains a global epidemic threat. Our objectives are to assess the case fatality risk (CFR) among COVID-19 patients detected in mainland China, stratified by clinical category and age group.\n\nMethodsWe collected individual information on laboratory-confirmed COVID-19 cases from publicly available official sources from December 29, 2019 to February 23, 2020. We explored the risk factors associated with mortality. We used methods accounting for right-censoring and survival analyses to estimate the CFR among detected cases.\n\nResultsOf 12,863 cases reported outside Hubei, we obtained individual records for 9,651 cases, including 62 deaths and 1,449 discharged cases. The deceased were significantly older than discharged cases (median age: 77 vs 39 years, p<0.001). 58% (36/62) were male. Older age (OR 1.18 per year; 95%CI: 1.14 to 1.22), being male (OR 2.02; 95%CI: 1.02 to 4.03), and being treated in less developed economic regions (e.g., West and Northeast vs. East, OR 3.93; 95%CI: 1.74 to 8.85) were mortality risk factors. The estimated CFR was 0.89-1.24% among all cases. The fatality risk among critical patients was 2-fold higher than that among severe and critical patients, and 24-fold higher than that among moderate, severe and critical patients.\n\nConclusionsOur estimates of CFR based on laboratory-confirmed cases ascertained outside of Hubei suggest that COVID-19 is not as severe as severe acute respiratory syndrome and Middle East respiratory syndrome, but more similar to the mortality risk of 2009 H1N1 influenza pandemic in hospitalized patients. The fatality risk of COVID-19 is higher in males and increases with age. Our study improves the severity assessment of the ongoing epidemic and can inform the COVID-19 outbreak response in China and beyond.",
+    "rel_num_authors": 22,
     "rel_authors": [
       {
-        "author_name": "Ge Chen",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Xiaowei Deng",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Jiarong Xie",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Juan Yang",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Guangli Dai",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Wei Wang",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Peijun Zheng",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Xiling Wang",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Xiaqing Hu",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Jiaxin Zhou",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Hongpeng Lu",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Zhiyuan Chen",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Lei Xu",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Jing Li",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Xueqin Chen",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Yinzi Chen",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       },
       {
-        "author_name": "Xiaomin Chen",
-        "author_inst": "Ningbo First Hospital"
+        "author_name": "Han Yan",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
+      },
+      {
+        "author_name": "Juanjuan Zhang",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
+      },
+      {
+        "author_name": "Yongli Zhang",
+        "author_inst": "Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China"
+      },
+      {
+        "author_name": "Yan Wang",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
+      },
+      {
+        "author_name": "Qi Qiu",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
+      },
+      {
+        "author_name": "Hui Gong",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
+      },
+      {
+        "author_name": "Xianglin Wei",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
+      },
+      {
+        "author_name": "Lili Wang",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
+      },
+      {
+        "author_name": "Kaiyuan Sun",
+        "author_inst": "Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA"
+      },
+      {
+        "author_name": "Peng Wu",
+        "author_inst": "WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hon"
+      },
+      {
+        "author_name": "Marco Ajelli",
+        "author_inst": "Bruno Kessler Foundation, Trento, Italy"
+      },
+      {
+        "author_name": "Benjamin J. Cowling",
+        "author_inst": "WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hon"
+      },
+      {
+        "author_name": "Cecile Viboud",
+        "author_inst": "Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA"
+      },
+      {
+        "author_name": "Hongjie Yu",
+        "author_inst": "School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China"
       }
     ],
     "version": "1",
     "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "public and global health"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.03.04.20031039",
@@ -1564607,37 +1568156,61 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.03.03.20030627",
-    "rel_title": "SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19",
+    "rel_doi": "10.1101/2020.03.03.20030593",
+    "rel_title": "Evolving Epidemiology and Impact of Non-pharmaceutical Interventions on the Outbreak of Coronavirus Disease 2019 in Wuhan, China",
     "rel_date": "2020-03-06",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.03.20030627",
-    "rel_abs": "ObjectiveEstablishing a social contact data sharing initiative and an interactive tool to assess mitigation strategies for COVID-19.\n\nResultsWe organized data sharing of published social contact surveys via online repositories and formatting guidelines. We analyzed this social contact data in terms of weighted social contact matrices, next generation matrices, relative incidence and R0. We incorporated location-specific isolation measures (e.g. school closure or telework) and capture their effect on transmission dynamics. All methods have been implemented in an online application based on R Shiny and applied to COVID-19 with age-specific susceptibility and infectiousness. Using our online tool with the available social contact data, we illustrate that social distancing could have a considerable impact on reducing transmission for COVID-19. The effect itself depends on assumptions made about disease-specific characteristics and the choice of intervention(s).",
-    "rel_num_authors": 6,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.03.20030593",
+    "rel_abs": "BACKGROUNDWe described the epidemiological features of the coronavirus disease 2019 (Covid-19) outbreak, and evaluated the impact of non-pharmaceutical interventions on the epidemic in Wuhan, China.\n\nMETHODSIndividual-level data on 25,961 laboratory-confirmed Covid-19 cases reported through February 18, 2020 were extracted from the municipal Notifiable Disease Report System. Based on key events and interventions, we divided the epidemic into four periods: before January 11, January 11-22, January 23 - February 1, and February 2-18. We compared epidemiological characteristics across periods and different demographic groups. We developed a susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions.\n\nRESULTSThe median age of the cases was 57 years and 50.3% were women. The attack rate peaked in the third period and substantially declined afterwards across geographic regions, sex and age groups, except for children (age <20) whose attack rate continued to increase. Healthcare workers and elderly people had higher attack rates and severity risk increased with age. The effective reproductive number dropped from 3.86 (95% credible interval 3.74 to 3.97) before interventions to 0.32 (0.28 to 0.37) post interventions. The interventions were estimated to prevent 94.5% (93.7 to 95.2%) infections till February 18. We found that at least 59% of infected cases were unascertained in Wuhan, potentially including asymptomatic and mild-symptomatic cases.\n\nCONCLUSIONSConsiderable countermeasures have effectively controlled the Covid-19 outbreak in Wuhan. Special efforts are needed to protect vulnerable populations, including healthcare workers, elderly and children. Estimation of unascertained cases has important implications on continuing surveillance and interventions.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Lander Willem",
-        "author_inst": "Centre for Health Economic Research and Modelling Infectious Diseases,University of Antwerp, Antwerp, Belgium"
+        "author_name": "Chaolong Wang",
+        "author_inst": "Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Li Liu",
+        "author_inst": "Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Thang Van Hoang",
-        "author_inst": "Interuniversity Institute of Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium"
+        "author_name": "Xingjie Hao",
+        "author_inst": "Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Sebastian Funk",
-        "author_inst": "Centre for the Mathematical Modelling of Infectious Diseases,London School of Hygiene & Tropical Medicine, London, United Kingdom"
+        "author_name": "Huan Guo",
+        "author_inst": "Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Pietro Coletti",
-        "author_inst": "Interuniversity Institute of Biostatistics and statistical Bioinformatics, Data Science Institute,Hasselt University, Hasselt, Belgium"
+        "author_name": "Qi Wang",
+        "author_inst": "Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Philippe Beutels",
-        "author_inst": "(1) Centre for Health Economic Research and Modelling Infectious Diseases,University of Antwerp, Antwerp, Belgium; (2) School of Public health and Community Med"
+        "author_name": "Jiao Huang",
+        "author_inst": "Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Niel Hens",
-        "author_inst": "(1) Centre for Health Economic Research and Modelling Infectious Diseases,University of Antwerp, Antwerp, Belgium; (2) Interuniversity Institute of Biostatistic"
+        "author_name": "Na He",
+        "author_inst": "Fudan University"
+      },
+      {
+        "author_name": "Hongjie Yu",
+        "author_inst": "Fudan University"
+      },
+      {
+        "author_name": "Xihong Lin",
+        "author_inst": "Harvard University"
+      },
+      {
+        "author_name": "An Pan",
+        "author_inst": "Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Sheng Wei",
+        "author_inst": "Huazhong University of Science and Technology"
+      },
+      {
+        "author_name": "Tangchun Wu",
+        "author_inst": "Huazhong University of Science and Technology"
       }
     ],
     "version": "1",
@@ -1566280,39 +1569853,67 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.02.973255",
-    "rel_title": "Evidence for RNA editing in the transcriptome of 2019 Novel Coronavirus",
+    "rel_doi": "10.1101/2020.02.28.20029025",
+    "rel_title": "Clinical significance of IgM and IgG test for diagnosis of highly suspected COVID-19 infection",
     "rel_date": "2020-03-03",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.02.973255",
-    "rel_abs": "The COVID-19 outbreak has become a global health risk and understanding the response of the host to the SARS-CoV-2 virus will help to contrast the disease. Editing by host deaminases is an innate restriction process to counter viruses, and it is not yet known whether it operates against Coronaviruses. Here we analyze RNA sequences from bronchoalveolar lavage fluids derived from infected patients. We identify nucleotide changes that may be signatures of RNA editing: Adenosine-to-Inosine changes from ADAR deaminases and Cytosine-to-Uracil changes from APOBEC ones. A mutational analysis of genomes from different strains of human-hosted Coronaviridae reveals mutational patterns compatible to those observed in the transcriptomic data. Our results thus suggest that both APOBECs and ADARs are involved in Coronavirus genome editing, a process that may shape the fate of both virus and patient.\n\nFor the casual ReaderJust to make a few things clear: - RNA editing and DNA editing are PHYSIOLOGICAL processes. Organisms uses them to (a) try to fight viruses, (b) increase heterogeneity inside cells (on many levels), (c) recognise their own RNA.\n- our work suggests that: (a) cells use RNA editing in trying to deal with Coronaviruses. We don't know to what extent they succeed (and it would be nice if we could help them). (b) Whatever happens, mutations inserted by RNA editing fuel viral evolution. We don't know whether viruses actively exploit this.\n- If you (scientist or not) think our work suggests ANYTHING ELSE, contact us. It can be a first step to help fight these !@#$ coronavirus, or towards a Nobel prize - but we need to discuss it thoroughly.\n- If you think these cellular processes are fascinating, join the club and contact us. We can have a nice cup of tea while chatting how wondrous nature is at coming up with extraordinary solutions...",
-    "rel_num_authors": 5,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.28.20029025",
+    "rel_abs": "Quick, simple and accurate diagnosis of suspected COVID-19 is very important for the screening and therapy of patients. Although several methods were performed in clinical practice, however, the IgM and IgG diagnostic value evaluation was little performed. 57 suspected COVID-19 infection patients were enrolled in our study. 24 patients with positive and 33 patients with negative nucleic acid test. The positive rate of COVID-19 nucleic acid was 42.10%. The positive detection rate of combination of IgM and IgG for patients with COVID-19 negative and positive nucleic acid test was 72.73% and 87.50%. The results were significantly higher than the nucleic acid or IgM, IgG single detection. hsCRP in the COVID-19 nucleic acid negative group showed significantly higher than the positive groups (P=0.0298). AST in the COVID-19 IgM negative group showed significantly lower than the positive groups (P=0.0365). We provided a quick, simple, accurate aided detection method for the suspected patients and on-site screening in close contact with the population.",
+    "rel_num_authors": 12,
     "rel_authors": [
       {
-        "author_name": "Salvatore Di Giorgio",
-        "author_inst": "Core Research Laboratory, ISPRO, Firenze, 50139, Italy; Department of Medical Biotechnologies, University of Siena, Siena, 53100, Italy"
+        "author_name": "Xingwang Jia",
+        "author_inst": "Department of Clinical Laboratory Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
       },
       {
-        "author_name": "Filippo Martignano",
-        "author_inst": "Core Research Laboratory, ISPRO, Firenze, 50139, Italy; Department of Medical Biotechnologies, University of Siena, Siena, 53100, Italy"
+        "author_name": "Pengjun Zhang",
+        "author_inst": "Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Interventional Therapy Department, Peking University Cancer Hospita"
       },
       {
-        "author_name": "Maria Gabriella Torcia",
-        "author_inst": "Department of Experimental and Clinical Medicine, University of Florence, Firenze 50139, Italy"
+        "author_name": "Yaping Tian",
+        "author_inst": "Department of Translational Medicine, Chinese PLA General Hospital, Beijing, China."
       },
       {
-        "author_name": "Giorgio Mattiuz",
-        "author_inst": "Core Research L 5 aboratory, ISPRO, Firenze, 50139, Italy; Department of Experimental and Clinical Medicine, University of Florence, Firenze 50139, Italy"
+        "author_name": "Junli Wang",
+        "author_inst": "Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
+      },
+      {
+        "author_name": "Huadong Zeng",
+        "author_inst": "Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
+      },
+      {
+        "author_name": "Jun Wang",
+        "author_inst": "Department of Respiratory and Critical Care Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
       },
       {
-        "author_name": "Silvestro G Conticello",
-        "author_inst": "Institute for Cancer Research, Prevention and Clinical Network (ISPRO); Institute of Clinical Physiology, National Research Council, 56124, Pisa, Italy"
+        "author_name": "Liu Jiao",
+        "author_inst": "Department of Clinical Laboratory Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
+      },
+      {
+        "author_name": "Zeyan Chen",
+        "author_inst": "Department of Clinical Laboratory Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
+      },
+      {
+        "author_name": "Lijun Zhang",
+        "author_inst": "Department of Clinical Laboratory Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China."
+      },
+      {
+        "author_name": "Haihong He",
+        "author_inst": "Department of Clinical Laboratory Medicine, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
+      },
+      {
+        "author_name": "Kunlun He",
+        "author_inst": "Key Laboratory of Ministry of Industry and Information Technology of Biomedical Engineering and Translational Medicine, Chinese PLA General Hospital, Beijing, C"
+      },
+      {
+        "author_name": "Yajie Liu",
+        "author_inst": "Department of Neurology, Shenzhen Hospital, Southern Medical University, Shenzhen, China"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "bioinformatics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.03.02.972935",
@@ -1568150,51 +1571751,51 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.03.02.20030080",
-    "rel_title": "Estimation of local novel coronavirus (COVID-19) cases in Wuhan, China from off-site reported cases and population flow data from different sources",
-    "rel_date": "2020-03-02",
+    "rel_doi": "10.1101/2020.02.28.20029173",
+    "rel_title": "Analysis on the Clinical Characteristics of 36 Cases of Novel Coronavirus Pneumonia in Kunming",
+    "rel_date": "2020-03-01",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.02.20030080",
-    "rel_abs": "BackgroundsIn December 2019, a novel coronavirus (COVID-19) pneumonia hit Wuhan, Hubei Province, China and spread to the rest of China and overseas. The emergence of this virus coincided with the Spring Festival Travel Rush in China. It is possible to estimate total number of cases of COVID-19 in Wuhan, by 23 January 2020, given the cases reported in other cities and population flow data between cities.\n\nMethodsWe built a model to estimate the total number of cases in Wuhan by 23 January 2020, based on the number of cases detected outside Wuhan city in China, with the assumption that if the same screening effort used in other cities applied in Wuhan. We employed population flow data from different sources between Wuhan and other cities/regions by 23 January 2020. The number of total cases was determined by the maximum log likelihood estimation.\n\nFindingsFrom overall cities/regions data, we predicted 1326 (95% CI: 1177, 1484), 1151 (95% CI: 1018, 1292) and 5277 (95% CI: 4732, 5859) as total cases in Wuhan by 23 January 2020, based on different source of data from Changjiang Daily newspaper, Tencent, and Baidu. From separate cities/regions data, we estimated 1059 (95% CI: 918, 1209), 5214 (95% CI: 4659, 5808) as total cases in Wuhan in Wuhan by 23 January 2020, based on different sources of population flow data from Tencent and Baidu.\n\nConclusionSources of population follow data and methods impact the estimates of local cases in Wuhan before city lock down.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.28.20029173",
+    "rel_abs": "ObjectiveTo analyze the clinical characteristics of patients with novel coronavirus pneumonia in Kunming City, and to study the correlation between nutritional status and immune function.\n\nMethodsClinical data of 36 patients with novel coronavirus pneumonia in isolation area of Kunming Third Peoples Hospital from January 31 to February 15, 2020 were collected, and the basic situation, clinical characteristics, laboratory examination and CT imaging characteristics were analyzed. Serum albumin (ALB), prealbumin (PAB), hypersensitive c-reactive protein (hs-crp), CD3T cells, CD4T cells, CD8T cells and normal control group were analyzed. A simple linear regression analysis of the relationship between proalbumin and T cell subpopulation counts in the blood of patients.\n\nResults(1) The patients with new coronavirus pneumonia in Kunming were mainly of common type. (2) 50% of the patients first symptoms were fever and cough; (3) The total number of white blood cells in peripheral blood was normal or decreased in 23 cases (79%), and the lymphocyte count decreased in 5 cases (13.89%), without anemia. Hypersensitive c-reactive protein increased in 19 (52.78%) cases, and procalcitonin increased in 1 case. Albumin decreased in 5 cases (13.89%), proalbumin decreased in 15 cases (41.67%), alanine transaminase increased slightly in 4 cases (11.11%), alanine transaminase increased slightly in 4 cases (11.11%), total bilirubin increased slightly in 11 cases (30.56%), and renal function and blood coagulation were normal. Absolute value of CD3+T cells is with a decrease in 21 cases (58.3%), CD4+T in 28 cases (77.8%), CD8+T in 17 cases (47.2%), and CD4+/ CD8+ inverse in 6 cases (16.7%). (4) The prealbumin, CD3 T cells, CD4 T cells and CD8 T cells in the new coronavirus pneumonia group were significantly lower than those in the normal control group, and the hypersensitive c-reactive protein was higher than that in the normal control group. (5) The levels of PAB in the serum of the patients were linearly correlated with hs-crp, CD3 T cells, CD4 T cells and CD8 T cells, and the correlation coefficients were -0.474, 0.558, 0.467 and 0.613, respectively, showing statistical differences.\n\nConclusionThe clinical characteristics of the novel coronavirus pneumonia in Kunming are different from those in Wuhan. The changes of serum proalbumin and T cell subsets are relatively obvious. Changes in serum proalbumin may contribute to the early warning of novel coronavirus pneumonia. The nutritional status of patients with common and mild pneumonia should be considered.",
     "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Zian Zhuang",
-        "author_inst": "Hong Kong Polytechnic University"
+        "author_name": "Haiyan Fu",
+        "author_inst": "1.Kunming Third People's Hospital Isolation Ward"
       },
       {
-        "author_name": "Peihua Cao",
-        "author_inst": "Southern Medical University"
+        "author_name": "Hongjuan Li",
+        "author_inst": "1.Kunming Third People's Hospital Isolation Ward"
       },
       {
-        "author_name": "Shi Zhao",
-        "author_inst": "Chinese University of Hong Kong"
+        "author_name": "Xiaoqing Tang",
+        "author_inst": "1.Kunming Third People's Hospital Isolation Ward"
       },
       {
-        "author_name": "Yijun Lou",
-        "author_inst": "Hong Kong Polytechnic University"
+        "author_name": "Xiang Li",
+        "author_inst": "1.Kunming Third People's Hospital Isolation Ward"
       },
       {
-        "author_name": "Weiming Wang",
-        "author_inst": "Huaiyin Normal University"
+        "author_name": "Jie Shen",
+        "author_inst": "1.Kunming Third People's Hospital Isolation Ward"
       },
       {
-        "author_name": "Shu Yang",
-        "author_inst": "Chengdu University of Traditional Chinese Medicine, Chengdu, China"
+        "author_name": "Yujun Zhou",
+        "author_inst": "1.Kunming Third People's Hospital Isolation Ward"
       },
       {
-        "author_name": "Lin Yang",
-        "author_inst": "The Hong Kong Polytechnic University"
+        "author_name": "Bing Xu",
+        "author_inst": "1.Kunming Third People's Hospital Isolation Ward"
       },
       {
-        "author_name": "Daihai He",
-        "author_inst": "Hong Kong Polytechnic University"
+        "author_name": "Yu Luo",
+        "author_inst": "Kunming Third People's Hospital"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_by_nd",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.02.27.20028027",
@@ -1569763,21 +1573364,57 @@
     "category": "respiratory medicine"
   },
   {
-    "rel_doi": "10.1101/2020.02.24.20027649",
-    "rel_title": "Transmission potential of the New Corona (COVID-19) onboard the Princess Cruises Ship, 2020",
+    "rel_doi": "10.1101/2020.02.25.20025643",
+    "rel_title": "Correlation Analysis Between Disease Severity and Inflammation-related Parameters in Patients with COVID-19 Pneumonia",
     "rel_date": "2020-02-27",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.24.20027649",
-    "rel_abs": "An outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as [~]11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.",
-    "rel_num_authors": 2,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.25.20025643",
+    "rel_abs": "AimThe new coronavirus (COVID-19) pneumonia outbreaking at the end of 2019 is highly contagious. Crude mortality rate reached 49% in critical patients. Inflammation matters on disease progression. This study analyzed blood inflammation indicators among mild, severe and critical patients, helping to identify severe or critical patients early.\n\nMethodsIn this cross-sectional study, 100 patients were included and divided to mild, severe or critical groups. Correlation of peripheral blood inflammation-related indicators with disease criticality was analyzed. Cut-off values for critically ill patients were speculated through the ROC curve.\n\nResultsSignificantly, disease severity was associated with age (R=-0.564, P<0.001), interleukin-2 receptor (IL2R) (R=-0.534, P<0.001), interleukin-6 (IL-6) (R=-0.535, P<0.001), interleukin-8 (IL-8) (R=-0.308, P<0.001), interleukin-10 (IL-10) (R=-0.422, P<0.001), tumor necrosis factor  (TNF) (R=-0.322, P<0.001), C-reactive protein (CRP) (R=-0.604, P<0.001), ferroprotein (R=-0.508, P<0.001), procalcitonin (R=-0.650, P<0.001), white cell counts (WBC) (R=-0.54, P<0.001), lymphocyte counts (LC) (R=0.56, P<0.001), neutrophil count (NC) (R=-0.585, P<0.001) and eosinophil counts (EC) (R=0.299, P=0.01).\n\nConclusionWith following parameters such as age >67.5 years, IL2R >793.5U/mL, CRP >30.7ng/mL, ferroprotein >2252g/L, WBC>9.5*10^9/L or NC >7.305*10^9/L, the progress of COVID-19 to critical stage should be closely observed and possibly prevented. Inflammation is closely related to severity of COVID-19, and IL-6, TNF and IL-8 might be promising therapeutic targets.",
+    "rel_num_authors": 11,
     "rel_authors": [
       {
-        "author_name": "Kenji Mizumoto",
-        "author_inst": "Kyoto University"
+        "author_name": "Jing Gong",
+        "author_inst": "Department of Integrated Traditional Chinese and Western Medicine"
       },
       {
-        "author_name": "Gerardo Chowell",
-        "author_inst": "Georgia State University School of Public Health"
+        "author_name": "Hui Dong",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Song Qing Xia",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Yi Zhao Huang",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Dingkun Wang",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Yan Zhao",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Wenhua Liu",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Shenghao Tu",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Mingmin Zhang",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Qi Wang",
+        "author_inst": "TongJiHospital"
+      },
+      {
+        "author_name": "Fuer Lu",
+        "author_inst": "felu@tjh.tjmu.edu.cn"
       }
     ],
     "version": "1",
@@ -1571353,81 +1574990,49 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.02.20.20025999",
-    "rel_title": "Generation of antibodies against COVID-19 virus for development of diagnostic tools",
+    "rel_doi": "10.1101/2020.02.23.20026864",
+    "rel_title": "Higher severity and mortality in male patients with COVID-19 independent of age and susceptibility",
     "rel_date": "2020-02-25",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.20.20025999",
-    "rel_abs": "The COVID-19 China coronavirus started in Dec 2019 was challenged by the lack of accurate serological diagnostic tool for this deadly disease to quickly identify and isolate the infected patients. The generation of COVID-19-specific antibodies is essential for such tasks. Here we report that polyclonal and monoclonal antibodies were generated by immunizing animals with synthetic peptides corresponding to different areas of Nucleoprotein (N) of COVID-19. The specificities of the COVID-19 antibodies were assessed by Western Blot analysis against NPs from COVID-19, MERS and SARS. Antibodies were used for immunohistochemistry staining of the tissue sections from COVID-19 infected patient, as a potential diagnostic tool. A Sandwich ELISA kit was quickly assembled for quantitation of the virus/NP of COVID-19 concentrations in the vaccine preparations. Development of POCT is also aggressively undergoing.",
-    "rel_num_authors": 16,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.23.20026864",
+    "rel_abs": "ImportanceThe recent outbreak of Novel Coronavirus (SARS-CoV-2) Disease (COVID-19) has put the world on alert, that is reminiscent of the SARS outbreak seventeen years ago.\n\nObjectiveWe aim to compare the severity and mortality between male and female patients with both COVID-19 and SARS, to explore the most useful prognostic factors for individualized assessment.\n\nDesign, Setting, and ParticipantsWe extracted the data from a case series of 43 hospitalized patients we treated, a public data set of the first 37 cases died of COVID-19 in Wuhan city and 1019 survived patients from six cities in China. We also analyzed the data of 524 patients with SARS, including 139 deaths, from Beijing city in early 2003.\n\nMain Outcomes and MeasuresSeverity and mortality.\n\nResultsOlder age and high number of comorbidities were associated with higher severity and mortality in patients with both COVID-19 and SARS. The percentages of older age ([&ge;]65 years) were much higher in the deceased group than in the survived group in patients with both COVID-19 (83.8 vs. 13.2, P<0.001) and SARS (37.4 vs. 4.9, P<0.001). In the case series, men tend to be more serious than women (P=0.035), although age was comparable between men and women. In the public data set, age was also comparable between men and women in the deceased group or the survived group in patients with COVID-19. Meanwhile, gender distribution was exactly symmetrical in the 1019 survivors of COVID-19. However, the percentage of male were higher in the deceased group than in the survived group (70.3 vs. 50.0, P=0.015). The gender role in mortality was also observed in SARS patients. Survival analysis showed that men (hazard ratio [95% CI] 1.47 [1.05-2.06, P= 0.025) had a significantly higher mortality rate than women in patients with SARS.\n\nConclusions and RelevanceOlder age and male gender are risk factors for worse outcome in patients with COVID. While men and women have the same susceptibility to both SARS-CoV-2 and SARS-CoV, men may be more prone to have higher severity and mortality independent of age and susceptibility.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSAre men more susceptible to getting and dying from COVID-19?\n\nFindingsIn the case series, men tend to be more serious than women. In the public data set, the percentage of men were higher in the deceased group than in the survived group, although age was comparable between men and women.\n\nMeaningMale gender is a risk factor for worse outcome in patients with COVID independent of age and susceptibility.",
+    "rel_num_authors": 8,
     "rel_authors": [
       {
-        "author_name": "Maohua Li",
-        "author_inst": "AbMax Biotechnology Co., LTD"
-      },
-      {
-        "author_name": "Ronghua Jin",
-        "author_inst": "Beijing You'an Hospital, Capital Medical University"
-      },
-      {
-        "author_name": "Ya Peng",
-        "author_inst": "Laboratory of Animal Infectious Diseases, College of Animal Sciences and Veterinary Medicine, Guangxi University"
-      },
-      {
-        "author_name": "Cuiyan Wang",
-        "author_inst": "AbMax Biotechnology Co., LTD"
-      },
-      {
-        "author_name": "Wenlin Ren",
-        "author_inst": "AbMax Biotechnology Co., LTD"
-      },
-      {
-        "author_name": "Fudong Lv",
-        "author_inst": "Beijing You'an Hospital, Capital Medical University"
-      },
-      {
-        "author_name": "Sitao Gong",
-        "author_inst": "AbMax Biotechnology Co., LTD"
-      },
-      {
-        "author_name": "Feng Fang",
-        "author_inst": "AbMax Biotechnology Co., LTD"
-      },
-      {
-        "author_name": "Qianyun Wang",
-        "author_inst": "AbMax Biotechnology Co., LTD"
+        "author_name": "Jian-Min Jin",
+        "author_inst": "Beijing Tongren Hospital, Capital Medical University"
       },
       {
-        "author_name": "Jianli Li",
-        "author_inst": "AbMax Biotechnology Co., LTD"
+        "author_name": "Peng Bai",
+        "author_inst": "Beijing Tongren Hospital, Capital Medical University"
       },
       {
-        "author_name": "Tong Shen",
-        "author_inst": "AbMax Biotechnology Co., LTD"
+        "author_name": "Wei He",
+        "author_inst": "Beijing Tongren Hospital, Capital Medical University"
       },
       {
-        "author_name": "Hunter Sun",
-        "author_inst": "AnyGo Technology Co., Ltd"
+        "author_name": "Fei Wu",
+        "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Lei Zhou",
-        "author_inst": "State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences"
+        "author_name": "Xiao-Fang Liu",
+        "author_inst": "Beijing Tongren Hospital, Capital Medical University"
       },
       {
-        "author_name": "Yali Cui",
-        "author_inst": "College of Life Sciences, Northwest University"
+        "author_name": "De-Min Han",
+        "author_inst": "Beijing Tongren Hospital, Capital Medical University"
       },
       {
-        "author_name": "Hao Song",
-        "author_inst": "Research Network of Immunity and Health (RNIH), Beijing Institutes of Life Science, Chinese Academy of Sciences"
+        "author_name": "Shi Liu",
+        "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology"
       },
       {
-        "author_name": "Le Sun",
-        "author_inst": "AbMax Biotechnology Co., LTD"
+        "author_name": "Jin-Kui Yang",
+        "author_inst": "Beijing Tongren Hospital, Capital Medical University"
       }
     ],
     "version": "1",
-    "license": "cc_by_nd",
+    "license": "cc_by_nc_nd",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1573103,33 +1576708,77 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.02.20.20025866",
-    "rel_title": "Estimating the Asymptomatic Ratio of 2019 Novel Coronavirus onboard the Princess Cruises Ship, 2020",
+    "rel_doi": "10.1101/2020.02.22.20025460",
+    "rel_title": "Development and Evaluation of A CRISPR-based Diagnostic For 2019-novel Coronavirus",
     "rel_date": "2020-02-23",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.20.20025866",
-    "rel_abs": "The potential infectiousness of asymptomatic COVID-19 cases together with a substantial fraction of asymptomatic infections among all infections, have been highlighted in clinical studies. We conducted statistical modeling analysis to derive the delay-adjusted asymptomatic proportion of the positive COVID-19 infections onboard the Princess Cruises ship along with the timeline of infections. We estimated the asymptomatic proportion at 17.9% (95% CrI: 15.5%-20.2%), with most of the infections occurring before the start of the 2-week quarantine.",
-    "rel_num_authors": 4,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.22.20025460",
+    "rel_abs": "BackgroundThe recent outbreak of infections by the 2019 novel coronavirus (2019-nCoV), the third zoonotic CoV has raised great public health concern. The demand for rapid and accurate diagnosis of this novel pathogen brought significant clinical and technological challenges. Currently, metagenomic next-generation sequencing (mNGS) and reverse-transcription PCR (RT-PCR) are the most widely used molecular diagnostics for 2019-nCoV.\n\nMethods2019-nCoV infections were confirmed in 52 specimens by mNGS. Genomic information was analyzed and used for the design and development of an isothermal, CRISPR-based diagnostic for the novel virus. The diagnostic performance of CRISPR-nCoV was assessed and also compared across three technology platforms (mNGS, RT-PCR and CRISPR)\n\nResults2019-nCoVs sequenced in our study were conserved with the Wuhan strain, and shared certain genetic similarity with SARS-CoV. A high degree of variation in the level of viral RNA was observed in clinical specimens. CRISPR-nCoV demonstrated a near single-copy sensitivity and great clinical sensitivity with a shorter turn-around time than RT-PCR.\n\nConclusionCRISPR-nCoV presents as a promising diagnostic option for the emerging pathogen.",
+    "rel_num_authors": 15,
     "rel_authors": [
       {
-        "author_name": "Kenji Mizumoto",
-        "author_inst": "Kyoto University"
+        "author_name": "Tieying Hou",
+        "author_inst": "Laboratory Medicine, Provincial People's Hospital, Guangdong Academy of Medical Sciences Guangzhou, Guangdong 510000, China"
       },
       {
-        "author_name": "Katsushi Kagaya",
-        "author_inst": "Kyoto University"
+        "author_name": "Weiqi Zeng",
+        "author_inst": "Vision Medicals, Co., Ltd, Guangzhou, Guangdong 510000, China"
       },
       {
-        "author_name": "Alexander Zarebski",
-        "author_inst": "Oxford University"
+        "author_name": "Minling Yang",
+        "author_inst": "Vision Medicals, Co., Ltd, Guangzhou, Guangdong 510000, China"
       },
       {
-        "author_name": "Gerardo Chowell",
-        "author_inst": "Georgia State University School of Public Health"
+        "author_name": "Wenjing Chen",
+        "author_inst": "Vision Medicals Co., Ltd, Guangzhou"
+      },
+      {
+        "author_name": "Lili Ren",
+        "author_inst": "National Health Commission of the People's Republic of China Key Laboratory of Systems Biology of Pathogens; Christophe M\u00e9rieux Laboratory, Institute of Pathoge"
+      },
+      {
+        "author_name": "Jingwen Ai",
+        "author_inst": "Department of Infectious Diseases, Huashan Hospital affiliated to Fudan University, Shanghai 200040, China"
+      },
+      {
+        "author_name": "Ji Wu",
+        "author_inst": "Laboratory Medicine, Provincial People's Hospital, Guangdong Academy of Medical Sciences Guangzhou, Guangdong 510000, China"
+      },
+      {
+        "author_name": "Yalong Liao",
+        "author_inst": "Laboratory Medicine, Provincial People's Hospital, Guangdong Academy of Medical Sciences Guangzhou, Guangdong 510000, China"
+      },
+      {
+        "author_name": "Xuejing Gou",
+        "author_inst": "Vision Medicals, Co., Ltd, Guangzhou, Guangdong 510000, China"
+      },
+      {
+        "author_name": "Yongjun Li",
+        "author_inst": "Vision Medicals, Co., Ltd, Guangzhou, Guangdong 510000, China"
+      },
+      {
+        "author_name": "Xiaorui Wang",
+        "author_inst": "Vision Medicals, Co., Ltd, Guangzhou, Guangdong 510000, China"
+      },
+      {
+        "author_name": "Hang Su",
+        "author_inst": "Vision Medicals, Co., Ltd, Guangzhou, Guangdong 510000, China"
+      },
+      {
+        "author_name": "Bing Gu",
+        "author_inst": "Affiliated Hospital of Xuzhou Medical University"
+      },
+      {
+        "author_name": "Jianwei Wang",
+        "author_inst": "NHC Key Laboratory of Systems Biology of Pathogens and Christophe Merieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Pek"
+      },
+      {
+        "author_name": "Teng Xu",
+        "author_inst": "Vision Medicals Co., Ltd, 31 Kefeng Rd, G10-301, Guangzhou 510000, China"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "infectious diseases"
   },
@@ -1574604,47 +1578253,119 @@
     "category": "microbiology"
   },
   {
-    "rel_doi": "10.1101/2020.02.17.952895",
-    "rel_title": "Functional pangenome analysis provides insights into the origin, function and pathways to therapy of SARS-CoV-2 coronavirus",
+    "rel_doi": "10.1101/2020.02.21.959817",
+    "rel_title": "Rapid reconstruction of SARS-CoV-2 using a synthetic genomics platform",
     "rel_date": "2020-02-21",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.17.952895",
-    "rel_abs": "The spread of the novel coronavirus (SARS-CoV-2) has triggered a global emergency, that demands urgent solutions for detection and therapy to prevent escalating health, social and economic impacts. The spike protein (S) of this virus enables binding to the human receptor ACE2, and hence presents a prime target for vaccines preventing viral entry into host cells1. The S proteins from SARS-CoV-1 and SARS-CoV-2 are similar2, but structural differences in the receptor binding domain (RBD) preclude the use of SARS-CoV-1-specific neutralizing antibodies to inhibit SARS-CoV-23. Here we used comparative pangenomic analysis of all sequenced Betacoronaviruses to reveal that, among all core gene clusters present in these viruses, the envelope protein E shows a variant shared by SARS and SARS-Cov2 with two completely-conserved key functional features, an ion-channel and a PDZ-binding Motif (PBM). These features trigger a cytokine storm that activates the inflammasome, leading to increased edema in lungs causing the acute respiratory distress syndrome (ARDS)4-6, the leading cause of death in SARS-CoV-1 and SARS-CoV-2 infection7,8. However, three drugs approved for human use may inhibit SARS-CoV-1 and SARS-CoV-2 Protein E, either acting upon the ion channel (Amantadine and Hexamethylene amiloride9,10) or the PBM (SB2035805), thereby potentially increasing the survival of the host, as already demonstrated for SARS-CoV-1in animal models. Hence, blocking the SARS protein E inhibits development of ARDS in vivo. Given that our results demonstrate that the protein E subcluster for the SARS clade is quasi-identical for the key functional regions of SARS-CoV-1 and SARS-CoV-2, we conclude that use of approved drugs shown to act as SARS E protein inhibitors can help prevent further casualties from COVID-2019 while vaccines and other preventive measures are being developed.",
-    "rel_num_authors": 7,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.21.959817",
+    "rel_abs": "Reverse genetics has been an indispensable tool revolutionising our insights into viral pathogenesis and vaccine development. Large RNA virus genomes, such as from Coronaviruses, are cumbersome to clone and to manipulate in E. coli hosts due to size and occasional instability1-3. Therefore, an alternative rapid and robust reverse genetics platform for RNA viruses would benefit the research community. Here we show the full functionality of a yeast-based synthetic genomics platform for the genetic reconstruction of diverse RNA viruses, including members of the Coronaviridae, Flaviviridae and Paramyxoviridae families. Viral subgenomic fragments were generated using viral isolates, cloned viral DNA, clinical samples, or synthetic DNA, and reassembled in one step in Saccharomyces cerevisiae using transformation associated recombination (TAR) cloning to maintain the genome as a yeast artificial chromosome (YAC). T7-RNA polymerase has been used to generate infectious RNA, which was then used to rescue viable virus. Based on this platform we have been able to engineer and resurrect chemically-synthetized clones of the recent epidemic SARS-CoV-24 in only a week after receipt of the synthetic DNA fragments. The technical advance we describe here allows to rapidly responding to emerging viruses as it enables the generation and functional characterization of evolving RNA virus variants - in real-time - during an outbreak.",
+    "rel_num_authors": 25,
     "rel_authors": [
       {
-        "author_name": "Intikhab Alam",
-        "author_inst": "King Abdullah University of Science and Technology (KAUST)"
+        "author_name": "Tran Thi Nhu Thao",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
       },
       {
-        "author_name": "Allan K Kamau",
-        "author_inst": "King Abdullah University of Science and Technology (KAUST)"
+        "author_name": "Fabien Labroussaa",
+        "author_inst": "Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland"
       },
       {
-        "author_name": "Maxat Kulmanov",
-        "author_inst": "King Abdullah University of Science and Technology"
+        "author_name": "Nadine Ebert",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
       },
       {
-        "author_name": "Stefan T Arold",
-        "author_inst": "King Abdullah University of Science and Technology"
+        "author_name": "Hanspeter Stalder",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
       },
       {
-        "author_name": "Arnab T Pain",
-        "author_inst": "King Abdullah University of Science and Technology (KAUST)"
+        "author_name": "Jamine Portmann",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
       },
       {
-        "author_name": "Takashi Gojobori",
-        "author_inst": "King Abdullah University of Science and Technology (KAUST)"
+        "author_name": "Jenna Kelly",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
       },
       {
-        "author_name": "Carlos M. Duarte",
-        "author_inst": "King Abdullah University of Science and Technology (KAUST)"
+        "author_name": "Silvio Steiner",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
+      },
+      {
+        "author_name": "Melle Holwerda",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
+      },
+      {
+        "author_name": "Annika Kratzel",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
+      },
+      {
+        "author_name": "Mitra Gultom",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
+      },
+      {
+        "author_name": "Laura Laloli",
+        "author_inst": "Insitute for Infectious Diseases, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Linda Huesser",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
+      },
+      {
+        "author_name": "Manon Wider",
+        "author_inst": "Insitute for Infectious Diseases, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Stephanie Pfaender",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
+      },
+      {
+        "author_name": "Dagny Hirt",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
+      },
+      {
+        "author_name": "Valentina Cippa",
+        "author_inst": "Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Silvia Crespo-Pomar",
+        "author_inst": "Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Simon Schroeder",
+        "author_inst": "Institute of Virology, Charite-Universitaetsmedizin Berlin, corporatemember of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute "
+      },
+      {
+        "author_name": "Doreen Muth",
+        "author_inst": "Institute of Virology, Charite-Universitaetsmedizin Berlin, corporatemember of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute "
+      },
+      {
+        "author_name": "Daniela Niemeyer",
+        "author_inst": "Institute of Virology, Charite-Universitaetsmedizin Berlin, corporatemember of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute "
+      },
+      {
+        "author_name": "Marcel A Mueller",
+        "author_inst": "Institute of Virology, Charite-Universitaetsmedizin Berlin, corporatemember of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute "
+      },
+      {
+        "author_name": "Christian Drosten",
+        "author_inst": "Institute of Virology, Charite-Universitaetsmedizin Berlin, corporatemember of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, and Berlin Institute "
+      },
+      {
+        "author_name": "Ronald Dijkman",
+        "author_inst": "Insitute for Infectious Diseases, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Joerg Jores",
+        "author_inst": "Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland"
+      },
+      {
+        "author_name": "Volker Thiel",
+        "author_inst": "Institute of Virology and Immunology (IVI), Bern, Switzerland"
       }
     ],
     "version": "1",
     "license": "cc_by_nd",
     "type": "new results",
-    "category": "genomics"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.02.15.20023333",
@@ -1576062,47 +1579783,31 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.02.18.955195",
-    "rel_title": "Structure and immune recognition of the porcine epidemic diarrhea virus spike protein",
+    "rel_doi": "10.1101/2020.02.18.20021881",
+    "rel_title": "Association between 2019-nCoV transmission and N95 respirator use",
     "rel_date": "2020-02-19",
-    "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.18.955195",
-    "rel_abs": "Porcine epidemic diarrhea virus is an alphacoronavirus responsible for significant morbidity and mortality in pigs. A key determinant of viral tropism and entry, the PEDV spike protein is a key target for the host antibody response and a good candidate for a protein-based vaccine immunogen. We used electron microscopy to evaluate the PEDV spike structure, as well as pig polyclonal antibody responses to viral infection. The structure of the PEDV spike reveals a configuration similar to that of HuCoV-NL63. Several PEDV protein-protein interfaces are mediated by non-protein components including a glycan at Asn264 and two bound palmitoleic acid molecules. The polyclonal antibody response to PEDV infection shows a dominance of epitopes in the S1 region. This structural and immune characterization provides new insights into coronavirus spike stability determinants and explores the immune landscape of viral spike proteins.",
-    "rel_num_authors": 7,
+    "rel_site": "medRxiv",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.18.20021881",
+    "rel_abs": "2019-nCoV had caused pneumonia outbreak in Wuhan. Existing evidence have confirmed the human-to-human transmission of 2019-nCoV. We retrospectively collected infection data from 2 January to 22 January at six departments from Zhongnan Hospital of Wuhan University. In our study, we found N95 respirators, disinfection and hand washing can help to reduce the risk of 2019-nCoV infection in medical staffs. Our results call for re-emphasizing strict occupational protection code in battling this novel contagious disease. The risk of 2019-nCoV infection was higher in the open area than in the quarantined area. N95 may be more effective for 2019-nCoV infections.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Robert Kirchdoerfer",
-        "author_inst": "University of Wisconsin-Madison"
-      },
-      {
-        "author_name": "Mahesh Bhandari",
-        "author_inst": "Iowa State University"
-      },
-      {
-        "author_name": "Olnita Martini",
-        "author_inst": "The Scripps Research Intitute"
-      },
-      {
-        "author_name": "Leigh M Sewell",
-        "author_inst": "The Scripps Research Institute"
-      },
-      {
-        "author_name": "Sandhya Bangaru",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Xinghuan Wang",
+        "author_inst": "Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China"
       },
       {
-        "author_name": "Kyoung-Jin Yoon",
-        "author_inst": "Iowa State University"
+        "author_name": "Zhenyu Pan",
+        "author_inst": "Department of Infection Management, Zhongnan Hospital of Wuhan University, Wuhan, China"
       },
       {
-        "author_name": "Andrew Ward",
-        "author_inst": "The Scripps Research Institute"
+        "author_name": "Zhenshun Cheng",
+        "author_inst": "Department of Respiratory medicine, Zhongnan Hospital of Wuhan University, Wuhan, China"
       }
     ],
     "version": "1",
-    "license": "cc_by_nc_nd",
-    "type": "new results",
-    "category": "biophysics"
+    "license": "cc_no",
+    "type": "PUBLISHAHEADOFPRINT",
+    "category": "infectious diseases"
   },
   {
     "rel_doi": "10.1101/2020.02.16.20023903",
@@ -1577472,41 +1581177,37 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.02.14.20022913",
-    "rel_title": "Estimating the Efficacy of Traffic Blockage and Quarantine for the Epidemic Caused by 2019-nCoV (COVID-19)",
+    "rel_doi": "10.1101/2020.02.14.20021535",
+    "rel_title": "Clinical Characteristics of 2019 Novel Infected Coronavirus Pneumonia\uff1aA Systemic Review and Meta-analysis",
     "rel_date": "2020-02-17",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.14.20022913",
-    "rel_abs": "BackgroundSince the 2019-nCoV (COVID-19) outbreaks in Wuhan, China, the cumulative number of confirmed cases is increasing every day, and a large number of populations all over the world are at risk. The quarantine and traffic blockage can alleviate the risk of the epidemic and the infections, henceforth evaluating the efficacy of such actions is essential to inform policy makers and raise the public awareness of the importance of self-isolation and quarantine.\n\nMethodWe collected confirmed case data and the migration data, and introduced the quarantine factor and traffic blockage factor to the Flow-SEIR model. By varying the quarantine factor and traffic blockage factor, we simulated the change of the peak number and arrival time of infections, then the efficacy of these two intervation measures can be analyzed in our simulation. In our study, the self-protection at home is also included in quarantine.\n\nResultsIn the simulated results, the quarantine and traffic blockage are effective for epidemic control. For Hubei province, the current quarantine factor is estimaed to be 0.405, which means around 40.5% of suceptibles who are close contacting with are in quarantine, and the current traffic blockage factor is estimaed to be 0.66, which indicates around 34% of suceptibles who had flowed out from Hubei. For the other provinces outside Hubei, the current quarantine factor is estimated to be 0.285, and the current traffic blockage factor is estimated to be 0.26. With the quarantine and traffic blockage factor increasing, the number of infections decrease dramatically. We also simulated the start dates of quarantine and traffic blockage at four time points, the simulated results show that the early of warning is also effective for epidemic containing. However, provincial level traffic blockage can only alleviate 21.06% - 22.38% of the peak number of infections. In general, the quarantine is much more effective than the traffic blockage control.\n\nConclusionBoth of quarantine and traffic blockage are effective ways to control the spread of COVID-19. However, the eff icacy of quarantine is found to be much stronger than that of traffic blockage. Considering traffic blockage may also cause huge losses of economy, we propose to gradually deregulate the traffic blockage, and improve quarantine instead. Also, there might be a large number of asymptomatic carriers of COVID-19, the quarantine should be continued for a long time until the epidemic is totally under control.",
-    "rel_num_authors": 7,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.14.20021535",
+    "rel_abs": "BackgroundA novel pneumonia associated with the 2019 coronavirus infected pneumonia (NCIP) suddenly broke out in Wuhan, China in December 2019. 37287 confirmed cases and 813 death case in China (Until 8th/Feb/2019) have been reported in just fortnight. Although this risky pneumonia with high infection rates and high mortality rates need to be resolved immediately, major gaps in our knowledge of clinical characters of it were still not be established. The aim of this study is to summaries and analysis the clinical characteristics of 2019-nCoV pneumonia.\n\nMethodsLiteratures have been systematically performed a search on PubMed, Embase, Web of Science, GreyNet International, and The Cochrane Library from inception up to February 8, 2020. The Newcastle-Ottawa Scale was used to assess quality, and publication bias was analyzed by Eggers test. In the single-arm meta-analysis, A fix-effects model was used to obtain a pooled incidence rate. We conducted subgroup analysis according to geographic region and research scale.\n\nResultsA total of nine studies including 356 patients were included in this study, the mean age was 52.4 years and 221 (62.1%) were male. The pooled incidences rate of symptoms as follows: pharyngalgia (12.2%, 95% CI: 0.087-0.167), diarrhea (9.2%, 95% CI: 0.062-0.133) and headache (8.9%, 95% CI: 0.063-0.125). Meanwhile, 5.7% (95% CI: 0.027-0.114) of patients were found without any symptoms although they were diagnosed by RT-PCR. In the terms of CT imaging examination, the most of patients showed bilateral mottling or ground-glass opacity, 8.6% (95% CI: 0.048-0.148) of patients with crazy-paving pattern, and 11.5% (95% CI: 0.064-0.197) of patients without obvious CT imaging presentations. The pooled incidence of mortality was 8.9% (95% CI: 0.062-0.126).\n\nConclusionsTo our knowledge, this is the first evidence-based medicine research to further elaborate the clinical characteristics of NCIP, which is beneficial to the next step of prevention and treatment.",
+    "rel_num_authors": 6,
     "rel_authors": [
       {
-        "author_name": "Deqiang Li",
-        "author_inst": "Southeast University"
-      },
-      {
-        "author_name": "Zhicheng Liu",
-        "author_inst": "Southeast University"
+        "author_name": "Kai Qian",
+        "author_inst": "Kunming University of Science and Technology"
       },
       {
-        "author_name": "Qinghe Liu",
-        "author_inst": "Southeast University"
+        "author_name": "Yi Deng",
+        "author_inst": "Daping Hospital, Army Medical University"
       },
       {
-        "author_name": "Zefei Gao",
-        "author_inst": "Southeast University"
+        "author_name": "Yonghang Tai",
+        "author_inst": "Yunnan Normal University"
       },
       {
-        "author_name": "Junkai Zhu",
-        "author_inst": "Southeast University"
+        "author_name": "Jun Peng",
+        "author_inst": "The First People's Hospital of Yunnan Province"
       },
       {
-        "author_name": "Junyan Yang",
-        "author_inst": "Southeast University"
+        "author_name": "Hao Peng",
+        "author_inst": "The First People's Hospital of Yunnan Province"
       },
       {
-        "author_name": "Qiao Wang",
-        "author_inst": "Southeast University"
+        "author_name": "Lihong Jiang",
+        "author_inst": "The First People's Hospital of Yunnan Province"
       }
     ],
     "version": "1",
@@ -1578814,35 +1582515,35 @@
     "category": "infectious diseases"
   },
   {
-    "rel_doi": "10.1101/2020.02.10.20021725",
-    "rel_title": "Beyond R0: the importance of contact tracing when predicting epidemics",
+    "rel_doi": "10.1101/2020.02.11.20022095",
+    "rel_title": "Primary Care Practitioners' Response to 2019 Novel Coronavirus Outbreak in China",
     "rel_date": "2020-02-12",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.10.20021725",
-    "rel_abs": "The basic reproductive number -- R0 -- is one of the most common and most commonly misapplied numbers in public health. Although often used to compare outbreaks and forecast pandemic risk, this single number belies the complexity that two different pathogens can exhibit, even when they have the same R0 [1-3]. Here, we show how to predict outbreak size using estimates of the distribution of secondary infections, leveraging both its average R0 and the underlying heterogeneity. To do so, we reformulate and extend a classic result from random network theory [4] that relies on contact tracing data to simultaneously determine the first moment (R0) and the higher moments (representing the heterogeneity) in the distribution of secondary infections. Further, we show the different ways in which this framework can be implemented in the data-scarce reality of emerging pathogens. Lastly, we demonstrate that without data on the heterogeneity in secondary infections for emerging infectious diseases like COVID-19, the uncertainty in outbreak size ranges dramatically. Taken together, our work highlights the critical need for contact tracing during emerging infectious disease outbreaks and the need to look beyond R0 when predicting epidemic size.",
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.11.20022095",
+    "rel_abs": "The emerging outbreak of the 2019 novel coronavirus (2019-nCoV) originated from Wuhan poses a great challenge to healthcare system in China.1 Primary care practitioners (PCPs) have an important role in district communicable disease control.2 However, because primary health-care system in China still needs to be substantially strengthened,3,4 whether PCPs are proactive and capable in responding to the outbreak remains unclear. Using an electronic questionnaire, we surveyed a national sample of PCPs to assess their response to novel coronavirus outbreak.",
     "rel_num_authors": 4,
     "rel_authors": [
       {
-        "author_name": "Laurent H\u00e9bert-Dufresne",
-        "author_inst": "University of Vermont"
+        "author_name": "Zhijie Xu",
+        "author_inst": "Department of General Practice, Sir Run Run Shaw hospital, Zhejiang University School of Medicine"
       },
       {
-        "author_name": "Benjamin M. Althouse",
-        "author_inst": "Institute for Disease Modeling"
+        "author_name": "Yi Qian",
+        "author_inst": "Department of General Practice, Sir Run Run Shaw hospital, Zhejiang University School of Medicine"
       },
       {
-        "author_name": "Samuel V. Scarpino",
-        "author_inst": "Northeastern University"
+        "author_name": "Lizheng Fang",
+        "author_inst": "Department of General Practice, Sir Run Run Shaw hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province"
       },
       {
-        "author_name": "Antoine Allard",
-        "author_inst": "Universit\u00e9 Laval"
+        "author_name": "Mi Yao",
+        "author_inst": "Institute of Applied Health Research, University of Birmingham"
       }
     ],
     "version": "1",
-    "license": "cc_by",
+    "license": "cc_no",
     "type": "PUBLISHAHEADOFPRINT",
-    "category": "epidemiology"
+    "category": "primary care research"
   },
   {
     "rel_doi": "10.1101/2020.02.11.20021956",
@@ -1580388,53 +1584089,29 @@
     "category": "biochemistry"
   },
   {
-    "rel_doi": "10.1101/2020.02.07.20021071",
-    "rel_title": "Incorporating Human Movement Data to Improve Epidemiological Estimates for 2019-nCoV",
+    "rel_doi": "10.1101/2020.02.06.20020941",
+    "rel_title": "Analysis of the epidemic growth of the early 2019-nCoV outbreak using internationally confirmed cases",
     "rel_date": "2020-02-09",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.07.20021071",
-    "rel_abs": "Estimating the key epidemiological features of the novel coronavirus (2019-nCoV) epidemic proves to be challenging, given incompleteness and delays in early data reporting, in particular, the severe under-reporting bias in the epicenter, Wuhan, Hubei Province, China. As a result, the current literature reports widely varying estimates. We developed an alternative geo-stratified debiasing estimation framework by incorporating human mobility with case reporting data in three stratified zones, i.e., Wuhan, Hubei Province excluding Wuhan, and mainland China excluding Hubei. We estimated the latent infection ratio to be around 0.12% (18,556 people) and the basic reproduction number to be 3.24 in Wuhan before the citys lockdown on January 23, 2020. The findings based on this debiasing framework have important implications to prioritization of control and prevention efforts.\n\nOne Sentence SummaryA geo-stratified debiasing approach incorporating human movement data was developed to improve modeling of the 2019-nCoV epidemic.",
-    "rel_num_authors": 9,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.06.20020941",
+    "rel_abs": "BackgroundOn January 23, 2020, a quarantine was imposed on travel in and out of Wuhan, where the 2019 novel coronavirus (2019-nCoV) outbreak originated from. Previous analyses estimated the basic epidemiological parameters using symptom onset dates of the confirmed cases in Wuhan and outside China.\n\nMethodsWe obtained information on the 46 coronavirus cases who traveled from Wuhan before January 23 and have been subsequently confirmed in Hong Kong, Japan, Korea, Macau, Singapore, and Taiwan as of February 5, 2020. Most cases have detailed travel history and disease progress. Compared to previous analyses, an important distinction is that we used this data to informatively simulate the infection time of each case using the symptom onset time, previously reported incubation interval, and travel history. We then fitted a simple exponential growth model with adjustment for the January 23 travel ban to the distribution of the simulated infection time. We used a Bayesian analysis with diffuse priors to quantify the uncertainty of the estimated epidemiological parameters. We performed sensitivity analysis to different choices of incubation interval and the hyperparameters in the prior specification.\n\nResultsWe found that our model provides good fit to the distribution of the infection time. Assuming the travel rate to the selected countries and regions is constant over the study period, we found that the epidemic was doubling in size every 2.9 days (95% credible interval [CrI], 2 days--4.1 days). Using previously reported serial interval for 2019-nCoV, the estimated basic reproduction number is 5.7 (95% CrI, 3.4--9.2). The estimates did not change substantially if we assumed the travel rate doubled in the last 3 days before January 23, when we used previously reported incubation interval for severe acute respiratory syndrome (SARS), or when we changed the hyperparameters in our prior specification.\n\nConclusionsOur estimated epidemiological parameters are higher than an earlier report using confirmed cases in Wuhan. This indicates the 2019-nCoV could have been spreading faster than previous estimates.",
+    "rel_num_authors": 3,
     "rel_authors": [
       {
-        "author_name": "Zhidong Cao",
-        "author_inst": "Institute of Automation, Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Qingpeng Zhang",
-        "author_inst": "City University of Hong Kong"
-      },
-      {
-        "author_name": "Xin Lu",
-        "author_inst": "National University of Defense Technology"
-      },
-      {
-        "author_name": "Dirk Pfeiffer",
-        "author_inst": "City University of Hong Kong"
-      },
-      {
-        "author_name": "Lei Wang",
-        "author_inst": "Chinese Academy of Sciences"
-      },
-      {
-        "author_name": "Hongbing Song",
-        "author_inst": "Chinese PLA Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Tao Pei",
-        "author_inst": "Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences"
+        "author_name": "Qingyuan Zhao",
+        "author_inst": "University of Cambridge"
       },
       {
-        "author_name": "Zhongwei Jia",
-        "author_inst": "Peking University"
+        "author_name": "Yang Chen",
+        "author_inst": "University of Michigan"
       },
       {
-        "author_name": "Daniel Dajun Zeng",
-        "author_inst": "Institute of Automation, Chinese Academy of Sciences"
+        "author_name": "Dylan S Small",
+        "author_inst": "University of Pennsylvania"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by",
     "type": "PUBLISHAHEADOFPRINT",
     "category": "epidemiology"
   },
@@ -1581834,45 +1585511,97 @@
     "category": "epidemiology"
   },
   {
-    "rel_doi": "10.1101/2020.01.31.20019901",
-    "rel_title": "Early dynamics of transmission and control of 2019-nCoV: a mathematical modelling study",
+    "rel_doi": "10.1101/2020.01.30.20019844",
+    "rel_title": "Early evaluation of the Wuhan City travel restrictions in response to the 2019 novel coronavirus outbreak",
     "rel_date": "2020-02-02",
     "rel_site": "medRxiv",
-    "rel_link": "https://medrxiv.org/cgi/content/short/2020.01.31.20019901",
-    "rel_abs": "BackgroundAn outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.\n\nMethodsWe combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas.\n\nFindingsWe estimated that the median daily reproduction number, Rt, declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.\n\nInterpretationOur results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually.\n\nFundingWellcome Trust (206250/Z/17/Z, 210758/Z/18/Z), HDR UK (MR/S003975/1), Gates Foundation (INV-003174), NIHR (16/137/109)",
-    "rel_num_authors": 8,
+    "rel_link": "https://medrxiv.org/cgi/content/short/2020.01.30.20019844",
+    "rel_abs": "Respiratory illness caused by a novel coronavirus (COVID-19) appeared in China during December 2019. Attempting to contain infection, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. Here we evaluate the spread and control of the epidemic based on a unique synthesis of data including case reports, human movement and public health interventions. The Wuhan shutdown slowed the dispersal of infection to other cities by an estimated 2.91 days (95%CI: 2.54-3.29), delaying epidemic growth elsewhere in China. Other cities that implemented control measures pre-emptively reported 33.3% (11.1-44.4%) fewer cases in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Among interventions investigated here, the most effective were suspending intra-city public transport, closing entertainment venues and banning public gatherings. The national emergency response delayed the growth and limited the size of the COVID-19 epidemic and, by 19 February (day 50), had averted hundreds of thousands of cases across China.\n\nOne sentence summaryTravel restrictions and the national emergency response delayed the growth and limited the size of the COVID-19 epidemic in China.",
+    "rel_num_authors": 21,
     "rel_authors": [
       {
-        "author_name": "Adam J Kucharski",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Huaiyu Tian",
+        "author_inst": "Beijing Normal University"
       },
       {
-        "author_name": "Timothy W Russell",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Yonghong Liu",
+        "author_inst": "Beijing Normal University"
       },
       {
-        "author_name": "Charlie Diamond",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Yidan Li",
+        "author_inst": "Beijing Normal University"
       },
       {
-        "author_name": "Yang Liu",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Chieh-Hsi Wu",
+        "author_inst": "University of Southampton"
       },
       {
-        "author_name": "CMMID nCoV working group",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Bin Chen",
+        "author_inst": "University of California Davis"
       },
       {
-        "author_name": "John Edmunds",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Moritz U. G. Kraemer",
+        "author_inst": "University of Oxford"
       },
       {
-        "author_name": "Sebastian Funk",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Bingying Li",
+        "author_inst": "Beijing Normal University"
       },
       {
-        "author_name": "Rosalind M Eggo",
-        "author_inst": "London School of Hygiene & Tropical Medicine"
+        "author_name": "Jun Cai",
+        "author_inst": "Tsinghua University"
+      },
+      {
+        "author_name": "Bo Xu",
+        "author_inst": "Tsinghua University"
+      },
+      {
+        "author_name": "Qiqi Yang",
+        "author_inst": "Beijing Normal University"
+      },
+      {
+        "author_name": "Ben Wang",
+        "author_inst": "Beijing Normal University"
+      },
+      {
+        "author_name": "Peng Yang",
+        "author_inst": "Beijing Center for Disease Prevention and Control"
+      },
+      {
+        "author_name": "Yujun Cui",
+        "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"
+      },
+      {
+        "author_name": "Yimeng Song",
+        "author_inst": "The University of Hong Kong"
+      },
+      {
+        "author_name": "Pai Zheng",
+        "author_inst": "Peking University"
+      },
+      {
+        "author_name": "Quanyi Wang",
+        "author_inst": "Beijing Center for Disease Prevention and Control"
+      },
+      {
+        "author_name": "Ottar N Bjornstad",
+        "author_inst": "Penn State University"
+      },
+      {
+        "author_name": "Ruifu Yang",
+        "author_inst": "Beijing Institute of Microbiology and Epidemiology"
+      },
+      {
+        "author_name": "Bryan Grenfell",
+        "author_inst": "Princeton University"
+      },
+      {
+        "author_name": "Oliver Pybus",
+        "author_inst": "University of Oxford"
+      },
+      {
+        "author_name": "Christopher Dye",
+        "author_inst": "University of Oxford"
       }
     ],
     "version": "1",
@@ -1582995,119 +1586724,27 @@
     "category": "bioinformatics"
   },
   {
-    "rel_doi": "10.1101/2020.01.25.919787",
-    "rel_title": "Transmission dynamics of 2019 novel coronavirus (2019-nCoV)",
+    "rel_doi": "10.1101/2020.01.25.919688",
+    "rel_title": "Origin time and epidemic dynamics of the 2019 novel coronavirus",
     "rel_date": "2020-01-26",
     "rel_site": "bioRxiv",
-    "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.25.919787",
-    "rel_abs": "RationaleSeveral studies have estimated basic production number of novel coronavirus pneumonia (NCP). However, the time-varying transmission dynamics of NCP during the outbreak remain unclear.\n\nObjectivesWe aimed to estimate the basic and time-varying transmission dynamics of NCP across China, and compared them with SARS.\n\nMethodsData on NCP cases by February 7, 2020 were collected from epidemiological investigations or official websites. Data on severe acute respiratory syndrome (SARS) cases in Guangdong Province, Beijing and Hong Kong during 2002-2003 were also obtained. We estimated the doubling time, basic reproduction number (R0) and time-varying reproduction number (Rt) of NCP and SARS.\n\nMeasurements and main resultsAs of February 7, 2020, 34,598 NCP cases were identified in China, and daily confirmed cases decreased after February 4. The doubling time of NCP nationwide was 2.4 days which was shorter than that of SARS in Guangdong (14.3 days), Hong Kong (5.7 days) and Beijing (12.4 days). The R0 of NCP cases nationwide and in Wuhan were 4.5 and 4.4 respectively, which were higher than R0 of SARS in Guangdong (R0=2.3), Hongkong (R0=2.3), and Beijing (R0=2.6). The Rt for NCP continuously decreased especially after January 16 nationwide and in Wuhan. The R0 for secondary NCP cases in Guangdong was 0.6, and the Rt values were less than 1 during the epidemic.\n\nConclusionsNCP may have a higher transmissibility than SARS, and the efforts of containing the outbreak are effective. However, the efforts are needed to persist in for reducing time-varying reproduction number below one.\n\nAt a Glance CommentaryO_ST_ABSScientific Knowledge on the SubjectC_ST_ABSSince December 29, 2019, pneumonia infection with 2019-nCoV, now named as Novel Coronavirus Pneumonia (NCP), occurred in Wuhan, Hubei Province, China. The disease has rapidly spread from Wuhan to other areas. As a novel virus, the time-varying transmission dynamics of NCP remain unclear, and it is also important to compare it with SARS.\n\nWhat This Study Adds to the FieldWe compared the transmission dynamics of NCP with SARS, and found that NCP has a higher transmissibility than SARS. Time-varying production number indicates that rigorous control measures taken by governments are effective across China, and persistent efforts are needed to be taken for reducing instantaneous reproduction number below one.",
-    "rel_num_authors": 25,
+    "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.25.919688",
+    "rel_abs": "The 2019 novel coronavirus (2019-nCoV) have emerged from Wuhan, China. Studying the epidemic dynamics is crucial for further surveillance and control of the outbreak. We employed a Bayesian framework to infer the time-calibrated phylogeny and the epidemic dynamics represented by the effective reproductive number (Re) changing over time from 33 genomic sequences available from GISAID. The time of the most recent common ancestor (MRCA) was December 17, 2019 (95% HPD: December 7, 2019 - December 23, 2019). The median estimate of Re shifted from 1.6 to 1.1 on around January 1, 2020. This study provides an early insight of the 2019-nCoV epidemic. However, due to limited amount of data, one should be cautious when interpreting the results at this stage.",
+    "rel_num_authors": 2,
     "rel_authors": [
       {
-        "author_name": "Tao Liu",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Jianxiong Hu",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Jianpeng Xiao",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Guanhao He",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Min Kang",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Zuhua Rong",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Lifeng Lin",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Haojie Zhong",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Qiong Huang",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Aiping Deng",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Weilin Zeng",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Xiaohua Tan",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Siqing Zeng",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Zhihua Zhu",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Jiansen Li",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Dexin Gong",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Donghua Wan",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Shaowei Chen",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Lingchuan Guo",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Yan Li",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Limei Sun",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Wenjia Liang",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Tie Song",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
-      },
-      {
-        "author_name": "Jianfeng He",
-        "author_inst": "Guangdong Provincial Center for Disease Control and Prevention"
+        "author_name": "Chi Zhang",
+        "author_inst": "IVPP, CAS"
       },
       {
-        "author_name": "Wenjun Ma",
-        "author_inst": "Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention"
+        "author_name": "Mei Wang",
+        "author_inst": "PKU"
       }
     ],
     "version": "1",
-    "license": "cc_no",
+    "license": "cc_by_nc_nd",
     "type": "new results",
-    "category": "systems biology"
+    "category": "microbiology"
   },
   {
     "rel_doi": "10.1101/2020.01.24.919159",